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High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs and novel candidate genes influencing cow milk traits

机译:通过测序和关联的高密度全基因组基因分型可识别常见和低频SNP以及影响母乳性状的新候选基因

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摘要

High-throughput sequencing technologies have increased the ability to detect sequence variations for complex trait improvement. A high throughput genome wide genotyping-by-sequencing (GBS) method was used to generate 515,787 single nucleotide polymorphisms (SNPs), from which 76,355 SNPs with call rates >85% and minor allele frequency ≥1.5% were used in genome wide association study (GWAS) of 44 milk traits in 1,246 Canadian Holstein cows. GWAS was accomplished with a mixed linear model procedure implementing the additive and dominant models. A strong signal within the centromeric region of bovine chromosome 14 was associated with test day fat percentage. Several SNPs were associated with eicosapentaenoic acid, docosapentaenoic acid, arachidonic acid, CLA:9c11t and gamma linolenic acid. Most of the significant SNPs for 44 traits studied are novel and located in intergenic regions or introns of genes. Novel potential candidate genes for milk traits or mammary gland functions include ERCC6, TONSL, NPAS2, ACER3, ITGB4, GGT6, ACOX3, MECR, ADAM12, ACHE, LRRC14, FUK, NPRL3, EVL, SLCO3A1, PSMA4, FTO, ADCK5, PP1R16A and TEP1. Our study further demonstrates the utility of the GBS approach for identifying population-specific SNPs for use in improvement of complex dairy traits.
机译:高通量测序技术提高了检测序列变异以提高复杂性状的能力。采用高通量全基因组测序基因分型(GBS)方法生成515,787个单核苷酸多态性(SNP),其中76,355个SNP的检出率> 85%,次要等位基因频率≥1.5%,用于基因组范围的关联研究(GWAS)在1,246头加拿大荷斯坦奶牛中表现出44种牛奶特征。 GWAS是通过实现加性模型和优势模型的混合线性模型程序完成的。牛14号染色体着丝粒区域内的强信号与测试日的脂肪百分比有关。几种SNP与二十碳五烯酸,二十二碳五烯酸,花生四烯酸,CLA:9c11t和γ亚麻酸有关。研究的44个性状的大多数重要SNP都是新颖的,位于基因的基因间区域或内含子中。牛奶性状或乳腺功能的新型潜在候选基因包括ERCC6,TONSL,NPAS2,ACER3,ITGB4,GGT6,ACOX3,MECR,ADAM12,ACHE,LRRC14,FUK,NPRL3,EVL,SLCO3A1,PSMA4,FTO,ADCK5,PP1R16A和TEP1。我们的研究进一步证明了GBS方法可用于识别特定人群的SNP,以改善复杂的乳品性状。

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