Development of a high density 600K SNP genotyping array for chicken.
Development of a high density 600K SNP genotyping array for chicken.
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DOI：
10.1186/1471-2164-14-59
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发表时间：
2013-01-28
期刊：
影响因子：
4.4
通讯作者：
Burt DW
中科院分区：
文献类型：
--
作者：
Kranis A;Gheyas AA;Boschiero C;Turner F;Yu L;Smith S;Talbot R;Pirani A;Brew F;Kaiser P;Hocking PM;Fife M;Salmon N;Fulton J;Strom TM;Haberer G;Weigend S;Preisinger R;Gholami M;Qanbari S;Simianer H;Watson KA;Woolliams JA;Burt DW
高密度SNP基因分型是动植物遗传分析的重要工具。虽然鸡是最重要的农场动物之一，但目前还没有HD阵列可用于该物种的高分辨率遗传分析。我们在此报告了600 K Affymetrix®Axiom®HD基因分型阵列的开发，该阵列利用多种鸡种群的snp分离设计。为了生成一个大的分离snp目录，我们对来自不同来源（实验肉鸡、商品肉鸡和蛋鸡）的24个鸡品系的243只鸡进行了重新测序，每个品系收集10-15个样本。通过将序列reads定位到新的参考基因组（Gallus_gallus_4.0），检测到约1.39亿(M)个推测snp，其中约78 M可能在不同的品系中分离。使用诸如高snp质量评分、可接受设计评分预测最终阵列的高转换性能以及整个基因组分布均匀性等标准，我们选择了约1.8 M个snp，通过在一组独立样本（n = 282）上进行基因分型验证。约64%的snp具有较高的召唤率（约98%）、良好的聚类分离性和稳定的孟德尔遗传。进一步分析了多态性snp的群体特征和基因组效应。极度违反Hardy-Weinberg平衡（P < 0.00001）的SNPs被排除在面板之外。在这些分析的基础上设计的最终阵列由580,954个snp组成，包括21,534个编码变体。根据遗传图谱距离选择snp，使肉鸡和蛋系的snp分布基本均匀。由于肉仔鸡的LD程度低于蛋鸡，因此如以往研究报道，阵列中肉仔鸡与蛋鸡snp的比例保持为3:2。结果表明，最终的小组对包括肉鸡和蛋鸡在内的广泛样本进行了基因分型，每条线的信息snp超过100 K至450 K。主成分分析用于证明该阵列检测预期群体结构的能力，这是许多全基因组分析的重要预调查步骤。该Affymetrix®Axiom®阵列是第一个用于鸡的SNP基因分型阵列，已作为一种商业产品向公众提供。该阵列有望在基因组选择、全基因组关联研究、选择特征分析、qtl精细定位和拷贝数变异检测等研究和商业应用中得到广泛应用。
High density (HD) SNP genotyping arrays are an important tool for genetic analyses of animals and plants. Although the chicken is one of the most important farm animals, no HD array is yet available for high resolution genetic analysis of this species. We report here the development of a 600 K Affymetrix® Axiom® HD genotyping array designed using SNPs segregating in a wide variety of chicken populations. In order to generate a large catalogue of segregating SNPs, we re-sequenced 243 chickens from 24 chicken lines derived from diverse sources (experimental, commercial broiler and layer lines) by pooling 10–15 samples within each line. About 139 million (M) putative SNPs were detected by mapping sequence reads to the new reference genome (Gallus_gallus_4.0) of which ~78 M appeared to be segregating in different lines. Using criteria such as high SNP-quality score, acceptable design scores predicting high conversion performance in the final array and uniformity of distribution across the genome, we selected ~1.8 M SNPs for validation through genotyping on an independent set of samples (n = 282). About 64% of the SNPs were polymorphic with high call rates (>98%), good cluster separation and stable Mendelian inheritance. Polymorphic SNPs were further analysed for their population characteristics and genomic effects. SNPs with extreme breach of Hardy-Weinberg equilibrium (P < 0.00001) were excluded from the panel. The final array, designed on the basis of these analyses, consists of 580,954 SNPs and includes 21,534 coding variants. SNPs were selected to achieve an essentially uniform distribution based on genetic map distance for both broiler and layer lines. Due to a lower extent of LD in broilers compared to layers, as reported in previous studies, the ratio of broiler and layer SNPs in the array was kept as 3:2. The final panel was shown to genotype a wide range of samples including broilers and layers with over 100 K to 450 K informative SNPs per line. A principal component analysis was used to demonstrate the ability of the array to detect the expected population structure which is an important pre-investigation step for many genome-wide analyses. This Affymetrix® Axiom® array is the first SNP genotyping array for chicken that has been made commercially available to the public as a product. This array is expected to find widespread usage both in research and commercial application such as in genomic selection, genome-wide association studies, selection signature analyses, fine mapping of QTLs and detection of copy number variants.
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影响因子：
4.4
作者：
Groenen MA;Megens HJ;Zare Y;Warren WC;Hillier LW;Crooijmans RP;Vereijken A;Okimoto R;Muir WM;Cheng HH
通讯作者：
Cheng HH
影响因子：
2.9
作者：
Megens HJ;Crooijmans RP;Bastiaansen JW;Kerstens HH;Coster A;Jalving R;Vereijken A;Silva P;Muir WM;Cheng HH;Hanotte O;Groenen MA
通讯作者：
Groenen MA
影响因子：
7
作者：
Li, Ruiqiang;Zhu, Hongmei;Wang, Jun
通讯作者：
Wang, Jun
影响因子：
1.7
作者：
Aerts, J.;Megens, H. J.;Groenen, M.
通讯作者：
Groenen, M.
影响因子：
4.1
作者：
Eding, H;Crooijmans, RPMA;Meuwissen, THE
通讯作者：
Meuwissen, THE