Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we de...Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we developed a genome-wide scanning plus machine learning framework,integrated with advanced computational techniques,to propose a novel algorithm named Fast3VmrMLM.This algo-rithm aims to enhance the identification of abundant and key genes for polygenic traits in the era of big data and artificial intelligence.The algorithm was extended to identify haplotype(Fast3VmrMLM-Hap)and molecular(Fast3VmrMLM-mQTL)variants.In simulation studies,Fast3VmrMLM outperformed existing methods in detecting dominant,small,and rare variants,requiring only 3.30 and 5.43 h(20 threads)to analyze the 18K rice and UK Biobank-scale datasets,respectively.Fast3VmrMLM identified more known(211)and candidate(384)genes for 14 traits in the 18K rice dataset than FarmCPU(100 known genes).Additionally,it identified 26 known and 24 candidate genes for seven yield-related traits in a maize NC II design;Fast3VmrMLM-mQTL identified two known soybean genes near structural variants.We demonstrated that this novel two-step framework outperformed genome-wide scanning alone.In breeding by design,a genetic network constructed via machine learning using all known and candidate genes identified in this study revealed 21 key genes associated with rice yield-related traits.All associated markers yielded high prediction accuracies in rice(0.7443)and maize(0.8492),en-abling the development of superior hybrid combinations.A new breeding-by-design strategy based on the identified key genes was also proposed.This study provides an effective method for gene mining and breeding by design.展开更多
Southern corn rust(SCR),caused by the fungal pathogen Puccinia polysora,is a major threat to maize pro-duction worldwide.Efficient breeding and deployment of resistant hybrids are key to achieving durable control of S...Southern corn rust(SCR),caused by the fungal pathogen Puccinia polysora,is a major threat to maize pro-duction worldwide.Efficient breeding and deployment of resistant hybrids are key to achieving durable control of SCR.Here,we report the molecular cloning and characterization of RppC,which encodes an NLR-type immune receptor and is responsible for a major SCR resistance quantitative trait locus.Further-more,we identified the corresponding avirulence effector,AvrRppC,which is secreted by P.polysora and triggers RppC-mediated resistance.Allelic variation of AvrRppC directly determines the effectiveness of RppC-mediated resistance,indicating that monitoring of AvrRppC variants in the field can guide the rational deployment of RppC-containing hybrids in maize production.Currently,RppC is the most frequently deployed SCR resistance gene in China,and a better understanding of its mode of action is crit-ical for extending its durability.展开更多
Artemisia annua is the main natural source of artemisinin production.In A.annua,extended drought stress severely reduces its biomass and artemisinin production while short-term water-withholding or abscisic acid(ABA)t...Artemisia annua is the main natural source of artemisinin production.In A.annua,extended drought stress severely reduces its biomass and artemisinin production while short-term water-withholding or abscisic acid(ABA)treatment can increase artemisinin biosynthesis.ABA-responsive transcription factor AabZIP1 and JA signaling AaMYC2 have been shown in separate studies to promote artemisinin production by targeting several artemisinin biosynthesis genes.Here,we found AabZIP1 promote the expression of multiple artemisinin biosynthesis genes including AaDBR2 and AaALDH1,which AabZIP1 does not directly activate.Subsequently,it was found that AabZIP1 up-regulates AaMYC2expression through direct binding to its promoter,and that AaMYC2 binds to the promoter of AaALDH1to activate its transcription.In addition,AabZIP1 directly transactivates wax biosynthesis genes AaCER1and AaCYP86A1.The biosynthesis of artemisinin and cuticular wax and the tolerance of drought stress were significantly increased by AabZIP1 overexpression,whereas they were significantly decreased in RNAi-AabZIP1 plants.Collectively,we have uncovered the AabZIP1-AaMYC2 transcriptional module as a point of cross-talk between ABA and JA signaling in artemisinin biosynthesis,which may have general implications.We have also identified AabZIP1 as a promising candidate gene for the development of A.annua plants with high artemisinin content and drought tolerance in metabolic engineering breeding.展开更多
基金supported by the National Natural Science Foundation of China,China(32470657 and 32270673).
