A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations
Identifieur interne : 000F89 ( Pmc/Curation ); précédent : 000F88; suivant : 000F90A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations
Auteurs : Weiling Li [États-Unis] ; Lin Lin [États-Unis] ; Raunaq Malhotra [États-Unis] ; Lei Yang [États-Unis] ; Raj Acharya [États-Unis] ; Mary Poss [États-Unis]Source :
- PLoS Computational Biology [ 1553-734X ] ; 2019.
Abstract
Human Endogenous Retrovirus type K (HERV-K) is the only HERV known to be insertionally polymorphic; not all individuals have a retrovirus at a specific genomic location. It is possible that HERV-Ks contribute to human disease because people differ in both number and genomic location of these retroviruses. Indeed viral transcripts, proteins, and antibody against HERV-K are detected in cancers, auto-immune, and neurodegenerative diseases. However, attempts to link a polymorphic HERV-K with any disease have been frustrated in part because population prevalence of HERV-K provirus at each polymorphic site is lacking and it is challenging to identify closely related elements such as HERV-K from short read sequence data. We present an integrated and computationally robust approach that uses whole genome short read data to determine the occupation status at all sites reported to contain a HERV-K provirus. Our method estimates the proportion of fixed length genomic sequence (
Url:
DOI: 10.1371/journal.pcbi.1006564
PubMed: 30921327
PubMed Central: 6456218
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Sciences, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">30921327</idno><idno type="pmc">6456218</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6456218</idno><idno type="RBID">PMC:6456218</idno><idno type="doi">10.1371/journal.pcbi.1006564</idno><date when="2019">2019</date><idno type="wicri:Area/Pmc/Corpus">000F89</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000F89</idno><idno type="wicri:Area/Pmc/Curation">000F89</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000F89</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations</title><author><name sortKey="Li, Weiling" sort="Li, Weiling" uniqKey="Li W" first="Weiling" last="Li">Weiling Li</name><affiliation wicri:level="1"><nlm:aff id="aff001"><addr-line>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author><author><name sortKey="Lin, Lin" sort="Lin, Lin" uniqKey="Lin L" first="Lin" last="Lin">Lin Lin</name><affiliation wicri:level="1"><nlm:aff id="aff002"><addr-line>Department of Statistics, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author><author><name sortKey="Malhotra, Raunaq" sort="Malhotra, Raunaq" uniqKey="Malhotra R" first="Raunaq" last="Malhotra">Raunaq Malhotra</name><affiliation wicri:level="1"><nlm:aff id="aff001"><addr-line>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author><author><name sortKey="Yang, Lei" sort="Yang, Lei" uniqKey="Yang L" first="Lei" last="Yang">Lei Yang</name><affiliation wicri:level="1"><nlm:aff id="aff003"><addr-line>Department of Biology, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author><author><name sortKey="Acharya, Raj" sort="Acharya, Raj" uniqKey="Acharya R" first="Raj" last="Acharya">Raj Acharya</name><affiliation wicri:level="1"><nlm:aff id="aff001"><addr-line>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff004"><addr-line>School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN</wicri:regionArea></affiliation></author><author><name sortKey="Poss, Mary" sort="Poss, Mary" uniqKey="Poss M" first="Mary" last="Poss">Mary Poss</name><affiliation wicri:level="1"><nlm:aff id="aff003"><addr-line>Department of Biology, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff005"><addr-line>Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA</wicri:regionArea></affiliation></author></analytic><series><title level="j">PLoS Computational Biology</title><idno type="ISSN">1553-734X</idno><idno type="eISSN">1553-7358</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Human Endogenous Retrovirus type K (HERV-K) is the only HERV known to be insertionally polymorphic; not all individuals have a retrovirus at a specific genomic location. It is possible that HERV-Ks contribute to human disease because people differ in both number and genomic location of these retroviruses. Indeed viral transcripts, proteins, and antibody against HERV-K are detected in cancers, auto-immune, and neurodegenerative diseases. However, attempts to link a polymorphic HERV-K with any disease have been frustrated in part because population prevalence of HERV-K provirus at each polymorphic site is lacking and it is challenging to identify closely related elements such as HERV-K from short read sequence data. We present an integrated and computationally robust approach that uses whole genome short read data to determine the occupation status at all sites reported to contain a HERV-K provirus. Our method estimates the proportion of fixed length genomic sequence (<italic>k-mers</italic>) from whole genome sequence data matching a reference set of <italic>k-mers</italic> unique to each HERV-K locus and applies mixture model-based clustering of these values to account for low depth sequence data. Our analysis of 1000 Genomes Project Data (KGP) reveals numerous differences among the five KGP super-populations in the prevalence of individual and co-occurring HERV-K proviruses; we provide a visualization tool to easily depict the proportion of the KGP populations with any combination of polymorphic HERV-K provirus. Further, because HERV-K is insertionally polymorphic, the genome burden of known polymorphic HERV-K is variable in humans; this burden is lowest in East Asian (EAS) individuals. Our study identifies population-specific sequence variation for HERV-K proviruses at several loci. We expect these resources will advance research on HERV-K contributions to human diseases.