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      CONDOR: a database resource of developmentally associated conserved non-coding elements

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          Abstract

          Background

          Comparative genomics is currently one of the most popular approaches to study the regulatory architecture of vertebrate genomes. Fish-mammal genomic comparisons have proved powerful in identifying conserved non-coding elements likely to be distal cis-regulatory modules such as enhancers, silencers or insulators that control the expression of genes involved in the regulation of early development. The scientific community is showing increasing interest in characterizing the function, evolution and language of these sequences. Despite this, there remains little in the way of user-friendly access to a large dataset of such elements in conjunction with the analysis and the visualization tools needed to study them.

          Description

          Here we present CONDOR (COnserved Non-coDing Orthologous Regions) available at: http://condor.fugu.biology.qmul.ac.uk. In an interactive and intuitive way the website displays data on > 6800 non-coding elements associated with over 120 early developmental genes and conserved across vertebrates. The database regularly incorporates results of ongoing in vivo zebrafish enhancer assays of the CNEs carried out in-house, which currently number ~100. Included and highlighted within this set are elements derived from duplication events both at the origin of vertebrates and more recently in the teleost lineage, thus providing valuable data for studying the divergence of regulatory roles between paralogs. CONDOR therefore provides a number of tools and facilities to allow scientists to progress in their own studies on the function and evolution of developmental cis-regulation.

          Conclusion

          By providing access to data with an approachable graphics interface, the CONDOR database presents a rich resource for further studies into the regulation and evolution of genes involved in early development.

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          Most cited references20

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          LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA.

          To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. We present LAGAN, a system for rapid global alignment of two homologous genomic sequences, and Multi-LAGAN, a system for multiple global alignment of genomic sequences. We tested our systems on a data set consisting of greater than 12 Mb of high-quality sequence from 12 vertebrate species. All the sequence was derived from the genomic region orthologous to an approximately 1.5-Mb region on human chromosome 7q31.3. We found that both LAGAN and Multi-LAGAN compare favorably with other leading alignment methods in correctly aligning protein-coding exons, especially between distant homologs such as human and chicken, or human and fugu. Multi-LAGAN produced the most accurate alignments, while requiring just 75 minutes on a personal computer to obtain the multiple alignment of all 12 sequences. Multi-LAGAN is a practical method for generating multiple alignments of long genomic sequences at any evolutionary distance. Our systems are publicly available at http://lagan.stanford.edu.
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            Ensembl 2007

            The Ensembl () project provides a comprehensive and integrated source of annotation of chordate genome sequences. Over the past year the number of genomes available from Ensembl has increased from 15 to 33, with the addition of sites for the mammalian genomes of elephant, rabbit, armadillo, tenrec, platypus, pig, cat, bush baby, common shrew, microbat and european hedgehog; the fish genomes of stickleback and medaka and the second example of the genomes of the sea squirt (Ciona savignyi) and the mosquito (Aedes aegypti). Some of the major features added during the year include the first complete gene sets for genomes with low-sequence coverage, the introduction of new strain variation data and the introduction of new orthology/paralog annotations based on gene trees.
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              Identification and characterization of multi-species conserved sequences.

              Comparative sequence analysis has become an essential component of studies aiming to elucidate genome function. The increasing availability of genomic sequences from multiple vertebrates is creating the need for computational methods that can detect highly conserved regions in a robust fashion. Towards that end, we are developing approaches for identifying sequences that are conserved across multiple species; we call these "Multi-species Conserved Sequences" (or MCSs). Here we report two strategies for MCS identification, demonstrating their ability to detect virtually all known actively conserved sequences (specifically, coding sequences) but very little neutrally evolving sequence (specifically, ancestral repeats). Importantly, we find that a substantial fraction of the bases within MCSs (approximately 70%) resides within non-coding regions; thus, the majority of sequences conserved across multiple vertebrate species has no known function. Initial characterization of these MCSs has revealed sequences that correspond to clusters of transcription factor-binding sites, non-coding RNA transcripts, and other candidate functional elements. Finally, the ability to detect MCSs represents a valuable metric for assessing the relative contribution of a species' sequence to identifying genomic regions of interest, and our results indicate that the currently available genome sequences are insufficient for the comprehensive identification of MCSs in the human genome.
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                Author and article information

                Journal
                BMC Dev Biol
                BMC Developmental Biology
                BioMed Central (London )
                1471-213X
                2007
                30 August 2007
                : 7
                : 100
                Affiliations
                [1 ]School of Biological Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK
                [2 ]Genomic Functional Analysis Section, National Human Genome Research Institute, National Institutes of Health, Rockville, MD 20870, USA
                Article
                1471-213X-7-100
                10.1186/1471-213X-7-100
                2020477
                17760977
                6a1fc12e-d216-4c0f-b547-1caa270ac3b2
                Copyright © 2007 Woolfe et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 June 2007
                : 30 August 2007
                Categories
                Database

                Developmental biology
                Developmental biology

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