中国农业科学 ›› 2013, Vol. 46 ›› Issue (4): 819-829.doi: 10.3864/j.issn.0578-1752.2013.04.016
王继英, 王海霞, 迟瑞宾, 郭建凤, 武英
收稿日期:
2012-08-22
出版日期:
2013-02-15
发布日期:
2012-10-29
联系方式:
王继英,E-mail:jnwangjiying@163.com
基金资助:
优质肉猪新品种(配套系)选育研究(2010LZ013-01)、转基因生物新品种培育重大专项(2011ZX08006-005)、国家生猪产业技术体系(CARS-36)、山东省农业产业技术体系生猪创新团队建设项目
WANG Ji-Ying, WANG Hai-Xia, CHI Rui-Bin, GUO Jian-Feng, WU Ying
Received:
2012-08-22
Published:
2013-02-15
Online:
2012-10-29
摘要: 全基因组关联分析(genome-wide association studies,GWAS)是近几年发展起来的一种复杂性状研究的新方法。在过去几年中,国内外不少研究者对畜禽的重要经济性状、遗传缺陷性疾病、复杂疾病的抗性、品种的某些特征等性状开展了GWAS。这些研究不仅大大丰富了畜禽标记辅助选择中可利用的分子标记,而且为这些性状分子机理的探索研究提供了重要线索。本文对国内外畜禽GWAS中所用的群体、主要分析方法和研究结果进行综述,并对GWAS的研究应用做一展望,以期为进一步利用GWAS进行畜禽各种性状遗传基础的研究提供参考。
王继英, 王海霞, 迟瑞宾, 郭建凤, 武英. 全基因组关联分析在畜禽中的研究进展[J]. 中国农业科学, 2013, 46(4): 819-829.
WANG Ji-Ying, WANG Hai-Xia, CHI Rui-Bin, GUO Jian-Feng, WU Ying. Progresses in Research of Genome-Wide Association Studies in Livestock and Poultry[J]. Scientia Agricultura Sinica, 2013, 46(4): 819-829.
[1]Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science, 1996, 273(5281): 1516-1517.[2]Hirschhorn J N, Daly M J. Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics, 2005, 6(2): 95-108.[3]Klein R J, Zeiss C, Chew E Y, Tsai J Y, Sackler R S, Haynes C, Henning A K, SanGiovanni J P, Mane S M, Mayne S T, Bracken M B, Ferris F L, Ott J, Barnstable C, Hoh J. Complement factor H polymorphism in age-related macular degeneration. Science, 2005, 308(5720): 385-389.[4]McCarthy M I, Hirschhorn J N. Genome-wide association studies: potential next steps on a genetic journey. Human molecular Genetics, 2008, 17(R2): R156-R165.[5]Matukumalli L K, Lawley C T, Schnabel R D, Taylor J F, Allan M F, Heaton M P, O’Connell J, Moore S S, Smith T, Sonstegard T S, van Tassell C P. Development and characterization of a high density SNP genotyping assay for cattle. PLoS One, 2009, 4(4): e5350.[6]Ramos A M, Crooijmans R P, Affara N A, Amaral A J, Archibald A L, Beever J E, Bendixen C, Churcher C, Clark R, Dehais P, Hansen M S, Hedegaard J, Hu Z L, Kerstens H H, Law A S, Megens H J, Milan D, Nonneman D J, Rohrer G A, Rothschild M F, Smith T P, Schnabel R D, van Tassell C P, Taylor J F, Wiedmann R T, Schook L B, Groenen M A. Design of a high density SNP genotyping assay in the pig using SNPs identified and characterized by next generation sequencing technology. PLoS One, 2009, 4(8): e6524.[7]Groenen M A M, Megens H J, Zare Y, Warren W C, Hillier L D W, Crooijmans R P M A, Vereijken A, Okimoto R, Muir W M, Cheng H H. The development and characterization of a 60K SNP chip for chicken. BMC Genomics, 2011, 12(1): 274-282.[8]McCue M E, Bannasch D L, Petersen J L, Gurr J, Bailey E, Binns M M, Distl O, Guérin G, Hasegawa T, Hill E W, Leeb T, Lindgren G, Penedo M C, Røed K H, Ryder O A, Swinburne J E, Tozaki T, Valberg S J, Vaudin M, Lindblad-Toh K, Wade C M, Mickelson J R. A High density SNP array for the domestic horse and extant perissodactyla: utility for association mapping, genetic diversity, and phylogeny studies. PLoS Genetics, 2012, 8(1): e1002451.