Estimating and accounting for genotyping errors in RAD-seq experiments.
Identifieur interne : 000422 ( Main/Exploration ); précédent : 000421; suivant : 000423Estimating and accounting for genotyping errors in RAD-seq experiments.
Auteurs : Luisa Bresadola [Suisse] ; Vivian Link [Suisse] ; C Alex Buerkle [États-Unis] ; Christian Lexer [Autriche] ; Daniel Wegmann [Suisse]Source :
- Molecular ecology resources [ 1755-0998 ] ; 2020.
Abstract
In non-model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy-Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD-seq), arguably the most popular reduced representation sequencing technique, revealed per-allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome-wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD-seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.
DOI: 10.1111/1755-0998.13153
PubMed: 32142201
Affiliations:
- Autriche, Suisse, États-Unis
- Canton de Fribourg, Vienne (Autriche), Wyoming
- Fribourg, Vienne (Autriche)
- Université de Fribourg
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Estimating and accounting for genotyping errors in RAD-seq experiments.</title><author><name sortKey="Bresadola, Luisa" sort="Bresadola, Luisa" uniqKey="Bresadola L" first="Luisa" last="Bresadola">Luisa Bresadola</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation></author><author><name sortKey="Link, Vivian" sort="Link, Vivian" uniqKey="Link V" first="Vivian" last="Link">Vivian Link</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation><affiliation wicri:level="1"><nlm:affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Swiss Institute of Bioinformatics, Fribourg</wicri:regionArea><wicri:noRegion>Fribourg</wicri:noRegion></affiliation></author><author><name sortKey="Buerkle, C Alex" sort="Buerkle, C Alex" uniqKey="Buerkle C" first="C Alex" last="Buerkle">C Alex Buerkle</name><affiliation wicri:level="2"><nlm:affiliation>Department of Botany, University of Wyoming, Laramie, WY, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Botany, University of Wyoming, Laramie, WY</wicri:regionArea><placeName><region type="state">Wyoming</region></placeName></affiliation></author><author><name sortKey="Lexer, Christian" sort="Lexer, Christian" uniqKey="Lexer C" first="Christian" last="Lexer">Christian Lexer</name><affiliation wicri:level="3"><nlm:affiliation>Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.</nlm:affiliation><country xml:lang="fr">Autriche</country><wicri:regionArea>Department of Botany and Biodiversity Research, University of Vienna, Vienna</wicri:regionArea><placeName><settlement type="city">Vienne (Autriche)</settlement><region nuts="2" type="province">Vienne (Autriche)</region></placeName></affiliation></author><author><name sortKey="Wegmann, Daniel" sort="Wegmann, Daniel" uniqKey="Wegmann D" first="Daniel" last="Wegmann">Daniel Wegmann</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation><affiliation wicri:level="1"><nlm:affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Swiss Institute of Bioinformatics, Fribourg</wicri:regionArea><wicri:noRegion>Fribourg</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32142201</idno><idno type="pmid">32142201</idno><idno type="doi">10.1111/1755-0998.13153</idno><idno type="wicri:Area/Main/Corpus">000412</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000412</idno><idno type="wicri:Area/Main/Curation">000412</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000412</idno><idno type="wicri:Area/Main/Exploration">000412</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Estimating and accounting for genotyping errors in RAD-seq experiments.</title><author><name sortKey="Bresadola, Luisa" sort="Bresadola, Luisa" uniqKey="Bresadola L" first="Luisa" last="Bresadola">Luisa Bresadola</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation></author><author><name sortKey="Link, Vivian" sort="Link, Vivian" uniqKey="Link V" first="Vivian" last="Link">Vivian Link</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation><affiliation wicri:level="1"><nlm:affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Swiss Institute of Bioinformatics, Fribourg</wicri:regionArea><wicri:noRegion>Fribourg</wicri:noRegion></affiliation></author><author><name sortKey="Buerkle, C Alex" sort="Buerkle, C Alex" uniqKey="Buerkle C" first="C Alex" last="Buerkle">C Alex Buerkle</name><affiliation wicri:level="2"><nlm:affiliation>Department of Botany, University of Wyoming, Laramie, WY, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Botany, University of Wyoming, Laramie, WY</wicri:regionArea><placeName><region type="state">Wyoming</region></placeName></affiliation></author><author><name sortKey="Lexer, Christian" sort="Lexer, Christian" uniqKey="Lexer C" first="Christian" last="Lexer">Christian Lexer</name><affiliation wicri:level="3"><nlm:affiliation>Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.