Polymorphic edge detection (PED): two efficient methods of polymorphism detection from next-generation sequencing data
Identifieur interne : 000213 ( Pmc/Checkpoint ); précédent : 000212; suivant : 000214Polymorphic edge detection (PED): two efficient methods of polymorphism detection from next-generation sequencing data
Auteurs : Akio Miyao [Japon] ; Jianyu Song Kiyomiya [Japon] ; Keiko Iida [Japon] ; Koji Doi [Japon] ; Hiroshi Yasue [Japon]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2019.
Abstract
Accurate detection of polymorphisms with a next generation sequencer data is an important element of current genetic analysis. However, there is still no detection pipeline that is completely reliable.
We demonstrate two new detection methods of polymorphisms focusing on the Polymorphic Edge (PED). In the matching between two homologous sequences, the first mismatched base to appear is the SNP, or the edge of the structural variation. The first method is based on
Using Polymorphic Edge Detection (PED), the
The PED software is available at:
The online version of this article (10.1186/s12859-019-2955-6) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12859-019-2955-6
PubMed: 31253084
PubMed Central: 6599308
Affiliations:
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PMC:6599308Le document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Polymorphic edge detection (PED): two efficient methods of polymorphism detection from next-generation sequencing data</title>
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<author><name sortKey="Kiyomiya, Jianyu Song" sort="Kiyomiya, Jianyu Song" uniqKey="Kiyomiya J" first="Jianyu Song" last="Kiyomiya">Jianyu Song Kiyomiya</name>
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<author><name sortKey="Yasue, Hiroshi" sort="Yasue, Hiroshi" uniqKey="Yasue H" first="Hiroshi" last="Yasue">Hiroshi Yasue</name>
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<series><title level="j">BMC Bioinformatics</title>
<idno type="eISSN">1471-2105</idno>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p id="Par1">Accurate detection of polymorphisms with a next generation sequencer data is an important element of current genetic analysis. However, there is still no detection pipeline that is completely reliable.</p>
</sec>
<sec><title>Result</title>
<p id="Par2">We demonstrate two new detection methods of polymorphisms focusing on the Polymorphic Edge (PED). In the matching between two homologous sequences, the first mismatched base to appear is the SNP, or the edge of the structural variation. The first method is based on <italic>k</italic>
-mers from short reads and detects polymorphic edges with <italic>k</italic>
-mers for which there is no match between target and control, making it possible to detect SNPs by direct comparison of short-reads in two datasets (target and control) without a reference genome sequence. The second method is based on bidirectional alignment to detect polymorphic edges, not only SNPs but also insertions, deletions, inversions and translocations. Using these two methods, we succeed in making a high-quality comparison map between rice cultivars showing good match to the theoretical value of introgression, and in detecting specific large deletions across cultivars.</p>
</sec>
<sec><title>Conclusions</title>
<p id="Par3">Using Polymorphic Edge Detection (PED), the <italic>k</italic>
-mer method is able to detect SNPs by direct comparison of short-reads in two datasets without genomic alignment step, and the bidirectional alignment method is able to detect SNPs and structural variations from even single-end short-reads. The PED is an efficient tool to obtain accurate data for both SNPs and structural variations.</p>
</sec>
<sec><title>Availability</title>
<p id="Par4">The PED software is available at: <ext-link ext-link-type="uri" xlink:href="https://github.com/akiomiyao/ped">https://github.com/akiomiyao/ped</ext-link>
.</p>
</sec>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (10.1186/s12859-019-2955-6) contains supplementary material, which is available to authorized users.</p>
</sec>
</div>
</front>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id>
<journal-id journal-id-type="iso-abbrev">BMC Bioinformatics</journal-id>
<journal-title-group><journal-title>BMC Bioinformatics</journal-title>
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<issn pub-type="epub">1471-2105</issn>
<publisher><publisher-name>BioMed Central</publisher-name>
<publisher-loc>London</publisher-loc>
</publisher>
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<article-meta><article-id pub-id-type="pmid">31253084</article-id>
<article-id pub-id-type="pmc">6599308</article-id>
<article-id pub-id-type="publisher-id">2955</article-id>
<article-id pub-id-type="doi">10.1186/s12859-019-2955-6</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
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</article-categories>
<title-group><article-title>Polymorphic edge detection (PED): two efficient methods of polymorphism detection from next-generation sequencing data</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-2822-2866</contrib-id>
<name><surname>Miyao</surname>
<given-names>Akio</given-names>
</name>
