研究报告

京海黄鸡体重性状全基因组关联分析

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  • 1. 扬州大学动物科学与技术学院,扬州 225009;
    2. 江苏省动物遗传繁育与分子设计重点实验室,扬州 225009;
    3. 江苏京海集团,南通 226103
张涛,博士研究生,研究方向:动物遗传育种与繁殖。E-mail: zt991279320@126.com

收稿日期: 2015-02-11

  修回日期: 2015-04-13

  网络出版日期: 2015-08-20

基金资助

国家肉鸡产业技术体系项目(编号:nycytx-42-G1-05),江苏高校优势学科建设工程项目和江苏省动物遗传繁育与分子设计重点实验室项目资助

A genome-wide association study on body weight traits of Jinghai yellow chicken

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  • 1. College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China;
    2. Key Laboratory of Animal Genetics, Breeding, Reproduction and Molecular Design of Jiangsu Province, Yangzhou 225009, China;
    3. Jiangsu Jinghai Poultry Group Co., Ltd., Nantong 226103, China

Received date: 2015-02-11

  Revised date: 2015-04-13

  Online published: 2015-08-20

摘要

体重性状是肉鸡重要的经济性状。为了寻找可用于京海黄鸡体重性状遗传改良的分子标记及候选基因,本文以400只京海黄鸡核心群母鸡为基础,测定了0~14周龄体重,利用简化基因组测序技术(Specific-locus amplified fragment sequencing, SLAF-seq)对京海黄鸡体重性状进行全基因组关联研究(Genome-wide association stndy, GWAS),筛选与京海黄鸡体重性状相关的SNPs位点。结果共检测到100个与京海黄鸡体重相关的SNPs位点,其中15个位点效应达到全基因组显著水平(P<1.87E-06),85个位点效应达到全基因组潜在显著水平(P<3.73E-05)。通过筛选每个显著SNP周围1 Mb区域内的基因,共找到9个可能的候选基因,其中FAM124A(Family with sequence similarity 124A)、QDPR(Quinoid dihydropteridine reductase)WDR1(WD repeat domain 1)和SLC2A9(Solute carrier family 2 (facilitated glucose transporter), member 9) 4个基因可能是影响体重性状的重要候选基因。同时还发现,4号染色体75.6~80.7 Mb区域集中了大部分与京海黄鸡中后期体重性状显著相关的SNPs位点,该区域可能是影响京海黄鸡中后期生长体重的重要候选区域。

本文引用格式

张涛, 王文浩, 张跟喜, 王金玉, 薛倩, 顾玉萍 . 京海黄鸡体重性状全基因组关联分析[J]. 遗传, 2015 , 37(8) : 811 -820 . DOI: 10.16288/j.yczz.15-080

Abstract

Body weight traits are important economic characters of broilers. This study was carried out to screen for molecular markers and candidate genes that can be used to improve the body weight traits. A herd of 400 female Jinghai yellow chickens were measured for body weights from 0 to 14 weeks of age. Genome-wide association study (GWAS) was carried out using specific-locus amplified fragment sequencing (SLAF-seq) technology to detect SNPs associated with body weight traits of Jinghai yellow chicken. Finally, 100 SNPs that associated with body weight traits were detected. The results showed that effects of 15 SNPs reached 5% Bonferroni genome-wide significance and 85 SNPs reached potential genome-wide significance. Genes in the candidate regions with 1 Mb windows (SNP position ±0.5 Mb) surrounding each significant SNP were screened. Finally, nine candidate genes were obtained, among which four genes of FAM124A (Family with sequence similarity 124A), QDPR (Quinoid dihydropteridine reductase), WDR1 (WD repeat domain 1) and SLC2A9 (Solute carrier family 2 (facilitated glucose transporter), member 9) might be important candidate genes influencing body weight traits of Jinghai yellow chicken. Furthermore, it was also found that most SNPs associated with mid and late growth and body weights were intensively located in the region of 75.6?80.7 Mb on chromosome 4. Our study thus provides a basis for genetic understanding of the Jinghai yellow chicken body weight traits.