[9]Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M A R, Bender D, Maller J, Sklar P, de Bakker P I W, Daly M J, Sham P C. PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics, 2007, 81(3): 559-575.[10]Aulchenko Y S, Ripke S, Isaacs A, van Duijn C M. GenABEL: an R library for genome-wide association analysis. Bioinformatics, 2007, 23(10): 1294-1296.[11]Amin N, van Duijn C M, Aulchenko Y S. A genomic background based method for association analysis in related individuals. PLoS One, 2007, 2(12): e1274.[12]Thornton T, McPeek M S. ROADTRIPS: case-control association testing with partially or completely unknown population and pedigree structure. The American Journal of Human Genetics, 2010, 86(2): 172-184.[13]严卫丽. 复杂疾病全基因组关联研究进展—遗传统计分析. 遗传, 2008, 30(5): 543-549. Yan W L. Genome-wide association study on complex diseases: genetic statistical issues. Hereditas, 2008, 30(5): 543-549. (in Chinese)[14]Jiang L, Liu J F, Sun D X, Ma P P, Ding X D, Yu Y, Zhang Q. Genome wide association studies for milk production traits in Chinese Holstein population. PLoS One, 2010, 5(10): e13661.[15]Zhang Z, Buckler E S, Casstevens T M, Bradbury P J. Software engineering the mixed model for genome-wide association studies on large samples. Briefings in Bioinformatics, 2009, 10(6): 664-675.[16]Lam A C, Schouten M, Aulchenko Y, Haley C S, de Koning D J. Rapid and robust association mapping of expression quantitative trait loci. BMC Proceedings, 2007, 1(Suppl.1): S144-S148.[17]Zhao H H, Fernando R L, Dekkers J C M. Power and precision of alternate methods for linkage disequilibrium mapping of quantitative trait loci. Genetics, 2007, 175(4): 1975-1986.[18]Grapes L, Dekkers J C M, Rothschild M F, Fernando R L. Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci. Genetics, 2004, 166(3): 1561-1570.[19]Newton-Cheh C, Hirschhorn J N. Genetic association studies of complex traits: design and analysis issues. Mutation Research/ Fundamental and Molecular Mechanisms of Mutagenesis, 2005, 573(1/2): 54-69.[20]Wang K, Li M, Hakonarson H. Analysing biological pathways in genome-wide association studies. Nature Reviews Genetics, 2010, 11(12): 843-854.[21]Daetwyler H D, Schenkel F S, Sargolzaei M, Robinson J A B. A genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using two methods and a dense single nucleotide polymorphism map. Journal of Dairy Science, 2008, 91(8): 3225-3236.[22]Mai M D, Sahana G, Christiansen F B, Guldbrandtsen B. A genome-wide association study for milk production traits in Danish Jersey cattle using a 50K single nucleotide polymorphism chip. Journal of Animal Science, 2010, 88(11): 3522-3528.[23]Schopen G C B, Visker M H P W, Koks P D, Mullaart E, van Arendonk J A M, Bovenhuis H. Whole-genome association study for milk protein composition in dairy cattle. Journal of Dairy Science, 2011, 94(6): 3148-3158.[24]Bouwman A C, Bovenhuis H, Visker M H P W, van Arendonk J A M. Genome-wide association of milk fatty acids in Dutch Dairy cattle. BMC Genetics, 2011, 12(1): 43-54.[25]Meredith B K, Kearney F J, Finlay E K, Bradley D G, Fahey A G, Berry D P, Lynn D J. Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland. BMC Genetics, 2012, 13(1): 21-32.[26]Olsen H G, Hayes B J, Kent M P, Nome T, Svendsen M, Lien S. A genome wide association study for QTL affecting direct and maternal effects of stillbirth and dystocia in cattle. Animal Genetics, 2010, 41(3): 273-280. [27]Olsen H G, Hayes B J, Kent M P, Nome T, Svendsen M, Larsgard A G, Lien S. Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12. Animal Genetics, 2011, 42(5): 466-474.[28]Sahana G, Guldbrandtsen B, Bendixen C, Lund M S. Genome-wide association mapping for female fertility traits in Danish and Swedish Holstein cattle. Animal Genetics, 2010, 41(6): 579-588.[29]Sahana G, Guldbrandtsen B, Lund M S. Genome-wide association study for calving traits in Danish and Swedish Holstein cattle. Journal of Dairy Science, 2011, 94(1): 479-486.[30]Huang W, Kirkpatrick B W, Rosa G J M, Khatib H. A genome-wide association study using selective DNA pooling identifies candidate markers for fertility in Holstein cattle. Animal Genetics, 2010, 41(6): 570-578.[31]Settles M, Zanella R, McKay S D, Schnabel R D, Taylor J F, Whitlock R, Schukken Y, van Kessel J S, Smith J M, Neibergs H. A whole genome association analysis identifies loci associated with Mycobacterium avium subsp. paratuberculosis infection status in US holstein cattle. Animal Genetics, 2009, 40(5): 655-662.[32]Pant S D, Schenkel F S, Verschoor C P, You Q, Kelton D F, Moore S S, Karrow N A. A principal component regression based genome wide analysis approach reveals the presence of a novel QTL on BTA7 for MAP resistance in holstein cattle. Genomics, 2010, 95(3): 176-182.[33]Kirkpatrick B W, Shi X, Shook G E, Collins M T. Whole-genome association analysis of susceptibility to paratuberculosis in Holstein cattle. Animal Genetics, 2011, 42(2): 149-160.[34]Zanella R, Settles M L, McKay S D, Schnabel R, Taylor J, Whitlock R H, Schukken Y, van Kessel J S, Smith J M, Neibergs H L. Identification of loci associated with tolerance to Johne’s disease in Holstein cattle. Animal Genetics, 2011, 42(1): 28-38.[35]Finlay E K, Berry D P, Wickham B, Gormley E P, Bradley D G. A genome eide association scan of bovine tuberculosis susceptibility in Holstein-Friesian Dairy cattle. PLoS One, 2012, 7(2): e30545.[36]Sodeland M, Kent M P, Olsen H G, Opsal M A, Svendsen M, Sehested E, Hayes B J, Lien S. Quantitative trait loci for clinical mastitis on chromosomes 2, 6, 14 and 20 in Norwegian Red cattle. Animal Genetics, 2011, 42(5): 457-465.[37]Bolormaa S, Neto L R P, Zhang Y D, Bunch R J, Harrison B E, Goddard M F, Barendse W. A genome-wide association study of meat and carcass traits in Australian cattle. Journal of Animal Science, 2011, 89(8): 2297-2309.[38]Duijvesteijn N, Knol E F, Merks J W M, Crooijmans R P M A, Groenen M A M, Bovenhuis H, Harlizius B. A genome-wide association study on androstenone levels in pigs reveals a cluster of candidate genes on chromosome 6. BMC Genetics, 2010, 11(1): 42-52.[39]Fan B, Onteru S K, Du Z Q, Garrick D J, Stalder K J, Rothschild M F, Sorensen T I A. Genome-wide association study identifies loci for body composition and structural soundness traits in pigs. PLoS One, 2010, 6(2): e14726.