Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistan...Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.展开更多
The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL ...The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.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
The development of wheat cultivars with improved nitrogen(N),phosphorus(P),and potassium(K)use efficiency is essential for sustainable agriculture.Genetic dissection and identification of causative genes underlying nu...The development of wheat cultivars with improved nitrogen(N),phosphorus(P),and potassium(K)use efficiency is essential for sustainable agriculture.Genetic dissection and identification of causative genes underlying nutrient use efficiency represent a key strategy toward this goal.We conducted an extensive genome-wide association study(GWAS)using a panel of 431 wheat cultivars,identifying 1,659 significant single-nucleotide polymorphisms(SNPs)(LOD>5)through genotyping-by-sequencing.This analysis revealed 534 quantitative trait loci(QTLs)associated with 12 nutrient use efficiency traits across five distinct environments,among which 14 QTLs were consistently detected in at least three environments.Notably,meta-QTL analysis,showed that QTL80(72.12–74.24 Mb,chr2A),QTL387(32.88–33.56 Mb,chr6A),and QTL500(535.53–540.80 Mb,chr7B)exhibit clear co-localization with MQTL-2A-2,MQTL-6A-1,and MQTL-7B-2,respectively.This overlap highlights their robustness across diverse environmental conditions.Within these regions,critical candidate genes-including members of the bZIP transcription factor family and a potassium transporter gene-were identified in relation to nutrient use efficiency.Furthermore,a novel locus,QTL234,was discovered,harboring key candidate genes such as dof zinc finger protein,Ankyrin repeat family protein,and cytochrome P450.To validate the SNP within QTL234 associated with nitrogen harvest index(NHI),we developed a dCAPS marker for AX-109095537.These findings demonstrate the effectiveness of high-resolution SNP-based GWAS in rapidly pinpointing promising candidate genes.They also establish a foundation for large-scale QTL fine mapping,candidate gene validation,and the development of functional markers essential for enhancing nutrient use efficiency in wheat breeding programs.展开更多
Despite the longstanding importance of silage as a critical feed source for ruminants,its quality improvement has been largely overlooked.Although numerous quantitative trait loci(QTL)and genes affecting silage qualit...Despite the longstanding importance of silage as a critical feed source for ruminants,its quality improvement has been largely overlooked.Although numerous quantitative trait loci(QTL)and genes affecting silage quality in maize have been reported,only a few have been effectively incorporated into breeding programs.Addressing this gap,the present study undertook a comprehensive meta-QTL(MQTL)analysis involving 523 QTL associated with silage-quality traits collected from 14 published studies.Of the 523 QTL,405 were projected onto a consensus map comprising 62,424 genetic markers,resulting in the identification of 60 MQTL and eight singletons.The average confidence interval(CI)of the MQTL was 3.9-fold smaller than that of the source QTL.Nine of the 60 identified MQTL were classified as breeder’s MQTL owing to their small CIs,involvement of more QTL,and large contribution to phenotypic variation.One-third of the MQTL co-localized with DNA marker-trait associations identified in previous genomewide association mapping studies.A set of 78 high-confidence candidate genes influencing silage quality were identified in the MQTL regions.These genes and associated markers may advance marker-assisted breeding for maize silage quality.展开更多
基金supported by the National Key R&D Program,Intergovernmental Key Items for International Scientific and Technological Innovation Cooperation(2018YFE0107700)the National Natural Science Foundation of China(31771772)+2 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX19_2109)the National Key R&D Program for Breeding of Top-seven Crops(2017YFD0100801)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。
摘要Fusarium head blight(FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike(type Ⅱ resistance) and to mycotoxin accumulation in infected kernel(type Ⅲ resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL(mQTL)that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using metaanalysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL(gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL(hcmQTL) were selected from the reference sequence-based mQTL(smQTL).Locus-specific single nucleotide polymorphism(SNP) and simple sequence repeat(SSR) markers and17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.
基金supported by Indian Council of Agricultural Research(ICAR),New Delhi for assistance.
摘要The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.
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).
摘要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.
基金funded by the National Key R&D Program of China(2021YFD1900700)。
摘要The development of wheat cultivars with improved nitrogen(N),phosphorus(P),and potassium(K)use efficiency is essential for sustainable agriculture.Genetic dissection and identification of causative genes underlying nutrient use efficiency represent a key strategy toward this goal.We conducted an extensive genome-wide association study(GWAS)using a panel of 431 wheat cultivars,identifying 1,659 significant single-nucleotide polymorphisms(SNPs)(LOD>5)through genotyping-by-sequencing.This analysis revealed 534 quantitative trait loci(QTLs)associated with 12 nutrient use efficiency traits across five distinct environments,among which 14 QTLs were consistently detected in at least three environments.Notably,meta-QTL analysis,showed that QTL80(72.12–74.24 Mb,chr2A),QTL387(32.88–33.56 Mb,chr6A),and QTL500(535.53–540.80 Mb,chr7B)exhibit clear co-localization with MQTL-2A-2,MQTL-6A-1,and MQTL-7B-2,respectively.This overlap highlights their robustness across diverse environmental conditions.Within these regions,critical candidate genes-including members of the bZIP transcription factor family and a potassium transporter gene-were identified in relation to nutrient use efficiency.Furthermore,a novel locus,QTL234,was discovered,harboring key candidate genes such as dof zinc finger protein,Ankyrin repeat family protein,and cytochrome P450.To validate the SNP within QTL234 associated with nitrogen harvest index(NHI),we developed a dCAPS marker for AX-109095537.These findings demonstrate the effectiveness of high-resolution SNP-based GWAS in rapidly pinpointing promising candidate genes.They also establish a foundation for large-scale QTL fine mapping,candidate gene validation,and the development of functional markers essential for enhancing nutrient use efficiency in wheat breeding programs.
摘要Despite the longstanding importance of silage as a critical feed source for ruminants,its quality improvement has been largely overlooked.Although numerous quantitative trait loci(QTL)and genes affecting silage quality in maize have been reported,only a few have been effectively incorporated into breeding programs.Addressing this gap,the present study undertook a comprehensive meta-QTL(MQTL)analysis involving 523 QTL associated with silage-quality traits collected from 14 published studies.Of the 523 QTL,405 were projected onto a consensus map comprising 62,424 genetic markers,resulting in the identification of 60 MQTL and eight singletons.The average confidence interval(CI)of the MQTL was 3.9-fold smaller than that of the source QTL.Nine of the 60 identified MQTL were classified as breeder’s MQTL owing to their small CIs,involvement of more QTL,and large contribution to phenotypic variation.One-third of the MQTL co-localized with DNA marker-trait associations identified in previous genomewide association mapping studies.A set of 78 high-confidence candidate genes influencing silage quality were identified in the MQTL regions.These genes and associated markers may advance marker-assisted breeding for maize silage quality.