Department of ZoologyMaharshi Dayanand UniversityRohtak - 124001 (Haryana)www:mdurohtak.com

Publication data

Reviewed Proceedings of ,NationalSeminar on NGSV (2014)ISBN : 978-81-920945-4-0

is the science of estimating certain keypopulation dynamics parameters inorder to manage fishery resourceseffectively. Stock structure studies arenecessdry'for. designing appropriatemanagement regulations in fishbrieswhere multiple stocks are difFerentiallyexploited (Ricker 1981). Stockidentification is vital to stockassessment as stocks cannot beassessed unless their boundaries are

Next Generation Sciences: Vision 2020 and Beyond

Microsatellites : An Overview with Referenceto Fish Stock ldentification

Aafaq Nazir and M. Atzal Khan*Section of Fishery Science & Aquaculture, Department of. Zoology,

Aligarh Muslim University, Aligarh - 202 002 (U.p.), tndia.*Corresponding Author : khanmafzal@yahoo.com

Received

Revisedreceived

Accepted

12.4.14

08.6.14

10.8.14

AbstractThe proper management decisions in fisheries are based onknowledge of fish stock structure. However, to set the boundariesof stocks in marine or freshwater environments is a complicatedand difficult assignment. lnformation on fish stocks is requiredto meet the objectives of effective fisheries management toachieve sustainable yield, as well as to protect threatened andendangered species. Microsatellites are repetitive nuclear DNAsequences that are being commonly used in fish stockidentification studles largely due to their relatively small size,abundance, co dominance, very high levels of variability thathave been observed and investigated using pCR technology,and data reliability. The microsatellite markers used in stockidentification studies usually are di-, tri- or tetra- nucleotides. Themajority of microsatellites (30-65%) found are dinucleotides andare somewhat easier to isolate than longer tri- andtetranucleotides. The popularity of microsatellite maikers is largelydue to moderate to high levels of allelic diversity observed atindividual microsatellite loci. Usually 4-10 microsatellite loci arescreened in stock identification studies, because the most lociare unlinked and inherited independently. The flanking region isthe DNA surrounding a microsatellite locus and this region isgenerally conserved across individuals of the same species, aparticular microsatellite locus can often be identified by its flankingregion. The present paper presents an overview on microsatellitedistribution; evolution; isolation and amplification; and itsapplication in fish stock identification.

Keywords: Fish stock, microsatellite DNA, hypervariation

l

1i

lntroduction

A stock is a discrete entity with its ownphysical life history, naturaldemographic influences, complete-to-partial isolation, and abundances.Stocks are random group of fishes thatare essentially self-reproducing, withmembers of each group having similarlife history features (Hilborn andWalters 1992). Fish stock assessment

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defined in relation to other stocks ofthe same species. Larkin (1972)defined stock "a population oforganisms which share a commongene pool and sufficiently discrete tobe considered as a self-per,petuatingsystem which can be managed". Themost robust definition and sufficientlyspecific to be useful, was provided bylhssen et al. (1981) who proposed thata stobk is "an intraspecific group ofrandomly mating individuals withtemporal or spatial integrity". Thisdefinition is operational at whateverlevel temporal or spatial integrity isdisplayed.

Studies on fish stock identification areon quantitative genetic traits, typicallycontrolled by rnany genes and affectedby the environment'in which thosegenes are expressed. Morphometric(Truss network) analysis providesinformation on groups of individualswith similar growth, reproductive rate,and mortality (Booke 1981). The useof morphometric landmark charactersto identify phenotypic stocks is veryold, but recent advances like imagingand analytical techniques have boostedthe ability of rnorphor.netric analysis forf ish stock identif ication andcomposition. The elementalcomposition of otoliths often serve asa natural marker as it is metabolicallyinert (Campana and Neilson 1985)anduptake of trace elements onto thegrowing otolith shows the physical andchemical environment (Gallahar andKingsford 1996), therefore thesestructures'ii're used to identify fishstocks (Campana et aI.1999; Kennedyet al. 2000; Secor et al. 2@1; and Khanet al. 2012\. The elemental compositionof otoliths tend to be physically stable,reproducible, and different amongstocks,, but are not necessarily stableover long time and thus, they do notact as substitute for genetic identity.

