Population- and individual-specific regulatory variation in Sardinia

Francesco Cucca, Stephen Montgomery and colleagues identify regulatory variants that influence gene expression and splicing using whole-genome and transcriptome sequence data from 624 Sardinians. They find a high frequency of splicing and expression quantitative trait loci near genes involved in mal...

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Vydané v:Nature genetics Ročník 49; číslo 5; s. 700 - 707
Hlavní autori: Pala, Mauro, Zappala, Zachary, Marongiu, Mara, Li, Xin, Davis, Joe R, Cusano, Roberto, Crobu, Francesca, Kukurba, Kimberly R, Gloudemans, Michael J, Reinier, Frederic, Berutti, Riccardo, Piras, Maria G, Mulas, Antonella, Zoledziewska, Magdalena, Marongiu, Michele, Sorokin, Elena P, Hess, Gaelen T, Smith, Kevin S, Busonero, Fabio, Maschio, Andrea, Steri, Maristella, Sidore, Carlo, Sanna, Serena, Fiorillo, Edoardo, Bassik, Michael C, Sawcer, Stephen J, Battle, Alexis, Novembre, John, Jones, Chris, Angius, Andrea, Abecasis, Gonçalo R, Schlessinger, David, Cucca, Francesco, Montgomery, Stephen B
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Nature Publishing Group US 01.05.2017
Nature Publishing Group
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Agriculture
Alternative Splicing
Animal Genetics and Genomics
Bioinformatics
Biomedicine
Blood
Cancer Research
Chromosome Mapping
Epidemiology
Family Health
Female
Gene expression
Gene Expression Profiling - methods
Gene Function
Gene mapping
Genes
Genetic Predisposition to Disease - genetics
Genetic Variation
Genetics
Genetics, Population
Genome-Wide Association Study - methods
Genomes
Genotype
Human Genetics
Humans
Italy
Male
Multiple sclerosis
Outliers (statistics)
Polymorphism, Single Nucleotide
Population
Population genetics
Proteins
Quantitative trait loci
Quantitative Trait Loci - genetics
Splicing
Studies
Transcription Initiation Site
United States > US
California
ISSN:1061-4036, 1546-1718, 1546-1718
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Abstract Francesco Cucca, Stephen Montgomery and colleagues identify regulatory variants that influence gene expression and splicing using whole-genome and transcriptome sequence data from 624 Sardinians. They find a high frequency of splicing and expression quantitative trait loci near genes involved in malarial resistance and multiple sclerosis. Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
AbstractList Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Genetic studies of complex traits have mainly identified associations with non-coding variants. To further determine the contribution of regulatory variation, we combined whole genome and transcriptome data for 624 individuals from Sardinia in order to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 novel QTLs. We identified high-frequency QTLs and evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z-score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Francesco Cucca, Stephen Montgomery and colleagues identify regulatory variants that influence gene expression and splicing using whole-genome and transcriptome sequence data from 624 Sardinians. They find a high frequency of splicing and expression quantitative trait loci near genes involved in malarial resistance and multiple sclerosis. Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation, we combined whole-genome and transcriptome data for 624 individuals from Sardinia to identify common and rare variants that influence gene expression and splicing. We identified 21,183 expression quantitative trait loci (eQTLs) and 6,768 splicing quantitative trait loci (sQTLs), including 619 new QTLs. We identified high-frequency QTLs and found evidence of selection near genes involved in malarial resistance and increased multiple sclerosis risk, reflecting the epidemiological history of Sardinia. Using family relationships, we identified 809 segregating expression outliers (median z score of 2.97), averaging 13.3 genes per individual. Outlier genes were enriched for proximal rare variants, providing a new approach to study large-effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.
Author Bassik, Michael C
Montgomery, Stephen B
Battle, Alexis
Cucca, Francesco
Davis, Joe R
Berutti, Riccardo
Marongiu, Michele
Piras, Maria G
Jones, Chris
Schlessinger, David
Li, Xin
Pala, Mauro
Zappala, Zachary
Sanna, Serena
Busonero, Fabio
Reinier, Frederic
Maschio, Andrea
Hess, Gaelen T
Cusano, Roberto
Marongiu, Mara
Angius, Andrea
Sidore, Carlo
Sawcer, Stephen J
Steri, Maristella
Gloudemans, Michael J
Sorokin, Elena P
Smith, Kevin S
Zoledziewska, Magdalena
Fiorillo, Edoardo
Novembre, John
Mulas, Antonella
Crobu, Francesca
Kukurba, Kimberly R
Abecasis, Gonçalo R
AuthorAffiliation 2 Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
1 Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
5 CRS4, Advanced Genomic Computing Technology, Pula, Italy
10 Laboratory of Genetics, NIA, Baltimore, Maryland
9 Center for Statistical Genetics, University of Michigan, Ann Arbor, MI
3 Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
11 Dipartimento di Scienze Biomediche, Università di Sassari, Sassari, Italy
4 Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA, USA
8 Department of Human Genetics, University of Chicago
6 Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
7 Center for Computational Biology, John Hopkins University
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/28394350$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright Springer Nature America, Inc. 2017
Copyright Nature Publishing Group May 2017
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Equal contributions statement
co-first authors
These authors contributed equally: Mauro Pala, Zachary Zappala
co-senior authors
ORCID 0000-0002-3768-1749
0000-0001-5869-3872
0000-0002-5287-627X
0000-0001-7685-0974
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SSID ssj0014408
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Snippet Francesco Cucca, Stephen Montgomery and colleagues identify regulatory variants that influence gene expression and splicing using whole-genome and...
Genetic studies of complex traits have mainly identified associations with noncoding variants. To further determine the contribution of regulatory variation,...
Genetic studies of complex traits have mainly identified associations with non-coding variants. To further determine the contribution of regulatory variation,...
SourceID pubmedcentral
proquest
pubmed
crossref
springer
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 700
SubjectTerms 38
38/91
45
45/23
45/43
631/208/191/2018
631/208/205/2138
631/208/212/2019
631/208/457
Agriculture
Alternative Splicing
Animal Genetics and Genomics
Bioinformatics
Biomedicine
Blood
Cancer Research
Chromosome Mapping
Epidemiology
Family Health
Female
Gene expression
Gene Expression Profiling - methods
Gene Function
Gene mapping
Genes
Genetic Predisposition to Disease - genetics
Genetic Variation
Genetics
Genetics, Population
Genome-Wide Association Study - methods
Genomes
Genotype
Human Genetics
Humans
Italy
Male
Multiple sclerosis
Outliers (statistics)
Polymorphism, Single Nucleotide
Population
Population genetics
Proteins
Quantitative trait loci
Quantitative Trait Loci - genetics
Splicing
Studies
Transcription Initiation Site
Title Population- and individual-specific regulatory variation in Sardinia
URI https://link.springer.com/article/10.1038/ng.3840
https://www.ncbi.nlm.nih.gov/pubmed/28394350
https://www.proquest.com/docview/1894951173
https://www.proquest.com/docview/1886342558
https://pubmed.ncbi.nlm.nih.gov/PMC5411016
Volume 49
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