SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand
Identifieur interne : 000059 ( Pmc/Curation ); précédent : 000058; suivant : 000060SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand
Auteurs : Haibao Tang [République populaire de Chine] ; Matthew D. Bomhoff ; Evan Briones ; Liangsheng Zhang [République populaire de Chine] ; James C. Schnable ; Eric LyonsSource :
- Genome Biology and Evolution [ 1759-6653 ] ; 2015.
Abstract
The identification of conserved syntenic regions enables discovery of predicted
locations for orthologous and homeologous genes, even when no such gene is present.
This capability means that synteny-based methods are far more effective than sequence
similarity-based methods in identifying true-negatives, a necessity for studying gene
loss and gene transposition. However, the identification of syntenic regions requires
complex analyses which must be repeated for pairwise comparisons between any two
species. Therefore, as the number of published genomes increases, there is a growing
demand for scalable, simple-to-use applications to perform comparative genomic
analyses that cater to both gene family studies and genome-scale studies. We
implemented SynFind, a web-based tool that addresses this need. Given one query
genome, SynFind is capable of identifying conserved syntenic regions in any set of
target genomes. SynFind is capable of reporting per-gene information, useful for
researchers studying specific gene families, as well as genome-wide data sets of
syntenic gene and predicted gene locations, critical for researchers focused on
large-scale genomic analyses. Inference of syntenic homologs provides the basis for
correlation of functional changes around genes of interests between related
organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic
data from over 15,000 organisms from all domains of life as well as supporting
multiple releases of the same organism. SynFind makes use of a powerful job execution
framework that promises scalability and reproducibility. SynFind can be accessed at
Url:
DOI: 10.1093/gbe/evv219
PubMed: 26560340
PubMed Central: 4700967
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Haibao Tang<affiliation><nlm:aff id="evv219-AFF2">School of Plant Sciences, iPlant Collaborative, University of Arizona</nlm:aff>
<wicri:noCountry code="subfield">University of Arizona</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="evv219-AFF2">School of Plant Sciences, iPlant Collaborative, University of Arizona</nlm:aff>
<wicri:noCountry code="subfield">University of Arizona</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="evv219-AFF2">School of Plant Sciences, iPlant Collaborative, University of Arizona</nlm:aff>
<wicri:noCountry code="subfield">University of Arizona</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="evv219-AFF3">Department of Agronomy and Horticulture, University of Nebraska, Lincoln</nlm:aff>
<wicri:noCountry code="subfield">Lincoln</wicri:noCountry>
</affiliation>
<affiliation><nlm:aff id="evv219-AFF2">School of Plant Sciences, iPlant Collaborative, University of Arizona</nlm:aff>
<wicri:noCountry code="subfield">University of Arizona</wicri:noCountry>
</affiliation>
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<front><div type="abstract" xml:lang="en"><p>The identification of conserved syntenic regions enables discovery of predicted
locations for orthologous and homeologous genes, even when no such gene is present.
This capability means that synteny-based methods are far more effective than sequence
similarity-based methods in identifying true-negatives, a necessity for studying gene
loss and gene transposition. However, the identification of syntenic regions requires
complex analyses which must be repeated for pairwise comparisons between any two
species. Therefore, as the number of published genomes increases, there is a growing
demand for scalable, simple-to-use applications to perform comparative genomic
analyses that cater to both gene family studies and genome-scale studies. We
implemented SynFind, a web-based tool that addresses this need. Given one query
genome, SynFind is capable of identifying conserved syntenic regions in any set of
target genomes. SynFind is capable of reporting per-gene information, useful for
researchers studying specific gene families, as well as genome-wide data sets of
syntenic gene and predicted gene locations, critical for researchers focused on
large-scale genomic analyses. Inference of syntenic homologs provides the basis for
correlation of functional changes around genes of interests between related
organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic
data from over 15,000 organisms from all domains of life as well as supporting
multiple releases of the same organism. SynFind makes use of a powerful job execution
framework that promises scalability and reproducibility. SynFind can be accessed at
<ext-link ext-link-type="uri" xlink:href="http://genomevolution.org/CoGe/SynFind.pl">http://genomevolution.org/CoGe/SynFind.pl</ext-link>
. A video tutorial of SynFind
using <italic>Phytophthrora</italic>
as an example is available at <ext-link ext-link-type="uri" xlink:href="http://www.youtube.com/watch?v=2Agczny9Nyc">http://www.youtube.com/watch?v=2Agczny9Nyc</ext-link>
.</p>
</div>
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<biblStruct><analytic><author><name sortKey="Woodhouse, Mr" uniqKey="Woodhouse M">MR Woodhouse</name>
</author>
<author><name sortKey="Pedersen, B" uniqKey="Pedersen B">B Pedersen</name>
</author>
<author><name sortKey="Freeling, M" uniqKey="Freeling M">M Freeling</name>
</author>
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<biblStruct><analytic><author><name sortKey="Woodhouse, Mr" uniqKey="Woodhouse M">MR Woodhouse</name>
</author>
<author><name sortKey="Tang, H" uniqKey="Tang H">H Tang</name>
</author>