[40]Luo W Z, Cheng D X, Chen S K, Wang L G, Li Y, Ma X J, Song X, Liu X, Li W, Liang J, Yan H, Zhao K B, Wang C D, Wang L, Zhang L X, Zhang L C. Genome-wide association analysis of meat quality traits in a porcine large White × Minzhu intercross population. International Journal of Biological Sciences, 2012, 8(4): 580-595.[41]Ren J, Mao H, Zhang Z, Xiao S, Ding N, Huang L. A 6-bp deletion in the TYRP1 gene causes the brown colouration phenotype in Chinese indigenous pigs. Heredity, 2011, 106: 862-868.[42]Cho I C, Zhong T, Seo B Y, Jung E J, Yoo C K, Kim J H, Lee J B, Lim H T, Kim B W, Lee J H, Ko M S, Jeon J T. Whole-genome association study for the roan coat color in an intercrossed pig population between Landrace and Korean native pig. Genes and Genomics, 2011, 33(1): 17-23.[43]Onteru S K, Fan B, Nikkila M T, Garrick D J, Stalder K J, Rothschild M F. Whole-genome association analyses for lifetime reproductive traits in the pig. Journal of Animal Science, 2011, 89(4): 988-995.[44]Onteru S K, Fan B, Du Z Q, Garrick D J, Stalder K J, Rothschild M F. A whole-genome association study for pig reproductive traits. Animal Genetics, 2012, 43(1): 18-26.[45]卢昕. 猪部分免疫性状的QTL定位及全基因组关联分析[D]. 北 京: 中国农业大学, 2010.Lu X. Quantitative trait Loci (QTL) mapping and genome-wide association study for some immune traits in swine[D]. Beijing: China Agricultural University, 2010. (in Chinese)[46]罗艳茹. 猪血常规和溶菌酶性状的全基因组关联分析[D]. 北京: 中国农业大学, 2010.Luo Y R. Genome-wide association study for haematological parameters and lysozyme concentration in swine[D]. Beijing: China Agricultural University, 2010. (in Chinese)[47]Wang J Y, Luo Y R, Fu W X, Lu X, Zhou J P, Ding X D, Liu J F, Zhang Q. Genome-wide association studies for hematological traits in swine. Animal Genetics, 2012. doi: 10.1111/j.1365-2052.2012. 02366.x.[48]王继英. 猪免疫性状的全基因组关联分析及拷贝数变异的检测[D]. 北京: 中国农业大学, 2012.Wang J Y. Genome-wide association studies for immune traits and detection of copy number variations in swine[D]. Beijing: China Agricultural University, 2010. (in Chinese)[49]Fu W X, Liu Y, Lu X, Niu X Y, Ding X D, Liu J F, Zhang Q. A genome-wide association study identifies two novel promising candidate genes affecting escherichia coli F4ab/F4ac susceptibility in swine. PLoS One, 2012, 7(3): e32127.[50]Luo W Z, Chen S K, Cheng D X, Wang L G, Li Y, Ma X J, Song X, Liu X, Li W, Liang J, Yan H, Zhao K B, Wang C D, Wang L X, Zhang L C. Genome-wide association study of porcine hematological parameters in a large White×Minzhu F2 resource population. International Journal of Biological Sciences, 2012, 8(6): 870-881.[51]Abasht B, Lamont S J. Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population. Animal Genetics, 2007, 38(5): 491-498.[52]Liu W B, Li D F, Liu J F, Chen S R, Qu L J, Zheng J X, Xu G Y, Yang N. A genome-wide SNP scan reveals novel loci for egg production and quality traits in White Leghorn and Brown-Egg dwarf layers. PLoS One, 2011, 6(12): e28600.