The characterization of goat genetic diversity: Towards a genomic approach

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Pleasecitethisarticleinpressas:Ajmone-Marsan,P.,etal.,Thecharacterizationofgoatgeneticdiversity:Towardsa genomicapproach.SmallRuminantRes.(2014),http://dx.doi.org/10.1016/j.smallrumres.2014.06.010

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ContentslistsavailableatScienceDirect

Small

Ruminant

Research

j o urna l h o m e pa g e: www.e l s e v i e r . c o m / l o c a t e / s m a l l r u m r e s

The

characterization

of

goat

genetic

diversity:

Towards

a

genomic

approach

P. Ajmone-Marsan

a,b,∗

_,

_L.

_Colli

a,b

_,

_J.L.

_Han

c,d

_,

_A.

_Achilli

e

_,

_H.

_Lancioni

e

_,

_S.

_Joost

f

_,

P. Crepaldi

g

_,

_F.

_Pilla

h

_,

_A.

_Stella

i,j

_,

_P.

_Taberlet

k

_,

_P.

_Boettcher

l

_,

_R.

_Negrini

a,m

_,

J.A.

Lenstra

n

_,

_Italian

_Goat

_Consortium

1

_,

_Econogene

_Consortium

2

_,

Econogene

Consortium

2

_Globaldiv

_Consortium

3

_,

_Globaldiv

_Consortium

3

a_Institute_of_Zootechnics,_Università_Cattolica_del_S._Cuore,_Piacenza,_Italy

b_Research_Center_on_Biodiversity_and_Ancient_DNA_–_BioDNA,_Università_Cattolica_del_S._Cuore,_Piacenza,_Italy

c_CAAS-ILRI_Joint_Laboratory_on_Livestock_and_Forage_Genetic_Resources,_Institute_of_Animal_Science,_Chinese_Academy_of_Agricultural

Sciences(CAAS),Beijing100193,China

d_{International}_Livestock_Research_Institute_(ILRI),_P.O._Box_30709,_Nairobi,_Kenya e_Dipartimento_di_Biologia_Cellulare_e_Ambientale,_Università_di_Perugia,_Perugia,_Italy

f_Laboratory_of_Geographical_Information_Systems_(LASIG),_School_of_{Architecture,}_Civil_and_{Environmental}_Engineering_(ENAC),_Ecole

PolytechniqueFédéraledeLausanne(EPFL),Lausanne,Switzerland

g_Università_di_Milano,_Dipartimento_di_Scienze_Veterinarie_e_Sanità_Pubblica,_Milano,_Italy h_University_of_Molise,_SAVA,_Campobasso,_Italy

i_Institute_of_Agricultural_Biology_and_{Biotechnology,}_Consiglio_Nazionale_delle_Ricerche,_Lodi,_Italy j_Parco_Tecnologico_Padano,_Lodi,_Italy

k_Laboratoire_d’Ecologie_Alpine,_CNRS_UMR_5553,_Université_Joseph_Fourier,_Grenoble,_France l_Food_and_Agriculture_{Organization,}_Rome,_Italy

m_Associazione_Italiana_Allevatori,_Rome,_Italy n_Utrecht_University,_Utrecht,_The_Netherlands

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Availableonlinexxx Keywords: Caprahircus

Nuclearandmitochondrialgenome Diversity

Breeding SNP

a

b

s

t

r

a

c

t

Theinvestigationofgeneticdiversityatmolecularlevelhasbeenproposedasavaluable complementandsometimesproxytophenotypicdiversityoflocalbreedsandispresently consideredasoneoftheFAOprioritiesforbreedcharacterization.Byrecommendingaset ofselectedmolecularmarkersforeachofthemainlivestockspecies,FAOhaspromotedthe meta-analysisoflocaldatasets,toachieveaglobalviewofmoleculargeneticdiversity. Anal-ysiswithintheEUGlobaldivprojectoftwolargegoatmicrosatellitedatasetsproducedby theEconogeneConsortiumandtheIAEACRP–AsiaConsortium,respectively,hasgenerated apictureofgoatdiversityacrosscontinents.Thisindicatesagradientofdecreasingdiversity fromthedomesticationcentretowardsEuropeandAsia,aclearphylogeographicstructure atthecontinentalandregionallevels,andinAsiaalimitedgeneticdifferentiationamong localbreeds.ThedevelopmentofSNPpanelsthatassaythousandsofmarkersandthewhole genomesequencingoflivestockpermitanaffordableuseofgenomictechnologiesinall live-stockspecies,goatsincluded.PreliminarydatafromtheItalianGoatConsortiumindicate thattheSNPpaneldevelopedforthisspeciesishighlyinformative.Theexistingpanelcan beimprovedbyintegratingadditionalSNPsidentiﬁedfromthewholegenomesequence alignmentofgoats adaptedtoextremeclimates.Part ofthis effortis beingachieved

∗ Correspondingauthorat:InstituteofZootechnics,UniversitàCattolicadelS.Cuore,Piacenza,Italy.Tel.:+390523599204;fax:+390523599276. E-mailaddress:[email protected](P.Ajmone-Marsan).

1 _{http://www.italiangoat.it}_. 2 _{http://www.econogene.eu}_. 3 _{http://www.globaldiv.eu}_.

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byinternationalprojects(e.g.EUFP7NextGenand3SRprojects),butafairrepresentationof theglobaldiversityingoatsrequiresalargepanelofsamples(i.e.asintherecentlylaunched 1000cattlegenomesinitiative).Genomictechnologiesoffernewstrategiestoinvestigate complextraitsdifﬁculttomeasure.Forexample,thecomparisonofpatternsofdiversity amongthegenomesinselectedgroupsofanimals(e.g.adaptedtodifferentenvironments) andtheintegrationofgenome-widediversitywithnewGIScience-basedmethodsareable toidentifymolecularmarkersassociatedwithgenomicregionsofputativeimportancein adaptationandthuspavethewayfortheidentiﬁcationofcausativegenes.Goatbreeds adaptedtodifferentproductionsystemsinextremeandharshenvironmentswillplayan importantroleinthisprocess.Thenewsequencingtechnologiesalsopermittheanalysisof theentiremitochondrialgenomeatmaximumresolution.ThecompletemtDNAsequence isnowthecommonstandardformatfortheinvestigationofhumanmaternallineages.A preliminaryanalysisofthecompletegoatmtDNAgenomesupportsasingleNeolithicorigin ofdomesticgoatsratherthanmultipledomesticationeventsindifferentgeographicareas. ©2014ElsevierB.V.Allrightsreserved.

