整合GWAS和WGCNA分析挖掘甘蓝型油菜黄籽微效作用位点
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摘要
甘蓝型油菜是世界上最重要的油料作物之一,黄籽是提高品质的重要育种目标。本研究以520份具有代表性的甘蓝型油菜品种(系)为材料,结合种子发育过程中8个时期的转录组数据,采取整合全基因组关联分析(GWAS)和权重基因共表达网络分析(WGCNA)的策略,挖掘油菜黄籽性状微效作用位点,2年共检测到199个SNP位点,在SNP位点附近共挖掘出1826个名义候选基因。利用R语言中的WGCNA软件包构建了8个共表达模块,基因功能富集分析显示,turquoise模块和blue模块与黄籽表型相关。苯丙烷代谢途径、类黄酮途径的关键基因BnATCAD4、BnF3H以及BnANS为turquoise模块的枢纽基因(hub gene)。通过已知的黄籽相关基因,挖掘出了一部分黄籽微效作用基因,这些基因多参与苯丙烷、类黄酮以及原花青素代谢途径。本研究挖掘的这些位点和候选基因可作为影响油菜黄籽形成的重要候选区域和基因,有助于探究甘蓝型油菜黄籽基因资源信息、揭示油菜黄籽性状的遗传基础和分子机制、丰富分子育种理论以及提高油菜品质。
Brassica napus is one of the most important oil crops in the world, and developing yellow-seeded B. napus with improved qualities is a major breeding goal. The yellow-seeded minor genes were mined by genome-wide association study(GWAS) and weighted gene co-expression network analysis(WGCNA) with 520 representative varieties(or lines) and the transcriptional data at eight time points during the seed development. The 199 SNPs and 1826 nominally significant GWAS candidate genes were detected. Weighted gene co-expression network analysis was performed using the WGCNA R package to construct the resulting network composing eight distinct gene modules. Among them, the turquoise module and the blue module were related to the seed coat color based on gene function enrichment analysis. BnATCAD4, BnF3 H, and BnANS, the key enzymes genes of phenylpropane metabolic pathway and flavonoid metabolic pathway were found in turquoise module. Through the characterization of module content and topology, we mined a number of micro effect genes based on known yellow-seed related genes mainly involved in the phenylpropanoid metabolic process, flavonoid metabolic process and proanthocyanidin biosynthetic process. This information of minor loci and candidate genes should be useful in the breeding for yellow-seeded B. napus.
Brassica napus is one of the most important oil crops in the world, and developing yellow-seeded B. napus with improved qualities is a major breeding goal. The yellow-seeded minor genes were mined by genome-wide association study(GWAS) and weighted gene co-expression network analysis(WGCNA) with 520 representative varieties(or lines) and the transcriptional data at eight time points during the seed development. The 199 SNPs and 1826 nominally significant GWAS candidate genes were detected. Weighted gene co-expression network analysis was performed using the WGCNA R package to construct the resulting network composing eight distinct gene modules. Among them, the turquoise module and the blue module were related to the seed coat color based on gene function enrichment analysis. BnATCAD4, BnF3 H, and BnANS, the key enzymes genes of phenylpropane metabolic pathway and flavonoid metabolic pathway were found in turquoise module. Through the characterization of module content and topology, we mined a number of micro effect genes based on known yellow-seed related genes mainly involved in the phenylpropanoid metabolic process, flavonoid metabolic process and proanthocyanidin biosynthetic process. This information of minor loci and candidate genes should be useful in the breeding for yellow-seeded B. napus.
