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Aquaculture represents the fastest-growing global food production sector, as it has become an essential component of the global food supply. China has the world's largest aquaculture industry in terms of production volume. However, the sustainable development of fish culture is hindered by several concerns, including germplasm degradation and disease outbreaks. The practice of genomic breeding, which relies heavily on genome information and genotypephenotype relationships, has significant potential for increasing the efficiency of aquaculture production. In 2014, the completion of the genome sequencing and annotation of the Chinese tongue sole signified the beginning of the fish genomics era in China. Since then, domestic researchers have made dramatic progress in functional genomic studies. To date, the genomes of more than 60 species of fish in China have been assembled and annotated. Based on these reference genomes, evolutionary, comparative, and functional genomic studies have revolutionized our understanding of a wide range of biologically and economically important traits of fishes, including growth and development, sex determination, disease resistance, metamorphosis, and pigmentation. Furthermore, genomic tools and breeding techniques such as SNP arrays, genomic selection, and genome editing have greatly accelerated genetic improvement through the incorporation of functional genomic information into breeding activities. This review aims to summarize the current status, advances, and perspectives of the genome resources, genomic study of important traits, and genomic breeding techniques of fish in China. The review will provide aquaculture researchers, fish breeders, and farmers with updated information concerning fish genomic research and breeding technology. The summary will help to promote the genetic improvement of production traits and thus will support the sustainable development of fish aquaculture. [ABSTRACT FROM AUTHOR]

Rapeseed (Brassica napus) is an oil crop grown worldwide, making it a key plant species in molecular breeding research. However, the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy. Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest. In this study, 588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T. The platform comprised 54,765, with 54,058 resequenced markers from the pan-genome, and 855 variant trait-associated markers for 12 agronomic traits. The capture quality of BnaPan50T was demonstrated well in 12 typical accessions. Compared with a conventional genotyping array, BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes, promising wide application. Target capture sequencing and whole-genome resequencing in 90 doubled-haploid lines yielded 60% specificity, 78% uniformity within tenfold coverage range, and 93% genotyping accuracy for the platform. BnaPan50T was used to construct a genetic map for quantitative trait loci (QTL) mapping, identify 21 unique QTL, and predict several candidate genes for yield-related traits in multiple environments. A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources. This study provides genomics resources to support target capture sequencing, genetic analysis and genomic breeding of rapeseed.

The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomicsassisted breeding. [ABSTRACT FROM AUTHOR]

Knowledge of rice (Oryza sativa L.) genes and various DNA markers can be used in genomic breeding programs aimed at developing improved elite rice cultivars. We used an efficient genomic breeding approach to pyramid four resistance genes (Pi2, Xa23, Bph14, and Bph15) in the popular photoperiod- and thermo-sensitive genic male sterile (PTGMS) rice line Feng39S. We performed foreground selection for the target genes, followed by recombinant selection and background selection. This process reduced the sizes of the genomic segments harboring the target genes (566.8 kb for Pi2, 1143.9 kb for Xa23, 774.7 kb for Bph14, and 1574.9 kb for Bph15) and accelerated the recovery of the recurrent parent genome to proportions ranging from 98.77% to 99.16%, thus resulting in four near-isogenic lines. To assemble the four resistance genes in Feng39S, we performed a double-way cross combined with foreground and background selection to generate two improved lines of Feng39S (Pi2 + Xa23 + Bph14 + Bph15) with a recurrent parent genome recovery of 98.98%. The two lines showed agronomic performance, grain quality, and fertility–sterility transition characteristics similar to those of the original Feng39S line. The newly developed PTGMS lines and corresponding hybrid combinations were resistant to various field blast isolates and seven representative isolates of bacterial blight. At the seedling stage, the lines also showed resistance against brown planthopper. This study provides an efficient and accurate genomic breeding approach for introducing desirable traits into PTGMS lines.

Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high‐impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome‐based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics‐enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry. [ABSTRACT FROM AUTHOR]

Grain quality has become one of the foci in rice breeding worldwide since it is crucial for farmers, millers and consumers. Previous studies have revealed that rice gain quality is mainly determined with several major characteristics including milling, physical appearance, eating and cooking, sensory and nutritional value. In genetics, rice grain quality is a complex trait controlled by polygene/QTL. Better understanding the mechanism underlying the grain quality is fundamental for developing new breeding strategies. Therefore, abundant studies had been conducted to discover the factors that control the quality traits, and led to dozens of QTL identified and several major genes cloned. This has enabled development of the functional markers to facilitate selection of the complex traits. But breeding for rice varieties with desired grain quality needs to pyramid multiple and beneficial loci or alleles, some of which are still untapped. In this chapter, we first summarize the literatures on rice grain quality traits and the relevant phenotyping approaches, and then review the progress in genetic dissection of these traits. This review also presented the breeding attempts using marker-assisted selection, genomics-assisted breeding approaches, as well as genome editing technologies, and finally provided innovative insights into the future of rice grain quality breeding by using the modern technology with integration of machine learning and genomic selection. [ABSTRACT FROM AUTHOR]

Producing sufficient food with finite resources to feed the growing global population while having a smaller impact on the environment has always been a great challenge. Here, we review the concept and practices of Green Super Rice (GSR) that have led to a paradigm shift in goals for crop genetic improvement and models of food production for promoting sustainable agriculture. The momentous achievements and global deliveries of GSR have been fueled by the integration of abundant genetic resources, functional gene discoveries, and innovative breeding techniques with precise gene and whole-genome selection and efficient agronomic management to promote resource-saving, environmentally friendly crop production systems. We also provide perspectives on new horizons in genomic breeding technologies geared toward delivering green and nutritious crop varieties to further enhance the development of green agriculture and better nourish the world population. Green Super Rice is defined not only as a new type of rice cultivar but also as an innovative model of crop production for resource-saving, environmentally-friendly agriculture. Green Super Rice has contributed to a paradigm shift in crop genetic improvement and food production to better nourish the world population while maintaining a healthier environment. [ABSTRACT FROM AUTHOR]

Abstract The current pace of crop improvement is inadequate to feed the burgeoning human population by 2050. Higher, more stable, and sustainable crop production is required against a backdrop of drought stress, which causes significant losses in crop yields. Tailoring crops for drought adaptation may hold the key to address these challenges and provide resilient production systems for future harvests. Understanding the genetic and molecular landscape of the functionality of alleles associated with adaptive traits will make designer crop breeding the prospective approach for crop improvement. Here, we highlight the potential of genomics technologies combined with crop physiology for high‐throughput identification of the genetic architecture of key drought‐adaptive traits and explore innovative genomic breeding strategies for designing future crops.

Key message: An integrated research approach to ensure sustainable rice yield increase of a crop grown by 25% of the world's farmers in 10% of cropland is essential for global food security. Rice, being a global staple crop, feeds about 56% of the world population and sustains 40% of the world's poor. At ~ $200 billion, it also accounts for 13% of the annual crop value. With hunger and malnutrition rampant among the poor, rice research for development is unique in global food and nutrition security. A systems-based, sustainable increase in rice quantity and quality is imperative for environmental and biodiversity benefits. Upstream 'discovery' through biotechnology, midstream 'development' through breeding and agronomy, downstream 'dissemination and deployment' must be 'demand-driven' for 'distinct socio-economic transformational impacts'. Local agro-ecology and livelihood nexus must drive the research agenda for targeted benefits. This necessitates sustained long-term investments by government, non-government and private sectors to secure the future food, nutrition, environment, prosperity and equity status. [ABSTRACT FROM AUTHOR]