1. Introduction

Localbreeds,welladaptedtoarangeofagro-ecologicalconditions (differentclimates,diseases,localfeed),grantthesustainabilityofanimal farminginmarginalanddifﬁcultareasinbothdevelopedand develop-ingcountries.Theyaresourceofmeat,milkandskinandcontributeto maintainlivelihoodintheharshestareasoftheplanet(Lampkinand Measures,2001).Localgeneticresourcesarethreatenedbyanumberof factors,includingindiscriminatecrossbreedingwithcosmopolitanbreeds anduncontrolledintermixing(Hanotteetal.,2010).However,among live-stockspecies,goatisonlymarginallyaffectedbycrossbreeding.Rather, concernsaboutgoatgeneticdiversitylossarisefromtheabandonment ofmarginalruralareaswheregoatsarefrequentlyreared.The conse-quentreductionofpopulationsizeoflocalbreedsincreasestheriskof inbreeding(Taberletetal.,2008).Therefore,themolecular characteri-zationofavailablegeneticresourcesandinformationondiversityand geneticstructureisdesirablealsointhisspecies,toserveasarational basisforthecharacterizationandconservationofgoatgermplasm.

Theinvestigationofgeneticdiversityatthemolecularlevelhasbeen proposedasavaluablecomplementtotheevaluationofphenotypesand productionsystems,andsometimesasaproxyforphenotypicdiversityof localbreeds.Thishasexpandedourinsightintobreedhistory,inorderto guidebreeddevelopment,utilizationandconservationdecisions. Charac-terizationofbreedsispresentlyconsideredbyFAOasoneofthestrategic prioritiestobeundertakeninthedevelopmentofanationalplanforthe managementofanimalgeneticresources(AnGR).Thereforemolecular characterizationhasaprominentroleinStrategicPriorityArea1– Char-acterization,InventoryandMonitoringofTrendsandAssociatedRisks– oftheGlobalPlanofActionforAnGR(FAO,2007).

Inthelate1990s,andlateronin2004,FAOhasrecommendedthe useofpanelsofselectedmicrosatellitemarkersforeachofthemain live-stockspecies.Theassayofthesamelociacrossprojectsfacilitatesthe joiningofmoleculardatasetsandthecombinedanalysisofindependent investigationsofgeneticdiversitythatotherwisewouldremainlocaland fragmented.Thisinitiativehasonlypartiallysucceeded.Someprojects havenotconsideredFAOrecommendationsorhaveuseddifferent sub-setsoftherecommendedmarkers,notfollowingtherankingorderinthe panel(Baumungetal.,2004).Evenlarge-scaleprojectshavesometimes notusedthesamesetofmicrosatellites;thereforeaworldwidepictureof livestockdiversityisyettobedrawn(Groeneveldetal.,2010).

2. Analysisofgoatgeneticdiversitywithclassical markers

Several local studies have characterized the nuclear genetic diversity using molecular markers, mainly microsatellites,inEuropean, AfricanandAmericangoats

(Table1).Duringthelastdecade,anumberofinternational

research projects have also attempted to analyse the patternsofgoatdiversityatabroaderscale(Table2).

So far, the largest scale datasetpublished has been generated by the Econogene Consortium (http://www.

econogene.eu)withina projectfundedby theEuropean

Commissionduringthe5thFrameworkProgramme.The dataset describes the genetic diversity of 1426 goats from 45 traditional or rare breeds from 15 countries in Europe and southwest Asia, genotyped with the 30 FAO microsatellite markers. Results revealed the exist-enceoffourdiscretegroupsofgoatbreedsinsouthwest Asia,centralMediterranean,westernMediterraneanand northern-central Europe.Geneticdiversity,measuredas allelic richness, decreases fromsoutheast to northwest, presumablyasaconsequenceofrepeatedfoundereffects occurring during the colonization of Europe following domestication(Ca ˜nónetal.,2006).

Thejointanalysisofthesedatawiththose produced bytheFAO/IAEACRP(CoordinatedResearchProjectofthe International Atomic Energy Agency)/Asian Consortium hasbeenattemptedintheframeworkoftheEUGlobaldiv project(http://www.globaldiv.eu).

The FAO/IAEA CRP project (http://www-naweb.iaea.

org/nafa/aph/crp/aph-livestock-phase1.html) genotyped

1629 samples from 43 local populations from 8 Asian countries(China,Bangladesh,Indonesia,Iran,SaudiArabia, Sri Lanka,Pakistan,andVietnam)with15microsatellite markers(Zeinetal.,2012;Dietal.,2011;Afrozetal.,2010;

Fanetal.,2008;Mburuetal.,2006;Vahidietal.,2014).The

highestnumberofalleleswasobservedinIranianandSaudi Arabian nativegoats, followed byChinese, Bangladeshi, Pakistani and Sri Lankan indigenous goat populations. Low genetic diversity wasobserved in Vietnamese and Indonesianlocalgoats.Althoughgeneticdifferentiationin allpairsofpopulationsbetweencountrieswassigniﬁcant (pairwiseFSTestimatesatP<0.01),relativelyclosegenetic relationshipswerefoundamongmostoftheChinesegoat populations, Iranianand SaudiArabiangoatsas wellas amongBangladeshi,PakistaniandSriLankangoat popu-lations,whiletheVietnameseandmostoftheIndonesian goatpopulationslooselygroupedtogether(Mburuetal.,

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Please cite this article in press as: Ajmone-Marsan, P., et al., The characterization of goat genetic diversity: Towards a genomic approach. Small Ruminant Res. (2014), http://dx.doi.org/10.1016/j.smallrumres.2014.06.010

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Listofmolecularmarkerbasedgeneticdiversitystudiesingoats.Indicatedarebreeds,thegeographicareaoforiginofthebreedsinvestigated,thetypeandnumberofmolecularmarkersused,themainpopulation geneticsparametersinvestigatedandthebibliographicreference..

No.ofbreeds Breeds Geographicarea Markertype No.of

markers

Parametersofdiversitya _Reference

Ho HE NA AR Fst Fis PS

1 AzpiGorri Spain Microsatellites 29 • • • Martínezetal.(2012)

8 CamosciatadelleAlpi,Valdostana,

Biondadell’Adamello,Orobica,Grigia Molisana,Girgentana,Argentata dell’Etna,Sarda

Italy Microsatellites 30 • • • • • Negrinietal.(2012)

6 Algarvia,Bravia,Charnequeira,Preta

deMontesinho,Serpentina,Serrana

Portugal Microsatellites 25 • • • • Bruno-de-Sousaetal.(2011)

1 Capore Albania Microsatellites 30 • • • • Hoda(2011)

1 CroatianSpotted Croatia Microsatellites 20 • • • • Jelenaetal.(2011)

6 Saanen,Anglo-Nubian,Alpine,

Carpathin,Whiteimproved,Pygmy

Poland Microsatellites 6 • • • Sikoraetal.(2011)

4 Girgentana,DerivatadiSiria,Maltese,

Messinese

Italy Microsatellites 19 • • Siweketal.(2011)

