Predicting site-specific human selective pressure using evolutionary signatures
ABSTRACT The identification of non-coding functional regions of the human genome remains one of the main challenges of genomics. By observing how a given region evolved over time, one can detect signs of negative or positive selection hinting that the region may be functional. With the quickly increasing number of vertebrate genomes to compare with our own, this type of approach is set to become extremely powerful, provided the right analytical tools are available.
A large number of approaches have been proposed to measure signs of past selective pressure, usually in the form of reduced mutation rate. Here, we propose a radically different approach to the detection of non-coding functional region: instead of measuring past evolutionary rates, we build a machine learning classifier to predict current substitution rates in human based on the inferred evolutionary events that affected the region during vertebrate evolution. We show that different types of evolutionary events, occurring along different branches of the phylogenetic tree, bring very different amounts of information. We propose a number of simple machine learning classifiers and show that a Support-Vector Machine (SVM) predictor clearly outperforms existing tools at predicting human non-coding functional sites. Comparison to external evidences of selection and regulatory function confirms that these SVM predictions are more accurate than those of other approaches.
The predictor and predictions made are available at http://www.mcb.mcgill.ca/~blanchem/sadri.
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ABSTRACT: Identifying and characterizing the transcription factor binding site (TFBS) patterns of cis-regulatory elements represents a challenge, but holds promise to reveal the regulatory language the genome uses to dictate transcriptional dynamics. Several studies have demonstrated that regulatory modules are under positive selection and, therefore, are often conserved between related species. Using this evolutionary principle, we have created a comparative tool, rVISTA, for analyzing the regulatory potential of noncoding sequences. Our ability to experimentally identify functional noncoding sequences is extremely limited, therefore, rVISTA attempts to fill this great gap in genomic analysis by offering a powerful approach for eliminating TFBSs least likely to be biologically relevant. The rVISTA tool combines TFBS predictions, sequence comparisons and cluster analysis to identify noncoding DNA regions that are evolutionarily conserved and present in a specific configuration within genomic sequences. Here, we present the newly developed version 2.0 of the rVISTA tool, which can process alignments generated by both the zPicture and blastz alignment programs or use pre-computed pairwise alignments of several vertebrate genomes available from the ECR Browser and GALA database. The rVISTA web server is closely interconnected with the TRANSFAC database, allowing users to either search for matrices present in the TRANSFAC library collection or search for user-defined consensus sequences. The rVISTA tool is publicly available at http://rvista.dcode.org/.Nucleic Acids Research 08/2004; 32(Web Server issue):W217-21. DOI:10.1093/nar/gkh383 · 9.11 Impact Factor
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ABSTRACT: It is believed that most modern mammalian lineages arose from a series of rapid speciation events near the Cretaceous-Tertiary boundary. It is shown that such a phylogeny makes the common ancestral genome sequence an ideal target for reconstruction. Simulations suggest that with methods currently available, we can expect to get 98% of the bases correct in reconstructing megabase-scale euchromatic regions of an eutherian ancestral genome from the genomes of approximately 20 optimally chosen modern mammals. Using actual genomic sequences from 19 extant mammals, we reconstruct 1.1 Mb of ancient genome sequence around the CFTR locus. Detailed examination suggests the reconstruction is accurate and that it allows us to identify features in modern species, such as remnants of ancient transposon insertions, that were not identified by direct analysis. Tracing the predicted evolutionary history of the bases in the reconstructed region, estimates are made of the amount of DNA turnover due to insertion, deletion, and substitution in the different placental mammalian lineages since the common eutherian ancestor, showing considerable variation between lineages. In coming years, such reconstructions may help in identifying and understanding the genetic features common to eutherian mammals and may shed light on the evolution of human or primate-specific traits.Genome Research 01/2005; 14(12):2412-23. DOI:10.1101/gr.2800104 · 13.85 Impact Factor
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ABSTRACT: Comparisons of orthologous genomic DNA sequences can be used to characterize regions that have been subject to purifying selection and are enriched for functional elements. We here present the results of such an analysis on an alignment of sequences from 29 mammalian species. The alignment captures approximately 3.9 neutral substitutions per site and spans approximately 1.9 Mbp of the human genome. We identify constrained elements from 3 bp to over 1 kbp in length, covering approximately 5.5% of the human locus. Our estimate for the total amount of nonexonic constraint experienced by this locus is roughly twice that for exonic constraint. Constrained elements tend to cluster, and we identify large constrained regions that correspond well with known functional elements. While constraint density inversely correlates with mobile element density, we also show the presence of unambiguously constrained elements overlapping mammalian ancestral repeats. In addition, we describe a number of elements in this region that have undergone intense purifying selection throughout mammalian evolution, and we show that these important elements are more numerous than previously thought. These results were obtained with Genomic Evolutionary Rate Profiling (GERP), a statistically rigorous and biologically transparent framework for constrained element identification. GERP identifies regions at high resolution that exhibit nucleotide substitution deficits, and measures these deficits as "rejected substitutions". Rejected substitutions reflect the intensity of past purifying selection and are used to rank and characterize constrained elements. We anticipate that GERP and the types of analyses it facilitates will provide further insights and improved annotation for the human genome as mammalian genome sequence data become richer.Genome Research 08/2005; 15(7):901-13. DOI:10.1101/gr.3577405 · 13.85 Impact Factor