APPLICABILITY OF MITOCHONDRIAL GENOME DATA TO ANNELID 
PHYLOGENY AND THE EVOLUTION OF GROUP II INTRONS  
 
 
 
Except where reference is made to the work of others, the work described in this 
dissertation is my own or was done in collaboration with my advisory committee.  
This dissertation does not include proprietary or classified information. 
 
 
 
 
_______________________________ 
Min Zhong 
 
 
Certificate of Approval: 
 
 
 
_______________________________ 
Zhanjiang Liu 
Alumni Professor 
Fisheries and Allied Aquacultures 
 
 
 
_______________________________ 
Scott R. Santos 
Assistant Professor 
Biological Sciences 
 
 
_______________________________ 
Kenneth M. Halanych, Chair 
Alumni Professor 
Biological Sciences 
 
 
 
_______________________________ 
Leslie R. Goertzen 
Assistant Professor 
Biological Sciences 
 
 
 
_______________________________ 
George T. Flowers 
Dean 
Graduate School 
APPLICABILITY OF MITOCHONDRIAL GENOME DATA TO ANNELID 
PHYLOGENY AND THE EVOLUTION OF GROUP II INTRONS 
Min Zhong 
 
A Dissertation 
Submitted to 
the Graduate Faculty of 
Auburn University 
in Partial Fulfillment of the 
Requirements for the 
Degree of 
Doctor of Philosophy 
 
 
Auburn, Alabama 
August 10, 2009 
 
 
iii
APPLICABILITY OF MITOCHONDRIAL GENOME DATA TO ANNELID 
PHYLOGENY AND THE EVOLUTION OF GROUP II INTRONS  
 
Min Zhong 
 
 
 
Permission is granted to Auburn University to make copies of this dissertation at its 
discretion, upon request of individuals or institutions and at their expense. The author 
reserves all publication rights. 
 
 
 
 
 
 
______________________________ 
Signature of Author 
 
 
 
______________________________ 
Date of Graduation 
 
iv
DISSERTATION ABSTRACT 
APPLICABILITY OF MITOCHONDRIAL GENOME DATA TO ANNELID 
PHYLOGENY AND THE EVOLUTION OF GROUP II INTRONS 
Min Zhong 
Doctor of Philosophy, August 10, 2009 
(M.S., China Agricultural University, 2004) 
 (B.S., Qufu Normal University, 2001) 
150 Typed Pages 
Directed by Kenneth M. Halanych 
Annelida is a very diverse group of segmented worms with over 16,500 described 
species. They play an important role in both terrestrial and aquatic environments. Despite 
this, their phylogenetic and evolutionary relationships of many groups within annelids are 
still poorly understood. This study focused on Terebelliformia annelids, a group of tube-
dwelling worms used for investigation, comprises five recognized families with 
ambiguous phylogeny and a myzostomid worm, whose annelid affinity has been debated 
in recent years. In view of the conserved composition across bilaterians and the 
hypothesis of conserved gene order pattern across annelids, the mitochondrial genomic 
data have been becoming increasingly useful for applications to resolve this issue. 
 
v
The main aim of this research is to characterize the mtDNA genomes in above annelids 
and resolve certain relationships within annelids with mitochondrial genome to evaluate 
their applicability to annelid phylogeny.  Additionally, two group II introns that 
unexpectedly discovered in the myzostomid mtDNA drew our attentions to explore the 
evolution of such introns as they are rarely found in bilaterian genomes.  
This study showed that the mitochondrial gene arrangement pattern is 
evolutionarily conserved as previously hypothesized, especially for protein-coding genes. 
Phylogenetic analyses based on the mitochondrial genome data indicated a well-resolved 
phylogeny within Terebelliformia group: Pectinariidae was placed as a basal clade to all 
other Terebelliformia families; Ampharetidae and Alvinellidae were sister to each other; 
Trichobranchidae and Terebellidae were sister clade with strong support. This suggests 
the great potential applicability of mitochondrial genomes which could likely be applied 
to the phylogenetic reconstruction of other annelid clades. 
Two group II introns (divergent Mintron1 and degenerated Mintron2) which are 
characterized here in a partial mitochondrial genome of Endomyzostoma sp. 
(Myzostomida), is the first report of multiple introns in bilaterian genomes. The study 
implicated that both introns belong to the mitochondrial class and they could have 
independent origins given the dissimilarity between their RNA structures. It offers an 
important basis for the future studies in regard to the evolution and function of bilaterian 
group II introns.  
Overall, the study implies an increasingly potential applicability to explore the 
mitochondrial genomes of annelids in terms of the phylogenetic and evolutionary 
examinations.  
 
vi
ACKNOWLEDGEMENTS 
I wish to express my deepest appreciation to Dr. Ken Halanych for his great 
support, assistance and encouragement throughout my PhD training and the dissertation 
process. Thank you for the understanding especially in the last year of my study. I am 
also grateful to you for contributing a lot of time, effort and patience to my writings in 
English as a second language. Your guidance, comprehensive knowledge and precise 
attitude for the science are highly invaluable for my life. I would also like to express my 
heartfelt gratitude to the committee memebers, Dr. Zhanjiang Liu for his special support 
for my future career, Dr. Leslie Goertzen for his valuable comments in my written and 
oral exams and Dr. Scott Santos for his constructive feedback and suggestions for the 
manuscripts, as well as Dr Fenny Dane as my outside reader. Thanks for the financial 
support provided by the NSF-EPSCOR and CMB program. Many thanks go to all 
members in KMH lab: Torsten Struck, Nerida Wilson, Heather Eccleston, Dan Thornhill, 
Andy Mahon, Liz Borda, Rebecca Hunter, Alexis Janosik, Joie Cannon, Kevin Kocot for 
their helps during the research and lab work. Special thanks are extended to Rebecca and 
Alexis for their kind assistances to me the many ways in the aspect of personal and life. 
Finally, I would like to thank my husband, Yu Xiang, for his endurance and love. It 
would not be easy for me to study and live in a strange country without your support. 
Thanks for your constant encouragement for me to achieve the goal in my life. Special 
thanks to my sweet little daughter, Grace Xiang. Her birth brings the family great joy! 
 
vii
Style manual of journal used: 
Chapter 1: Gene
Chapter 2: Gene
Chapter 3: Systematic Biology
Chapter 4: Molecular Biology and Evolution
Chapter 5: Gene
Computer software used: Adobe Illustrator, Microsoft Excel, Microsoft Word,  
MacClade, DNASTAR? Lasergene (MegAlign, GeneQuest, SeqMan) ModelTest, 
MrBayes, MrModelTest, PAUP, RAxML, ProtTest, mfold, Clustal X. TreeView, Se-Al, 
Gblocks, tRNAscan, Artemis.  
TABLE OF CONTENTS 
LIST OF TABLES..............................................................................................................xi 
LIST OF FIGURES..........................................................................................................xiii 
CHAPTER 1: INTRODUCTION AND BACKGROUND.................................................1 
1. OVERVIEW???????????............................................................2 
2. ANNELID MITOCHONDRIAL GENOMES..................................................3 
3. TEREBELLIDORMIA ANNELIDS??...........................................................4 
4. MYZOSTOMIDA?????????............................................................5 
5. GROUP II INTRONS????..........................................................................6 
APPENDIX: PHYLOGENETIC METHODS.........................................................8 
REFERENCES......................................................................................................16 
CHAPTER 2: PHYLOGENETIC INFORMATION FROM THE THREE 
MITOCHONDRIAL GENOMES OF TEREBELLIFORMIA (ANNELIDA) WORMS 
AND DUPLICATION OF THE METHIONINE tRNA...................................................29 
ABBREVIATIONS...............................................................................................30 
ABSTRACT???...............................................................................................31 
1. INTRODUCTION.............................................................................................32 
2. MATERIALS AND METHODS.......................................................................33 
2.1 SAMPLE COLLECTION AND DNA EXTRACTION??..............33 
2.2 MTDNA DATA COLLECTION.......................................?..............34 
2.3 GENOMIC ASSEMBLY......................?..........................................36 
2.4 PHYLOGENETIC ANALYSIS........................................?..............37 
3. RESULTS AND DISCUSSION........................................................................39 
3.1 GENOME COMPOSITION..................?..........................................39 
3.2 PROTEIN-CODING GENES?????..........................................40 
3.3 tRNAS....................................................?..........................................42 
3.4 UNK REGION?.................................................................................43 
3.5 STRUCTURE AND GENE CODE...................................?..............43 
3.6 PHYLOGENETIC ANALYSIS?????......................................44 
ACKNOWLEDGEMENTS...................................................................................46 
REFERENCES......................................................................................................46 
CHAPTER 3: PHYLOGENETIC INFERENCE OF TEREBELLIFORMIA WORMS  
BASED ON MITOCHONDRIAL GENOMIC DATA.....................................................66 
 
viii
 
ix
ABSTRACT???...............................................................................................67 
1. INTRODUCTION.............................................................................................68 
2. MATERIALS AND METHODS.......................................................................71 
2.1 SAMPLE COLLECTION AND DNA EXTRACTION??..............71 
2.2 MTDNA DATA COLLECTION.......................................?..............72 
2.3 GENOMIC ASSEMBLY......................?..........................................73 
2.4 PHYLOGENETIC ANALYSES.......................................?..............74 
3. RESULTS????????........................................................................76 
3.1 MITOCHONDRIAL GENOMES AND GENE ORDER....................76 
3.2 PHYLOGENETIC ANALYSES???..........................................77 
4. DISCUSSION???????........................................................................78 
4.1 PHYLOGENETIC RELATIONSHIP WITH  
TEREBELLIFORMIA...?????????????????78 
4.2 TRNM DUPLICATION EVENT AND GENE ORDER??............79 
CONCLUSIONS....................................................................................................80 
ACKNOWLEDGEMENTS...................................................................................81 
REFERENCES......................................................................................................81 
CHAPTER 4: TWO GROUP II INTRONS AND THEIR EVOLUTIONARY ORIGINS 
IN ENDOMYZOSTOMA (MYZOSTOMIDA) MITOCHONDRIAL GENOME??....95 
ABSTRACT???...............................................................................................96 
1. INTRODUCTION.............................................................................................97 
2. MATERIALS AND METHODS....................................................................100 
2.1 SAMPLE COLLECTION AND DNA EXTRACTION??............100 
2.2 MTDNA DATA COLLECTION.......................................?............100 
2.3 GENOMIC ASSEMBLY......................?........................................101 
2.4 INTRON IDENTIFICATION........................................?.............102 
2.5 PHYLOGENETIC ANALYSIS AND SEQUENCES  
ALIGNMENTS??????...?????????????...102 
3. RESULTS????????........................................................................103 
3.1 GENOME COMPOSITION AND EVOLUTION?........................103 
3.2 INTRON STRUCTURES???......................................................104 
3.3 ORF ALIGNMENT AND PHYLOGENETIC ANALYSIS.............104 
4. DISCUSSION???????......................................................................105 
4.1 MINTRON1: A DIVERGENT MITOCHONDRIAL GROUP II  
INTRON?????????..?????..????????106 
4.2 MINTRON2: UNDERGOING EVOLUTIONARY 
DEGENERATION??????????????????.107 
4.3 INTRON EVOLUTIONARY ORIGINS...........................................108 
ACKNOWLEDGEMENTS.................................................................................109 
LITERATURE CITED........................................................................................109 
CHAPTER 5: CONCLUSIONS......................................................................................130 
1. MITOCHONDRIAL GENOMES AND PHYLOGENETIC  
 
x
RELATIONSHIPS WITHIN TEREBELLIFORMIA GROUP.......................131 
2. THE MITOCHONDRIAL GENOME OF A MYZOSTOMIDA WORM  
AND GROUP II INTRONS............................................................................132 
REFERENCES???........................................................................................134 
 
 
xi
LIST OF TABLES 
CHAPTER 1 
Table 1: Parameters in evolutionary models (Model abnreviations: JC, Jukes and Cantor 
(1969) model; K2P, Kimura (1980) two-parameter model; TrN, TrN model with 
equal base frequencies, Tamura and Nei 1993; SYM, Zharkikh 1994; F81, model 
of Felsenstein, Felsenstein 1981); HKY85, Hasegawa-Kishino-Yano model, 
Hasegawa et al., 1985; K3ST, Kimura 3 substitution type model, Kimura, 1981), 
GTR, General time-reversible model, Lanave et al., 1984; Rodrigues et al.,  
1990).....................................................................................................................25 
CHAPTER 2 
Table 1: Taxonomically-inclusive PCR primers to amplify small conserved 
regions..................................................................................................................52 
Table 2: Primers for long PCR with annealing temperatures............................................53 
Table 3: Sequencing Primers for sequencing the mitochondrial genomes of Terebellides 
stroemi, Pista cristata and Eclysippe vanelli......................................................54 
Table 4: Taxa used in phylogenetic analysis???????????.........................57 
Table 5: Base composition and skewness measures..........................................................58 
Table 6: Relative synonymous codon usages (RSCU) in the 13 protein-coding genes in T. 
stroemi, P. cristata and E. vanelli.......................................................................59 
CHAPTER 3 
Table 1: Primers used in long-run PCR amplifications.....................................................87 
Table 2: Primers used for sequencing the mitochondrial genomes of Auchenoplax crinita, 
Paravinella  sulfincola and Pectinaria gouldii...................................................88 
Table 3: Taxa used in the phylogenetic analysis????...............................................91 
 
xii
CHAPTER 4 
Table 1: Long PCR primers used in amplifications.........................................................116 
Table 2: Sequencing primers used for sequencing mitochondrial genomes....................117 
Table 3: Intron identification primers..............................................................................119 
Table 4: Group II ORFs used in the phylogenetic analysis.............................................120 
 
LIST OF FIGURES 
CHAPTER 1 
Figure 1: Five families of Terebelliformia worms. A.Terebellidea; B. Avinellidae 
(http://www.mbari.org/expeditions/ridges2005/august_11.htm); C. Pectinariidae; 
D. Trichobranchidae; E. Ampharetidae (Both D and E are from Rouse and 
Pleijel, 2001).......................................................................................................26 
Figure 2: Microscopic views of Endomyzostoma sp. (Figures are from Lanterbecq et al., 
2006) B: Endomyzostoma deformator; D: Endomyzostoma sp..........................27 
Figure 3: Substitution rates between all bases in evolutionary models.............................28 
CHAPTER 2 
Figure 1: Gene orders of mitochondrial genomes in Annelida. Different colors shows 
conserved gene clusters. Dots indicate missing regions.....................................60 
Figure 2: Putative secondary structures of tRNA genes in 3 Terebelliformia worms. (A) 
23 tRNA genes in T. stroemi. (B) 23 tRNA genes in P. cristata. (C) 20  
recovered tRNA genes in E. vanelli...................................................................63 
Figure 3: Phylogenetic reconstructions. (A) The single combined tree represents the 
identical topology from both ML and Bayesian inference methods (non-
partitioned and partitioned) with GTR+?+I model. Nodal support values are 
given at branches with ML bootstrap values first and posterior probabilities of 
the partitioned Bayesian analysis second (non-partition values not shown). A 
dash indicates < 50% on trees. (B) Non-partitioned Bayesian analyses of amino 
acid dataset with the mixed amino acid substitution model. Posterior 
probabilities are shown at the nodes. (C) ML analyses of amino acid dataset 
using RAxML by 200 bootstrap replicates. Bootstrap values are shown at the 
nodes. Black bars indicate trnM gene duplication event. Terebratalia transversa 
(brachiopod) and Katharina tunicata (mollusk) were used as outgroups. Details 
of analyses are given in the text..........................................................................64 
Figure 4: Partitioned Bayesian analyses of amino acid dataset with the mixed amino acid 
substitution model with partitions unlinked during the run. Posterior 
probabilities are shown at the nodes...................................................................65 
 
 
xiii
CHAPTER 3 
Figure 1: Mitochondrial gene order of six Terebelliformia worms. Different colors shows  
conserved gene clusters. Dots indicate missing regions.....................................92 
Figure 2: Phylogenetic reconstructions for 17-taxon mitochondrial datasets. (A) The 
mitochondrial nucleotide tree represents the identical topology from both ML 
and partitioned Bayesian inference methods. (B) The mitochondrial amino acid 
tree with the identical topology from both ML and partitioned Bayesian 
inference methods. Nodal support values are given at branches with posterior 
probabilities of the partitioned Bayesian analysis first and ML bootstrap values 
second. A dash indicates < 50% on trees. The representative branch lengths are  
from the Bayesian trees.......................................................................................93 
Figure 3: Character mapping on Terebelliformia ingroup trees based on mitochondrial 
datasets. The bar represents trnM duplication event. The circle represents the 
specific gene order of nad5-nad4L-nad4 cluster in mitochondrial genomes. 
Open bar: duplication absent; Black bar: duplication present; open ellipses: 
nad5- trnF-trnE-trnP-trnT-nad4L-nad4; black ellipses: trnE-trnT-trnP-trnY--
nad4L-nad4-trnC-trnM-trnH-nad5; shaded ellipse: nad5- trnF-trnE-trnP-trnT- 
trnR-nad4L-nad4.................................................................................................94 
CHAPTER 4 
Figure 1: The secondary structures of 14 discovered tRNA in the mitochondrial genome 
of Endomyzostoma sp.......................................................................................125 
Figure 2: (A) Insertion locations of both Mintron1 and Mintron2 in the cox1 gene. The 
dot line on the left end of cox1 gene means this region was not recovered. (B) 
Secondary structure of Mintron1. Domain 4 contains the ORF. (C) Secondary 
structure of Mintron2. The stars label the conserved nucleotides in the central 
core as the major features of group IIA1 subclass which is the mitochondrial 
class. ORF, open reading frame; EBS, exon binding sequences; IBS, intron  
binding sequences.............................................................................................127 
Figure 3: (A) Intron-encoded ORF domain structure. (modified from Zimmerly et al., 
2001; Fig1A). (B) Alignment of subdomain 4 region of RT domain and one 
conserved region in X domain. The most conserved amino acids were identified 
by Gblocks showing as the black bars. The representative ORFs from each 
major category (three mitochondrial, two chloroplast and four bacteria) were 
selected to align with the ORFs from both Mintron1 and Nephtys group II intron. 
The purple bars are showing the most conserved regions across all ORFs. 
Species abbreviations are as follows: M.m.I1, Methanosarcina mazei; A.v.I1, 
Azotobacter vinelandii; W.e.I2, Wolbachia endosymbiont of Drosophila 
melanogaster; Kl.pn.I1, Klebsiella pneumoniae isolate YMC. The intron 
category labels: Bac, Bacteria; Chl, Chloroplast; Mt, Mitochondrion.  Other  
 
xiv
information about the taxa see table 4..............................................................128 
Figure 4: Phylogenetic analyses of 105 group II intron ORFs by the MrBayes program. 
Taxa sampling included all mitochondrial and chloroplast group II ORFs and 
some representatives of bacterial classes (table 4). Dark shades are the 
mitochondrial group II introns including the Mintron1 and Nephtys ORFs 
(showing as bold font). Light shade is the chloroplast group II intron lineage. 
All other unshaded are the group II intron ORFs found in bacteria.  
Archaebacterial taxa were used as outgroups...................................................129 
 
xv
 
1
CHAPTER 1 
INTRODUCTION AND BACKGROUND 
 
2
1. Overview 
 Annelida is a very diverse group of animals living in marine, freshwater and 
terrestrial environments. It comprises around 16,500 described species and this number is 
likely underestimated as annelids are the most abundant macrofauna in the unexplored 
deep-sea area (Grassle and Maciolek, 1992). Traditionally, Annelida was divided into 
Polychaeta and Clitellata, the latter including Oligochaeta and Hirudinida. However, 
recent phylogenetic studies have indicated a paraphyletic Polychaeta that includes several 
previously recognized ?phyla? (echiurids, sipunculids, and siboglinids ? a.k.a. 
pogonophorans; McHugh, 1997; Boore and Staton, 2002; Bleidorn et al., 2006a; Struck et 
al., 2007) and the Clitellata. Annelids are typically an important food source for many 
economically important species and play a key role in nutrient cycling and energy flow in 
terrestrial and aquatic environments (Losteste and Marchese 1994; Aston, 1984). 
Annelids often have abundant populations with diverse life histories. Because they are 
environmentally important and easy-to-handle in the lab, they are a good candidate for 
the model of lophotrochozoan animals.  
Despite their importance, we still have a poor understanding of annelid 
evolutionary relationships, and they continue to be debated. The overall goal of this 
project is to resolve certain relationships within annelids and to characterize 
mitochondrial genomes including their applicability to annelid phylogeny.  
 
 
3
To this end, I focus on a well-described group, Terebelliformia annelids, 
comprised of five recognized families, and aim to determine their evolutionary history 
using mitochondrial DNA (mtDNA) data. Furthermore, I examine myzostomids, a group 
of worms whose annelid affiliation has been debated. Molecular evolution of myzostomid 
mtDNA is interesting because of the unexpected presence of two group II introns.  
2. Annelid mitochondrial genomes 
 Gene content of the mtDNA genome is conserved across Bilateria. The 
mitochondrial genome contains 13 protein-coding genes, two ribosomal genes, 22 tRNA 
genes and one non-coding unknown region (UNK - the presumed origin of replication). 
Generally, the size of mitochondrial genomes is about 15-17 kB (Boore, 1999; Vall?s and 
Boore, 2006). Whereas some taxa have highly rearranged mitochondrial genomes, gene 
order within annelids is hypothesized to be relatively conserved (Jennings and Halanych, 
2005; Vall?s and Boore, 2006; Zhong et al., 2008). Despite the utility of mitochondrial 
genomes for phylogenetic reconstructions of major animal taxa, only seven complete and 
five partial annelid mitochondrial genomes are available in GenBank (September 2008). 
One reason for the paucity of mtDNA genome data is that in some taxa, including 
annelids, the UNK region (also called the D-loop or control region) has been difficult to 
amplify and sequence presumably because of secondary structure and/or the present of 
microsatellite regions (Boore and Brown, 2000; Boore, 2001; Jennings and Halanych, 
2005; Bleidorn et al., 2006a, b; Zhong et al., 2008). 
 
