Summary
Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse, biobank-scale GWAS data, massively parallel CRISPR screens, and single-cell transcriptomic and proteomic sequencing, we discovered 124 <i>cis</i>-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion through base editing, we connected specific variants with gene expression changes. We also identified <i>trans</i>-effect networks of noncoding loci when <i>cis</i> target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively paral
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.