引文
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[2]张永泰,李爱民,蒋金金,王娟,王幼平.新型黄籽甘蓝型油菜的获得及其遗传规律分析.中国油料作物学报,2011,33:302-306Zhang Y T,Li A M,Jiang J J,Wang J,Wang Y P.Discovery and genetics of new type of yellow seed Brassica napus.Chin J Oil Crop Sci,2011,33:302-306(in Chinese with English abstract)
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[5]Wang J,Xian X H,Xu X F,Qu C M,Lu K,Li J N,Liu L Z.Genome wide association mapping of seed coat color in Brassica napus.J Agric Food Chem,2017,65:5229-5237
[6]杨小红,严建兵,郑艳萍,余建明,李建生.植物数量性状关联分析研究进展,作物学报,2007,33:523-530Yang X H,Yan J B,Zheng Y P,Yu J M,Li J S.Reviews of association analysis for quantitative traits in plants.Acta Agron Sin,2007,33:523-530(in Chinese with English abstract)
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[8]刘伟,李立,叶桦,屠伟.权重基因共表达网络分析在生物医学中的应用.生物工程学报,2017,33:1791-1801Liu W,Li L,Ye H,Tu W.Weighted gene co-expression network analysis in biomedicine research.Chin J Biotech,2017,33:1791-1801(in Chinese with English abstract)
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[11]Huang D,Koh C,Feurtado J A,Tsang E W,Cutler A J.Micro RNAs and their putative targets in Brassica napus seed maturation.BMC Genomics,2013,14:140
[12]Langfelder P,Horvath S.WGCNA:an R package for weighted correlation network analysis.BMC Bioinformatics,2008,9:559
[13]甘蓓,杨红玉.拟南芥中类黄酮代谢途径及其调控.安徽农业科学,2008,36:5290-5292Gan B,Yang H Y.Metabolic approach of flavonoids and its regulation in Arabidopsis thaliana.J Anhui Agric Sci,2008,36:5290-5292(in Chinese with English abstract)
[14]Pourcel L,Routaboul J M,Kerhoas L,Caboche M,Lepiniec L,Debeaujon I.TRANSPARENT TESTA10 encodes a laccase-like enzyme involved in oxidative polymerization of flavonoids in Arabidopsis seed coat.Plant Cell,2005,17:2966-2980
[15]黄杨岳,孔祥祯,甄宗雷,刘嘉.全基因组关联研究中的多重校正方法比较.心理科学进展,2013,21:1874-1882Huang Y Y,Kong X Z,Zhen Z L,Liu J.The comparison of multiple testing corrections methods in genome-wide association studies.Adv Psycholog Sci,2013,21:1874-1882
[16]Sato S,Uemoto Y,Kikuchi T,Egawa S,Kohira K,Saito S,Sakuma H,Miyashita S,Arata S,Kojima T,Suzuki K.SNP-and haplotype-based genome-wide association studies for growth,carcass,and meat quality traits in a Duroc multigenerational population.BMC Genet,2016,17:60
[17]Zhang W,Li J,Guo Y,Zhang L,Xu L,Gao X,Zhu B,Gao H,Ni H,Chen Y.Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle.Sci Rep,2016,6:38073
[18]Marshall C R,Howrigan D P,Merico D,Thiruvahindrapuram B,Wu W,Greer D S,Antaki D,Shetty A,Holmans P A,Pinto D,Gujral M,Brandler W M,Malhotra D,Wang Z,Fajarado K V F,Maile M S,Ripke S,Agartz I,Albus M,Alexander M,Amin F,Atkins J,Bacanu S A,Belliveau R A,Bergen S E,Bertalan M,Bevilacqua E,Bigdeli T B,Black D W,Bruggeman R,Buccola NG,Buckner R L,Bulik-Sullivan B,Byerley W,Cahn W,Cai G,Cairns M J,Campion D,Cantor R M,Carr V J,Carrera N,Catts S V,Chambert K D,Cheng W,Cloninger C R,Cohen D,Cormican P,Craddock N,Crespo-Facorro