Genomics-assisted Breeding Research Articles

Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding

Key messageLarge genetic improvement can be achieved by simultaneous genomic selection for grain yield and protein content when combining different breeding strategies in the form of selection indices.Genomic selection has been implemented in many national and international breeding programmes in recent years. Numerous studies have shown the potential of this new breeding tool; few have, however, taken the simultaneous selection for multiple traits into account that is though common practice in breeding programmes. The simultaneous improvement in grain yield and protein content is thereby a major challenge in wheat breeding due to a severe negative trade-off. Accordingly, the potential and limits of multi-trait selection for this particular trait complex utilizing the vast phenotypic and genomic data collected in an applied wheat breeding programme were investigated in this study. Two breeding strategies based on various genomic-selection indices were compared, which (1) aimed to select high-protein genotypes with acceptable yield potential and (2) develop high-yielding varieties, while maintaining protein content. The prediction accuracy of preliminary yield trials could be strongly improved when combining phenotypic and genomic information in a genomics-assisted selection approach, which surpassed both genomics-based and classical phenotypic selection methods both for single trait predictions and in genomic index selection across years. The employed genomic selection indices mitigated furthermore the negative trade-off between grain yield and protein content leading to a substantial selection response for protein yield, i.e. total seed nitrogen content, which suggested that it is feasible to develop varieties that combine a superior yield potential with comparably high protein content, thus utilizing available nitrogen resources more efficiently.

Epistatic interactions of major effect drought QTLs with genetic background loci determine grain yield of rice under drought stress

Epistatic interactions of QTLs with the genetic background and QTL-QTL interaction plays an important role in the phenotypic performance of introgression lines developed through genomic-assisted breeding (GAB). In this context, NIL pairs developed with various drought QTL (qDTY) combinations in the genetic background of IR64, TDK1-Sub1 and Savitri backgrounds were utilized to study the interactions. Multi-season phenotyping of NIL pairs harboring similar qDTY combinations provided contrasting performance for grain yield under drought (RS) (classified as high and low yielding NILs) but nearly similar performance under non-stress(NS) conditions. Genome wide genotyping data revealed a total of 16, 5 and 6 digenic interactions were detected under RS conditions in low yielding NILs of IR64, TDK1-Sub1 and Savitri respectively while no significant interaction was found in high yielding NILs under RS and NS conditions in any of the genetic backgrounds used in this study. It is evident from this study that existence of epistatic interactions between QTLs with genetic background, QTL-QTL interaction and interactions among background markers loci itself on different chromosomes influences the expression of a complex trait such as grain yield under drought. The generated information will be useful in all the GAB program of across the crops for precise breeding.

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984\xd7Opata reference populations provide insights into wheat structural diversity

Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961 cM, harboring 3,634 and 6,580 markers, respectively. Using imputation, we added 43,013 and 86,042 markers to the SynOpRIL and SynOpDH maps. We observed preferential recombination in telomeric regions and reduced recombination in pericentromeric regions. Recombination rates varied between subgenomes, with the D genomes of the two populations exhibiting the highest recombination rates of 0.26–0.27 cM/Mb. QTL mapping identified two additive and three epistatic loci associated with crossover number. Additionally, we used published POPSEQ data from SynOpDH to explore the structural variation in W7984 and Opata. We found that chromosome 5AS is missing from W7984. We also found 2,332 variations larger than 100 kb. Structural variants were more abundant in distal regions, and overlapped 9,196 genes. The two maps provide a resource for trait mapping and genomic-assisted breeding.

ABC Transporter-Mediated Transport of Glutathione Conjugates Enhances Seed Yield and Quality in Chickpea.

The identification of functionally relevant molecular tags is vital for genomics-assisted crop improvement and enhancement of seed yield, quality, and productivity in chickpea (Cicer arietinum). The simultaneous improvement of yield/productivity as well as quality traits often requires pyramiding of multiple genes, which remains a major hurdle given various associated epistatic and pleotropic effects. Unfortunately, no single gene that can improve yield/productivity along with quality and other desirable agromorphological traits is known, hampering the genetic enhancement of chickpea. Using a combinatorial genomics-assisted breeding and functional genomics strategy, this study identified natural alleles and haplotypes of an ABCC3-type transporter gene that regulates seed weight, an important domestication trait, by transcriptional regulation and modulation of the transport of glutathione conjugates in seeds of desi and kabuli chickpea. The superior allele/haplotype of this gene introgressed in desi and kabuli near-isogenic lines enhances the seed weight, yield, productivity, and multiple desirable plant architecture and seed-quality traits without compromising agronomic performance. These salient findings can expedite crop improvement endeavors and the development of nutritionally enriched high-yielding cultivars in chickpea.

