| Cotton is one of the most important cash crops in the world.The agronomic trait,fiber quality trait and yield trait are three important categories of traits for cotton and it is the main goal for cotton breeders to improve them for a long time.But the three categories of traits especially yield trait and fiber quality traits are quantitative traits,which are controlled by multiple genes and influenced greatly by environment.In the previous reports,lots of researches about analyzing the correlation between fiber quality traits and yield traits and identifying QTLs for these traits have been published in cotton.But there were no report about combining them to explain the genetic basis of corelation between fiber quality traits and yield traits.In our research,a RIL population harbored 196 lines,developed with two parents of upland cotton 0-153 and sGK9708,was used to analyze the agronomic traits(plant height and branch number)across seven environments and the yield trait and fiber quality traits across 22 environments.The results showed the transgressive segregation for most of the eight traits.The absolute values of skewness of all the traits were less than one and showed normal distribution in the all environments.For correlation analysis,there was no correlation between the plant height and the branch number;high or medium significant positive correlation between fiber strength and fiber length,fiber strength and seed index,fiber length and seed index,micronaire and boll weight,boll weight and seed index;high or medium significant negative correlation between fiber strength and micronaire,fiber length and micronaire,fiber strength and lint percentage,fiber length and lint percentage,lint percentage and seed index;and low or no significant correlation between micronaire and lint percentage,fiber strength and boll weight,fiber length and boll weight,micronaire and seed index,and boll weight and lint percentage.Combining these results,all the seven environments for agronomic traits and 17 of the 22 environments for fiber quality and yield traits could be used for QTL identification.A genetic map was constructed by SNP markers discovered by SLAF-Seq with this population.This map harbored 5521 SNP markers,spanned the total genetic distance of 3259.37 cM and avenge genetic distance of 0.78 cM between adjust markers.By adding the SNP markers developed by cotton 70 K chip and SSR markers,a consensus genetic map of upland cotton was also constructed.This map harbored 8295 markers,spanned the total genetic distance of 5197.17 cM and avenge genetic distance of 0.63 cM between adjust markers.This consensus genetic map covered the whole genome of upland cotton with high saturation and is a valuable tool for QTL and candidate gene identification,functional characterization,and pyramiding breeding across the whole genome.Using the SLAF-SNP map and phenotype data of agronomic traits,a total of 68 QTLs for plant height and branch number were identified,of which 17 were detected in at least two environments and could be considered as stable ones(nine for plant height and eight for branch number);using the consensus map and phenotype data of fiber quality and yield traits,a total of 983 QTLs were identified,of which 198 were detected in at least three environments and could be considered as stable ones(33 for fiber strength,35 for fiber length,32 for micronaire,42 for boll weight,28 for lint percentage,and 37 for seed index).Therefore,this study identified the greatest number of stable QTLs for fiber quality and yield traits.These results could provide more information about the genetic mechanisms underlying cotton fiber development and provide important loci related to the improvement of both cotton fiber quality and yield.In our research,37 QTL clusters were identified and harbored 59 paired-trait QTL clusters for the fiber yield and quality traits;28(47.5%)showed the same QTL additive effect direction(positive or negative),and 31(52.5%)showed the opposite QTL additive effect directions(positive and negative).Five paired traits(FS and FL,FS and SI,FL and SI,FM and BW,and BW and SI)showed significant medium or high positive correlations in most environments;27 paired-trait QTL clusters were identified for these traits.Except for two of the paired-trait QTL clusters between FM and BW and SI and BW,the other 25 paired-trait QTL clusters(92.8%)showed the same QTL additive effect directions(positive or negative),especially the 14 QTL clusters identified between FS and FL;five paired traits(FS and FM,FS and LP,FL and FM,FL and LP,and LP and SI)showed significant medium or high negative correlations in most environments,and 16 paired-trait QTL clusters were identified for these traits,all of which(100%)showed opposite QTL additive effect directions(positive and negative);five paired traits(FM and LP,FS and BW,FL and BW,FM and SI,and BW and LP)showed no or weak positive or negative correlations in most environments and 16 paired-trait QTL clusters were identified for these traits.Some of them showed same QTL additive effect directions(positive or negative)and the others showed opposite QTL additive effect directions(positive and negative).There were a total of 1297 candidate genes that located in the confidence intervals of QTL Clusters.Combing two RNA-Seq data for cotton fiber development and cotton tissue,414 genes were found being expressed in two transcriptome data(FPKM>10).There were 63 genes related to “cell wall” in GO database,15 related to “Starch and sucrose metabolism” in KEGG database,28 related to “Cell wall/membrane/envelope biogenesis” in KOG database.Combined all this results and the previous studies,23 of all the genes in the confidence intervals of QTL clusters were the promising candidate genes.In three sub-species of Gossypium,there were total 179 GATA transcript factors.Among them,46 were in Gossypium raimondii,46 in Gossypium arboreum,and 87 in Gossypium hirsutum.The 179 GATA transcript factors were divided into four subfamilies,each containing 75,52,32,and 20 respectively.Total 11 GATA transcript factors were expressed during cotton fiber development in G.hirsutum,21 expressed in G.arboretum and 12 expressed in G.raimondiiThis whole genome genetic mapping could be a powerful complementary strategy to dissect the genetic basis of complex traits and their genetic correlations in cotton.In addition to providing new insights into the genetic basis of the traits related to fiber quality and yield and their relationships,this study also provided information about improving cotton fiber quality and yield simultaneously. |
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