Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat

Genome sequencing reveals the genetic architecture of heterostyly and domestication history of common buckwheat

Common buckwheat, Fagopyrum esculentum, is an orphan crop domesticated in southwest China that exhibits heterostylous self-incompatibility. Here we present chromosome-scale assemblies of a self-compatible F. esculentum accession and a self-compatible wild relative, Fagopyrum homotropicum, together with the resequencing of 104 wild and cultivated F. esculentum accessions. Using these genomic data, we report the roles of transposable elements and whole-genome duplications in the evolution of Fagopyrum. In addition, we show that (1) the breakdown of heterostyly occurs through the disruption of a hemizygous gene jointly regulating the style length and female compatibility and (2) southeast Tibet was involved in common buckwheat domestication. Moreover, we obtained mutants conferring the waxy phenotype for the first time in buckwheat. These findings demonstrate the utility of our F. esculentum assembly as a reference genome and promise to accelerate buckwheat research and breeding.

Buckwheat OMICS: present status and future prospects

Buckwheat (Fagopyrum spp.) is an underutilized resilient crop of North Western Himalayas belonging to the family Polygonaceae and is a source of essential nutrients and therapeutics. Common Buckwheat and Tatary Buckwheat are the two main cultivated species used as food. It is the only grain crop possessing rutin, an important metabolite with high nutraceutical potential. Due to its inherent tolerance to various biotic and abiotic stresses and a short life cycle, Buckwheat has been proposed as a model crop plant. Nutritional security is one of the major concerns, breeding for a nutrient-dense crop such as Buckwheat will provide a sustainable solution. Efforts toward improving Buckwheat for nutrition and yield are limited due to the lack of available: genetic resources, genomics, transcriptomics and metabolomics. In order to harness the agricultural importance of Buckwheat, an integrated breeding and OMICS platforms needs to be established that can pave the way for a better understanding of crop biology and developing commercial varieties. This, coupled with the availability of the genome sequences of both Buckwheat species in the public domain, should facilitate the identification of alleles/QTLs and candidate genes. There is a need to further our understanding of the molecular basis of the genetic regulation that controls various economically important traits. The present review focuses on: the food and nutritional importance of Buckwheat, its various omics resources, utilization of omics approaches in understanding Buckwheat biology and, finally, how an integrated platform of breeding and omics will help in developing commercially high yielding nutrient rich cultivars in Buckwheat.

Genomic prediction through machine learning and neural networks for traits with epistasis

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Performance of machine learning and neural netowrks in Genomic analysis.

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Heritability and QTL number impacts on performance machine learning methods.

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Machine learning models in genomic analyses.

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Neural networks can present better performance for complex quantitative traits.

Genomic wide selection (GWS) is one contributions of molecular genetics to breeding. Machine learning (ML) and artificial neural networks (ANN) methods are non-parameterized and can develop more accurate and parsimonious models for GWS analysis. Multivariate Adaptive Regression Splines (MARS) is considered one of the most flexible ML methods, automatically modeling nonlinearities and interactions of the predictor variables. This study aimed to evaluate and compare methods based on ANN, ML, including MARS, and G-BLUP through GWS. An F2 population formed by 1000 individuals and genotyped for 4010 SNP markers and twelve traits from a model considering epistatic effect, with QTL numbers ranging from eight to 480 and heritability (h2) of 0.3, 0.5 or 0.8 were simulated. Variation in heritability and number of QTL impacts the performance of methods. About quantitative traits (40, 80, 120, 240, and 480 QTLs) was observed highest R2 to Radial Base Network (RBF) and G-BLUP, followed by Random Forest (RF), Bagging (BA), and Boosting (BO). RF and BA also showed better results for traits to h2 of 0.3 with R2 values 16.51% and 16.30%, respectively, while MARS methods showed better results for oligogenic traits with R2 values ranging from 39,12 % to 43,20 % in h2 of 0.5 and from 59.92% to 78,56% in h2 of 0.8. Non-additive MARS methods also showed high R2 for traits with high heritability and 240 QTLs or more. ANN and ML methods are powerful tools to predict genetic values in traits with epistatic effect, for different degrees of heritability and QTL numbers.

Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava

GWAS identified eight yield-related, peak starch type of waxy and wild-type starch and 21 starch pasting property-related traits (QTLs). Prediction ability of eight GS models resulted in low to high predictability, depending on trait, heritability, and genetic architecture. Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We carried out a genome-wide association study to clarify the molecular mechanisms underlying these traits and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection (GS) using parametric, semi-parametric, and nonparametric GS models with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped via genotyping-by-sequencing, and 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected by the fixed and random model circulating probability unification (FarmCPU), Bayesian-information and linkage-disequilibrium iteratively nested keyway and compressed mixed linear model, respectively. GS models were developed, and forward predictabilities using all the prediction methods resulted in values of - 0.001-0.71 for the four yield-related traits and 0.33-0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs.

Beyond the Cereal Box: Breeding Buckwheat as a Strategic Crop for Human Nutrition

While intensification of farming systems is essential for achieving the Millennium Development Goal of "Zero hunger", issues such as availability of nutritious foods would demand increased attention if any long-term form of food security is to be achieved. Since wheat, rice and maize have reached near to 80 percent of their yield potential and reliance on these crops alone would not be sufficient to close the gap between demand and supply, there is a need to bring other climate-resilient and nutritionally dense crops into agricultural portfolio. Buckwheat (Fagopyrum spp.) has attracted considerable interest amongst global scientific community due to its nutritional and pharmaceutical properties. The gluten free nature of buckwheat, nutritionally balanced amino acid composition of its grain protein, and high levels of anti-oxidants, such as rutin, makes buckwheat an important crop with immense nutraceutical benefits. However, a key challenge in buckwheat cultivation is the variation in yield between years, which impacts the entire value chain. Current information on buckwheat indicates existence of significant phenotypic variation for agronomic and nutritional traits. However, genetic bottlenecks in conventional breeding restrict effective utilization of the existing diversity in mainstreaming buckwheat cultivation. Availability of high density buckwheat genome map for both the cultivated species viz. F. esculentum and F. tataricum would add to our understanding of genetic basis of their agronomic traits. The review examines the potential of buckwheat as a strategic crop for human nutrition and prospects of effective exploitation genomic information of common and Tartary buckwheat for genome assisted breeding.

Genomic Selection in Sugarcane: Current Status and Future Prospects

Sugarcane is a C4 and agro-industry-based crop with a high potential for biomass production. It serves as raw material for the production of sugar, ethanol, and electricity. Modern sugarcane varieties are derived from the interspecific and intergeneric hybridization between Saccharum officinarum, Saccharum spontaneum, and other wild relatives. Sugarcane breeding programmes are broadly categorized into germplasm collection and characterization, pre-breeding and genetic base-broadening, and varietal development programmes. The varietal identification through the classic breeding programme requires a minimum of 12-14 years. The precise phenotyping in sugarcane is extremely tedious due to the high propensity of lodging and suckering owing to the influence of environmental factors and crop management practices. This kind of phenotyping requires data from both plant crop and ratoon experiments conducted over locations and seasons. In this review, we explored the feasibility of genomic selection schemes for various breeding programmes in sugarcane. The genetic diversity analysis using genome-wide markers helps in the formation of core set germplasm representing the total genomic diversity present in the Saccharum gene bank. The genome-wide association studies and genomic prediction in the Saccharum gene bank are helpful to identify the complete genomic resources for cane yield, commercial cane sugar, tolerances to biotic and abiotic stresses, and other agronomic traits. The implementation of genomic selection in pre-breeding, genetic base-broadening programmes assist in precise introgression of specific genes and recurrent selection schemes enhance the higher frequency of favorable alleles in the population with a considerable reduction in breeding cycles and population size. The integration of environmental covariates and genomic prediction in multi-environment trials assists in the prediction of varietal performance for different agro-climatic zones. This review also directed its focus on enhancing the genetic gain over time, cost, and resource allocation at various stages of breeding programmes.

Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing

Genomic selection and marker-assisted recurrent selection have been applied to improve quantitative traits in many cross-pollinated crops. However, such selection is not feasible in self-pollinated crops owing to laborious crossing procedures. In this study, we developed a simulation-based selection strategy that makes use of a trait prediction model based on genomic information to predict the phenotype of the progeny for all possible crossing combinations. These predictions are then used to select the best cross combinations for the selection of the given trait. In our simulated experiment, using a biparental initial population with a heritability set to 0.3, 0.6, or 1.0 and the number of quantitative trait loci set to 30 or 100, the genetic gain of the proposed strategy was higher or equal to that of conventional recurrent selection method in the early selection cycles, although the number of cross combinations of the proposed strategy was considerably reduced in each cycle. Moreover, this strategy was demonstrated to increase or decrease seed protein content in soybean recombinant inbred lines using SNP markers. Information on 29 genomic regions associated with seed protein content was used to construct the prediction model and conduct simulation. After two selection cycles, the selected progeny had significantly higher or lower seed protein contents than those from the initial population. These results suggest that our strategy is effective in obtaining superior progeny over a short period with minimal crossing and has the potential to efficiently improve the target quantitative traits in self-pollinated crops.

Biotechnological Methods for Buckwheat Breeding

The Fagopyrum genus includes two cultivated species, namely common buckwheat (F. esculentum Moench) and Tartary buckwheat (F. tataricum Gaertn.), and more than 25 wild buckwheat species. The goal of breeders is to improve the properties of cultivated buckwheat with methods of classical breeding, with the support of biotechnological methods or a combination of both. In this paper, we reviewed the possibility to use transcriptomics, genomics, interspecific hybridization, tissue cultures and plant regeneration, molecular markers, genetic transformation, and genome editing to aid in both the breeding of buckwheat and in the identification and production of metabolites important for preserving human health. The key problems in buckwheat breeding are the unknown mode of inheritance of most traits, associated with crop yield and the synthesis of medicinal compounds, low seed yield, shedding of seeds, differential flowering and seed set on branches, and unknown action of genes responsible for the synthesis of buckwheat metabolites of pharmaceutical and medicinal interest.

Comprehensive genotyping of a Brazilian cassava (Manihot esculenta Crantz) germplasm bank: insights into diversification and domestication

KEY MESSAGE

Brazilian cassava diversity was characterized through population genetics and clustering approaches, highlighting contrasted genetic groups and spatial genetic differentiation. Cassava (Manihot esculenta Crantz) is a major staple root crop of the tropics, originating from the Amazonian region. In this study, 3354 cassava landraces and modern breeding lines from the Embrapa Cassava Germplasm Bank (CGB) were characterized. All individuals were subjected to genotyping-by-sequencing (GBS), identifying 27,045 single-nucleotide polymorphisms (SNPs). Identity-by-state and population structure analyses revealed a unique set of 1536 individuals and 10 distinct genetic groups with heterogeneous linkage disequilibrium (LD). On this basis, a density of 1300-4700 SNP markers were selected for large-effect quantitative trait loci (QTL) detection. Identified genetic groups were further characterized for population genetics parameters including minor allele frequency (MAF), observed heterozygosity [Formula: see text], effective population size estimate [Formula: see text]) and polymorphism information content (PIC). Selection footprints and introgressions of M. glaziovii were detected. Spatial population structure analysis revealed five ancestral populations related to distinct Brazilian ecoregions. Estimation of historical relationships among identified populations suggests an early population split from Amazonian to Atlantic forest and Caatinga ecoregions and active gene flows. This study provides a thorough genetic characterization of ex situ germplasm resources from cassava's center of origin, South America, with results shedding light on Brazilian cassava characteristics and its biogeographical landscape. These findings support and facilitate the use of genetic resources in modern breeding programs including implementation of association mapping and genomic selection strategies.

Comprehensive genotyping of a Brazilian cassava (Manihot esculenta Crantz) germplasm bank: insights into diversification and domestication