 
 
4
3. Terebelliformia annelids 
In order to accurately interpret annelid genomic evolution and molecular 
phylogeny, I used Terebelliformia annelids as a test group.  
Terebelliformia annelids, also known as Terebellomorpha, are mainly tube-
dwelling worms, found in diverse marine habitats, including the intertidal, coral reefs, the 
deep-sea and hydrothermal vents, and can be found in both soft and hard substrates (Fig. 
1).  They are sedentary in nature and have a well-developed anterior end with modified 
appendages for feeding and respiration. Terebelliformia worms are comprised of five 
?families?, Alvinellidae, Ampharetidae, Terebellidae, Trichobranchidae and Pectinariidae 
(Hessle, 1917; Holthe, 1986; Rouse and Pleijel, 2001). Even though Terebelliformia is 
one of the few clades in Annelida argued to be well defined by morphology, phylogenetic 
relationships among these five families are ambiguous and consistently debated (Rouse 
and Fauchald, 1997; Colgan et al., 2001; Rousset et al., 2003; Glasby et al., 2004; 
Rousset et al., 2007; Struck et al., 2007).  
Based on morphological data, Trichobranchidae was originally treated as the 
subfamily Trichobranchinae within Terebellidae (Malmgren, 1866) and elevated to family 
rank in 1917 because two genera of Trichobranchidae (Trichobranchus and Terebellides) 
were suggested to be allied with Ampharetidae and Terebellidae, respectively, based on 
similar characteristics of their branchiae and digestive system, respectively (Hessle, 
1917). Rouse and Fauchald (1997) suggested a close affinity between Terebellidae and 
Trichobranchiae, which was sister to the Alvinellidae/Ampharetidae/Pectinariidae clade. 
However, Fauchald and Rouse (1997) treated Pectinariidae together with Terebellidae and 
Ampharetidae as Terebellida or Terebellimorpha. Recent morphological analyses 
 
5
indicated that Pectinariidae was either sister to the Ampharetidae/Alvinellidae clade 
(Rouse and Fauchald, 1997), or related to Terebellidae (Glasby, et al., 2004). 
Nevertheless, some molecular studies and combined data indicate contradicting views of 
relationships within Terebelliformia. Trichobranchus was suggested to be associated with 
one subfamily of Terebellidae making Trichobranchidae paraphyletic based on five 
mitochondrial and nuclear genes (Colgan et al., 2001), whereas a sister relationship 
between Trichobranchidae and Alvinellidae was suggested based on morphology 
combined with molecular data (Rousset et al., 2003). Additionally, the affinity of 
Pectinariidae has been questioned based on recent molecular and combined data. Its sister 
relationship to Trichobranchidae,/Alvinellidae clade (Rousset et al., 2003), within 
Ampharetidae (Colgan et al., 2001), or close to all other four terebelliform lineages 
(Struck et al., 2007) or even other annelids (which would break up the monophyly of 
Terebelliformia) (Rousset et al., 2007) indicates that Pectinariidae is a family of 
ambiguous phylogenetic position influencing phylogenetic relationships within 
terebelliforms. 
4. Myzostomida 
Myzostomida are small parasitic marine worms, living mostly on crinoid and 
ophiuroid echinoderms (Grygier, 2000; Zrzav? et al., 2001; Bleidorn et al., 2007). Their 
body is typically soft and flattened with many radiating cirri on the thin rounded body 
edge and five pairs of parapodia on the ventral side (Fig. 2). They have high host-
specificity as many myzstomid species are only associated with a single crinoid species 
(Eeckhaut et al., 1998), with a few exceptions (Lanterbecq et al., 2006). Fossils from the 
Ordovician suggest an ancient association between myzostomids and their crinoid hosts 
 
6
(Eeckhaut et al., 1998), which may explain the highly derived body plan of myzostomids 
and their disputable phylogenetic position within metazoans (Zrzav? et al., 2001; 
Bleidorn et al., 2007). Although some studies predicted that Myzostomida are not allied 
with annelids (Haszprunar, 1996; Eeckhaut et al., 2000; Littlewood et al., 2001; Zrzav? et 
al., 2001; Giribet et al. 2004), their polycheate origins are indicated by both 
morphological (Eackhaut et al., 1998; Haszprunar, 1996) and molecular studies (Bleidorn 
et al 2007) with robust support. The monophyletic Myzostomida group comprises two 
orders (Proboscidea and Pharyngidea), 12 genera and about 170 described species 
(Lanterbecq et al., 2006). Endomyzostoma sp. belongs to Endomyzostomatidae 
(Pharyngidea). 
Originally I began work on myzostomid mtDNA to determine their phylogenetic 
placement. However, I discovered interesting group II introns in their mitochondrial 
genome. Additionally, a colleague, Christoph Bleidorn (Free University of Berlin), was 
also working on myzostomid mtDNA. To avoid dupliation, I focused my efforts on the 
introns and have been working with Bleidorn on the phylogenetic issues. 
5. Group II introns 
Group II introns are self-splicing ribozymes that are commonly present in the 
genomes of bacteria, and organellar genomes of fungi, plants and animals (Lehmann and 
Schmidt, 2003; Rot et al., 2006; Beagley et al., 1998; Dellaporta et al., 2006; Vall?s et al., 
2008). The secondary structure of a typical group II intron contains 6 obvious stem-loop 
domains, D1 to D6. All domains radiate from a central core comprised of a few 
nucleotides to form the proximal helix that is required for self-splicing. There are several 
conserved primary sequences which are the key identifiers of group II introns including 
 
7
5? and 3? splicing sites (5??GUGYG and AY?3?), an unpaired adenosine in D6 and a 
number of conserved nucleotides in D5 (Knoop et al., 1994; Lambowitz and Zimmerly, 
2004). 
Group II introns are mobile and generally have two forms, OpenReadingFrame 
(ORF)-containing and ORF-less which only consists of the six domains. ORF-less introns 
primarily occur in organelles rather than bacteria. All ORFs in group II introns are found 
in D4 that involve four functional domains: reverse transcriptases (RTs) domain, X 
domain with maturase activities, non-conserved D domain (for DNA-binding) and En 
domain with endonuclease activity (Lambowitz et al., 1999; Zimmerly et al., 2001; San 
Filippo and Lambowitz, 2002; Dai and Zimmerly, 2002). RTs in bacterial group II introns 
were believed to mainly function as retroelements and play an essential role in intron 
homing events (Dai and Zimmerly, 2002). Intron homing is a common mobile 
phenomenon widely distributed in protists and other eukaryotes. Intron homing is enacted 
by both RNA-catalytic and RT activities. Target homing sites, both upstream and 
downstream of exons, are highly specific and provide an additional tool for intron 
classification. ORFs are also used for intron identification analyses because normally 
ORFs in one category are related to their specific structures of intron RNAs (Zimmerly et 
al., 2001; Toor et al., 2001; Dai and Zimmerly, 2002; Vall?s et al., 2008). Based on 
phylogenetic analyses of ORFs, group II introns were divided into three major categories, 
mitochondrial (including fungi), chloroplast and bacterial lineages. ORFs in bacterial 
introns are considered basal to mitochondrial and chloroplast ORFs (Toor et al., 2001). 
An evolutionary model of group II introns was predicted where all currently known 
group II introns, including ORF-containing and ORF-less, are derivatives of bacterial 
 
8
ORF-containing introns and most ORF-less introns derived from ORF-containing introns 
based on the relative high identity from sequence alignments among several liverwort mt-
introns and land plants (Toor et al., 2001). 
The first report of a group II intron in the mitochondrial genome of any bilaterian 
was from the annelid Nephtys sp. which was inferred to be derived from a recent 
horizontal gene transfer (Vall?s et al., 2008). 
Appendix: Phylogenetic Methods 
Phylogenetics is a subject of studying evolutionary relationships among 
organisms. It can reconstruct the phylogeny through various methods. Evolution is the 
central idea running through the whole process to build the phylogeny. The ?evolution? 
can be tracked and expressed using some ways which make it possible to reconstruct the 
original relationships among them. The most common methods involved in inferring 
phylogenetics or for constructing trees from morphological and genetic sequence data are 
distance, parsimony and likelihood. Distance is an algorithmic approach which can only 
yield one single tree with high speed from any given datasets. Whereas parsimony and 
likelihood are tree-searching approaches that can construct many trees and then performs 
some criteria to choose the best tree(s) with relative lower speed. 
Distance 
Algorithm 
Whenever we want to start a phylogenetic method, the first thing we need to 
consider is the algorithm to make the tree. Neighbor-joining is a widely used algorithm 
 
9
for tree-building (Saitou and Nei, 1987). This method infers phylogeny by using a 
pairwise distance matrix which can be generated from various sources, morphological 
data, genetic data, etc. Basically, the algorithm calculates the number of changes between 
pairwise sequence data as different distances to create the matrix. Then, it requires to find 
a pair of taxa with lowest distance value to join together and create a node, followed, find 
the other taxa with the lowest value to the node, so on and so forth (join the closest 
neighbors). Obviously, the reconstructed tree by using NJ method does not really stand 
for the one with the smallest branch length. However, the calculation is very fast as 
compared to other methods especially with large datasets. In addition, it has been proven 
to be comparatively accurate and statistically consistent. Therefore, with large datasets, 
NJ method is always first used to quickly preview the reconstructed phylogeny. This 
algorithm allows selection of a specific model to correct the distance matrix when it is 
calculated. The simple measure of the changes will be the directly observed difference 
between pairwise. However, it can underestimate the actual changes by ignoring multiple 
changes occurring at a certain site (i.e. convergent, parallel, reversal and so on). So as to 
minimize errors due to multiple changes, models can be chosen to correct and estimate 
the actual number of changes (See Model part in Maximum Likelihood). 
The simplest distance algorithm is UPGMA (Unweighted Pair Group Method 
with Arithmetic mean), which assumes a constant evolution rate (the existence of 
molecular clock) (Sneath and Sokal 1973). After constructing the distance matrix, the 
nearest two groups will be clustered into a higher group level. Then, by taking average of 
the distances between members in one group with members in the other to decide how 
groups are related. Although it was once used in protein electrophoresis, this method has 
 
10
been seldom used in recent studies due to the inappropriate constant evolution rate 
assumption and has totally been replaced by NJ (Neighbor-joining) method.  
Optimality Criterion 
After obtaining a tree, optimality criteria should be implemented to search or 
estimate the best-fit tree. Minimum evolution is an optimal criterion used in the distance 
approach which assumes that the best phylogenetic tree has the smallest branch length 
(distances) by calculating the pairwise from distance matrix. This method will compute 
all possible trees and then compare branch lengths for those trees. However, the branch 
lengths calculated under distance approach may not be evolutionary interpretable. 
Additionally, because distance uses the transformed pairwise matrix to build trees, it is 
eventually possible to lose some information from the original dataset, for instance, DNA 
alignment. 
Maximum Parsimony 
As compared to the cluster-based distance method (NJ), discrete methods witch 
are character-based, like parsimony, maximum likelihood and Bayesian inferences 
operate directly on the sequence alignment by comparing characters at each site, and thus 
avoid loss of information. 
Algorithm 
The algorithm under maximum parsimony approach can also start from either a 
NJ tree or a random tree. 
 
 
11
Optimality Criterion 
Maximum parsimony is a non-statistical character-based criterion. Maximum 
parsimony tree with fewest total number of evolutionary changes or substitutions 
(minimize the total tree length) requires to explain the differences across taxa in a given 
dataset (e.g., Farris, 1970). The assumption is that all investigated taxa share a common 
characteristic since they all evolved from a common ancestor without considering the 
homoplasy which makes a character in a same state with different evolutionary history 
and origins caused by reversal, convergence and parallelism. The total number of 
evolutionary changes on a tree (branch length of this tree) is simply the sum of the 
change numbers at each site. Under the criterion of maximum parsimony, a tree-searching 
strategy will be performed to look for the best tree(s) by calculating the total number of 
changes for each tree.  
Problems with parsimony 
Parsimony doesn?t guarantee finding the best tree, multiple trees may be the most 
parsimonious with the same branch length in some cases. So, an unresolved consensus 
tree can be constructed to visualize the congruity. The most parsimonious tree(s) may not 
be the true one. Additionally, it doesn?t correct for multiple mutations within one site 
(homoplasy) because it doesn?t imply an evolutionary model. Branch lengths cannot be 
accurately estimated (underestimated). It is relative slow in computing time in 
comparison with distance methods. 
 
 
 
12
Maximum likelihood 
Algorithm 
The algorithm under maximum likelihood approach can also allow getting start 
from either a NJ tree or a random tree. 
Optimality Criterion 
Maximum likelihood (ML) is a powerful tree-searching criterion and very widely 
used in phylogenetic analyses (Cavalli-Sforza and Edwards, 1967; Felsenstein, 1981). 
The principle of ML is the phylogeny with the highest likelihood is taken to be correct. 
When we calculate the likelihood of a phylogeny, we score the probability of all possible 
ancestral states across each site for each possible topology based on the specific 
evolutionary model. 
ML method of inference is available for both nucleic acid and protein data using 
PAUP for nucleic acids (Swofford, 2002) and RAxML for amino acid datasets 
(Stamatakis, 2006), for example. It always generates one single tree with the lowest tree 
length and highest likelihood score. It is most likely to be the true tree. A likelihood tree 
has meaningful branch lengths. If a branch length is equal to 1, meaning that one change 
per character on that branch.  
Given the model and a possible tree, ML calculates the likelihood of observing 
the data:  
L(Model) = P(Data|Model), 
First of all, we select a specific model for a data alignment and generate all possible tree 
structures for each site. The state of each character within that site is plotted on the tree. 
 
13
Based on the selected model, the probability of the distribution of character states is 
calculated to get the probability of that character, given the tree. Then, the probabilities of 
all of the characters is multiplied together in form of negative log-transformed and sum 
the probabilities for each position to get the probability of the data, given the tree. Finally, 
a tree is chosen with the highest likelihood (lowest negative log-transformed likelihood). 
Evolutionary model 
ML searches for an evolutionary tree with the highest probability of observing the 
data given an explicit model. Different models have variable parameters to express their 
evolutionary process. For instance, one-parameter model (Jukes-Cantor model, Jukes and 
Cantor, 1969) assumes equal nucleotide frequencies of all four bases (A, T, G, C) and 
constant substitution rate between all bases (Fig 3. a=b=c=d=e=f). In Kimura?s two-
parameter model (Kimura, 1980), different substitutions occur at different rates 
(transitions occur at rate a=c=d=f, transversions occur at rate b=e) with equal nucleotide 
frequencies. The F81 model assumes four unequal base frequencies with constant 
substitution rate (Felsenstein, 1981). Other models with different modifications of 
substitution rates and base frequencies are shown in Table 1.  
The most commonly used model for DNA data is the general time-reversible 
(GTR) model which combines all of the above models and assumes six different 
substitution rates with unequal base frequencies as special cases (Lanave et al., 1984; 
Barry and Hartigan, 1987; Rodriguez et al., 1990). This model can be time-reversible. 
Taking evolutionary rate heterogeneity among the lineages of particular genes into 
account, GTR+G+I is often modified from GTR with the discrete Gamma distribution (G) 
and addition of invariable sites (I). Gamma distribution is used to correct the substitution 
 
14
rate across sites by estimating rates across all sites. Gamma distribution has two 
parameters, a (shape parameter) and b (scale parameter). As a increases, higher frequency 
of variable sites have equal substitution rate (equal-rate model). As a decreases, stronger 
among-site variation in the data. Gamma distribution models the variant distribution 
among sites with different substitution rates. With this parameter, rate heterogeneity can 
be corrected. 
Furthermore, because almost all genes have invariable sites across lineages, the 
proportion of invariable positions may change with an enlarged time scale or different 
lineages, which is usually considered as a plus parameter.  
A specific model can be selected by Modeltest program (Posada and Crandall, 
1998) for nucleotide dataset or ProtTest for amino acid dataset (Abascal st al., 2005).  
Advantages and disadvantages 
Because ML requires computation of likelihood for all the candidate topologies of 
each site, it evaluates all possible tree topologies and calculates all their likelihoods. It 
provides more confidence than other methods. Additionally, ML is a model-based method 
which tends to be robust. The big problem of ML is that it is time consuming and 
computationally intensive. It is virtually impossible to compute all the probabilities when 
taxa number is large. Additionally, results are based on the model chosen. A bad model 
can lead to a tree with less reliability. 
Tree-searching strategy under optimality criteria 
Under the selected optimality criterion, the optimal tree(s) need(s) to be evaluated 
among all searched trees by tree-searching methods. NJ tree is often treated as a starting 
 
15
point for tree-searching. The methods include exhaustive search which uses exact 
algorithm (with branch-and-bound or branch-addition algorithm) and heuristic strategy 
(with stepwise addition, branch swapping or star decomposition method; Hendy and 
Penny, 1982; Swofford, 1996). Exhaustive search evaluates every tree and guarantees 
finding the optimal tree. It can only conduct small datasets. Heuristic search can be used 
to search trees with a  larger dataset, however, it can?t guarantee that the best tree is found 
and can result in more than one equally parsimonious tree. So a consensus tree needs to 
be created to mix all possible relationships in one unresolved tree. The reason that 
heuristic search can?t guarantee the best tree is because it is essentially based on a hill-
climbing algorithm in which a single initial tree is built then rearrangements are 
performed to improve the tree and keep the tree better than the previous one. 
Bootstrapping 
Once we obtain the best tree, its topology with the order of branches may not be 
very reliable. So it is very important to perform a statistical estimation for a reliability test. 
Bootstrapping is a way to estimate the reliability of the tree by generating a 
pseudoreplicate datasets (alignment) and creating trees based on those datasets using 
same tree-construction methods (Bradley et al., 1996). The randomly resampling method 
is used to sample the original alignment so as to produce a new character alignment with 
same size as the original one. The resampling allows replacement meaning that the same 
site can occur in new alignment more than once or disappear. In phylogenetic analyses, 
nonparametric bootstrapping is very commonly used. The frequency that a given branch 
can be found during bootstrapping will be written as a proportion number on each branch. 
These numbers can measure the reliability of individual branches. Since the larger the 
 
16
number, the higher the reliability. These frequency numbers can examine how often an 
individual branch appears in resampled pseudoalignment and evaluate their reliability, the 
larger the number, the higher the reliability for each branch. Both parsimony and 
likelihood method need bootstrapping after a tree is obtained. 
Bayesian Inference 
The Bayesian approach is relative new and has a strong connection with 
likelihood method (Geyer, 1991; Hueslenbeck and Ronquist, 2001). The only difference 
is that it calculates the posterior probability which is proportional to the likelihood 
multiplied by the prior probability (Yang and Rannala, 1997; Larget and Simon, 1999). 
The product of these two quantities over all possible parameter values is integrated to 
score the posterior probability for the tree.  
In Bayesian approach, the Markov chain Monte Carlo (MCMC) algorithm is 
implemented. MCMC can approximate the probability distribution over a vast range. 
MCMC works by forming a conceptual chain (Larget and Simon, 1999). In each step, it 
proposed a new location as the next link of the chain. Then the posterior-probability 
density of that new location is calculated. If the score is higher than the one in current 
location of the chain, the new location will be the next link of the chain so as to push the 
chain moving forward. If the score is lower than the current one, the chain will keep its 
present location and not move on until it finds a new one with higher score. After 
repeating the same procedure a million times, a long chain forms and would always stay 
in locations with the highest posterior probability. Then, it will combine all trees to 
calculate the probability of the appearance for each tree, the highest probability, the best 
tree. During phylogenetics, MCMC forms a long chain by estimating the posterior 
 
17
probability through different trees and evolutionary models. 
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25
Table 1. Parameters in evolutionary models (Model abnreviations: JC, Jukes and Cantor 
(1969) model; K2P, Kimura (1980) two-parameter model; TrN, TrN model with equal 
base frequencies, Tamura and Nei 1993; SYM, Zharkikh 1994; F81, model of Felsenstein, 
Felsenstein 1981); HKY85, Hasegawa-Kishino-Yano model, Hasegawa et al., 1985; 
K3ST, Kimura 3 substitution type model, Kimura, 1981), GTR, General time-reversible 
model, Lanave et al., 1984; Rodrigues et al., 1990) 
Model Substitution Rate Base frequencies 
JC a=b=c=d=e=f equal 
K2P a=c=d=f, b=e equal 
TrN a=c=d=f, b, e equal 
SYM a, b, c, d, e, f equal 
K3ST a=c=d=f, b, e equal 
F81 a=b=c=d=e unequal 
HKY85 a=c=d=f, b=e unequal 
GTR a, b, c, d, e, f unequal 
 
 
Figure 1. Five families of Terebelliformia worms. A. Terebellidea; B. Avinellidae 
(http://www.mbari.org/expeditions/ridges2005/august_11.htm); C. Pectinariidae; D. 
Trichobranchidae; E. Ampharetidae (Both D and E are from Rouse and Pleijel, 2001). 
 
26
 
Figure 2. Microscopic views of Endomyzostoma sp. (Figures are from Lanterbecq et al., 
2006) B: Endomyzostoma deformator; D: Endomyzostoma sp.. 
 
27
 
Figure 3. Substitution rates between all bases in evolutionary models. 
 
