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Nat Commun. 2019 Aug 8;10(1):3583. doi: 10.1038/s41467-019-11526-w.

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

Author information

1
Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA. martin.kircher@bihealth.de.
2
Berlin Institute of Health (BIH), Berlin, 10117, Germany. martin.kircher@bihealth.de.
3
Charité - Universitätsmedizin Berlin, Berlin, 10117, Germany. martin.kircher@bihealth.de.
4
Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, 94158, USA.
5
Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94158, USA.
6
Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
7
Berlin Institute of Health (BIH), Berlin, 10117, Germany.
8
Charité - Universitätsmedizin Berlin, Berlin, 10117, Germany.
9
Department of Neurosurgery, University of California San Francisco, San Francisco, CA, 94158, USA.
10
Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA. shendure@uw.edu.
11
Brotman Baty Institute for Precision Medicine, Seattle, WA, 98195, USA. shendure@uw.edu.
12
Howard Hughes Medical Institute, Seattle, WA, 98195, USA. shendure@uw.edu.
13
Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, 94158, USA. Nadav.Ahituv@ucsf.edu.
14
Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94158, USA. Nadav.Ahituv@ucsf.edu.

Abstract

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.

PMID:
31395865
PMCID:
PMC6687891
DOI:
10.1038/s41467-019-11526-w
[Indexed for MEDLINE]
Free PMC Article

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