Soybean seeds contain approximately 40% protein,making soybeans an important source of plant-based protein.Research on QTN mapping,molecular design breeding and mining of genes related to seed protein formation provid...Soybean seeds contain approximately 40% protein,making soybeans an important source of plant-based protein.Research on QTN mapping,molecular design breeding and mining of genes related to seed protein formation provides guiding significance for the analysis of the underlying genetic mechanisms of seed protein formation and the selection of high-protein varieties.The seed protein contents(SPCs)of 144 lines of a soybean four-way recombinant inbred line(FW-RIL)population were determined in 8 environments.A three-variance component multisite random effects mixed linear model(3VmrMLM)was used to conduct a genome-wide association study on protein content.A single detected QTN explained 0.53%-3.37% of the phenotypic variation.A molecular-assisted selection breeding model containing the18 QTNs explained 51.97% of the phenotypic variation in protein content.Eight biparental and five triparental crosses that produced excellent lines with the greatest protein content-related genotype values that could be generated by phenotypic and molecular-assisted selection were screened.An LD block of 17QTNs(QEIs)was identified,and one key candidate gene related to protein formation was predicted by haplotype analysis.The proportion of Hap 1 varieties in the spring-sowing soybean region in North China was lower than those in the Huang-Huai-Hai soybean region in Central China and the multiripe soybean region in South China.The proportion of Hap 1 varieties among the wild varieties and landraces was greater than that among the improved varieties.The results of this study provide important insights into the genetic basis of soybean protein content and information to aid in molecular design breeding methods to improve protein content.展开更多
The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This...The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This era integrates biotechnology,artificial intelligence(AI),and big data information technology.In contrast,China is still in a transition period between stages 2.0 and 3.0,which primarily relies on conventional selection and molecular breeding.In the context of increasingly complex international situations,accurately identifying core issues in China's seed industry innovation and seizing the frontier of international seed technology are strategically important.These efforts are essential for ensuring food security and revitalizing the seed industry.This paper systematically analyzes the characteristics of crop breeding data from artificial selection to intelligent design breeding.It explores the applications and development trends of AI and big data in modern crop breeding from several key perspectives.These include highthroughput phenotype acquisition and analysis,multiomics big data database and management system construction,AI-based multiomics integrated analysis,and the development of intelligent breeding software tools based on biological big data and AI technology.Based on an in-depth analysis of the current status and challenges of China's seed industry technology development,we propose strategic goals and key tasks for China's new generation of AI and big data-driven intelligent design breeding.These suggestions aim to accelerate the development of an intelligent-driven crop breeding engineering system that features large-scale gene mining,efficient gene manipulation,engineered variety design,and systematized biobreeding.This study provides a theoretical basis and practical guidance for the development of China's seed industry technology.展开更多
How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades,especially under an unpredicted climate change.Crop breeding,initiating from the phenotype-based sel...How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades,especially under an unpredicted climate change.Crop breeding,initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding,has played a critical role in securing the global food supply.However,regarding the changing environment and ever-increasing human population,can we breed outstanding crop varieties fast enough to achieve high productivity,good quality,and widespread adaptability?This review outlines the recent achievements in understanding cereal crop breeding,including the current knowledge about crop agronomic traits,newly developed techniques,crop big biological data research,and the possibility of integrating them for intelligence-driven breeding by design,which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops.This review focuses on the major cereal crops,including rice,maize,and wheat,to explain how intelligence-driven breeding by design is becoming a reality.展开更多
Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis unde...Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands.In this context,we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade,accompanied by a summary of functional genomic platforms.We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits.Lastly,we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles,with the aim of accelerating the development of desired sorghum varieties.展开更多
Progress in plant breeding depends on the development of genetic resources,genetic knowledge,and breeding techniques.The core of plant breeding is the use of naturally occurring variation.At the beginning of the post-...Progress in plant breeding depends on the development of genetic resources,genetic knowledge,and breeding techniques.The core of plant breeding is the use of naturally occurring variation.At the beginning of the post-genomic era,a new concept of"breeding by design"was proposed,which aims to control all allelic variation for all genes of agronomic importance.In the past two decades,we have applied a three-step strategy for research on rice breeding by design.In the first step,we constructed a singlesegment substitution line(SSSL)library using Huajingxian 74(HJX74),an elite xian(indica)rice cultivar,as the recipient in which to assemble genes from the rice AA genome.In the second step,we identified a series of desirable genes in the SSSL library.In the third step,we designed new rice lines,and achieved the breeding goals by pyramiding target genes in the HJX74-SSSL library.This review introduces the background,concept,and strategy of breeding by design,as well as our achievements in rice breeding by design using the HJX74-SSSL platform.Our practice shows that target chromosome-segment substitution is a way to breeding by design.展开更多
