Natural selection on human microRNA binding sites inferred from SNP data Export

@article{citeulike:920864, abstract = {A fundamental problem in biology is understanding how natural selection has shaped the evolution of gene regulation. Here we use SNP genotype data and techniques from population genetics to study an entire layer of short, cis-regulatory sites in the human genome. MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally repress mRNA through cis-regulatory sites in 3' UTRs. We show that negative selection in humans is stronger on computationally predicted conserved miRNA binding sites than on other conserved sequence motifs in 3' UTRs, thus providing independent support for the target prediction model and explicitly demonstrating the contribution of miRNAs to darwinian fitness. Our techniques extend to nonconserved miRNA binding sites, and we estimate that 30\%–50\% of these are functional when the mRNA and miRNA are endogenously coexpressed. As we show that polymorphisms in predicted miRNA binding sites are likely to be deleterious, they are candidates for causal variants of human disease. We believe that our approach can be extended to studying other classes of cis-regulatory sites.}, address = {Center for Comparative Functional Genomics, Department of Biology, New York University, New York, New York 10003, USA.}, author = {Chen, Kevin and Rajewsky, Nikolaus}, citeulike-article-id = {920864}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/ng1910}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/ng1910}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/17072316}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=17072316}, day = {29}, doi = {10.1038/ng1910}, issn = {1061-4036}, journal = {Nature Genetics}, keywords = {human, microarray, microrna, prediction, snp, target}, month = {October}, number = {12}, pages = {1452--1456}, posted-at = {2006-12-01 13:19:21}, priority = {0}, publisher = {Nature Publishing Group}, title = {Natural selection on human microRNA binding sites inferred from SNP data}, url = {http://dx.doi.org/10.1038/ng1910}, volume = {38}, year = {2006} }

TY - JOUR ID - citeulike:920864 L3 - citeulike-article-id:920864 N2 - A fundamental problem in biology is understanding how natural selection has shaped the evolution of gene regulation. Here we use SNP genotype data and techniques from population genetics to study an entire layer of short, cis-regulatory sites in the human genome. MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally repress mRNA through cis-regulatory sites in 3' UTRs. We show that negative selection in humans is stronger on computationally predicted conserved miRNA binding sites than on other conserved sequence motifs in 3' UTRs, thus providing independent support for the target prediction model and explicitly demonstrating the contribution of miRNAs to darwinian fitness. Our techniques extend to nonconserved miRNA binding sites, and we estimate that 30%–50% of these are functional when the mRNA and miRNA are endogenously coexpressed. As we show that polymorphisms in predicted miRNA binding sites are likely to be deleterious, they are candidates for causal variants of human disease. We believe that our approach can be extended to studying other classes of cis-regulatory sites. IS - 12 JF - Nature Genetics SN - 1061-4036 AD - Center for Comparative Functional Genomics, Department of Biology, New York University, New York, New York 10003, USA. EP - 1456 TI - Natural selection on human microRNA binding sites inferred from SNP data PB - Nature Publishing Group VL - 38 SP - 1452 KW - human KW - microarray KW - microrna KW - prediction KW - snp KW - target AU - Chen, Kevin AU - Rajewsky, Nikolaus PY - 2006/10/29/ UR - http://dx.doi.org/10.1038/ng1910 ER -