Brazilian cassava diversity was characterized through population genetics and clustering approaches, highlighting contrasted genetic groups and spatial genetic differentiation. Cassava (Manihot esculenta Crantz) is a major staple root crop of the tropics, originating from the Amazonian region. In this study, 3354 cassava landraces and modern breeding lines from the Embrapa Cassava Germplasm Bank (CGB) were characterized. All individuals were subjected to genotyping-by-sequencing (GBS), identifying 27,045 single-nucleotide polymorphisms (SNPs). Identity-by-state and population structure analyses revealed a unique set of 1536 individuals and 10 distinct genetic groups with heterogeneous linkage disequilibrium (LD). On this basis, a density of 1300-4700 SNP markers were selected for large-effect quantitative trait loci (QTL) detection. Identified genetic groups were further characterized for population genetics parameters including minor allele frequency (MAF), observed heterozygosity [Formula: see text], effective population size estimate [Formula: see text]) and polymorphism information content (PIC). Selection footprints and introgressions of M. glaziovii were detected. Spatial population structure analysis revealed five ancestral populations related to distinct Brazilian ecoregions. Estimation of historical relationships among identified populations suggests an early population split from Amazonian to Atlantic forest and Caatinga ecoregions and active gene flows. This study provides a thorough genetic characterization of ex situ germplasm resources from cassava's center of origin, South America, with results shedding light on Brazilian cassava characteristics and its biogeographical landscape. These findings support and facilitate the use of genetic resources in modern breeding programs including implementation of association mapping and genomic selection strategies.

Integrated genomic selection for rapid improvement of crops

An increase in the rate of crop improvement is essential for achieving sustained food production and other needs of ever-increasing population. Genomic selection (GS) is a potential breeding tool that has been successfully employed in animal breeding and is being incorporated into plant breeding. GS promises accelerated breeding cycles through a rapid selection of superior genotypes. Numerous empirical and simulation studies on GS and realized impacts on improvement in the crop yields are recently being reported. For a holistic understanding of the technology, we briefly discuss the concept of genetic gain, GS methodology, its current status, advantages of GS over other breeding methods, prediction models, and the factors controlling prediction accuracy in GS. Also, integration of speed breeding and other novel technologies viz. high throughput genotyping and phenotyping technologies for enhancing the efficiency and pace of GS, followed by its prospective applications in varietal development programs is reviewed.

Breeding Buckwheat for Increased Levels and Improved Quality of Protein

Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn.) and common buckwheat (Fagopyrum esculentum Moench) are important sources of proteins with balanced amino-acid compositions, and thus of high nutritional value. The polyphenols naturally present in Tartary buckwheat and common buckwheat lower the true digestibility of the proteins. Digestion-resistant peptides are a vehicle for fecal excretion of steroids, and in this way, for bile acid elimination and reduction of cholesterol concentrations in serum. Buckwheat proteins are more effective compared to soy proteins for the prevention of gallstone formation. Tartary and common buckwheat grain that contains appropriate amounts of selenium-containing amino acids can be produced as functional food products. The protein-rich by-products of buckwheat are a good source of bioactive substances that can suppress colon carcinogenesis by reducing cell proliferation. The grain embryo is a rich source of proteins, so breeding buckwheat with larger embryos is a possible strategy to increase protein levels in Tartary and common buckwheat grain. However, chemical analysis of the grain is the most relevant criterion for assessing grain protein levels and quality.

Simulation-based optimization of genomic selection scheme for accelerating genetic gain while preventing inbreeding depression in onion breeding

Genomic selection (GS) is being increasingly employed in plant breeding programs to accelerate genetic gain of economically important traits. However, its efficiency differs greatly across species, due to differences in reproduction and breeding strategies. Onion (Allium cepa L.) is an out-crossing crop but can be easily self-pollinated. High inbreeding depression occurs, and contamination of self-pollinated seeds is unavoidable in onion breeding. Taking this into consideration, 10-year breeding programs with and without GS were simulated. In addition to general GS, we proposed GS schemes to prevent inbreeding depression by avoiding co-selection of close relatives and combining the shortening of generation time and updating of the prediction model. The results showed that general GS with shortening of generation time yielded the highest genetic gain among the selection schemes in early years. However, inbreeding increased rapidly, reaching very high levels in later years. The proposed GS combining shortening of generation time with updating of the prediction model was superior to the others in later years, as it yielded relatively high genetic gain while maintaining significantly low levels of inbreeding. These results suggested that GS can be beneficial in onion breeding, and an optimal scheme should be selected depending on the selection period.