28
 
29 
CHAPTER 2 
PHYLOGENETIC INFORMATION FROM THE THREE MITOCHONDRIAL 
GENOMES OF TEREBELLIFORMIA (ANNELIDA) WORMS AND 
DUPLICATION OF THE METHIONINE tRNA 
 
30 
Abbreviations 
A - adenine; AIC - Akaike information criterion; atp6 and 8 ? ATP synthase 
subunits 6 and 8; bp ? base pair; 
o
C ? degrees Celsius; C - cytosine; cob ? cytochrome b 
apoenzyme; cox1-3 ? cytochrome c oxidase subunits 1-3; dNTP ? deoxy- nucleotide 
triphosphate; G - guanine; kb ? kilobases; ML ? maximum likelihood; mLSU ? 
mitochondrial large subunit ribosomal gene; mSSU ? mitochondrial small subunit 
ribosomal gene; mtDNA -  mitochondrial deoxyribonucleic acid; N - nucleotide; nad1-6 
and 4L ? NADH dehydrogenase subunits 1-6 and 4L; NADH ? nicotinamide adenine 
dinucleotide; Nc ? effective number of codons; PCR ? polymerase chain reaction; RSCU 
- relative synonymous codon usage; T ? thymine; TBR - tree-bisection-reconnection; 
tRNA ? transfer ribonucleic acid; trnL1 and trnL2 ? tRNA leucine 1 and 2; trnM -  tRNA 
methionine; trnR ? tRNA arginine; trnS1 and trnS2 ? tRNA serine 1 and 2; trnW ? tRNA 
tryptophane; UNK ? unknown region. 
 
31 
Abstract 
Mitochondrial genomes have been useful for inferring animal phylogeny across a 
wide range of clades, however they are still poorly sampled in some animal taxa, limiting 
our knowledge of mtDNA evolution. For example, despite being one of the most diverse 
animal phyla, only 5 complete annelid mitochrondial genomes have been published. To 
address this paucity of information, we obtained complete mitochondrial genomic 
sequences from Pista cristata (Terebellidae) and Terebellides stroemi (Trichobranchidae) 
as well as one nearly complete mitochondrial genome from Eclysippe vanelli 
(Ampharetidae). These taxa are within Terebelliformia (Annelida), which include 
spaghetti worms, icecream cone worms and their relatives. In contrast to the 37 genes 
found in most bilaterian metazoans, we recover 38 genes in the mitochondrial genomes of 
T. stroemi and P. cristata due to the presence of a second methionine tRNA (trnM). 
Interestingly, the two trnMs are located next to each other and are possibly a 
synapomorphy of these two taxa. The E. vanelli partial mitochondrial genome lacks this 
additional trnM at the same position, but it may be present in the region not sampled. 
Compared to other annelids, gene orders of these three mitochondrial genomes are 
generally conserved except for the atp6-mSSU region. Phylogenetic analyses reveal that 
mtDNA data strongly supports a Trichobranchidae/Terebellidae clade. 
 
32 
1. Introduction 
Composition of the mtDNA genome is conserved across Bilateria containing 13 
protein-coding genes, two ribosomal genes, 22 tRNA genes and one non-coding UNK 
region (unknown region), the presumed origin of replication. Generally, the size of 
mitochondrial genomes is about 15-17kb with homologous genes across Bilateria (Boore, 
1999; Vall?s and Boore, 2006). Whereas some taxa have highly rearranged mitochondrial 
genomes, gene order within annelids is hypothesized to be relatively conserved (Jennings 
and Halanych, 2005; Vall?s and Boore, 2006). Despite the utility of mitochondrial 
genomes for phylogenetic reconstructions of major animal taxa, only five complete and 
five partial annelid mitochondrial genomes are available in GenBank as of October 2007. 
One reason for this bias in sampling is that in some taxa, including annelids, the UNK 
region (also called the D-loop or control region) has been difficult to amplify and 
sequence presumably because of secondary structure and/or microsatellite regions (Boore 
and Brown, 2000; Boore, 2001; Jennings and Halanych, 2005; Bleidorn et al., 2006a, b). 
Annelida is a very diverse group of animals comprising around 16,500 described 
species including previously recognized ?phyla? (echiurids, sipunculids, and siboglinids ? 
a.k.a. pogonophorans; McHugh, 1997; Boore and Staton, 2002; Bleidorn et al. 2006a; 
Struck et al., 2007). Even though relationships among annelid groups are not well 
understood, some higher-level annelid clades have been recovered with both morphology  
(Rouse and Fauchald, 1997) and molecular tools (Rousset et al., 2006; Struck et al., 
 
33 
2007). One such group, Terebelliformia, comprises five ?families? (including Alvinellidae, 
Ampharetidae, Terebellidae, Trichobranchidae and Pectinariidae), which are typically 
sedentary benthic tube dwellers (Rouse and Pleijel, 2001). Phylogenetic position of 
Terebelliformia within annelids and relationships among those five ?families? remain 
debatable, but terebelliform monophyly has been recovered (Colgan et al., 2001; Struck 
et al., 2007) with Trichobranchidae treated as either a ?subfamily? of Terebellidae (e.g. 
Rouse and Pleijel, 2001), or a recognized ?family? (McHugh, 1995; Fauchald and Rouse, 
1997; Glasby et al., 2004).  
 To further understand the phylogenetic utility of mitochondrial genome data 
within annelids, we examined mitochondrial genomes of three Terebelliformia worms 
(Eclysippe vanelli--Ampharetidae, Pista cristata--Terebellidae and Terebellides stroemi-- 
Trichobranchidae). Gene composition and arrangement, tRNA folding patterns, and 
nucleotide patterns were examined.  A phylogenetic assessment was performed to assess 
these Terebelliformia taxa relative to other annelid mitochondrial genome data available 
in GenBank.  
2. Materials and Methods 
2.1 Sample collection and DNA extraction 
Pista cristata (Terebellidae) was collected in central Californian waters (36
o
23.0N, 
121
o
57.9W) using the R/V Pt. Sur, Terebellides stroemi (Trichobranchidae) was obtained 
off southern New England (40
o
 46.1N, 71
o
156.2W) using the R/V Oceanus, and 
Eclysippe vanelli (Ampharetidae) was collected near Trosm? Norway (63
o
30.8N, 
10
o
25.0E ) using the R/V H?kon Mosby. All organisms were frozen at -80?C after 
 
34 
collection. Total genomic DNA extractions employed the DNeasy? Tissue Kit (Qiagen) 
according to the manufacture?s instructions.  
2.2 mtDNA data collection 
Gene nomenclature and abbreviations in this paper follow Jennings and Halanych 
(2005). 
Terebellides stroemi 
 The genome was amplified in three overlapping sections. First, conserved regions 
of mLSU, cox1, cob genes were amplified using taxonomically-inclusive primers (Table 
1). After purification with QIAquick PCR purification kit (Qiagen), and sequencing of 
these products using a CEQ8000 (Beckmann), three pairs of species-specific primers for 
long PCRs were generated: Ter-16S-F/Ter-CO1-R, Ter-CO1-F/Ter-Cytb-R and Ter-Cytb-
F/Ter-16S-R (Table 2). Long PCRs were performed on Eppendorf Mastercycler 
(Eppendorf) using Takara LA-Taq or the Eppendorf
?
 TripleMaster PCR System. 50 ?l 
long PCR reactions using Takara LA-Taq were set up as follows: 5?l 10?buffer, 8?l 
dNTP (2mM), 5?l MgCl
2
 (25mM), 2?l of each long PCR specific primers (10?M each), 
0.5?l Takara LA-Taq (5U/?l), 2?l DNA template and 25.5?l sterilized distilled water. 
The protocol for HotStart long PCRs was 94 ?C for 3min; then polymerase was added by 
pipette (while samples were in the 94?C block) followed by 35 cycles with 94?C for 30 
sec, 52?C for 30s, and 70?C for 12min; final extension at 72?C for 10min and hold at 4?C. 
Both mLSU-cox1 and cox1-cob regions were 4-5 kb in size. For cob-mLSU fraction we 
used Eppendorf
?
 TripleMaster PCR System with the 50?l reactions containing 5?l 
Tuning buffer with 25mM Mg
2+
, 12.5?l dNTP (2mM), 3?l of each long PCR specific 
 
35 
primers (10?M each), 0.4?l TripleMaster (5U/?l), 2?l DNA template and 24.1?l 
sterilized distilled water. The cycling profile was as follows: 93 ?C for 3min; then 10 
cycles with 93?C for 15sec, 50?C for 30sec, and 68?C for 4min 30sec; followed by 28 
cycles with 93?C for 15sec, 50?C for 30sec, and 68?C for 4min 30sec (20sec increase 
each subsequent cycle); final extension at 68?C for 15min and hold at 4?C. The cob-
mLSU fragment was approximately 7.5 kb in size.  
All three long fragments were purified with QiaQuick Gel Extraction Kit (Qiagen) 
and cloned into the pGEM-T Easy vector (Promega). Clones were verified by PCR, 
grown overnight, and plasmids were isolated using the QIAprep
?
 Spin Miniprep Kit 
(Qiagen). Purified plasmids were digested by EcoRI to check the insert size. 
Using EZ::TN5? Insertion Kit (EPICENTRE), primer regions were inserted 
according to the manufacturer?s instruction for subsequent sequencing. Unfortunately this 
kit was biased with many more transposons inserted (per kb) into the 3kb vector rather 
than the cloned mtDNA region, thus primer walking was employed to complete the 
fragments. Information for all sequencing primers can be found in Table 3. 
Pista cristata and Eclysippe vanelli 
 Genomes for P. cristata and E. vanelli were amplified in four segments. 
Fragments of mLSU, cox1, cob and nad4 genes were amplified by taxonomically 
inclusive primers (Table 1) and sequenced. For each species, four pairs of specific long-
PCR primers (Table 2) were designed to amplify long fragments: mLSU-cox1, cox1-cob, 
cob-nad4 and nad4-mLSU. Long PCRs employed Takara LA-Taq as described above. 
The protocols of long PCR and purification were similar to those of T. stroemi except for 
 
36 
annealing temperatures (see Table 2). All fragments were cloned into pGEM-T Easy 
vector (Promega) and clones screened as above. Fragments of mLSU-cox1 and cox1-cob 
in both species were sequenced by EZ::TN5? Insertion Kit (EPICENTRE) (with 
insertion bias again) and several internal primers. cob-nad4 and nad4-mLSU fragments 
were sequenced by primer walking.  
The nad4-mLSU fragment of Eclysippe, apparently containing the UNK region, 
was difficult to amplify. Thus, new degenerate primers were designed to amplify regions 
of nad5 and mSSU (Table 1) based on alignment of published annelid mitochondrial 
genomes. Subsequent long PCR primers (Nad5-Ev-698F/ Nad5-Ev-820R and 12S-Ev-
longR) were produced. This approach allowed recovery of the mSSU-mLSU  
(primers12S-Ann-256F/16SbrH) and the nad4-nad5 region (primers Nad4-Ev-startF/ 
Nad5-Ev-820R).  Resulting fragments were cloned, but the nad5-mSSU fragment could 
not be amplified despite several attempts. Based on the available information, E. vanelli?s 
missing region presumably includes part of nad5 and mSSU genes, the UNK region, trnK, 
and trnR. 
2.3 Genomic Assembly 
Sequences were edited and aligned using DNASTAR? Lasergene programs 
SeqMan and MegAlign (Burland, 2000). Protein-coding genes and ribosomal RNA genes 
were identified by Artemis (Rutherford et al., 2000) and Blast (Altschul et al., 1990). All 
tRNA genes were identified using tRNAscan-SE web server 
(http://lowelab.ucsc.edu/tRNAscan-SE/; Lowe and Eddy, 1997) under default settings 
and source = ?mito/chloroplast?, or by eye based on their potential secondary structures 
and anticodon sequences. Boundaries of UNK regions in P. cristata and T. stroemi were 
 
37 
inferred by identifying flanking tRNA sequence. Secondary structure of UNK region was 
examined with the ?mfold? online server (Zuker et al., 1999) and DNASTAR? 
Lasergene program GENEQUEST (Burland, 2000). 
2.4 Phylogenetic analysis 
 Analyses included all available annelid mitochondrial genomes with about 50% 
coverage or greater (Table 4). The alignment of Jennings and Halanych (2005) was 
employed, to which Orbinia latreillii, Scoloplos cf. armiger, Urechis caupo, and the three 
terebelliform mitochondrial genomes were added (Table 4). Because we are interested in 
relationships within annelids and given results of recent mitochondrial genome analyses 
(Jennings and Halanych, 2005; Bleidorn et al., 2006a), a representative brachiopod and a 
mollusk were used as outgroups. Two datasets were created for phylogenetic analyses. In 
the nucleotide dataset, the 2 rRNA genes and all protein-coding genes (except for atp6, 
atp8 and nad6 genes which exhibit high variability) were included. We used Clustal X 
(Thompson et al., 1997) under default setting to realign rRNA genes. MacClade4.08 
(Maddison and Maddison, 2002) was used to exclude most regions that contain 
insertions/deletions and all third codon positions in protein coding genes.  Gblocks 0.91b 
(Castresana, 2000) was used to identify ambiguous aligned regions in rRNA genes 
(mLSU and mSSU) that were excluded from analyses. The amino acid dataset was created 
from the translated (invertebrate mitochondrial code) aligned nucleotide dataset with 
exclusion of rRNA genes by MacClade4.08 and Se-Al v2.0a11 (Rambaut, 1996). All 
alignments are available at TreeBase (accession no SN3857 and SN3858). 
 For the nucleotide dataset, phylogenetic analyses employed both maximum 
likelihood and Bayesian-inference approaches.  Maximum-likelihood analyses were 
 
38 
performed in PAUP4.0b10 (Swofford et al., 2002) with a GTR+?+I model as determined 
by MODELTEST v3.7 based on the Akaike information criterion (AIC) (Posada and 
Crandall, 1998). Heuristic searches were run with random-taxon addition (10 replicates) 
using Tree-Bisection-Reconnection (TBR) swapping. All model parameters used fixed 
values as determined by MODELTEST v3.7. Bootstrap analysis employed 1,000 
iterations using heuristic searches with 10 random taxa addition. Bayesian inference 
analyses in MRBAYES version 3.1.2 (Huelsenbeck and Ronquist, 2001) used 5,000,000 
generations with 2 runs of chains (3 heated and 1 cold), and sampling every 100 
generations. Both non-partitioned and partitioned Bayesian analyses were employed.  For 
the non-partitioned analyses, we use prior distributions according to the GTR+?+I model 
selected under the AIC in MrModeltest (Nylander, 2004). The partitioned analysis used 
unlinked GTR+?+I models for which parameters were individually estimated for each 
gene partition (note nad3 and nad4 partitions used no proportion of invariant sites 
resulting in a GTR+? model).  Resulting -ln likelihood scores were graphed using X-Y 
scatter plots to identify the ?burn-in? point at which all estimated parameters reached 
stationarity (burnin = 2,500).  
 For the amino acid dataset, a non-partitioned ML analyses was run in addition to 
non-partitioned and partitioned Bayesian analyses. For ML analyses, model selection was 
performed in ProtTest (Abascal st al., 2005) and MtArt +?+I+F model was chosen as the 
best one under the AIC. As there is no MtArt model used in RAxML, we chose the next 
best model, MtREV+?+I+F, available in RAxML. A maximum likelihood search was 
implemented by 200 bootstrap replicates using RAxML 7.0.0 (Stamatakis, 2006) with 
MtREV+?+I+F model by the ?PROTGAMMAIMTREVF? option. The non-partitioned 
 
39 
Bayesian analysis was conducted with the mixed amino acid substitution model option 
plus a ? distribution and a proportion of invariant sites in MRBAYES v3.1.2 with 
5,000,000 generations sampled every 100 generations (burnin = 2,500). In the mixed 
model option, a specific model is not specified a priori, but each model is chosen during 
the runs based on its posterior probability. We also employed a partitioned amino acid 
analyses in MrBayes in which, the mixed amino acid substitution model option plus a ? 
distribution and a proportion of invariant sites was assigned to each partition individually 
and unlinked during the run. All other settings remained the same (burnin = 2,500). 
3. Results and Discussion 
3.1 Genome Composition 
 The complete mtDNA of T. stroemi  and P. cristata are 15,755 bp and 15,894 bp 
in length respectively. Both contain 38 genes including 13 protein-coding genes, two 
rRNA genes and 23 tRNAs. Both genomes contain 2 copies of the methionine tRNA gene. 
The partially sequenced mitochondrial genome of E. vanelli is 13,749 bp in length. 
However, regions of nad5 and mSSU genes, the UNK region and 2 tRNA genes (trnK and 
trnR) were not recovered for E. vanelli. Fig. 1 shows gene orders of these taxa as well as 
other annelids taxa available in GenBank. As in other annelids (Boore and Brown, 2000; 
Boore and Staton, 2002; Jennings and Halanych, 2005; Bleidorn et al., 2006a, b;), all 
Terebelliformia mitochondrial genes are transcribed from the same strand. Terebellides 
stroemi and P. cristata have identical gene arrangements, and are unique in containing 
two methionine tRNAs in tandem. Eclysippe vanelli has a different gene order and 
presumably, like other bilaterians, only one trnM.  
 
40 
 All three genomes are AT-rich (>66%) with T being the most common base (Table 
5). The low percentage of G in the third codon positions is also notable in both P. cristata 
(3.1%) and T. stroemi (4.5%), but in E. vanelli percentage of C is the lowest (see Table 5). 
Skewness, a measure of the bias of the base composition, is calculated as (A-T)/(A+T) 
and (G-C)/(G+C) for an individual strand (Perna and Kocher, 1995). Table 5 lists the AT-
skew and GC-skew in both protein-coding genes and whole genome sequences for the 
terebelliform genomes. Whereas both T. stroemi and P. cristata exhibit GC-skews more 
negative than AT-skews, E. vanelli has positive GC-skews. Negative values in skewness 
mean the coding strand has more Ts or Cs, respectively. In contrast, positive values 
indicate more As or Gs.  
3.2 Protein-coding genes 
 Terebelliform genomes contain all 13 protein-coding genes typically found in 
metazoan mtDNA (Boore, 1999). Effective number of codons used in a gene (Nc) can be 
used to quantify departure from equal codon usage of synonymous codons, that is codon 
usage bias (Wright, 1990) (Table 6). Nc is reported as values from 20 to 61, where 20 
represents extreme bias of one codon exclusively used for each amino acid and 61 
represents equal probability of alternative synonymous codons. Nc values, which are 
similar in all three terebelliform genomes (42.5 for T. stroemi, 40.1 for P. cristata and 
40.8 for E.vanelli), show greater codon usage bias than other annelid mitochondrial 
genomes (Bleidorn et al., 2006a). In all terebelliforms, third position As or Ts (NNA or 
NNU) are more used than third position Gs or Cs (NNG or NNC), respectively, for 2-fold 
degenerated codons (Table 6). For T. stroemi and P. cristata, the difference between the 
usage of NNA and NNG is more pronounced than for NNU versus NNC, but in E. vanelli 
 
41 
the situation is reversed. For 4-fold degenerated codons, NNC is more frequent than 
NNG in T. stroemi and P. cristata, but both are less common than NNU and NNA with 
the latter being used more often (Table 6). In E. vanelli however, NNG is more common 
than NNC and NNU than NNA. Thus, the bias in codon usage reflects the AT richness as 
well as the distribution of base frequencies at the third positions except for P. cristata, 
which shows a higher frequency of T than A confirming that codon usage bias and base 
frequency bias are tightly linked. Furthermore, the average relative synonymous codon 
usage (RSCU) of the tRNA?s found in the mitochondrial genomes of either T. stroemi or 
P. cristata is 1.41 or 1.31, respectively. In E. vanelli on the other hand, the RSCU for 
these tRNA?s is only 0.85. Correspondingly, the patterns in the 4-fold and 2-fold 
degenerated codons are the opposite to the ones in T. stroemi and P. cristata indicating a 
possible relative preference of nuclear tRNA?s in E. vanelli. 
 Other codon features include ATG, the start codon in all protein-coding genes 
with the exception of cox1 in E. vanelli which is initiated by the codon ATA. Our 
observations are consistent with previous reports in annelids where ATG is the most 
common initiation codon with the occasional use of ATA, ATC, GTG, GCC and GTT in 
some genes (Boore and Brown, 2000; Jennings and Halanych, 2005; Bleidorm et al., 
2006a).  
 An incomplete termination codon, a single T, is used for many NADH genes 
(nad4 and nad1 genes in T. stroemi; nad5, nad1 and atp8 genes in P. cristata; cox1, cob, 
nad5, nad4, nad3 and nad2 genes in E. vanelli). This incomplete codon is presumably 
completed to a TAA stop codon via a polyadenylation process (Ojala et al., 1981). All 
other protein-coding genes in T. stroemi and P. cristata contain the complete TAA 
 
42 
termination codon. In E. vanelli, TAG is used as a termination codon in three genes (cox3, 
cob and atp6). The cob gene in E. vanelli is ~20 bp shorter than in other annelids, 
yielding 19 intergenic nucleotides between cob and the adjacent trnW gene.       
Overlapping genes have been reported in compact genomes (Kurabayashi and 
Ueshima, 2000; Firth and Brown, 2006). In addition to the one overlap mentioned above, 
nad4L (which has a complete termination codon TAA) has a 7 bp overlap with the 
downstream nad4 genes in all three genomes.  
3.3 tRNAs 
 Secondary structures of all tRNAs are depicted in Fig. 2. Both T. stroemi and P. 
cristata have 23 tRNA genes respectively in their mitochondrial genomes. Only 20 tRNA 
genes were found in the partial E. vanelli mtDNA.  
 We found two trnMs adjacent to each other in mtDNAs of both T. stroemi and P. 
cristata. Unlike 2 trnLs and 2 trnSs, the trnMs have the same anticodon triplet (AUG) 
coding for methionine. For the sake of clarity, we have called the 5? upstream copy of the 
translated strand trnM1 and the 3? downstream copy trnM2. The T?C stems of both 
trnM2s with only 2 or 3 matching bases are much shorter than the ones of trnM1. The 
shorter T?C arm occurs in other Annelida taxa, including Clymenella torquata, Eclysippe 
vanelli, Platynereis dumerilii, Lumbricus terrestris, Riftia pachyptila and Urechis caupo 
(Boore and Brown, 1995, 2000; Boore et al., 1999; Jennings and Halanych, 2005). 
Additionally, both trnM2s possess identical 4 base-pair DHU stems, same as trnM1 of P. 
cristata, which is conserved in trnM across the sampled Annelida taxa and found in other 
bilaterians (e.g., the mollusk Katharina tunicata, and the cephalochordate Branchiostoma 
 