[53]Shen X, Zeng H, Xie L, He J, Li J, Xie X J, Luo C L, Xu H P, Zhou M, Nie Q H, Zhang X Q. The GTPase activating Rap/RanGAP domain-like 1 gene is associated with chicken reproductive traits. PLoS One, 2012, 7(4): e33851.[54]Gu X R, Feng C G, Ma L, Song C, Wang Y Q, Da Y, Li H F, Chen K W, Ye S H, Ge C R, Li X X, Li N. Genome-wide association study of body weight in chicken F2 resource population. PLoS One, 2011, 6(7): e21872.[55]Xie L, Luo C L, Zhang C G, Zhang R, Tang J, Nie Q H, Ma L, Hu X X, Li N, Da Y, Zhang X Q. Genome-wide association study identified a narrow chromosome 1 region associated with chicken growth traits. PLoS One, 2012, 7(2): e30910.[56]Zhao X, Dittmer K E, Blair H T, Thompson K G, Rothschild M F, Garrick D J. A novel nonsense mutation in the DMP1 gene identified by a genome-wide association study is responsible for inherited rickets in Corriedale sheep. PLoS One, 2011, 6(7): e21739.[57]Kemper K E, Emery D L, Bishop S C, Oddy H, Hayes B J, Dominik S, Henshall J M, Goddard M E. The distribution of SNP marker effects for faecal worm egg count in sheep, and the feasibility of using these markers to predict genetic merit for resistance to worm infections. Genetics Research, 2011, 93(3): 203-219.[58]Johnston S E, McEwan J C, Pickering N K, Kijas J W, Beraldi D, Pilkington J G, Pemberton J M, Slate J. Genome-wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population. Molecular Ecology, 2011, 20(12): 2555-2566.[59]Brooks S A, Gabreski N, Miller D, Brisbin A, Brown H E, Streeter C, Mezey J, Cook D, Antczak D F. Whole genome SNP association in the horse: identification of a deletion in myosin va responsible for lavender foal syndrome. PLoS Genetics, 2010, 6(4): e1000909.[60]Orr N, Back W, Gu J, Leegwater P, Govindarajan P, Conroy J, Ducro B, van Arendonk J A M, MacHugh D E, Ennis S, Hill E W, Brama P A J. Genome-wide SNP association-based localization of a dwarfism gene in Friesian dwarf horses. Animal Genetics, 2010, 41(Suppl. 2): 2-7.[61]Schurink A, Ducro B J, Bastiaansen J W M, Frankena K, van Arendonk J A M. Genome-wide association study of insect bite hypersensitivity in Dutch Shetland pony mares. Animal Genetics, 2012. doi: 10.1111/j.1365-2052.2012.02368.x.[62]Hill E W, McGivney B A, Gu J, Whiston R, MacHugh D E. A genome-wide SNP-association study confirms a sequence variant (g. 66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses. BMC Genomics, 2010, 11(1): 552-561.[63]Cardon L R, Palmer L J. Population stratification and spurious allelic association. The Lancet, 2003, 361(9357): 598-604.[64]Devlin B, Roeder K, Wasserman L. Genomic control, a new approach to genetic-based association studies. Theoretical Population Biology, 2001, 60(3): 155-166.[65]Zhu X F, Zhang S L, Zhao H Y, Cooper R S. Association mapping, using a mixture model for complex traits. Genetic Epidemiology, 2002, 23(2): 181-196.[66]Zhu X F, Li S C, Cooper R S, Elston R C. A unified association analysis approach for family and unrelated samples correcting for stratification. The American Journal of Human Genetics, 2008, 82(2): 352-365.