1 Guadarrama Spain Microsatellites 10 • • • • Serranoetal.(2009)

11 Swissgoatbreeds Switzerland – – • • Glowatzki-Mullisetal.(2008)

45

Capore,Dukati,Hasi,Liqenasi,Mati, Muzhake,Pinzgauer,TauernPied, SwissAlpine,GrisonsStriped,Peacock, St.GallenBooted,ValaisBlackNeck

Europe,SWAsia Microsatellites 30 • • • • • •

Ca ˜nón etal. (2006)

Makeras,GermanAlpine,Thuringian Forest,Florida,Guadarrama, Malaguena,Payoya,Verata,French Alpine,Corse,Pyreneenne,Rove, Greek,Skopelos

HungarianNative,Argentatadell’Etna, Biondadell’Adamello,Camosciata (Alpine),Girgentana,GrigiaMolisana, Orobica,Sarda,Valdostana PolishFawnColoured,Brava, Carpathian,Beeshi,Najrani,Abaza, Angora,Gurku,Hair

9 Sarda,DerivatadiSiria,lonica,Maltese,

Garganica,Girgentana,Montefalcone, Saanen,Alpine

Italy Microsatellites 15 • • Iamartinoetal.(2005)

3 Maltese,Sarda,crossbredbetween

MalteseandSarda

Italy Microsatellites 17 • • • Sechietal.(2005)

2 WhiteShort-Haired,Brown

Short-Haired

CzechRepublic Microsatellites 7 • Jandurováetal.(2004)

7 Biondadell’Adamello,Frisa,Orobica

andVerzaschese,ValdiLivo,Sarda, Saanen

Italy AFLPs – Ajmone-Marsanetal.(2001)

11 GrisonStriped,ChamoisColoured,

ChamoisColouredfromGrison, Verzasca,Peacock,Saanen,valais Blackneck,Toggenburg,Bezoar,Creole, Ibex

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markers

Ho HE NA AR Fst Fis PS 18 Shiba Japan Microsatellites 26 • • • • Nomura etal. (2012)

Southwest,Southeast Korea

West,East Taiwan

LuzonandMindoro Philippines

KambingKatjangBali,Kambing KatjangJava,Etawa

Indonesia

BlackBengal,Indianbreed Bangladesh

ZavkhanBuural,ZalaajinstWhite, ErchimBlack,UlgiiRed,Bayandelger, Dorgon,Sumber

Mongolia

4 Gembrong,Jawarandu,Peranakan

Etawa

Indonesia Microsatellites 13 • • • • Zeinetal.(2012)

14 Tangshan,_{Nanjiangyellow,}Liaoningcashmere,_Chengde_polled, Leizhoublack

• • • Zhang_et_al.

(2012)

Alashan,Erlangshan,Wuzhumuqin, Liaoning,Chaidamu,Shanbei,Xinjiang, Hexi,Hegu

3 Naini,Turki Iran – – • • • • • Di_et_al.

(2011)

GuineaBissau Africa

6 Plateau-typeTibetan,valley-type

Tibetan,Baiyu,Jianchangblack,Meigu, Xinjiang

Tibet Microsatellites 10 • • • Wangetal.(2011)

3 BlackBengal,ImportedIndian,

crossbredbetweenBlackBengaland exoticbreeds

Bangladesh Microsatellites 15 • • • Afrozetal.(2010)

1 Lori Iran Microsatellites 13 • • Mahmoudi(2010)

1 Vietnamese Vietnam Microsatellites 16 • • • • Berthoulyetal.(2009)

22 BlackBengal,Ganjam,Gohilwadi,

JharkhandBlack,Attappady, Changthangi,Kutchi,Mehsana,Sirohi, Malabari,Jamunapari,Jakhrana,Surti, Gaddi

India Microsatellites 25 • • • • • Dixit_et_al.

(2012)

Marwari,Barbari,Beetal,Kanniadu, Sangamneri,Osmanabadi,Zalawadi, Chegu

6 Attappady,Osmanabadi,Sangamneri,

MalabariandKanniadu,Ganjam

India Microsatellites 25 Dixitetal.(2010)

3 Kutchi,Mehsana,Sirohi India Microsatellites 25 Dixitetal.(2009)

10 Shannanwhite,Shanbeiwhite

cashmere,Funiu,Huanghuai,Taihang, Guanzhongdairy,XinongSaanen, Zhongwei,Tibetan,InnerMongolia cashmere

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markers

1 Barbari India Microsatellites 21 • • Ramamoorthietal.(2009)

5 Huai,Haimen,YichangWhite,Suining

White,Boer

China Microsatellites 18 • • • • Fanetal.(2008)

3 Zalawadi,Gohilwadi,Surti India Microsatellites 18 • • • • Fatimaetal.(2008)

7 Barbari,Jamunapari,BlackBengal,

Pashmina,Jakhrana,Marwari,Sirohi

India Microsatellites 17 • • • • Routetal.(2008)

1 Jamunapari India Microsatellites 17 • • • • Rout etal. (2012)

Milkproteinloci 2

mtDNAcontrolregionsequences

-Y-chromosomegenesequences 3

8 Bayandelger,UlgiiRed,Zavkhan

Buural,Sumber,ZalaajinstWhite, ErchimBlack,Dorgon,GobiGurvan Saikhan

Mongolia Microsatellites 10 • • • • Takahashietal.(2008)

7 Chinesegoatbreeds China mtDNAcontrolregionsequences - Wangetal.(2008)

1 Jamunapari India Microsatellites 23 Gouretal.(2006)

1 Marwari India Microsatellites 25 Kumaretal.(2005)

8 LiaoningCashmere,InnerMongolian

Cashmere,ChengdePolled,JiningGrey, ChengduBrown,Tibetan,Leizhou, ShannanWhite

China Microsatellites 18 LiandValenti(2004)

3 Koreangoat,Chinesegoat,Saanen Korea,China Microsatellites 9 • • • • Kimetal.(2002)

12 EastTibetan,Neimonggol,Liaoning,

Taihang,Wu,NanjiangBrown, ChuandongWhite,Black,Matou, South-eastTibetan,NorthTibetan, Small-xiang

China Microsatellites 25 • • • • • Lietal.(2002)

NA Theindigenousgoatsofsouth-east

Asiaarenotclassifedintobreeds SEAsia

Microsatellites 25 _• _• _• _• _•

Barkeretal.(2001)

Proteincodingloci 59

5 Tibetan,Neimonggol,Liaoning,

Taihang,Matou

China Microsatellites 5 Yangetal.(1999)

5 Angora,Kilis,Honamli,Hair,Norduz Turkey Microsatellites 20 • • • • • A˘gao˘gluandErtu˘grul(2012)

3 RoussedeMaradi(RedSokoto),

BurkinabéSahelian,Djallonkégoat

BurkinaFaso Microsatellites 19 • • • • • Álvarezetal.(2012)

6 Gumuz,Agew,Begia-Medir,Bati,

Abergelle,CentralAbergelle

Ethiopia Microsatellites 15 • • • • • Hassenetal.(2012)

1 Taleshigoat Iran Microsatellites 9 • • • MahmoudiandBabayev(2009)

6 Markhoz,Lori,Nadji,Tali,Raeini,Korbi

JonabKhorosan

Iran Microsatellites 10 • • Mahmoudietal.(2009a)

1 Markhozgoat Iran Microsatellites 13 • • • Mahmoudietal.(2009b)

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markers

19

Gubu/Bissau GuineaBissau

Microsatellites 11 • • • Muemaetal.