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, "Thompson Seedless" (TS, syn. "Sultania") and "Black Monukka" (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to "Sultania." Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11 S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding. [Display omitted] • Integrative genomics investigates the polygenic basis of grapevine seedlessness • Comparative genomics identified SVs specific to seedless grapes • Introgression rather than convergent evolution driving evolution of seed abortion • Machine learning-based GS predicts grape seedlessness with ∼97% accuracy Wang et al. investigate the importance of structural variation, evolutionary origin, and polygenic basis of seedlessness in grapevine using integrative genomics. Their machine learning-based genomic prediction achieves a prediction accuracy of ∼97% for seedlessness. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium spp.) is the most important natural fiber crop worldwide. The diversity of Gossypium species also provides an ideal model for investigating evolution and domestication of polyploids. However, the huge and complex cotton genome hinders genomic research. Technical advances in high-throughput sequencing and bioinformatics analysis have now largely overcome these obstacles, bringing about a new era of cotton genomics. Here, we review recent progress in Gossypium genomics based on whole genome sequencing, resequencing, and comparative genomics, which have provided insights about the genomic basis of fiber biogenesis and the landscape of cotton functional genomics. We address current challenges and present multidisciplinary genomics-enabled breeding strategies covering the breadth of high fiber yield, quality, and environmental resilience for future cotton breeding programs. Cotton is an important natural fiber crop cultivated worldwide that also provides an ideal model for investigating evolution and domestication of polyploids Combinations of the latest technologies, such as optical mapping, high-throughput chromosome conformation capture (Hi-C), and Pacific Biosciences (PacBio) long-reads, have been used to generate multiple high-quality reference genomes of diploid and allotetraploid cotton. Comparative population genomics illuminated the genetic history of cotton domestication and identified the genomic variation determining fiber yield, quality, and stress resistance. [ABSTRACT FROM AUTHOR]

The African continent is home to diverse populations of livestock breeds adapted to harsh environmental conditions with more than 70% under traditional systems of management. Animal productivity is less than optimal in most cases and is faced with numerous challenges including limited access to adequate nutrition and disease management, poor institutional capacities and lack of adequate government policies and funding to develop the livestock sector. Africa is home to about 1.3 billion people and with increasing demand for animal proteins by an ever growing human population, the current state of livestock productivity creates a significant yield gap for animal products. Although a greater section of the population, especially those living in rural areas depend largely on livestock for their livelihoods; the potential of the sector remains underutilized and therefore unable to contribute significantly to economic development and social wellbeing of the people. With current advances in livestock management practices, breeding technologies and health management, and with inclusion of all stakeholders, African livestock populations can be sustainably developed to close the animal protein gap that exists in the continent. In particular, advances in gene technologies, and application of genomic breeding in many Western countries has resulted in tremendous gains in traits like milk production with the potential that, implementation of genomic selection and other improved practices (nutrition, healthcare, etc.) can lead to rapid improvement in traits of economic importance in African livestock populations. The African livestock populations in the context of this review are limited to cattle, goat, pig, poultry, and sheep, which are mainly exploited for meat, milk, and eggs. This review examines the current state of livestock productivity in Africa, the main challenges faced by the sector, the role of various stakeholders and discusses in-depth strategies that can enable the application of genomic technologies for rapid improvement of livestock traits of economic importance.

Rice (Oryza sativa L.) is one of the most important crops worldwide, but its growth and production can be severely affected by climate change. As a tropical species, rice is in general vulnerable to the adverse effects of low temperature. To cope with or adapt to cold stress condition, rice has evolved elaborate regulatory mechanisms under both natural and artificial selection. Over the past few decades, intensive research efforts have been focused on abiotic stress biology in rice with genetic, genomic, and molecular strategies, disclosing a series of potential genetic determinants and mechanisms controlling cold stress tolerance. Here, we review cold tolerance (CT)-related quantitative trait loci (QTLs) identified by linkage and association mapping, together with key genes involved in cold sensing, signaling, and response. More importantly, recent studies have shown that CT-related QTLs/genes can be employed in genomic breeding aiming at developing cold-tolerant rice. Overall, the recent research progresses in understanding the complex genetic and molecular mechanisms of CT provide a substantial basis for CT improvement in rice. [ABSTRACT FROM AUTHOR]