[67]Pearson T A, Manolio T A. How to interpret a genome-wide association study. The Journal of the American Medical Association, 2008, 299(11): 1335-1344.[68]Chanock S J, Manolio T, Boehnke M, Boerwinkle E, Hunter D J, Thomas G, Hirschhorn J N, Abecasis G, Altshuler D, Bailey-Wilson J E. Replicating genotype-phenotype associations. Nature, 2007, 447(7145): 655-660.[69]Glass G V. Primary, secondary, and meta-analysis of research. Educational Researcher, 1976, 5(10): 3-8.[70]The International SNP Map Working Group. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature, 2001, 409(6822): 928-933.[71]McCarroll S A. Extending genome-wide association studies to copy-number variation. Human Molecular Genetics, 2008, 17(R2): R135-R142.[72]Iafrate A J, Feuk L, Rivera M N, Listewnik M L, Donahoe P K, Qi Y, Scherer S W, Lee C. Detection of large-scale variation in the human genome. Nature Genetics, 2004, 36(9): 949-951.[73]Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, Månér S, Massa H, Walker M, Chi M, Navin N, Lucito R, Healy J, Hicks J, Ye K, Reiner A, Gilliam T C, Trask B, Patterson N, Zetterberg A, Wigler M. Large-scale copy number polymorphism in the human genome. Science, 2004, 305(5683): 525-528.[74]Seroussi E, Glick G, Shirak A, Yakobson E, Weller J I, Ezra E, Zeron Y. Analysis of copy loss and gain variations in Holstein cattle autosomes using BeadChip SNPs. BMC Genomics, 2010, 11(1): 673-682.[75]Liu G E, Brown T, Hebert D A, Cardone M F, Hou Y, Choudhary R K, Shaffer J, Amazu C, Connor E E, Ventura M, Gasbarre L C. Initial analysis of copy number variations in cattle selected for resistance or susceptibility to intestinal nematodes. Mammalian Genome, 2011, 22: 111-121. |
[1] | 龚世飞, 肖能武, 丁武汉, 居学海, 吴平华, 余永松, 李虎. 基于耕地承载力的十堰市畜禽养殖环境风险评价[J]. 中国农业科学, 2023, 56(5): 920-934. |
[2] | 徐久凯, 袁亮, 温延臣, 张水勤, 李燕婷, 李海燕, 赵秉强. 畜禽有机肥氮在冬小麦季对化肥氮的相对替代当量[J]. 中国农业科学, 2023, 56(2): 300-313. |
[3] | 刘高远, 和爱玲, 杜君, 吕金岭, 聂胜委, 潘秀燕, 许纪东, 李珏, 杨占平. 有机肥替代化肥对砂姜黑土区小麦-玉米轮作系统N2O排放的影响[J]. 中国农业科学, 2023, 56(16): 3156-3167. |
[4] | 黄勋和,翁茁先,李威娜,王庆,何丹林,罗威,张细权,杜炳旺. 中国地方品种黄鸡线粒体DNA D-loop遗传多样性研究[J]. 中国农业科学, 2022, 55(22): 4526-4538. |
[5] | 刘泓,郭玉杰,许雄,李侠,张鸿儒,齐立伟,孙雪梅,张春晖. 不同畜禽骨蛋白肽的制备、理化特性表征及其生物活性[J]. 中国农业科学, 2022, 55(13): 2629-2642. |
[6] | 张鹏飞,史良玉,刘家鑫,李洋,吴成斌,王立贤,赵福平. 畜禽全基因组长纯合片段检测的研究进展[J]. 中国农业科学, 2021, 54(24): 5316-5326. |
[7] | 徐久凯,袁亮,温延臣,张水勤,林治安,李燕婷,李海燕,赵秉强. 畜禽有机肥磷素在冬小麦上替代化肥磷当量研究[J]. 中国农业科学, 2021, 54(22): 4826-4839. |
[8] | 张林林,智慧,汤沙,张仁梁,张伟,贾冠清,刁现民. 谷子抽穗时间基因SiTOC1的表达与单倍型变异分析[J]. 中国农业科学, 2021, 54(11): 2273-2286. |
[9] | 李奇峰,李嘉位,马为红,高荣华,余礼根,丁露雨,于沁杨. 畜禽养殖疾病诊断智能传感技术研究进展[J]. 中国农业科学, 2021, 54(11): 2445-2463. |
[10] | 王小彬, 闫湘, 李秀英. 畜禽粪污厌氧发酵沼液农用之环境安全风险[J]. 中国农业科学, 2021, 54(1): 110-139. |
[11] | 丁尚,付阳,郭浩浩,宋晨阳,李博玲,赵洪伟. 海南岛1988—2018年畜禽粪尿氮磷负荷量及环境效应[J]. 中国农业科学, 2020, 53(18): 3752-3763. |
[12] | 魏启航,任艳芳,何俊瑜,李兆君. 畜禽养殖废弃物堆肥过程中微生物除臭研究进展[J]. 中国农业科学, 2020, 53(15): 3134-3145. |
[13] | 秦艳红,王永江,王爽,乔奇,田雨婷,张德胜,张振臣. 甘薯羽状斑驳病毒O株系和RC株系中国分离物全基因组 序列分析及其遗传特征[J]. 中国农业科学, 2020, 53(11): 2207-2218. |
[14] | 汪开英,吴捷刚,赵晓洋. 畜禽场空气污染物检测技术综述[J]. 中国农业科学, 2019, 52(8): 1458-1474. |
[15] | 武炳超, 童磊, 杜昭昌, 胡家菱, 张欢, 陈燚, 刘伟, 张新全, 黄琳凯. 60Co-γ射线对2种狼尾草属牧草的诱变效应[J]. 中国农业科学, 2019, 52(3): 414-427. |
|