(2009)

BoranGalla Kenya

SmallEastAfrican Kenya,Tanzania

Maure Mali

Pafuri,Landim Mozambique

RedSokoto,BornWhite,WestAfrican Dwarf

Nigeria

GrisonStriped Switzerland

Maasai,Ugogo,Ujiji Tanzania

Karamoja,Teso,Kigezi,Sebei Uganda

2 Taligoat,Raeini Iran Microsatellites 13 • • Sadeghietal.(2009,2010)

3 Djallonké,Mossi,Sahelian BurkinaFaso Microsatellites 27 • • • • • Traoréetal.(2009)

5 EgyptianBaladi,Barki,Zaraibi Egypt Microsatellites 7 • • • • • • Aghaetal.(2008)

Maltese,Montefalcone Italy

7 Casamancegoat,LabeGoat,SahelGoat,

Redsokoto,Guera

WAfrica Microsatellites 6 • • • • • Missohouetal.(2006)

4 Ovambo,Caprivi,Kunene,Kavango Namibia Microsatellites 18 • • Elsetal.(2004)

20

Maasai,Kigezi,Mubende,NorthWest Highland,ArsiBale,Ndebele,Pafuri, WestAfricanDwarf,Maure,Djallonke

Africa

Microsatellites 19 • Chenyambuga₍₂₀₀₄₎ etal.

GrisonsStriped,Toggenburg Europe

MongolianCashmerindipur Asia

Arab SWAsia

6 Draa,Noire-Rahalii Morocco Microsatellites,asl-Casein

alleles 5 • • • • Ouaﬁetal.(2002)

Alpine,Saanen,Poitevine,Pyre’ne’enne France

– 626goatindividualsfrom14localities Colombia Microsatellites 12 • • • • • CalvoandGonzáles(2012)

12 Algarvia,Bravia,Charnequeira,Preta

deMontesinho,Serpentina,Serrana

Portugal Microsatellites

15 • • • • • • • Ribeiroetal.(2012)

Azul,Caninde’,Grauna,Marota, Moxoto,Repartida

Brazil

9 Anglo-Nubiancrossbred,Moxot6,

Caninde’,Alpine-GermanAlpine, Saanen,Toggenbourg,Anglo-Nubain, Undedinedbreed,Grauna

Brazil Microsatellites 13 • • • • • Oliveiraetal.(2007)

2 Moxot6breed Brazil Microsatellites 20 • • • • • • • Oliveiraetal.

(2010)

Serpentina Portugal

3 Alpine,Saanen Europe Microsatellites 11 • • • • • Araújoetal.(2006)

BrazilianMoxot6goats Brazil

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Researchprojectscitedinthetextandreferencewebsites.

Projectname Website

Econogene http://www.econogene.eu

Globaldiv http://www.globaldiv.eu

FAO/IAEACRP http://www-naweb.iaea.org/nafa/aph/crp/aph-livestock-phase1.html InternationalGoatGenomeConsortium http://www.goatgenome.org

ItalianGoatConsortium http://www.goatit.eu/

ADAPTmap http://bioinformatics.tecnoparco.org/adaptmap/

FeedtheFuture http://www.feedthefuture.gov

NextGen http://nextgen.epﬂ.ch/

3SR http://www.3srbreeding.eu/

1000genomeproject http://www.1000genomes.org

Genome10Kproject http://genome10k.soe.ucsc.edu

1000bullgenomesproject http://www.1000bullgenomes.com/

A total of 11 markers and a few populations of Mediterranean goats were shared by Econogene and FAO/IAEAdatasets,butnosamplewasgenotypedinboth projects.Thereforearound200samplesfromthe Econo-gene project were re-genotyped by the FAO/IAEA CRP projectintheChineseAcademyofAgricultural Sciences (CAAS)–International Livestock Research Institute (ILRI) jointlabinBeijing,ChinaandtheILRIlaboratoryinNairobi, Kenya,tocalibratetheallelicsizecallingmethods imple-mentedbythetwoprojects.Apreliminaryjointanalysis with the11 shared markers indicatesthe cleargenetic partitioningofgoatsintolargegeographicregionsand con-tinentsandsuggestsseparateancientmigrationroutesto AsiaandEurope.However,alimitedgenetic differentia-tionisobservedamongindigenousgoatswithinmostofthe countries,anindicationofarelativelyhighgeneﬂowacross localgoatpopulations,atleastuntilrecently.Aclear phylo-geographicpartitioningofgoatdiversitywasalsoobserved

byPereiraetal.(2009)thatinvestigatedthedistributionof

Y-chromosomalhaplotypesinEuropeanandNorthAfrican goatbreeds.

Traditionally, the molecular phylogeny of livestock species hasbeenbasedonthecharacterization ofshort fragments of the mitochondrial DNA (mtDNA) control region(d-loop). Ingoats, theﬁrst studiesbasedonthis regionhighlightedtheexistenceofseveralwell differen-tiated maternal lineages,whose variability hasa lower geographicstructurecomparedtootherlivestockspecies. Thisevidencewasﬁrstinterpretedasindicatingseparated andindependentdomesticationeventsintheFertile

Cres-centandinAsia(Luikartetal.,2001;Chenetal.,2005),

butmorerecently,bycomparingthemtDNAgenetic vari-ability of domestic and wildgoats, Naderi et al. (2007,

2008)showedthat,mostprobably,thedomesticationof

Caprahircustookplaceinawidegeographicareacentred aroundSouthwestAsia,andwasalarge-scalephenomenon bothfromthetemporalandnumericalpointofview.These resultslargelyagreewitharchaeologicalevidence,which alreadysuggestedthatgoatdomesticationtookplaceabout 10,000yearsagoinanareabetweentheZagrosmountains andtheFertileCrescent,placedbetweenthepresentday boundariesofIran,IraqandTurkey(ZederandHesse,2000;

Zeder,2008).

Thefractionoftheancestralmitochondrialvariability whichwascapturedatthoseearlytimesconstitutedthe startinggenepoolofdomesticgoatswhichsubsequently

spreadallovertheworldduringthemigrationwavesof Neolithicfarmers.Theanalysisoftherelationships exist-ingbetweenmitochondrialhaplotypesandhaplogroups, therefore,mayrevealhowthediffusionofdomesticgoats occurredandshedlightonthedynamicsofpasthuman migrations.

