Four genetic loci affecting swine lung lesions identified by whole-genome sequencing-based association studies

Genome-wide association studies (GWAS) have identified thousands of single nucleotide variants and small indels that contribute to the genetic architecture of hematologic traits. While structural variants (SVs) are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of SVs to quantitative blood cell trait variation is unknown. Here we utilized SVs detected from whole genome sequencing (WGS) in ancestrally diverse participants of the NHLBI TOPMed program (N=50,675). Using single variant tests, we assessed the association of common and rare SVs with red cell-, white cell-, and platelet-related quantitative traits. The results show 33 independent SVs (23 common and 10 rare) reaching genome-wide significance. The majority of significant association signals (N=27) replicated in independent datasets from deCODE genetics and the UK BioBank. Moreover, most trait-associated SVs (N=24) are within 1Mb of previously-reported GWAS loci. SV analyses additionally discovered an association between a complex structural variant on 17p11.2 and white blood cell-related phenotypes. Based on functional annotation, the majority of significant SVs are located in non-coding regions (N=26) and predicted to impact regulatory elements and/or local chromatin domain boundaries in blood cells. We predict that several trait-associated SVs represent the causal variant. This is supported by genome-editing experiments which provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.

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Very low depth whole genome sequencing in complex trait association studies

10.1101/169789 ◽

2017 ◽

Cited By ~ 7

Author(s):

Arthur Gilly ◽

Lorraine Southam ◽

Daniel Suveges ◽

Karoline Kuchenbaecker ◽

Rachel Moore ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Association Studies ◽

Low Frequency ◽

Cost Effective ◽

Complex Trait ◽

Whole Genome ◽

Supplementary Data ◽

Trait Association ◽

High Depth

AbstractMotivationVery low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking.ResultsWe perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.Supplementary DataSupplementary Data are appended to this manuscript.

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Whole genome sequencing association studies of lipids levels

Atherosclerosis ◽

10.1016/j.atherosclerosis.2018.06.278 ◽

2018 ◽

Vol 275 ◽

pp. e102

Author(s):

N. Rossi ◽

M. Falchi ◽

M. Bourbon ◽

A. Visconti

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Association Studies ◽

Whole Genome

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A Minimax Optimal Ridge-Type Set Test for Global Hypothesis With Applications in Whole Genome Sequencing Association Studies

Journal of the American Statistical Association ◽

10.1080/01621459.2020.1831926 ◽

2020 ◽

pp. 1-12

Author(s):

Yaowu Liu ◽

Zilin Li ◽

Xihong Lin

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Association Studies ◽

Whole Genome

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Resetting the bar: Statistical significance in whole-genome sequencing-based association studies of global populations

Genetic Epidemiology ◽

10.1002/gepi.22032 ◽

2016 ◽

Vol 41 (2) ◽

pp. 145-151 ◽

Cited By ~ 29

Author(s):

Sara L. Pulit ◽

Sera A. J. de With ◽

Paul I. W. de Bakker

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Association Studies ◽

Statistical Significance ◽

Whole Genome

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Genome-Based Characterization of Emergent Invasive Neisseria meningitidis Serogroup Y Isolates in Sweden from 1995 to 2012

Journal of Clinical Microbiology ◽

10.1128/jcm.03524-14 ◽

2015 ◽

Vol 53 (7) ◽

pp. 2154-2162 ◽

Cited By ~ 17

Author(s):

Bianca Törös ◽

Sara T. Hedberg ◽

Magnus Unemo ◽

Susanne Jacobsson ◽

Dorothea M. C. Hill ◽

...

Keyword(s):

Neisseria Meningitidis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Meningococcal Disease ◽

Association Studies ◽

Disease Incidence ◽

The United States ◽

Geographic Region ◽

Genome Wide Association Studies ◽

Whole Genome

Invasive meningococcal disease (IMD) caused byNeisseria meningitidisserogroup Y has increased in Europe, especially in Scandinavia. In Sweden, serogroup Y is now the dominating serogroup, and in 2012, the serogroup Y disease incidence was 0.46/100,000 population. We previously showed that a strain type belonging to sequence type 23 was responsible for the increased prevalence of this serogroup in Sweden. The objective of this study was to investigate the serogroup Y emergence by whole-genome sequencing and compare the meningococcal population structure of Swedish invasive serogroup Y strains to those of other countries with different IMD incidence. Whole-genome sequencing was performed on invasive serogroup Y isolates from 1995 to 2012 in Sweden (n= 186). These isolates were compared to a collection of serogroup Y isolates from England, Wales, and Northern Ireland from 2010 to 2012 (n= 143), which had relatively low serogroup Y incidence, and two isolates obtained in 1999 in the United States, where serogroup Y remains one of the major causes of IMD. The meningococcal population structures were similar in the investigated regions; however, different strain types were prevalent in each geographic region. A number of genes known or hypothesized to have an impact on meningococcal virulence were shown to be associated with different strain types and subtypes. The reasons for the IMD increase are multifactorial and are influenced by increased virulence, host adaptive immunity, and transmission. Future genome-wide association studies are needed to reveal additional genes associated with serogroup Y meningococcal disease, and this work would benefit from a complete serogroup Y meningococcal reference genome.

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