Research Article Signs of Selection in Synonymous Sites of ...downloads.hindawi.com/journals/bmri/2015/387913.pdfGreenIdye(BioDye,Russia), M of each dNTP, pmol ofeachprimer,and ngtemplateDNA.e

Research ArticleSigns of Selection in Synonymous Sites of the MitochondrialCytochrome b Gene of Baikal Oilfish (Comephoridae) by mRNASecondary Structure Alterations

Veronika I Teterina Anatoliy M Mamontov Lyubov V Sukhanova and Sergei V Kirilchik

Limnological Institute Siberian Branch Russian Academy of Sciences PO Box 278 Irkutsk 664033 Russia

Correspondence should be addressed to Veronika I Teterina veronikalinirkru

Received 10 July 2014 Revised 10 November 2014 Accepted 10 November 2014

Academic Editor Peter F Stadler

Copyright copy 2015 Veronika I Teterina et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Studies over the past decade have shown a significant role of synonymous mutations in posttranscriptional regulation of geneexpression which is particularly associated with messenger RNA (mRNA) secondary structure alterations Most studies focusedon prokaryote genomes and the nuclear genomes of eukaryotes while little is known about the regulation of mitochondrial DNA(mtDNA) gene expressionThis paper reveals signs of selection in synonymous sites of themitochondrial cytochrome b gene (Cytb)of Baikal oilfish or golomyankas (Comephoridae) directed towards altering the secondary structure of the mRNA and probablyaltering the character of mtDNA gene expression Our findings are based on comparisons of intraspecific genetic variation patternsof small golomyanka (Comephorus dybowski) and two genetic groups of big golomyanka (Comephorus dybowskii) Two approacheswere used (i) analysis of the distribution of synonymous mutations between weak-AT (W) and strong-GC (S) nucleotides withinspecies and groups in accordance with mutation directions from central to peripheral haplotypes and (ii) approaches based on thepredicted mRNA secondary structure

1 Introduction

Recent studies have shown a significant role of synonymoussites in the regulation of gene expression and fitness [1ndash5] Synonymous mutations influence not only the rate oftranslation but also posttranslationalmodification of proteins[6] One form of such regulation involves alterations of thesecondary structure of messenger RNA (mRNA)The impactof synonymous codon sites on mRNA stability folding andconsequently gene expression is greater than the impactof nonsynonymous codon sites [4 7] and can therefore beexposed to various forms of natural selection more thanpreviously believed To date most studies of the effects ofsynonymous mutations on gene expression have focused onprokaryote genomes and the nuclear genome of eukaryoteswhile virtually little is known at the mitochondrial DNA(mtDNA) level Meanwhile the identification of signs ofselection in synonymous sites of mitochondrial genes innatural objects can be an area of focus for understanding

these processes Baikal oilfish can be considered such anobject

Big golomyanka (BG) or big Baikal oilfish (Comephorusbaicalensis) and small golomyanka (SG) or little Baikal oilfish(Comephorus dybowskii) are the only representatives of theendemic genus Comephorus of the Comephoridae family ofLake Baikal cottoid fish [8] The habitats of these specieslargely overlap representatives of BG and SG are distributedthroughout Lake Baikal with the exception of the coastalzone and are found at all depths of the lake Baikal oilfishare the most abundant fish in Lake Baikal According toStarikov [9] the numbers of SG and BG were approximately222ndash412 and 71ndash108 billion specimens respectively for theperiod of 1969 to 1972 These species are very adapted tothe pelagic lifestyle of an open lake This is reflected in thefact that golomyankas are extremely sensitive to changes inenvironmental conditions The optimum water temperaturefor these species is sim36∘C During experiments when thetemperature rose above 80ndash85∘C BG instantly fell into

Hindawi Publishing CorporationBioMed Research InternationalVolume 2015 Article ID 387913 8 pageshttpdxdoiorg1011552015387913

2 BioMed Research International

Ancestor

BGa

BGp

SG

Figure 1 Schematic representation of the network of Baikal oilfishobtained by Teterina et al [15] Dark circle diameters are propor-tional to the frequencies of the main haplotypes of Cytb within thegroups and grey circle diameters are proportional to the respectivevalues of nucleotide diversity (120587)

a stupor and began to die [10] Both species are viviparousBG breeds throughout the year with two peaks of spawningin August September and December [11ndash13]

As previously demonstrated there are two genetic groupsof BG that differ by two nucleotide substitutions in themitochondrial cytochrome b gene (Cytb) [15] One group isrepresented by the line of ancestral haplotypes (BGa) whileanother is paraphyletically related to BGa (BGp) BGp andSG are derived from the central haplotype of BGa (Figure 1)Nuclear DNA analysis and morphological data revealed nodifferences between BGa and BGp It was suggested thatthese groups correspond to the two peaks of BG spawning Itwas also assumed that the differences in mitochondrial DNAare the result of differences in female breeding timing andnuclear genome panmixia is the result of independentmatingof males with females from both genetic groups