Interestingly,nuclearDNA shows a remarkablelevel ofgeographicstructuringthatisnotdetectedinmtDNA. Complexdemographicdynamicsmayexplainthispattern, however, a simplerreason can beidentiﬁed comparing goats toother livestockspecies, as cattle. In Bostaurus thegeographic structure ofthematernal lineageis due todifferencesinthefrequencyofdistincthaplogroupsin differentgeographic areas (e.g. T3 in Europeand T1 in Africa;Troyetal.,2001).Conversely,ingoatsasingle hap-logroup(haplogroupA)largelypredominatestheworld, likelymaskingtheexistenceofageographicstructuringof thematernalgeneticdiversity,evidentonlyinthecaseof rarehaplogroups(Naderietal.,2007).

3. Developmentofhigh-throughputSNPassaysfor theanalysisofgoatgeneticdiversity

Being highly polymorphic, microsatellites are very informativemarkers and havebeenextensively usedin diversitystudies.Alargenumberof thesehypervariable markersisavailableingoat(Sekietal.,2012),however, their genotyping and scoring are labour intensive, and allelesizecallingisdifﬁculttobecalibratedacrossapparata andlaboratories,intheabsenceofasubstantialnumberof sharedsamples.

Recently, thewhole genomesequencing of livestock species, and thedevelopment of panels of 50,000 to1 million SNPs,allow theuseof genomic technologiesin alllivestockspecies,goatsincluded.AdrawbackofSNPs is ascertainmentbias (Nielsen,2004; Albrechtsen et al., 2010),depending onthestrategyand theanimals used for their discovery.SNPs are alsoinefﬁcient to capture some relevant genome polymorphisms, such as certain types of copy number variation (e.g. Kijaset al., 2011;

Fontanesi et al., 2012). Nevertheless, they are quickly

replacingmicrosatellitesinpaternitytestingandgenetic diversity studies,due to theirrobustness, low cost and automatic allele calling. In addition, high-density SNP panels permit the investigation of the goat genome at very high resolution. This is a clear advantage for the

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8 P.Ajmone-Marsanetal./SmallRuminantResearchxxx(2014)xxx–xxx investigation of population structure, reconstruction of

demographic history and detection of recent and his-toricaladmixture,identiﬁcationof selectionsweepsand ofmarker–traitassociationsingenome-wideassociation studies(GWAS)ofnon-experimentalpopulations.A num-berof theseapproaches areeitherunfeasibleoratleast impreciseusinglow-densitymarkers,evenifhighly infor-mative as microsatellites. In addition, SNP panels are applied in breeding programmes as a support to tra-ditional selection and for genomic selection, presently implementedonalargescaleindairycattle.

A 50k goat SNP panel has been recently

devel-oped (http://www.goatgenome.org; Tosser-Klopp et al.,

2014) by the combined sequencing of whole genomes and reduced representation libraries from eight differ-entbreeds/populationsfromEuropeandAsiathroughthe cooperationoftheFrenchINRAInstitute,Utrecht Univer-sity(TheNetherlands),theMalaysianAgriculturalResearch andDevelopmentInstitute, andtheDNALandmark lab-oratory (Canada). The current panel comprises 53,347 SNPs(Illumina50kInﬁniumiSelectHDCustomBeadChip), whichhavebeenmappedongoatscaffolds/contigs pro-ducedbyajointeffortoftheBeijingGenomicsInstitute, KunmingInstituteofZoologyandInnerMongolia Agricul-turalUniversity(China).

The status of goat genome has improved since the releaseofthereferencegenomethatwasmadeavailable bytheIGGCin2012(Dongetal.,2013).Inparticular, addi-tionalIlluminanew-generationshortreadssequencingand theopticalmappingtechnologyoflargeDNAmolecules permittedtheassemblyof349super-scaffoldswithN50 reachingashighas18.2Mb.Thecurrentassembledbase pairstotal2.66Gb,whichisabout92%oftheestimatedgoat genomesize(∼2.9Gb).Dataisassembledinto30 pseudo-chromosomes,withhighcolinearity betweencattleand goat.

PacBiosequences(72×sequencereaddepthcoverage) fromahighlyinbredSanClementebuckarebeingusedto createadenovocaprinereferencegenomeassemblymodel toenhance identiﬁcationof importantadaptivevariants

(Sonstegardetal.,2013,2014).Thelong-termgoalofthese

effortsistodevelopgenomictoolsforgoatsthatcanbe usedtobreedgeneticallysuperioradaptedgoatsandhelp meetrisingglobaldemandsforanimalproteinbasedfood. Moreover,withintheEUFP7projectNextgen, popula-tionsofdomesticgoats(C.hircus)andtheirwildancestors (bezoars,Capraaegagrus)weresequencedandgenotyped. Inparticular,164domesticgoatsfromMoroccowerewhole genomesequenced.Theirsamplingwasbasedonagrid systemtoinvestigateadaptive variation bya landscape genomicsapproachnewlydevelopedwithinNextgen.An evaluationofthepotentialofwildancestorsandtraditional breeds,asreservoirsofneutralandadaptivegenetic diver-sitywasalsoconducted,byanalysingthewholegenome ofabout40individuals(bezoarsandlocalIraniandomestic goats),sampledinIran.Thegenomeofthewildancestors wasassembleddenovoandresultedin6676scaffoldswith N50reaching1.75Mbandatotallengthof2.58Gb.

Conversely,toourknowledgeonlyafewgoat transcrip-tomeshavebeensequencedtodate,e.g.withinthe3SR project,wholeblood, mammaryglandand milksomatic

cellsfrom10alpinegoatshavebeensequencedina differ-entialexpressionexperimenttargetingmastitis.

4. Detectionofselectionsignaturesinthegoat genome

The availability of dense marker panels through-out the genome marked a paradigm shift in the way livestockpopulationsareinvestigatedandanalysed genet-ically,eitherforstudyingthepopulationgeneticstructure

(McKayetal.,2008),searchingforQTLcontrollingcomplex

traits(Kolbehdarietal.,2008),performinggenome-wide marker-enhancedselectionofyounganimals(VanRaden

et al., 2009; Hayeset al., 2009), identifyingpatterns of

recentandpastselection(Luikartetal.,2003;MacEachern etal.,2009)oraddressingotherobjectives.

Genomic regions under selection have a relevant importancebothinconservationandintheanalysisof com-plextraits. For conservation,loci underselection reveal functionaladaptation,complementingtheinformation col-lectedfromneutralgenomicregions(Boninetal.,2007). In addition, theypermittoinvestigate thegenetic con-troloftraitsextremelydifﬁcult,costlyorevenimpossible tomeasureinexperimentalconditions.Amongtheseare adaptationtoextremeclimatesandlow-qualityfeed,and diseaseresistance.Thesetraitsmayverywellberelevant for thesustainabilityof livestockhusbandryin timesof rapid and unpredictable climatechange. Projections, in fact,indicatearapidtrendtowardsawarmerplanetand shortergrowingseasonsinalargepartoftheworld.