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Hayward, A" uniqKey="Hayward A">A Hayward</name></author><author><name sortKey="Grabherr, M" uniqKey="Grabherr M">M Grabherr</name></author><author><name sortKey="Jern, P" uniqKey="Jern P">P Jern</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Feschotte, C" uniqKey="Feschotte C">C Feschotte</name></author><author><name sortKey="Gilbert, C" uniqKey="Gilbert C">C Gilbert</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Stoye, Jp" uniqKey="Stoye J">JP Stoye</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gifford, R" uniqKey="Gifford R">R Gifford</name></author><author><name sortKey="Tristem, M" uniqKey="Tristem M">M 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Comput Biol</journal-id><journal-id journal-id-type="iso-abbrev">PLoS Comput. Biol</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">ploscomp</journal-id><journal-title-group><journal-title>PLoS Computational Biology</journal-title></journal-title-group><issn pub-type="ppub">1553-734X</issn><issn pub-type="epub">1553-7358</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, CA USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">30921327</article-id><article-id pub-id-type="pmc">6456218</article-id><article-id pub-id-type="doi">10.1371/journal.pcbi.1006564</article-id><article-id pub-id-type="publisher-id">PCOMPBIOL-D-18-01737</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Computational Biology</subject><subj-group><subject>Genome Analysis</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genomics</subject><subj-group><subject>Genome Analysis</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Mathematical and Statistical Techniques</subject><subj-group><subject>Statistical Methods</subject><subj-group><subject>Linear Discriminant Analysis</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Physical Sciences</subject><subj-group><subject>Mathematics</subject><subj-group><subject>Statistics</subject><subj-group><subject>Statistical Methods</subject><subj-group><subject>Linear Discriminant Analysis</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Database and Informatics Methods</subject><subj-group><subject>Biological Databases</subject><subj-group><subject>Sequence Databases</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Database and Informatics Methods</subject><subj-group><subject>Bioinformatics</subject><subj-group><subject>Sequence Analysis</subject><subj-group><subject>Sequence Databases</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Computer and Information Sciences</subject><subj-group><subject>Information Technology</subject><subj-group><subject>Data Mining</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genomics</subject><subj-group><subject>Human Genomics</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genomics</subject><subj-group><subject>Animal Genomics</subject><subj-group><subject>Mammalian Genomics</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject><subj-group><subject>Database and Informatics Methods</subject><subj-group><subject>Biological Databases</subject><subj-group><subject>Genomic Databases</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Computational Biology</subject><subj-group><subject>Genome Analysis</subject><subj-group><subject>Genomic Databases</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject><subj-group><subject>Genetics</subject><subj-group><subject>Genomics</subject><subj-group><subject>Genome Analysis</subject><subj-group><subject>Genomic Databases</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3"><subject>Computer and Information Sciences</subject><subj-group><subject>Data Visualization</subject></subj-group></subj-group></article-categories><title-group><article-title>A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations</article-title><alt-title alt-title-type="running-head">Genomic distribution of polymorphic HERV-K</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Li</surname><given-names>Weiling</given-names></name><role content-type="http://credit.casrai.org/">Conceptualization</role><role content-type="http://credit.casrai.org/">Formal analysis</role><role content-type="http://credit.casrai.org/">Investigation</role><role content-type="http://credit.casrai.org/">Methodology</role><role content-type="http://credit.casrai.org/">Software</role><role content-type="http://credit.casrai.org/">Validation</role><role content-type="http://credit.casrai.org/">Writing – original draft</role><xref