A large amount of genome-wide association study(GWAS)panels together with quantitative-trait locus(QTL)information associated with breeding-targeted traits have been described in wheat(Triticum aestivum L.).However,th...A large amount of genome-wide association study(GWAS)panels together with quantitative-trait locus(QTL)information associated with breeding-targeted traits have been described in wheat(Triticum aestivum L.).However,the application of mapping results from a GWAS panel to conventional wheat breeding remains a challenge.In this study,we first report a general genetic map which was constructed from 44 published linkage maps.It permits the estimation of genetic distances between any two genetic loci with physical map positions,thereby unifying the linkage relationships between QTL,genes,and genomic markers from multiple genetic populations.Second,we describe QTL mapping in a wheat GWAS panel of 688 accessions,identifying 77 QTL associated with 12 yield and grain-quality traits.Because these QTL have known physical map positions,they could be mapped onto the general map.Finally,we present a design approach to wheat breeding by using known QTL information and computer simulation.Potential crosses between parents in the GWAS panel may be evaluated by the relative frequency of the target genotype,trait correlations in simulated progeny populations,and genetic gain of selected progenies.It is possible to simultaneously improve yield and grain quality by suitable parental selection,progeny population size,and progeny selection scheme.Applying the design approach will allow identifying the most promising crosses and selection schemes in advance of the field experiment,increasing predictability and efficiency in wheat breeding.展开更多
Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular ...Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.展开更多
Maize(Zea mays L.)is an indispensable crop worldwide for food,feed,and bioenergy production.Fusarium verticillioides(F.verticillioides)is a widely distributed phytopathogen and incites multiple destructive diseases in...Maize(Zea mays L.)is an indispensable crop worldwide for food,feed,and bioenergy production.Fusarium verticillioides(F.verticillioides)is a widely distributed phytopathogen and incites multiple destructive diseases in maize:seedling blight,stalk rot,ear rot,and seed rot.As a soil-,seed-,and airborne pathogen,F.verticillioides can survive in soil or plant residue and systemically infect maize via roots,contaminated seed,silks,or external wounds,posing a severe threat to maize production and quality.Infection triggers complex immune responses:induction of defense-response genes,changes in reactive oxygen species,plant hormone levels and oxylipins,and alterations in secondary metabolites such as flavonoids,phenylpropanoids,phenolic compounds,and benzoxazinoid defense compounds.Breeding resistant maize cultivars is the preferred approach to reducing F.verticillioides infection and mycotoxin contamination.Reliable phenotyping systems are prerequisites for elucidating the genetic structure and molecular mechanism of maize resistance to F.verticillioides.Although many F.verticillioides resistance genes have been identified by genome-wide association study,linkage analysis,bulkedsegregant analysis,and various omics technologies,few have been functionally validated and applied in molecular breeding.This review summarizes research progress on the infection cycle of F.verticillioides in maize,phenotyping evaluation systems for F.verticillioides resistance,quantitative trait loci and genes associated with F.verticillioides resistance,and molecular mechanisms underlying maize defense against F.verticillioides,and discusses potential avenues for molecular design breeding to improve maize resistance to F.verticillioides.展开更多
Breeding is the art and science of selecting and changing crop traits for the benefit of human beings. For several decades, tremendous efforts have been made by Chinese scientists in rice breeding in improving grain y...Breeding is the art and science of selecting and changing crop traits for the benefit of human beings. For several decades, tremendous efforts have been made by Chinese scientists in rice breeding in improving grain yield, nutrition quality, and environmental performance, achieving substantial progress for global food security. Several generations of crop breeding technologies have been developed, for example,selection of better performance in the field among variants(conventional breeding), application of molecular markers for precise selection(molecular marker assisted breeding), and development of molecular design(molecular breeding by rational design). In this review, we briefly summarize the advances in conventional breeding, functional genomics for genes and networks in rice that regulate important agronomic traits, and molecular breeding in China with focuses on high yield, good quality,stress tolerance, and high nutrient-use efficiency. These findings have paved a new avenue for rational design of crops to develop ideal varieties with super performance and productivity.展开更多
Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most mod...Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most modern crop phenomics use different sensors to collect reflective,emitted,and fluorescence signals,etc.,from plant organs at different spatial and temporal resolutions.Such multi-modal,high-dimensional data not only accelerates basic research on crop physiology,genetics,and whole plant systems modeling,but also supports the optimization of field agronomic practices,internal environments of plant factories,and ultimately crop breeding.Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection,management,sharing,and processing,developing capabilities to measure physiological parameters,and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.展开更多
