VikNGS: a C++ variant integration kit for next generation sequencing association analysis

Baskurt, Zeynep; Mastromatteo, Scott; Gong, Jiafen; Wintle, Richard F.; Scherer, Stephen W.; Strug, Lisa J.

doi:10.1093/bioinformatics/btz716

“…Interestingly, the most significant SLC26A9 SNPs from the CF GWASs (1, 7) also associate with lung function measurements in several large international studies: PEFand FEV 1 /FVC ratio in participants from the UK Biobank aged 40-69 (10, 58); PEF and FEV 1 /FVC ratio in the Spirometa consortium (58); and for the FEV 1 /FVC ratio in 8-year-olds from the UK10K consortium (72). These results align with our findings that, after correction of CF-causal CFTR variants with modulators, SLC26A9 SNPs are associated with improved lung function and CFTR function.…”

Section: Discussionmentioning

confidence: 99%

Genetic evidence supports the development of SLC26A9 targeting therapies for the treatment of lung disease

Gong

¹

,

He

²

,

Wang

³

et al. 2021

Preprint

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Background: Over 400 variants in the cystic fibrosis (CF) transmembrane conductance regulator (CFTR) are CF-causing. CFTR modulators target different variants to improve lung function, but large variability in response exists and current therapies do not address all CF-causing variants highlighting an unmet need. Alternative epithelial ion channels such as SLC26A9 could compensate for CFTR dysfunction, providing a therapeutic target that benefits all individuals with CF. Method: We investigate the relationship between SLC26A9 and lung function pre- and post-treatment with CFTR modulators in Canadian and US CF cohorts, in the general population, and in those with chronic obstructive pulmonary disease (COPD). Results: SLC26A9 rs7512462 CC genotype is associated with greater lung function in individuals with minimal function variants (for which there are currently no approved therapies; p=0.002); and gating (p=0.03) and p.Phe508del/ p.Phe508del (p=0.009) genotypes upon treatment with CFTR modulators. Analogously, p.Phe508del/p.Phe508del human nasal epithelia with CC after triple combination modulator treatment show greatest CFTR function (p=8x10-4). Beyond CF, rs7512462 is associated with lung function in the UK Biobank (meta-p=2.74x10-44) and in COPD (min p=0.007). Conclusion: These findings support SLC26A9 as a therapeutic target to improve lung function for all people with CF and in individuals with other obstructive lung diseases such as COPD.

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“…The use of the same framework to define testing units in the whole genome offers several advantages, including the region-specific filtering which enables to overcome the question of selecting a hard threshold to filter rare variants in RVAT. In addition, the newly defined CADD regions can be used in existing software that require regions as input parameters [ 54 , 55 ], enabling to apply a wide variety of RVAT available in those programs to the whole genome. Especially, Bayesian methods which have been shown to be of great promise in the analysis and filtering of rare variants [ 56 , 57 ] could be applied beyond genes by using CADD regions.…”

Section: Discussionmentioning

confidence: 99%

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

Bocher

¹

,

Ludwig

²

,

Oglobinsky

³

et al. 2022

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Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with subscores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a

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“…On the other hand, the pre-definition of regions in the whole genome offers several advantages, including the region-specific filtering mentioned before. In addition, the newly defined CADD regions can be used in existing software that require regions as input parameters (50,51), enabling to apply a wide variety of RVAT available in those programs to the whole genome. Especially, Bayesian methods which have been shown to be of great promise in the analysis and filtering of rare variants (52,53) could be applied beyond genes by using CADD regions.…”

Section: Discussionmentioning

confidence: 99%

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

Bocher

¹

,

Ludwig

²

,

Marenne

³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests.We propose a new strategy to perform RVAT on WGS data: “RAVA-FIRST” (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the GnomAD populations, which are referred to as “CADD regions”. (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 that is enriched for rare variants in early-onset patients and that was that was missed by standard sliding windows procedures.RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.Author SummaryTechnological progresses have made possible whole genome sequencing at an unprecedented scale, opening up the possibility to explore the role of genetic variants of low frequency in common diseases. The challenge is now methodological and requires the development of novel methods and strategies to analyse sequencing data that are not limited to assessing the role of coding variants. With RAVA-FIRST, we propose a novel strategy to investigate the role of rare variants in the whole-genome that takes benefit from biological information. Especially, RAVA-FIRST relies on testing units that go beyond genes to gather rare variants in the association tests. In this work, we show that this new strategy presents several advantages compared to existing methods. RAVA-FIRST offers an easy and straightforward analysis of genome-wide rare variants, especially the intergenic ones which are frequently left behind, making it a promising tool to get a better understanding of the biology of complex diseases.

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VikNGS: a C++ variant integration kit for next generation sequencing association analysis

Cited by 6 publications

References 14 publications

Genetic evidence supports the development of SLC26A9 targeting therapies for the treatment of lung disease

Genetic evidence supports the development of SLC26A9 targeting therapies for the treatment of lung disease

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

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