Single-cell RNA sequencing(scRNA-seq)technology enables a deep understanding of cellular differentiation during plant development and reveals heterogeneity among the cells of a given tissue.However,the computational c...Single-cell RNA sequencing(scRNA-seq)technology enables a deep understanding of cellular differentiation during plant development and reveals heterogeneity among the cells of a given tissue.However,the computational characterization of such cellular heterogeneity is complicated by the high dimensionality,sparsity,and biological noise inherent to the raw data.Here,we introduce PhytoCluster,an unsupervised deep learning algorithm,to cluster scRNA-seq data by extracting latent features.We benchmarked PhytoCluster against four simulated datasets and five real scRNA-seq datasets with varying protocols and data quality levels.A comprehensive evaluation indicated that PhytoCluster outperforms other methods in clustering accuracy,noise removal,and signal retention.Additionally,we evaluated the performance of the latent features extracted by PhytoCluster across four machine learning models.The computational results highlight the ability of PhytoCluster to extract meaningful information from plant scRNA-seq data,with machine learning models achieving accuracy comparable to that of raw features.We believe that PhytoCluster will be a valuable tool for disentangling complex cellular heterogeneity based on scRNA-seq data.展开更多
Modern cultivated rice plays a pivotal role in global food security.China accounts for nearly 30%of the world’s rice production and has developed numerous cultivated varieties over the past decades that are well adap...Modern cultivated rice plays a pivotal role in global food security.China accounts for nearly 30%of the world’s rice production and has developed numerous cultivated varieties over the past decades that are well adapted to diverse growing regions.However,the genomic bases underlying the phenotypes of these modern cultivars remain poorly characterized,limiting the exploitation of this vast resource for breeding specialized,regionally adapted cultivars.In this study,we constructed a comprehensive genetic variation map of modern rice using resequencing datasets from 6044 representative cultivars from five major ricegrowing regions in China.Our genomic and phenotypic analyses of this diversity panel revealed regional preferences for specific genomic backgrounds and traits,such as heading date,biotic/abiotic stress resistance,and grain shape,which are crucial for adaptation to local conditions and consumer preferences.We identified 3131 quantitative trait loci associated with 53 phenotypes across 212 datasets under various environmental conditions through genome-wide association studies.Notably,we cloned and functionally verified a novel gene related to grain length,OsGL3.6.By integrating multiple datasets,we developed RiceAtlas,a versatile multi-scale toolkit for rice breeding design.We successfully utilized the RiceAtlas breeding design function to rapidly improve the grain shape of the Suigeng4 cultivar.These valuable resources enhance our understanding of the adaptability and breeding requirements of modern rice and can facilitate advances in future rice-breeding initiatives.展开更多
The Dong people are one of China’s 55 recognized ethnic minorities,but there has been a long-standing debate about their origins.In this study,we performed whole-genome resequencing of Kam Sweet Rice(KSR),a valuable,...The Dong people are one of China’s 55 recognized ethnic minorities,but there has been a long-standing debate about their origins.In this study,we performed whole-genome resequencing of Kam Sweet Rice(KSR),a valuable,rare,and ancient rice landrace unique to the Dong people.Through comparative genomic analyses of KSR and other rice landraces from south of the Yangtze River Basin in China,we provide evidence that the ancestors of the Dong people likely originated from the southeast coast of China at least 1000 years ago.Alien introgression and admixture in KSR demonstrated multiple migration events in the history of the Dong people.Genomic footprints of domestication demonstrated characteristics of KSR that arose from artificial selection and geographical adaptation by the Dong people.The key genes GS3,Hd1,and DPS1(related to agronomic traits)and LTG1 and MYBS3(related to cold tolerance)were identified as domestication targets,reflecting crop improvement and changes in the geographical environment of the Dong people during migration.A genome-wide association study revealed a candidate yield-associated gene,Os01g0923300,a specific haplotype in KSR that is important for regulating grain number per panicle.RNA-sequencing and quantitative reverse transcription-PCR results showed that this gene was more highly expressed in KSR than in ancestral populations,indicating that it may have great value in increasing yield potential in other rice accessions.In summary,our work develops a novel approach for studying human civilization and migration patterns and provides valuable genomic datasets and resources for future breeding of high-yield and climate-resilient rice varieties.展开更多