</nlm:affiliation><country xml:lang="fr">Autriche</country><wicri:regionArea>Department of Botany and Biodiversity Research, University of Vienna, Vienna</wicri:regionArea><placeName><settlement type="city">Vienne (Autriche)</settlement><region nuts="2" type="province">Vienne (Autriche)</region></placeName></affiliation></author><author><name sortKey="Wegmann, Daniel" sort="Wegmann, Daniel" uniqKey="Wegmann D" first="Daniel" last="Wegmann">Daniel Wegmann</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Biology, University of Fribourg, Fribourg</wicri:regionArea><orgName type="university">Université de Fribourg</orgName><placeName><settlement type="city">Fribourg</settlement><region nuts="3" type="region">Canton de Fribourg</region></placeName></affiliation><affiliation wicri:level="1"><nlm:affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Swiss Institute of Bioinformatics, Fribourg</wicri:regionArea><wicri:noRegion>Fribourg</wicri:noRegion></affiliation></author></analytic><series><title level="j">Molecular ecology resources</title><idno type="eISSN">1755-0998</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In non-model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy-Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD-seq), arguably the most popular reduced representation sequencing technique, revealed per-allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome-wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD-seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">32142201</PMID><DateRevised><Year>2020</Year><Month>07</Month><Day>27</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1755-0998</ISSN><JournalIssue CitedMedium="Internet"><Volume>20</Volume><Issue>4</Issue><PubDate><Year>2020</Year><Month>Jul</Month></PubDate></JournalIssue><Title>Molecular ecology resources</Title><ISOAbbreviation>Mol Ecol Resour</ISOAbbreviation></Journal><ArticleTitle>Estimating and accounting for genotyping errors in RAD-seq experiments.</ArticleTitle><Pagination><MedlinePgn>856-870</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/1755-0998.13153</ELocationID><Abstract><AbstractText>In non-model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy-Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD-seq), arguably the most popular reduced representation sequencing technique, revealed per-allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome-wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD-seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.</AbstractText><CopyrightInformation>© 2020 John Wiley & Sons Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Bresadola</LastName><ForeName>Luisa</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Link</LastName><ForeName>Vivian</ForeName><Initials>V</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-2677-1180</Identifier><AffiliationInfo><Affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Buerkle</LastName><ForeName>C Alex</ForeName><Initials>CA</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-4222-8858</Identifier><AffiliationInfo><Affiliation>Department of Botany, University of Wyoming, Laramie, WY, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lexer</LastName><ForeName>Christian</ForeName><Initials>C</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-7221-7482</Identifier><AffiliationInfo><Affiliation>Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wegmann</LastName><ForeName>Daniel</ForeName><Initials>D</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-2866-6739</Identifier><AffiliationInfo><Affiliation>Department of Biology, University of Fribourg, Fribourg, Switzerland.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Swiss Institute of Bioinformatics, Fribourg, Switzerland.