To address the global demand for rapeseed while considering farmers’profit,we face the challenges of making a quantum leap in seed yield and,at the same time,reducing yield loss due to biotic and abiotic stresses.We ...To address the global demand for rapeseed while considering farmers’profit,we face the challenges of making a quantum leap in seed yield and,at the same time,reducing yield loss due to biotic and abiotic stresses.We also face the challenge of efficiently applying new transformative biotechnology tools such as gene editing and breeding by genome design to increase rapeseed productivity and profitability.In this Perspective,we review advances in research on the physiological and genetic bases of both stress factorsaffected yield stability and seed yield potential,focusing on source–sink relationships and allocation of photosynthetic assimilates to vegetative growth and seed development.We propose research directions and highlight the role of plant architecture in the relative contributions of the root system,leaves,and pods to seed yield.We call for de novo design of new rapeseed crops.We review trait variation in existing germplasm and biotechnologies available for crop design.Finally,we discuss opportunities to apply fundamental knowledge and key germplasm to rapeseed production and propose an ideotype for de novo design of future rapeseed cultivars.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
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
The past decade has witnessed rapid developments in gene discovery, biological big data(BBD),artificial intelligence(AI)-aided technologies, and molecular breeding. These advancements are expected to accelerate crop b...The past decade has witnessed rapid developments in gene discovery, biological big data(BBD),artificial intelligence(AI)-aided technologies, and molecular breeding. These advancements are expected to accelerate crop breeding under the pressure of increasing demands for food. Here, we first summarize current breeding methods and discuss the need for new ways to support breeding efforts. Then, we review how to combine BBD and AI technologies for genetic dissection, exploring functional genes, predicting regulatory elements and functional domains, and phenotypic prediction.Finally, we propose the concept of intelligent precision design breeding(IPDB) driven by AI technology and offer ideas about how to implement IPDB. We hope that IPDB will enhance the predictability, efficiency, and cost of crop breeding compared with current technologies. As an example of IPDB, we explore the possibilities offered by Crop GPT, which combines biological techniques, bioinformatics, and breeding art from breeders, and presents an open, shareable, and cooperative breeding system. IPDB provides integrated services and communication platforms for biologists, bioinformatics experts, germplasm resource specialists, breeders, dealers, and farmers,and should be well suited for future breeding.展开更多
“Breeding by design” for pure lines may be achieved by construction of an additive QTL-allele matrix in a germplasm panel or breeding population, but this option is not available for hybrids, where both additive and...“Breeding by design” for pure lines may be achieved by construction of an additive QTL-allele matrix in a germplasm panel or breeding population, but this option is not available for hybrids, where both additive and dominance QTL-allele matrices must be constructed. In this study, a hybrid-QTL identification approach, designated PLSRGA, using partial least squares regression(PLSR) for model fitting integrated with a genetic algorithm(GA) for variable selection based on a multi-locus, multi-allele model is described for additive and dominance QTL-allele detection in a diallel hybrid population(DHP). The PLSRGA was shown by simulation experiments to be superior to single-marker analysis and was then used for QTL-allele identification in a soybean DPH yield experiment with eight parents. Twenty-eight main-effect QTL with 138 alleles and nine QTL × environment QTL with 46 alleles were identified, with respective contributions of 61.8% and 23.5% of phenotypic variation. Main-effect additive and dominance QTL-allele matrices were established as a compact form of the DHP genetic structure. The mechanism of heterosis superior-to-parents(or superior-to-parents heterosis, SPH) was explored and might be explained by a complementary locus-set composed of OD+(showing positive over-dominance, most often), PD+(showing positive partial-to-complete dominance, less often) and HA+(showing positive homozygous additivity, occasionally) loci, depending on the parental materials. Any locus-type, whether OD+, PD + and HA+, could be the best genotype of a locus. All hybrids showed various numbers of better or best genotypes at many but not necessarily all loci, indicating further SPH improvement. Based on the additive/dominance QTL-allele matrices, the best hybrid genotype was predicted, and a hybrid improvement approach is suggested. PLSRGA is powerful for hybrid QTL-allele detection and cross-SPH improvement.展开更多
Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide.Therefore,understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical...Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide.Therefore,understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical significance.In recent decades,studies have characterized hundreds of genes associated with plant responses to salt stress in different plant species.These studies have substantially advanced our molecular and genetic understanding of salt tolerance in plants and have introduced an era of molecular design breeding of salt-tolerant crops.This review summarizes our current knowledge of plant salt tolerance,emphasizing advances in elucidating the molecular mechanisms of osmotic stress tolerance,salt-ion transport and compartmentalization,oxidative stress tolerance,alkaline stress tolerance,and the trade-off between growth and salt tolerance.We also examine recent advances in understanding natural variation in the salt tolerance of crops and discuss possible strategies and challenges for designing salt stress-resilient crops.We focus on the model plant Arabidopsis(Arabidopsis thaliana)and the four most-studied crops:rice(Oryza sativa),wheat(Triticum aestivum),maize(Zea mays),and soybean(Glycine max).展开更多