43 
floridae; Boore and Brown, 1994, 1995, 2000; Boore et al., 1999; Boore and Staton, 2002; 
Jennings and Halanych, 2005). In terms of both nucleotides and structure, trnM2 is much 
more similar to other annelid trnMs including E. vanelli. 
In T. stroemi, trnR lack potential for folding a DHU stem (D arm) which is 
thought to act as a recognition site for aminoacyl-tRNA synthetase (Clark, 2006). The 
lack of a DHU stem has been reported in several known mtDNAs of annelids taxa (Boore, 
2001; Jennings and Halanych, 2005).  
3.4 UNK region 
 The UNK region of T. stroemi, 802 bp, and P. cristata, 844 bp, is located between 
trnR and trnH. Both of them are AT-rich (T.stroemi: 72.5%; P. cristata: 78.4%) and 
possess microsatellite-like sequences. About 50 uncontinuous TATA-repeats mainly occur 
within 200 bp from trnR in T. stroemi and 350 bp in P. cristata. We have examined this 
region for secondary structure using both the ?mfold? online server (Zuker et al., 1999) 
and DNASTAR? Lasergene program GENEQUEST (Burland, 2000). Both approaches 
reported several hairpin structures within the UNK region. However, results between the 
two programs differed in size and location of secondary structures. Thus, secondary 
structure, in addition to nucleotide repeats, likely hindered our ability to recover the E. 
vanelli UNK region. 
3.5 Structure and Gene order 
 Gene orders of P. cristata and T. stroemi are identical to those of Clitellata, 
Siboglinidae and Maldinidae, except for the second trnM reported above and the position 
of trnK in maldanids (Fig. 1). Therefore, this gene order is most likely symplesiomorphic 
 
44 
for annelids. When genomes are aligned, a few clusters with conserved gene boundaries 
can be identified (see Fig. 1). The observation of conserved gene order for several 
protein-coding genes in association with rearrangements for tRNA genes and UNK 
region across Annelida worms has been previously noted (Jennings and Halanych, 2005; 
Vall?s and Boore, 2006; Bleidorn et al., 2006a). In contrast, E. vanelli is expected to 
show variation in the arrangement of several tRNA genes and the UNK region compared 
to these taxa (Fig. 1). Furthermore, nad4L and nad4 are placed before nad5 in E. vanelli, 
suggesting the atp6-mSSU region across annelids is more variable than other regions. In 
general, gene order is conserved across sampled annelids with the exception of Urechis 
caupo (the echiurid) and Phascolopsis gouldii (the sipunculid). Whereas the first part 
from cox1 to cob of the incomplete sipunculid genome is conserved, the remaining gene 
order shows rearrangements compared to other annelids (Vall?s and Boore, 2006).  
3.6 Phylogenetic Analyses 
Maximum likelihood and Bayesian inference (both non-partitioned and 
partitioned) of nucleotide data yielded identical topologies which are slightly different 
from that of the non-partitioned Bayesian inference and RAxML amino acid analyses 
(Fig. 3). The partitioned Bayesian amino acid analysis was poorly resolved (Fig. 4) and 
resulted in topology that was consistent with nucleotide trees. The siboglinids, echiurid 
and sipunculid fell inside Annelida with significant posterior probabilities in nucleotide 
and amino acid data. This finding is consistent with previous results from nuclear 
markers (e.g., McHugh, 1997; Bleidorn et al., 2003), mitochondrial DNA (Bleidorn et al., 
2006a) and combined molecular data (Struck et al., 2007). Placement of these taxa within 
Annelida confirms that segmentation has been highly modified or lost within annelid 
 
45 
lineages (Halanych et al., 2002; Struck et al., 2007). 
The close relationship between the echiurid and the aciculate Platynereis, found 
in the nucleotide trees here and in Bleidorn et al.?s (2006a) mtDNA analyses, has not 
been recovered in ML amino acid tree and combined nuclear gene trees (Rousset et al., 
2006; Struck et al., 2007), which placed echiurans as sister to Capitellidae. The sister 
relationship between Siboglinidae and Clitellata in both nucleotide and amino acid trees 
agrees with mitochondrial data analyses (Jennings and Halanych, 2005), but contrasts 
with other molecular markers (Rousset et al. 2003, Struck et al., 2007). Comparing three 
trees in figure 3, the positions of Nereididae, Echiura, Sipuncula and Orbiniidae are quite 
different and with low nodal support indicating that their relationships are not fully 
resolved. Orbiniidae is placed at the base of the MrBayes amino acid tree (Fig 3B) 
disagreeing with suggestions to place Orbiniidae closer to Nereididae (Struck et al., 2007). 
In both nucleotide trees (Fig 3A) and ML amino acid tree (Fig 3C), the sipunculid 
Phascolopsis is close to orbiniids (88% of ML, 100% of Bayesian; 90% of amino acid 
ML), which is consistent with mitochondrial genomic data (Bleidorn et al., 2006a).   
The three terebelliform taxa cluster with Clymenella torquata (Maldanidae, 
Scolecida) (69% of nucleotide ML bootstrap,100% of posterior probability for both 
nucleotide and the non-partitioned amino acid tree, and 91% in the amino acid ML 
bootstrap), albeit given that a more comprehensive taxon sampling is necessary to 
delineate the sister group of Terebelliformia. Within Terebelliformia, a 
Trichobranchidae/Terebellidae clade is strongly supported by the mitochondrial genomic 
data as hypothesized based on morphology (Rouse and Fauchald, 1997). The unique 
presence of two methionine-tRNAs appears to be an additional synapomorphy. In 
 
46 
contrast, previous morphological and molecular analyses (Rousset et al., 2003; Glasby et 
al., 2004; Struck et al., 2007) place other taxa (e.g. alvinellids) between terebellids and 
trichobranchids. However, in general the taxon sampling of mitochondrial genomes is 
still limited, and more taxa, especially from Terebellidae (see Colgan et al., 2001), need 
to be sampled to confirm such results.  
Acknowledgements 
We are grateful to Les Goertzen and Scott Santos for their helpful comments on 
this manuscript. This work was supported by National Science Foundation (NSF) 
WormNet grant (EAR-0120646) to K. M. H., and in part, by the Alabama Commission on 
Higher Education Graduate Research Scholar's Program through the Auburn University 
Cellular and Molecular Biosciences Program and NSF EPS-0447675. Contribution #35 to 
the AU Marine Biology Program. 
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52 
Table 1. Taxonomically-inclusive PCR primers to amplify small conserved regions. 
Primer name? Sequence? Reference?
mSU? ? ?
12S-An-256F? 5??AW TY GTG CA GCW RC GC?3?? Reported here?
12S-An-800R? 5??TCW TGT TAC GAC TA YCT C?3?? Reported here?
mLSU? ? ?
16SarL? 5??CGC TG TT ATC AA AC AT?3?? Palumbi (196)?
16SbrH? 5??CG TC TGA CT CAG ATC ACG T?3?? Palumbi (196)?
cob? ? ?
Cytb 424F? 5??GW TAY GTW YTW CW TGR GW CAR AT?3?? Bore and Brown (200)?
Cytb 876R? 5??GCR TAW GCR AW AR AR TAY CAY TCW G?3?? Bore and Brown (200)?
cox1? ? ?
LCO1490? 5??GT CA CA ATC ATA AG ATA TG ?3?? Folmer et al. (194)?
HCO2198? 5??TA ACT TCA GG TGA CA A AT CA?3?? Folmer et al. (194)?
nad4? ? ?
Nad4f? 5? ?TGR GN TAT CAR CN GAR CG?3?? Jenings and Halanych (205)?
Nad4r? 5? ?GCY TCN ACR TGN GCY TN G?3?? Jenings and Halanych (205)?
nad5? ?  
Nad5-An-482F? 5??ACN AY CGW ATY GR GA?3?? Reported here?
Nad5-An-937R? 5??GCY TA AT ADH GCR TGD GT?3?? Reported here?
 
 
53 
Table 2. Primers for long PCR with annealing temperatures. 
Fragments? Primer name? Sequence? Anealing Temp.?
T. stroemi ? ?  
?  mLSU -cox1? Ter-16S-F? 5??TG GCT TGT ATG AC GA TA ACG AG C?3? 
5??AW TY GTG CA GCW RC GC?3??
52?
 Ter-CO1-R? 5?GC A  AG TA GA AT AGC AG TC?3? 
5??CGC TG TT ATC AA AC AT?3??
52?
  cox1-cob Ter-CO1-F? 5?TAT AG CGT G AT AT CC-3?? 52?
? Ter-Cytb-R? 5??CAG T TGA TAT GA TG TG TGA CTA TG?3?? 52?
  cob-mLSU? Ter-Cytb-F? 5??AT AT CT CT GA T AGT AGT ACA TC?3? 
5??CG TC TGA CT CAG ATC ACG T?3??
50?
? Ter-16S-R? 5?TTG GTTTAA GC G?3? 
5??TCW TGT TAC GAC TA YCT C?3??
50?
P. cristata? ?  
5??GCW TAY GTW YTW CW TGR GW CAR AT?3??
?
   mLSU-cox1? Pis-16S-F? 5?TGCTGCTAGTACGTGA TC?3? 
5??GCR TAW GCR AW AR AR TAY CAY TCW G?3??
52?
? Pis-CO1-R? 5?TGTCT TT CT CGT A T GC AC 3? 
5??TA ACT TCA GG TGA CA A AT CA?3??
52?
   cox1-cob? Pis-CO1-F? 5?GCTATCT C T GT TC GT G3? 
5??GT CA CA ATC ATA AG ATA TG ?3??
52?
? Pis-Cytb-R? 5?CAGTTTGC ACA CG?3? 
 
5? ?TGR GN TAT CAR CN GAR CG?3??
52?
   cob-nad4? Pis-Cytb-F? 5??AG AGT TAG TC AA TAC AGA CA AT CC?3?? 55?
? Nad4-Pc-290R? 5?A AG C T GTA TA AC AT AGC TGC?3?? 55?
  nad4-mLSU? Nad4-Pc-startF? 5??TCT GC TA CA AG CC ATG TCG AG C?3?? 50?
? Pis-16S-R? 5??TAG AT CAG TC TCT TCA CT GA GC ?3?? 50?
E. vaneli?  
Nad4r?
 
5? ?GCY TCN ACR TGN GCY TN G?3??
?
  mLSU -cox1? Ecl-16S-F? 5?CTG AT GTG CA G AGCT GAT AT TCG?3?? 52 
 Ecl-CO1-R? 5??CG TA CAT GA TG AC AA CA AA GC?3?? 52 
  cox1-cob Ecl-CO1-F? 5??TG TAT GA TAC AT TGT GAC AGC TCA TGC?3?? 52 
? Ecl-Cytb-R? 5??ATC AT TCT CTG AT CC TA CA CA CAG?3?? 52 
 cob-nad4? Ecl-Cytb-F? 5??ACA TCA AC TG GTC TAG TA TC AT TG?3?? 52 
? Nad4-Ev-startR? 5??CC AC TA CA AG CA AGA TGC ACT TGA?3?? 52 
 nad4-nad5? Nad4-Ev-startF? 5??TCA GT GCA TCT TG CT TG TA GT GG?3?? 52 
? Nad5-Ev-820R? 5??ATC AC CA GT TGA CTC AA GT GAT AA G?3?? 52 
 mSU-mLSU? 12S-An-256F? 5??AW TY GTG CA GCW RC GC?3?? Degenerate 45-60?
? 16SbrH? 5??CG TC TGA CT CAG ATC ACG T?3?? Degenerate 45-60?
 
 
54 
Table 3. Sequencing Primers for sequencing the mitochondrial genomes of Terebellides stroemi, 
Pista cristata and Eclysippe vanelli. 
Fragments Primer name Sequence 
T. stroemi   
 mLSU -cox1 Nad1-Ts-753F 5??TA CAT CT AGT AT AG C?3? 
5??AW TY GTG CA GCW RC GC?3? 
 Nad3-Ts-endR TG CG TCA   T C3? 
 Nad2-Ts132F 5??TCA TT ATC CT TA CTA GC?3? 
 Nad2-Ts786R 5??TA CTA TAG CAG AA TGA C?3? 
cox1-cob CO1-Ts150R 5??TAT AT GA GT CTA G G?3? 
 Cytb-Ts50R 5??ATG TAG AC AA GA ACG ?3? 
 COII-Ts653F 5??TAT ACG AC TAT GTC ACA C?3? 
 Cytb-Ts27R 5??AT GAT GAT T CAT AG TG?3? 
  cob-mLSU tRNArg-TsF 5??CG CTC AA CT CA GG TG ?3? 
5??CG TC TGA CT CAG ATC ACG T?3? 
 Nad5-Ts-startR ACAGAGAT TC
 12S-Ts-startF 5??TCA CAG CT ATG TAT GC CG?3? 
 12S-Ts-midR 5??AC GCG A GT ATG TAG C?3? 
P. cristata   
5??GCW TAY GTW YTW CW TGR GW CAR AT?3? 
   mLSU-cox1 16S-Pc40F A CCCGG AACA ?3? 
5??GCR TAW GCR AW AR AR TAY CAY TCW 
GG?3? 
 16S-Pc-270F ATAGAT GCA GT GTG AG?3?
 tRNA-Pc-befNad1R 5?AA CA TA TCT GTC AC C?3? 
 Nad3-Pc207F 5??GA AT GCT CTC CTA TA C?3? 
 Nad2-Pc31R 5??ATA TA CA GAT AGT AG ?3? 
 Nad2-Pc307F 5??CA CAG TA TAT CTG CTC?3? 
   cox1-cob COII-Pc407F 5??TT AGC TC AG CGT AC CG ?3? 
5??GT CA CA ATC ATA AG ATA TG ?3? 
 COII-Pc-654R CAGTG GTTG?3? 
 Nad6-Pc106F 5??CA CAG CAG AT TA TG G?3? 
 Cytb-Pc357R 5??CT CT AA CGT CA CTA T?3? 
   cob-nad5 Cytb-Pc-900F 5??TG CA TAT TG CTG CTA TC ?3? 
 Nad5-Pc-405R 5??TAC CTG CAC CA TGT AT TAG CG ?3? 
 Atp6-Pc-172F 5??TAT ACA TAG TCA GT ATC GCG?3? 
 Nad5-Pc-startR 5??AA TCT GA AC ACA CT CAG?3? 
 Nad5-Pc-startF 5??AT ACT GAG TG TG TT CAG?3? 
 
55 
Fragments Primer name Sequence 
 Atp6-Pc-690F 5??TCT ATG CAG ATG AC ATA CTC?3? 
 Atp6-Pc-5F 5??TCT AA TC TGA TGC TGA CTG?3? 
 UNK-Pc-endR 5??GT AA CC TAT A CA GT G?3? 
 Nad5-Pc-350R 5??CTG CAC CA GTG AT TAG CG?3? 
  nad5-nad4 Nad5-Pc-300R 5??ACA AG TAT AT ATC TG C ?3? 
 Nad5-Pc-1616F 5??CAG AA TA GAT CTG CTG AG ?3? 
 Nad4-Pc-900F 5??ATA TCA TA TGT GCT GCA C ?3? 
 Nad4L-Pc-405R 5??GAT ATA GT AGA TGT T CGT G?3? 
  nad4-mLSU Nad4-Pc-695F 5??ATA TAG CAG CTC CTC CT CC TC?3? 
 Nad4-Pc-1350F 5??TA CTG ACT AA CTA C CG ?3? 
 Nad4-Pc-990R 5??TA ACT CG GT ATG AGT G?3? 
 16S-Pc-96R 5??TA GT CT TA CAG TAC TA G?3? 
 16S-Pc-240R 5??GTG AA CAT AG ACG TG G?3? 
 12S-Pc-640R 5??ATC TCT CT TC TCA TAG C?3? 
 12S-Pc-180R 5??TA TCG AT CTA GT GTC C?3? 
 CystRNA?Pc-10R 5??AT TCA CT ATG AGA CG G?3? 
 Nad4-Pc-262R 5??TCG TA TA AC ATA GCT GC?3? 
E. vaneli  
Nad4r 
 
5? ?GCY TCN ACR TGN GCY TN G?3? 
 mLSU -cox1 1-Ev498F 5?ATA A CT A CT TA  C 3? 
 Nad1-Ev854F 5??GTC TT C TCG AT GCG?3? 
 Nad2-Ev486R 5??AGT CTG AT TAT CC AC?3? 
 Nad2-Ev938R 5??ACT AT GC TA CT GCT C?3? 
  cox1-cob COI-Ev31F 5??TCT GAT GT TGT GAT CT GC ?3? 
 COII-Ev40R 5??AC ATG AA TCA CGA TAC C ?3? 
 cob-nad5 Cytb-Ev-1042F 5??TA TGA CTG T AG ACA G ?3? 
 Nad5-Ev-200R 5??ACT ATA GAT GTC AC AC C?3? 
 Nad5-Ev-582R 5??GCT CT TT GT ATA GCT GC ?3? 
 Nad5-Ev-384F 5??GG TG AGA TG TT AG TT AC?3? 
 Nad4-Ev-1300R 5??TAT CA CT ATA CAG CA TA AC?3? 
 Atp6-Ev-350F 5??TG T TA CTA TT GG CGA G?3? 
 tRNA-Ev-33R 5??AA TAC CG TC AC CG C?3? 
 Atp6-Ev-16F 5??GT T GAG TG TC CGA G?3? 
 
56 
Fragments Primer name Sequence 
 tRNA-Ev-30F 5??AC AT GCG CG GT GA CG?3? 
 Nad4-Ev-947R 5??TAC TAT A AC TA AGC C?3? 
 Nad4-Ev-942F 5??TAG T TA TAG TAG CC ACG ?3? 
 Nad4L-Ev-132F 5??AC CAG T AGT AC CT GCG?3? 
 Nad4-Ev-415R 5??ATA A CT AGC CTG CA CG?3? 
 Nad4-Ev-1049R 5??CAC CA AT CTC ATA CAC G?3? 
 mMSU-mLSU 12S-Ecl-midF 5??GT TG TC TG TA TG ?3? 
 16S-Ev-mid3R 5??GCG CTA CA TA GA G C?3? 
 16S-Ecl-midR 5??AT AGA GAC AGC ATA C ?3? 
 
 
57 
Table 4. Taxa used in phylogenetic analysis. 
Species? Clade? Nucleotides? GenBank Number?
Terebelides stroemi? Annelida, ?Canalipalpata?, Trichobranchidae? 15,75 complete? EU236701?
Pista cristata? Anelida, ?Canalipalpata?, Terebelidae? 15,894 complete? EU23968 ?
Eclysipe vaneli? Anelida, ?Canalipalpata?, Ampharetidae? 13,749 partial? EU239687?
Clymenela torquata? Anelida, ?Scolecida?, Maldanidae? 15,538 complete? AY74161?
Riftia pachyptila? Anelida, ?Canalipalpata?, Siboglinidae? 12,016 partial? AY74162?
Galathealinum brachiosum? Anelida, ?Canalipalpata?, Siboglinidae? 7,576 partial? AF178679?
Platynereis dumerili? Anelida, ?Aciculata?, Nereididae? 15,619 complete? NC_00931?
Lumbricus terestris? Anelida, ?Oligochaeta?, Lumbricidae? 14,98 complete? NC_01673?
Helobdela robusta? Anelida, Hirudinea, Glosiphonidae? 7,53 partial? AF178680?
Orbinia latreili? Anelida, ?Scolecida?, Orbinidae? 15,58 complete? AY961084       ?
Scoloplos cf. armiger? Anelida, ?Scolecida?, Orbinidae? 12,042 partial? DQ517436?
Phascolopsis gouldi? Anelida, Sipuncula? 7,470 partial? AF37437?
Urechis caupo? Anelida, Echiura? 15,13 complete? AY619711?
Katharina tunicata? Molusca, Polyplacophora 15,532 complete NC_01636 
Terebratalia transversa Brachiopoda, Articulata 14,291 complete NC_03086 
 
 
58 
Table 5. Base composition and skewness measures. 
 T. stroemi P. cristata E. vaneli 
 Whole 
genome 
Protein-coding 
genes 
3
rd
 position Whole 
genome 
Protein-coding 
genes 
3
rd
 position Whole 
sequences 
Protein-coding 
genes 
3
rd
 position 
A 31.0% 29.5% 40.4% 29.6% 28.0% 37.6% 27.2% 24.8% 29.8% 
T 36.1% 37.3% 38.0% 38.5% 39.3% 4.1% 41.9% 43.7% 50.0% 
G 12.8% 12.2% 4.5% 12.2% 1.6% 3.1% 19.3% 19.5% 15.9% 
C 20.1% 21.0% 17.1% 19.7% 21.0% 15.2% 1.6% 12% 4.4% 
A+T 67.1% 6.8% 78.4% 68.1% 67.3% 81.7% 69.1% 68.2% 79.8% 
AT-skew - 0.075 - 0.18 0.03 - 0.13 - 0.168 - 0.079 - 0.213 - 0.27 - 0.253 
GC-skew - 0.21 - 0.26 - 0.585 - 0.235 - 0.28 - 0.62 0.249 0.238 0.567 
 