B,Crowley J J,Curtis D,Davidson M,Davis K L,Degenhardt F,Del Favero J,De Lisi L E,Dikeos D,Dinan T,Djurovic S,Donohoe G,Drapeau E,Duan J,Dudbridge F,Eichhammer P,Eriksson J,Escott-Price V,Essioux L,Fanous A H,Farh K H,Farrell M S,Frank J,Franke L,Freedman R,Freimer N B,Friedman J I,Forstner A J,Fromer M,Genovese G,Georgieva L,Gershon E S,Giegling I,Giusti-Rodríguez P,Godard S,Goldstein J I,Gratten J,de Haan L,Hamshere M L,Hansen M,Hansen T,Haroutunian V,Hartmann A M,Henskens F A,Herms S,Hirschhorn J N,Hoffmann P,Hofman A,Huang H,Ikeda M,Joa I,K?hler A K,Kahn R S,Kalaydjieva L,Karjalainen J,Kavanagh D,Keller M C,Kelly B J,Kennedy J L,Kim Y,Knowles J A,Konte B,Laurent C,Lee P,Lee S H,Legge S E,Lerer B,Levy D L,Liang K Y,Lieberman J,L?nnqvist J,Loughland C M,Magnusson P K E,Maher B S,Maier W,Mallet J,Mattheisen M,Mattingsdal M,Mc Carley RW,Mc Donald C,Mc Intosh A M,Meier S,Meijer C J,Melle I,Mesholam-Gately R I,Metspalu A,Michie P T,Milani L,Milanova V,Mokrab Y,Morris D W,Müller-Myhsok B,Murphy K C,Murray R M,Myin-Germeys I,Nenadic I,Nertney D A,Nestadt G,Nicodemus KK,Nisenbaum L,Nordin A,O’Callaghan E,O’Dushlaine C,Oh S Y,Olincy A,Olsen L,O'Neill F A,Van Os J,Pantelis C,Papadimitriou G N,Parkhomenko E,Pato M T,Paunio T,Perkins D O,Pers T H,Pietil?inen O,Pimm J,Pocklington A J,Powell J,Price A,Pulver A E,Purcell S M,Quested D,Rasmussen H B,Reichenberg A,Reimers M A,Richards A L,Roffman J L,Roussos P,Ruderfer D M,Salomaa V,Sanders A R,Savitz A,Schall U,Schulze T G,Schwab S G,Scolnick E M,Scott R J,Seidman L J,Shi J,Silverman J M,Smoller J W,S?derman E,Spencer C C A,Stahl E A,Strengman E,Strohmaier J,Stroup T S,Suvisaari J,Svrakic D M,Szatkiewicz J P,Thirumalai S,Tooney P A,Veijola J,Visscher P M,Waddington J,Walsh D,Webb B T,Weiser M,Wildenauer D B,Williams NM,Williams S,Witt S H,Wolen A R,Wormley B K,Wray N R,Wu J Q,Zai C C,Adolfsson R,Andreassen O A,Blackwood D HR,Bramon E,Buxbaum J D,Cichon S,Collier D A,Corvin A,Daly M J,Darvasi A,Domenici E,Esko T,Gejman P V,Gill M,Gurling H,Hultman C M,Iwata N,Jablensky A V,J?nsson E G,Kendler K S,Kirov G,Knight J,Levinson D F,Li Q S,Mc Carroll S A,Mc Quillin A,Moran J L,Mowry B J,N?then M M,Ophoff R A,Owen M J,Palotie A,Pato C N,Petryshen T L,Posthuma D,Rietschel M,Riley B P,Rujescu D,Sklar P,St Clair D,Walters J T R,Werge T,Sullivan P F,O’Donovan M C,Scherer S W,Neale B M,Sebat J.Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321subjects.Nat Genet,2017,49:27-35
[19]He J,Meng S,Zhao T,Xing G,Yang S,Li Y,Guan R,Lu J,Wang Y,Xia Q,Yang B,Gai J.An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding.Theor Appl Genet,2017,130:2327-2343
[20]叶小利,李加纳,唐章林,梁颖,谌利.甘蓝型油菜种皮色泽及相关性状的研究.作物学报,2001,27:550-556Ye X L,Li J N,Tang Z L,Liang Y,Chen L.Study on seed coat color and related characters of Brassica napus.Acta Agron Sin,2001,27:550-556(in Chinese with English abstract)
