Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits

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• 作者：Alanna C. Morrison¹ ; ^{alanna.c.morrison@uth.tmc.edu} ; Zhuoyi Huang² ; Bing Yu¹ ; Ginger Metcalf² ; Xiaoming Liu¹ ; Christie Ballantyne³ ; ⁴ ; Josef Coresh⁵ ; Fuli Yu² ; Donna Muzny² ; Elena Feofanova¹ ; Navin Rustagi² ; Richard Gibbs² ; Eric Boerwinkle¹ ; ² ; ^{eric.boerwinkle@uth.tmc.edu}
• 关键词：whole-genome sequence ; quantitative traits ; genomic analysis
• 刊名：The American Journal of Human Genetics
• 出版年：2017
• 出版时间：2 February 2017
• 年：2017
• 卷：100
• 期：2
• 页码：205-215
• 全文大小：1056 K
• 卷排序：100

文摘

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.