Increasing Fusarium verticillioides resistance in maize by genomicsassisted breeding:Methods,progress,and prospects

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.

Breeding design in wheat by combining the QTL information in a GWAS panel with a general genetic map and computer simulation

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.

Target chromosome-segment substitution: A way to breeding by design in rice

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.

Simulation Modeling in Plant Breeding: Principles and Applications

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.

A novel procedure for identifying a hybrid QTL-allele system for hybrid-vigor improvement, with a case study in soybean(Glycine max)yield

“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.

Modern phenomics to empower holistic crop science, agronomy, and breeding research

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.

Computational tools for plant genomics and breeding

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.

Engineering the future cereal crops with big biological data:toward intelligence-driven breeding by design

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.

De novo design of future rapeseed crops:Challenges and opportunities

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.

Designing salt stress-resilient crops:Current progress and future challenges

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).

Integrating machine learning and genome editing for crop improvement

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.

Retrospective and perspective of rice breeding in China

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.

Systems Biology Application in Research on Sustainable Utilization of Chinese Materia Medica Resources

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.

Causal gene identification and desirable trait recreation in goldfish

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.