[21]Fu F Y,Liu L Z,Chai Y R,Chen L,Yang T,Jin M Y,Ma A F,Yan X Y,Zhang Z S,Li J N.Localization of QTLs for seed color using recombinant inbred lines of Brassica napus in different environments.Genome,2007,50:840-854
[22]Chai Y R,Lei B,Huang H L,Li J N,Yin J M,Tang Z L,Wang R,Chen L.TRANSPARENT TESTA12 genes from Brassica napus and parental species:cloning,evolution,and differential involvement in yellow seed trait.Mol Genet Genom,2009,281:109-123
[23]Zhang J,Lu Y,Yuan Y,Zhang X,Geng J,Chen Y,Cloutier S,Mc Vetty P B,Li G.Map-based cloning and characterization of a gene controlling hairiness and seed coat color traits in Brassica rapa.Plant Mol Biol,2009,69:553-563
[24]Stein A,Wittkop B,Liu L,Obermeier C,Friedt W,Snowdon R J.Dissection of a major QTL for seed colour and fibre content in Brassica napus reveals colocalization with candidate genes for phenylpropanoid biosynthesis and flavonoid deposition.Plant Breed,2013,132:382-389
[25]Padmaja L K,Agarwal P,Gupta V,Mukhopadhyay A,Sodhi Y S,Pental D,Pradhan A K.Natural mutations in two homoeologous TT8 genes control yellow seed coat trait in allotetraploid Brassica juncea(AABB).Theor Appl Genet,2014,127:339-347
[2]张永泰,李爱民,蒋金金,王娟,王幼平.新型黄籽甘蓝型油菜的获得及其遗传规律分析.中国油料作物学报,2011,33:302-306Zhang Y T,Li A M,Jiang J J,Wang J,Wang Y P.Discovery and genetics of new type of yellow seed Brassica napus.Chin J Oil Crop Sci,2011,33:302-306(in Chinese with English abstract)
[3]Remington D L,Thornsberry J M,Matsuoka Y,Wilson L M,Whitt S R,Doebley J,Kresovich S,Goodman M M,and Buckler E S.Structure of linkage disequilibrium and phenotypic associations in the maize genome.Proc Natl Acad Sci USA,2001,98:11479-11484
[4]Hasan M,Friedt W,Pons-Kuehnemann J,Freitag N M,Link K,Snowdon R J.Association of gene-linked SSR markers to seed glucosinolate content in oilseed rape(Brassica napus ssp.napus).Theor Appl Genet,2008,116:1035-1049
[5]Wang J,Xian X H,Xu X F,Qu C M,Lu K,Li J N,Liu L Z.Genome wide association mapping of seed coat color in Brassica napus.J Agric Food Chem,2017,65:5229-5237
[6]杨小红,严建兵,郑艳萍,余建明,李建生.植物数量性状关联分析研究进展,作物学报,2007,33:523-530Yang X H,Yan J B,Zheng Y P,Yu J M,Li J S.Reviews of association analysis for quantitative traits in plants.Acta Agron Sin,2007,33:523-530(in Chinese with English abstract)
[7]Zhang B,Horvath S.A general framework for weighted gene co-expression network analysis.Stat Appl Genet Mol Biol,2005,4:17
[8]刘伟,李立,叶桦,屠伟.权重基因共表达网络分析在生物医学中的应用.生物工程学报,2017,33:1791-1801Liu W,Li L,Ye H,Tu W.Weighted gene co-expression network analysis in biomedicine research.Chin J Biotech,2017,33:1791-1801(in Chinese with English abstract)
[9]Weiss J N,Karma A,Mac Lellan W R,Deng M,Rau C D,Rees CN,Wang J,Wisniewski N,Eskin E,Horvath S,Qu Z L,Wang YB,Lusis A J.“Good enough solutions”and the genetics of complex diseases.Circ Res,2012,111:493-504
[10]Farber C R.Systems-level analysis of genome-wide association data.G3:Genes Genom Genet,2013,3:119-129