 
59 
Table 6. Relative synonymous codon usages (RSCU) in the 13 protein-coding genes in T. 
stroemi, P. cristata and E. vanelli.  
AA Codon T. stroemi P. cristata E. vaneli  AA Codon T. stroemi P. cristata E. vaneli 
Ala GCA 82 1.276 104 1.541 57 1.163  Lys AAA 93 1.86 76 1.949 59 1.457 
 GC 57 0.87 52 0.7 4 0.082   AAG 7 0.14 2 0.051 22 0.543 
 GCG 3 0.047 6 0.089 19 0.38  Met AUA 194 1.709 151 1.787 184 1.579 
 GCU 115 1.79 108 1.6 116 2.367   AUG 33 0.291 18 0.213 49 0.421 
Arg CGA 41 2.563 42 2.625 22 1.22  Phe UUC 91 0.565 51 0.289 10 0.054 
 CGC 9 0.563 3 0.18 2 0.11   UUU 231 1.435 302 1.71 361 1.946 
 CG 3 0.18 3 0.18 17 0.94  Pro CCA 84 1.768 67 1.396 35 0.979 
 CGU 11 0.68 16 1 31 1.72   CCC 13 0.274 32 0.67 1 0.028 
Asn AAC 48 0.756 52 0.689 24 0.39   CCG 8 0.168 2 0.042 18 0.503 
 AAU 79 1.24 99 1.31 99 1.61   CCU 85 1.789 91 1.896 89 2.49 
Asp GAC 30 0.82 21 0.627 13 0.371  Ser AGA 39 0.782 49 1.071 78 1.651 
 GAU 38 1.18 46 1.373 57 1.629   AGC 19 0.381 10 0.219 6 0.127 
Cys UGC 14 1 10 0.5 10 0.328   AGG 9 0.18 2 0.04 45 0.952 
 UGU 14 1 30 1.5 51 1.672   AGU 18 0.361 17 0.372 47 0.95 
Gln CA 64 1.753 66 1.86 37 1.194   UCA 122 2.46 118 2.579 59 1.249 
 CAG 9 0.247 4 0.14 25 0.806   UC 44 0.82 33 0.721 6 0.127 
Glu GAA 59 1.71 65 1.857 35 0.875   UCG 3 0.06 2 0.04 14 0.296 
 GAG 10 0.29 5 0.143 45 1.125   UCU 145 2.907 135 2.951 123 2.603 
Gly GGA 83 1.747 97 2.132 59 0.904  Ter(.) UA/U 13 2 13 2 10 1.538 
 GGC 30 0.632 28 0.615 18 0.276   UAG 0 0 0 0 3 0.462 
 GGG 32 0.674 20 0.439 90 1.379  Thr ACA 91 1.562 98 1.587 49 1.41 
 GGU 45 0.947 37 0.813 94 1.4   AC 38 0.652 59 0.95 8 0.235 
His CAC 38 0.835 25 0.568 11 0.268   ACG 5 0.086 3 0.049 12 0.353 
 CAU 53 1.165 63 1.432 71 1.731   ACU 99 1.69 87 1.409 67 1.971 
Ile AUC 106 0.607 78 0.49 13 0.09  Trp UGA 92 1.804 80 1.616 41 0.812 
 AUU 243 1.393 269 1.5 250 1.901   UGG 10 0.196 19 0.384 60 1.18 
Leu CUA 147 1.586 114 1.136 30 0.35  Tyr UAC 55 0.873 36 0.61 21 0.28 
 CUC 23 0.248 60 0.598 2 0.023   UAU 71 1.127 82 1.39 125 1.712 
 CUG 12 0.129 3 0.03 10 0.17  Val GUA 66 1.83 42 1.292 75 0.92 
 CU 122 1.316 193 1.923 75 0.875   GUC 22 0.61 15 0.462 14 0.172 
 UUA 236 2.547 216 2.153 285 3.327   GUG 7 0.194 9 0.27 54 0.63 
 UUG 16 0.173 16 0.159 112 1.307   GUU 49 1.361 64 1.969 183 2.245 
2fold NNA 10.4 1.767 87.6 1.819 71.2 1.183  4fold NNA 74.5 1.792 75.0 1.762 49.5 1.105 
 NNG 13.8 0.23 9.6 0.181 40.2 0.817   NNC 28.2 0.603 31.5 0.610 7.8 0.151 
 NNC 54.6 0.78 39.0 0.53 14.6 0.257   NNG 9.7 0.26 7.2 0.181 35.0 0.705 
 NNU 104.1 1.212 127.3 1.467 14.9 1.743   NNU 67.3 1.379 67.2 1.48 96.7 2.039 
A, amino acid; Ter(.), Terminator codons 
 
60 
Figure 1. Gene orders of mitochondrial genomes in Annelida. Different colors shows 
conserved gene clusters. Dots indicate missing regions. 
 
61 
 
A. 
 
62 
 
B. 
 
63 
 
C. 
Figure 2. Putative secondary structures of tRNA genes in 3 Terebelliformia worms. (A) 
23 tRNA genes in T. stroemi. (B) 23 tRNA genes in P. cristata. (C) 20 recovered tRNA 
genes in E. vanelli. 
 
64
 
Figure 3. Phylogenetic reconstructions. (A) The single combined tree represents the identical topology from both ML and 
Bayesian inference methods (non-partitioned and partitioned) with GTR+?+I model. Nodal support values are given at branches 
with ML bootstrap values first and posterior probabilities of the partitioned Bayesian analysis second (non-partition values not 
shown). A dash indicates < 50% on trees. (B) Non-partitioned Bayesian analyses of amino acid dataset with the mixed amino acid 
substitution model. Posterior probabilities are shown at the nodes. (C) ML analyses of amino acid dataset using RAxML by 200 
bootstrap replicates. Bootstrap values are shown at the nodes. Black bars indicate trnM gene duplication event. Terebratalia 
transversa (brachiopod) and Katharina tunicata (mollusk) were used as outgroups. Details of analyses are given in the text.  
 
65 
 
Figure 4. Partitioned Bayesian analyses of amino acid dataset with the mixed amino acid substitution 
model with partitions unlinked during the run. Posterior probabilities are shown at the nodes. 
 
  66
CHAPTER 3  
PHYLOGENETIC INFERENCE OF TEREBELLIFORMIA WORMS BASED ON 
MITOCHONDRIAL GENOMIC DATA 
 
  67
Abstract 
Terebelliformia worms are mainly tube-dwelling annelids comprising of five 
?families?, Alvinellidae, Ampharetidae, Terebellidae, Trichobranchidae and Pectinariidae. 
Even though Terebelliformia is one of the few, more-inclusive clades of Annelida well-
defined by morphology, relationships among terebelliform lineages are not resolved. 
Here we addressed phylogenetic relationships among five Terebelliformia families using 
mitochondrial genomic datasets. Monophyly of Terebelliformia was strongly supported. 
Both nucleotide and amino acid datasets supported a sister relationship between 
Ampharetidae and Alvinellidae and the basal placement of Pectinariidae. 
Trichobranchidae and Terebellidae were sisters to each other with high nodal values. 
Furthermore, we mapped mitochondrial gene order characters (trnM duplication and gene 
order of nad5-nad4L-nad4 cluster) on the topology to understand mtDNA genome 
evolution. trnM duplication was presumed to be a primitive trait of terebelliforms. 
Ampharetidae and Alvinellidae lineages have secondarily lost the duplication event. 
Based on the mapping of the nad5-nad4L-nad4 gene order, ampharetids were indicated to 
be a more divergent clade.  
  68
1. Introduction 
Terebelliformia worms are mainly tube-dwelling annelids, found in diverse 
marine habitats, including intertidal, deep-sea and even hydrothermal vents. Terebellidae 
is a species-rich family containing over 400 described species (Hutchings, 2000), living 
in marine environments worldwide. Terebelliformia worms comprise of five ?families?, 
Alvinellidae, Ampharetidae, Terebellidae, Trichobranchidae and Pectinariidae (Hessle, 
1917; Holthe, 1986; Rouse and Pleijel, 2001).  
These annelid clades have a long and intertwined history. Terebellidae was 
erected as a family in 1850, although the first terebellid worm, Terebella lapidaria, was 
described in 1776 (M?ller, 1776; Grube, 1850). Trichobranchidae, only containing a few 
genera (Octobranchus, Terebellides, Trichobranchus and Artacamella), was originally 
treated as a subfamily Trichobranchinae within Terebellidae (Malmgren, 1866) and 
suggested to be family rank by Hessle in 1917. Ampharetidae, which typically live in 
fragile tubes as deposit feeders, is another species-rich family from relative diverse 
habitats. Many ampharetids have been found in deep sea with some taxa occurred in 
hydrothermal vent areas and fresh water (Solis-Weiss, 1993; Desbruy?res and Laubier, 
1991; Holthe, 1986). Ampharetidae was referred to as a family in 1866 by Malmgren 
(1866). Pectinariidae, first recognized as a separate taxon by Quatrefages in 1865, was 
once named as Amphictenidae and recurred in a ruling of the International Commission 
on Zoological Nomenclature in 1982 (Rouse and Pleijel, 2001). Pectinariids can be 
  69
generally found in muddy or sandy shallow waters with filter/suspension feeding during 
burrowing and digging activity (Watson, 1928). Alvinellidae was originally erected based 
on the description of the ?Pompeii worm?, Alvinella pompejana, Desbruy?res and 
Laubier 1980.  Alvinellids were originally placed as a subfamily within Ampharetidae, 
and only later described as a separate family (Desbruy?res and Laubier 1986).  
Phylogenetic relationship among these five families is ambiguous and 
consistently debated by recent researchers (Rouse and Fauchald, 1997; Colgan et al., 
2001; Rousset et al., 2003; Glasby et al., 2004; Rousset et al., 2007; Struck et al., 2007; 
Zhong et al., 2008). For example, Trichobranchidae was originally treated as a subfamily, 
Trichobranchinae, within Terebellidae (Malmgren, 1866), but later elevated to family 
rank (Hessle, 1917) because two genera of Trichobranchidae (Trichobranchus and 
Terebellides) were thought not to be closely related. Trichobranchus was placed close to 
Ampharetidae based on similar branchiae, and Terebellides was placed close to 
Terebellidae based on the digestive system. Placement of Trichobranchidae has been 
debated by subsequent authors (Day, 1967; Fauchald, 1977; McHugh, 1995; Fauchald 
and Rouse, 1997; Rouse and Fauchald, 1997; Rouse and Pleijel, 2001; Colgan et al., 
2001). Rouse and Fauchald (1997) referred a close affinity between Terebellidae and 
Trichobranchiae and, based on morphological characters, placed this group as sister to an 
Alvinellidae/Ampharetidae/Pectinariidae clade. In contrast, combined morphological and 
molecular data suggest that Trichobranchidae is sister to Alvinellidae and not 
Terebellidae (Rousset et al., 2003). Although the close relationship between alvinellids 
and ampharetids has been suspected based on morphology (Rouse and Fauchald, 1997; 
Glasby et al., 2004), it has not been supported by molecular data (e.g., Rousset et al., 
  70
2003; Struck et al., 2007). In contrast, some have assumed Ampharetidae as closely 
related to Terebellidae and Trichobranchidae (Hessle, 1917; Fauchald and Rouse, 1997). 
However, Pectinariidae, together with Terebellidae and Ampharetidae, was proposed to 
be Terebellida or Terebellimorpha (Fauchald and Rouse, 1997). Recent morphological 
analyses indicated that Pectinariidae as either sister to Ampharetidae and Alvinellidae 
clade (Rouse and Fauchald, 1997), or related to Terebellidae (Glasby, et al., 2004). 
Nonetheless, some molecular studies and combined data indicated contradictory views 
for terebelliform relationships. Based on the five combined genes, Trichobranchus was 
suggested to be associated with one subfamily of Terebellidae making Trichobranchidae 
paraphyletic (Colgan et al., 2001). Whereas a sister relationship between 
Trichobranchidae and Alvinellidae was suggested based on combined molecular and 
morphological data (Rousset et al., 2003). Furthermore, using complete mitochondrial 
genomes, the terebellid Pista cristata and the trichobranchid Terebellides stroemi were 
recovered together (Zhong et al., 2008). This study also reported additional copy of the 
methionine tRNA in these taxa, and such duplications are not common bilaterian 
mitochondrial genomes. Elucidating the affinity of Pectinariidae has been particularly 
problematic has it have been recovered as sister to a Trichobranchidae,/Alvinellidae clade 
(Rousset et al., 2003), within Ampharetidae (Colgan et al., 2001), basal to all other 
terebelliform lineages (Struck et al., 2007), or even other annelids outside of 
Terebelliformia (Rousset et al., 2007). 
As more and more bilaterian mitochondrial genomes are sequenced, they become 
useful for phylogenetic reconstructions of major groups. Mitochondrial genomes are 
generally 15-17kb in size and contain conserved homologous genes across bilaterian 
  71
animals (Boore, 1999; Vall?s and Boore, 2006). Apart from highly variable non-coding 
UNK region (unknown region), typical bilaterian mitochondrial genomes are comprised 
of 37 genes with13 protein-coding, two ribosomal and 22 tRNAs. The gene arrangement 
of mitochondrial genomes within annelids is presumably conserved with some exceptions 
(Jennings and Halanych, 2005; Vall?s and Boore, 2006; Zhong et al., 2008). 
To elucidating the ambiguous annelid phylogeny so as to provide a powerful 
framework to further studies, the goal of the present study is to further examine 
relationships of Terebelliformia by examining a mitochondrial genome data. Partial 
mitochondrial genomes of three Terebelliformia worms (Auchenoplax crinita ? 
Ampharetidae, Paralvinella sulfincola ? Alvinellidae and Pectinaria gouldii -- 
Pectinaridae) are reported here. Both nucleotide and amino acid datasets were established 
to reconstruct the evolutionary history within Terebelliformia. 
2. Materials and Methods 
2.1 Sample collection and DNA extraction 
Auchenoplax crinita (Ampharetidae) was collected south of Cap Code, 
Massachusetts, USA, Pectinaria gouldii (Pectinaridae) was obtained in Egypt Lane, 
Fairhaven, Massachusetts, USA, and Paralvinella sulfincola (Alvinellidae) was collected 
in Juan de Fuca Ridge system on the Visions 05 cruise in Oct. 2005 (and kindly provided 
by Dr. Peter Girguis from Harvard University). Each organism is a representative of 
every above family. All organisms were stored at -80?C after collection. Total genomic 
DNA extractions employed the DNeasy? Tissue Kit (Qiagen) according to the 
manufacture?s instructions. 
  72
2.2 mtDNA data collection 
Gene nomenclature and abbreviations in this paper follow Jennings and Halanych 
(2005). 
Auchenoplax crinita and Paralvinella sulfincola 
The genomes were amplified in four overlapping segments. Conserved regions of 
mLSU, cox1, cob and nad5 genes were amplified using taxonomically-inclusive primers 
(Zhong et al., 2008) and purified by QIAquick PCR purification kit (Qiagen). PCR 
products were sequenced on a CEQ8000 (Beckmann) and four pairs of species-specific 
primers for long PCRs were designed (Table 1). HotStart long PCRs were performed on 
Eppendorf Mastercycler (Eppendorf) using Takara LA- Taq? (Takara) by following 
protocol: 94 ?C for 3min; then addition of polymerase followed by 35 cycles with 94?C 
for 30 sec, 52?C for 30 sec, and 70?C for 8 min; final extension at 72?C for 10 min and 
hold at 6?C. 50 ?l long PCR reactions using Takara LA-Taq were set up as follows: 5?l 
10?buffer, 8?l dNTP (2mM), 5?l MgCl
2
 (25mM), 2?l of each long PCR specific primers 
(10?M each), 0.5?l Takara LA-Taq (5U/?l), 2?l DNA template and 25.5?l sterilized 
distilled water. Both mLSU-cox1 and cox1-cob regions were about 4 kb in size. Both cob-
nad5 fraction of A. crinita and nad5- mLSU of P. sulfincola were obtained about 6-7 kb 
in size. The unobtained nad5-mLSU of A. crinita and cob-nad5 of P. sulfincola 
containing the UNK region, were difficult to amplify despite many tries (see Boore and 
Brown, 2000; Jennings and Halanych 2005).  
All long fragments were purified with QiaQuick Gel Extraction Kit (Qiagen) and 
sequenced directly or cloned into the pGEM-T Easy vector (Promega). Clones were 
  73
verified by PCR and plasmids were isolated using the QIAprep
?
 Spin Miniprep Kit 
(Qiagen). Purified plasmids were digested by EcoRI to check the insert size and 
sequenced by primer walking. 
Pectinaria gouldii 
The genome of P. gouldii was amplified in six segments. Conserved fragments of 
mLSU, cox1, nad5 and nad4 genes were amplified by taxonomically inclusive primers 
(Zhong et al., 2008) and sequenced. Two new primers were designed based on cox3 
conserved region (see Table 1). Specific long-PCR primers (Table 1) were then designed 
to amplify long fragments: mLSU-cox1, cox1-cox3, nad5-nad4 and nad4-mLSU. The 
universal cob reverse primer ?Cytb 876R? was used to pair with cox3 forward one to 
amplify cox3-cob fragment. After sequence it, a specific cob forward long-PCR primer 
was designed to pair with nad5 reverse primer. Long PCRs employed Takara LA-Taq as 
described above. The protocols of long PCR and purification were similar with some 
modifications of annealing temperatures based on different pairs of primers (Table 1). All 
long fragments were sequenced directly by primers walking. The unobtained cob-nad5 
fragment was hard to obtain presumably due to the inclusion of the UNK region. 
Information for all sequencing primers can be found in the table 2. 
2.3 Genomic Assembly 
Sequences were edited and aligned using DNASTAR? Lasergene programs 
SeqMan and MegAlign (Burland, 2000). Protein-coding genes and ribosomal RNA genes 
were identified by BLAST (Altschul et al., 1990). tRNA genes were identified using 
tRNAscan-SE web server (http://lowelab.ucsc.edu/tRNAscan-SE/; Lowe and Eddy, 1997) 
  74
under default settings and source = ?mito/chloroplast?, or by hand based on their 
potential secondary structures and anticodon sequences.  
2.4 Phylogenetic analyses 
Seventeen available annelid mitochondrial genomes with 50% coverage or greater 
were used for phylogenetic analyses. The alignment of Zhong et al. (2008) was employed 
with the additions of Nephtys sp. ?San Juan Island?, Pectinaria gouldii, Paravinella  
sulfincola and Auchenoplax crinita (Table 3).  Because we are interested in the 
relationships within Terebelliformia, we deleted the mitochondrial data of Katharina 
(Mollusca) and Terebratalia (Branchiopoda) from the Zhong et al. data set and used all 
other annelids as outgroups.  
Phylogenetic analyses were based on nucleotide and amino acid datasets. The 
nucleotide dataset included all protein-coding genes (except for atp6, atp8 and nad6 
genes which exhibit high variability) and the two rRNA genes (mLSU and mSSU). Clustal 
X (Thompson et al., 1997) under default setting was used to realign rRNA genes. 
MacClade4.08 (Maddison and Maddison, 2002) was used to exclude the most regions 
that contain insertions/deletions and all third codon positions in protein coding genes.  
Gblocks 0.91b (Castresana, 2000) was used to identify ambiguous aligned regions in 
rRNA genes that were excluded from analyses. Using MacClade4.08 (Maddison and 
Maddison, 2002) and Se-Al v2.0a11 (Rambaut, 1996), the amino acid dataset was created 
from the aligned nucleotide dataset translated with the Drosophilia mitochondrial code, 
and with rRNA genes excluded. 
  75
Both maximum likelihood and Bayesian-inference approaches were employed on 
all datasets. For the nucleotide dataset, Maximum-likelihood analyses were performed in 
PAUP4.0b10 (Swofford et al., 2002) with a GTR+?+I model as determined by 
MODELTEST v3.7 based on the Akaike information criterion (AIC) (Posada and 
Crandall, 1998). Heuristic searches were run with random-taxon addition (10 replicates) 
using Tree-Bisection-Reconnection (TBR) swapping. All model parameters used fixed 
values as determined by MODELTEST v3.7. Bootstrap analysis employed 1,000 
iterations using heuristic searches with 10 random taxa addition. Partitioned Bayesian 
inference analyses in MRBAYES version 3.1.2 (Huelsenbeck and Ronquist, 2001) used 
5,000,000 generations with 2 runs of chains (3 heated and 1 cold), and sampling every 
100 generations. Unlinked GTR+?+I models were selected under the AIC in 
MrModeltest (Nylander, 2004) for which parameters were separately estimated for each 
gene partition with the exception of GTR+I models for both 12S and 16S genes; GTR+? 
model for cox3 gene and HKY+? model for nad2, nad4L and nad5 genes.  Resulting -ln 
likelihood scores were graphed using X-Y scatter plots to identify the ?burn-in? point at 
which all estimated parameters reached stationarity (burnin = 10,000). For the nucleotide 
dataset of the combined matrix, similar ML and partitioned Bayesian analyses were 
performed in PAUP and MrBayes separately after model-selections. 
For the amino acid dataset, a non-partitioned ML analyses was run in addition to 
partitioned Bayesian analyses. For ML analyses, model selection was performed in 
ProtTest (Abascal et al., 2005) and MtArt +?+F model was chosen as the best one under 
the AIC. As there is no MtArt model used in RAxML, we chose the next best model, 
MtREV+?+F, available in RAxML. A maximum likelihood search was implemented by 
  76
200 bootstrap replicates using RAxML web-server (http://phylobench.vital-it.ch/raxml-
bb/. Stamatakis, 2006) with MtREV+?+F model. In partitioned Bayesian analysis, the 
mixed amino acid substitution model option plus a ? distribution and a proportion of 
invariant sites was assigned to each partition individually and unlinked in MRBAYES 
v3.1.2 with 2,000,000 generations sampled every 500 generations (burnin = 10,000). In 
the mixed model option, a specific model is not specified a priori, but each model is 
chosen during the runs based on its posterior probability. 
3. Results 
3.1 Mitochondrial genomes and gene order 
The three genomes recovered generally conform to the conserved annelid mtDNA 
gene order (Jennings and Halanych, 1995), but for all recover the UNK region proved 
difficult and can?t be discovered here. The partial mtDNA of Aucheoplax crinita is 
13,759 bp in length, of Paralvinella sulfincola is 13,640 bp and of Pectinaria gouldii is 
13,438 bp. A. crinita contains 34 recovered genes including 13 protein-coding genes, two 
rRNA genes and 19 tRNAs. There are 33 genes found in mtDNA of P. sulfincola with 12 
protein-coding genes, two rRNA genes and 19 tRNAs, 34 genes in the one of P. gouldii 
with 12 protein-coding genes, two rRNA genes and 20 tRNAs. Interestingly, the partial 
genome of P. gouldii possesses the identical gene order as both the trichobranchid T. 
stroemi and the terebellid P. cristata, including adjacent duplicate methionine tRNA gene 
(see Zhong et al., 2008). Fig. 1 shows gene orders of all six available terebelliform taxa. 
All mitochondrial genes are transcribed from the same strand, similar to other annelids 
(Boore and Brown, 2000; Boore and Staton, 2002; Jennings and Halanych, 2005; 
  77
Bleidorn et al., 2006a, 2006b; Zhong et al., 2008). Gene order of A. crinita is identical to 
another published ampharetid, E. vanelli, (Zhong et al., 2008) except for the trnF 
between nad1 and nad3 genes in E. vanelli. 
3.2 Phylogenetic analyses 
The mitochondrial nucleotide dataset comprised 17 taxa with 6287 unambiguous 
characters. Both maximum likelihood and partitioned Bayesian analyses inferred an 
identical topology (Fig. 2A). The amino acid dataset from 10 mitochondrial protein-
coding genes (with the exception of atp6, atp8 and nad6 genes) consisted 17 taxa with 
3149 unambiguous characters. Maximum likelihood (RAxML) and Bayesian inference of 
animo acid data resulted in the same topology (Fig. 2B), which was identical to the 
nucleotide topology within Terebelliformia (including strong nodal support), but differed 
in outgroup relationships. Monophyly of Terebelliformia is also well supported by both 
datasets (BS: 100 for DNA dataset /97 for AA-dataset; PP: 1.00 for both). The sister 
relationship between Trichobranchidae and Terebellidae was strongly suggested by 
mitochondrial datasets (BS: 95 for DNA/85 for AA; PP: 1.00 for both). Two 
Ampharetidae taxa were close to Alvinellidae with highest values from both analyses for 
both datasets (BS: 100; PP: 1.00). The mitochondrial datasets also showed that the 
Trichobranchidae/Terebellidae clade was sister to Ampharetidae/Ampharetidae. However, 
it didn?t have a good nodal support value by the ML analysis for DNA dataset (BS: 69). 
Pectinariidae was shown to be a basal clade in Terebelliformia (BS: 100 for DNA/97 for 
AA; PP: 1.00 for both). Outgroup topologies differed in the placement of Urechis caupo 
  78
(Echiura), Platynereis dumerilii (Nereididae) and Nephtys sp. (Nephtyidae), suggesting it 
still need more informative datasets to make clear their relationships. 
4. Discussion 
4.1 Phylogenetic relationship within Terebelliformia 
Monophyly of Terebelliformia was recovered in both topologies, agreeing with 
some morphological and molecular studies (Rouse and Fauchald, 1997; Colgan et al., 
2001; Rousset et al., 2004; Rousset et al., 2007). Furthermore, Zhong et al. (2008) 
hypothesis that Clymenella torquata might be a sister group to Terebelliformia is 
supported herein by both mitochondrial datasets (Fig. 2).  
In our analyses, Pectinariidae was placed as the most basal Terebelliformia 
lineage in both nucleotide and amino acid topologies with strong nodal supports (BS: 100 
for both mtDNA and AA; PP: 1.00 for mtDNA/97 for AA). This placement is congruent 
with previous molecular study (Struck et al., 2007) of annelid phylogeny which showed 
Pectinariidae basal. Both trees provided strong support for the close affinity between 
Ampharetidae and Alvinellidae, which contradicted views proposing Paralvinella 
(Alvinellidae) as close to Terebellidae (Colgan et al., 2001; Rousset et al., 2007), or to 
Trichobranchidae (Rousset et al., 2003). However, this relationship was congruent with 
the previous morphological studies which described the similar features, such as buccal 
tentacles attached to a dorsal curtain and retractable into the mouth, hood-like upper lip 
regions and so on (Rouse and Fauchald, 1997; Glasby et al., 2004).  
A sister relationship between Trichobranchidae and Terebellidae was strongly 
supported by both datasets (Fig. 2) and the identical mitochondrial gene order (Zhong et 
  79
al., 2008). This was in agreement with the family-based morphological cladistic 
analyses (Rouse and Fauchald, 1997). In contrast, other morphological and molecular 
analyses of Terebelliformia did not find a closer relationship of Terebellidae and 
Trichobranchidae (Rousset et al., 2003; Galsby et al., 2004; Struck et al., 2007). 
Additionally, all datasets used here haven?t included the genus Trichobranchus, 
which was speculated to be distant to Terebellides used in our analyses (Hessle, 1917; 
Colgan et al., 2001). We would consequently suggest the further investigations with 
larger sampling are still in need, especially the coverage of Trichonbranchus genus.  
4.2 trnM duplication event and gene order mapping 
Character mapping on the phylogenetic tree is essential to understand the 
evolutionary history of some traits (Felsenstein, 1985). Parsimony is the most 
universal method used to map characters implemented in some programs, such as 
MacClade and Mesquite (Maddison and Maddison, 2002; 2004). Two adjacent trnM 
genes were discovered in pectinariid P. gouldii, as well as terebellid and 
trichobranchid worms (Zhong et al., 2008), but not in the alvinellid and ampharetids. 
The unique duplication event was speculated based on their similar secondary 
structure, identical anticodons and the same sequences in stems. Their functions are 
still under explorations. To examine the evolutionary history of trnM duplication trait, 
we mapped it on the Terebelliformia tree by hand as well as the gene order of nad5-
nad4L-nad4 cluster characters (Fig. 3). As Pectinariidae was highly supported as a 
basal clade of Terebelliformia, trnM duplication was noted to be a symplesiomorphy 
of terebelliforms instead of synapomorphy for Trichobranchidae and Terebellidae 
  80
(Zhong et al., 2008). Both Ampharetidae and Alvinellidae have secondarily lost the 
duplication event and one trnM. In term of the nad5-nad4L-nad4 gene cluster, both 
ampharetids have different gene arrangement from all other published annelids 
(except for the echiurid Urechis caupo) (Fig. 1). Their nad5 were placed to 3? end of 
nad4L and nad4 genes with trnF-trnE-trnP-trnT genes translocated.  Comparing with 
Alvinellid Paralvinella sulfincola that only has variable tRNA gene order with the 
invariable protein-coding gene order, ampharetids have more evolutionarily divergent. 
The well-resolved phylogenetic trees of terebelliforms in our study sill 
provide some insight into the potential capability of mtDNA for annelid phylogenetic 
reconstruction. However, the combined datasets including mitochondrial genomes 
and nuclear genes are still highly suggested for continued research investigations as 
well as the large sampling size for each family.  
Conclusions 
Our data addressed well-resolved phylogenetic relationships within 
Terebelliformia worms based on mitochondrial genome data.  (1) Pectinariidae was 
placed as a basal clade to all other Terebelliformia families. (2) Ampharetidae and 
Alvinellidae were sister to each other. (3) Trichobranchidae and Terebellidae were 
sister clade with strong support by both phylogenetic analyses and mitochondrial 
gene order, but require further attention with large samplings. (4) trnM duplication 
event was inferred to be a symplesiomorphy of terebelliforms. Both Ampharetidae 
and Alvinellidae have secondarily lost the duplication. 
  81
Acknowledgements 
We are grateful to Dr Peter Girguis (Harvard Univeristy) for kindly providing 
Paralvinella sulfincola samples. This work was support by the USA National Science 
Foundation (NSF) WormNet grant (EAR-0120646) to K.M.H. and by the Alabama 
Commission on Higher Education Graduate Research Scholar's Program through the 
Auburn University Cellular and Molecular Biosciences Program and NSF EPS-
0447675.  
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TABLE 1: Primers used in long-run PCR amplifications. 
Fragments Primer name Sequence Annealing Temp. 
A. crinita   
 
