Genome Wide Association Study: Opportunities and Challenges in Genomic Research

Abstract

Abstract: Genome wide association study(GWAS)is about screening for high-density molecular markers in certain populations in the range of the whole genome, then analyzing the correlations between the data of the molecular markers and the phenotypic traits. GWAS opened up a new chapter in genomic and genetic research, enabling linking genomics and genetics in unprecedented scale. GWAS is mainly applied in the analysis of complex traits of human diseases, leading to the identification of a number of genetic variants related to complex diseases and quantitative traits in human, hence it is to become one of the key approaches for human genomics. Application of GWAS in plant genomics just began, yet it has shown great advantages. It is becoming a research trend in plant genomics to use GWAS to discover genes related to complex quantitative traits to guide breeding programs. However, there exist some problems in GWAS, which are not as simple as expected. This review summarizes the current knowledge on GWAS with special emphasis on its applications in human and plant genomes and highlights its potential areas for future research.

Key words: Genome wide association study(GWAS), Molecular markers, Functional genomics

Zhang Yanming, Xing Guofang, Liu Meitao, Liu Xiaodong, Han Yuanhuai. Genome Wide Association Study: Opportunities and Challenges in Genomic Research[J]. Biotechnology Bulletin, 2013, 0(6): 1-6.

References

[1] 崔东红, 江开达. 精神分裂症的全基因关联分析研究[J]. 上海精神医学, 2011, 5(23):261-264.
[2] Aranzana MJ, Kim S, Zhao K, et al. Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes[J]. PloS Genetics, 2005, 1(5):e60.
[3] Risch N, Merikangas K. The future of genetic studies of complex human diseases[J]. Science, 1996, 273(5281):1516-1517.
[4] Hansen M, Kraft T, Ganestam S, et al. Linkage disequilibrium mapping of the bolting gene in sea beet using AFLP markers[J]. Genetical Research, 2001, 77(1):61-66.
[5] Klein RJ, Zeiss C, Chew EY, et al. Complement factor H polymorph-ism in age-related macular degeneration[J]. Science, 2005, 308(5720):385-389.
[6] 胡艳玲. 复杂性状与基因组多位点的关联分析方法研究[D]. 上海:上海交通大学, 2009.
[7] Van SK, McQueen MB, Herbert A, et al. Genomic screening and replication using the same data set in family-based association testi-ng[J]. Nature Genetics, 2005, 37(7):683-691.
[8] Sham PC, Cherny SS, Purcell S, et al. Power of linkage versus ass-ociation analysis of quantitative traits, by use of variance-components models, for sibship data[J]. American Journal of Human Genetics, 2000, 66(5):1616-1630.
[9] 严卫丽. 复杂疾病全基因组关联研究进展——研究设计和遗传标记[J]. 遗传, 2008, 30(4):400-406.
[10] 于海霞, 肖静, 田纪春, 等. 关联分析及其在植物中的应用[J]. 基因组学和应用生物学, 2009, 28(1):187-194.
[11] 金亮. 水稻关联定位群体的构建及若干品质性状的关联分析[D]. 杭州:浙江大学, 2009.
[12] 李海权, 刁现民. 关联分析及其在植物研究中的应用[D]. 河北农业科学, 2010, 14(11):157-160.
[13] Yang J, Ferreira T, Morris AP, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits[D]. Nature Genetics, 2012, 44(4):369-375.
[14] Todd JA. Statistical false positive or true disease pathway?[J]. Nature Genetics, 2006, 38(7):731-733.
[15] Herbert A, Gerry NP, McQueen MB, et al. A common genetic variant is associated with adult and childhood obesity[J]. Science, 2006, 312(5771):279-283.
[16] Rosskopf D, Bornhorst A, Rimmbach C, et al. Comment on “A common genetic variant is associated with adult and childhood obesity”[J]. Science, 2007, 315(5809):187.
[17] Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity[J]. Science, 2007, 316:889-894.
[18] Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for type 2 diabetes[J]. Nature, 2007, 445(7130):881-885.
[19] Steinthorsdottir V, Thorleifsson G, Reynisdottir I, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes[J]. Nature Genetics, 2007, 39(6):770-775.
[20] Saxena R, Voight BF, Lyssenko V, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels[J]. Science, 2007, 316(5829):133l-1336.
[21] Zeggini E, Weedon MN, Lindgren CM, et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes[J]. Science, 2007, 316(5829):1336-1341.
[22] Scott LJ, Mohike KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants[J]. Science, 2007, 316:1341-1345.