ref-type="aff" rid="aff001"><sup>1</sup></xref></contrib><contrib contrib-type="author"><contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0002-7464-1172</contrib-id><name><surname>Lin</surname><given-names>Lin</given-names></name><role content-type="http://credit.casrai.org/">Formal analysis</role><role content-type="http://credit.casrai.org/">Methodology</role><role content-type="http://credit.casrai.org/">Supervision</role><xref ref-type="aff" rid="aff002"><sup>2</sup></xref></contrib><contrib contrib-type="author"><contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0002-7253-850X</contrib-id><name><surname>Malhotra</surname><given-names>Raunaq</given-names></name><role content-type="http://credit.casrai.org/">Conceptualization</role><role content-type="http://credit.casrai.org/">Formal analysis</role><role content-type="http://credit.casrai.org/">Investigation</role><role content-type="http://credit.casrai.org/">Methodology</role><role content-type="http://credit.casrai.org/">Validation</role><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="author-notes" rid="currentaff001"><sup>¤a</sup></xref></contrib><contrib contrib-type="author"><name><surname>Yang</surname><given-names>Lei</given-names></name><role content-type="http://credit.casrai.org/">Formal analysis</role><role content-type="http://credit.casrai.org/">Investigation</role><xref ref-type="aff" rid="aff003"><sup>3</sup></xref></contrib><contrib contrib-type="author"><name><surname>Acharya</surname><given-names>Raj</given-names></name><role content-type="http://credit.casrai.org/">Funding acquisition</role><role content-type="http://credit.casrai.org/">Resources</role><role content-type="http://credit.casrai.org/">Supervision</role><xref ref-type="aff" rid="aff001"><sup>1</sup></xref><xref ref-type="aff" rid="aff004"><sup>4</sup></xref></contrib><contrib contrib-type="author"><contrib-id authenticated="true" contrib-id-type="orcid">http://orcid.org/0000-0003-4147-2410</contrib-id><name><surname>Poss</surname><given-names>Mary</given-names></name><role content-type="http://credit.casrai.org/">Conceptualization</role><role content-type="http://credit.casrai.org/">Formal analysis</role><role content-type="http://credit.casrai.org/">Funding acquisition</role><role content-type="http://credit.casrai.org/">Investigation</role><role content-type="http://credit.casrai.org/">Project administration</role><role content-type="http://credit.casrai.org/">Resources</role><role content-type="http://credit.casrai.org/">Supervision</role><role content-type="http://credit.casrai.org/">Validation</role><role content-type="http://credit.casrai.org/">Writing – original draft</role><role content-type="http://credit.casrai.org/">Writing – review & editing</role><xref ref-type="aff" rid="aff003"><sup>3</sup></xref><xref ref-type="aff" rid="aff005"><sup>5</sup></xref><xref ref-type="author-notes" rid="currentaff002"><sup>¤b</sup></xref><xref ref-type="corresp" rid="cor001">*</xref></contrib></contrib-group><aff id="aff001"><label>1</label><addr-line>The School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, PA, United States of America</addr-line></aff><aff id="aff002"><label>2</label><addr-line>Department of Statistics, The Pennsylvania State University, University Park, PA, United States of America</addr-line></aff><aff id="aff003"><label>3</label><addr-line>Department of Biology, The Pennsylvania State University, University Park, PA, United States of America</addr-line></aff><aff id="aff004"><label>4</label><addr-line>School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, United States of America</addr-line></aff><aff id="aff005"><label>5</label><addr-line>Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, United States of America</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Wilke</surname><given-names>Claus O.</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>University of Texas at Austin, UNITED STATES</addr-line></aff><author-notes><fn fn-type="COI-statement" id="coi001"><p>The authors have declared that no competing interests exist.</p></fn><fn fn-type="current-aff" id="currentaff001"><label>¤a</label><p>Current address: GNS Healthcare, Cambridge, MA, United States of America</p></fn><fn fn-type="current-aff" id="currentaff002"><label>¤b</label><p>Current address: Division of Hematology and Oncology, University of Virginia School of Medicine, Charlottesville, VA, United States of America</p></fn><corresp id="cor001">* E-mail: <email>maryposs@gmail.com</email></corresp></author-notes><pub-date pub-type="epub"><day>28</day><month>3</month><year>2019</year></pub-date><pub-date pub-type="collection"><month>3</month><year>2019</year></pub-date><volume>15</volume><issue>3</issue><elocation-id>e1006564</elocation-id><history><date date-type="received"><day>10</day><month>10</month><year>2018</year></date><date date-type="accepted"><day>5</day><month>3</month><year>2019</year></date></history><permissions><copyright-statement>© 2019 Li et al</copyright-statement><copyright-year>2019</copyright-year><copyright-holder>Li et al</copyright-holder><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="pcbi.1006564.pdf"></self-uri><abstract><p>Human Endogenous Retrovirus type K (HERV-K) is the only