This paper showed signs of selection in synonymous sitesof Cytb of Baikal golomyankas directed towards alteringthe secondary structure of the mRNA and probably alteringthe character of mtDNA gene expression We examined thepatterns of Cytb molecular variation with the methods ofprediction of the secondary structure of nucleic acids andused the data on the fishesrsquo life history

2 Materials and Methods

21 Sampling and DNA Extraction Adult specimens weresampled using a beam trawl between 2000 and 2010 in threeLake Baikal basins southern central and northern Larvaewere collected with a large DJOM plankton closing net (2mdiameter 1 vvmesh) in July September and February 2005to 2011 To determine which of the two spawning groups theBG larvae belonged to the body lengths of the larvae weremeasured which allowed approximate determination of theirtime of birth Only individuals with a body length lt20mmwere used Larvae age was approximately assessed as followsindividuals with a body length up to 10mm were gradedas being 1 to 15 months old and specimens with a lengthof 10 to 20mm were considered to be 15 to 3 months old(Elena V Dzyuba LIN SB RAS personal communication)The larvae collected in July and September were attributed tothe ldquosummerrdquo spawning peak whereas the larvae collected inFebruary were attributed to the ldquowinterrdquo maximum

Total DNA was isolated from fish muscle or from wholelarvae using phenol-chloroform extraction [18] An allele-specific real-time polymerase chain reaction (PCR) protocolwas developed to identify individuals belonging to a partic-ular genetic group of BG A similar system was developedto identify BG and SG individuals since species affiliation oflarvae and juveniles cannot always be accurately determinedbased solely on external morphology

22 Single Nucleotide Polymorphism (SNP) Analysis For therapid and reliable separation of the oilfish individuals byspecies and groups SNP markers were designed based onthe same DNA sequences as in [15] The substitutions bywhich the species and the genetic groups were differentiatedare shown in Table 1 To identify the representatives of BGand SG we used the BG-specific forward primer FBG (51015840-ACTACGGATGACTTATCCGTAACC-31015840) and the SG-specific forward primer FSG (51015840-ACTACGGATGACTTA-TCCGTAACAC-31015840) The reverse primer was common inboth cases RBGSG (51015840-TACCCTACGAAAGCGGTTATT-ATTACAA-31015840) To identify the representatives of BGp andBGa we employed the BGp-specific forward primer FBGp(51015840-GCCTGAGTGGTACTTCCTGTTC-31015840) and the (BGa +SG) specific forward primer FBGa (51015840-GCCTGAGTGGTA-CTTCTTGTTT-31015840) Again the reverse primer was the samefor both RBGaBGp (51015840-CTCCAAGTTTGTTGGGGAT-31015840)

Real-time PCR was performed on a Rotor-Gene Q (Qia-gen) in a 15 120583L reaction mixture containing 15U Encyclopolymerase (Evrogen Russia) 15120583L Encyclo buffer 1x SYBRGreen I dye (BioDye Russia) 200120583M of each dNTP 5 pmolof each primer and 5ndash50 ng template DNAThe PCR temper-ature profile involved a 3min denaturation at 95∘C followedby 35 cycles of 10 s at 95∘C and 10 s at 60∘C Each reaction wasconducted at least in triplicate and all runs were completedwith a melt curve analysis

23 Distribution ofMutations Cytb analyses were performedusing largely the same DNA sequences as in [15] supple-mented by nine haplotypes of BGp (GenBank AccessionNumbers KC571825ndashKC571833) Mutation calculations wereperformed according to direction in haplotype genealogy asevaluated by an unrooted network and a statistical parsimonycriterion with NETWORK 46 [19] and using the optionldquostatisticsrdquo The distribution of nucleotide diversity (120587) alongCytb was explored using the Sliding Window Option (SWA)of the program VariScan version 1 [20] The width of thewindow was 100 bp and the window slide was 10 bp

24 Prediction of mRNA Secondary Structure Prediction ofmRNAsecondary structure (RSSP)was performedusing pro-grams UNAFold version 38 [16] and RNAfold of the ViennaRNA Package version 185 [17] Both synonymous andnonsynonymous mutations were used A temperature optionequal to 35∘C (which is close to the natural environmentaltemperature of golomyankas) was chosen to calculate theminimum free energy To calculate distances between RNAsecondary structures 31 runs of RNAfold and RNAdistanceprograms [17] were performed with temperatures ranging