Plant genomics and crop breeding are at the intersection of biotechnology and information technology.Driven by a combination of highthroughput sequencing,molecular biology and data science,great advances have been mad...Plant genomics and crop breeding are at the intersection of biotechnology and information technology.Driven by a combination of highthroughput sequencing,molecular biology and data science,great advances have been made in omics technologies at every step along the central dogma,especially in genome assembling,genome annotation,epigenomic profiling,and transcriptome profiling.These advances further revolutionized three directions of development.One is genetic dissection of complex traits in crops,along with genomic prediction and selection.The second is comparative genomics and evolution,which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery.The third direction is the development of deep learning approaches for the rational design of biological sequences,especially proteins,for synthetic biology.All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.展开更多
Goldfish(Carassius auratus) have long fascinated evolutionary biologists and geneticists because of their diverse morphological and color variations.Recent genome-wide association studies have provided a clue to uncov...Goldfish(Carassius auratus) have long fascinated evolutionary biologists and geneticists because of their diverse morphological and color variations.Recent genome-wide association studies have provided a clue to uncover genomic basis underlying these phenotypic variations,but the causality between phenotypic and genotypic variations have not yet been confirmed.Here,we edited proposed candidate genes to recreate phenotypic traits and developed a rapid biotechnology approach which combines gene editing with high-efficiency breeding,artificial gynogenesis,and temperature-induced sex reversal to establish homozygous mutants within two generations(approximately eight months).We first verified that low-density lipoprotein receptorrelated protein 2B(lrp2a B) is the causal gene for the dragon-eye variation and recreated the dragon-eye phenotype in side-view Pleated-skirt Lion-head goldfish.Subsequently,we demonstrated that the albino phenotype was determined by both homeologs of oculocutaneous albinism type II(oca2),which has subfunctionalized to differentially govern melanogenesis in the goldfish body surface and pupils.Overall,we determined two causal genes for dragon-eye and albino phenotypes,and created four stable homozygous strains and more appealing goldfish with desirable traits.The developed biotechnology approach facilitates precise genetic breeding,which will accelerate re-domestication and recreation of phenotypically desirable goldfish.展开更多
Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements.Simultaneously,the exponential growth of computational power and big data now promote the a...Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements.Simultaneously,the exponential growth of computational power and big data now promote the application of machine learning for biological research.In this regard,machine learning shows great potential in the refinement of genome editing systems and crop improvement.Here,we review the advances of machine learning to genome editing optimization,with emphasis placed on editing efficiency and specificity enhancement.Additionally,we demonstrate how machine learning bridges genome editing and crop breeding,by accurate key site detection and guide RNA design.Finally,we discuss the current challenges and prospects of these two techniques in crop improvement.By integrating advanced genome editing techniques with machine learning,progress in crop breeding will be further accelerated in the future.展开更多
This paper reviews the progress of systems biology applied to researching on sustainable utilization of Chinese materia medica （CMM） resources in the following aspects： identification and evaluation of CMM resource...This paper reviews the progress of systems biology applied to researching on sustainable utilization of Chinese materia medica （CMM） resources in the following aspects： identification and evaluation of CMM resources, analysis of biosynthesis and their regulation of active ingredients in medicinal plants, metabolic engineering and synthetic biology research of medicinal plants, and molecular breeding of medicinal plants. Development of systems biology is currently leading to extremely broad applications in the field of CMM resources, and systems biology wiil become a significant approach for the sustainable utilization of CMM resources.展开更多
基金funded by the Opening Competition Mechanism to Select the Best Candidates Project of Heilongjiang Province for Science and Technology Science(2023ZXJ02B02)。
文摘Soybean seeds contain approximately 40% protein,making soybeans an important source of plant-based protein.Research on QTN mapping,molecular design breeding and mining of genes related to seed protein formation provides guiding significance for the analysis of the underlying genetic mechanisms of seed protein formation and the selection of high-protein varieties.The seed protein contents(SPCs)of 144 lines of a soybean four-way recombinant inbred line(FW-RIL)population were determined in 8 environments.A three-variance component multisite random effects mixed linear model(3VmrMLM)was used to conduct a genome-wide association study on protein content.A single detected QTN explained 0.53%-3.37% of the phenotypic variation.A molecular-assisted selection breeding model containing the18 QTNs explained 51.97% of the phenotypic variation in protein content.Eight biparental and five triparental crosses that produced excellent lines with the greatest protein content-related genotype values that could be generated by phenotypic and molecular-assisted selection were screened.An LD block of 17QTNs(QEIs)was identified,and one key candidate gene related to protein formation was predicted by haplotype analysis.The proportion of Hap 1 varieties in the spring-sowing soybean region in North China was lower than those in the Huang-Huai-Hai soybean region in Central China and the multiripe soybean region in South China.The proportion of Hap 1 varieties among the wild varieties and landraces was greater than that among the improved varieties.The results of this study provide important insights into the genetic basis of soybean protein content and information to aid in molecular design breeding methods to improve protein content.
