Cargando…

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

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 e...

Descripción completa

Detalles Bibliográficos
Autores principales: Bocher, Ozvan, Ludwig, Thomas E., Oglobinsky, Marie-Sophie, Marenne, Gaëlle, Deleuze, Jean-François, Suryakant, Suryakant, Odeberg, Jacob, Morange, Pierre-Emmanuel, Trégouët, David-Alexandre, Perdry, Hervé, Génin, Emmanuelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518893/
https://www.ncbi.nlm.nih.gov/pubmed/36112662
http://dx.doi.org/10.1371/journal.pgen.1009923
_version_ 1784799285270806528
author Bocher, Ozvan
Ludwig, Thomas E.
Oglobinsky, Marie-Sophie
Marenne, Gaëlle
Deleuze, Jean-François
Suryakant, Suryakant
Odeberg, Jacob
Morange, Pierre-Emmanuel
Trégouët, David-Alexandre
Perdry, Hervé
Génin, Emmanuelle
author_facet Bocher, Ozvan
Ludwig, Thomas E.
Oglobinsky, Marie-Sophie
Marenne, Gaëlle
Deleuze, Jean-François
Suryakant, Suryakant
Odeberg, Jacob
Morange, Pierre-Emmanuel
Trégouët, David-Alexandre
Perdry, Hervé
Génin, Emmanuelle
author_sort Bocher, Ozvan
collection PubMed
description 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 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 strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.
format Online
Article
Text
id pubmed-9518893
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-95188932022-09-29 Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score Bocher, Ozvan Ludwig, Thomas E. Oglobinsky, Marie-Sophie Marenne, Gaëlle Deleuze, Jean-François Suryakant, Suryakant Odeberg, Jacob Morange, Pierre-Emmanuel Trégouët, David-Alexandre Perdry, Hervé Génin, Emmanuelle PLoS Genet Methods 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 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 strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages. Public Library of Science 2022-09-16 /pmc/articles/PMC9518893/ /pubmed/36112662 http://dx.doi.org/10.1371/journal.pgen.1009923 Text en © 2022 Bocher et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Methods
Bocher, Ozvan
Ludwig, Thomas E.
Oglobinsky, Marie-Sophie
Marenne, Gaëlle
Deleuze, Jean-François
Suryakant, Suryakant
Odeberg, Jacob
Morange, Pierre-Emmanuel
Trégouët, David-Alexandre
Perdry, Hervé
Génin, Emmanuelle
Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title_full Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title_fullStr Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title_full_unstemmed Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title_short Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score
title_sort testing for association with rare variants in the coding and non-coding genome: rava-first, a new approach based on cadd deleteriousness score
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9518893/
https://www.ncbi.nlm.nih.gov/pubmed/36112662
http://dx.doi.org/10.1371/journal.pgen.1009923
work_keys_str_mv AT bocherozvan testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT ludwigthomase testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT oglobinskymariesophie testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT marennegaelle testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT deleuzejeanfrancois testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT suryakantsuryakant testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT odebergjacob testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT morangepierreemmanuel testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT tregouetdavidalexandre testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT perdryherve testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore
AT geninemmanuelle testingforassociationwithrarevariantsinthecodingandnoncodinggenomeravafirstanewapproachbasedoncadddeleteriousnessscore