scholarly journals Very low depth whole genome sequencing in complex trait association studies

2017 ◽  
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.

scholarly journals Very low-depth whole-genome sequencing in complex trait association studies

2018 ◽  
Vol 35 (15) ◽  
pp. 2555-2561 ◽  
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 ◽  
Supplementary Information ◽  
Whole Genome ◽  
Trait Association ◽  
High Depth

Abstract Motivation Very 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 characterization of the genotype quality and association power for very low-depth sequencing designs is still lacking. Results We perform cohort-wide whole-genome sequencing (WGS) at low depth in 1239 individuals (990 at 1× depth and 249 at 4× 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 (75× depth) and high-depth (22×) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1× 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, 1× 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. Availability and implementation The HELIC genotype and WGS datasets have been deposited to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAD00010000518; EGAD00010000522; EGAD00010000610; EGAD00001001636, EGAD00001001637. The peakplotter software is available at https://github.com/wtsi-team144/peakplotter, the transformPhenotype app can be downloaded at https://github.com/wtsi-team144/transformPhenotype. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Integrating DNA sequencing and transcriptomic data for association analyses of low-frequency variants and lipid traits

2020 ◽  
Vol 29 (3) ◽  
pp. 515-526 ◽  
Author(s):  
Tianzhong Yang ◽  
Chong Wu ◽  
Peng Wei ◽  
Wei Pan
Keyword(s):  
Gene Expression ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Low Frequency ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Common Variants ◽  
Transcriptomic Data ◽  
Genome Wide

Abstract Transcriptome-wide association studies (TWAS) integrate genome-wide association studies (GWAS) and transcriptomic data to showcase their improved statistical power of identifying gene–trait associations while, importantly, offering further biological insights. TWAS have thus far focused on common variants as available from GWAS. Compared with common variants, the findings for or even applications to low-frequency variants are limited and their underlying role in regulating gene expression is less clear. To fill this gap, we extend TWAS to integrating whole genome sequencing data with transcriptomic data for low-frequency variants. Using the data from the Framingham Heart Study, we demonstrate that low-frequency variants play an important and universal role in predicting gene expression, which is not completely due to linkage disequilibrium with the nearby common variants. By including low-frequency variants, in addition to common variants, we increase the predictivity of gene expression for 79% of the examined genes. Incorporating this piece of functional genomic information, we perform association testing for five lipid traits in two UK10K whole genome sequencing cohorts, hypothesizing that cis-expression quantitative trait loci, including low-frequency variants, are more likely to be trait-associated. We discover that two genes, LDLR and TTC22, are genome-wide significantly associated with low-density lipoprotein cholesterol based on 3203 subjects and that the association signals are largely independent of common variants. We further demonstrate that a joint analysis of both common and low-frequency variants identifies association signals that would be missed by testing on either common variants or low-frequency variants alone.

scholarly journals Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Gabriel Costa Monteiro Moreira ◽  
Clarissa Boschiero ◽  
Aline Silva Mello Cesar ◽  
James M. Reecy ◽  
Thaís Fernanda Godoy ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Fat Deposition ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide

scholarly journals Using molecular testing and whole-genome sequencing for tuberculosis diagnosis in a low-burden setting: a cost-effectiveness analysis using transmission-dynamic modelling

Thorax ◽  
2021 ◽  
Vol 76 (3) ◽  
pp. 281-291 ◽  
Author(s):  
Tendai Mugwagwa ◽  
Ibrahim Abubakar ◽  
Peter J White
Keyword(s):  
Cost Effectiveness ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Drug Sensitivity ◽  
Cost Effective ◽  
Molecular Testing ◽  
Whole Genome ◽  
Transmission Dynamic ◽  
Sensitivity Testing ◽  
Combined Use

BackgroundDespite progress in TB control in low-burden countries like England and Wales, there are still diagnostic delays. Molecular testing and/or whole-genome sequencing (WGS) provide more rapid diagnosis but their cost-effectiveness is relatively unexplored in low-burden settings.MethodsAn integrated transmission-dynamic health economic model is used to assess the cost-effectiveness of using WGS to replace culture-based drug-sensitivity testing, versus using molecular testing versus combined use of WGS and molecular testing, for routine TB diagnosis. The model accounts for the effects of faster appropriate treatment in reducing transmission, benefiting health and reducing future treatment costs. Cost-effectiveness is assessed using incremental net benefit (INB) over a 10-year horizon with a quality-adjusted life-year valued at £20 000, and discounting at 3.5% per year.ResultsWGS shortens the time to drug sensitivity testing and treatment modification where necessary, reducing treatment and hospitalisation costs, with an INB of £7.1 million. Molecular testing shortens the time to TB diagnosis and treatment. Initially, this causes an increase in annual costs of treatment, but averting transmissions and future active TB disease subsequently, resulting in cost savings and health benefits to achieve an INB of £8.6 million (GeneXpert MTB/RIF) or £11.1 million (Xpert-Ultra). Combined use of Xpert-Ultra and WGS is the optimal strategy we consider, with an INB of £16.5 million.ConclusionRoutine use of WGS or molecular testing is cost-effective in a low-burden setting, and combined use is the most cost-effective option. Adoption of these technologies can help low-burden countries meet the WHO End TB Strategy milestones, particularly the UK, which still has relatively high TB rates.

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