Landscape of allele-specific transcription factor binding in the human genome.

Autor: Abramov S; Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia.; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.; Moscow Institute of Physics and Technology, Dolgoprudny, Russia., Boytsov A; Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia.; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.; Moscow Institute of Physics and Technology, Dolgoprudny, Russia., Bykova D; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia., Penzar DD; Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia.; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.; Moscow Institute of Physics and Technology, Dolgoprudny, Russia.; Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia., Yevshin I; Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia.; Sirius University of Science and Technology, Sochi, Russia.; BIOSOFT.RU LLC, Novosibirsk, Russia., Kolmykov SK; Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia.; Sirius University of Science and Technology, Sochi, Russia.; BIOSOFT.RU LLC, Novosibirsk, Russia., Fridman MV; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia., Favorov AV; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.; Johns Hopkins University School of Medicine, Baltimore, MD, USA., Vorontsov IE; Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia.; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia., Baulin E; Moscow Institute of Physics and Technology, Dolgoprudny, Russia.; Institute of Mathematical Problems of Biology RAS-The Branch of Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Pushchino, Russia., Kolpakov F; Federal Research Center for Information and Computational Technologies, Novosibirsk, Russia.; Sirius University of Science and Technology, Sochi, Russia.; BIOSOFT.RU LLC, Novosibirsk, Russia., Makeev VJ; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia. vsevolod.makeev@vigg.ru.; Moscow Institute of Physics and Technology, Dolgoprudny, Russia. vsevolod.makeev@vigg.ru.; State Research Institute of Genetics and Selection of Industrial Microorganisms of the National Research Center Kurchatov Institute, Moscow, Russia. vsevolod.makeev@vigg.ru.; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia. vsevolod.makeev@vigg.ru., Kulakovskiy IV; Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia. ivan.kulakovskiy@gmail.com.; Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia. ivan.kulakovskiy@gmail.com.; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia. ivan.kulakovskiy@gmail.com.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2021 May 12; Vol. 12 (1), pp. 2751. Date of Electronic Publication: 2021 May 12.
DOI: 10.1038/s41467-021-23007-0
Abstrakt: Sequence variants in gene regulatory regions alter gene expression and contribute to phenotypes of individual cells and the whole organism, including disease susceptibility and progression. Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Differential transcription factor binding in heterozygous genomic loci provides a natural source of information on such regulatory variants. We present a novel approach to call the allele-specific transcription factor binding events at single-nucleotide variants in ChIP-Seq data, taking into account the joint contribution of aneuploidy and local copy number variation, that is estimated directly from variant calls. We have conducted a meta-analysis of more than 7 thousand ChIP-Seq experiments and assembled the database of allele-specific binding events listing more than half a million entries at nearly 270 thousand single-nucleotide polymorphisms for several hundred human transcription factors and cell types. These polymorphisms are enriched for associations with phenotypes of medical relevance and often overlap eQTLs, making candidates for causality by linking variants with molecular mechanisms. Specifically, there is a special class of switching sites, where different transcription factors preferably bind alternative alleles, thus revealing allele-specific rewiring of molecular circuitry.
Databáze: MEDLINE
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