基金partially supported by the Construction of Collaborative Innovation Center of Beijing Academy of Agricultural and Forestry Sciences(KJCX20240406)the Beijing Natural Science Foundation(JQ24037)+1 种基金the National Natural Science Foundation of China(32330075)the Earmarked Fund for China Agriculture Research System(CARS-02 and CARS-54)。
文摘The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This era integrates biotechnology,artificial intelligence(AI),and big data information technology.In contrast,China is still in a transition period between stages 2.0 and 3.0,which primarily relies on conventional selection and molecular breeding.In the context of increasingly complex international situations,accurately identifying core issues in China's seed industry innovation and seizing the frontier of international seed technology are strategically important.These efforts are essential for ensuring food security and revitalizing the seed industry.This paper systematically analyzes the characteristics of crop breeding data from artificial selection to intelligent design breeding.It explores the applications and development trends of AI and big data in modern crop breeding from several key perspectives.These include highthroughput phenotype acquisition and analysis,multiomics big data database and management system construction,AI-based multiomics integrated analysis,and the development of intelligent breeding software tools based on biological big data and AI technology.Based on an in-depth analysis of the current status and challenges of China's seed industry technology development,we propose strategic goals and key tasks for China's new generation of AI and big data-driven intelligent design breeding.These suggestions aim to accelerate the development of an intelligent-driven crop breeding engineering system that features large-scale gene mining,efficient gene manipulation,engineered variety design,and systematized biobreeding.This study provides a theoretical basis and practical guidance for the development of China's seed industry technology.
基金supported by the National Science Foundation of China(32341029)Science and Technology Innovation 2030 Major Projects(2023ZD0406804)Outstanding Youth Team Cultivation Project of Center Universities(2662023PY007)。
文摘How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades,especially under an unpredicted climate change.Crop breeding,initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding,has played a critical role in securing the global food supply.However,regarding the changing environment and ever-increasing human population,can we breed outstanding crop varieties fast enough to achieve high productivity,good quality,and widespread adaptability?This review outlines the recent achievements in understanding cereal crop breeding,including the current knowledge about crop agronomic traits,newly developed techniques,crop big biological data research,and the possibility of integrating them for intelligence-driven breeding by design,which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops.This review focuses on the major cereal crops,including rice,maize,and wheat,to explain how intelligence-driven breeding by design is becoming a reality.
基金the National Science Foundation for Young Scientists of China(32201780)the Fundamental Research Fund for the Central Universities(77000–12240011)+2 种基金Shenzhen Postdoctoral Funding Project(szbo202410)the National Natural Science Foundation of China(32241045 and 32241038)the National Key Research and Development Program of China(2022YFD1500503,2023YFD1200700,and 2023YFD1200704).
文摘Sorghum,renowned for its substantial biomass production and remarkable tolerance to various stresses,possesses extensive gene resources and phenotypic variations.A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands.In this context,we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade,accompanied by a summary of functional genomic platforms.We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits.Lastly,we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles,with the aim of accelerating the development of desired sorghum varieties.
基金supported by the Major Program of Transgenic New Variety Breeding of China(2009ZX08009005)the National Natural Science Foundation of China(91435207 and 91735304)。
文摘Progress in plant breeding depends on the development of genetic resources,genetic knowledge,and breeding techniques.The core of plant breeding is the use of naturally occurring variation.At the beginning of the post-genomic era,a new concept of"breeding by design"was proposed,which aims to control all allelic variation for all genes of agronomic importance.In the past two decades,we have applied a three-step strategy for research on rice breeding by design.In the first step,we constructed a singlesegment substitution line(SSSL)library using Huajingxian 74(HJX74),an elite xian(indica)rice cultivar,as the recipient in which to assemble genes from the rice AA genome.In the second step,we identified a series of desirable genes in the SSSL library.In the third step,we designed new rice lines,and achieved the breeding goals by pyramiding target genes in the HJX74-SSSL library.This review introduces the background,concept,and strategy of breeding by design,as well as our achievements in rice breeding by design using the HJX74-SSSL platform.Our practice shows that target chromosome-segment substitution is a way to breeding by design.
基金the Hainan Yazhou Bay Seed Laboratory(B21Y10209 and B22C10212)China Postdoctoral Science Foundation(2022M713433)+1 种基金National Natural Science Foundation of China(31861143003)Innovation Program of Chinese Academy of Agricultural Sciences.
文摘A large amount of genome-wide association study(GWAS)panels together with quantitative-trait locus(QTL)information associated with breeding-targeted traits have been described in wheat(Triticum aestivum L.).However,the application of mapping results from a GWAS panel to conventional wheat breeding remains a challenge.In this study,we first report a general genetic map which was constructed from 44 published linkage maps.It permits the estimation of genetic distances between any two genetic loci with physical map positions,thereby unifying the linkage relationships between QTL,genes,and genomic markers from multiple genetic populations.Second,we describe QTL mapping in a wheat GWAS panel of 688 accessions,identifying 77 QTL associated with 12 yield and grain-quality traits.Because these QTL have known physical map positions,they could be mapped onto the general map.Finally,we present a design approach to wheat breeding by using known QTL information and computer simulation.Potential crosses between parents in the GWAS panel may be evaluated by the relative frequency of the target genotype,trait correlations in simulated progeny populations,and genetic gain of selected progenies.It is possible to simultaneously improve yield and grain quality by suitable parental selection,progeny population size,and progeny selection scheme.Applying the design approach will allow identifying the most promising crosses and selection schemes in advance of the field experiment,increasing predictability and efficiency in wheat breeding.