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Different species of fishes havecharacteristic fatty acid profiles(Ackman 1980), therefore the fatty acidprofiles serve as natural marker for fishstock identification. The application offatty acid profiles for identifcation isbased on two purposes, one is thatdiet affects the composition of fattyacids and other is the composition offatty acids in membrane phospholipidsthat is genetically controlled and stableover time. The phospholipid fatty acidmay therefore be used as abiochemical marker over a longertimescale. Several moleculartechniques have been developed todirectly examine genetic variationswithin and between groups (e.9.allozymes, mitochondrial DNA, RFLP,RAPD, AFLP, microsatellite DNA, andsingle nucleotide polymorphism).Allozymes are used as markersbecause of polymorphism and allelicvariants of proteins produced by singlelocus. The observed allozyme variationfollows Mendalian inheritance patternaccording to which two alleles of eachgene are inherited from both parents.Starch gel electrophoresis of allozymeshas been commonly used in fisherygenetics (Ryman and Utter 1987; Hillset al. 1996). The technique is rapid,relatively inexpensive and provides anestimate of level of variation withinpopulation without morphologicalsurvey. The sequence divergenceaccumulates rapidly in mitochondrialDNA than nuclear DNA in vertebrates(Brown 1985). The mitochondrial DNAloci display large number of alleles perloci than allozymes but lower thanhighly variable nuclear markers, suchas RAPD,'rnicrosatelliies, and SNP.The mitochondrial DNA must beconsidered a single locus in geneticstudies due to its non-Mendelian modeof inheritance (Avise 1994). Due to itsrapid rate of evolution, themitochondrial DNA analysis has proven

useful in clarifying relationships among

closelY related sPecies' ln RFLP'

digestion of DNA with restriction

"n-ryr"t results in fragments whose

number and size varY amongindividuals, populations, and species'

CommonlY, fragments are seParated

using Southern blot analysis (Southern

1976). The RFLP markers are co-

dominant and scoring is easy as slze

difference is often large but low level

of polymorPhism is observed' RAPD

tecfrnique enables the detection of DNA

polymorphism bv amplifvins lT!"TJyselected regions of DNA bY PCR with

single random Primers' Other

adv-ntages of.RAPDs include the ease

with wh'rch a large number of loci and

individuals can be screenedsimultaneously. The probability of

amplifying multiple products is large

and each product represents a different

locu's as primers are short with low

Snnealing ternperature. AFLP is a PCR-

based technique that combines the*advantales of RFLP and RAPD

methods. ln AFLP, the DNA is digested

with restriction enzymes, the sequence

of the resulting DNA fragments are

unknown and adaPtors of known

sequence are ligated to the ends of

the DNA fragments to generate primer-

binding sites for PCR amplification'

AFL.P markers are inherited as

dominant markers and provide a much

greater level of polymorphism (Liu and

Lordes 2OO4). With the beginning of

DNA sequencing in 1977, the

sequence differences due to base

substitution have been characterized'Singte Nucleotide PolYmorPhismdesiribes polymorphism due to point

mutations that give rise to different

alleles containing alternative bases at

a given nucleotide position within a

tocus. SNP within a locus can produce

four alleles but practically most SNPs

are usually limited to one or two alleles

and have been considered as bi-atlelic'

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SNP markers are inherited as co-

dominant markers. SNP genotyping is

stitt a challenging effort and requires

specialized equipments (Liu. and

iordes 2004), Microsatellites or simple

sequence repeats (SSRs) .are highly

repetitive DNA sequences that consist

of short (1-6 bp) tandem repeats and

dispersed throughout the gengm.e

(Tautz and Renz 1984; Litt and LutY

i gAg). Among the molecular markers

available in PoPulation genetics'

microsatellites are widety used due to

their high variability, neutral behaviour,

co dominance, and abundance (Tautz

1989; Weber and MaY 1989)' The

relatively small size and variability of

microsaiellites is significant to identify

stocks using PCR technologY'Microsatellite polymorphism is based

on size differences due to varYing

number of repeat units contained by

alleles at a given locus'