<address><email>miyao@affrc.go.jp</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kiyomiya</surname>
<given-names>Jianyu Song</given-names>
</name>
<address><email>songjjyy@affrc.go.jp</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Iida</surname>
<given-names>Keiko</given-names>
</name>
<address><email>ookei@affrc.go.jp</email>
</address>
<xref ref-type="aff" rid="Aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Doi</surname>
<given-names>Koji</given-names>
</name>
<address><email>kdoi@tsukuba-genetech.com</email>
</address>
<xref ref-type="aff" rid="Aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Yasue</surname>
<given-names>Hiroshi</given-names>
</name>
<address><email>hyasue@tsukuba-genetech.com</email>
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<xref ref-type="aff" rid="Aff2">2</xref>
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<institution>National Agriculture and Food Research Organization,</institution>
</institution-wrap>
2-1-2, Kannondai, Tsukuba, Ibaraki, 305-8518 Japan</aff>
<aff id="Aff2"><label>2</label>
Tsukuba Gene Technology Laboratories Inc, 6-320, Arakawaoki, Tsuchiura, Ibaraki, 300-0873 Japan</aff>
</contrib-group>
<pub-date pub-type="epub"><day>28</day>
<month>6</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>28</day>
<month>6</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="collection"><year>2019</year>
</pub-date>
<volume>20</volume>
<elocation-id>362</elocation-id>
<history><date date-type="received"><day>7</day>
<month>4</month>
<year>2019</year>
</date>
<date date-type="accepted"><day>17</day>
<month>6</month>
<year>2019</year>
</date>
</history>
<permissions><copyright-statement>© The Author(s). 2019</copyright-statement>
<license license-type="OpenAccess"><license-p><bold>Open Access</bold>
This article is distributed under the terms of the Creative Commons Attribution 4.0 International 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 use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>
) applies to the data made available in this article, unless otherwise stated.</license-p>
</license>
</permissions>
<abstract id="Abs1"><sec><title>Background</title>
<p id="Par1">Accurate detection of polymorphisms with a next generation sequencer data is an important element of current genetic analysis. However, there is still no detection pipeline that is completely reliable.</p>
</sec>
<sec><title>Result</title>
<p id="Par2">We demonstrate two new detection methods of polymorphisms focusing on the Polymorphic Edge (PED). In the matching between two homologous sequences, the first mismatched base to appear is the SNP, or the edge of the structural variation. The first method is based on <italic>k</italic>
-mers from short reads and detects polymorphic edges with <italic>k</italic>
-mers for which there is no match between target and control, making it possible to detect SNPs by direct comparison of short-reads in two datasets (target and control) without a reference genome sequence. The second method is based on bidirectional alignment to detect polymorphic edges, not only SNPs but also insertions, deletions, inversions and translocations. Using these two methods, we succeed in making a high-quality comparison map between rice cultivars showing good match to the theoretical value of introgression, and in detecting specific large deletions across cultivars.</p>
</sec>
<sec><title>Conclusions</title>
<p id="Par3">Using Polymorphic Edge Detection (PED), the <italic>k</italic>
-mer method is able to detect SNPs by direct comparison of short-reads in two datasets without genomic alignment step, and the bidirectional alignment method is able to detect SNPs and structural variations from even single-end short-reads. The PED is an efficient tool to obtain accurate data for both SNPs and structural variations.</p>
</sec>
<sec><title>Availability</title>
<p id="Par4">The PED software is available at: <ext-link ext-link-type="uri" xlink:href="https://github.com/akiomiyao/ped">https://github.com/akiomiyao/ped</ext-link>
.</p>
</sec>
<sec><title>Electronic supplementary material</title>
<p>The online version of this article (10.1186/s12859-019-2955-6) contains supplementary material, which is available to authorized users.</p>
</sec>
</abstract>
<kwd-group xml:lang="en"><title>Keywords</title>
<kwd>NGS</kwd>
<kwd>Mutation</kwd>
<kwd>Polymorphism</kwd>
<kwd>Indel</kwd>
<kwd>SV</kwd>
</kwd-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© The Author(s) 2019</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Japon</li>
</country>
</list>
<tree><country name="Japon"><noRegion><name sortKey="Miyao, Akio" sort="Miyao, Akio" uniqKey="Miyao A" first="Akio" last="Miyao">Akio Miyao</name>
</noRegion>
<name sortKey="Doi, Koji" sort="Doi, Koji" uniqKey="Doi K" first="Koji" last="Doi">Koji Doi</name>
<name sortKey="Iida, Keiko" sort="Iida, Keiko" uniqKey="Iida K" first="Keiko" last="Iida">Keiko Iida</name>
<name sortKey="Kiyomiya, Jianyu Song" sort="Kiyomiya, Jianyu Song" uniqKey="Kiyomiya J" first="Jianyu Song" last="Kiyomiya">Jianyu Song Kiyomiya</name>
<name sortKey="Yasue, Hiroshi" sort="Yasue, Hiroshi" uniqKey="Yasue H" first="Hiroshi" last="Yasue">Hiroshi Yasue</name>
</country>
</tree>
</affiliations>
</record>
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