文摘Conventional plant breeding largely depends on phenotypic selection and breeder＇s experience, therefore the breeding efficiency is low and the predictions are inaccurate. Along with the fast development in molecular biology and biotechnology, a large amount of biological data is available for genetic studies of important breeding traits in plants, which in turn allows the conduction of genotypic selection in the breeding process. However, gene information has not been effectively used in crop improvement because of the lack of appropriate tools. The simulation approach can utilize the vast and diverse genetic information, predict the cross performance, and compare different selection methods. Thus, the best performing crosses and effective breeding strategies can be identified. QuLine is a computer tool capable of defining a range, from simple to complex genetic models, and simulating breeding processes for developing final advanced lines. On the basis of the results from simulation experiments, breeders can optimize their breeding methodology and greatly improve the breeding efficiency. In this article, the underlying principles of simulation modeling in crop enhancement is initially introduced, following which several applications of QuLine are summarized, by comparing the different selection strategies, the precision parental selection, using known gene information, and the design approach in breeding. Breeding simulation allows the definition of complicated genetic models consisting of multiple alleles, pleiotropy, epistasis, and genes, by environment interaction, and provides a useful tool for breeders, to efficiently use the wide spectrum of genetic data and information available.
基金the National Natural Science Foundation of China(32201787,32201793)the Innovation Special Program of Henan Agricultural University for Science and Technology(30501044)the Special Support Fund for High-Level Talents of Henan Agricultural University(30501302).
文摘Maize(Zea mays L.)is an indispensable crop worldwide for food,feed,and bioenergy production.Fusarium verticillioides(F.verticillioides)is a widely distributed phytopathogen and incites multiple destructive diseases in maize:seedling blight,stalk rot,ear rot,and seed rot.As a soil-,seed-,and airborne pathogen,F.verticillioides can survive in soil or plant residue and systemically infect maize via roots,contaminated seed,silks,or external wounds,posing a severe threat to maize production and quality.Infection triggers complex immune responses:induction of defense-response genes,changes in reactive oxygen species,plant hormone levels and oxylipins,and alterations in secondary metabolites such as flavonoids,phenylpropanoids,phenolic compounds,and benzoxazinoid defense compounds.Breeding resistant maize cultivars is the preferred approach to reducing F.verticillioides infection and mycotoxin contamination.Reliable phenotyping systems are prerequisites for elucidating the genetic structure and molecular mechanism of maize resistance to F.verticillioides.Although many F.verticillioides resistance genes have been identified by genome-wide association study,linkage analysis,bulkedsegregant analysis,and various omics technologies,few have been functionally validated and applied in molecular breeding.This review summarizes research progress on the infection cycle of F.verticillioides in maize,phenotyping evaluation systems for F.verticillioides resistance,quantitative trait loci and genes associated with F.verticillioides resistance,and molecular mechanisms underlying maize defense against F.verticillioides,and discusses potential avenues for molecular design breeding to improve maize resistance to F.verticillioides.
基金supported by grants from the National Key Research and Development Program of China (2016YFD0100603)the National Natural Science Foundation of China (No.91635301)
文摘Breeding is the art and science of selecting and changing crop traits for the benefit of human beings. For several decades, tremendous efforts have been made by Chinese scientists in rice breeding in improving grain yield, nutrition quality, and environmental performance, achieving substantial progress for global food security. Several generations of crop breeding technologies have been developed, for example,selection of better performance in the field among variants(conventional breeding), application of molecular markers for precise selection(molecular marker assisted breeding), and development of molecular design(molecular breeding by rational design). In this review, we briefly summarize the advances in conventional breeding, functional genomics for genes and networks in rice that regulate important agronomic traits, and molecular breeding in China with focuses on high yield, good quality,stress tolerance, and high nutrient-use efficiency. These findings have paved a new avenue for rational design of crops to develop ideal varieties with super performance and productivity.
基金supported by National Research and Development Program of Ministry of Science and Technology of China(2020YFA0907600,2018YFA0900600,2019YFA09004600)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB27020105,XDB37020104,XDA24010203,XDA0450202)+2 种基金National Science Foundation of China(31870214)the National Key Research and Development Program of China(2023YFF1000100)STI2030eMajor Projects(2023ZD04076).