BioMed Research International 3

Table 1 Substitutions segregating SG BGa and BGp and their location in the Cytb

Sympatric groups Substitution positionslowast

15627 15966 16004 16206 16211 16502BGp C A C C C ABGa C A C T T ASG A C T T T GlowastThe substitution positions are given relative to the mitochondrial sequence of Salmo salar [14] (GenBank Accession Number U12143)Substitutions used for SNP analysis in bold

Table 2 Number of BGa and BGp adults collected from the southmiddle and north basins of the lake

Sympatricgroups

Basins of the lake TotalnumberSouth Middle North

BGa 114 19 32 165BGp 108 18 32 158

from 1 to 4∘C and steps equal to 01∘C The chosen tem-perature interval roughly covers the range of golomyankatemperature environments The Fitch-Margoliash methodimplemented in the Fitch program (PHYLIP package version36) was used to generate the series of trees based onthe distance matrices and the Consense program (PHYLIPpackage) was then used to generate a majority rule consensustree [21]The values obtained in the internal edges were inter-preted as branch support measurements Sequence analysistree drawings and tree manipulations were performed usingMEGA version 6 [22]

3 Results

31 SNP Analysis The allele-specific primers were testedusing DNA samples with known Cytb sequences [15] In allcases there was strict conformity between the test resultsand the nucleotide sequence We used this approach todetermine the ratio of individuals belonging to differentgenetic groups of BG collected from different regions of LakeBaikal (Table 2)We also analyzed the larvae born in differentseasons (Table 3) It was evident that the ratio of individualsbelonging to different genetic groups in different basins andin the lake as a whole was close to 1 1 Larvae analysis didnot reveal any clear patterns between the time of birth andaffiliation with a certain genetic group Representatives ofBGa and BGp of the same larval size range were present ineach sample

32 Mutations Bias As can be seen in Table 1 the BGa andBGp haplotypes groups differed in two substitutions locatedat four nucleotides from one another These were the keysubstitutions that formed the main haplotypes of the groupsConsidering the direction from BGa to BGp (Figure 1) bothsubstitutions were from T to C (TrarrC) The TrarrC typepolymorphism was also found at position 15500 (data notshown) where the C nucleotide was present at a very highfrequency in BGp and absent in BGa All substitutions were

synonymous Furthermore we analyzed the amount and dis-tribution of mutations affecting the GC composition of Cytbwhich were mutations of weak-AT (W) or strong-GC (S)nucleotides according to their direction from the central toperipheral haplotypes (Test of Centrifugal Substitution BiasTCSB) within each group (Figure 1 as well as Figure 1 in [15])To reveal more detailed patterns of mutation distributionswithin the Comephoridae family a group of SG haplotypeswas also included in the analysis Nonsynonymousmutationswere excluded from the calculations in five sites within BGpand SG and one site within BGa

TCSB revealed some differences among the studiedgroups (Figure 2) The direction of mutations within BGashowed strong deviation toward theWrarrS typeWithin BGpthe predominance ofWrarrS mutations was much weakerTheSG group demonstrated the opposite pattern the directionto W was prevalent Fisherrsquos exact test failed to show anysignificant differences between BGa and BGp but we foundstatistically significant differences between BGp and SG andvery statistically significant differences between BGa and SG(two-tailed 119875 values of 03073 00147 and 00006 resp)SlidingWindow Analysis (SWA) of Cytb showed that withinBGa WrarrS mutations dominated over SrarrW for almost theentire Cytb gene with two maxima located at sim400 and600 bp (Figure 3)Thus the dominance ofWrarrSmutations inthis group did not appear to be site- or region-specificWithinSG the opposite picture was observed with a few exceptionsSrarrW mutations dominated No clear patterns were foundwithin BGp

33 RNA Secondary Structure As noted above the mainhaplotypes of BGa and BGp were separated by the twosynonymous substitutions TrarrC located in close proximityto each other This probably led to alterations of the localthermodynamic stability of DNA and corresponding mRNATo test how these substitutions could affect mRNA foldingthe secondary structures of mRNA for the main haplotypesof BGa BGp and SG were predicted The mRNA structurespredicted by UNAFold and RNAfold were different forthe same Cytb sequences However both programs showedthat the main haplotypes of BGa and SG had very similarstructures while the structure for BGp was considerablydifferent (Figure 4)

According to the tree based on mRNA structures(Figure 5) BGa and SG haplotypes were largely mixed whilethe representatives of BGpwith few exceptions were arrangedin a more compact manner 15 representatives formed onemonophyletic group Although the reliability of the tree was


Table 3 Number of BGa and BGp larvae sampled in the summer (July September) and winter (February) at height of spawning

