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
SWU18673SWU18673genetic_marker
SWU18674SWU18674genetic_marker
SWU18694SWU18694genetic_marker
SWU18696SWU18696genetic_marker
SWU18853SWU18853genetic_marker
SWU18880SWU18880genetic_marker
SWU18919SWU18919genetic_marker
SWU18923SWU18923genetic_marker
SWU18933SWU18933genetic_marker
SWU18938SWU18938genetic_marker
SWU18939SWU18939genetic_marker
SWU18942SWU18942genetic_marker
SWU18945SWU18945genetic_marker
SWU18951SWU18951genetic_marker
SWU18959SWU18959genetic_marker
SWU18985SWU18985genetic_marker
SWU19004SWU19004genetic_marker
SWU19005SWU19005genetic_marker
SWU19010SWU19010genetic_marker
SWU19012SWU19012genetic_marker
SWU19017SWU19017genetic_marker
SWU19021SWU19021genetic_marker
SWU19034SWU19034genetic_marker
SWU19078SWU19078genetic_marker
SWU19222SWU19222genetic_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