Background:Soil salt stress seriously restricts the yield and quality of cotton worldwide.To investigate the molecular mechanism of cotton response to salt stress,a main cultivated variety Gossypium hirsutum L.acc.Xin...Background:Soil salt stress seriously restricts the yield and quality of cotton worldwide.To investigate the molecular mechanism of cotton response to salt stress,a main cultivated variety Gossypium hirsutum L.acc.Xinluzhong 54 was used to perform transcriptome and proteome integrated analysis.Results:Through transcriptome analysis in cotton leaves under salt stress for 0 h(T0),3 h(T3)and 12 h(T12),we identified 8436,11628 and 6311 differentially expressed genes(DEGs)in T3 vs.T0,T12 vs.T0 and T12 vs.T3,respectively.A total of 459 differentially expressed proteins(DEPs)were identified by proteomic analysis,of which 273,99 and 260 DEPs were identified in T3 vs.T0,T12 vs.T0 and T12 vs.T3,respectively.Metabolic pathways,biosynthesis of secondary metabolites,photosynthesis and plant hormone signal transduction were enriched among the identified DEGs or DEPs.Detail analysis of the DEGs or DEPs revealed that complex signaling pathways,such as abscisic acid(ABA)and jasmonic acid(JA)signaling,calcium signaling,mitogen-activated protein kinase(MAPK)signaling cascade,transcription factors,activation of antioxidant and ion transporters,were participated in regulating salt response in cotton.Conclusions:Our research not only contributed to understand the mechanism of cotton response to salt stress,but also identified nine candidate genes,which might be useful for molecular breeding to improve salt-toleranee in cotton.展开更多
Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL i...Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL intervals,significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.Results:In our study,884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1,as a result,74 meta-QTLs were identified,including 19 meta-QTLs for fiber length;18 meta-QTLs for fiber strength;11 meta-QTLs for fiber uniformity;11 meta-QTLs for fiber elongation;and 15 meta-QTLs for micronaire.Combined with 8589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies,297 candidate genes were identified in the meta-QTL intervals,20 of which showed high expression levels specifically in the developing fibers.According to the function annotations,some of the 20 key candidate genes are associated with the fiber development.Conclusions:This study provides not only stable QTLs used for marker-assisted selection,but also candidate genes to uncover the molecular mechanisms for cotton fiber development.展开更多
基金This work was supported by National R&D Project of Transgenic Crops of Ministry of Science and Technology of China(2016ZX08005–004-002).
文摘Background:Soil salt stress seriously restricts the yield and quality of cotton worldwide.To investigate the molecular mechanism of cotton response to salt stress,a main cultivated variety Gossypium hirsutum L.acc.Xinluzhong 54 was used to perform transcriptome and proteome integrated analysis.Results:Through transcriptome analysis in cotton leaves under salt stress for 0 h(T0),3 h(T3)and 12 h(T12),we identified 8436,11628 and 6311 differentially expressed genes(DEGs)in T3 vs.T0,T12 vs.T0 and T12 vs.T3,respectively.A total of 459 differentially expressed proteins(DEPs)were identified by proteomic analysis,of which 273,99 and 260 DEPs were identified in T3 vs.T0,T12 vs.T0 and T12 vs.T3,respectively.Metabolic pathways,biosynthesis of secondary metabolites,photosynthesis and plant hormone signal transduction were enriched among the identified DEGs or DEPs.Detail analysis of the DEGs or DEPs revealed that complex signaling pathways,such as abscisic acid(ABA)and jasmonic acid(JA)signaling,calcium signaling,mitogen-activated protein kinase(MAPK)signaling cascade,transcription factors,activation of antioxidant and ion transporters,were participated in regulating salt response in cotton.Conclusions:Our research not only contributed to understand the mechanism of cotton response to salt stress,but also identified nine candidate genes,which might be useful for molecular breeding to improve salt-toleranee in cotton.
基金This work was supported by the National Natural Science Foundation of China(31760402)Public Welfare Research Projects in the Autonomous Region(KY2019002)Special Programs for New Varieties Cultivation of Shihezi University(YZZX201701).
文摘Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL intervals,significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.Results:In our study,884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1,as a result,74 meta-QTLs were identified,including 19 meta-QTLs for fiber length;18 meta-QTLs for fiber strength;11 meta-QTLs for fiber uniformity;11 meta-QTLs for fiber elongation;and 15 meta-QTLs for micronaire.Combined with 8589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies,297 candidate genes were identified in the meta-QTL intervals,20 of which showed high expression levels specifically in the developing fibers.According to the function annotations,some of the 20 key candidate genes are associated with the fiber development.Conclusions:This study provides not only stable QTLs used for marker-assisted selection,but also candidate genes to uncover the molecular mechanisms for cotton fiber development.