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>31003A_149306</GrantID><Agency>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</Agency><Country></Country></Grant><Grant><GrantID>31003A_173062</GrantID><Agency>Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>04</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Mol Ecol Resour</MedlineTA><NlmUniqueID>101465604</NlmUniqueID><ISSNLinking>1755-098X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Populus</Keyword><Keyword MajorTopicYN="N">RAD-seq</Keyword><Keyword MajorTopicYN="N">genotype likelihoods</Keyword><Keyword MajorTopicYN="N">genotyping</Keyword><Keyword MajorTopicYN="N">genotyping errors</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>07</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>02</Month><Day>21</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>02</Month><Day>26</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32142201</ArticleId><ArticleId IdType="doi">10.1111/1755-0998.13153</ArticleId></ArticleIdList><ReferenceList><Title>REFERENCES</Title><Reference><Citation>Andrews, K. R., Good, J. M., Miller, M. R., Luikart, G., & Hohenlohe, P. A. (2016). Harnessing the power of RADseq for ecological and evolutionary genomics. Nature Reviews Genetics, 17(2), 81-92.</Citation></Reference><Reference><Citation>Andrews, K. R., & Luikart, G. (2014). Recent novel approaches for population genomics data analysis. Molecular Ecology, 23, 1661-1667.</Citation></Reference><Reference><Citation>Andrews, S. (2010). FastQC: A quality control tool for high throughput sequence data. Retrieved from http://www.bioinformatics.babraham.ac.uk/projects/fastqc.</Citation></Reference><Reference><Citation>Arnold, B., Corbett-Detig, R. B., Hartl, D., & Bomblies, K. (2013). RADseq underestimates diversity and introduces genealogical biases due to nonrandom haplotype sampling. Molecular Ecology, 22(11), 3179-3190.</Citation></Reference><Reference><Citation>Aronesty, E. (2011). ea-utils: Command-line tools for processing biological sequencing data. Retrieved from https://github.com/ExpressionAnalysis/ea-utils.</Citation></Reference><Reference><Citation>Baird, N. A., Etter, P. D., Atwood, T. S., Currey, M. C., Shiver, A. L., Lewis, Z. A., … Johnson, E. A. (2008). Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE, 3(10), e3376.</Citation></Reference><Reference><Citation>Buerkle, A. C., & Gompert, Z. (2013). Population genomics based on low coverage sequencing: How low should we go? Molecular Ecology, 22(11), 3028-3035.</Citation></Reference><Reference><Citation>Cariou, M., Duret, L., & Charlat, S. (2013). Is RAD-seq suitable for phylogenetic inference? An in silico assessment and optimization. Ecology and Evolution, 3(4), 846-852.</Citation></Reference><Reference><Citation>Cariou, M., Duret, L., & Charlat, S. (2016). How and how much does RAD-seq bias genetic diversity estimates? BMC Evolutionary Biology, 16(1), 240.</Citation></Reference><Reference><Citation>Casbon, J. A., Osborne, R. J., Brenner, S., & Lichtenstein, C. P. (2011). A method for counting PCR template molecules with application to next-generation sequencing. Nucleic Acids Research, 39(12), e81.</Citation></Reference><Reference><Citation>Chen, P. B., Zhu, L. J., Hainer, S. J., McCannell, K. N., & Fazzio, T. G. (2014). Unbiased chromatin accessibility profiling by RED-seq uncovers unique features of nucleosome variants in vivo. BMC Genomics, 15, 1104.</Citation></Reference><Reference><Citation>Christe, C., Stölting, K. N., Bresadola, L., Fussi, B., Heinze, B., Wegmann, D., & Lexer, C. (2016). Selection against recombinant hybrids maintains reproductive isolation in hybridizing Populus species despite F1 fertility and recurrent gene flow. Molecular Ecology, 25(11), 2482-2498.</Citation></Reference><Reference><Citation>Christe, C., Stölting, K. N., Paris, M., Fraїsse, C., Bierne, N., & Lexer, C. (2017). Adaptive evolution and segregating load contribute to the genomic landscape of divergence in two tree species connected by episodic gene flow. Molecular Ecology, 26(1), 59-76.</Citation></Reference><Reference><Citation>Chutimanitsakun, Y., Nipper, R. W., Cuesta-Marcos, A., Cistué, L., Corey, A., Filichkina, T., … Hayes, P. M. (2011). Construction and application for QTL analysis of a Restriction Site Associated DNA (RAD) linkage map in barley. BMC Genomics, 12, 4.</Citation></Reference><Reference><Citation>Cooke, T. F., Yee, M.