文摘Crop phenomics enables the collection of diverse plant traits for a large number of samples along different time scales,representing a greater data collection throughput compared with traditional measurements.Most modern crop phenomics use different sensors to collect reflective,emitted,and fluorescence signals,etc.,from plant organs at different spatial and temporal resolutions.Such multi-modal,high-dimensional data not only accelerates basic research on crop physiology,genetics,and whole plant systems modeling,but also supports the optimization of field agronomic practices,internal environments of plant factories,and ultimately crop breeding.Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection,management,sharing,and processing,developing capabilities to measure physiological parameters,and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.
基金the National Natural Science Foundation of China(U20A2034 and 32070217)the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ZDRW202105 and CAASASTIP-2013-OCRI)。
文摘To address the global demand for rapeseed while considering farmers’profit,we face the challenges of making a quantum leap in seed yield and,at the same time,reducing yield loss due to biotic and abiotic stresses.We also face the challenge of efficiently applying new transformative biotechnology tools such as gene editing and breeding by genome design to increase rapeseed productivity and profitability.In this Perspective,we review advances in research on the physiological and genetic bases of both stress factorsaffected yield stability and seed yield potential,focusing on source–sink relationships and allocation of photosynthetic assimilates to vegetative growth and seed development.We propose research directions and highlight the role of plant architecture in the relative contributions of the root system,leaves,and pods to seed yield.We call for de novo design of new rapeseed crops.We review trait variation in existing germplasm and biotechnologies available for crop design.Finally,we discuss opportunities to apply fundamental knowledge and key germplasm to rapeseed production and propose an ideotype for de novo design of future rapeseed cultivars.
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 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 the National Key Research and Development Program of China (2023YFF1000100) (to L.L. and W.L.)the National Natural Science Foundation of China (32321005) (to L.L.)。
文摘The past decade has witnessed rapid developments in gene discovery, biological big data(BBD),artificial intelligence(AI)-aided technologies, and molecular breeding. These advancements are expected to accelerate crop breeding under the pressure of increasing demands for food. Here, we first summarize current breeding methods and discuss the need for new ways to support breeding efforts. Then, we review how to combine BBD and AI technologies for genetic dissection, exploring functional genes, predicting regulatory elements and functional domains, and phenotypic prediction.Finally, we propose the concept of intelligent precision design breeding(IPDB) driven by AI technology and offer ideas about how to implement IPDB. We hope that IPDB will enhance the predictability, efficiency, and cost of crop breeding compared with current technologies. As an example of IPDB, we explore the possibilities offered by Crop GPT, which combines biological techniques, bioinformatics, and breeding art from breeders, and presents an open, shareable, and cooperative breeding system. IPDB provides integrated services and communication platforms for biologists, bioinformatics experts, germplasm resource specialists, breeders, dealers, and farmers,and should be well suited for future breeding.
基金supported by the National Key Research and Development Program of China (2021YFF1001204,2017YFD0101500)the MOE Program of Introducing Talents of Discipline to Universities (“111”Project, B08025)+4 种基金the MOE Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT_17R55)the MARA CARS-04 Programthe Jiangsu Higher Education PAPD Programthe Fundamental Research Funds for the Central Universities (KYZZ201901)the Jiangsu JCICMCP Program。
文摘“Breeding by design” for pure lines may be achieved by construction of an additive QTL-allele matrix in a germplasm panel or breeding population, but this option is not available for hybrids, where both additive and dominance QTL-allele matrices must be constructed. In this study, a hybrid-QTL identification approach, designated PLSRGA, using partial least squares regression(PLSR) for model fitting integrated with a genetic algorithm(GA) for variable selection based on a multi-locus, multi-allele model is described for additive and dominance QTL-allele detection in a diallel hybrid population(DHP). The PLSRGA was shown by simulation experiments to be superior to single-marker analysis and was then used for QTL-allele identification in a soybean DPH yield experiment with eight parents. Twenty-eight main-effect QTL with 138 alleles and nine QTL × environment QTL with 46 alleles were identified, with respective contributions of 61.8% and 23.5% of phenotypic variation. Main-effect additive and dominance QTL-allele matrices were established as a compact form of the DHP genetic structure. The mechanism of heterosis superior-to-parents(or superior-to-parents heterosis, SPH) was explored and might be explained by a complementary locus-set composed of OD+(showing positive over-dominance, most often), PD+(showing positive partial-to-complete dominance, less often) and HA+(showing positive homozygous additivity, occasionally) loci, depending on the parental materials. Any locus-type, whether OD+, PD + and HA+, could be the best genotype of a locus. All hybrids showed various numbers of better or best genotypes at many but not necessarily all loci, indicating further SPH improvement. Based on the additive/dominance QTL-allele matrices, the best hybrid genotype was predicted, and a hybrid improvement approach is suggested. PLSRGA is powerful for hybrid QTL-allele detection and cross-SPH improvement.
