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1、作物学报ACTAAGRONOMICASINICA2016,42(7):945956http://zwxb.chinacrops.org/ISSN0496-3490;CODENTSHPA9E-mail:xbzw@chinajournal.net.cnDOI:10.3724/SP.J.1006.2016.00945植物关联分析方法的研究进展1112,*冯建英温阳俊张瑾章元明12南京农业大学作物遗传与种质创新国家重点实验室,江苏南京210095;华中农业大学植物科技学院,湖北武汉430070摘要:关联分析在人类和动植物遗传研究中的应用日益广泛,新方法及其软件包不断涌现。为对其更好选
2、择和应用,本文综述了关联分析的主要方法及其软件包。首先,介绍了群体结构对关联分析的影响;其次,重点介绍了单位点关联分析、多位点关联分析、上位性和多性状关联分析方法及其软件包;最后,展望了关联分析的发展动向。应当指出,基于群体结构和多基因整体背景控制的全基因组单标记快速扫描算法在目前的实际资料分析中应用较广泛,与其结果互补的是假阳性率较高的非参数方法。但是,今后的方法应当是以多位点模型、环境互作、上位性检验和多个相关性状联合分析为主。这为今后的理论与应用研究提供了有益信息。关键词:全基因组关联分析;上位性;混合线性模型;多位点模型AdvancesonMethodologiesfo
3、rGenome-wideAssociationStudiesinPlants1112,*FENGJian-Ying,WENYang-Jun,ZHANGJin,andZHANGYuan-Ming12StateKeyLaboratoryofCropGeneticsandGermplasmEnhancement,NanjingAgriculturalUniversity,Nanjing210095,China;CollegeofPlantScienceandTechnology,HuazhongAgriculturalUniversity,Wuhan430070,ChinaAbstr
4、act:Genome-wideassociationstudies(GWAS)havebeenwidelyusedinhuman,animalandplantgenetics,andmanynewapproachesandtheirsoftwareshavebeendevelopedinrecentyears.TomakeabetteruseoftheGWASmethodsinappliedresearch,inthisstudywesummarizedtheadvancesonmethodologiesandsoftwaresforGWAS.First,LDscoreregr
5、essionwasintroducedtoinvestigatetheeffectofpopulationstructureonGWAS.Then,themainapproachesandtheirsoftwaresforGWASinplantswerereviewed,includingasingle-locusmodel,amulti-locusmodel,epistasis,andmultiplecorrelatedtraits.Finally,weprospectedthefuturedevelopmentsinGWAS.Itshouldbenotedthat,inre
6、aldataanalysisatpresent,themethod-ologiesforgenome-widesingle-markerscanunderpolygenicbackgroundandpopulationstructurecontrolsarewidelyused,andthecorrespondingresultsarecomplementarytothosederivedfromnon-parameterapproacheswithhighfalsediscoveryrate.However,thefutureapproachesforGWASshouldbe
7、basedonthemulti-locusgeneticmodel,QTN-by-environmentin-teraction,epistaticdetectionandmultivariateanalysis.Ourpurposewastoprovidebeneficialinformationintheoreticalandappliedresearches.Keywords:Genome-wideassociationstudy;Epistasis;Mixedlinearmodel;