[23] Burton PR, Clayton DG, Cardon LR, et al. Genome-wide association study of 14, 000 cases of seven common diseases and 3, 000 shared controls[J]. Nature, 2007, 447(7145):661-678.
[24] Takeuchi F, Serizawa M, Yamamoto K, et al. Confirmation of multiple risk loci and genetic impacts by a genome-wide association study of type 2 diabetes in the Japanese population[J]. Diabetes, 2009, 58(7):1690-1699.
[25] Zeggini E, Scott LJ, Saxena R, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes[J]. Nature Genetics, 2008, 40(5):638-645.
[26] Tsai FJ, Yang CF, Chen CC, et al. A genome-wide association study identifies susceptibility variants for type 2 diabetes in Han Chinese[J]. PLoS Genetics, 2010, 6(2):e1000847.
[27] 黄琼, 尹继业, 刘昭前. 2型糖尿病全基因组关联分析的研究进展[J]. 中华内分泌代谢杂志, 2010, 26(5):432-436.
[28] Mah S, Nelson MR, Delisi LE, et al. Identification of the semaphorin receptorPLXNA2 as a candidate for susceptibility to schizophrenia[J]. Mol Psychiatry, 2006, 11(5):471-478.
[29] Shifman S, Johannesson M, Bronstein M, et al. Genome wide association identifies a common variant in the reelin gene that increases the risk of schizophrenia only in women[J]. PLoS Genetics, 2008, 4(2):e28.
[30] Kirov G, Zaharieva I, Georgieva L, et al. A genome wide association study in 574 schizophrenia trios using DNA pooling[J].Molecular Psychiatry, 2009, 14(8):796-803.
[31] Shi J, Levinson DF, Duan J, et al. Common variants on chromosome 6p22.1 are associated with schizophrenia[J].Nature, 2009, 460(7256):753-757.
[32] Hunter DJ, Altshuler D, Rader DJ. From Darwin’s finches to cana-ries in the coal mine—mining the genome for new biology[J].New England Journal of Medicine, 2008, 358(26):2760-2763.
[33] Athanasiu L, Mattingsdal M, Kahler AK, et al.Gene variants associated with schizophrenia in a Norwegian genome-wide study are replicated in a large European cohort[J]. J Psychiatr Res, 2010, 44(12):748-753.
[34] Alkelai A, Lupoli S, Greenbaum L, et al. DOCK4 and CEACAM21 as novel schizophrenia candidate genes in the Jewish population[J].Int J Neuropsychopharmacol, 2012, 15(4):541.
[35] Ma X, Deng W, Liu X, et al. A genome-wide association study for quantitative traits in schizophrenia in China[J]. Genes Brain and Behavior, 2011, 10(7):734-739.
[36] Barrett JC, Hansoul S, Nicolae DL, et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's dise-ase[J]. Nature Genetic, 2008, 40(8):955-962.
[37] Weiss LA, Arking DE, Daly MJ, et al. A genome-wide linkage and association scan reveals novel loci for autism[J]. Nature, 2009, 461(7265):802-808.
[38] Parisseaux B, Bernardo R. In silico mapping of quantitative trait loci in maize[J]. Theor Appl Genet, 2004, 109(3):508-514.
[39] Stich B, Melchinger AE, Frisch M, et al. Linkage disequilibrium in European elite maize germplasm investigated with SSRs[J]. Theoretical and Applied Genetics, 2005, 111(4):723-730.
[40] Breseghello F, Sorrells ME. Association mapping of kernel size and milling quality in wheat(Triticum aestivum L.)cultivars[J]. Genetics, 2006, 172(2):1165-1177.
[41] Jun TH, Van K, Kim MY, et al. Association analysis using SSR markers to find QTL for seed protein content in soybean[J]. Euphytica, 2008, 162(2):179-191.
[42] Kraakman AT, Niks RE, Berg PM, et al. Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars[J]. Genetics, 2004, 168(1):435-446.
[43] Aranzana MJ, Kim S, Zhao K, et al. Genome-wide association map-ping in Arabidopsis identifies previously known flowering time and pathogen resistance genes[J]. PLoS Genet, 2005, 1(5):e60.
[44] Susanna A, Huang YS, Vilhjálmsson BJ, et al. Genome-wide association study of 107 phenotypes in a common set of Arabidopsis thaliana inbred lines[J]. Nature, 2010, 465(7298):627-631.
[45] Atwell S, Huang YS, Vilhjálmsson BJ, et al. Genome-wide association studies of 14 agronomic traits in rice landraces[J]. Nature Genetics, 2010, 42(11):961-967.
[46] Zhao KY, Tung CW, Eizenga GC, et al. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa[J]. Nature Genetics, 2011, 2(467):1467.
[47] Huang XH, Zhao Y, Wei XH, et al. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm[J]. Nature Genetics, 2012, 44(1):32-39.
[48] 凃欣, 石立松, 汪樊, 等. 全基因组关联分析的进展与反思[J]. 生理科学进展, 2010, 41(2):87-93