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dc.contributor.authorLee, Jonghoon
dc.contributor.authorIzzah, Nur K.
dc.contributor.authorJayakodi, Murukarthick
dc.contributor.authorPerumal, Sampath
dc.contributor.authorJoh, Ho J.
dc.contributor.authorLee, Hyeon J.
dc.contributor.authorLee, Sang-Choon
dc.contributor.authorPark, Jee Y.
dc.contributor.authorYang, Ki-Woung
dc.contributor.authorNou, Il-Sup
dc.contributor.authorSeo, Joodeok
dc.contributor.authorYoo, Jaeheung
dc.contributor.authorSuh, Youngdeok
dc.contributor.authorAhn, Kyounggu
dc.contributor.authorLee, Ji Hyun
dc.contributor.authorChoi, Gyung Ja
dc.contributor.authorYu, Yeisoo
dc.contributor.authorKim, Heebal
dc.contributor.authorYang, Tae-Jin
dc.date.accessioned2016-05-20T09:03:31Z
dc.date.available2016-05-20T09:03:31Z
dc.date.issued2015en
dc.identifier.citationLee et al. BMC Plant Biology (2015) 15:32 DOI 10.1186/s12870-015-0424-6en
dc.identifier.doi10.1186/s12870-015-0424-6en
dc.identifier.urihttp://hdl.handle.net/10150/610296
dc.description.abstractBACKGROUND: Black rot is a destructive bacterial disease causing large yield and quality losses in Brassica oleracea. To detect quantitative trait loci (QTL) for black rot resistance, we performed whole-genome resequencing of two cabbage parental lines and genome-wide SNP identification using the recently published B. oleracea genome sequences as reference. RESULTS: Approximately 11.5 Gb of sequencing data was produced from each parental line. Reference genome-guided mapping and SNP calling revealed 674,521 SNPs between the two cabbage lines, with an average of one SNP per 662.5 bp. Among 167 dCAPS markers derived from candidate SNPs, 117 (70.1%) were validated as bona fide SNPs showing polymorphism between the parental lines. We then improved the resolution of a previous genetic map by adding 103 markers including 87 SNP-based dCAPS markers. The new map composed of 368 markers and covers 1467.3 cM with an average interval of 3.88 cM between adjacent markers. We evaluated black rot resistance in the mapping population in three independent inoculation tests using F₂:₃ progenies and identified one major QTL and three minor QTLs. CONCLUSION: We report successful utilization of whole-genome resequencing for large-scale SNP identification and development of molecular markers for genetic map construction. In addition, we identified novel QTLs for black rot resistance. The high-density genetic map will promote QTL analysis for other important agricultural traits and marker-assisted breeding of B. oleracea.
dc.language.isoenen
dc.publisherBioMed Central Ltden
dc.relation.urlhttp://www.biomedcentral.com/1471-2229/15/32en
dc.rights© 2015 Lee et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0).en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCabbageen
dc.subjectWhole-genome resequencingen
dc.subjectGenetic linkage mapen
dc.subjectBlack roten
dc.subjectQTLen
dc.titleGenome-wide SNP identification and QTL mapping for black rot resistance in cabbageen
dc.typeArticleen
dc.identifier.eissn1471-2229en
dc.contributor.departmentDepartment of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National Universityen
dc.contributor.departmentIndonesian Researcg Institute for Industrial and Beverage Crops (IRIIBC), Pakuwonen
dc.contributor.departmentDepartment of Horticulture, Sunchon National Universityen
dc.contributor.departmentJoeun Seeden
dc.contributor.departmentResearch Center for Biobased Chemistry, Korea Research Institute of Chemical Technologyen
dc.contributor.departmentArizona Genomics Institute, School of Plant Sciences, University of Arizonaen
dc.contributor.departmentDepartment of Agricultural Biotechnology, Seoul National Universityen
dc.contributor.departmentCHO & KIM genomics, Seoul National University Mt.4-2en
dc.identifier.journalBMC Plant Biologyen
dc.description.collectioninformationThis item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-08-20T03:58:15Z
html.description.abstractBACKGROUND: Black rot is a destructive bacterial disease causing large yield and quality losses in Brassica oleracea. To detect quantitative trait loci (QTL) for black rot resistance, we performed whole-genome resequencing of two cabbage parental lines and genome-wide SNP identification using the recently published B. oleracea genome sequences as reference. RESULTS: Approximately 11.5 Gb of sequencing data was produced from each parental line. Reference genome-guided mapping and SNP calling revealed 674,521 SNPs between the two cabbage lines, with an average of one SNP per 662.5 bp. Among 167 dCAPS markers derived from candidate SNPs, 117 (70.1%) were validated as bona fide SNPs showing polymorphism between the parental lines. We then improved the resolution of a previous genetic map by adding 103 markers including 87 SNP-based dCAPS markers. The new map composed of 368 markers and covers 1467.3 cM with an average interval of 3.88 cM between adjacent markers. We evaluated black rot resistance in the mapping population in three independent inoculation tests using F₂:₃ progenies and identified one major QTL and three minor QTLs. CONCLUSION: We report successful utilization of whole-genome resequencing for large-scale SNP identification and development of molecular markers for genetic map construction. In addition, we identified novel QTLs for black rot resistance. The high-density genetic map will promote QTL analysis for other important agricultural traits and marker-assisted breeding of B. oleracea.


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© 2015 Lee et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0).
Except where otherwise noted, this item's license is described as © 2015 Lee et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0).