Microsatellite Distribution

Microsatellites contain tandem

repeated motifs of 1-6 bP that are

distributed in all ProkarYote and

eukarYote genomes studied to date

(Hamida et al. 1982; and Gur-Arie et

al. 2000). A single microsatellite locus

may contain 5 to 100 tandem coPies

of i repeat motif. Microsatellite markers

used in stock identification studies

typically contain di (AC)n, tri (ACC)n'

or tetranucleotide (GATA)n repeats'

The majority of microsatellites (30-

65%) found are dinucleotides, the most

common dinucteotide motif is (AC)n in

vertebrate genome (Toth et al' 2000)'

Trinucleotide and hexanucleotiderepeais aPPeai in coding regions

because they do not cause a frameshift

(Toth et at'2000). Mononucleotideiepeats are less reliable for molecular

genetic studies because ofimplification Problems, as longer

repeat tYPes are less common (Li et

Next Generation Sciences: Vision 2020 andBeyond

significant allelic frequency differencesamong stocks. The PCR technology isused to analyse microsatellitepolymorphism in which primers aredesigned based on flanking sequencessurroulnding a microsatellite locus. Theprimers are selected such that pCRproducts are of small size, providingease in amplification from low qualityDNA. The small differences inmolecular size of alleles amongindividuals can be characierized bvusing gel or automated DNAsequencer. Microsatellites arecodominant and are inherited In .*,,r;

Mendelian manner, therefore eachindividual shows a single or two bandpattern with one band from each

. parent. Microsatellite variability haSbeen investigat'ed in a number of fishpopulations both marine andfreshwater. Mc Connell et al. (1995a)in a preliminary study of microsatellitevariation in Atlantic salmon from bothsides of Atlantic Ocean show significantallele frbquency differences betweenNorth American and Europeanpopulations. ihe most intensivelysurveyed marine fish species is Aflanticcod, whose microsatellite loci showvery high levels of variability asdescribed by Brooker et al. (1994).Genetic diversity was investigatedusing microsatellites between farmedandwild populations of Atlantic salmon.Farmed salmon showed less geneticvariability than natural populations interms of allelic diversity (Norris et al.1999). 'Genetic variation has beenassessed using microsatellite markersto identify the population structure offourteen populations of northern. pikein the North Central United States andin six populations from Quebec, Alaska,Siberia, and Finland (Senanan et al.2000). Microsatellite analysis at ninelociwas used to discriminate cod fromthe three populations in the North Sea,the Baltic Sea, and the north-eastern

Next Generation Sciences: Vision 2020 and Beyond

Artic Ocearr and to assign individualfish to their population of origin (Nielsenet al. 20Ol ). The severe decline ofpopulations of lake trout in the NorthAmerican Great lakes and brown troutin Denmark have been successfullyexplained by analyzing microsatellites(Hansen et al. 2002; and Guinand etal. 2003). Based on five microsatelliteloci, the genetic structure ofendangered fish species Anaecyprishispanica was studied in eight distinctpopulations in the Portugal todetermine levels of genetic variationwithin and among populations andconservation of the species (Salgueiroet-.a|. 2003). The analySis of geneticvariation in microsatellite lociwere usedfor identification of Cirrhinus mrigalastocks from five rivers of lndia (Lal etal. 2004). The genetic variation andpopulation structure of yellow catfishfrom three rivers of western ghats,lndia were studied and all the sixamplified microsatellite loci werepolymorphic, showed heterogeneity inallele frequency and displayednoticeable genetic differentiationbetween pairs of fish populationsexamined (Muneer et al. 2009).Microsatellite markers were used todetermine population genetic structurein the Coilia dussumieri and it wasfound that all the ten amplifiedmicrosatellite loci were polymorphicand showed heterogeneity in allelefrequency for all the four populations.The populations that are divergent intheir genetic characteristics can beidentified through microsatellite lopi(Kathirvelpandian et al. 2014). Thehete.rozygosity (the rati.o ofheterozygous individuals in thepopulation), the proportion ofpolymorphic loci, and the allelicdiversity (number of alleles at a locusin the population) are acceptedmeasures of genetic diversity (pujolar *et al. 2OO5). The mutations at -

