Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.

Genome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Her...

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Main Authors: Robert A Power, Siva Davaniah, Anne Derache, Eduan Wilkinson, Frank Tanser, Ravindra K Gupta, Deenan Pillay, Tulio de Oliveira
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5038937?pdf=render
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author Robert A Power
Siva Davaniah
Anne Derache
Eduan Wilkinson
Frank Tanser
Ravindra K Gupta
Deenan Pillay
Tulio de Oliveira
author_facet Robert A Power
Siva Davaniah
Anne Derache
Eduan Wilkinson
Frank Tanser
Ravindra K Gupta
Deenan Pillay
Tulio de Oliveira
author_sort Robert A Power
collection DOAJ
description Genome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Here we perform the first proof of concept viral GWAS examining drug resistance (DR), a phenotype with well understood genetics.We performed a GWAS of DR in a sample of 343 HIV subtype C patients failing 1st line antiretroviral treatment in rural KwaZulu-Natal, South Africa. The majority and minority variants within each sequence were called using PILON, and GWAS was performed within PLINK. HIV WGS from patients failing on different antiretroviral treatments were compared to sequences derived from individuals naïve to the respective treatment.GWAS methodology was validated by identifying five associations on a genetic level that led to amino acid changes known to cause DR. Further, we highlighted the ability of GWAS to identify epistatic effects, identifying two replicable variants within amino acid 68 of the reverse transcriptase protein previously described as potential fitness compensatory mutations. A possible additional DR variant within amino acid 91 of the matrix region of the Gag protein was associated with tenofovir failure, highlighting GWAS's ability to identify variants outside classical candidate genes. Our results also suggest a polygenic component to DR.These results validate the applicability of GWAS to HIV WGS data even in relative small samples, and emphasise how high throughput sequencing can provide novel and clinically relevant insights. Further they suggested that for viruses like HIV, population structure was only minor concern compared to that seen in bacteria or parasite GWAS. Given the small genome length and reduced burden for multiple testing, this makes HIV an ideal candidate for GWAS.
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spelling doaj.art-ae05502fafb345179b13813932b51a342022-12-21T18:57:30ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01119e016374610.1371/journal.pone.0163746Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.Robert A PowerSiva DavaniahAnne DeracheEduan WilkinsonFrank TanserRavindra K GuptaDeenan PillayTulio de OliveiraGenome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Here we perform the first proof of concept viral GWAS examining drug resistance (DR), a phenotype with well understood genetics.We performed a GWAS of DR in a sample of 343 HIV subtype C patients failing 1st line antiretroviral treatment in rural KwaZulu-Natal, South Africa. The majority and minority variants within each sequence were called using PILON, and GWAS was performed within PLINK. HIV WGS from patients failing on different antiretroviral treatments were compared to sequences derived from individuals naïve to the respective treatment.GWAS methodology was validated by identifying five associations on a genetic level that led to amino acid changes known to cause DR. Further, we highlighted the ability of GWAS to identify epistatic effects, identifying two replicable variants within amino acid 68 of the reverse transcriptase protein previously described as potential fitness compensatory mutations. A possible additional DR variant within amino acid 91 of the matrix region of the Gag protein was associated with tenofovir failure, highlighting GWAS's ability to identify variants outside classical candidate genes. Our results also suggest a polygenic component to DR.These results validate the applicability of GWAS to HIV WGS data even in relative small samples, and emphasise how high throughput sequencing can provide novel and clinically relevant insights. Further they suggested that for viruses like HIV, population structure was only minor concern compared to that seen in bacteria or parasite GWAS. Given the small genome length and reduced burden for multiple testing, this makes HIV an ideal candidate for GWAS.http://europepmc.org/articles/PMC5038937?pdf=render
spellingShingle Robert A Power
Siva Davaniah
Anne Derache
Eduan Wilkinson
Frank Tanser
Ravindra K Gupta
Deenan Pillay
Tulio de Oliveira
Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
PLoS ONE
title Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
title_full Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
title_fullStr Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
title_full_unstemmed Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
title_short Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance.
title_sort genome wide association study of hiv whole genome sequences validated using drug resistance
url http://europepmc.org/articles/PMC5038937?pdf=render
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