基金financial support from the National Science Fund for Distinguished Young Scholars(32325037)the China National Key Program for Research and Development(2022YFA1303400)the National Natural Science Foundation of China(32201718 and 32100234)。
文摘Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide.Therefore,understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical significance.In recent decades,studies have characterized hundreds of genes associated with plant responses to salt stress in different plant species.These studies have substantially advanced our molecular and genetic understanding of salt tolerance in plants and have introduced an era of molecular design breeding of salt-tolerant crops.This review summarizes our current knowledge of plant salt tolerance,emphasizing advances in elucidating the molecular mechanisms of osmotic stress tolerance,salt-ion transport and compartmentalization,oxidative stress tolerance,alkaline stress tolerance,and the trade-off between growth and salt tolerance.We also examine recent advances in understanding natural variation in the salt tolerance of crops and discuss possible strategies and challenges for designing salt stress-resilient crops.We focus on the model plant Arabidopsis(Arabidopsis thaliana)and the four most-studied crops:rice(Oryza sativa),wheat(Triticum aestivum),maize(Zea mays),and soybean(Glycine max).
基金supported by the National Key Research and Development Program of China(2022YFD1201100)the National Natural Science Foundation of China(32071464)+1 种基金Chinese Universities Scientific Fund(2023RC002)the 2115 Talent Development Program of China Agricultural University.
文摘Plant genomics and crop breeding are at the intersection of biotechnology and information technology.Driven by a combination of highthroughput sequencing,molecular biology and data science,great advances have been made in omics technologies at every step along the central dogma,especially in genome assembling,genome annotation,epigenomic profiling,and transcriptome profiling.These advances further revolutionized three directions of development.One is genetic dissection of complex traits in crops,along with genomic prediction and selection.The second is comparative genomics and evolution,which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery.The third direction is the development of deep learning approaches for the rational design of biological sequences,especially proteins,for synthetic biology.All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.
基金supported by the National Key Research and Development Program of China(2018YFD0901202)the Strategic Priority Research Program of Chinese Academy of Sciences(XDB31000000)+3 种基金the Knowledge Innovation Program of Wuhan-Basic Research(2022020801010143)the Autonomous Project of the State Key Laboratory of Freshwater Ecology and Biotechnology(2021FB02)the China Agriculture Research System of MOF and MARAsupported by the Wuhan Branch,Supercomputing Center,Chinese Academy of Sciences,China。
文摘Goldfish(Carassius auratus) have long fascinated evolutionary biologists and geneticists because of their diverse morphological and color variations.Recent genome-wide association studies have provided a clue to uncover genomic basis underlying these phenotypic variations,but the causality between phenotypic and genotypic variations have not yet been confirmed.Here,we edited proposed candidate genes to recreate phenotypic traits and developed a rapid biotechnology approach which combines gene editing with high-efficiency breeding,artificial gynogenesis,and temperature-induced sex reversal to establish homozygous mutants within two generations(approximately eight months).We first verified that low-density lipoprotein receptorrelated protein 2B(lrp2a B) is the causal gene for the dragon-eye variation and recreated the dragon-eye phenotype in side-view Pleated-skirt Lion-head goldfish.Subsequently,we demonstrated that the albino phenotype was determined by both homeologs of oculocutaneous albinism type II(oca2),which has subfunctionalized to differentially govern melanogenesis in the goldfish body surface and pupils.Overall,we determined two causal genes for dragon-eye and albino phenotypes,and created four stable homozygous strains and more appealing goldfish with desirable traits.The developed biotechnology approach facilitates precise genetic breeding,which will accelerate re-domestication and recreation of phenotypically desirable goldfish.
基金supported by the National Natural Science Foundation of China(grant no.32270585)Key R&D Program of Jiangsu Province(Modern Agriculture)(BE2022335)+1 种基金the Project of Zhongshan Biological Breeding Laboratory(BM2022008-02)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements.Simultaneously,the exponential growth of computational power and big data now promote the application of machine learning for biological research.In this regard,machine learning shows great potential in the refinement of genome editing systems and crop improvement.Here,we review the advances of machine learning to genome editing optimization,with emphasis placed on editing efficiency and specificity enhancement.Additionally,we demonstrate how machine learning bridges genome editing and crop breeding,by accurate key site detection and guide RNA design.Finally,we discuss the current challenges and prospects of these two techniques in crop improvement.By integrating advanced genome editing techniques with machine learning,progress in crop breeding will be further accelerated in the future.
基金National Natural Science Foundation of China(81130070,81430096)Important National Science&Technology Specific Projects(2012BAI29B02,2012BAI28B002)
文摘This paper reviews the progress of systems biology applied to researching on sustainable utilization of Chinese materia medica （CMM） resources in the following aspects： identification and evaluation of CMM resources, analysis of biosynthesis and their regulation of active ingredients in medicinal plants, metabolic engineering and synthetic biology research of medicinal plants, and molecular breeding of medicinal plants. Development of systems biology is currently leading to extremely broad applications in the field of CMM resources, and systems biology wiil become a significant approach for the sustainable utilization of CMM resources.
