| Literature DB >> 31201519 |
Yuzhen Shi1, Aiying Liu1, Junwen Li1, Jinfa Zhang2, Baocai Zhang1, Qun Ge1, Muhammad Jamshed1, Quanwei Lu1, Shaoqi Li1, Xianghui Xiang1, Juwu Gong1, Wankui Gong1, Haihong Shang1, Xiaoying Deng1, Jingtao Pan1, Youlu Yuan3.
Abstract
Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC1F1, BC1S1, BC2F1, and BC3F0) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC1F1, BC1S1, BC2F1 and BC3F0 populations in the field and from the BC2F1 population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC1F1 population. These QTLs were located on 24 chromosomes, and each could explain 4.98-19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.Entities:
Keywords: Fiber quality; Interspecific backcross populations; QTL cluster; Quantitative trait locus (QTL); Yield
Mesh:
Year: 2019 PMID: 31201519 DOI: 10.1007/s00438-019-01582-8
Source DB: PubMed Journal: Mol Genet Genomics ISSN: 1617-4623 Impact factor: 3.291