生物
数量性状位点
遗传学
候选基因
遗传连锁
基于家系的QTL定位
人口
基因座(遗传学)
等位基因
基因定位
基因
SNP公司
多基因
主基因
SNP阵列
连锁不平衡
包含复合区间映射
性状
遗传建筑学
遗传力
遗传标记
表型
粳稻
关联映射
染色体区
遗传关联
进化生物学
选择性育种
遗传变异
全基因组关联研究
作者
Fenfei Liang,Zhiru Yang,Wei Liu,Faling Zhang,Xia Liang,Cheng Zhao,Guosong Zhang
出处
期刊:Genomics
[Elsevier BV]
日期:2025-11-01
卷期号:117 (6): 111157-111157
标识
DOI:10.1016/j.ygeno.2025.111157
摘要
The Chinese longsnout catfish (Leiocassis longirostris) is an important freshwater aquaculture species, and the selective breeding of fast-growth and hypoxia tolerance population will have a positive impact on its industry. In order to promote the breeding process of Chinese longsnout catfish, construction of the genetic linkage map and identification of molecular markers associated with fast-growth and hypoxia tolerance is critical for the marker-assisted selection (MAS) of Chinese longsnout catfish. In the present study, whole-genome resequencing was used to construct a high-density genetic linkage map of the Chinese longsnout catfish. The map containing 2946 bin markers was distributed over 26 linkage groups (LGs) with a total genetic coverage of 1980.76 cM and an average density of 0.67 cM. Based on the genetic map, quantitative trait locus (QTL) mapping results suggested that 17 QTLs associated with growth traits and 1 QTL associated with hypoxia tolerance were identified in eight LGs with the phenotypic variability explained (PVE) ranged from 5.1 % to 9.3 %. Four SNP loci from these QTLs were associated with the phenotypic traits validated by Kompetitive Allele Specific PCR or Sanger sequencing. In addition, the expression of three candidate genes for growth traits and five candidate genes for hypoxia tolerance was examined in different growth speed populations and the process of hypoxia exposure and reoxygenation, respectively. The high-density genetic linkage map and QTLs for growth traits and hypoxia tolerance obtained in the present study could further provide the basis for genetic breeding and molecular marker-assisted breeding of Chinese longsnout catfish.
科研通智能强力驱动
Strongly Powered by AbleSci AI