<author><name sortKey="Freeling, M" uniqKey="Freeling M">M Freeling</name>
</author>
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</TEI>
<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Genome Biol Evol</journal-id>
<journal-id journal-id-type="iso-abbrev">Genome Biol Evol</journal-id>
<journal-id journal-id-type="publisher-id">gbe</journal-id>
<journal-id journal-id-type="hwp">gbe</journal-id>
<journal-title-group><journal-title>Genome Biology and Evolution</journal-title>
</journal-title-group>
<issn pub-type="epub">1759-6653</issn>
<publisher><publisher-name>Oxford University Press</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">26560340</article-id>
<article-id pub-id-type="pmc">4700967</article-id>
<article-id pub-id-type="doi">10.1093/gbe/evv219</article-id>
<article-id pub-id-type="publisher-id">evv219</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Genome Resources</subject>
</subj-group>
</article-categories>
<title-group><article-title>SynFind: Compiling Syntenic Regions across Any Set of Genomes on
Demand</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Tang</surname>
<given-names>Haibao</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF1"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="evv219-AFF2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Bomhoff</surname>
<given-names>Matthew D.</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Briones</surname>
<given-names>Evan</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF2"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zhang</surname>
<given-names>Liangsheng</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF1"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Schnable</surname>
<given-names>James C.</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF3"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Lyons</surname>
<given-names>Eric</given-names>
</name>
<xref ref-type="aff" rid="evv219-AFF2"><sup>2</sup>
</xref>
<xref ref-type="corresp" rid="evv219-COR1">*</xref>
</contrib>
<aff id="evv219-AFF1"><sup>1</sup>
Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China</aff>
<aff id="evv219-AFF2"><sup>2</sup>
School of Plant Sciences, iPlant Collaborative, University of Arizona</aff>
<aff id="evv219-AFF3"><sup>3</sup>
Department of Agronomy and Horticulture, University of Nebraska, Lincoln</aff>
</contrib-group>
<author-notes><corresp id="evv219-COR1">*Corresponding author: E-mail:
<email>elyons.uoa@gmail.com</email>
.</corresp>
<fn id="FN1"><p><bold>Associate editor:</bold>
Kenneth Wolfe</p>
</fn>
</author-notes>
<pub-date pub-type="collection"><month>12</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="epub"><day>11</day>
<month>11</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>11</day>
<month>11</month>
<year>2015</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the
. </pmc-comment>
<volume>7</volume>
<issue>12</issue>
<fpage>3286</fpage>
<lpage>3298</lpage>
<history><date date-type="accepted"><day>6</day>
<month>11</month>
<year>2015</year>
</date>
</history>
<permissions><copyright-statement>© The Author(s) 2015. Published by Oxford University Press on
behalf of the Society for Molecular Biology and Evolution.</copyright-statement>
<copyright-year>2015</copyright-year>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/" license-type="creative-commons"><license-p>This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>
), which permits
unrestricted reuse, distribution, and reproduction in any medium, provided the
original work is properly cited.</license-p>
</license>
</permissions>
<abstract><p>The identification of conserved syntenic regions enables discovery of predicted
locations for orthologous and homeologous genes, even when no such gene is present.
This capability means that synteny-based methods are far more effective than sequence
similarity-based methods in identifying true-negatives, a necessity for studying gene
loss and gene transposition. However, the identification of syntenic regions requires
complex analyses which must be repeated for pairwise comparisons between any two
species. Therefore, as the number of published genomes increases, there is a growing
demand for scalable, simple-to-use applications to perform comparative genomic
analyses that cater to both gene family studies and genome-scale studies. We
implemented SynFind, a web-based tool that addresses this need. Given one query
genome, SynFind is capable of identifying conserved syntenic regions in any set of
target genomes. SynFind is capable of reporting per-gene information, useful for
researchers studying specific gene families, as well as genome-wide data sets of
syntenic gene and predicted gene locations, critical for researchers focused on
large-scale genomic analyses. Inference of syntenic homologs provides the basis for
correlation of functional changes around genes of interests between related
organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic
data from over 15,000 organisms from all domains of life as well as supporting
multiple releases of the same organism. SynFind makes use of a powerful job execution
framework that promises scalability and reproducibility. SynFind can be accessed at
<ext-link ext-link-type="uri" xlink:href="http://genomevolution.org/CoGe/SynFind.pl">http://genomevolution.org/CoGe/SynFind.pl</ext-link>
. A video tutorial of SynFind
using <italic>Phytophthrora</italic>
as an example is available at <ext-link ext-link-type="uri" xlink:href="http://www.youtube.com/watch?v=2Agczny9Nyc">http://www.youtube.com/watch?v=2Agczny9Nyc</ext-link>
.</p>
</abstract>
<kwd-group><kwd>synteny</kwd>
<kwd>homology</kwd>
<kwd>genome evolution</kwd>
<kwd>cyberinfrastructure</kwd>
</kwd-group>
<counts><page-count count="13"></page-count>
</counts>
</article-meta>
</front>
</pmc>
</record>
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