文摘Genetic dissection and breeding by design for polygenic traits remain substantial challenges.To ad-dress these challenges,it is important to identify as many genes as possible,including key regulatory genes.Here,we developed a genome-wide scanning plus machine learning framework,integrated with advanced computational techniques,to propose a novel algorithm named Fast3VmrMLM.This algo-rithm aims to enhance the identification of abundant and key genes for polygenic traits in the era of big data and artificial intelligence.The algorithm was extended to identify haplotype(Fast3VmrMLM-Hap)and molecular(Fast3VmrMLM-mQTL)variants.In simulation studies,Fast3VmrMLM outperformed existing methods in detecting dominant,small,and rare variants,requiring only 3.30 and 5.43 h(20 threads)to analyze the 18K rice and UK Biobank-scale datasets,respectively.Fast3VmrMLM identified more known(211)and candidate(384)genes for 14 traits in the 18K rice dataset than FarmCPU(100 known genes).Additionally,it identified 26 known and 24 candidate genes for seven yield-related traits in a maize NC II design;Fast3VmrMLM-mQTL identified two known soybean genes near structural variants.We demonstrated that this novel two-step framework outperformed genome-wide scanning alone.In breeding by design,a genetic network constructed via machine learning using all known and candidate genes identified in this study revealed 21 key genes associated with rice yield-related traits.All associated markers yielded high prediction accuracies in rice(0.7443)and maize(0.8492),en-abling the development of superior hybrid combinations.A new breeding-by-design strategy based on the identified key genes was also proposed.This study provides an effective method for gene mining and breeding by design.
基金supported by grants from the National Key Research and Development Program of China(2021YFF1000302)the National Natural Science Foundation of China(31901550)+2 种基金the Ministry of Science and Technology of China(2016YFD0101803)the National Natural Science Foundation of China(31501326)Innovative Talents in Colleges and Universities of Henan Province(19HASTIT010)was a funding pro-vided by Henan Province government of China.
文摘Southern corn rust(SCR),caused by the fungal pathogen Puccinia polysora,is a major threat to maize pro-duction worldwide.Efficient breeding and deployment of resistant hybrids are key to achieving durable control of SCR.Here,we report the molecular cloning and characterization of RppC,which encodes an NLR-type immune receptor and is responsible for a major SCR resistance quantitative trait locus.Further-more,we identified the corresponding avirulence effector,AvrRppC,which is secreted by P.polysora and triggers RppC-mediated resistance.Allelic variation of AvrRppC directly determines the effectiveness of RppC-mediated resistance,indicating that monitoring of AvrRppC variants in the field can guide the rational deployment of RppC-containing hybrids in maize production.Currently,RppC is the most frequently deployed SCR resistance gene in China,and a better understanding of its mode of action is crit-ical for extending its durability.
基金financially supported by the NSFC project(81973420 and 81803660)the National Key Research and Development Project(2019YFE0108700,China)+1 种基金the Natural Science Foundation of Chongqing(cstc2018jcyj AX0328,China)the Science Funding of Sichuan Province(2020YJ0171,China)。
文摘Artemisia annua is the main natural source of artemisinin production.In A.annua,extended drought stress severely reduces its biomass and artemisinin production while short-term water-withholding or abscisic acid(ABA)treatment can increase artemisinin biosynthesis.ABA-responsive transcription factor AabZIP1 and JA signaling AaMYC2 have been shown in separate studies to promote artemisinin production by targeting several artemisinin biosynthesis genes.Here,we found AabZIP1 promote the expression of multiple artemisinin biosynthesis genes including AaDBR2 and AaALDH1,which AabZIP1 does not directly activate.Subsequently,it was found that AabZIP1 up-regulates AaMYC2expression through direct binding to its promoter,and that AaMYC2 binds to the promoter of AaALDH1to activate its transcription.In addition,AabZIP1 directly transactivates wax biosynthesis genes AaCER1and AaCYP86A1.The biosynthesis of artemisinin and cuticular wax and the tolerance of drought stress were significantly increased by AabZIP1 overexpression,whereas they were significantly decreased in RNAi-AabZIP1 plants.Collectively,we have uncovered the AabZIP1-AaMYC2 transcriptional module as a point of cross-talk between ABA and JA signaling in artemisinin biosynthesis,which may have general implications.We have also identified AabZIP1 as a promising candidate gene for the development of A.annua plants with high artemisinin content and drought tolerance in metabolic engineering breeding.