The African continent is home to diverse populations of livestock breeds adapted to harsh environmental conditions with more than 70% under traditional systems of management. Animal productivity is less than optimal in most cases and is faced with numerous challenges including limited access to adequate nutrition and disease management, poor institutional capacities and lack of adequate government policies and funding to develop the livestock sector. Africa is home to about 1.3 billion people and with increasing demand for animal proteins by an ever growing human population, the current state of livestock productivity creates a significant yield gap for animal products. Although a greater section of the population, especially those living in rural areas depend largely on livestock for their livelihoods; the potential of the sector remains underutilized and therefore unable to contribute significantly to economic development and social wellbeing of the people. With current advances in livestock management practices, breeding technologies and health management, and with inclusion of all stakeholders, African livestock populations can be sustainably developed to close the animal protein gap that exists in the continent. In particular, advances in gene technologies, and application of genomic breeding in many Western countries has resulted in tremendous gains in traits like milk production with the potential that, implementation of genomic selection and other improved practices (nutrition, healthcare, etc.) can lead to rapid improvement in traits of economic importance in African livestock populations. The African livestock populations in the context of this review are limited to cattle, goat, pig, poultry, and sheep, which are mainly exploited for meat, milk, and eggs. This review examines the current state of livestock productivity in Africa, the main challenges faced by the sector, the role of various stakeholders and discusses in-depth strategies that can enable the application of genomic technologies for rapid improvement of livestock traits of economic importance. [ABSTRACT FROM AUTHOR]

Barley is the fourth most important cereal crop and has been domesticated and cultivated for more than 10,000 years. Breeding climate-smart and stress-tolerant cultivars is considered the most suitable way to accelerate barley improvement. However, the conventional breeding framework needs to be changed to facilitate genomics-based breeding of barley. The continuous progress in genomics has opened up new avenues and tools that are promising for making barley breeding more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing to delineate breeding have led to the development of more efficient barley cultivars. Genetic analysis, such as QTL mapping and GWAS studies using sequencing approaches, have led to the identification of molecular markers, genomic regions and novel genes associated with the agronomic traits of barley. Furthermore, SNP marker technologies and haplotype-based GWAS have become the most applied methods for supporting molecular breeding in barley. The genetic information is also used for high-efficiency gene editing by means of CRISPR-Cas9 technology, the best example of which is the cv. Golden Promise. In this review, we summarize the genomic databases that have been developed for barley and explain how the genetic resources of the reference genome, the available state-of-the-art bioinformatics tools, and the most recent assembly of a barley pan-genome will boost the genomics-based breeding for barley improvement.

Summary: Improvements in living standards have resulted in consumers having higher expectations for chicken meat quality. This is particularly true in Asia, where there is high consumer preference for local breeds. Nothing is presently known about the effectiveness of using genomic selection (GS) strategies in chickens to genetically improve meat quality traits that cannot be measured in living potential parents. In this study, 724 Beijing‐You chickens were used as a training population; all were genotyped using Illumina 60K SNP chips, and intramuscular fat content in breast muscle (IMFbr) was measured. Birds in the GS line were selected based on genomic estimated breeding values, IMFbr being the sole trait. Genetic progress in one generation was compared to that from conventional family‐based selection, and both were evaluated against random‐bred controls. Results showed that relative to the random‐bred controls, IMF percentage was improved 9.62% using GS, comparable to the 10.38% improvement using family‐based selection. We quantified the effectiveness of GS when applied to a meat quality trait with low heritability in chickens. We plan to introduce custom SNP chips, appropriate for native chicken breeds in China, to assist in applying GS in local breeding and accelerate genetic gain. [ABSTRACT FROM AUTHOR]

