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Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution.

Martin KircherChenling XiongBeth K MartinMax SchubachFumitaka InoueRobert J A BellJoseph F CostelloJay ShendureNadav Ahituv
Published in: Nature communications (2019)
The majority of common variants associated with common diseases, as well as an unknown proportion of causal mutations for rare diseases, fall in noncoding regions of the genome. Although catalogs of noncoding regulatory elements are steadily improving, we have a limited understanding of the functional effects of mutations within them. Here, we perform saturation mutagenesis in conjunction with massively parallel reporter assays on 20 disease-associated gene promoters and enhancers, generating functional measurements for over 30,000 single nucleotide substitutions and deletions. We find that the density of putative transcription factor binding sites varies widely between regulatory elements, as does the extent to which evolutionary conservation or integrative scores predict functional effects. These data provide a powerful resource for interpreting the pathogenicity of clinically observed mutations in these disease-associated regulatory elements, and comprise a rich dataset for the further development of algorithms that aim to predict the regulatory effects of noncoding mutations.
Keyphrases
  • transcription factor
  • crispr cas
  • genome wide
  • machine learning
  • genome wide identification
  • high throughput
  • gene expression
  • big data
  • electronic health record
  • dna methylation
  • artificial intelligence
  • cystic fibrosis