July September FebruarySympatric groups Length mm Total number Length mm Total number

lt10 lt10 11ndash15 11ndash15 16ndash20BGa 6 8 1 15 3 7 10BGp 5 7 5 17 6 2 8

BGa BGp

G C

A

T

G

C

G C

A

T

G

C

A T A T A TG C

A

T

G

CSG

From

To

22 068

31 13

2115

8

13

31

21

10

21

10

25

7

32

20

(ATrarrGC)(GCrarrAT)

= 39

Figure 2 Synonymous mutations in Cytb mapped according to their directions from the central to peripheral haplotypes Circle sizes andnumbers indicate the total number of the mutations as percentages

200 400 600 800 1000 1200

001

0008

0006

0004

0002

BGa

Nuc

leot

ide d

iver

sity

(120587)

Base pairs0

0

(a)

20000

400 600 800 1000 1200

001

0008

0006

0004

0002

BGp

Nuc

leot

ide d

iver

sity

(120587)

Base pairs

(b)

200 400 600 800 1000 1200

001

0008

0006

0004

0002

SG

Base pairs

Nuc

leot

ide d

iver

sity

(120587)

00

(c)

Figure 3 Sliding Window Analysis of nucleotide diversity (120587) along the Cytb Bold solid lines indicate WrarrS mutations and thin dashedlines indicate SrarrWmutations


SG BGa BGp

UNAfold

CC

A C

C

A

UU

C U

A

G

RNAfold

CCCC

A

UUUU

C

AC

CU

GA

5998400

5998400

5998400 5

998400

59984003

998400

3998400 3

998400 3998400

3998400

5998400

3998400

dG = minus48855 dG = minus48798 dG = minus48243


Figure 4 mRNA secondary structure of the main haplotypes of Cytb of BGa BGp and SG predicted by UNAFold [16] and RNAfold [17]programs Black and white arrows indicate substitutions between the main haplotypes of BGaharrSG and BGaharrBGp respectively

not evaluated in a traditional way and branch support valueswere not high its pattern could serve as an additional indirectindicator of a nonrandomdistribution of substitutions duringthe formation of genetic polymorphismof the groups (ie theaction of selection)

4 Discussion

Mutational biases and differences in the nucleotide composi-tion of homologous mtDNA sequences in animals and plantsare widely known Several analyses have been performedand various hypotheses have been proposed to explain thesephenomena but the causes remain unclear [23ndash25] TheMtDNA of Baikal oilfish can serve as a good exampleof mutational biases caused by the action of translationalselection

As noted above very little is known about the post-transcriptional regulation of gene expression in synony-mous sites of mtDNA Many tests and methods used tostudy these processes in the nuclear genome have beenineffective for mtDNA Jia and Higgs suggested tests forcontext-dependent mutation and translational selection inmtDNA [26] However these tests could hardly be usedfor phylogenetically closely related species and groups (egBaikal oilfish) especially when the analysis is restricted toa small DNA fragment (Cytb) The approach used here(TCSB + SWA + RSSP + phylogenetic) was definitely notuniversal and did not show absolute proof of translational

selection in the mtDNA of golomyankas Nevertheless therewere serious grounds for such assumptions for the followingreasons the distinguishing feature of the studied objectswas a close phylogenetic proximity of sympatric species andgroups that had similar nucleotide sequence compositionsof mtDNA [15 27] on the one hand and had differentvectors of Cytb mutational processes in the different groupson the other hand (Figure 2) One of our results suggestedthat the distribution of larvae was not consistent with thepreviously proposed hypothesis of the origin of BGa andBGp representatives from different spawning stock [15] andthat the representatives of both BG groups were present inequal amounts in any place within the lake at any time andany age Taking into account the sympatric character of theformation of intraspecific BG and SG genetic structure andsimilar demographic characteristics of BGa and BGp [15]the TCSB and SWA differences obtained could not be fullyexplained by the forces of nonadaptive nature that is forcesthat did not affect the expression of Cytb

There are several ways of regulating gene expression insynonymous sites associated with mRNA folding mRNAstability andmRNA splicing and with preferred synonymouscodons [2 5 7 28] The latter two are apparently not thecase in the mtDNA of most animals [26] The assumptionof translational selection was indirectly confirmed by theresults of the four tests used here TCSB SWA RSSP andphylogenetic analysis

Identified regularities could be associated with theextreme sensitivity of golomyankas to temperature variations


100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast

Figure 5 Fitch-Margoliash consensus tree of the Cytb haplotypes of BGa BGp and SG based on genetic distances betweenmRNA secondarystructures Haplotypes are shown as GenBank Accession Numbers Small letters represent SG large black letters represent BGa large whiteletters in black rectangles represent BGp Asterisks indicate the main haplotypes Numbers indicate percentage support values

