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Am J Hum Genet. 2017 Feb 2;100(2):205-215. doi: 10.1016/j.ajhg.2016.12.009. Epub 2017 Jan 12.

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

Author information

1
Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA. Electronic address: alanna.c.morrison@uth.tmc.edu.
2
Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
3
Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA.
4
Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX 77030, USA; Houston Methodist Debakey Heart and Vascular Center, Houston, TX 77030, USA.
5
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21287, USA.
6
Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA. Electronic address: eric.boerwinkle@uth.tmc.edu.

Abstract

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.

KEYWORDS:

genomic analysis; quantitative traits; whole-genome sequence

PMID:
28089252
PMCID:
PMC5294677
DOI:
10.1016/j.ajhg.2016.12.009
[Indexed for MEDLINE]
Free PMC Article

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