QTL Mapping Of Salt Tolerance,Fiber Quality And Yield Related Traits In An Intra-Specific F_2:3 Upland Cotton

Over 6%of agricultural land is affected by salinity.It is becoming obligatory to use saline soils,so growing salt-tolerant plants is a priority.To gain an understanding of the genetic basis of upland cotton tolerance to salinity at seedling stage,an intra-specific cross was developed from CCRI 35,tolerant to salinity,as female with Nan Dan（NH）,sensitive to salinity,as the male.A genetic map of 5178 SNP markers were developed from 277 F_2:3:3 populations.The map spanned 4768.098 cM,with an average distance of 0.92 cM.A total of 66 QTLs for 10 traits related to salinity were detected in three environments（0,110,and 150 mM salt treatment）.Only 14 QTLs were consistent,accounting for2.72%to 9.87%of phenotypic variation.Parental contributions were found to be in the ratio of 3:1,10QTLs from the sensitive and four QTLs from the resistant parent.Five QTLs were located in A_t and nine QTLs in the D_t sub-genome.Moreover,eight clusters were identified,in which 12 putative key genes were found to be related to salinity.The GBS-SNPs-based genetic map developed is the first high-density genetic map that has the potential to provide deeper insights into upland cotton salinity tolerance.The 12 key genes found in this study could be used for QTL fine mapping and cloning for further studies.Fiber quality and yield improvement are crucial for cotton domestication and breeding.With the transformation in spinning techniques and multiplicity needs,the development of cotton fiber quality and yield is of great importance.A genetic map of 5178 Single Nucleotide Polymorphism（SNP）markers were generated using 277 F_2:3 population,from an intra-specific cross between two upland cotton accessions,CCRI 35 a high fiber quality as female and Nan Dan Ba Di Da Hua（NH）,with good yield properties as male parent.The map spanned 4768.098 cM with an average distance of 0.92 cM.A total of 110 Quantitative Traits Loci（QTLs）were identified for 11 traits,but only 30 QTLs were consistent in at least two environments.The highest percentage of phenotypic variance explained by a single QTL was 15.45%.Two major cluster regions were found,cluster 1（chromosome17-D03）and cluster 2（chromosome26-D12）.Five candidate genes were identified in the two QTL cluster regions.Based on GO functional annotation,all the genes were highly correlated with fiber development,with functions such as protein kinase and phosphorylation.The five genes were associated with various fiber traits as follows:Gh_D03G0889 linked to qFM-D03_cb,Gh_D12G0093,Gh_D12G0410,Gh_D12G0435 associated with q FS-D12_cb and Gh_D12G0969 linked to qFY-D12_cb.Further structural annotation and fine mapping are needed to determine the specific role played by the five identified genes in fiber quality and yield related pathway.