-C., Muzzio, M., Sockell, A., Bell, R., Cornejo, O. E., … Kenny, E. E. (2016). GBStools: A statistical method for estimating allelic dropout in reduced representation sequencing data. PLOS Genetics, 12(2), e1005631.</Citation></Reference><Reference><Citation>Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., … 1000 Genomes Project Analysis Group (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158.</Citation></Reference><Reference><Citation>Davey, J. W., Cezard, T., Fuentes-Utrilla, P., Eland, C., Gharbi, K., & Blaxter, M. L. (2013). Special features of RAD Sequencing data: Implications for genotyping. Molecular Ecology, 22(11), 3151-3164.</Citation></Reference><Reference><Citation>DePristo, M. A., Banks, E., Poplin, R., Garimella, K. V., Maguire, J. R., Hartl, C., … Daly, M. J. (2011). A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genetics, 43(5), 491-498.</Citation></Reference><Reference><Citation>Emerson, K. J., Merz, C. R., Catchen, J. M., Hohenlohe, P. A., Cresko, W. A., Bradshaw, W. E., & Holzapfel, C. M. (2010). Resolving postglacial phylogeography using high-throughput sequencing. Proceedings of the National Academy of Sciences of the United States of America, 107(37), 16196-16200.</Citation></Reference><Reference><Citation>Euclid, P. T., McKinney, G. J., Bootsma, M., Tarsa, C., Meek, M. H., & Larson, W. A. (2020). Attack of the PCR clones: Rates of clonality have little effect on RAD-seq genotype calls. Molecular Ecology Resources, 20(1), 66-78. (in press).</Citation></Reference><Reference><Citation>Fumagalli, M., Vieira, F. G., Linderoth, T., & Nielsen, R. (2014). ngsTools: Methods for population genetics analyses from next-generation sequencing data. Bioinformatics, 30(10), 1486-1487.</Citation></Reference><Reference><Citation>Gautier, M., Gharbi, K., Cezard, T., Foucaud, J., Kerdelhué, C., Pudlo, P., … Estoup, A. (2013). The effect of RAD allele dropout on the estimation of genetic variation within and between populations. Molecular Ecology, 22(11), 3165-3178.</Citation></Reference><Reference><Citation>Gompert, Z., Lucas, L. K., Alex Buerkle, C., Forister, M. L., Fordyce, J. A., & Nice, C. C. (2014). Admixture and the organization of genetic diversity in a butterfly species complex revealed through common and rare genetic variants. Molecular Ecology, 23(18), 4555-4573.</Citation></Reference><Reference><Citation>Hoffman, J. I., Simpson, F., David, P., Rijks, J. M., Kuiken, T., Thorne, M. A. S., … Dasmahapatra, K. K. (2014). High-throughput sequencing reveals inbreeding depression in a natural population. Proceedings of the National Academy of Sciences, 111(10), 3775-3780.</Citation></Reference><Reference><Citation>Jørsboe, E., Hanghøj, K., & Albrechtsen, A. (2017). fastNGSadmix: Admixture proportions and principal component analysis of a single NGS sample. Bioinformatics, 33(19), 3148-3150.</Citation></Reference><Reference><Citation>Kersten, B., Faivre Rampant, P., Mader, M., Le Paslier, M.-C., Bounon, R., Berard, A., … Fladung, M. (2016). Genome sequences of Populus tremula chloroplast and mitochondrion: Implications for holistic poplar breeding. PLoS ONE, 11(1), e0147209.</Citation></Reference><Reference><Citation>Korneliussen, T. S., Albrechtsen, A., & Nielsen, R. (2014). ANGSD: Analysis of next generation sequencing data. BMC Bioinformatics, 15, 356.</Citation></Reference><Reference><Citation>Kousathanas, A., Leuenberger, C., Link, V., Sell, C., Burger, J., & Wegmann, D. (2017). Inferring heterozygosity from ancient and low coverage genomes. Genetics, 205(1), 317-332.</Citation></Reference><Reference><Citation>Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357-359.</Citation></Reference><Reference><Citation>Leaché, A. D., Chavez, A. S., Jones, L. N., Grummer, J. A., Gottscho, A. D., & Linkem, C. W. (2015). Phylogenomics of phrynosomatid lizards: Conflicting signals from sequence capture versus restriction site associated DNA sequencing. Genome Biology and Evolution, 7(3), 706-719.</Citation></Reference><Reference><Citation>Li, H. (2013). Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv, 1303.3997.</Citation></Reference><Reference><Citation>Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., & Homer, N., … 1000 Genome Project Data Processing Subgroup (2009). The sequence alignment/map format and SAMtools. Bioinformatics, 25(16), 2078-2079.