Construction of a high-density genetic map and identification of QTLs related to agronomic and physiological traits in an interspecific (Gossypium hirsutum × Gossypium barbadense) F2 population.
BMC Genomics
; 23(1): 307, 2022 Apr 15.
Article
em En
| MEDLINE
| ID: mdl-35428176
ABSTRACT
BACKGROUND:
Advances in genome sequencing technology, particularly restriction-site associated DNA sequence (RAD-seq) and whole-genome resequencing, have greatly aided the construction of cotton interspecific genetic maps based on single nucleotide polymorphism (SNPs), Indels, and other types of markers. High-density genetic maps can improve accuracy of quantitative trait locus (QTL) mapping, narrow down location intervals, and facilitate identification of the candidate genes.RESULT:
In this study, 249 individuals from an interspecific F2 population (TM-1 and Hai7124) were re-sequenced, yielding 6303 high-confidence bin markers spanning 5057.13 cM across 26 cotton chromosomes. A total of 3380 recombination hot regions RHRs were identified which unevenly distributed on the 26 chromosomes. Based on this map, 112 QTLs relating to agronomic and physiological traits from seedling to boll opening stage were identified, including 15 loci associated with 14 traits that contained genes harboring nonsynonymous SNPs. We analyzed the sequence and expression of these ten candidate genes and discovered that GhRHD3 (GH_D10G0500) may affect fiber yield while GhGPAT6 (GH_D04G1426) may affect photosynthesis efficiency.CONCLUSION:
Our research illustrates the efficiency of constructing a genetic map using binmap and QTL mapping on the basis of a certain size of the early-generation population. High-density genetic map features high recombination exchanges in number and distribution. The QTLs and the candidate genes identified based on this high-density genetic map may provide important gene resources for the genetic improvement of cotton.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Gossypium
/
Locos de Características Quantitativas
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article