参考文献

[1] 樊庆灿, 王金玉, 张跟喜, 唐莹, 张涛, 顾玉萍, 施会强. 运用四种线性模型对京海黄鸡上市体重进行全基因组关联分析. 畜牧兽医学报, 2014, 45(7): 1053-1059.
[2] 葛玉洋, 李琦华, 樊月圆, 初晓辉, 徐志强, 陈小波, 葛长荣, 贾俊静, 荣华. 单核苷酸多态性在鸡生长发育中的应用. 安徽农业科学, 2013, 41(8): 3395-3396.
[3] 冯春刚, 胡晓湘, 赵要风, 李宁. 全基因组选择及其在动物育种中的应用. 中国家禽, 2008, 30(22): 5-8.
[4] Xie L, Luo CL, Zhang CG, Zhang R, Tang J, Nie QH, Ma L, Hu XX, Li N, Da Y, Zhang XQ. Genome-wide association study identified a narrow chromosome 1 region associated with chicken growth traits. PLoS One , 2012, 7(2): e30910.
[5] Gu XR, Feng CG, Ma L, Song C, Wang YQ, Da Y, Li HF, Chen KW, Ye SH, Ge CR, Hu XX, Li N. Genome-wide association study of body weight in chicken F 2 resource population. PLoS One , 2011, 6(7): e21872.
[6] Liu WB, Li DF, Liu JF, Chen SR, Qu LJ, Zheng JX, Xu GY, 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.
[7] Wolc A, Arango J, Settar P, Fulton JE, O&#x02019;Sullivan NP, Preisinger R, Habier D, Fernando R, Garrick DJ, Hill WG, Dekkers JCM. Genom-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens. Anim Genet , 2012, 43(Suppl. 1): 87-96.
[8] Noorai RE, Freese NH, Wright LM, Chapman SC, Clark LA. Genome-wide association mapping and identification of candidate genes for the rumpless and ear-tufted traits of the araucana chicken. PLoS One , 2012, 7(7): e40974.
[9] Liu RR, Sun YF, Zhao GP, Wang FJ, Wu D, Zheng MQ, Chen JL, Zhang L, Hu YD, Wen J. Genome-wide association study identifies loci and candidate genes for body composition and meat quality traits in Beijing-You chickens. PLoS One , 2013, 8(4): e61172.
[10] Li DF, Lian L, Qu LJ, Chen YM, Liu WB, Chen SR, Zheng JX, Xu GY, Yang N. A genome-wide SNP scan reveals two loci associated with the chicken resistance to Marek's disease. Anim Genet , 2013, 44(2): 217-222.
[11] Luo CL, Qu H, Ma J, Wang J, Li CY, Yang CF, Hu XX, Li N, Shu DM. Genome-wide association study of antibody response to Newcastle disease virus in chicken. BMC Genet , 2013, 14(1): 42.
[12] Sun XW, Liu DY, Zhang XF, Li WB, Liu H, Hong WG, Jiang CB, Guan N, Ma CX, Zeng HP, Xu CH, Song J, Huang L, Wang CM, Shi JJ, Wang R, Zheng XH, Lu CY, Wang XW, Zheng HK. SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS One , 2013, 8(3): e58700.
[13] 马新红, 亢娟娟, 康相涛, 韩瑞丽, 孙桂荣, 潘军, 黄煌, 刘凯, 张立恒. 鸡基因组DNA不同提取方法的比较研究. 江西农业大学学报, 2010, 32(1): 181-184.
[14] Li RQ, Yu C, Li YR, Lam TW, Yiu SM, Kristiansen K, Wang J. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics , 2009, 25(15): 1966-1967.
[15] Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet , 2007, 81(3): 559-575.
[16] Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individual. Genome Res , 2009, 19(9): 1655-1664.
[17] Bradbury PJ, Zhang ZW, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics , 2007, 23(19): 2633-2635.
[18] Wang D, Sun Y, Stang P, Berlin JA, Wilcox MA, Li QQ. Comparison of methods for correcting population stratification in a genome-wide association study of rheumatoid arthritis: principal-component analysis versus multidimensional scaling. BMC Proc , 2009, 3(Suppl. 7): S109.
[19] Zhang ZW, Ersoz E, Lai CQ, Todhunter RJ, Tiwari HK, Gore MA, Bradbury PJ, Yu JM, Arnett DK, Ordovas JM, Buckler ES. Mixed linear model approach adapted for genome-wide association studies. Nat Genet , 2010, 42(4): 355-360.
[20] Johansson AM, Pettersson ME, Siegel PB, Carlborg &#x000d6;. Genome-wide effects of long-term divergent selection. PLoS Genet , 2010, 6(11): e1001
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