Candidate silencer elements for the human and mouse genomes.
Naresh Doni JayaveluAjay JajodiaArpit MishraR David HawkinsPublished in: Nature communications (2020)
The study of gene regulation is dominated by a focus on the control of gene activation or increase in the level of expression. Just as critical is the process of gene repression or silencing. Chromatin signatures have identified enhancers, however, genome-wide identification of silencers by computational or experimental approaches are lacking. Here, we first define uncharacterized cis-regulatory elements likely containing silencers and find that 41.5% of ~7500 tested elements show silencer activity using massively parallel reporter assay (MPRA). We trained a support vector machine classifier based on MPRA data to predict candidate silencers in over 100 human and mouse cell or tissue types. The predicted candidate silencers exhibit characteristics expected of silencers. Leveraging promoter-capture HiC data, we find that over 50% of silencers are interacting with gene promoters having very low to no expression. Our results suggest a general strategy for genome-wide identification and characterization of silencer elements.
Keyphrases
- genome wide
- genome wide identification
- transcription factor
- dna methylation
- endothelial cells
- copy number
- poor prognosis
- gene expression
- induced pluripotent stem cells
- electronic health record
- big data
- crispr cas
- single cell
- machine learning
- cell therapy
- long non coding rna
- body composition
- stem cells
- oxidative stress