Construction of an integrated genetic linkage map and detection of quantitative trait loci for ascochyta blight resistance in faba bean (Vicia faba L.)

Ascochyta blight (AB), caused by Ascochyta fabae Speg., is an economically important disease that has been reported in most of the faba bean growing regions worldwide. Breeding for resistance is the most environmentally acceptable and economically feasible method to address the disease, for which a detailed understanding of the genetic basis of AB resistance is required. In the current study, a genetic linkage map based on single nucleotide polymorphisms was developed from Nura × Farah recombinant inbred line (RIL) population and contained 705 loci across 1021.8 cM. The marker information from Nura × Farah map was combined with previously published maps to generate an integrated map consisting of 1850 markers distributed across six linkage groups, with a cumulative length of 1439 cM at an average density of one marker per 0.80 cM. Parents and RIL progeny were screened for AB with two strains of A. fabae and quantitative trait locus analysis identified two genomic regions explaining up to 49% of the phenotypic variation. Evaluation of linked markers in a diverse set of faba bean genotypes validated their utility for marker assisted selection. The availability of high density genetic linkage map along with the linked markers for AB resistance provides opportunities for genomics-assisted breeding, map based gene isolation and comparative genetics in faba bean.

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL-seq approach in cultivated peanut (Arachis hypogaea L.).

SummaryCultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.

Genotype by Sequencing Method and Its Application for Crop Improvement (A Review)

Genotype by sequencing (GBS) is a next generation sequencing based method that takes advantage of reduced representation to enable genotyping of large numbers of individuals at a large number of SNP markers. It is relatively straightforward, robust, and cost-effective method to reduce problems in crop caused by a large genome size, reduced representation libraries are produced using a restriction enzyme that targets genomic regions while multiplexing with barcodes reduces the cost for individual sample. Several types of molecular markers, such as single nucleotide polymorphism (SNP), have been identified and effectively used in plant breeding. The application of next-generation sequencing (NGS) technologies has led to remarkable advances in whole genome sequencing, which provides ultra- throughput sequences to revolutionize plant genotyping and breeding. The GBS approach includes the digestion of genomic DNA with restriction enzymes followed by the ligation of barcode adapter, PCR amplification and sequencing of the amplified DNA pool on a single lane of flow cells. GBS has been successfully used in implementing genome-wide association study (GWAS), genomic diversity study, QTL mapping, genetic linkage analysis, molecular marker discovery and genomic selection under a large scale of plant breeding programs. GBS will have broad application in genomics-assisted plant breeding programs.

Genome-wide association study for an efficient selection of Fusarium head blight resistance in winter triticale

Fusarium head blight (FHB) is one of the most serious diseases in small-grain cereals including triticale (× Triticosecale Wittmack). The disease reduces yield and accumulates mycotoxins which are harmful to human and animal health. Triticale grain is almost exclusively used on-farm in feed formulations for swine and other animals, and swine is the most susceptible farm animal to Fusarium mycotoxins. In order to evaluate the potential of genomics-assisted breeding to FHB, we performed the first genome-wide association study for FHB resistance in triticale. QTL for FHB resistance were identified on chromosomes 2A, 2B, 5B and 3R with an explained genotypic variance ranging from 0.28 to 30.23% and a total explained genetic variance of 56.64%. A QTL on chromosome 3R that explained 15.38% of the genotypic variance was identified for the first time. Association mapping was complemented by genome-wide prediction, which yielded a high prediction accuracy of 0.78 for FHB resistance when weighted genomic selection was performed. Collectively our findings highlight the potential of genomics-assisted approaches to improve Fusarium resistance in triticale in early generations.

Genotyping-by-sequencing based genetic mapping reveals large number of epistatic interactions for stem rot resistance in groundnut.

Genetic mapping identified large number of epistatic interactions indicating the complex genetic architecture for stem rot disease resistance. Groundnut (Arachis hypogaea) is an important global crop commodity and serves as a major source of cooking oil, diverse confectionery preparations and livestock feed. Stem rot disease caused by Sclerotium rolfsii is the most devastating disease of groundnut and can cause up to 100% yield loss. Genomic-assisted breeding (GAB) has potential for accelerated development of stem rot resistance varieties in short period with more precision. In this context, linkage analysis and quantitative trait locus (QTL) mapping for resistance to stem rot disease was performed in a bi-parental recombinant inbred line population developed from TG37A (susceptible) × NRCG-CS85 (resistant) comprising of 270 individuals. Genotyping-by-sequencing approach was deployed to generate single nucleotide polymorphism (SNP) genotyping data leading to development of a genetic map with 585 SNP loci spanning map distance of 2430cM. QTL analysis using multi-season phenotyping and genotyping data could not detect any major main-effect QTL but identified 44 major epistatic QTLs with phenotypic variation explained ranging from 14.32 to 67.95%. Large number interactions indicate the complexity of genetic architecture of resistance to stem rot disease. A QTL of physical map length 5.2Mb identified on B04 comprising 170 different genes especially leucine reach repeats, zinc finger motifs and ethyleneresponsive factors, etc., was identified. The identified genomic regions and candidate genes will further validate and facilitate marker development to deploy GAB for developing stem rot disease resistance groundnut varieties.