Reducing Flower Competition for Assimilates by Half Results in Higher Yield of Fagopyrum esculentum

Despite abundant flowering throughout the season, common buckwheat develops a very low number of kernels probably due to competition for assimilates. We hypothesized that plants with a shorter flowering period may give a higher seed yield. To verify the hypothesis, we studied nutrient stress in vitro and in planta and analyzed different embryological and yield parameters, including hormone profile in the flowers. In vitro cultivated flowers on media with strongly reduced nutrient content demonstrated a drastic increase in degenerated embryo sacs. In in planta experiments, where 50% or 75% of flowers or all lateral ramifications were removed, the reduction of the flower competition by half turned out to be the most promising treatment for improving yield. This treatment increased the frequency of properly developed embryo sacs, the average number of mature seeds per plant, and their mass. Strong seed compensation under 50% inflorescence removal could result from increased production of salicylic and jasmonic acid that both favor more effective pollinator attraction. Plants in single-shoot cultivation finished their vegetation earlier, and they demonstrated greater single seed mass per plant than in control. This result suggests that plants of common buckwheat with shorter blooming period could deliver higher seed yield.

Breeding Buckwheat for Increased Levels of Rutin, Quercetin and Other Bioactive Compounds with Potential Antiviral Effects

Common buckwheat (Fagopyrum esculentum Moench) and Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn.) are sources of many bioactive compounds, such as rutin, quercetin, emodin, fagopyrin and other (poly)phenolics. In damaged or milled grain under wet conditions, most of the rutin in common and Tartary buckwheat is degraded to quercetin by rutin-degrading enzymes (e.g., rutinosidase). From Tartary buckwheat varieties with low rutinosidase activity it is possible to prepare foods with high levels of rutin, with the preserved initial levels in the grain. The quercetin from rutin degradation in Tartary buckwheat grain is responsible in part for inhibition of α-glucosidase in the intestine, which helps to maintain normal glucose levels in the blood. Rutin and emodin have the potential for antiviral effects. Grain embryos are rich in rutin, so breeding buckwheat with the aim of producing larger embryos may be a promising strategy to increase the levels of rutin in common and Tartary buckwheat grain, and hence to improve its nutritional value.

Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models

Genomic prediction (GP) is expected to become a powerful technology for accelerating the genetic improvement of complex crop traits. Several GP models have been proposed to enhance their applications in plant breeding, including environmental effects and genotype-by-environment interactions (G×E). In this study, we proposed a two-step model for plant biomass prediction wherein environmental information and growth-related traits were considered. First, the growth-related traits were predicted by GP. Second, the biomass was predicted from the GP-predicted values and environmental data using machine learning or crop growth modeling. We applied the model to a 2-year-old field trial dataset of recombinant inbred lines of japonica rice and evaluated the prediction accuracy with training and testing data by cross-validation performed over two years. Therefore, the proposed model achieved an equivalent or a higher correlation between the observed and predicted values (0.53 and 0.65 for each year, respectively) than the model in which biomass was directly predicted by GP (0.40 and 0.65 for each year, respectively). This result indicated that including growth-related traits enhanced accuracy of biomass prediction. Our findings are expected to contribute to the spread of the use of GP in crop breeding by enabling more precise prediction of environmental effects on crop traits.

IonBreeders: bioinformatics plugins toward genomics-assisted breeding

Polymorphism information generated by next-generation sequencing (NGS) technologies has enabled applications of genome-wide markers assisted breeding. However, handling such large-scale data remains a challenge for experimental researchers and breeders, calling for the urgent development of a flexible and straightforward analysis tool for NGS data. We developed "IonBreeders" as bioinformatics plugins that implement general analysis steps from genotyping to genomic prediction. IonBreeders comprises three plugins, "ABH", "IMPUTATION", and "GENOMIC PREDICTION", for format conversion of genotyping data, preprocessing and imputation of genotyping data, and genomic prediction, respectively. "ABH" converts genotyping data derived from NGS into the ABH format, which is acceptable for our further plugins and with other breeding software tools, R/qtl, MapMaker, and AntMap. "IMPUTATION" filters out non-informative markers and imputes missing marker genotypes. In "GENOMIC PREDICTION", users can use four statistical methods based on their target trait, quantitative trait locus effect, and number of markers, and construct a prediction model for genomic selection. IonBreeders is operated in Torrent Suite, but can also handle genotype data in standard formats, e.g., Variant Call Format (VCF), by format conversion using free software or our provided scripts.