mLSU -cox1 16S-Ac-longF 5??GCG GTA TCC TGA CTG TGC TAA GGT AGC GTG?3? 53 
 CO1-Ac-longR 5??AGA ATG AGC AAT ATT ACT AGA TAA GGG CGG?3? 53 
cox1-cob CO1-Ac-longF 5??TTA ATT CGT GTT GAG CTT GGA CAG CCA GGC-3? 53 
 Cytb-Ac-longR 5??AGA GGG GTT ACT AGT GGA TTT GCT AAT AGC C?3? 53 
cob-nad5 Cytb-Ac-longF 5??ATT TTC TTG TGC CTT TTA TTA TGG TAG CAC?3? 54 
 Nad5-Ac-789R 5??ATC GCA CTC TAC CAA AGC TGA AAA CGC AGC?3? 54 
nad5-mLSU Nad5-Ac-645F 5??CGC TAG TTC ATT CGT CTA CAC TTG TAA CAG C?3? -- 
 16S-Ac-longR 5??TGT CCC ACA CTT ACA TTC AGG TAT TTT CAC C?3? -- 
P. sulfincola    
mLSU-cox1 16S-PS-longF 5??GTT CTA ACT GCA TAT CAA GGC AAA ACC AGC C?3? 58 
 CO1-PS-longR 5??GCC TGC GTG TGC CAT GTT TCC TGC TAG TGG?3? 58 
cox1-cob CO1-PS-longF1 5??AAT CTA CCC ACC ACT AGC AGG AAA CAT GGC?3? 55 
 cob-PS-longR 
5??AAT TGA TCA GTT TTC TGG TTC TCC CAG GGC?3? 
55 
cob-nad5 cob-PS-longF 5??ACA ACC CTC TTG GTA TTA ACT CAG ACT CCG?3? -- 
 Nad5-PS-longR 5??AGT GTG GAT GAG TGG ACT AGT GCA GAG ACG?3? -- 
nad5-mLSU Nad5-PS-longF 5??GAC TTC CAG CAG CAA TGG CAG CAC CTA CGC?3? 58 
 16S-PS-longR 5??ATC AGT TGT GCT TGT GTG GCT GGT TTT GCC?3? 58 
P. gouldii  
mLSU -cox1 16S-PecG-longF 5??AAA TCA TAG GAC AAG AAG ACC CCG TAG AGC?3? 58 
 CO1-PecG-longR 5??AAA AAT AGC AAG ATC CAC GGA AGG GCC TGC?3? 58 
cox1-cox3 CO1-PecG-longF 5??CTT AAT TCG TGT AGA ACT TGG TCA ACC AGG C?3? 52 
 CO3-Ann-724R 5??ACR TCS ACA AAR TGT CAR TAY CA?3? 52 
cox3-cob CO3-PG-long627F 5??GAT TCC ACG GGC TTC ATG TTC TAA TTG GC?3? 52 
 Cytb 876R 5??GCR TAW GCR AAW ARR AAR TAY CAY?3? 52 
cob-nad5 Cob-PG-midF 5??TTG CTT CGA AAC CTT CAT GCT AAC GGA GC?3? -- 
 Nad5-PG-675R 5??AAT CGG ACT AAA AGA AAC ACT CCT GCC G?3? -- 
nad5-nad4 Nad5-PG-453F 5??TTA TAC TTC TTT TAT CTA TTG GAT GAG CCC?3? 53 
 Nad4-PecG-longR 5??ATT GGG AGG AGT TAA AAG AGT AAA GGA TTG C?3? 53 
nad4-mLSU Nad4-PecG-longF 5??TTT AAC TCC TCC CAA TCC CTA TCT TTT AGC?3? 58 
 16S-PecG-longR 5??GTT TAG GTT AGG CGG GAT GCC TTA TTG CTC?3? 58 
 
  88
Table 2: Primers used for sequencing the mitochondrial genomes of Auchenoplax 
crinita, Paravinella  sulfincola and Pectinaria gouldii. 
Fragments Primer name Sequence 
A. crinita   
   mLSU -cox1 CO1-Auc1-startR 5??GTC GCA TAT AAC CAA CGC?3? 
 16S-Auc1-560F 5??AAT CCT ACA TGA GCT GAG?3? 
 16S-Auc1-midF 5??AAT CCT ACA TGA GCT GAG?3? 
 Nad2-Auc1-705R 5??CTA CTT GTC TAG ATC TTC C?3? 
 Nd2-Auc-189R 5??CAA CTC AAA TAG CTA GCC?3? 
 Nd2-Auc-508R 5??TAA TAC TAC TTG TCT AGA TC?3? 
 Nad1-Auc-37F 5??TTT ATG CGC TAT ACT AGC?3? 
 Nad3-Auc1-startR 5??AGA AAT AAC CAT TAA CGC C?3? 
 Nad1-Auc1-561F 5??TGT TTC GGT TTT AGC TGA G?3? 
 Nad1-Auc1-521R 5??GAT AAT CAA ACT TGC CG?3? 
 Nad2-Auc-599R 5??AAT TAT TGA CCC TGC TAC?3? 
 Nad2-Auc-588F 5??AAT TTC TAG TGT TAG AGC?3? 
 Nad1-Auc-startF 5??TGG CAG ACT AGT GCG TTG G?3? 
 Nad2-A1-5R 5??AGG TTT TCC ATG TTA ATG C?3? 
 Nd1-A1-500F 5??TGT TTC GGT TTT AGC TGA G?3? 
   cox1-cob CO1-Auc1-591F 5??TTC GTT ACC AGT ACT GGC?3? 
 Cytb-Auc1-417R 5??CCA TAA TAA ATT CCA CGC?3? 
 Cob-Auc1-mid2R 5??ACA TAC ACG CTG AGT AAC?3? 
 CO3-Auc1-middR 5??CTA CTG GCG GTC ATA CAC?3? 
 Nad6-Auc1-156R 5??TTC ATG ACG TTG ATT AGG?3? 
 CO1-Auc1-1004F 5??AAA ATA GTT TAT GAT CCT GC?3? 
 Atp8-Auc1-startR1 5??AAT AGG AGA CAA ATG AGG C?3? 
 CO1-Auc-911R 5??TTG ACA AAA TAA TCC CAG?3? 
 Nad6-Auc-startR 5??AAT CAA AAC CCT ATG TGC?3? 
 Nad6-Auc-45F 5??TAG TTT TAG TAT TAC TTG G?3? 
 Atp8-A1-endR 5??TAA TAG GAG ACA AAT GAG GC?3? 
 CO3-A1-startR 5??TAC TGT CAC ACC AGA AGC?3? 
   cob-nad5 Cob-Auc1-942F 5??AGC AGA AGC GTA GAA GAC ?3? 
  89
Fragments Primer name Sequence 
 Nd5-Auc1-436R 5??AAC TAT GAT TAT CCC AGC?3? 
 Atp6-Auc1-70F 5??AGT TTC TGT AAT AGG AGT G?3? 
 Cob-Auc1-enddR 5??AAA GTA CAC ATA AAG CTC C?3? 
 Nad4-Auc-812R 5??ACA AAC TTC CAT GTT GAG?3? 
 Nad5-Auc-middR 5??GAA GTT ATT ATC CCA GGC?3? 
 Nad5-Auc-middF 5??TTA ACT TAT ATG GCG TAT G?3? 
 Nad4-Auc1-672R 5??TAG ACC CAG CAA CAG GAG C?3? 
 tRNAx-Auc-befNd5R 5??AAC ATC GAA ACC ATG GGC?3? 
 Atp6-Auc-220F 5??TAT GTT TAC TCA GTC ACG?3? 
 Atp6-Auc-235R 5??ACG CTG ATA AAA CAC TTC?3? 
 Nad4-A1-312R 5??CTA AAA TTA TAG ACC CAG C?3? 
 Atp6-A1-530F 5??TAA GAG CAG GGC ATA TTG CG?3? 
P. sulfincola   
   mLSU-cox1 16S-PS-midF 5??CTA CCT GCT ACA GTT CTC C ?3? 
 16S-PS-endF 5??AAA ATA TGC CCT ACT AGG CTC?3? 
 tRNAX-PS-R 5??TTA TGA AGA CGA CTT TGA GG?3? 
 Nad2-PS-235R 5??GGA AAC CAT TGA TGA CAC GG?3? 
 Nad1-PS-endF 5??TGA ACG GAT AGC TCT GAT GC?3? 
Nad3-PS-211R 5??TGT GGC TGA GTG CTT AGA CG?3? 
 Nad1-PS-308R 5??GTT GAT ATT GGA TAA TTG GC?3? 
   cox1-cob CO1-PS-834F 5??AGA CAC ACG AGC CTA CTT TAC CGC ?3? 
 Cob-PS-202R 5??TGA GAA GGC TAG GTC TAC ATT TGG?3? 
 CO1-PS-1500F 5??CAC CAG CAT TCC ACT CAG GAG CCG?3? 
 Nad6-PS-108R 5??GTG TTA GAG TCG ATA GTC TGC?3? 
 CO2-PS-497F 5??AGC AGA CGT AAT TCA TTC ATG AGC C?3? 
CO3-PS-333R 5??TTA AGA GTG GTA CTG CAA ATG GGT C?3? 
   nad5-mLSU 12S-PS-endR 5??ATG CAG TGA CAT GGT GGC TTG CTG CGG ?3? 
 Nad5-PS-1160F 5??GTG CCG CAG CTG CCT ACT CAA CAC G ?3? 
 12S-PS-startR 5??TTC AGT GTA AGT GAG TGG CAT CAC C?3? 
 tRNAX-PS-R2 5??TCT ATT TGG ACA TTT CGT TAA ACC G?3? 
 Nad4-PS-200F 5??ATT CAT CAT TGT AGT CTC TTT CGC?3? 
 Nad4-PS-531F 5??CGT TGC CGC ATC TTT ACC GC?3? 
  90
Fragments Primer name Sequence 
 Nad4-PS-1176R 5??ATA AGA TTA AAG AGT ATG TAC C?3? 
P. gouldii   
  mLSU -cox1 16S-PG-720F 5??GCC CAG CTA ATT GGC AGA CTA GTG C ?3? 
 CO1-PG-startR 5??GAG ATA ACG TGG CAC AAA CCA AAG C?3? 
 Nad1-PG-261F 5??TCT GCG CTT TAA CCT TAG CCC TGC?3? 
 Nad2-PG-495R 5??CCC GTA TTT GGG TTT GAT TTA GC?3? 
 Nad1-PG-656F 5??ATT GAA TAT AGA AGT GGC AGC?3? 
 Nad2-PG-2R 5??TTT ATA GGG GCA GTC ATA GG?3? 
 Nad2-PG-321F 5??GTA CAA TTT CAA TCA ACC AG?3? 
  cox1-cox3 CO1-PG-900R 5??CAT GGT TGC GGC AGT AAA ATA GGC ?3? 
 CO3-PG-204R 5??CCT AAA AAA GTT CCC TCA CG ?3? 
 CO2-PG-591R 5??GCA TTG ACC ATA GAA TAC TCC G?3? 
CO2-PG-startR 5??TCT TGG AAG GAT AGT TGG GCT C?3? 
 CO1-PG-1257F 5??TTC TTC CCT CAA CAC TTC CTC GG?3? 
 CO1-PG-1134R 5??AGA GGA AAC CAG TGG TTA AAT GC?3? 
  cox3-cob Cob-PG-midF 5??TTG CTT CGA AAC CTT CAT GCT AAC GGA GC ?
 Nad6-PG-273F 5??CTA ATT GCA CTC CTT TTG TCA GGC?3? 
 CO3-PG-L627F 5??GAT TCC ACG GGC TTC ATG TTC TAA TTG GC ?3?
   nad5-nad4 Nad4-PG-186F 5??TCT TAA CCT TAT GAA TTT CCA GCC?3? 
 Nad4-PG-516R 5??TTT ATG AGG ATC GAG TAA CTT GC?3? 
 Nad4L-PG-75F 5??ATG GCG ACC CTG ATT ATT CAA CG?3? 
 Nd5-PG-1005R 5??GTT TGC AAT TAA AAG GCA GGA C?3? 
 Nd5-PG-1065F 5??GCC GGG TTC TAC TCT AAA GAC C?3? 
 Nd5-PG-1587F 5??CAA GGT TGA AAC GAA ATA GCC GG?3? 
 Nad4-PG-453R 5??CTA TAA GGA GTG GTA GTG AAG C?3? 
  nad4-mLSU Nad4-PG-846F 5??CTT ATT GCT TAT TCC TCA GTT GGT C ?3? 
 Nad4-PG-1026F 5??GGG TTA CTC ATT AAT ACT TTC CAG?3? 
12S-PG-startR 5??AAT TTT TCA ATA GTT TAC TCA TGG AG ?3? 
 tRNAX-PG-F 5??CAT GAC CCA AAA GTG GAA ACA ATC C?3? 
 12S-PG-111F 5??TGT CCT CTA ACT CGA TAA TCC ACG?3? 
 12S-PG-midR 5??ATT CCT GAT GCT ATG CTT TGT GGC?3? 
Nad4-PG-519R 5??TGG CTG GAA AGT ATA TGA GTA ACC?3? 
 
