<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE169200" accession="SRP311321">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP311321</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA715632</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE169200</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Neanderthal Adaptively Introgressed Genetic Variants Regulate Human Immune Genes In Vitro.</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>Some Neanderthal introgressed variation underwent selective sweeps, but little is known about their functional significance. We used a Massively Parallel Reporter Assay (MPRA) to test 5,353 high-frequency introgressed variants for evidence of being in active cis-regulatory elements (CREs) and modulating gene expression in immune cell lines. We identified 2,546 variants in CREs and 292 expression-modulating variants (emVars). These emVars are predicted to regulate genes that are enriched for function in innate immune pathways including interferon signaling, toll like receptor pathways, and anti-viral response; one such emVar is significantly associated with protection against severe COVID-19 response. Using CRISPR-Cas9, we deleted two CREs containing expression-modulation variants linked to immune function, rs11624425 and rs80317430, identifying their primary genic targets as ELMSAN1, and PAN2 and STAT2 respectively, three genes differentially expressed during influenza infection. Overall, we present the first database of directly identified expression-modulating Neanderthal-introgressed alleles contributing to potential immune response in modern humans. Overall design: MPRA testing the regulatory potential of 5,353 putatively adaptively introgressed variants. Four replicates were performed in K562 cells and 2 replicates in Jurkat cells.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE169200</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>34662402</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
    <STUDY_ATTRIBUTES>
      <STUDY_ATTRIBUTE>
        <TAG>parent_bioproject</TAG>
        <VALUE>PRJEB40771</VALUE>
      </STUDY_ATTRIBUTE>
    </STUDY_ATTRIBUTES>
  </STUDY>
</STUDY_SET>