Positivedirectionalselectionrapidlyfixesadvantageous allelesinapopulation.Iffixationisrapid,relativetotherate ofrecombination,neutralallelesaroundtheselectedlocus arefixedaswell,creatingalonginvarianthaplotypeblock aroundtheselectedlocusassignatureofrecentdirectional selection.

Rapidfixationofnewallelesbyselectionalsoincreases the divergence between selected and non-selected (or divergentlyselected)populationsintheregionaroundthe selectedlocus,comparedtoothergenomicregions.In con-trast,balancingselectionactivelymaintainsdiversityina populationforlongerthanexpectedunderneutralgenetic drift.Hence,regionsunderselection canbedetectedby searchingforoutliermarkersorhaplotypesineitherthe distributionofallelefrequencieswithinorbetween popu-lations(orgroupsofpopulations),orthepatternsoflinkage disequilibrium along the genome. This is based onthe assumption that selection hits specific genomic regions (theselectedlocusandlinkedgeneticmarkers),whiledrift and inbreeding influencethe entiregenome. These and similarmethodsfortheidentificationofselection signa-tureshavebeenreviewedinmoredetailbyOleksyketal.

(2010).

GiventheearlieravailabilityofSNPmarkers, genome-wide selectionsignatures havebeenmostly searchedin humans,usingbothsequence andgenome-widemarker

data (Oleksyk et al., 2010). In farm animals, they have

beeninvestigatedintheframeworkoftheHapMapproject and re-sequencing projects (e.g. The Bovine HapMap

Consortium,2009;Stellaetal.,2010).Inchicken,whole

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P.Ajmone-Marsanetal./SmallRuminantResearchxxx(2014)xxx–xxx 9 identiﬁed58genomicregionsunderselectioncontaining

geneslikely involved inthedomestication process.One ofthemostinterestingsignatureswasfoundindomestic chickens at the locus for thyroid stimulating hormone receptor (TSHR),which has a pivotal role in metabolic regulationandphotoperiodcontrolofreproduction(Rubin et al., 2010). However, inferring the cause of sweeps (i.e.theselectionforce)andidentifyingthegenesunder selectionarestilldifﬁculttasks,andrequireproper exper-imentaldesign, particularlywhenstudyingthecomplex traitsinvolvedinadaptation.

Aninterestingapproachhasrecentlybeenproposedby

Gautieretal.(2009).Asystembiologystrategywasused

toidentifythephysiologicalfunctionscontrolledbythe genomicregionsinvolvedinadaptivegeneticdivergencein WestAfricancattle.Bycontrastinggenome-widescansof ninecattlebreeds,andusingaBayesianmethod,they iden-tiﬁed53selectivesweeps.Thegenesclosesttothepeaks of signaturewere submittedto functionaland network analysesandfoundtobeinvolvedinthreemain physiolog-icalfunctions:immuneresponse,nervoussystemandhair andskindevelopment.Thisapproachispresentlylimited, however,by thedifﬁcultyin identifyingtherightgenes toincludeinsystembiologyanalyses,sincetheprecision withwhichselectionsignaturesarelocalizedisrelatively low, and bythepresent incompleteknowledge of gene functions.Theselimitationsmaybepartiallyovercomeby recentlydesignedmethodsthatuseacompositeof multi-plesignalstodetectselectionsignatures,greatlyincreasing theresolutionofdetection(Grossmanetal.,2010).

Selectionsignaturesspeciﬁcforadaptationhavebeen identiﬁed in humans (e.g. Harris and Meyer, 2006;

Lappalainenetal.,2010)andinwildorganisms(Boninetal.,

2006;Poncetetal.,2010)buttheirdiscoverywillbemost

usefulinlivestockspecies,inwhichtheymightverywell becometargetsofmarkerassistedorgenomicselection. Thishighlightstheneedforstrengtheningthe collabora-tionamongscientiﬁccommunitiesontheuseofemerging technologiesandnewanalyticalapproaches(Joostetal.,

2011).

Adifferentapproachtoidentifygenomicregions associ-atedtoenvironmentalvariablesisbasedonthecombined use of genomics and GIScience. GIScience permits to depict,exploreandcomparevariablesaccordingtotheir geographic coordinates. This allows the detection and description of spatial synchrony, identiﬁcation of data combinations associated with effects speciﬁc to a geo-graphicarea,calculationofsyntheticindicatorsand,most importantlyinthiscase,ofhiddenrelationshipsbetween variables (Joost etal., 2010).Recently a spatialanalysis method(SAM)basedonGISciencehasbeendevelopedto assessthelevelofassociationbetweenmolecularmarkers andenvironmentalparameters(Joostetal.,2007,2008). SAMisbasedonthespatialcoincidenceconcepttoconnect geneticinformationwithgeo-environmentaldata.Logistic regressionprovidesameasureoftheassociationbetween thefrequencyofmolecularmarkersandthe environmen-talparametersatsamplingsites.Theproofofconceptof the method was obtainedin the pine weevil (Hylobius abietis)andinsheep(Joostetal.,2007).Interestingly,in sheeptheDYMS1microsatellitemarker,previouslyshown

tobeinvolvedinparasiteresistance(Buítkampetal.,1996) wasfoundtobeassociatedtothenumberofwetdays,an environmentalvariablegreatlyinﬂuencingparasiteload.A fewotherinterestingexamplesoftheapplicationofSAM recentlyappeared in theliterature(Parisetet al.,2009;

ParisodandJoost,2010).Theinterestinthismethodstems

from its independency on population genetics models andcomplementaritytothepopulationgenomics meth-ods previously described (Pariset et al., 2009). Indeed, SAMappearstobemoresensitivecomparedtoFst-based approachesandabletolinksigniﬁcantgenomicregionsto speciﬁcenvironmentalvariables,rather thanidentifying signaturescausedbyselectionforcesnoteasytoidentify.

Goatbreedsadaptedtosustainableproductionsystems inextremeandharshenvironmentswillplayanimportant role inthis since responsemechanisms to environmen-talchallengeshavebeenevolvingformillionsofyears,in thewildancestorandinderiveddomesticates.The post-domesticationglobalcolonization,alongwithagriculture expansionand humanmigrations, hastaken goats well outsidetheagro-climaticrangeofadaptationofwild ances-tors. Nowadaysgoats countthousand localpopulations adaptedtoenvironmentsasdifferentassub-SaharanAfrica andNorway.AsingleexampleoftheSAMmethodapplied togoats hasto dateappeared in theliterature (Pariset etal., 2009).Theseauthors analysedsome 500animals from16Mediterraneanbreedswith27SNPsinfunctional genes.ThecombineduseofSAMandanFst-basedmethod identifiedthreeallelesunderenvironmentalselectionat avery highconfidencelevel. TwoSNPs areinthealpha S1 casein (CSN1S1) gene. The first SNP (CSN1S1ex9) is associatedtoseven andthe second(CSN1S1-5)tothree environmentalparameters. The third SNP, in the lipase gene,isalsoassociatedtothreeenvironmentalparameters. AsecondinvestigationusedtheEconogenegoatdataset (1228animalsbelongingto43EuropeanandNear East-erngoatbreedsspanningfromJordantoPoland)tolook forassociationbetweenenvironmentalvariables and96 AFLPmarkers.A totaloffourmarkerswerefoundtobe significantlyassociatedwithenvironmentalvariablesand confirmedtobeunderselectionbyatleastoneothertest implemented in either MCHEZA (Antao and Beaumont, 2011)orBAYESCAN(Gaggiotti,2010)software(Collietal., 2014)to search for associationbetween environmental variablesandAFLPmarkers.