Hybridization between Xian/indica(XI)and Geng/japonica(GJ)rice combined with utilization of plant ideotypes has greatly contributed to yield improvements in modern GJ rice in China over the past 50 years.To explore th...Hybridization between Xian/indica(XI)and Geng/japonica(GJ)rice combined with utilization of plant ideotypes has greatly contributed to yield improvements in modern GJ rice in China over the past 50 years.To explore the genomic basis of improved yield and disease resistance in GJ rice,we conducted a large-scale genomic landscape analysis of 816 elite GJ cultivars representing multiple eras of germplasm from China.We detected consistently increasing introgressions from three XI subpopulations into GJ cultivars since the 1980s and found that the XI genome introgressions significantly increased the grain number per panicle(GN)and decreased the panicle number per plant.This contributed to the improvement of plant type during modern breeding,changing multi-tiller plants tomoderate tiller plants with a large panicle size and increasing the blast resistance.Notably,we found that key gene haplotypes controlling plant architecture,yield components,and pest and disease resistance,including IPA1,SMG1,DEP3,Pib,Pi-d2,and Bph3,were introduced from XI rice by introgression.By GWAS analysis,we detected a GN-related gene Gnd5,which had been consistently introgressed from XI into GJ cultivars since the 1980s.Gnd5 is a GRAS transcription factor gene,and Gnd5 knockout mutants showed a significant reduction in GN.The estimated genetic effects of genes varied among different breeding locations,which explained the distinct introgression levels of XI gene haplotypes,including Gnd5,DEP3,etc.,to these GJ breeding pedigrees.These findings reveal the genomic contributions of introgressions from XI to the trait improvements of GJ rice cultivars and provide new insights for future rice genomic breeding.展开更多
基金supported by the National Natural Science Foundation of China(32371996 and 62372158)the National Key R&D Program of China(2022YFF0711802)+1 种基金the STI 2030-Major Projects(2022ZD04017)the National Key Research and Development Program of China(2019YFA0802202 and 2020YFA0803401).
文摘Single-cell RNA sequencing(scRNA-seq)technology enables a deep understanding of cellular differentiation during plant development and reveals heterogeneity among the cells of a given tissue.However,the computational characterization of such cellular heterogeneity is complicated by the high dimensionality,sparsity,and biological noise inherent to the raw data.Here,we introduce PhytoCluster,an unsupervised deep learning algorithm,to cluster scRNA-seq data by extracting latent features.We benchmarked PhytoCluster against four simulated datasets and five real scRNA-seq datasets with varying protocols and data quality levels.A comprehensive evaluation indicated that PhytoCluster outperforms other methods in clustering accuracy,noise removal,and signal retention.Additionally,we evaluated the performance of the latent features extracted by PhytoCluster across four machine learning models.The computational results highlight the ability of PhytoCluster to extract meaningful information from plant scRNA-seq data,with machine learning models achieving accuracy comparable to that of raw features.We believe that PhytoCluster will be a valuable tool for disentangling complex cellular heterogeneity based on scRNA-seq data.
基金supported by the National Key Research and Development Program of China(2021YFD1200500)the Biological Breeding-National Science and Technology Major Project(2022ZD04017)+2 种基金the Biological Breeding-Major Projects(2023ZD04076)the National Natural Science Foundation of China(32371996)the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences.
文摘Modern cultivated rice plays a pivotal role in global food security.China accounts for nearly 30%of the world’s rice production and has developed numerous cultivated varieties over the past decades that are well adapted to diverse growing regions.However,the genomic bases underlying the phenotypes of these modern cultivars remain poorly characterized,limiting the exploitation of this vast resource for breeding specialized,regionally adapted cultivars.In this study,we constructed a comprehensive genetic variation map of modern rice using resequencing datasets from 6044 representative cultivars from five major ricegrowing regions in China.Our genomic and phenotypic analyses of this diversity panel revealed regional preferences for specific genomic backgrounds and traits,such as heading date,biotic/abiotic stress resistance,and grain shape,which are crucial for adaptation to local conditions and consumer preferences.We identified 3131 quantitative trait loci associated with 53 phenotypes across 212 datasets under various environmental conditions through genome-wide association studies.Notably,we cloned and functionally verified a novel gene related to grain length,OsGL3.6.By integrating multiple datasets,we developed RiceAtlas,a versatile multi-scale toolkit for rice breeding design.We successfully utilized the RiceAtlas breeding design function to rapidly improve the grain shape of the Suigeng4 cultivar.These valuable resources enhance our understanding of the adaptability and breeding requirements of modern rice and can facilitate advances in future rice-breeding initiatives.