  91
Table 3: Taxa used in the phylogenetic analysis. 
Species Clade Nucleotides GenBank Number
Auchenoplax crinita Annelida, ?Canalipalpata?, Ampharetidae 13,759 partial FJ976041 
Pectinaria gouldii Annelida, ?Canalipalpata?, Pectinariidae 13,438 partial FJ976040 
Paralvinella sulfincola Annelida, ?Canalipalpata?, Alvinellidae 13,640 partial FJ976042   
Terebellides stroemi Annelida, ?Canalipalpata?, Trichobranchidae 15,755 complete EU236701 
Pista cristata Annelida, ?Canalipalpata?, Terebellidae 15,894 complete EU239688 
Eclysippe vanelli Annelida, ?Canalipalpata?, Ampharetidae 13,749 partial EU239687 
Clymenella torquata Annelida, ?Scolecida?, Maldanidae 15,538 complete AY741661 
Riftia pachyptila Annelida, ?Canalipalpata?, Siboglinidae 12,016 partial AY741662 
Galathealinum brachiosum Annelida, ?Canalipalpata?, Siboglinidae 7,576 partial AF178679 
Platynereis dumerilii Annelida, ?Aciculata?, Nereididae 15,619 complete NC_000931 
Lumbricus terrestris Annelida, ?Oligochaeta?, Lumbricidae 14,998 complete NC_001673 
Helobdella robusta Annelida, Hirudinea, Glossiphoniidae 7,553 partial AF178680 
Orbinia latreillii Annelida, ?Scolecida?, Orbiniidae 15,558 complete AY961084              
Scoloplos cf. armiger Annelida, ?Scolecida?, Orbiniidae 12,042 partial DQ517436 
Phascolopsis gouldii Annelida, Sipuncula 7,470 partial AF374337 
Urechis caupo Annelida, Echiura 15,113 complete AY619711 
Nephtys sp. Annelida, ?Aciculata?, Nephtyidae 17,217 complete EU293739 
  
 
Figure 1: Mitochondrial gene order of six Terebelliformia worms. Different colors shows 
conserved gene clusters. Dots indicate missing regions. 
92
  
93 
 
Figure 2: Phylogenetic reconstructions for 17-taxon mitochondrial datasets. (A) The mitochondrial nucleotide tree represents the 
identical topology from both ML and partitioned Bayesian inference methods. (B) The mitochondrial amino acid tree with the 
identical topology from both ML and partitioned Bayesian inference methods. Nodal support values are given at branches with 
posterior probabilities of the partitioned Bayesian analysis first and ML bootstrap values second. A dash indicates < 50% on trees. 
The representative branch lengths are from the Bayesian trees. 
 
Figure 3:  Character mapping on Terebelliformia ingroup trees based on mitochondrial 
datasets. The bar represents trnM duplication event. The circle represents the specific 
gene order of nad5-nad4L-nad4 cluster in mitochondrial genomes. Open bar: duplication 
absent; Black bar: duplication present; open ellipses: nad5- trnF-trnE-trnP-trnT-nad4L-
nad4; black ellipses: trnE-trnT-trnP-trnY--nad4L-nad4-trnC-trnM-trnH-nad5; shaded 
ellipse: nad5- trnF-trnE-trnP-trnT-trnR-nad4L-nad4. 
  94
 95
CHAPTER 4 
TWO GROUP II INTRONS AND THEIR EVOLUTIONARY ORIGINS IN 
ENDOMYZOSTOMA (MYZOSTOMIDA) MITOCHONDRIAL GENOME 
 96
Abstract 
Group II introns are self-splicing ribozymes or retroelements thought to be 
evolutionary precursors to spliceosomal introns. They consist of a distinctive secondary 
structure and have been described from eukaryotic organelles and bacteria. Interestingly, 
they are lacking from genomes of bilaterian animals, with the exception of a species 
annelid worm, Nephtys sp. Here, we report two group II introns identified in the 
mitochondrial genome of the annelid-like myzostomid worm, Endomyzostoma. Similar to 
the Nepthys intron, the myzostomid introns, designated as Mintron1 and Mintron2, are 
found in the cox1 gene. Mintron1 has a 1424 bp ORF in the loop area of domain 4 which 
includes only the RT and X domains that are assumed to assist the self-splicing efficiency 
in vivo. Based on both the ORF nucleotide sequence and RNA structure, we hypothesize 
Mintron1 is a divergent group II intron. In contrast Mintron2 is a short (384 bp) 
degenerate intron that lacks an ORF which cannot perform retrohoming mobility, but can 
perform RNA-mediated splicing in vitro. Mintron1 lacks of both D and En domains in 
the ORF which play a key role in retrohoming process, but it may still maintain its 
capability for retrohoming by insertion into replication forks. Both introns are in the 
mitochondrial class of group II introns as suggested by RNA folding structure (for 
Mintron2) and phylogenetic analysis (for Mintron1). They likely are products of 
independent horizontal transfer events based on the close relationship to Nephtys? intron 
suggested by the ORF phylogeny.  
 97
1. Introduction  
Group II introns are self-splicing ribozymes that are found in the genomes of 
bacteria as well as organelle genomes of fungi, plants and animals (Beagley et al. 1998; 
Lehmann and Schmidt 2003; Rot et al. 2006; Dellaporta et al. 2006; Vall?s et al. 2008) 
and are hypothesized to be the ancestor of eukaryotic spliceosomal introns (e.g., 
Cavalier-Smith, 1991). Secondary structure of a typical group II intron consists of 6 
stem-loop domains, D1 to D6, with all domains radiating from a central core to form the 
proximal helix that facilitates self-splicing. Several conserved nucleotide sequences are 
diagnostic of group II introns including 5? and 3? splicing sites (5?-GUGYG and AY-3?), 
an unpaired adenosine in D6 and a number of conserved nucleotides in D5 (Knoop et al. 
1994; Lambowitz and Zimmerly 2004; Lang et al. 2007). 
Group II introns are mobile and generally have two forms, a larger ORF-
containing form and an ORF-less form that only consists of the six domains. ORF-less 
introns primarily occur in organelles rather than bacteria (Dai and Zimmerly 2002). All 
ORFs in group II introns are found in D4 and involve four functional domains: reverse 
transcriptases (RTs) domains, a X domain with maturase activities, a non-conserved D 
domain (for DNA-binding) and an En domain with endonuclease activity (Lambowitz et 
al. 1999; Zimmerly et al. 2001; San Filippo and Lambowitz 2002; Dai and Zimmerly 
2002). ORF proteins mainly have two functions: 1) to facilitate the RNA-mediated intron 
splicing process through both RT and X activities, and 2) to act as an element for 
 98
retrohoming which requires all four domains cooperating with intron RNA (reviewed by 
Robart and Zimmerly 2005). Intron retrohoming is a common mobile phenomenon in 
group II introns by inserting into specific target sites with the assistance of ORF proteins 
that widely distributed in protists and eukaryotes. But introns lacking an ORF will only 
perform the RNA-mediated splicing activity in vitro with the requirement of extreme 
unphysiological conditions (high concentrations of magnesium and high temperature) and 
cannot home (Michel and Ferat 1995). But in vivo, the splicing activity relies on the aid 
of proteins coded by the ORF (Michel and Ferat 1995; Bonen and Vogel 2001). 
Retrohoming usually occurs at very specific insertion site sequences, but insertions into 
non-specific site are also known (Cousineau et al. 2000).  ORFs are associated with their 
specific intron RNA structures allowing their sequences to be for categorizing and 
identifying group II introns (Zimmerly et al. 2001; Toor et al. 2001; Dai and Zimmerly 
2002). Phylogenetic analyses of the various ORFs can divide group II introns into several 
major classes: six bacterial classes (A, B, C, D, E, F), one mitochondrial class (with 
uniform group IIA1 RNA structures) and two chloroplast classes (IIB1 and IIB2 in 
structures) (Toor et al. 2001; Zimmerly et al. 2001; Toro et al. 2002; Simon et al. 2008). 
Bacterial introns are considered basal to mitochondrial and chloroplast forms, and all 
currently known group II introns have been hypothesized to descend from bacterial ORF-
containing group II introns (Toor et al. 2001). 
Eukaryotic mitochondrial genomes, which can harbor Group II introns, have 
variable gene compliments across organismal lineages. In contrast, bilaterian 
mitochondrial genomes are remarkably conserved with a typical size of 15-17kb and a 37 
gene compliment consisting of 13 protein-coding genes, two ribosomal genes, 22 tRNA 
 99
genes and one non-coding region referred to as the UNK or D-loop (Boore 1999; Vall?s 
and Boore 2006; Zhong et al. 2008).  To date, there have been over one thousand 
bilaterian mitochondrial genomes published. Of these, only the mitochondrial genome of 
the annelid Nephtys sp. possesses a group II intron which was the first report of group II 
intron in animal genomes (Vall?s et al. 2008).  
Myzostomida are small parasitic marine worms, living mostly on as 
ectocommensals or endoparasites of echinoderms (Grygier 2000). Their body is typically 
soft and flattened with many radiating cirri on the thin rounded body edge and five pairs 
of parapodia on the ventral side. With limited exception (Lanterbecq et al. 2006), all have 
high host-specificity, as a myzstomid species usually associates with a single crinoid 
species (Eeckhaut 1998). Fossils from the Ordovician suggest an ancient association 
between myzostomids and their crinoid hosts (Eeckhaut 1998), which may explain the 
highly derived body plan of myzostomids and their disputable phylogenetic position 
within metazoans (Zrzav? et al. 2001; Bleidorn et al. 2007). Although some studies 
question their placement with annelids (e.g., Eeckhaut et al. 2000; Zrzav? et al. 2001), 
their affinity with the group is indicated by morphological data (e.g., Haszprunar 1996; 
Rouse and Fauchald 1997) and a recent molecular study (Bleidorn et al. 2007) provides 
strong additional support.  
While determining the mitochondrial genome of a marine worm of 
Endomyzostoma sp. (Myzostomida), we discovered two group II introns. Interestingly, 
the mtDNA genome of Myzostoma seymourcollegiorum (Bleidorn et al. 2007) does not 
have introns. Below we describe these introns and discuss implications for both bilaterian 
mitochondrial genome and group II intron evolution. This is the first report of multiple 
 100
introns in bilaterian mitochondrial genomes. The association between two introns as well 
as their evolutionary origins will be the focus in our study. 
2. Materials and Methods 
2.1 Sample collection and DNA extraction 
Endomyzostoma sp. was collected in the Bransfield Straight region of the 
Antarctic Pennisula (S 63
o
40.145', W 61
o
10.047') by Blake trawl using the R/V Lawrence 
M. Gould. Tissue was initially frozen at -80?C then dissected in ethanol after DNA 
collections. Total genomic DNA extractions employed the DNeasy? Tissue Kit (Qiagen) 
according to the manufacture?s instructions.  
2.2 MtDNA data collection 
The mitochondrial genome of Endomyzostoma sp. was amplified in four 
overlapping fragments. Taxonomically-inclusive primers (Zhong et al. 2008) were first 
used to amplify conserved regions of mLSU, cox1, cob and nad5 genes. PCR products 
were then purified using QIAquick PCR purification kit (Qiagen) and sequenced using a 
Beckman CEQ8000. Four pairs of specific long-PCR primers (table 1) were subsequently 
designed to amplify fragments spanning mLSU-cox1, cox1-cob, cob-nad5 and nad5-
mLSU. Long PCRs were employed on an Eppendorf Mastercycler (Eppendorf) using 
Takara LA-Taq PCR System. 50 ?l long PCR reactions were set up including 5?l 
10?buffer, 8?l dNTP (2mM), 5?l MgCl
2
 (25mM), 2?l of each long PCR specific primers 
(10?M each), 0.5?l Takara LA-Taq (5U/?l), 2?l DNA template and 25.5?l sterilized 
distilled water. The long PCR protocol was 94 ?C for 3min, followed by 35 cycles with 
 101
94?C for 30 sec, 53 or 54?C for 30s (annealing temperatures for different pairs of primers 
are in table 1), and 70?C for 12min; final extension at 72?C for 10 min and hold at 4?C. 
The cox1-cob fragment was approximately 8 kb, cob-nad5 was 2 kb, and nad5-mLSU 
was about 4.5kb in size. These three fragments were purified using QiaQuick Gel 
Extraction Kit (Qiagen) and then cloned into the pGEM-T Easy vector (Promega). 
Positive clones were screened by PCRs and plasmids were isolated by QIAprep
?
 Spin 
Miniprep Kit (Qiagen). Size of the inserted plasmid was confirmed by EcoRI digestion. 
Primer walking was employed to sequence inserts of plasmids. All sequencing primers 
were listed in the table 2. 
The mLSU-cox1 fragment repeatedly proved difficult to be amplified probably 
due to the effects of the potential UNK region that it contained (see Boore and Brown 
2000; Jennings and Halanych 2005). Thus, we were not able to obtain the complete 
sequence of the mtDNA genome. Presumably, nad1, nad3, nad2 and several tRNA genes 
are located in this currently uncharacterized region (see below). The GenBank accession 
number for the partial mitochondrial genome is FJ975144. Gene nomenclature and 
abbreviations used here follow Jennings and Halanych (2005). 
2.3 Genomic Assembly 
Sequences were assembled and edited using SeqMan and MegAlign (Burland 
2000) in the DNASTAR? Lasergene suite. BLAST (Altschul et al. 1990) was used to 
identify protein-coding genes and ribosomal RNA genes. Boundaries of tRNA sequences 
were inferred by identifying flanking prtein-coding and rRNA genes. The tRNA genes 
were identified using the tRNAscan-SE web server (http://lowelab.ucsc.edu/tRNAscan-
 102
SE/; Lowe and Eddy 1997) under default settings with the sequence source set to 
?mito/chloroplast?, or drawn by hand based on their potential secondary structures and 
anticodon sequences.  
2.4 Intron identification 
Secondary structures of introns were examined with the ?mfold? online server 
(Zuker 2003) and refined by eye based on comparisons with the typical structures of 
group II introns (Toor et al. 2001). To confirm introns existed in the mitochondrial 
genome of Endomyzostoma sp., two pairs of primers spanning the intron-exon boundary 
were employed for PCR amplifications. For intron1 (here after called Mintron1), Intron-
Myz-635R was designed to anneal within the intron1 sequence and paired with the cox1 
primer LCO1490 (Folmer et al. 1994). A 1.4 kb fragment was obtained using the 
Eppendorf High Fidelity PCR system and genomic DNA as template. A similar test was 
performed for the second intron (here after Mintron2) by using the intron specific primer, 
CO1-Myz-Intron2F and a cox1 gene degenerated primer, CO1-Ann-1300R from the 3? 
region of cox1. In this case, a 500 bp fragment was generated. Sequencing results of these 
two fragments confirm sequences obtained from clone fragments, thus verifying that 
Mintron1 & 2 are not recombinant products or PCR artifacts. All the primers used for 
intron identification are shown in table 3. 
2.5 Phylogenetic analyses and sequence alignments 
For phylogenetic analyses, 105 ORF amino acid sequences for group II introns 
were collected from bacteria, mitochondrion and chloroplast based on the organism list in 
the Zimmerly database (http://www.fp.ucalgary.ca/group2introns/; Dai et al. 2003). The 
 103
dataset included all ORFs from published mitochondrial and chloroplast group II introns 
as well as 46 bacterial group II introns (table 4). An Archaebacteria ORF (M.a.I1-1) was 
used as the outgroup to polarize the resultant tree. Sequences were aligned by MAFFT 
version 6  (Katoh and Toh 2008) and examined by Gblocks 0.91b (Castresana 2000). 
MacClade 4.08 (Maddison and Maddison 2002) was used to exclude ambiguously 
aligned regions. The employed alignment is available in TreeBASE with the assession 
number XXXXXX (www.TreeBASE.org). Bayesian analyses of amino acid sequences 
were performed in MrBayes version 3.1.2 (Huelsenbeck and Ronquist 2001) with the 
mixed amino acid substitution model. Two sets of four chains were run simultaneously 
for 2,000,000 generations sampled every 100 generations. Burnin  (2,500 generations) 
was determined by assessing stationarity in ?ln likelihood values. 
3. Results 
3.1 Genome Composition and Evolution 
The partial mitochondrial genome of Endomyzostoma sp. is 13,190 bp in length 
and contains 26 genes including 10 protein-coding genes, two rRNA genes and 14 tRNAs. 
The region from mLSU to cox1 gene was not recovered. All recovered genes are 
transcribed from the same strand. The tRNA secondary structures are presented in figure 
1. The gene orders of Endomyzostoma sp. and Myzostoma seymourcollegiorum mtDNA 
have the same protein-coding and rRNA gene order (Bleidorn et al. 2007; Bleidorn et al. 
revised). tRNAs have relocated in the fragment from atp6 to mSSU, the region Zhong et 
al. (2008) noticed was less conserved. The partial mitochondrial gene arrangments in two 
myzostomids share the same protein-coding gene arrangement pattern as all published 
 104
annelids other than the sipunculid and echiurid (Vall?s and Boore 2006; Zhong et al. 
2008; Bleidorn et al. revised). 
3.2 Intron structures 
Two group II introns, Mintron 1 and Mintron 2, were identified in the cox1 gene 
by their potential secondary structures and ORF sequences (fig. 2A). The total length of 
Mintron1 is 1424bp, with an ORF 1056bp in size whereas Mintron2 is only 384bp in 
length and lacks an ORF. The secondary structures contain six helical domains radiating 
from a central core. Conserved GUGYG and AY nucleotides at 5? and 3? end, 
respectively, were identified in Mintron1 (fig. 2B). However, one nucleotide difference 
was located at the 5? end (GCGCG) of the Mintron2 sequences (fig. 2C). Two Exon 
Binding Sequences (EBSs) were located in D1 for both Mintron1 and Mintron2. These 
sites can bind specifically with intron binding sequences (IBSs) in 5? end exon sequences 
during splicing (fig. 2B and C) (Lambowitz et al. 1999; Bonen and Vogel 2001). 
3.3 ORF alignment and phylogenetic analyses 
Group II intron ORFs typically have several domains with a few conserved 
regions (fig. 3A) (Zimmerly et al. 2001; San Filippo and Lambowitz 2002; Robart and 
Zimmerly 2005). The alignment of 105 ORF amino acid sequences revealed that both 
Mintron1 and the Nephtys intron have the RT and X domains while lacking both D and 
En domains. The amino acid sequences of both ORFs were highly divergent. From the 
alignment, the Mintron1 ORF shows sub-domain 2 and 4 of the RT domain and the X 
domain are the most conserved sub-domains present (fig. 3B). 
 105
The ORF phylogenetic analysis revealed that most group II introns found in 
mitochondria fall into one main clade (fig. 4). Mintron1 is inferred to be sister to the 
Nephtys? although nodal support as judged by posterior probabilities is weak (fig. 4). 
4. Discussion 
Animal mitochondrial genomes usually lack any introns, with the exception of 
some Cnidaria and the Placozoa (Lavrov 2007). It has been noticed that bilaterian 
mitochondrial genomes provide a population genetic environment which encourages 
elimination of mutationally disadvantageous noncoding DNA (Lynch 2007). Discovery 
of two group II introns within the mitochondrial genome of the myzostomid, 
Endomyzostoma sp., along with their previous discovery in Nephtys (Vall?s et al. 2008), 
contrast sharply with the otherwise highly conserved and intron-free mitochondrial 
genomes found in the bilaterian. This suggests that some animal lineages may be more 
susceptible to retroelement ?attack?. Additionally, one of the most basal groups of 
metazoans, Placozoa, also contains group II introns (Dellaporta et al. 2008), as do some 
other annelids (KMH unpublished data). To date, all of these metazoan mitochondrial 
group II introns have been discovered in the cox1 gene. When aligned, the insertion site 
of the Nephtys intron and Mintron1 are only 24 bp apart, and Mintron 2 is further 
downstream in the 3? direction.  Presumably, the sequence motif recognized by these 
group II introns for insertion is found in higher prevalence in this region of the cox1 gene 
than other mtDNA genes. In view of the conserved regions of host cox1 genes for both 
Mintron1 and Mintron2, our result is consistent with the previous prediction that 
 106
organellar group II introns often locate in conserved housekeeping genes (Dai and 
Zimmerly 2002; Robart and Zimmerly 2005). 
4.1 Mintron1: a divergent mitochondrial group II intron 
Although Mintron1 is an ORF-containing intron, the amino acid sequence of the 
ORF is considerably different from other investigated taxa. Only a limited number of 
amino acid residues found in the RT 0-7 subdomains and one region in X domain are 
conserved relative to other group II ORFs. Given that both RT (for reverse transcriptase 
activity) and X (maturase activity for splicing) domains are required for mobility in vivo 
(Matsuura et al. 1997; Wank et al. 1999; Bonen and Vogel 2001; Cui et al. 2004;), 
Mintron1 can presumably accomplish reverse splicing in the genome. Generally, only 
single-stranded DNA will be reverse transcribed as the lacking D (C-terminal DNA-
binding domain) and En (endonuclease activity) domains interfere with the recognition of 
the second-strand DNA cleavage (Guo et al. 1997; Lambowitz and Zimmerly 2004). 
Mintron1, however, probably does not totally lose mobility since they may insert into the 
replication fork to complete the double strand DNA replication for retrotransposition 
without the second-strand cleavage (Ichiyanaqi et al. 2002; Zhong and Lambowitz 2003).  
Secondary structure of Mintron1 is typical of group II introns with six domains 
and one ORF in the D4 domain. Comparing secondary structures in each sub-class, we 
don?t find any similarity in Mintron1 to any previously identified category (Toor et al. 
2001). However, the ORF phylogenetic tree suggests it belongs to the mitochondrial class 
with close relationship to the intron found in Nephtys (fig. 4). Therefore, we infer 
 107
Mintron1 to be a divergent mitochondrial group II intron. Alternatively, Mintron1 could 
fold in other configurations. 
4.2 Mintron2: undergoing evolutionary degeneration 
Compared to the typical mitochondrial class group IIA1 structure (Toor et al. 
2001), the secondary structure of Mintron2 has several conserved nucleotides in the 
central core. These are key A1 features, for instance, CGGA between D2 and D3, only 
one A locating between D3 and D4, and GGA between D4 and D5 (fig. 2C). Mintron2 
has apparently lost its mobility and is speculated to be undergoing degeneration as it 
lacks any ORFs and has one substitution in the critical 5? region. Nevertheless, in order 
for the cox1 gene that harbors the insertion to be functional, Mintron2 must be spliced out 
prior to translation (Dai and Zimmerly 2002; Robart and Zimmerly 2005). Thus, because 
Mintron2 lacks the ORF encoded proteins, it can?t perform splicing in vivo only by the 
RNA structure and presumably needs host accessory proteins to increase splicing 
efficiency allowing the cox1 gene, which is critical to oxidative phosphorylation, to 
function (Jenkins and Barkan 2001; Dai and Zimmerly 2002). Alternatively, Mintron 2 
could use the reverse transcriptase and maturase activities encoded by Mintron1?s ORF 
for splicing. 
The presence of substitutions at the 5? end of Mintron2 challenges our knowledge 
of the actual mechanism of self splicing. The 5? splice sites play a critical role in 
initiating group II intron self-splicing events by interaction with a bulged adenosine in D6 
domain to form a lariat (Bonen and Vogel 2001). Whereas such substitutions would be 
expected to cause lose of splicing function, the 5? sites retain splicing proficiency 
 108
suggesting the mechanism is not as conserved as previously hypothesized (Michel and 
Ferat 1995; Bonen and Vogel 2001). Such substitutional changes are consistent with the 
?Retroelement Ancestor Hypothesis? which posits that most ORF-less introns are derived 
from ORF-containing elements (Toor et al. 2001; Robart and Zimmerly 2005).  
4.3 Intron evolutionary origins 
Phylogenetic analysis shows the ORF-containing Mintron1 belongs to the main 
mitochondrial class (fig. 4). The similarity of secondary structure of the Mintron2 to the 
group IIA1 class also suggests its mitochondrial origin. Although Mintron2 has lost 
retrohoming capability as a transposable element, it can presumably still perform splicing 
in vivo under aid of recruited proteins and despite substitutions at the 5? end. Toor et al.?s 
(2001) retroelement ancestor hypothesis posits that major RNA structural forms of group 
II introns coevolve with the intron-encoded proteins leading to most ORF-less introns 
evolving from ORF-containing ones (see also Hausner et al. 2005). However, the 
difference in secondary structure of Mintron 1 and 2 seems to suggest the two introns 
originated from different lineages.   
Interestingly, Mintron 1 is recovered as sister to the Nephyts intron, but based on 
the ORF alignment dataset, limited similarity was found among Mintron1, the Nephtys 
intron and Trichoplax ORF domains, suggesting that an independent origin of introns in 
these three metazoans.  The close phylogenetic placement of Mintron1 to the Nephtys? 
intron, however, may indicate a common ancestor that separately infected both organells 
by a horizontal transfer (as discussed in Vall?s et al. 2008). In these organisms, introns 
occur in roughly the same 3? region of cox1 perhaps indicating a common insertion site 
 109
by the group II introns. The discovery of multiple groups II introns restricted to one 
lineage of bilaterians, annelids, implicates the bigger potential to accept retroelements in 
its mitochondrial genomes and may provide insight into their origins and functional 
contributions to the hosts.  
Acknowledgements 
We thank T. Struck, Y. Vall?s, and J. Boore for constructive comments with the 
mtDNA genome work, S. Zimmerly for the helpful suggestions with the group II intron 
analyses. This work was made possible with support from the National Science 
Foundation (EAR-0120646) to KMH. This is contribution #XX to the AU Marine 
Biology Program. 
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Table 1. Long PCR primers used in amplifications. 
Fragments Primer name Sequence Annealing Temp.
  mLSU -cox1 16S-Myz-longF 5??AGG GTT AAT TAA ATC AAT CCT ACT AGT AAG AC?3?  
 CO1-Myz-longR 5??TAT TCG TTC TAA TTT CAA TGC TGT TGA TCG?3?  
cox1-cob CO1-Myz-longF 5??ATT TTT TCC TTA CAT TTA GCT GGG GCT AGG-3? 53 
 Cytb-Myz-longR 5??TGT TTA ACT CCT AAA GGG TTT GAT GAC CCG C?3? 53 
   cob-nad5 Cytb-Myz-longF 5??TCC TCA TTA ATA AAA ATC CCG TTC CAC CCG?3? 54 
 Nad5-Myz-618R 5??TAC TAG TGC AGA AAC GGG TGT AGG TGC TGC?3? 54 
  nad5-mLSU Nad5-Myz-615F 5??GTA CAC TCA TCA ACA TTA GTA ACA GCA GGC?3? 54 
 16S-Myz-longR 5??CTT TAG AAA AAT AAA CCT GTT ATC CCT GTG G?3? 54 
 