Genetic and genomic research for the development of an efficient breeding system in heterostylous self-incompatible common buckwheat (Fagopyrum esculentum)

Common buckwheat (Fagopyrum esculentum Moench; 2n = 2x = 16) is an annual crop that is cultivated widely around the world and contains an abundance of nutrients and bioactive compounds. However, the yield of buckwheat is low compared to that of other major crops, and it contains proteins that cause allergic reactions in some people. Much research has aimed to improve or eliminate these undesirable traits, and some major advances have recently been made. Here, we review recent advances in buckwheat breeding materials, tools, and methods, including the development of self-compatible lines, genetic maps, a buckwheat genome database, and an efficient breeding strategy. We also describe emerging breeding methods for high-value lines.

Present status and future perspectives of breeding for buckwheat quality

Buckwheat is an important crop globally. It has been processed into cereal grain, noodles, confectionery, bread, and fermented foods for many years. Buckwheat production and processing has supported local economies and is deeply related to the culture of some regions. Buckwheat has many unique traits as a food, with a good flavor and color. In addition, buckwheat is also a healthy food because it contains bioactive compounds that have anti-oxidative, anti-hypertensive, and anti-obesity properties. Therefore, breeding of buckwheat for quality is an important issue to be addressed. Compared to other crops, there is still a lack of basic information on quality, including bioactive compounds generation and enhancement. However, some mechanisms for modifying and improving the quality of buckwheat varieties have recently been identified. Further, some varieties with improved quality have recently been developed. In this review, we summarize the issues around buckwheat quality and review the present status and future potential of buckwheat breeding for quality.

History of the progressive development of genetic marker systems for common buckwheat

Genotyping is an essential procedure for identifying agronomically useful genes and analyzing population structure. Various types of genetic marker systems have been developed in common buckwheat (Fagopyrum esculentum Moench). In the 1980s, morphological and allozyme markers were used to construct linkage maps. Until the early 2000s, allozyme markers were widely used in population genetics studies. Such studies demonstrated that cultivated common buckwheat likely originated in the Sanjiang area of China. In the late 1990s and early 2000s, advances in PCR technology led to the development of various DNA marker systems for use in linkage mapping. However, PCR-based markers did not completely cover the genome, making genetic analysis of buckwheat challenging. The subsequent development of next generation sequencing, a game-changing technology, has allowed genome-wide analysis to be performed for many species. Indeed, 8,884 markers spanning 756 loci were recently mapped onto eight linkage groups of common buckwheat; these markers were successfully used for genomic selection to increase yield. Furthermore, draft genome sequences are now available in the Buckwheat Genome DataBase (BGDB). In this review, I summarize advances in the breeding and genetic analysis of common buckwheat based on contemporary genetic marker systems.

Current status and prospects of common buckwheat breeding in Japan

In this review, the current status and prospects of common buckwheat (Fagopyrum esculentum Moench.) breeding in Japan are summarized. The varieties that have been registered in Japan so far are introduced with details regarding their breeding source populations and breeding methods. Because the main breeding method used for common buckwheat is mass selection, the merits and demerits of this method are explored from the perspective of heritability. Although there are many breeding objectives in common buckwheat, high yield and yield stability are discussed here. Regarding the potential of common buckwheat breeding in the future, the prospects of effective exploitation of self-fertility and selection based on genomic information are examined.

Genomics-assisted breeding in minor and pseudo-cereals

Minor and pseudo-cereals, which can grow with lower input and often produce specific nutrients compared to major cereal crops, are attracting worldwide attention. Since these crops generally have a large genetic diversity in a breeding population, rapid genetic improvement can be possible by the application of genomics-assisted breeding methods. In this review, we discuss studies related to biparental quantitative trait locus (QTL) mapping, genome-wide association study, and genomic selection for minor and pseudo-cereals. Especially, we focus on the current progress in a pseudo-cereal, buckwheat. Prospects for the practical utilization of genomics-assisted breeding in minor and pseudo-cereals are discussed including the issues to overcome especially for these crops.