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microsatellite loci are mainlyunidentified, thereby complicating theanalysis of microsatellite data. Thedominant mutation for microsatellitesis slipped-strand mispairing duringreplication (Schlotterer and Tautz1992). Due to this mutational processthe microsatellite alleles arise multipletimes, thereby generating homoplasy.The mutation models that account forthis homoplasy have been put forward.The stepwise mutation model (SMM)assumes that all mutational incidentsinvolve a change in a single repeatonly (Bell and Jurka 1997) whereaschange involving more than than onerepeat is explained by two-phasemutation model (TPM) (Di Rienzo etal. 1994.). lnfinite allele modet (tAtU)suggests that every mutation results inmaking of a new allele, thereby rejectshomoplasy (Kimura and Crow 1964).The information of mutation modelsupon which data analysis is establishedin determining genetic distancesamong populations using microsatellitevariability in fishes, conventional F-statistics are being used (Weir andCockerham 1984). An important issuewith microsatellite is the difficulty inprecisely typing alleles before data canbe applied to identification studies. Thisissue is more intense in fishes thathave large microsatellites, as stutteringlevel is usually higher in microsatelliteswith larger repeats. The feasible meansto avoid this problem is to selecttetranucleotide loci, these loci are easyto score because of the greaterdistance between alleles and reducedstutter (O' Reilly and Wright 1995). lnfish stock identification studies it isessential to include size standards onall gels and to add a number of controlsamples into each gel to report smallvariations within and between gels andbetween people preparing the samples.Another issue is null alleles, whichaffect significantly to the pattern of

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variation at microsatellite loci becausethese are weakly amplified or notvisible after amplification. The highfrequency of null alleles inay beobserved through an increase innumber of PCR failures. The excessof homozygotes than expected underHardy-Weinberg equilibrium may bedue to null alleles. The probability ofchanges in the flanking sequenceswhile using loci originally developed foralternate species may also be thecause of null alleles, therefore in thesecases it is recommended to carry outthat the sequence characterization ofalleles in alternate species.

Gonclusion

The analyses of nuclear DNA are usedin fish stock identification to detect DNAthat are polymorphic within a species,exhibit variation in frequency of theiralleles, and are very precisely screenedto describe the population structure,and can be used to assess thecontribution of individual populations tofisheries. A number of moleculartechniqueg are now available for usein fishery science but microsatelliteanalysis is the most widely acceptedmethod for the identification of fishstocks because of hypervariability,codominance, and data reliability (Table1). Microsatellite approach is PCRbased and a very small tissue sampleis required; this adds to its utility inpoplrlation studies of endangered andthreatened species. The microsatelliteloci study does not require a high levelof expertise once isolated, the transferof this technique is possible to those

. .. countries with limited financialresources but rich in'biological diversity.Apart from fish stock identification,microsatellites are used in genomemapping, parentage and kinshipanalysis, phylogeny, conservationgenetics, molecular epidemiology andpathology.

)Next Gene#ion Sciences : Vision 2V20 and Beyond

&

Table 1: Types of DNA markers used in fishery science, their characteristics and applications

Technique Geneticvariation

PCR-based

Reproducibili\ Cost Applications

Populationgenetics

Genomemapping

Parentageassessment

Allozymes Low No High Low Moderate/High

Low Low

MitochondrialDNA

Moderate Yes High Moderate Moderate Nit Moderate

RFLP Low-High Yes High Low Moderate High Low

RAPD High Yes Low Low Low High Moderate

AFLP High Yes Moderate Low High High Low

Minisatellites Very High No, butcan be"

Moderate High High High High

Microsatellites Very High Yes High Low/High.

High High High

SNP Very High Yes' High High High High High

" No, but assay can be made PCR-based at individual minisatellite loci.. Low if taxon-specific primers have already been developed; high if taxon-specific PCR primers needto be developed.

Acknowledgements

The authors are thankful to theChairman, Department of Zoology,Alig'arh Muslim University, Aligarh,lndia for providing necessaryfacilities for the study. We are alsogratefulto the Scierrce and EngineeringResearch Board, Department ofScience and Technology, New Delhiforfunding the study and providingfinancial assistarrce to the first author(sFyso/AS-4at2012).

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