[10] It is known for example that the initial stages of thermalalterations in the intensity of oxidative phosphorylation incardiac muscle cells of Atlantic wolffish occur in enzymaticcomplex III which includes the cytochrome b protein [29]It can be assumed that the synonymous diversity of Cytbwithin the species and groups of golomyankas could beformed to some extent as a result of the selection pressureof different intensities and directions We assumed that thegenetic diversity within BGa was apparently formed underthe action of selection that was directional with respect tothe type of mutations against W nucleotides and diversifyingwith respect to mutation localization (Figure 3) It is possiblethat selection was associated with the expression of elec-tron transport chain genes by altering the thermodynamic

characteristics of the mRNA and consequent refolding Thecompactness of BGp on the tree (Figure 5) could indicatean increasing role of a stabilizing selection which supportsa specific mRNA structure It can be assumed from the twosubstitutions that separate BGa and BGp made it possible forthe representatives of BGp to obtain a partial selective advan-tage acting for example only under certain environmentalconditions so that the total domination of BGp haplotypeswithin BG did not occur In that case the formation ofBGp could have happened very quickly in geological timescales and much earlier than the emergence of SG Thiscould explain some of the discrepancies between the levelsof nucleotide diversity within the groups and the number ofsubstitutions between them For SG and BGp which have


passed through the bottleneck stage and currently have alarge population size [9 15] one would expect a positivecorrelation to some extent between the distance from theancestral line (BGaharrBGp BGaharr SG) and the magnitudeof nucleotide diversity However we actually observed aninverse relationship (Figure 1)

One more important result of this work was thatgolomyankas could serve as a valuable data source for furtherstudy of the regulation of mtDNA gene expression and therole of synonymous substitutions in these processes

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors are grateful to I V Khanaev for his helpwith sampling and to E V Dzyuba for valuable discus-sion This work was supported by Budget Research Projectsno VI5014 and in part by the Russian Foundation forBasic Research (Grant nos 08-04-01434-a and 08-04-10123-k) Language support was provided by The CharlesworthGroup Author Services (httpwwwcharlesworthauthorser-vicescom)

References

[1] J V Chamary J L Parmley and L D Hurst ldquoHearing silencenon-neutral evolution at synonymous sites in mammalsrdquoNature Reviews Genetics vol 7 no 2 pp 98ndash108 2006

[2] A G Nackley S A Shabalina I E Tchivileva et alldquoHuman catechol-O-methyltransferase haplotypes modulateprotein expression by altering mRNA secondary structurerdquoScience vol 314 no 5807 pp 1930ndash1933 2006

[3] A A Komar ldquoSNPs silent but not invisiblerdquo Science vol 315no 5811 pp 466ndash467 2007

[4] J L Parmley and L D Hurst ldquoHow do synonymous mutationsaffect fitnessrdquo BioEssays vol 29 no 6 pp 515ndash519 2007

[5] S A Shabalina N A Spiridonov and A Kashina ldquoSoundsof silence synonymous nucleotides as a key to biologicalregulation and complexityrdquo Nucleic Acids Research vol 41 no4 pp 2073ndash2094 2013

[6] C Kimchi-Sarfaty J M Oh I-W Kim et al ldquoA ldquosilentrdquopolymorphism in theMDR1 gene changes substrate specificityrdquoScience vol 315 no 5811 pp 525ndash528 2007

[7] S A Shabalina A Y Ogurtsov and N A Spiridonov ldquoAperiodic pattern of mRNA secondary structure created by thegenetic coderdquo Nucleic Acids Research vol 34 no 8 pp 2428ndash2437 2006

[8] V G Sideleva The Endemic Fishes of Lake Baikal BackhuysPublishers Leiden The Netherlands 2003

[9] G V Starikov Lake Baikal Golomyanka Nauka NovosibirskRussia 1977 (Russian)

[10] D N Taliev Lake Baikal Sculpins (Cottoidei) USSRAcademy ofSciences Moscow Russia 1955 (Russian)

[11] Z A Chernyaev ldquoMorphoecological peculiarities of reproduc-tion and growth of big golomyanka Comephorus baicalensis(Pallas)rdquo Journal of Ichthyology vol 14 pp 990ndash1003 1974

[12] L V Zubina L V Dzyuba and A N Zaitseva ldquoAre we real wit-nesses of life cycle transformation of hydrobionts (case studyLake Baikal golomyanka)rdquo in Recent Problems of Hydrobiologyin Siberia V I Romanov Ed pp 40ndash41 Tomsk StateUniversityTomsk Russia 2001 (Russian)

[13] E V Dzyuba ldquoTwo coexisting species of Baikal golomyankasComephorus baicalensis and C dybowski Seasonal dynamics ofjuveniles and their feedingrdquo Hydrobiologia vol 568 no 1 pp111ndash114 2006

[14] C D Hurst S E Bartlett W S Davidson and I J Bruce ldquoThecomplete mitochondrial DNA sequence of the Atlantic salmonSalmo salarrdquo Gene vol 239 no 2 pp 237ndash242 1999

