MOTIVATION: In the living cell nucleus, genomic DNA is packaged into chromatin. DNA sequences that regulate transcription and other chromosomal processes are associated with local disruptions, or 'openings', in chromatin structure caused by the cooperative action of regulatory proteins. Such perturbations are extremely specific for cis-regulatory elements and occur over short stretches of DNA (typically approximately 250 bp). They can be detected experimentally as DNaseI hypersensitive sites (HSs) in vivo, though the process is extremely laborious and costly. The ability to discriminate DNaseI HSs computationally would have a major impact on the annotation and utilization of the human genome. RESULTS: We found that a supervised pattern recognition algorithm, trained using a set of 280 DNaseI HS and 737 non-HS control sequences from erythroid cells, was capable of de novo prediction of HSs across the human genome with surprisingly high accuracy determined by prospective in vivo validation. Systematic application of this computational approach will greatly facilitate the discovery and analysis of functional non-coding elements in the human and other complex genomes. AVAILABILITY: Supplementary data is available at noble.gs.washington.edu/proj/hs
MOTIVATION: In the living cell nucleus, genomic DNA is packaged into chromatin. DNA sequences that regulate transcription and other chromosomal processes are associated with local disruptions, or 'openings', in chromatin structure caused by the cooperative action of regulatory proteins. Such perturbations are extremely specific for cis-regulatory elements and occur over short stretches of DNA (typically approximately 250 bp). They can be detected experimentally as DNaseI hypersensitive sites (HSs) in vivo, though the process is extremely laborious and costly. The ability to discriminate DNaseI HSs computationally would have a major impact on the annotation and utilization of the human genome. RESULTS: We found that a supervised pattern recognition algorithm, trained using a set of 280 DNaseI HS and 737 non-HS control sequences from erythroid cells, was capable of de novo prediction of HSs across the human genome with surprisingly high accuracy determined by prospective in vivo validation. Systematic application of this computational approach will greatly facilitate the discovery and analysis of functional non-coding elements in the human and other complex genomes. AVAILABILITY: Supplementary data is available at noble.gs.washington.edu/proj/hs
Authors: Mathieu Blanchette; Alain R Bataille; Xiaoyu Chen; Christian Poitras; Josée Laganière; Céline Lefèbvre; Geneviève Deblois; Vincent Giguère; Vincent Ferretti; Dominique Bergeron; Benoit Coulombe; François Robert Journal: Genome Res Date: 2006-04-10 Impact factor: 9.043
Authors: J D Lieb; S Beck; M L Bulyk; P Farnham; N Hattori; S Henikoff; X S Liu; K Okumura; K Shiota; T Ushijima; J M Greally Journal: Cytogenet Genome Res Date: 2006 Impact factor: 1.636
Authors: James Taylor; Svitlana Tyekucheva; David C King; Ross C Hardison; Webb Miller; Francesca Chiaromonte Journal: Genome Res Date: 2006-10-19 Impact factor: 9.043
Authors: Bei Wei; Arttu Jolma; Biswajyoti Sahu; Lukas M Orre; Fan Zhong; Fangjie Zhu; Teemu Kivioja; Inderpreet Sur; Janne Lehtiö; Minna Taipale; Jussi Taipale Journal: Nat Biotechnol Date: 2018-05-21 Impact factor: 54.908