基金supported by the National Key Research and Development Program of China(2021YFD1200500)the National Natural Science Foundation of China(31901487)+2 种基金the CAAS Science and Technology Innovation Program,the Protective Program of Crop Germplasm of China(19200385-1)the Third National Survey and Collection Action on Crop Germplasm Resource(19210859,19210860)the National Crop Germplasm Resources Center(NCGRC-2021-02).
文摘The Dong people are one of China’s 55 recognized ethnic minorities,but there has been a long-standing debate about their origins.In this study,we performed whole-genome resequencing of Kam Sweet Rice(KSR),a valuable,rare,and ancient rice landrace unique to the Dong people.Through comparative genomic analyses of KSR and other rice landraces from south of the Yangtze River Basin in China,we provide evidence that the ancestors of the Dong people likely originated from the southeast coast of China at least 1000 years ago.Alien introgression and admixture in KSR demonstrated multiple migration events in the history of the Dong people.Genomic footprints of domestication demonstrated characteristics of KSR that arose from artificial selection and geographical adaptation by the Dong people.The key genes GS3,Hd1,and DPS1(related to agronomic traits)and LTG1 and MYBS3(related to cold tolerance)were identified as domestication targets,reflecting crop improvement and changes in the geographical environment of the Dong people during migration.A genome-wide association study revealed a candidate yield-associated gene,Os01g0923300,a specific haplotype in KSR that is important for regulating grain number per panicle.RNA-sequencing and quantitative reverse transcription-PCR results showed that this gene was more highly expressed in KSR than in ancestral populations,indicating that it may have great value in increasing yield potential in other rice accessions.In summary,our work develops a novel approach for studying human civilization and migration patterns and provides valuable genomic datasets and resources for future breeding of high-yield and climate-resilient rice varieties.
基金This work was supported by the National Key Research and Development Program of China(2021YFD1200500 and 2016YFD0100101)National Key Research and Development Program of China(2016YFD0100801 and 2017YFA0503800)+3 种基金CAAS Science and Technology Innovation Pro-gram,Protective Program of Crop Germplasm of China(19200385-1)Third National Survey And Collection Action On Crop Germplasm Resource(19210859 and 19210860)National Crop Germplasm Re-sources Center(NCGRC-2021-02)Project of Sanya Yazhou Bay Sci-ence and Technology City(SKJC-2020-02-001)。
文摘Hybridization between Xian/indica(XI)and Geng/japonica(GJ)rice combined with utilization of plant ideotypes has greatly contributed to yield improvements in modern GJ rice in China over the past 50 years.To explore the genomic basis of improved yield and disease resistance in GJ rice,we conducted a large-scale genomic landscape analysis of 816 elite GJ cultivars representing multiple eras of germplasm from China.We detected consistently increasing introgressions from three XI subpopulations into GJ cultivars since the 1980s and found that the XI genome introgressions significantly increased the grain number per panicle(GN)and decreased the panicle number per plant.This contributed to the improvement of plant type during modern breeding,changing multi-tiller plants tomoderate tiller plants with a large panicle size and increasing the blast resistance.Notably,we found that key gene haplotypes controlling plant architecture,yield components,and pest and disease resistance,including IPA1,SMG1,DEP3,Pib,Pi-d2,and Bph3,were introduced from XI rice by introgression.By GWAS analysis,we detected a GN-related gene Gnd5,which had been consistently introgressed from XI into GJ cultivars since the 1980s.Gnd5 is a GRAS transcription factor gene,and Gnd5 knockout mutants showed a significant reduction in GN.The estimated genetic effects of genes varied among different breeding locations,which explained the distinct introgression levels of XI gene haplotypes,including Gnd5,DEP3,etc.,to these GJ breeding pedigrees.These findings reveal the genomic contributions of introgressions from XI to the trait improvements of GJ rice cultivars and provide new insights for future rice genomic breeding.