</Citation></Reference><Reference><Citation>Lindtke, D., Buerkle, C. A., Barbará, T., Heinze, B., Castiglione, S., Bartha, D., & Lexer, C. (2012). Recombinant hybrids retain heterozygosity at many loci: New insights into the genomics of reproductive isolation in Populus. Molecular Ecology, 21(20), 5042-5058.</Citation></Reference><Reference><Citation>Lindtke, D., Gompert, Z., Lexer, C., & Buerkle, C. A. (2014). Unexpected ancestry of Populus seedlings from a hybrid zone implies a large role for postzygotic selection in the maintenance of species. Molecular Ecology, 23(17), 4316-4330.</Citation></Reference><Reference><Citation>Link, V., Kousathanas, A., Veeramah, K., Sell, C., Scheu, A., & Wegmann, D. (2017). ATLAS: Analysis Tools for Low-depth and Ancient Samples. https://doi.org/10.1101/105346</Citation></Reference><Reference><Citation>Luca, F., Hudson, R. R., Witonsky, D. B., & Di Rienzo, A. (2011). A reduced representation approach to population genetic analyses and applications to human evolution. Genome Research, 21(7), 1087-1098.</Citation></Reference><Reference><Citation>Macaya-Sanz, D., Suter, L., Joseph, J., Barbará, T., Alba, N., González-Martínez, S. C., … Lexer, C. (2011). Genetic analysis of post-mating reproductive barriers in hybridizing European Populus species. Heredity, 107(5), 478-486.</Citation></Reference><Reference><Citation>Marques, D. A., Lucek, K., Meier, J. I., Mwaiko, S., Wagner, C. E., Excoffier, L., & Seehausen, O. (2016). Genomics of rapid incipient speciation in sympatric threespine stickleback. PLOS Genetics, 12(2), e1005887.</Citation></Reference><Reference><Citation>Mastretta-Yanes, A., Arrigo, N., Alvarez, N., Jorgensen, T. H., Piñero, D., & Emerson, B. C. (2015). Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference. Molecular Ecology Resources, 15(1), 28-41.</Citation></Reference><Reference><Citation>Miller, M. R., Dunham, J. P., Amores, A., Cresko, W. A., & Johnson, E. A. (2007). Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome Research, 17(2), 240-248.</Citation></Reference><Reference><Citation>Nadeau, N. J., Ruiz, M., Salazar, P., Counterman, B., Medina, J. A., Ortiz-Zuazaga, H., … Papa, R. (2014). Population genomics of parallel hybrid zones in the mimetic butterflies, H. melpomene and H. erato. Genome Research, 24(8), 1316-1333.</Citation></Reference><Reference><Citation>Narum, S. R., Buerkle, C. A., Davey, J. W., Miller, M. R., & Hohenlohe, P. A. (2013). Genotyping-by-sequencing in ecological and conservation genomics. Molecular Ecology, 22(11), 2841-2847.</Citation></Reference><Reference><Citation>Nielsen, R., Paul, J. S., Albrechtsen, A., & Song, Y. S. (2011). Genotype and SNP calling from next-generation sequencing data. Nature Reviews Genetics, 12(6), 443-451.</Citation></Reference><Reference><Citation>Peterson, B. K., Weber, J. N., Kay, E. H., Fisher, H. S., & Hoekstra, H. E. (2012). Double digest RADseq: An inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS ONE, 7(5), e37135.</Citation></Reference><Reference><Citation>Pootakham, W., Sonthirod, C., Naktang, C., Jomchai, N., Sangsrakru, D., & Tangphatsornruang, S. (2016). Effects of methylation-sensitive enzymes on the enrichment of genic SNPs and the degree of genome complexity reduction in a two-enzyme genotyping-by-sequencing (GBS) approach: A case study in oil palm (Elaeis guineensis). Molecular Breeding, 36(11), 154.</Citation></Reference><Reference><Citation>Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics, 155(2), 945-959.</Citation></Reference><Reference><Citation>Puritz, J. B., Matz, M. V., Toonen, R. J., Weber, J. N., Bolnick, D. I., & Bird, C. E. (2014). Demystifying the RAD fad. Molecular Ecology, 23(24), 5937-5942.</Citation></Reference><Reference><Citation>Roshyara, N. R., & Scholz, M. (2014). fcGENE: A versatile tool for processing and transforming SNP datasets. PLoS ONE, 9(7), e97589.</Citation></Reference><Reference><Citation>Rowe, H. C., Renaut, S., & Guggisberg, A. (2011). RAD in the realm of next-generation sequencing technologies. Molecular Ecology, 20(17), 3499-3502.</Citation></Reference><Reference><Citation>Rustagi, N., Zhou, A., Watkins, W. S., Gedvilaite, E., Wang, S., Ramesh, N., … Xing, J. (2017). Extremely low-coverage whole genome sequencing in South Asians captures population genomics information. BMC Genomics, 18(1), 396.</Citation></Reference><Reference><Citation>Sambrook, J., & Russell, D. W. (2006). Fragmentation of DNA by sonication. Cold Spring Harbor Protocols, 2006(23), pdb.prot4538-pdb.prot4538.