[11]Huang D,Koh C,Feurtado J A,Tsang E W,Cutler A J.Micro RNAs and their putative targets in Brassica napus seed maturation.BMC Genomics,2013,14:140
[12]Langfelder P,Horvath S.WGCNA:an R package for weighted correlation network analysis.BMC Bioinformatics,2008,9:559
[13]甘蓓,杨红玉.拟南芥中类黄酮代谢途径及其调控.安徽农业科学,2008,36:5290-5292Gan B,Yang H Y.Metabolic approach of flavonoids and its regulation in Arabidopsis thaliana.J Anhui Agric Sci,2008,36:5290-5292(in Chinese with English abstract)
[14]Pourcel L,Routaboul J M,Kerhoas L,Caboche M,Lepiniec L,Debeaujon I.TRANSPARENT TESTA10 encodes a laccase-like enzyme involved in oxidative polymerization of flavonoids in Arabidopsis seed coat.Plant Cell,2005,17:2966-2980
[15]黄杨岳,孔祥祯,甄宗雷,刘嘉.全基因组关联研究中的多重校正方法比较.心理科学进展,2013,21:1874-1882Huang Y Y,Kong X Z,Zhen Z L,Liu J.The comparison of multiple testing corrections methods in genome-wide association studies.Adv Psycholog Sci,2013,21:1874-1882
[16]Sato S,Uemoto Y,Kikuchi T,Egawa S,Kohira K,Saito S,Sakuma H,Miyashita S,Arata S,Kojima T,Suzuki K.SNP-and haplotype-based genome-wide association studies for growth,carcass,and meat quality traits in a Duroc multigenerational population.BMC Genet,2016,17:60
[17]Zhang W,Li J,Guo Y,Zhang L,Xu L,Gao X,Zhu B,Gao H,Ni H,Chen Y.Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle.Sci Rep,2016,6:38073
[18]Marshall C R,Howrigan D P,Merico D,Thiruvahindrapuram B,Wu W,Greer D S,Antaki D,Shetty A,Holmans P A,Pinto D,Gujral M,Brandler W M,Malhotra D,Wang Z,Fajarado K V F,Maile M S,Ripke S,Agartz I,Albus M,Alexander M,Amin F,Atkins J,Bacanu S A,Belliveau R A,Bergen S E,Bertalan M,Bevilacqua E,Bigdeli T B,Black D W,Bruggeman R,Buccola NG,Buckner R L,Bulik-Sullivan B,Byerley W,Cahn W,Cai G,Cairns M J,Campion D,Cantor R M,Carr V J,Carrera N,Catts S V,Chambert K D,Cheng W,Cloninger C R,Cohen D,Cormican P,Craddock N,Crespo-Facorro B,Crowley J J,Curtis D,Davidson M,Davis K L,Degenhardt F,Del Favero J,De Lisi L E,Dikeos D,Dinan T,Djurovic S,Donohoe G,Drapeau E,Duan J,Dudbridge F,Eichhammer P,Eriksson J,Escott-Price V,Essioux L,Fanous A H,Farh K H,Farrell M S,Frank J,Franke L,Freedman R,Freimer N B,Friedman J I,Forstner A J,Fromer M,Genovese G,Georgieva L,Gershon E S,Giegling I,Giusti-Rodríguez P,Godard S,Goldstein J I,Gratten J,de Haan L,Hamshere M L,Hansen M,Hansen T,Haroutunian V,Hartmann A M,Henskens F A,Herms S,Hirschhorn J N,Hoffmann P,Hofman A,Huang H,Ikeda M,Joa I,K?hler A K,Kahn R S,Kalaydjieva L,Karjalainen J,Kavanagh D,Keller M C,Kelly B J,Kennedy J L,Kim Y,Knowles J A,Konte B,Laurent C,Lee P,Lee S H,Legge S E,Lerer B,Levy D L,Liang K Y,Lieberman J,L?nnqvist J,Loughland C M,Magnusson P K E,Maher B S,Maier W,Mallet J,Mattheisen M,Mattingsdal M,Mc Carley RW,Mc Donald C,Mc Intosh A M,Meier S,Meijer C J,Melle I,Mesholam-Gately R I,Metspalu A,Michie P T,Milani L,Milanova V,Mokrab Y,Morris D W,Müller-Myhsok B,Murphy K C,Murray R M,Myin-Germeys I,Nenadic I,Nertney D A,Nestadt G,Nicodemus KK,Nisenbaum L,Nordin A,O’Callaghan