Important agronomic characteristics of yielding ability in common buckwheat; ecotype and ecological differentiation, preharvest sprouting resistance, shattering resistance, and lodging resistance

Common buckwheat is recognized as a healthy food because its seed contains large amounts of protein, minerals, and rutin. However, the yielding ability of common buckwheat is lower than that of other major crops. The short growing period, moisture injury, occurrence of sterile seeds due to lack of flower-visiting insects, and yield loss due to lodging and shattering cause low and unstable grain yield. Therefore, many common buckwheat breeders have tried to increase yielding ability by improving various characteristics. Recently, new breeding objectives for improving yielding ability by increasing preharvest sprouting resistance; reducing shattering loss; introducing self-compatibility; the ecotype, and semidwarf have been reported. In this review, we introduce the research on the important agronomic characteristics, preharvest sprouting resistance, ecotype and ecological differentiation, shattering resistance, and lodging resistance in common buckwheat.

Strategic enhancement of genetic gain for nutraceutical development in buckwheat: A genomics-driven perspective

Buckwheat (Fagopyrum spp.) under the family Polygonaceae is an ancient pseudocereal with stupendous but less studied nutraceutical properties. The gluten free nature of protein, balanced amino acid profile and health promoting bioactive flavonoids make it a golden crop of future. Besides a scanty basic research, not much attention has been paid to the improvement of plant type and breeding of nutraceutical traits. Scanning of scientific literature indicates that adequate genetic variation exists for agronomic and nutritional traits in mainstream and wild gene pool of buckwheat. However, the currently employed conventional approaches together with poorly understood genetic mechanisms restrict effective utilization of the existing genetic variation in nutraceutical breeding of buckwheat. The latest trends in buckwheat genomics, particularly avalilabity of draft genome sequences for both the cultivated species (F. esculentum and F.tataricum) hold immense potential to overcome these limitations. Utilizing the transgenic hairy rot cultures, role of various transcription factors and gene families have been deduced in production and biosynthesis of bioactive flavonoids. Further, the acquisition of high-density genomics data coupled with the next-generation phenotyping will certainly improve our understanding of underlying genetic regulation of nutraceutical traits. The present paper highlights the application of multilayered omics interventions for tailoring a nutrient rich buckwheat cultivar and nutraceutical product development.

Revisiting the versatile buckwheat: reinvigorating genetic gains through integrated breeding and genomics approach

Emerging insights in buckwheat molecular genetics allow the integration of genomics driven breeding to revive this ancient crop of immense nutraceutical potential from Asia. Out of several thousand known edible plant species, only four crops-rice, wheat, maize and potato provide the largest proportion of daily nutrition to billions of people. While these crops are the primary supplier of carbohydrates, they lack essential amino acids and minerals for a balanced nutrition. The overdependence on only few crops makes the future cropping systems vulnerable to the predicted climate change. Diversifying food resources through incorporation of orphan or minor crops in modern cropping systems is one potential strategy to improve the nutritional security and mitigate the hostile weather patterns. One such crop is buckwheat, which can contribute to the agricultural sustainability as it grows in a wide range of environments, requires relatively low inputs and possess balanced amino acid and micronutrient profiles. Additionally, gluten-free nature of protein and nutraceutical properties of secondary metabolites make the crop a healthy alternative of wheat-based diet in developed countries. Despite enormous potential, efforts for the genetic improvement of buckwheat are considerably lagged behind the conventional cereal crops. With the draft genome sequences in hand, there is a great scope to speed up the progress of genetic improvement of buckwheat. This article outlines the state of the art in buckwheat research and provides concrete perspectives how modern breeding approaches can be implemented to accelerate the genetic gain. Our suggestions are transferable to many minor and underutilized crops to address the issue of limited genetic gain and low productivity.

Gene flow signature in the S-allele region of cultivated buckwheat

BACKGROUND

Buckwheat (Fagopyrum esculentum Moench.) is an annual crop that originated in southern China. The nutritious seeds are used in cooking much like cereal grains. Buckwheat is an outcrossing species with heteromorphic self-incompatibility due to its dimorphic (i.e., short- and long-styled) flowers and intra-morph infertility. The floral morphology and intra-morph incompatibility are both determined by a single S locus. Plants with short-styled flowers are heterozygous (S/s) and plants with long-styled flowers are homozygous recessive (s/s) at this locus, and the S/S genotype is not found. Recently, we built a draft genome assembly of buckwheat and identified the 5.4-Mb-long S-allele region harbored by short-styled plants. In this study, the first report on the genome-wide diversity of buckwheat, we used a genotyping-by-sequencing (GBS) dataset to evaluate the genome-wide nucleotide diversity within cultivated buckwheat landraces worldwide. We also investigated the utility of the S-allele region for phylogenetic analysis of buckwheat.

