Common wheat(Triticum aestivum L.)is a leading cereal crop,but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and mai...Common wheat(Triticum aestivum L.)is a leading cereal crop,but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize.The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets.Meanwhile,the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals.One such productive avenue is combining metabolomics approaches with genetic designs.However,this trial is not as widespread as that for sequencing technologies,especially when the acquisition,understanding,and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized.In this review,we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes.Considerable progress has been made in delivering improved varieties,suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and,as such,this procedure could serve as an-omics-informed roadmap for executing similar improvement strategies in wheat and other species.展开更多
Maize flowering is an important agronomic character,which is controlled by quantitative trait loci(QTL).Over the years,a large number of flowering-related QTL have been found in maize and exist in public databases.How...Maize flowering is an important agronomic character,which is controlled by quantitative trait loci(QTL).Over the years,a large number of flowering-related QTL have been found in maize and exist in public databases.However,combining these data,re-analyzing and mining candidate loci and fine mapping of flowering-related traits to reduce confidence intervals has become a hot issue in maize.In this study,the QTL of 6 important agronomic traits of maize flowering were collected from 15 published articles,including flowering period(DA),Days to tasseling(DTT),Days to silking(DS),Days to pollen shedding(DTP),anthesis-silking interval(ASI)and the photosensitive(PS).Through meta-analysis,622 QTL were integrated into 26 meta-QTLs(MQTL).Finally,the candidate genes related to maize flowering(Gene IDs:ZM00001D005791,ZM00001D019045,ZM00001D050697,ZM00001D011139)were identified by Gene Ontology(GO)enrichment and hierarchical cluster analysis of expression profile.Based on the results of this study,the genetic characteristics of maize flowering traits will be further analyzed,which is of great significance to guide the improvement of important agronomic characters and improve the efficiency of breeding.展开更多
基金supported by the National Natural Science Foundation of China(91935304,31770328,and 32001541)the Huazhong Agricultural University Scientific&Technological Self-Innovation Foundation(2017RC006)+1 种基金the China Postdoctoral Science Foundation(2018M642866 and 2021T140246)the Hubei Provincial Natural Science Foundation(2020CFB149).
文摘Common wheat(Triticum aestivum L.)is a leading cereal crop,but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize.The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets.Meanwhile,the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals.One such productive avenue is combining metabolomics approaches with genetic designs.However,this trial is not as widespread as that for sequencing technologies,especially when the acquisition,understanding,and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized.In this review,we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes.Considerable progress has been made in delivering improved varieties,suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and,as such,this procedure could serve as an-omics-informed roadmap for executing similar improvement strategies in wheat and other species.
基金Science and Technology Project of Jilin Provincial Department of Education[JJKH20210351KJ,JJKH20210346KJ]Jilin Province Science and Technology Development Plan Project[20200402023NC]。
文摘Maize flowering is an important agronomic character,which is controlled by quantitative trait loci(QTL).Over the years,a large number of flowering-related QTL have been found in maize and exist in public databases.However,combining these data,re-analyzing and mining candidate loci and fine mapping of flowering-related traits to reduce confidence intervals has become a hot issue in maize.In this study,the QTL of 6 important agronomic traits of maize flowering were collected from 15 published articles,including flowering period(DA),Days to tasseling(DTT),Days to silking(DS),Days to pollen shedding(DTP),anthesis-silking interval(ASI)and the photosensitive(PS).Through meta-analysis,622 QTL were integrated into 26 meta-QTLs(MQTL).Finally,the candidate genes related to maize flowering(Gene IDs:ZM00001D005791,ZM00001D019045,ZM00001D050697,ZM00001D011139)were identified by Gene Ontology(GO)enrichment and hierarchical cluster analysis of expression profile.Based on the results of this study,the genetic characteristics of maize flowering traits will be further analyzed,which is of great significance to guide the improvement of important agronomic characters and improve the efficiency of breeding.
