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
SWU12882SWU12882genetic_marker
SWU12884SWU12884genetic_marker
SWU12887SWU12887genetic_marker
SWU12897SWU12897genetic_marker
SWU12909SWU12909genetic_marker
SWU12962SWU12962genetic_marker
SWU12967SWU12967genetic_marker
SWU12969SWU12969genetic_marker
SWU13009SWU13009genetic_marker
SWU13032SWU13032genetic_marker
SWU13047SWU13047genetic_marker
SWU13083SWU13083genetic_marker
SWU13257SWU13257genetic_marker
SWU13265SWU13265genetic_marker
SWU13267SWU13267genetic_marker
SWU13279SWU13279genetic_marker
SWU13492SWU13492genetic_marker
SWU13669SWU13669genetic_marker
SWU13681SWU13681genetic_marker
SWU13712SWU13712genetic_marker
SWU13744SWU13744genetic_marker
SWU13745SWU13745genetic_marker
SWU13749SWU13749genetic_marker
SWU13755SWU13755genetic_marker
SWU13758SWU13758genetic_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