</Citation></Reference><Reference><Citation>Scheet, P., & Stephens, M. (2006). A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotypic phase. American Journal of Human Genetics, 78(4), 629-644.</Citation></Reference><Reference><Citation>Schweyen, H., Rozenberg, A., & Leese, F. (2014). Detection and removal of PCR duplicates in population genomic ddRAD studies by addition of a degenerate base region (DBR) in sequencing adapters. The Biological Bulletin, 227(2), 146-160.</Citation></Reference><Reference><Citation>Smeds, L., & Künstner, A. (2011). ConDeTri - A content dependent read trimmer for illumina data. PLoS ONE, 6(10), e26314.</Citation></Reference><Reference><Citation>Stölting, K. N., Nipper, R., Lindtke, D., Caseys, C., Waeber, S., Castiglione, S., & Lexer, C. (2013). Genomic scan for single nucleotide polymorphisms reveals patterns of divergence and gene flow between ecologically divergent species. Molecular Ecology, 22(3), 842-855.</Citation></Reference><Reference><Citation>Toonen, R. J., Puritz, J. B., Forsman, Z. H., Whitney, J. L., Fernandez-Silva, I., Andrews, K. R., & Bird, C. E. (2013). ezRAD: A simplified method for genomic genotyping in non-model organisms. PeerJ, 1, e203.</Citation></Reference><Reference><Citation>Tuskan, G. A., Difazio, S., Jansson, S., Bohlmann, J., Grigoriev, I., Hellsten, U., … Rokhsar, D. (2006). The genome of black cottonwood, Populus trichocarpa (Torr. & Gray). Science, 313(5793), 1596-1604.</Citation></Reference><Reference><Citation>Wall, J. D., Tang, L. F., Zerbe, B., Kvale, M. N., Kwok, P.-Y., Schaefer, C., & Risch, N. (2014). Estimating genotype error rates from high-coverage next-generation sequence data. Genome Research, 24(11), 1734-1739.</Citation></Reference><Reference><Citation>Wang, S., Meyer, E., McKay, J. K., & Matz, M. V. (2012). 2b-RAD: A simple and flexible method for genome-wide genotyping. Nature Methods, 9(8), 808-810.</Citation></Reference><Reference><Citation>Wegmann, D., Kessner, D. E., Veeramah, K. R., Mathias, R. A., Nicolae, D. L., Yanek, L. R., … Novembre, J. (2011). Recombination rates in admixed individuals identified by ancestry-based inference. Nature Genetics, 43(9), 847-853.</Citation></Reference><Reference><Citation>Wright, S. (1931). Evolution in Mendelian populations. Genetics, 16(2), 97-159.</Citation></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Autriche</li><li>Suisse</li><li>États-Unis</li></country><region><li>Canton de Fribourg</li><li>Vienne (Autriche)</li><li>Wyoming</li></region><settlement><li>Fribourg</li><li>Vienne (Autriche)</li></settlement><orgName><li>Université de Fribourg</li></orgName></list><tree><country name="Suisse"><region name="Canton de Fribourg"><name sortKey="Bresadola, Luisa" sort="Bresadola, Luisa" uniqKey="Bresadola L" first="Luisa" last="Bresadola">Luisa Bresadola</name></region><name sortKey="Link, Vivian" sort="Link, Vivian" uniqKey="Link V" first="Vivian" last="Link">Vivian Link</name><name sortKey="Link, Vivian" sort="Link, Vivian" uniqKey="Link V" first="Vivian" last="Link">Vivian Link</name><name sortKey="Wegmann, Daniel" sort="Wegmann, Daniel" uniqKey="Wegmann D" first="Daniel" last="Wegmann">Daniel Wegmann</name><name sortKey="Wegmann, Daniel" sort="Wegmann, Daniel" uniqKey="Wegmann D" first="Daniel" last="Wegmann">Daniel Wegmann</name></country><country name="États-Unis"><region name="Wyoming"><name sortKey="Buerkle, C Alex" sort="Buerkle, C Alex" uniqKey="Buerkle C" first="C Alex" last="Buerkle">C Alex Buerkle</name></region></country><country name="Autriche"><region name="Vienne (Autriche)"><name sortKey="Lexer, Christian" sort="Lexer, Christian" uniqKey="Lexer C" first="Christian" last="Lexer">Christian Lexer</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Bois/explor/PoplarV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000422 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000422 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Bois
|area= PoplarV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:32142201
|texte= Estimating and accounting for genotyping errors in RAD-seq experiments.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:32142201" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a PoplarV1
| This area was generated with Dilib version V0.6.37. |  |