In this paper we first provide a brief review of main results from our previously published studies on genome-wide gene expression (transcriptomics) in donor and recipient cattle used in in vitro production (IVP) of embryos and embryo transfer (ET). Then, we present novel results from applying integrative systems genomics and biological analyses where transcriptomics data are combined with genomic data in both donor and recipient cattle to map expression quantitative trait loci (eQTLs). The eQTLs are genetic markers that can regulate or control the expression of genes in the entire genome, via complex molecular mechanisms, and thus can act as a powerful tool for genomic and gene-assisted selection. We identified significant eQTLs potentially controlling the expression of 13 candidate genes for donor cow quality (IVP parameters; e.g. cyclin B1 (CCNB1), outer dense fiber of sperm tails 2 like (ODF2L)) and 19 candidate genes for recipient cows quality (endometrial receptivity; e.g. ER membrane protein complex subunit 9 (EMC9), mannosidase beta (MANBA), peptidase inhibitor 16 (PI16)). Annotation and colocation of detected eQTLs show that some of the eQTLs are in the same genomic regions previously reported as QTLs for reproduction-related traits. However, eQTLs and the candidate genes identified should be further validated in larger populations before implementation as genetic markers or used in genomic selection for improving IVP and ET performance. [ABSTRACT FROM AUTHOR]

A significant gap exists between animal production and world's population demand. Although conventional breeding methods have been effectual for selection of animal populations on many traits of economic importance, with these methods, the accuracy of breeding value always remains questionable. Simulation and experimental results suggest that breeding values can be predicted with high accuracy by genomic selection for young animals without own performance. Genomic selection is a type of marker-assisted selection in which genetic markers covering the whole genome are used so that all quantitative trait loci are in linkage disequilibrium with at least one marker. The possibility to select animals at an early stage allows defining new breeding strategies aiming at boosting genetic progress while reducing costs. Genomic selection is the future of livestock breeding companies; it improves the genetic gain by decreasing genetic interval and improving reliability. Further research is required to improve the accuracy of genomic estimated value and manage long-term genetic gain. The aim of this review was to provide an overview of the developments of genomic selection and its application in animal breeding. [ABSTRACT FROM AUTHOR]

The advances in genotyping technology provide an opportunity to use genomic tools in crop breeding. As compared to field selections performed in conventional breeding programmes, genomics-based genotype screen can potentially reduce number of breeding cycles and more precisely integrate target genes for particular traits into an ideal genetic background. We developed a whole-genome single nucleotide polymorphism ( SNP) array, RICE6K, based on Infinium technology, using representative SNPs selected from more than four million SNPs identified from resequencing data of more than 500 rice landraces. RICE6K contains 5102 SNP and insertion-deletion (InDel) markers, about 4500 of which were of high quality in the tested rice lines producing highly repeatable results. Forty-five functional markers that are located inside 28 characterized genes of important traits can be detected using RICE6K. The SNP markers are evenly distributed on the 12 chromosomes of rice with the average density of 12 SNPs per 1 Mb and can provide information for polymorphisms between indica and japonica subspecies as well as varieties within indica and japonica groups. Application tests of RICE6 K showed that the array is suitable for rice germplasm fingerprinting, genotyping bulked segregating pools, seed authenticity check and genetic background selection. These results suggest that RICE6K provides an efficient and reliable genotyping tool for rice genomic breeding. [ABSTRACT FROM AUTHOR]

Barley is the fourth most important cereal crop and has been domesticated and cultivated for more than 10,000 years. Breeding climate-smart and stress-tolerant cultivars is considered the most suitable way to accelerate barley improvement. However, the conventional breeding framework needs to be changed to facilitate genomics-based breeding of barley. The continuous progress in genomics has opened up new avenues and tools that are promising for making barley breeding more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing to delineate breeding have led to the development of more efficient barley cultivars. Genetic analysis, such as QTL mapping and GWAS studies using sequencing approaches, have led to the identification of molecular markers, genomic regions and novel genes associated with the agronomic traits of barley. Furthermore, SNP marker technologies and haplotype-based GWAS have become the most applied methods for supporting molecular breeding in barley. The genetic information is also used for high-efficiency gene editing by means of CRISPR-Cas9 technology, the best example of which is the cv. Golden Promise. In this review, we summarize the genomic databases that have been developed for barley and explain how the genetic resources of the reference genome, the available state-of-the-art bioinformatics tools, and the most recent assembly of a barley pan-genome will boost the genomics-based breeding for barley improvement. [ABSTRACT FROM AUTHOR]

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965−85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture. [ABSTRACT FROM AUTHOR]