Theidentiﬁcationof genes,causativemutations, and ultimatelythebiologicmechanismsinvolvedinadaptation remainachallengingundertaking,requiringtheintegrated approach of differentexpertise andthe difﬁculttaskof designingproperexperimentaldesignforvalidation exper-iments.However,theavailabilityofthegoat50kSNPpanel andof exome/wholegenome sequenceswillpermitthe testingandexploitationofSAMandothermethods detec-tingselectionsweepsattheirfullpotential,bypassingthe limitsoflowdensityofmicrosatellitesandAFLPs.

5. LandscapeGeneticsprojectsingoats

TheADAPTmap(http://bioinformatics.tecnoparco.org/

adaptmap/) is an International effort planned in

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10 P.Ajmone-Marsanetal./SmallRuminantResearchxxx(2014)xxx–xxx Consortium (IGGC) (http://www.goatgenome.org) and

withtheFeedtheFutureprogrammeoftheUSAIDagency

(http://www.feedthefuture.gov)toimprovecoordination

among otherwise independent projects for genotyping andre-sequencingofgoatbreeds.TheaimofADAPTmap istousebothtraditionalandnovelapproachestoexplore diversityofbreedsandpopulationsaroundtheworld. Pop-ulationstudiesaretargetedtoassessvariabilitybasedon mutationclassiﬁcation,analysingtheeffectsofmutations onproteinstructureasatagforadaptation.

Methods used for efﬁciently storing, querying and retrieving large-scale genomic, phenotyping and envi-ronmental data have been developed and an on-line questionnairedistributedtocollectandsummarize infor-mation on the various genomic initiatives on goats worldwide. Information hasbeen so far collected from 14 projects, most of which coordinated at thenational level. Thenumber of sampledbreeds ranges from 3 to 15andcoveredintotal31countriesandawide variabil-ityof environmentsand breedingsystems.Mostbreeds areautochthonous(80%) andmostlybredfor meat pro-duction(63%).In mostcases(about 70%),samplingand genotyping/re-sequencing activities are planned to be completedinearly2013.CollectionofFAOproduction envi-ronmentdescriptors(PED)isforeseenforabout40%ofthe populations.

A few large international projects, as FeedtheFuture and NextGen (Next Generation methods to preserve farm animal biodiversity, http://nextgen.epﬂ.ch/) are disentangling the diversity of the breeds/populations investigated,byrecordingandrelatinggenomicdiversity, morphologicaltraitsandseveralgeo-climaticparameters, for characterizing the breeding environment. In these projects,GlobalPositioningSystem(GPS)coordinatesare availablefor eachﬂock,allowingforapplicationof Geo-graphicalInformationSystems(GIS)and spatialanalysis

(Joostetal.,2007;Joostetal.,2010).

A few national and international projects, as 3SR (Sustainable Solutions for Small Ruminants;

http://www.3srbreeding.eu/), plan large-scale

geno-typing efforts to characterize commercial populations of goats and investigate marker–trait associations. The resultof linkageand genome-wide associationanalyses areusedtoselectindividualanimalsfor wholegenome re-sequencing.

Genomicanalysescomprisea largeamountof geno-typing with the Illumina 50k SNP panel. However, re-sequencingandgenotypingbysequencingtechniques willbeappliedonsomeofthesamepopulationsandde novosequencingapproacheswillbeappliedtowild ances-tors.Integrationofdatafromvarioussourceswillallow forthecomprehensiveapplicationofpopulationgenomics, forexample,toidentifyselectionsignaturesingroupsof breedsthatsharecommonphenotypes.

PreliminarydatafromtherecentlyestablishedItalian GoatConsortiumindicatethattheSNPpaneldeveloped in this species is highly polymorphic. Results on Oro-bica,Biondadell’AdamelloandValpassiriabreedsreared in the Central and Eastern Alps in Northern Italy and onGrigia CiociarafromCentral Italy, analysed withthe 50kSNPchip,indicatethat98.25%SNPsarepolymorphic

(rarealleleobservedatleastonce),1.1%monomorphicand 0.5%givenoresults.Inaddition97.6%hasMAF>1%.The existinggoatSNPpanelcanbepartiallyimprovedby inte-gratingadditionalwholegenomesequencesproducedby thepreviouslydescribedinternationalprojects,targeting populationsfromdifferentgeographiclocalities represent-ingtheareasofthedomesticationevent(s)andpotential agro-climatic adaptability.Hence, the contribution of a largernumberofsamples(i.e.asintherecentlylaunched 1000cattlegenomesinitiative)isneededtoachievea com-prehensiverepresentationoftheglobaldiversityingoats.

6. Reconstructionofgoatevolutionaryhistory

Theﬁrstresearchesontheevolutionarysystematicsof thegenusCapraandontheidentiﬁcationofthedomestic goatswildrelativeweremostlybasedontheanalysisof mitochondrialDNA.Thesestudiesshowedthatthebezoar C. aegagrus, themarkhor Capra falconeri,theKuban tur Capracaucasica, andtheeasternturCapracylindricornis, arethewildspeciesmorecloselyrelatedtodomesticgoats

(Pidancieretal.,2006).

Contrastinghypothesesregardingthewildancestorof domesticgoatshavebeensuggested,proposingeitherthe bezoar (Zeuner, 1963) or themarkhor, or both (Harris, 1962)as candidates.Inthe caseof theGirgentana goat breed(nativetoSicilyinsouthernItaly),forexample,the presence of screw-shapedhornssimilar tothose ofthe markhorandofsomehighlydivergentmtDNAhaplotypes

(Sardinaetal.,2006)seemedtosuggest anAsianorigin

(Portolano,1987)andadirectdescentfromC.falconeri.

Although some cases of introgressive hybridization betweenthewildspeciesandthedomesticgoatshavebeen reported(Giacometti etal., 2004;Hammer etal., 2008;

Alasaadetal.,2012),severalevidencebasedon

mitochon-drialcontrolregionvariation(Takadaetal.,1997;Mannen

etal.,2001;Naderietal.,2007,2008)ﬁnallychallengedthe

contributionofmarkhorandconﬁrmedthebezoarasthe wildancestorofC.hircus.

