Biology subjects

Adam Siepel

Publications and source records attributed to Adam Siepel.

4 recordsLinked to original sources

bioRxiv2016

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data

Across many species, a large fraction of genetic variants that influence phenotypes of interest is located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here, we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which therefore are likely to be phenotypically important. LINSIGHT combines a simple neural network for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the \"Big Data\" available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell-type, tissue specificity, and constraints at associated promoters.

Genomics↗

bioRxiv2014

Accurate Identification of Active Transcriptional Regulatory Elements from Global Run-On and Sequencing Data

Identification of the genomic regions that regulate transcription remains an important open problem. We have recently shown that global run-on and sequencing (GRO-seq) with enrichment for 5'-capped RNAs reveals patterns of divergent transcription that accurately mark active transcriptional regulatory elements (TREs), including enhancers and promoters. Here, we demonstrate that active TREs can be identified with comparable accuracy by applying sensitive machine-learning methods to standard GRO-seq and PRO-seq data, allowing TREs to be assayed together with transcription levels, elongation rates, and other transcriptional features, in a single experiment. Our method, called discriminative Regulatory Element detection from GRO-seq (dREG), summarizes GRO-seq read counts at multiple scales and uses support vector regression to predict active TREs. The predicted TREs are strongly enriched for marks associated with functional elements, including H3K27ac, transcription factor binding sites, eQTLs, and GWAS-associated SNPs. Using dREG, we survey TREs in eight cell types and provide new insights into global patterns of TRE assembly and function.

Genomics↗

bioRxiv2014

Probabilities of Fitness Consequences for Point Mutations Across the Human Genome

We describe a novel computational method for estimating the probability that a point mutation at each position in a genome will influence fitness. These fitness consequence (fit-Cons) scores serve as evolution-based measures of potential genomic function. Our approach is to cluster genomic positions into groups exhibiting distinct \"fingerprints\" based on high-throughput functional genomic data, then to estimate a probability of fitness consequences for each group from associated patterns of genetic polymorphism and divergence. We have generated fitCons scores for three human cell types based on public data from EN-CODE. Compared with conventional conservation scores, fitCons scores show considerably improved prediction power for cis-regulatory elements. In addition, fitCons scores indicate that 4.2-7.5% of nucleotides in the human genome have influenced fitness since the human-chimpanzee divergence, and, in contrast to several recent studies, they suggest that recent evolutionary turnover has had limited impact on the functional content of the genome.

Genomics↗

bioRxiv2014

Cis-regulatory elements and human evolution

Modification of gene regulation has long been considered an important force in human evolution, particularly through changes to cis-regulatory elements (CREs) that function in transcriptional regulation. For decades, however, the study of cis-regulatory evolution was severely limited by the available data. New data sets describing the locations of CREs and genetic variation within and between species have now made it possible to study CRE evolution much more directly on a genome-wide scale. Here, we review recent research on the evolution of CREs in humans based on large-scale genomic data sets. We consider inferences based on primate divergence,human polymorphism, and combinations of divergence and polymorphism. We then consider "new frontiers" in this field stemming from recent research on transcriptional regulation.

Evolutionary Biology↗