| Literature DB >> 31806698 |
Sean E McGeary1,2,3, Kathy S Lin1,2,3,4, Charlie Y Shi1,2,3, Thy M Pham1,2,3, Namita Bisaria1,2,3, Gina M Kelley1,2,3, David P Bartel5,2,3,4.
Abstract
MicroRNAs (miRNAs) act within Argonaute proteins to guide repression of messenger RNA targets. Although various approaches have provided insight into target recognition, the sparsity of miRNA-target affinity measurements has limited understanding and prediction of targeting efficacy. Here, we adapted RNA bind-n-seq to enable measurement of relative binding affinities between Argonaute-miRNA complexes and all sequences ≤12 nucleotides in length. This approach revealed noncanonical target sites specific to each miRNA, miRNA-specific differences in canonical target-site affinities, and a 100-fold impact of dinucleotides flanking each site. These data enabled construction of a biochemical model of miRNA-mediated repression, which was extended to all miRNA sequences using a convolutional neural network. This model substantially improved prediction of cellular repression, thereby providing a biochemical basis for quantitatively integrating miRNAs into gene-regulatory networks.Entities:
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Year: 2019 PMID: 31806698 PMCID: PMC7051167 DOI: 10.1126/science.aav1741
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728