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以酒浇愁:鉴定一个调节模块,预测影响犬被毛组成。

Hair of the Dog: Identification of a -Regulatory Module Predicted to Influence Canine Coat Composition.

机构信息

Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, 20894, United States of America.

出版信息

Genes (Basel). 2019 Apr 26;10(5):323. doi: 10.3390/genes10050323.

Abstract

Each domestic dog breed is characterized by a strict set of physical and behavioral characteristics by which breed members are judged and rewarded in conformation shows. One defining feature of particular interest is the coat, which is comprised of either a double- or single-layer of hair. The top coat contains coarse guard hairs and a softer undercoat, similar to that observed in wolves and assumed to be the ancestral state. The undercoat is absent in single-coated breeds which is assumed to be the derived state. We leveraged single nucleotide polymorphism (SNP) array and whole genome sequence (WGS) data to perform genome-wide association studies (GWAS), identifying a locus on chromosome (CFA) 28 which is strongly associated with coat number. Using WGS data, we identified a locus of 18.4 kilobases containing 62 significant variants within the intron of a long noncoding ribonucleic acid (lncRNA) upstream of ADRB1. Multiple lines of evidence highlight the locus as a potential cis-regulatory module. Specifically, two variants are found at high frequency in single-coated dogs and are rare in wolves, and both are predicted to affect transcription factor (TF) binding. This report is among the first to exploit WGS data for both GWAS and variant mapping to identify a breed-defining trait.

摘要

每一个犬种都有严格的身体和行为特征,这些特征是在犬类形态展示中评判和奖励犬种成员的依据。一个特别有趣的特征是毛发,它由双层或单层毛发组成。外层毛发包含粗糙的保护毛和更柔软的内层毛,类似于狼的毛发,被认为是原始状态。单层被毛的犬种则没有内层毛,被认为是衍生状态。我们利用单核苷酸多态性 (SNP) 芯片和全基因组序列 (WGS) 数据进行全基因组关联研究 (GWAS),在染色体 (CFA) 28 上确定了一个与毛发数量强烈相关的基因座。使用 WGS 数据,我们在 ADRB1 上游的长非编码 RNA (lncRNA) 内含子中发现了一个包含 62 个显著变异的 18.4 千碱基的基因座。多种证据表明该基因座可能是一个顺式调控模块。具体来说,两个变异在单层被毛犬中高频出现,而在狼中很少见,并且都被预测会影响转录因子 (TF) 结合。本报告是首次利用 WGS 数据进行 GWAS 和变异图谱分析,以确定一个犬种定义特征的报告之一。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/361a/6562840/3c6a5d5959b1/genes-10-00323-g001.jpg

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