HERV known to be insertionally polymorphic; not all individuals have a retrovirus at a specific genomic location. It is possible that HERV-Ks contribute to human disease because people differ in both number and genomic location of these retroviruses. Indeed viral transcripts, proteins, and antibody against HERV-K are detected in cancers, auto-immune, and neurodegenerative diseases. However, attempts to link a polymorphic HERV-K with any disease have been frustrated in part because population prevalence of HERV-K provirus at each polymorphic site is lacking and it is challenging to identify closely related elements such as HERV-K from short read sequence data. We present an integrated and computationally robust approach that uses whole genome short read data to determine the occupation status at all sites reported to contain a HERV-K provirus. Our method estimates the proportion of fixed length genomic sequence (<italic>k-mers</italic>) from whole genome sequence data matching a reference set of <italic>k-mers</italic> unique to each HERV-K locus and applies mixture model-based clustering of these values to account for low depth sequence data. Our analysis of 1000 Genomes Project Data (KGP) reveals numerous differences among the five KGP super-populations in the prevalence of individual and co-occurring HERV-K proviruses; we provide a visualization tool to easily depict the proportion of the KGP populations with any combination of polymorphic HERV-K provirus. Further, because HERV-K is insertionally polymorphic, the genome burden of known polymorphic HERV-K is variable in humans; this burden is lowest in East Asian (EAS) individuals. Our study identifies population-specific sequence variation for HERV-K proviruses at several loci. We expect these resources will advance research on HERV-K contributions to human diseases.</p></abstract><abstract abstract-type="summary"><title>Author summary</title><p>Human Endogenous Retrovirus type K (HERV-K) is the youngest of retrovirus families in the human genome and is the only group of endogenous retroviruses that has polymorphic members; a locus containing a HERV-K can be occupied in one individual but empty in others. HERV-Ks could contribute to disease risk or pathogenesis but linking one of the known polymorphic HERV-K to a specific disease has been difficult. We develop an easy to use method that reveals the considerable variation existing among global populations in the prevalence of individual and co-occurring polymorphic HERV-K, and in the number of HERV-K that any individual has in their genome. Our study provides a reference of diversity for the currently known polymorphic HERV-K in global populations and tools needed to determine the profile of all known polymorphic HERV-K in the genome of any patient population.</p></abstract><funding-group><award-group id="award001"><funding-source><institution>National Science Foundation (US)</institution></funding-source><award-id>1724008</award-id><principal-award-recipient><name><surname>Acharya</surname><given-names>Raj</given-names></name></principal-award-recipient></award-group><award-group id="award002"><funding-source><institution>National Science Foundation</institution></funding-source><award-id>1720635</award-id><principal-award-recipient><name><surname>Acharya</surname><given-names>Raj</given-names></name></principal-award-recipient></award-group><award-group id="award003"><funding-source><institution>National Cancer Institute (US)</institution></funding-source><award-id>RO1CA170334</award-id></award-group><funding-statement>This research was supported in part by the National Science Foundation award numbers 1724008 and 1720635 to RA. WL and LY were funded in part by by the National Cancer Institute of the National Institutes of Health under Award Number 7RO1CA170334 (MP subaward PI). WL was a recipient of the Louis S. and Sara S. Michael Endowed Graduate Fellowship in Engineering and the Fred A. and Susan Breidenbach Graduate Fellowship in Engineering. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><fig-count count="5"></fig-count><table-count count="1"></table-count><page-count count="21"></page-count></counts><custom-meta-group><custom-meta><meta-name>PLOS Publication Stage</meta-name><meta-value>vor-update-to-uncorrected-proof</meta-value></custom-meta><custom-meta><meta-name>Publication Update</meta-name><meta-value>2019-04-09</meta-value></custom-meta><custom-meta id="data-availability"><meta-name>Data Availability</meta-name><meta-value>All relevant data are within the manuscript and its Supporting Information files. The code is available at <ext-link ext-link-type="uri" xlink:href="https://github.com/lwl1112/polymorphicHERV">https://github.com/lwl1112/polymorphicHERV</ext-link>.</meta-value></custom-meta></custom-meta-group></article-meta><notes><title>Data Availability</title><p>All relevant data are within the manuscript and its Supporting Information files. The code is available at <ext-link ext-link-type="uri" xlink:href="https://github.com/lwl1112/polymorphicHERV">https://github.com/lwl1112/polymorphicHERV</ext-link>.</p></notes></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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