[15] V I Teterina L V Sukhanova and S V Kirilchik ldquoMoleculardivergence and speciation of Baikal oilfish (Comephoridae)facts and hypothesesrdquo Molecular Phylogenetics and Evolutionvol 56 no 1 pp 336ndash342 2010

[16] N R Markham and M Zuker ldquoUNAFold software for nucleicacid folding and hybridizationrdquo Methods in Molecular Biologyvol 453 pp 3ndash31 2008

[17] I L Hofacker W Fontana P F Stadler L S BonhoefferM Tacker and P Schuster ldquoFast folding and comparison ofRNA secondary structuresrdquo Monatshefte fur Chemie ChemicalMonthly vol 125 no 2 pp 167ndash188 1989

[18] J Sambrook E P Fritsch and T Maniatis Molecular CloningLaboratoryManual Cold SpringHarbor Laboratory Press NewYork NY USA 1989

[19] H-J Bandelt P Forster andA Rohl ldquoMedian-joining networksfor inferring intraspecific phylogeniesrdquo Molecular Biology andEvolution vol 16 no 1 pp 37ndash48 1999

[20] A J Vilella A Blanco-Garcia S Hutter and J RozasldquoVariScan analysis of evolutionary patterns from large-scaleDNA sequence polymorphism datardquo Bioinformatics vol 21 no11 pp 2791ndash2793 2005

[21] J Felsenstein ldquoPHYLIPmdashphylogeny inference package (version32)rdquo Cladistics vol 5 pp 164ndash166 1989

[22] K Tamura G Stecher D Peterson A Filipski and S KumarldquoMEGA6molecular evolutionary genetics analysis version 60rdquoMolecular Biology and Evolution vol 30 no 12 pp 2725ndash27292013

[23] K Tamura ldquoThe rate and pattern of nucleotide substitutionin Drosophila mitochondrial DNArdquo Molecular Biology andEvolution vol 9 no 5 pp 814ndash825 1992

[24] JWO Ballard ldquoComparative genomics ofmitochondrial DNAin members of the Drosophila melanogaster subgrouprdquo Journalof Molecular Evolution vol 51 no 1 pp 48ndash63 2000

[25] C Haag-Liautard N Coffey D Houle M Lynch BCharlesworth and P D Keightley ldquoDirect estimation of themitochondrial DNAmutation rate inDrosophila melanogasterrdquoPLoS Biology vol 6 no 8 article e204 2008

[26] W Jia and PGHiggs ldquoCodon usage inmitochondrial genomesdistinguishing context-dependent mutation from translationalselectionrdquo Molecular Biology and Evolution vol 25 no 2 pp339ndash351 2008

[27] T Kontula S V Kirilchik andRVainola ldquoEndemic diversifica-tion of themonophyletic cottoid fish species flock in LakeBaikal


explored with mtDNA sequencingrdquo Molecular Phylogeneticsand Evolution vol 27 no 1 pp 143ndash155 2003

[28] G Kudla A W Murray D Tollervey and J B PlotkinldquoCoding-sequence determinants of expression in Escherichiacolirdquo Science vol 324 no 5924 pp 255ndash258 2009

[29] H Lemieux J-C Tardif J-D Dutil and P U Blier ldquoTher-mal sensitivity of cardiac mitochondrial metabolism in anectothermic species from a cold environment Atlantic wolffish(Anarhichas lupus)rdquo Journal of Experimental Marine Biologyand Ecology vol 384 no 1-2 pp 113ndash118 2010

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Ancestor

BGa

BGp

SG

Figure 1 Schematic representation of the network of Baikal oilfishobtained by Teterina et al [15] Dark circle diameters are propor-tional to the frequencies of the main haplotypes of Cytb within thegroups and grey circle diameters are proportional to the respectivevalues of nucleotide diversity (120587)

a stupor and began to die [10] Both species are viviparousBG breeds throughout the year with two peaks of spawningin August September and December [11ndash13]

As previously demonstrated there are two genetic groupsof BG that differ by two nucleotide substitutions in themitochondrial cytochrome b gene (Cytb) [15] One group isrepresented by the line of ancestral haplotypes (BGa) whileanother is paraphyletically related to BGa (BGp) BGp andSG are derived from the central haplotype of BGa (Figure 1)Nuclear DNA analysis and morphological data revealed nodifferences between BGa and BGp It was suggested thatthese groups correspond to the two peaks of BG spawning Itwas also assumed that the differences in mitochondrial DNAare the result of differences in female breeding timing andnuclear genome panmixia is the result of independentmatingof males with females from both genetic groups