RESULTS

Buckwheat showed high nucleotide diversity (0.0065), comparable to that of other outcrossing plants, based on a genome-wide simple nucleotide polymorphism (SNP) analysis. Phylogenetic analyses based on genome-wide SNPs showed that cultivated buckwheat comprises two groups, Asian and European, and revealed lower nucleotide diversity in the European group (0.0055) and low differentiation between the Asian and European groups. The nucleotide diversity (0.0039) estimated from SNPs in the S-allele region is lower than that in genome-wide SNPs. Phylogenetic analysis based on this region detected three diverged groups, S-1, S-2, and S-3.

CONCLUSION

The SNPs detected using the GBS dataset were effective for elucidating the evolutionary history of buckwheat, and led to the following conclusions: (1) the low nucleotide diversity of the entire genome in the European group and low differentiation between the Asian and European groups suggested genetic bottlenecks associated with dispersion from Asia to Europe, and/or recent intensified cultivation and selection in Europe; and (2) the high diversification in the S-allele region was indicative of gene flows from wild to cultivated buckwheat, suggesting that cultivated buckwheat may have multiple origins.

Description of grain weight distribution leading to genomic selection for grain-filling characteristics in rice

Grain-filling ability is one of the factors that controls grain yield in rice (Oryza sativa L.). We developed a method for describing grain weight distribution, which is the probability density function of single grain weight in a panicle, using 128 Japanese rice varieties. With this method, we quantitively analyzed genotypic differences in grain-filling ability and used the grain weight distribution parameters for genomic prediction subject to genetic improvement in grain yield in rice. The novel description method could represent the observed grain weight distribution with five genotype-specific parameters of a mixture of two gamma distributions. The estimated genotype-specific parameters representing the proportion of filled grains had applicability to explain the grain filling ability of genotypes comparable to that of sink-filling rate and the conventionally measured proportion of filled grains, which suggested the efficiency and flexibility of grain weight distribution parameters to handle several genotypes. We revealed that perfectly filled grains have to be prioritized over partially filled grains for the optimum allocation of the source of yield in a panicle, from the analysis for obtaining an ideal shape of grain weight distribution. We conducted genomic prediction of grain weight distribution considering five genotype-specific parameters of the distribution as phenotypes relating to grain filling ability. The proportion of filled grains, average weight of filled grains, and variance of filled grain weight, which were considered to control grain yield to a certain degree, were predicted with accuracies of 0.30, 0.28, and 0.53, respectively. The proposed description method of grain weight distribution facilitated not only the investigation of the optimum allocation of nutrients in a panicle for realizing high grain-filling ability, but also allowed genomic selection of grain weight distribution.

Early Selection Enabled by the Implementation of Genomic Selection in Coffea arabica Breeding

Genomic Selection (GS) has allowed the maximization of genetic gains per unit time in several annual and perennial plant species. However, no GS studies have addressed Coffea arabica, the most economically important species of the genus Coffea. Therefore, this study aimed (i) to evaluate the applicability and accuracy of GS in the prediction of the genomic estimated breeding value (GEBV); (ii) to estimate the genetic parameters; and (iii) to evaluate the time reduction of the selection cycle by GS in Arabica coffee breeding. A total of 195 Arabica coffee individuals, belonging to 13 families in generation of F₂, susceptible backcross and resistant backcross, were phenotyped for 18 agronomic traits, and genotyped with 21,211 SNP molecular markers. Phenotypic data, measured in 2014, 2015, and 2016, were analyzed by mixed models. GS analyses were performed by the G-BLUP method, using the RKHS (Reproducing Kernel Hilbert Spaces) procedure, with a Bayesian algorithm. Heritabilities and selective accuracies were estimated, revealing moderate to high magnitude for most of the traits evaluated. Results of GS analyses showed the possibility of reducing the cycle time by 50%, maximizing selection gains per unit time. The effect of marker density on GS analyses was evaluated. Genomic selection proved to be promising for C. arabica breeding. The agronomic traits presented high complexity for they are controlled by several QTL and showed low genomic heritabilities, evidencing the need to incorporate genomic selection methodologies to the breeding programs of this species.