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Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals
Evelyn Jagoda; Davide Marnetto; Francesco Montinaro; Daniel Richard; Luca Pagani; Terence D Capellini.
Affiliation
  • Evelyn Jagoda; Harvard University
  • Davide Marnetto; University of Tartu
  • Francesco Montinaro; University of Bari
  • Daniel Richard; Harvard University
  • Luca Pagani; University of Padova
  • Terence D Capellini; Harvard University
Preprint in English | bioRxiv | ID: ppbiorxiv-448149
ABSTRACT
Individuals infected with the SARS-CoV-2 virus present with a wide variety of phenotypes ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe COVID-19 phenotype. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the severe COVID-19 phenotype. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform an locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify 4 introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. These variants likely drive the locus impact on severity by putatively modulating the regulation of two critical chemokine receptor genes CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.
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Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
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