This paper showed signs of selection in synonymous sitesof Cytb of Baikal golomyankas directed towards alteringthe secondary structure of the mRNA and probably alteringthe character of mtDNA gene expression We examined thepatterns of Cytb molecular variation with the methods ofprediction of the secondary structure of nucleic acids andused the data on the fishesrsquo life history

2 Materials and Methods

21 Sampling and DNA Extraction Adult specimens weresampled using a beam trawl between 2000 and 2010 in threeLake Baikal basins southern central and northern Larvaewere collected with a large DJOM plankton closing net (2mdiameter 1 vvmesh) in July September and February 2005to 2011 To determine which of the two spawning groups theBG larvae belonged to the body lengths of the larvae weremeasured which allowed approximate determination of theirtime of birth Only individuals with a body length lt20mmwere used Larvae age was approximately assessed as followsindividuals with a body length up to 10mm were gradedas being 1 to 15 months old and specimens with a lengthof 10 to 20mm were considered to be 15 to 3 months old(Elena V Dzyuba LIN SB RAS personal communication)The larvae collected in July and September were attributed tothe ldquosummerrdquo spawning peak whereas the larvae collected inFebruary were attributed to the ldquowinterrdquo maximum

Total DNA was isolated from fish muscle or from wholelarvae using phenol-chloroform extraction [18] An allele-specific real-time polymerase chain reaction (PCR) protocolwas developed to identify individuals belonging to a partic-ular genetic group of BG A similar system was developedto identify BG and SG individuals since species affiliation oflarvae and juveniles cannot always be accurately determinedbased solely on external morphology

22 Single Nucleotide Polymorphism (SNP) Analysis For therapid and reliable separation of the oilfish individuals byspecies and groups SNP markers were designed based onthe same DNA sequences as in [15] The substitutions bywhich the species and the genetic groups were differentiatedare shown in Table 1 To identify the representatives of BGand SG we used the BG-specific forward primer FBG (51015840-ACTACGGATGACTTATCCGTAACC-31015840) and the SG-specific forward primer FSG (51015840-ACTACGGATGACTTA-TCCGTAACAC-31015840) The reverse primer was common inboth cases RBGSG (51015840-TACCCTACGAAAGCGGTTATT-ATTACAA-31015840) To identify the representatives of BGp andBGa we employed the BGp-specific forward primer FBGp(51015840-GCCTGAGTGGTACTTCCTGTTC-31015840) and the (BGa +SG) specific forward primer FBGa (51015840-GCCTGAGTGGTA-CTTCTTGTTT-31015840) Again the reverse primer was the samefor both RBGaBGp (51015840-CTCCAAGTTTGTTGGGGAT-31015840)

Real-time PCR was performed on a Rotor-Gene Q (Qia-gen) in a 15 120583L reaction mixture containing 15U Encyclopolymerase (Evrogen Russia) 15120583L Encyclo buffer 1x SYBRGreen I dye (BioDye Russia) 200120583M of each dNTP 5 pmolof each primer and 5ndash50 ng template DNAThe PCR temper-ature profile involved a 3min denaturation at 95∘C followedby 35 cycles of 10 s at 95∘C and 10 s at 60∘C Each reaction wasconducted at least in triplicate and all runs were completedwith a melt curve analysis

23 Distribution ofMutations Cytb analyses were performedusing largely the same DNA sequences as in [15] supple-mented by nine haplotypes of BGp (GenBank AccessionNumbers KC571825ndashKC571833) Mutation calculations wereperformed according to direction in haplotype genealogy asevaluated by an unrooted network and a statistical parsimonycriterion with NETWORK 46 [19] and using the optionldquostatisticsrdquo The distribution of nucleotide diversity (120587) alongCytb was explored using the Sliding Window Option (SWA)of the program VariScan version 1 [20] The width of thewindow was 100 bp and the window slide was 10 bp

24 Prediction of mRNA Secondary Structure Prediction ofmRNAsecondary structure (RSSP)was performedusing pro-grams UNAFold version 38 [16] and RNAfold of the ViennaRNA Package version 185 [17] Both synonymous andnonsynonymous mutations were used A temperature optionequal to 35∘C (which is close to the natural environmentaltemperature of golomyankas) was chosen to calculate theminimum free energy To calculate distances between RNAsecondary structures 31 runs of RNAfold and RNAdistanceprograms [17] were performed with temperatures ranging






Sympatricgroups


BGa 114 19 32 165BGp 108 18 32 158


3 Results











BGa BGp

G C

A

T

G

C

G C

A

T

G

C

A T A T A TG C

A

T

G

CSG

From

To

22 068

31 13

2115

8

13

31

21

10

21

10

25

7

32

20


= 39


200 400 600 800 1000 1200

001

0008

0006

0004

0002

BGa

Nuc

leot

ide d

iver

sity

(120587)