E,O’Dushlaine C,Oh S Y,Olincy A,Olsen L,O'Neill F A,Van Os J,Pantelis C,Papadimitriou G N,Parkhomenko E,Pato M T,Paunio T,Perkins D O,Pers T H,Pietil?inen O,Pimm J,Pocklington A J,Powell J,Price A,Pulver A E,Purcell S M,Quested D,Rasmussen H B,Reichenberg A,Reimers M A,Richards A L,Roffman J L,Roussos P,Ruderfer D M,Salomaa V,Sanders A R,Savitz A,Schall U,Schulze T G,Schwab S G,Scolnick E M,Scott R J,Seidman L J,Shi J,Silverman J M,Smoller J W,S?derman E,Spencer C C A,Stahl E A,Strengman E,Strohmaier J,Stroup T S,Suvisaari J,Svrakic D M,Szatkiewicz J P,Thirumalai S,Tooney P A,Veijola J,Visscher P M,Waddington J,Walsh D,Webb B T,Weiser M,Wildenauer D B,Williams NM,Williams S,Witt S H,Wolen A R,Wormley B K,Wray N R,Wu J Q,Zai C C,Adolfsson R,Andreassen O A,Blackwood D HR,Bramon E,Buxbaum J D,Cichon S,Collier D A,Corvin A,Daly M J,Darvasi A,Domenici E,Esko T,Gejman P V,Gill M,Gurling H,Hultman C M,Iwata N,Jablensky A V,J?nsson E G,Kendler K S,Kirov G,Knight J,Levinson D F,Li Q S,Mc Carroll S A,Mc Quillin A,Moran J L,Mowry B J,N?then M M,Ophoff R A,Owen M J,Palotie A,Pato C N,Petryshen T L,Posthuma D,Rietschel M,Riley B P,Rujescu D,Sklar P,St Clair D,Walters J T R,Werge T,Sullivan P F,O’Donovan M C,Scherer S W,Neale B M,Sebat J.Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321subjects.Nat Genet,2017,49:27-35
[19]He J,Meng S,Zhao T,Xing G,Yang S,Li Y,Guan R,Lu J,Wang Y,Xia Q,Yang B,Gai J.An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding.Theor Appl Genet,2017,130:2327-2343
[20]叶小利,李加纳,唐章林,梁颖,谌利.甘蓝型油菜种皮色泽及相关性状的研究.作物学报,2001,27:550-556Ye X L,Li J N,Tang Z L,Liang Y,Chen L.Study on seed coat color and related characters of Brassica napus.Acta Agron Sin,2001,27:550-556(in Chinese with English abstract)
[21]Fu F Y,Liu L Z,Chai Y R,Chen L,Yang T,Jin M Y,Ma A F,Yan X Y,Zhang Z S,Li J N.Localization of QTLs for seed color using recombinant inbred lines of Brassica napus in different environments.Genome,2007,50:840-854
[22]Chai Y R,Lei B,Huang H L,Li J N,Yin J M,Tang Z L,Wang R,Chen L.TRANSPARENT TESTA12 genes from Brassica napus and parental species:cloning,evolution,and differential involvement in yellow seed trait.Mol Genet Genom,2009,281:109-123
[23]Zhang J,Lu Y,Yuan Y,Zhang X,Geng J,Chen Y,Cloutier S,Mc Vetty P B,Li G.Map-based cloning and characterization of a gene controlling hairiness and seed coat color traits in Brassica rapa.Plant Mol Biol,2009,69:553-563
[24]Stein A,Wittkop B,Liu L,Obermeier C,Friedt W,Snowdon R J.Dissection of a major QTL for seed colour and fibre content in Brassica napus reveals colocalization with candidate genes for phenylpropanoid biosynthesis and flavonoid deposition.Plant Breed,2013,132:382-389
[25]Padmaja L K,Agarwal P,Gupta V,Mukhopadhyay A,Sodhi Y S,Pental D,Pradhan A K.Natural mutations in two homoeologous TT8 genes control yellow seed coat trait in allotetraploid Brassica juncea(AABB).Theor Appl Genet,2014,127:339-347