Your browser doesn't support javascript.
loading
Transcriptomics and chromatin accessibility in multiple African population samples.
DeGorter, Marianne K; Goddard, Page C; Karakoc, Emre; Kundu, Soumya; Yan, Stephanie M; Nachun, Daniel; Abell, Nathan; Aguirre, Matthew; Carstensen, Tommy; Chen, Ziwei; Durrant, Matthew; Dwaracherla, Vikranth R; Feng, Karen; Gloudemans, Michael J; Hunter, Naiomi; Moorthy, Mohana P S; Pomilla, Cristina; Rodrigues, Kameron B; Smith, Courtney J; Smith, Kevin S; Ungar, Rachel A; Balliu, Brunilda; Fellay, Jacques; Flicek, Paul; McLaren, Paul J; Henn, Brenna; McCoy, Rajiv C; Sugden, Lauren; Kundaje, Anshul; Sandhu, Manjinder S; Gurdasani, Deepti; Montgomery, Stephen B.
Afiliação
  • DeGorter MK; Department of Pathology, Stanford University, Stanford, CA.
  • Goddard PC; Department of Genetics, Stanford University, Stanford, CA.
  • Karakoc E; Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
  • Kundu S; Department of Computer Science, Stanford University, Stanford CA.
  • Yan SM; Department of Biology, Johns Hopkins University, Baltimore.
  • Nachun D; Department of Pathology, Stanford University, Stanford, CA.
  • Abell N; Department of Genetics, Stanford University, Stanford, CA.
  • Aguirre M; Department of Biomedical Data Science, Stanford University, Stanford, CA.
  • Carstensen T; Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
  • Chen Z; Department of Computer Science, Stanford University, Stanford CA.
  • Durrant M; Department of Biology, Johns Hopkins University, Baltimore.
  • Dwaracherla VR; Department of Electrical Engineering, Stanford University, Stanford, CA.
  • Feng K; Department of Biomedical Data Science, Stanford University, Stanford, CA.
  • Gloudemans MJ; Department of Biomedical Data Science, Stanford University, Stanford, CA.
  • Hunter N; Department of Genetics, Stanford University, Stanford, CA.
  • Moorthy MPS; Department of Computer Science, Stanford University, Stanford CA.
  • Pomilla C; Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.
  • Rodrigues KB; Department of Pathology, Stanford University, Stanford, CA.
  • Smith CJ; Department of Genetics, Stanford University, Stanford, CA.
  • Smith KS; Department of Pathology, Stanford University, Stanford, CA.
  • Ungar RA; Department of Genetics, Stanford University, Stanford, CA.
  • Balliu B; Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA and Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA.
  • Fellay J; School of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland and Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
  • Flicek P; Department of Genetics, University of Cambridge, Cambridge, UK.
  • McLaren PJ; Sexually Transmitted and Blood-Borne Infections Division at JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Canada and Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada.
  • Henn B; Department of Anthropology, University of California Davis, Davis CA and Genome Center, University of California Davis, Davis CA.
  • McCoy RC; Department of Biology, Johns Hopkins University, Baltimore.
  • Sugden L; Department of Mathematics and Computer Science, Dusquesne University, Pittsburgh, PA.
  • Kundaje A; Department of Genetics, Stanford University, Stanford, CA.
  • Sandhu MS; Department of Computer Science, Stanford University, Stanford CA.
  • Gurdasani D; Department of Medicine, University of Cambridge, Cambridge, UK.
  • Montgomery SB; William Harvey Research Institute, Queen Mary University of London, London, UK; Kirby Institute, University of New South Wales, Australia; School of Medicine, University of Western Australia, Australia.
bioRxiv ; 2023 Nov 06.
Article em En | MEDLINE | ID: mdl-37986808
Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2023 Tipo de documento: Article