 
 117
Table 2. Sequencing primers used for sequencing mitochondrial genomes. 
Fragments Primer name Sequence 
cox1-cob CO1-Myzo-720F 5??GCA TAC AAA AAT ATC TTT CAA GGT G?3? 
 CO1-Myzo-636F 5??CAT CAT TTT TTG ACC CAT CG?3? 
 Cytb-Myzo-211R 5??TGA ATT AAC CGA ATC ACC C?3? 
 Intron-Myz-713F 5??AGG AAG CTA TAT TAA CGA C?3? 
 Intron-Myz-635R 5??AGG TAA TTT ATG CCT GTG?3? 
 Intron-Myz-201R 5??TTT TAG GTG CTA TTT AGC?3? 
 Cob-Myzo-241R 5??TTT GAG TAC AGG TGG TAG?3? 
 Cob-Myzo-161R 5?AAG TTT ATT GGT GCT GG?3? 
 CO3-Myz-453R 5??GAG TGG CCT ATA ATG CCT G?3? 
 CO1-Myz-1068F 5??ACT CAT CAC TAG ATA TAC C?3? 
 Intron-Myz-954F 5??AAT GAT AAT GTT AAA ATA CG?3? 
CO3-Myz-startR 5??TAA ATG GTA TGG TTG TCG G?3? 
 CO3-M-378F 5??AGA TTG GAA TAG TAT GGC?3? 
 CO1-M-918F 5??AGC CTA TTT CAC GTC TGC G?3? 
 Nad6-Myzo-164R 5??AGC TGT TGA AAT AGC TAA GC?3? 
 Intron-Myzo-470F 5??AAC TAC AAA ATT AAC CGC?3? 
 Intron-Myzo-1163F 5??ATA ATT TGA TAG GGC CAC C?3? 
 CO1-Myz-1389F 5??TTA TCA GGA ATA CCA CGA CG?3? 
 CO1-Myz-Intron2F 5??AAT ATC ACG TAC AAT TCG G?3? 
 CO2-Myz-422R 5??TTC AGT CGG TAA TAT GTA TG?3? 
 tRNAD-Myz-R 5??TAT TGG TGC AAG TTG AGG C?3? 
cob-nad5 Nad5-Myz-411R 5??TTA TAC CTG CAG ATA GTG?3? 
 Nad5-Myz-261R 5??GTA TTT GAT TTT GCT CAT C?3? 
 Cob-Myz-1020F 5??TAA TAT AGC TGT GCT ACC?3? 
 Cob-Myz-840R 5??GAT TGA TCG AAG CAT GGC?3? 
 Cob-Myz-enddR 5??CAT CAA AAT CTA GGC TAC C?3? 
 Atp6-Myz-midR 5??GAA ATG TAT AGT GAT AAC?3? 
 Atp6-Myz-midF 5??TTT TCT TTG TGC GTT AGG?3? 
   Nad5-mLSU Nad5-Myz-1015F 5??TAT TTA TCA GGG TTC TAT TC?3? 
 16S-Myz-59R 5??ATT ATG CTA CCT TAG TAC G ?3? 
 12S-Myz-midF 5??GTT TCT AGC CTA TAA GGC ?3? 
 118
Fragments Primer name Sequence 
 12S-Myz-mid2F 5??ACC AAC CTT ACA CAT TTC CG?3? 
 12S-Myz-endR 5??TTA TAT TTG CCG AAT TCC?3? 
 Nad5-Myz-1179F 5??TAA TAA TAT CAA CAC TAA TGA C?3? 
 12S-Myz-statR 5??TAT TTA TTT TTC CAA GGT TG?3? 
 Nd5-Myz-1611F 5??ATT ACA AAA GAG AAT CCC AAT C?3? 
 12S-Myz-startR2 5??ATA ATA GAG ATA GAT CAC ATC?3? 
 Nad4L-M-251F 5??ATC ATA ACT CGA ACA TAC GG?3? 
 Nad4-M-915R 5??CTT GAT GTA AGC CCA TGG GC?3? 
Nad4-M1-824R 5??ATG GGT AAT TGA TGA GTA TGC G?3? 
 
 119
Table 3. Intron identification primers.  
Introns Primer name Sequence 
Intron1 LCO1490 (Folmer et al.,1994) 5??GGT CAA CAA ATC ATA AAG ATA TTG?3? 
 Intron-Myz-635R 5??AGG TAA TTT ATG CCT GTG?3? 
Intron2 CO1-Myz-Intron2F 5??AAT ATC ACG TAC AAT TCG G?3? 
 CO1-Ann-1300R 5??TCC GGG TAR TCW GAR TAT CGT CGW GG?3? 
 
 
 120
Table 4. Group II ORFs used in the phylogenetic analysis. 
Intron Class Organism Class Species Host gene Intron 
mitochondrial Annelids Nephtys sp. cox1  
 Myzostomids Endomyzostoma sp. cox1 Mintron1
Placozoans Trichoplax ashaerens cox1 OFR677
 Green Plant Arabidopsis thaliana nad1 I4 
 Glycine max nad1 I4 
 Oenothera berteriana nad1 I4 
 Vicia faba nad1 I4 
 Zea mays nad1 I4 
Liverwort Marchantia polymorpha atpA I1 
  Marchantia polymorpha atpA I2 
Marchantia polymorpha Atp9 I1 
  Marchantia polymorpha cob1 I3 
Marchantia polymorpha cox1 I1 
  Marchantia polymorpha cox1 I2 
Marchantia polymorpha cox2 I2 
  Marchantia polymorpha SSU I1 
Algae Chara vulgaris nad3 I2 
  Mesostigma viride cox2 I1 
Porphyra purpurea LSU rDNA I1 
  Porphyra purpurea LSU rDNA I2 
Pavlova lutheri cox1 I1 
  Pylaiella littoralis LSU rDNA I1 
Pylaiella littoralis LSU rDNA I2 
  Pylaiella littoralis cox1 I1 
Pylaiella littoralis cox1 I2 
  Pylaiella littoralis cox1 I3 
Thalassiosira pseudoana cox1 I1 
  Rhodomonas salina cox1 I1 
 121
Intron Class Organism Class Species Host gene Intron 
  Rhodomonas salina cox1 I2 
Fungus Allomyces macrogynus cox1 I3 
  Rhizphydium sp. 136 cox1 I11 
Neurospora crassa cox1 I1 
  Podospora anserina cox1 I1 
Podospora anserine cox1 I4 
  Podospora anserina nad5 I4 
Podospora comata cox1 I1 
  Podospora curvicolla nad5 I1 
Venturia inaequalis cob1 I1 
 Yeast Candida parapsilosis cox1 I1 
 Candida stellata LSU I1 
 Kluyveromyces lactis cox1 I1 
 Saccharomyces cerevisiae cox1 I1 
 Saccharomyces cerevisiae cox1 I2 
 Schizosaccaromyces pombe EF2 cob1 I1 
 Schizosaccaromyces pombe cox1 I1 
 Schizosaccaromyces pombe cox2 I2 
 Schizosaccharomyces octosporus cox2 I1 
Ichthyospora Amoebidium parasiticum cox1 I6 
Chloroplast Plant Nicotiana tabacum trnK I1 
  Marchantia polymorpha trnK I1 
Green Algae Scenedesmus obliquus petD I1 
  Oocystacea sp. petD I1 
Bryopsis maxima rbcL I1 
  Pyrenomonas salina cpn60 I1 
Euglenoid Euglena gracilis psbC I4 
  Euglena gracilis psbD I8 
Euglena deces psbC I4 
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Intron Class Organism Class Species Host gene Intron 
  Euglena myxocylindracea psbC I4 
Euglena viridis psbC I4 
  Lepocinclis buetschli psbC I4 
Bacteria Eubacteria Alkaliphilus metalliredigenes (Al.me.I4) None  
  Sinorhizobium terangae strain ORS22 (Sr.t.I1) ISRm10-1  
Uncultured marine bacterium (UMB.I1) Unknown  
  Bradyrhizobium japonicum (B.j.I2-1) Putative transposase  
Chlorobium phaeobacteroides DSM 266 
(Ch.ph.I2-1)
none  
  Frankia sp. (Fr.sp.I1) Transposase  
Uncultured bacterium (UB.I1) none  
  Clostridium beijerincki NCIM 0852 (Cl.be.I2) none  
Wolbachia endosymbiont of Drosophila 
melanogaster (W.e.I2)
Hypothetical protein 
  Mycobacterium vanbaalenii (My.va.I1) none  
Burkholderia fungorum Bcep_271 (B.f.I1) none  
  Sodalis glossinidius (So.gl.I1) none  
Pseudomonas putida (P.p.I1) none  
  Syntrophobacter fumaroxidans (Sy.fu.I1) none  
Solibacter usitatus Ellin6076 (So.us.I3-1) none  
  Klebsiella pneumoniae isolate YMC (Kl.pn.I1) Metallo-beta-
lactamase VIM-2 
 
  Oceanobacillus iheyensis (O.i.I1) none  
Bacillus sp. NRRL (B.sp.I1) none  
  Clostridium acetobutylicum (C.a.I1) none  
Syntrophomonas wolfei subsp. wolfei str. 
Goettingen (Sy.wo.I2-1)
none  
  Desulfotalea psychrophila LSv54 (D.p.I1) none  
Bacillus anthracis (B.a.I2) pX01-24/ORFX  
 123
Intron Class Organism Class Species Host gene Intron 
  Clostridium perfringens (Cl.pe.I1) none  
Bacillus megaterium (B.me.I1) Conserved region  
  Bacillus thuringiensis (B.th.I1) Conserved 
hypothetical protein
 
  Enterococcus faecalis (E.f.I4) FtsK/SpoIIIE family
protein 
  
  Crocosphaera watsonii WH 8501 (C.w.I7) none  
Nostoc punctiforme Npun_200 (N.p.I1) none  
  Trichodesmium erythraeum IMS101(Tr.e.I4) Putative RP 
ribonucleotide 
reductase 
 
  Onion yellows phytoplasma (OYPI1) Putative helicase 
DnaB 
 
  Shigella flexneri (S.f.I1) IS629-like ORF  
Azotobacter vinelandii (A.v.I1) groEL  
  Alcanivorax borkumensis SK2 (Al.bo.I1) none  
Xylella fastidiosa (X.f.I1) DNA 
methyltransferase 
 
  Bacteroides thetaiotaomicron (B.t.I1) TraG like protein  
Shewanella baltica OS155 (Sh.ba.I1) none  
 Archaebacteria Methanococcoides burtonii DSM 6242 
 (Mc.b.I1-1)
RNA-directed DNA 
polymerase 
 
  Methanosarcina acetivorans (M.a.I1-1) Conserved region 
(species) 
 
  Methanosarcina acetivorans (M.a.I1-2) ORF of M.a.I3  
Methanosarcina mazei (M.m.I1) Transposase  
  Uncultured archaeon GZfos26G2 (UA.I1) none  
Uncultured archaeon GZfos28G7  (UA.I5) none  
  Methanospirillum hungatei (Me.hu.I2) none  
 124
Intron Class Organism Class Species Host gene Intron 
  Uncultured archaeon GZfos14B8 (UA.I4) none  
Methanosarcina acetivorans (M.a.I5-1) ORF of M.a.I1-3  
  Methanosarcina acetivorans (M.a.I5-3) ORF of M.a.I1-2  
 
Figure 1. The secondary structures of 14 discovered tRNA in the mitochondrial genome 
of Endomyzostoma sp.. 
 125
 
 126
 
Figure 2. (A) Insertion locations of both Mintron1 and Mintron2 in the cox1 gene. The 
dot line on the left end of cox1 gene means this region was not recovered. (B) Secondary 
structure of Mintron1. Domain 4 contains the ORF. (C) Secondary structure of Mintron2. 
The stars label the conserved nucleotides in the central core as the major features of 
group IIA1 subclass which is the mitochondrial class. ORF, open reading frame; EBS, 
exon binding sequences; IBS, intron binding sequences. 
 127
 
Figure 3. (A) Intron-encoded ORF domain structure. (modified from Zimmerly et al., 
2001; Fig1A). (B) Alignment of subdomain 4 region of RT domain and one conserved 
region in X domain. The most conserved amino acids were identified by Gblocks 
showing as the black bars. The representative ORFs from each major category (three 
mitochondrial, two chloroplast and four bacteria) were selected to align with the ORFs 
from both Mintron1 and Nephtys group II intron. The purple bars are showing the most 
conserved regions across all ORFs. Species abbreviations are as follows: M.m.I1, 
Methanosarcina mazei; A.v.I1, Azotobacter vinelandii; W.e.I2, Wolbachia endosymbiont 
of Drosophila melanogaster; Kl.pn.I1, Klebsiella pneumoniae isolate YMC. The intron 
category labels: Bac, Bacteria; Chl, Chloroplast; Mt, Mitochondrion.  Other information 
about the taxa see table 4. 
 128
 
 129
Figure 4. Phylogenetic analyses of 105 group II intron ORFs by the MrBayes program. 
Taxa sampling included all mitochondrial and chloroplast group II ORFs and some 
representatives of bacterial classes (table 4). Dark shades are the mitochondrial group II 
introns including the Mintron1 and Nephtys ORFs (showing as bold font). Light shade is 
the chloroplast group II intron lineage. All other unshaded are the group II intron ORFs 
found in bacteria. Archaebacterial taxa were used as outgroups. 
? 130
CHAPTER 5 
CONCLUSIONS 
? 131
1. Mitochondrial genomes and phylogenetic relationships within terebelliformia 
group 
Over the past few decades, phylogenetic relationships within annelids have been a 
disputed topic with a growing interest from many researchers (e.g. Rouse and Fauchald, 
1997; Bleidorn et al., 2003; McHugh, 2005; Rousset et al., 2006; Struck et al., 2007).  
Differences in data used for analyses, such as morphology or various molecular loci, can 
cause such phylogenetic discrepancies. In order to resolve this issue, current tendency is 
to use multiple-genes, and even genomic datasets (e.g, mitochondrial genome or 
Expressed Sequence Taq data) to develop robust phylogenentic hypotheses (Bleidorn et 
al., 2006; Zhong et al., 2008). Our study proposed a phylogenetic reconstruction among 
five families of Terebelliformia annelids by using data from the mitochondrial genome.  
Mitochondrial genomes were sequenced from six worms, representitive of five 
recognized Terebelliformia families. For two of species examined, UNK regions of the 
mitochondrial genomes were fully described. By comparison, the complete UNK regions 
in both Terebellides stroemi (Trichobranchidae) and Pista cristata (Terebellidae) are AT 
rich and consist microsatellite-like sequences which could form complicated secondary 
structures to affect the ability of polymerases during amplification or sequencing (see 
also Boore and Brown, 2000; Jennings and Halanych, 2005; Bleidorn et al., 2006; Zhong 
et al., 2008).  
? 132
The data recovered for Terebelliformia mitochondrial gene order fits previous hypotheses 
of conserved gene order among protein-coding genes in annelida (Jennings and 
Halanych, 2005; Vall?s and Boore, 2006; Bleidorn et al., 2006). Although 
rearrangements are observed for tRNA genes and UNK regions., mitochondrial gene 
order, within annelids, offers limited phylogenetic signal. Exceptions to this observation 
are the presence of a trnM duplication present in a terebellid, trichobranchid and 
pectinariid as well as a variable protein-coding gene order in atp6-mSSU region only 
found in ampharetids.  
Based on the mtDNA data, maximum likelihood and Bayesian inference 
approaches were used to reconstruct the tree topolog for both mitochondrial nucleotide 
and amino acid data. Both resultant trees have an identical topology within 
Terebelliformia groups with high nodal support values, suggesting well-resolved 
relationships among the five families based on mtDNA data. The results herein not only 
provide a phylogenetic hypothesis for Terebelliformia groups, but also indicate that 
mitochondrial genomes could be a useful tool for understanding phylogenetic 
relationships within annelids, especially when combined with other sources of data, such 
as nuclear markers. Moreover, as our efficiency of sequencing mtDNA genomes 
continues to improve, additional sampling will be essential to more thoroughly elucidate 
annelid phylogenetic relationships. 
2. The mitochondrial genome of a Myzostomida worm and group II introns 
Group II introns are self-splicing ribozymes that have only recently been reported 
in bilaterian animals (Vall?s et al., 2008, in a Nephtys annelid).  My studies discovered 
? 133
two group II introns in a partial mitochondrial genome of an Endomyzostoma 
(Myzostomida) worm. The protein-coding and rRNA gene order in mtDNA of 
Endomyzostom sp. matches another Myzostomida worm, Myzostoma 
seymourcollegiorum, which lacks such introns (Bleidorn et al., 2007). And both share the 
same protein-coding gene arrangement pattern as the majority published annelids (Vall?s 
and Boore, 2006; Zhong et al., 2008), further supporting the hypothesis of an annelid 
origin of myzostomids. 
This is the first study to describe multiple group II introns found in a bilaterian 
genome. Two group II introns, named as Mintron1 and Mintron2, were identified in cox1 
gene. The similarity of the insertion site between Mintron1 and Nephtys? intron implies 
the susceptible region in annelid cox1 genes for the group II intron recognization.  My 
work focused on characterizing the secondary structures of the introns, which holds 
implications for self-splicing and retrohoming ability.  Mintron2 lacks of an Open 
Reading Frame (ORF) and therefore presumably lacks retrohoming mobility. It could 
perform splicing ability in vivo by recruitment of some host proteins to keep the activity 
of the cox1 gene. Based on its contracted secondary structure and it has lost retrohoming 
capability, I predicted Mintron2 is undergoing evolutionary degeneration. Mintron1, 
however, possesses an ORF in D4 domain with only RT and X domains, inferring that it 
can presumably accomplish reverse splicing in vivo. But needs to insert into the 
replication fork to assist itself synthesize the double strand DNA for retrotransposition 
due to lacking of both D and En domains in the ORF (Zhong and Lambowitz, 2003). 
Despite there are several conserved regions found in the ORF, phylogenetic analyses 
? 134
showed Mintron1 is a divergent group II intron related to the other group II intron in 
Nephtys.  
In conclusion, the study indicated it is unquestionable to be very informative for 
the family level phylogenetic analyses using mitochondrial genome data. Future work 
would be focused phylogenetic reconstruction based on the combination datasets with 
nuclear markers as well as the large sampling of each Terebelliformia family. In terms of 
group II introns, the continuous work into their evolutionary and functional significance 
in bilaterian genomes is needed. 
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