Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.)

Publication Overview
TitleEnriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.)
AuthorsLiu X, Teng Z, Wang J, Wu T, Zhang Z, Deng X, Fang X, Tan Z, Ali I, Liu D, Zhang J, Liu D, Liu F, Zhang Z
TypeJournal Article
Journal NameMolecular genetics and genomics : MGG
Year2017
CitationLiu X, Teng Z, Wang J, Wu T, Zhang Z, Deng X, Fang X, Tan Z, Ali I, Liu D, Zhang J, Liu D, Liu F, Zhang Z. Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.). Molecular genetics and genomics : MGG. 2017 Jul 21.

Abstract

Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.

Features
This publication contains information about 706 features:
Feature NameUniquenameType
SWU17088SWU17088genetic_marker
SWU17108SWU17108genetic_marker
SWU17110SWU17110genetic_marker
SWU17164SWU17164genetic_marker
SWU17218SWU17218genetic_marker
SWU17233SWU17233genetic_marker
SWU17234SWU17234genetic_marker
SWU17238SWU17238genetic_marker
SWU17239SWU17239genetic_marker
SWU17251SWU17251genetic_marker
SWU17254SWU17254genetic_marker
SWU17257SWU17257genetic_marker
SWU17261SWU17261genetic_marker
SWU17270SWU17270genetic_marker
SWU17328SWU17328genetic_marker
SWU17335SWU17335genetic_marker
SWU17336SWU17336genetic_marker
SWU17342SWU17342genetic_marker
SWU17343SWU17343genetic_marker
SWU17349SWU17349genetic_marker
SWU17350SWU17350genetic_marker
SWU17353SWU17353genetic_marker
SWU17405SWU17405genetic_marker
SWU17414SWU17414genetic_marker
SWU17418SWU17418genetic_marker

Pages

Projects
This publication contains information about 1 projects:
Project NameDescription
CY-RIL-2017
Properties
Additional details for this publication include:
Property NameValue
ISSN1617-4623
Publication ModelPrint-Electronic
eISSN1617-4623
Publication Date2017 Jul 21
Journal AbbreviationMol. Genet. Genomics
DOI10.1007/s00438-017-1347-8
Elocation10.1007/s00438-017-1347-8
LanguageEnglish
Language Abbreng
Publication TypeJournal Article
Journal CountryGermany