Agronomic traits in maize(Zea mays L.)are complex and modulated by pleiotropic loci and interconnected genetic networks.However,the traditional single-trait genome-wide association study(GWAS)method often misses genet...Agronomic traits in maize(Zea mays L.)are complex and modulated by pleiotropic loci and interconnected genetic networks.However,the traditional single-trait genome-wide association study(GWAS)method often misses genetic associations among traits,overlooks pleiotropic effects,and underestimates shared regulatory mechanisms.In the current study,we employed multi-trait analysis of GWAS(MTAG)and constructed a genetic network to dissect the genetic architecture of 18 agronomic traits across a genetically diverse panel of 2,448 maize inbred lines.Incorporating MTAG significantly improved the detection of pleiotropic loci that had not been detected by single-trait GWAS.Using a genetic network,we uncovered numerous previously unrecognized connections among traits related to plant architecture,yield,and flowering time.The 49 detected hub nodes,including Zm00001d028840 and Zm00001d033859(knotted1),influence multiple traits.Co-expression analysis of candidate genes across two developmental stages validated their distinct yet complementary roles,with Zm00001d028840 linked to early cell wall remodeling and Zm00001d033849 involved in chromatin remodeling during tasseling.Moreover,we integrated results from GWAS,MTAG,and genetic network analyses to prioritize pleiotropic loci and hub genes that regulate multiple agronomic traits.This integrative approach offers a practical framework for selecting stable,multi-trait-associated targets,thereby supporting more precise and efficient crop improvement strategies.展开更多
With the increasing number of sequenced species,phylogenetic profiling(PP)has become a powerful method to predict functional genes based on co-evolutionary information.However,its potential in plant genomics has not y...With the increasing number of sequenced species,phylogenetic profiling(PP)has become a powerful method to predict functional genes based on co-evolutionary information.However,its potential in plant genomics has not yet been fully explored.In this context,we combined the power of machine learning and PP to identify salt stress-related genes in a halophytic grass,Spartina alterniflora,using evolutionary information generated from 365 plant species.Our results showed that the genes highly co-evolved with known salt stress-related genes are enriched in biological processes of ion transport,detoxification and metabolic pathways.For ion transport,five identified genes coding two sodium and three potassium transporters were validated to be able to uptake Na?.In addition,we identified two orthologs of trichome-related AtR3-MYB genes,SaCPC1 and SaCPC2,which may be involved in salinity responses.Genes co-evolved with SaCPCs were enriched in functions related to the circadian rhythm and abiotic stress responses.Overall,this work demonstrates the feasibility of mining salt stress-related genes using evolutionary information,highlighting the potential of PP as a valuable tool for plant functional genomics.展开更多
基金supported by the National Key R&D Program of China(2022ZD0115703)the Hainan Provincial Natural Science Foundation of China(725QN518)+1 种基金the project of Sanya Yazhou Bay Science and Technology City(SKIC-JYRC-2024-55)the Agricultural Science and Technology Innovation Program(CAAS-CSIAF-202303).
文摘Agronomic traits in maize(Zea mays L.)are complex and modulated by pleiotropic loci and interconnected genetic networks.However,the traditional single-trait genome-wide association study(GWAS)method often misses genetic associations among traits,overlooks pleiotropic effects,and underestimates shared regulatory mechanisms.In the current study,we employed multi-trait analysis of GWAS(MTAG)and constructed a genetic network to dissect the genetic architecture of 18 agronomic traits across a genetically diverse panel of 2,448 maize inbred lines.Incorporating MTAG significantly improved the detection of pleiotropic loci that had not been detected by single-trait GWAS.Using a genetic network,we uncovered numerous previously unrecognized connections among traits related to plant architecture,yield,and flowering time.The 49 detected hub nodes,including Zm00001d028840 and Zm00001d033859(knotted1),influence multiple traits.Co-expression analysis of candidate genes across two developmental stages validated their distinct yet complementary roles,with Zm00001d028840 linked to early cell wall remodeling and Zm00001d033849 involved in chromatin remodeling during tasseling.Moreover,we integrated results from GWAS,MTAG,and genetic network analyses to prioritize pleiotropic loci and hub genes that regulate multiple agronomic traits.This integrative approach offers a practical framework for selecting stable,multi-trait-associated targets,thereby supporting more precise and efficient crop improvement strategies.
基金supported by the National Key R&D Program of China(2022YFF0711802)the Nanfan special project of the Chinese Academy of Agricultural Sciences(ZDXM2309)+1 种基金the National Natural Science Foundation of China(32022064)the Innovation Program of the Chinese Academy of Agricultural Sciences,the Alibaba Foundation,and the High-performance Computing Platform of YZBSTCACC.
文摘With the increasing number of sequenced species,phylogenetic profiling(PP)has become a powerful method to predict functional genes based on co-evolutionary information.However,its potential in plant genomics has not yet been fully explored.In this context,we combined the power of machine learning and PP to identify salt stress-related genes in a halophytic grass,Spartina alterniflora,using evolutionary information generated from 365 plant species.Our results showed that the genes highly co-evolved with known salt stress-related genes are enriched in biological processes of ion transport,detoxification and metabolic pathways.For ion transport,five identified genes coding two sodium and three potassium transporters were validated to be able to uptake Na?.In addition,we identified two orthologs of trichome-related AtR3-MYB genes,SaCPC1 and SaCPC2,which may be involved in salinity responses.Genes co-evolved with SaCPCs were enriched in functions related to the circadian rhythm and abiotic stress responses.Overall,this work demonstrates the feasibility of mining salt stress-related genes using evolutionary information,highlighting the potential of PP as a valuable tool for plant functional genomics.