Base pairs0

0

(a)

20000

400 600 800 1000 1200

001

0008

0006

0004

0002

BGp

Nuc

leot

ide d

iver

sity

(120587)

Base pairs

(b)

200 400 600 800 1000 1200

001

0008

0006

0004

0002

SG

Base pairs

Nuc

leot

ide d

iver

sity

(120587)

00

(c)



SG BGa BGp

UNAfold

CC

A C

C

A

UU

C U

A

G

RNAfold

CCCC

A

UUUU

C

AC

CU

GA

5998400

5998400

5998400 5

998400

59984003

998400

3998400 3

998400 3998400

3998400

5998400

3998400





4 Discussion







100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast









Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology






Sympatricgroups


BGa 114 19 32 165BGp 108 18 32 158


3 Results











BGa BGp

G C

A

T

G

C

G C

A

T

G

C

A T A T A TG C

A

T

G

CSG

From

To

22 068

31 13

2115

8

13

31

21

10

21

10

25

7

32

20


= 39


200 400 600 800 1000 1200

001

0008

0006

0004

0002

BGa

Nuc

leot

ide d

iver

sity

(120587)

Base pairs0

0

(a)

20000

400 600 800 1000 1200

001

0008

0006

0004

0002

BGp

Nuc

leot

ide d

iver

sity

(120587)

Base pairs

(b)

200 400 600 800 1000 1200

001

0008

0006

0004

0002

SG

Base pairs

Nuc

leot

ide d

iver

sity

(120587)

00

(c)



SG BGa BGp

UNAfold

CC

A C

C

A

UU

C U

A

G

RNAfold

CCCC

A

UUUU

C

AC

CU

GA

5998400

5998400

5998400 5

998400

59984003

998400

3998400 3

998400 3998400

3998400

5998400

3998400





4 Discussion







100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast









Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology





BGa BGp

G C

A

T

G

C

G C

A

T

G

C

A T A T A TG C

A

T

G

CSG

From

To

22 068

31 13

2115

8

13

31

21

10

21

10

25

7

32

20


= 39


200 400 600 800 1000 1200

001

0008

0006

0004

0002

BGa

Nuc

leot

ide d

iver

sity

(120587)

Base pairs0

0

(a)

20000

400 600 800 1000 1200

001

0008

0006

0004

0002

BGp

Nuc

leot

ide d

iver

sity

(120587)

Base pairs

(b)

200 400 600 800 1000 1200

001

0008

0006

0004

0002

SG

Base pairs

Nuc

leot

ide d

iver

sity

(120587)

00

(c)



SG BGa BGp

UNAfold

CC

A C

C

A

UU

C U

A

G

RNAfold

CCCC

A

UUUU

C

AC

CU

GA

5998400

5998400

5998400 5

998400

59984003

998400

3998400 3

998400 3998400

3998400

5998400

3998400





4 Discussion







100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast









Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


SG BGa BGp

UNAfold

CC

A C

C

A

UU

C U

A

G

RNAfold

CCCC

A

UUUU

C

AC

CU

GA

5998400

5998400

5998400 5

998400

59984003

998400

3998400 3

998400 3998400

3998400

5998400

3998400





4 Discussion







100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast









Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


100

51

3251

51

5154

100

32

64

64

61

61

100

70

100

EU69

9793

EU69

9804

EU69

9772

EU69

9799

EU69

3113

EU69

9795

EU69

3109

EU69

3101

EU69

3110

EU6930

92

EU6930

95

EU693102

EU693084

EU693086

EU693094

EU693090

AY116356

EU693085

EU693105

EU693082EU693115EU693098

EU699791EU693108EU699783EU693112EU693100EU693097EU699805

EU693111EU693083EU693088

EU693107

EU699787

EU693106EU699784

EU699802

EU693087

EU699781

EU699800

EU693091

EU699778

EU69

3099

EU69

9788

EU69

9786

EU69

9780

EU69

3114

EU69

9808

EU69

3089

EU693103

EU699774EU699790KC571827

KC571826

KC571828

EU699792

EU699794

KC571833

AY116355

EU693096

EU693104EU693093

EU699775EU699807

EU699785

EU69

9779

EU69

9797

EU69

9782EU69

9789

KC5718

30

KC571831EU699803EU699796EU699777EU699806

EU699776

KC571832

EU699773

EU699798

EU699801

KC571829

KC571825

45

45

32

4141 29 25

lowast

lowast

lowast









Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology






Acknowledgments


References







































Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology












Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology








Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology

Documents

Research Article Signs of Selection in Synonymous Sites of ...downloads.hindawi.com/journals/bmri/2015/387913.pdfGreenIdye(BioDye,Russia), M of each dNTP, pmol ofeachprimer,and ngtemplateDNA.e