Recentevidence,bothinlivestockandwildlife,showed that molecular phylogenies based on a short and fast-evolving portionof mtDNA, suchas the controlregion, canbeheavilyaffectedbytheeffectsofNUMTs(NUclear Mitochondrial Transpositions, also called pseudogenes;

Hassaninetal.,2010;Moyleetal.,2013)andhomoplasy

(McCrackenand Sorenson,2005; Bonﬁglioet al., 2012),

whichmaymasktheactualextentofdivergence/similarity between mitochondrial lineages. mtDNA control region analysisincattleprovedtobeinadequateforathorough characterizationofmaternallineages,andafarmore pre-cisepicturehasbeenobtainedfromcompletesequencesof mitochondrialgenomes(Achillietal.,2008;Bonﬁglioetal.,

2010,2012).Nextgenerationsequencingtechnologiesnow

permit the high throughput/low cost analysis of entire mitochondrialgenomesatthemaximumresolution,and havebecomethecommonstandardfortheinvestigation of the human maternal lineages. The analysis of com-pletemitochondrialgenomeshasbeenrecentlyextended alsotogoat,toprovideamorecomprehensivemolecular phylogenyof thespecies.AﬁrststudybyNomuraetal.

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P.Ajmone-Marsanetal./SmallRuminantResearchxxx(2014)xxx–xxx 11 goatdomesticationdynamicsthroughtheanalysisofabout

10KbpofmtDNAprotein-encodinggenes.Further(andstill unpublished)analysesofmorethan70completemtDNA sequencesrepresentative ofC.hircus fromwestern Eur-asiaandonewildgoat(C.aegagrus)fromIranconfirmed a restricted number of mtDNA haplogroups. The topol-ogy of a maximum parsimony tree,based on complete mtDNAsandrootedwithaC.falconerisequence,revealed welldefinedmonophyleticcladescorrespondingto hap-logroupsA,B,CandG,allincludingatleastoneindividual ofsouthwestAsianorigin.HaplogroupAisconfirmedas themostfrequentinwesternEuropeangoats (including morethanhalfoftheanalysedsamples).Itsstar-likeshape suggeststheoccurrenceof arecent bottleneckfollowed byapopulationexpansionwhichlikelyrepresentsasingle domesticationeventoccurredinsouthwestAsiaand dat-ingbacktoNeolithictimes.Thestructureofsuchaclade closelyresemblesthatofthemtDNAhaplogroupT3of tau-rinecattle(Achillietal.,2008,2009),thussuggestingstrong similaritiesbetweenthedomesticationprocessesofthese twolivestockspecies.

7. Perspectives

The cost of DNA sequencing hasrecently decreased by orders of magnitude. This trend will likely con-tinue and open the door for very affordable whole genome sequencing in all livestock species, goats included. As a consequence, the amount of genomic informationisexpectedtogrowexponentially.Research focus is now shifting from the sequencing of a sin-gle individual to hundreds or even thousands of individuals. The “1000 genome project” in humans

(http://www.1000genomes.org), and the “Genome 10K

project” (http://genome10k.soe.ucsc.edu), targeting the wholegenome sequencing of 10,000vertebrate species areparadigmaticexamplesofthepresenttrend,recently extended to cattle (http://www.1000bullgenomes.com/) andinthenearfuturehopefullytogoats.

SequencingwillextendourknowledgeofSNPvariation, enhancingthediscoveryofrareallelesandallelesconﬁned to particular breeds or geographic areas, and on other polymorphisms potentially relevant for animal pheno-types,asinsertions,deletionsandcopynumbervariations (CNVs)(e.g.Beckmannetal.,2007).Arecentexampleof thepotentialofwholegenomesequence analysisisthe inference of human population size changes occurred during the last 10 Kya–1 Mya (Li and Durbin, 2011). Thisreconstructionwasbasedonapairwisesequentially Markoviancoalescentmodelthatallowstoinferthepast demographic history ofspeciesor populationsfromthe sequenceofsinglediploidgenomes.

Sequencingwillalsobeappliedtoidentifypatternsof methylationalongthegenome(Listeretal.,2009)andto quantifylevelsofgeneexpressionanddetectalternative splicingindifferenttissues,developmentaland environ-mentalconditions,hencepermittingtheinvestigationof genomefunctioninginagivenenvironment.

It isexpectedthat thesenewtoolswillfacilitatethe identiﬁcation and understanding of variation underpin-ningimportanttraits,includingphenotypesrelevant for

adaptationand sustainable exploitation.With regard to conservation,wholegenomesequencingwillalsoprovide moreobjectiveindicationsofuniquenessthananymarker panelandavoidtheascertainmentbiaspresentlyaffecting SNPpanels developed froma few breedsnot fully rep-resentingthegeneticvariationexistingwithinaspecies. In addition, adaptive variation will be included in pri-oritizationprotocols in order toensure conservationof unique adaptive variants, thus optimizing conservation effortsbothinvivoandinvitro.

Itisalsoenvisagedthatbreedingandselectionwillbe moreandmoreguidedbymolecularanalysis.Modelsareto bedevelopedandcustomizedtopopulationswithdifferent geneticstructure(smallvs.largebreeds)andtodifferent purposes(e.g.geneticimprovement,controlofinbreeding, maintenanceofdiversity).

Weconcludethatwearefacingachallengingand stim-ulatingtime.Althoughtherevolutionarydevelopmentof lowcostgenomicanalysismethodshascreated tremen-dousopportunitiesforgeneticanalysis,ithasalsocreated particularchallenges.Toolsforproducinggenomic infor-mationaboutlivestockbreedshaveadvancedfasterthan ourcapacitytoprocessandunderstandthisinformation. Storing,organizing,analysing,andinterpretationofthese datawillbethefuturechallengeforresearchersandwill morethaneverbeneﬁtfromnetworkingandintegrationof expertiseindifferentdisciplines.Inaddition,full exploita-tionoftheknowledgeresultingfromthisresearch,through itsapplicationinbreedingandconservationprogrammes, isalsohinderedbythelackofinfrastructureandtechnical capacity,especiallyindevelopingcountries.Underthese circumstances,anylossofbiodiversitybefore characteri-zationriskstoturnintoalossofinvaluableopportunities forbothscienceandagriculture.

Conﬂictofinterest

None of theauthors (P.Ajmone-Marsan, J.L.Han, A. Achilli,H.Lancioni,L.Colli,S.Joost,P.Crepaldi,F.Pilla,A. Stella,P.Taberlet,P.Boettcher,R.Negrini,J.A.Lenstra)has aﬁnancialorpersonalrelationshipwithotherpeopleor organizationsthatcouldinappropriatelyinﬂuenceorbias thepaperentitled “Thecharacterization of goatgenetic diversity:towardsagenomicapproach”.

Acknowledgement

WewishtothankDr.ElisaEufemiforthehelpprovided insummarizingtheinformationprovidedinTables1and2.

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