Exploring and exploiting the genetic variation of Fusarium head blight resistance for genomic-assisted breeding in the elite durum wheat gene pool

Key messageGenomic selection had a higher selection response for FHB resistance than phenotypic selection, while association mapping identified major QTL on chromosome 3B unaffected by plant height and flowering date.Fusarium head blight (FHB) is one of the most destructive diseases of durum wheat. Hence, minimizing losses in yield, quality and avoiding contamination with mycotoxins are of pivotal importance, as durum wheat is mostly used for human consumption. While growing resistant varieties is the most promising approach for controlling this fungal disease, FHB resistance breeding in durum wheat is hampered by the limited variation in the elite gene pool and difficulties in efficiently combining the numerous small-effect resistance quantitative trait loci (QTL) in the same line. We evaluated an international collection of 228 genotyped durum wheat cultivars for FHB resistance over 3 years to investigate the genetic architecture and potential of genomic-assisted breeding for FHB resistance in durum wheat. Plant height was strongly positively correlated with FHB resistance and led to co-localization of plant height and resistance QTL. Nevertheless, a major QTL on chromosome 3B independent of plant height was identified in the same chromosomal interval as reported for the prominent hexaploid resistance QTL Fhb1, though haplotype analysis highlighted the distinctiveness of both QTL. Comparison between phenotypic and genomic selection for FHB resistance revealed a superior prediction ability of the former. However, simulated selection experiments resulted in higher selection responses when using genomic breeding values for early generation selection. An earlier identification of the most promising lines and crossing parents was feasible with a genomic selection index, which suggested a much faster short-term population improvement than previously possible in durum wheat, complementing long-term strategies with exotic resistance donors.

Hotspots in the genomic architecture of field drought responses in wheat as breeding targets

Wheat can adapt to most agricultural conditions across temperate regions. This success is the result of phenotypic plasticity conferred by a large and complex genome composed of three homoeologous genomes (A, B, and D). Although drought is a major cause of yield and quality loss in wheat, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Here, we addressed this by utilizing an interdisciplinary approach involving field water status phenotyping, sampling, and gene expression analyses. Overall, changes at the transcriptional level were reflected in plant spectral traits amenable to field-level physiological measurements, although changes in photosynthesis-related pathways were found likely to be under more complex post-transcriptional control. Examining homoeologous genes with a 1:1:1 relationship across the A, B, and D genomes (triads), we revealed a complex genomic architecture for drought responses under field conditions, involving gene homoeolog specialization, multiple gene clusters, gene families, miRNAs, and transcription factors coordinating these responses. Our results provide a new focus for genomics-assisted breeding of drought-tolerant wheat cultivars.

Morphological characterization of gamma rays induced multipodding mutant (mp) in lentil cultivar Pant L 406

Purpose: Lentil (Lens culinaris Medik.), being a self-pollinated crop with narrow genetic base, is an important target crop for mutation breeding experiments. The purpose of the investigation was to create, select and characterize unique mutations in inflorescence traits that have strong impact on lentil yield and yield stability.Materials and methods: Healthy and uniform seeds (moisture 11.0%) of Lens culinaris Medik. cultivar Pant L 406 were irradiated with 100, 200, 300 and 400 Gy of gamma rays. The mutagenized populations were maintained up to mutant generation third (M3) to screen for stable mutations in the inflorescence architecture of the lentil. The selected mutant mp ‘Multipodding’ trait, i.e. multiple pods per peduncle, was morphologically characterized and quantified in subsequent mutant generation fourth (M4).Results: The morphological characterization of the ‘multipodding’ mutant (mp) revealed substantial morphological mutations were induced by the treatment of gamma rays. The estimation of yield per plant (g) between the mutant (mp) and parent cultivar Pant L 406 showed non-significant variation due to significant reduction in seed weight.Conclusions: The novel ‘multipodding’ (mp) mutant induced in the present study can play a key role in understanding the genetic network controlling legume inflorescence architecture and in genomics-assisted breeding for development of elite lentil cultivars.

Harnessing the Potential of Forage Legumes, Alfalfa, Soybean, and Cowpea for Sustainable Agriculture and Global Food Security.

Substantial improvements in access to food and increased purchasing power are driving many people toward consuming nutrition-rich foods causing an unprecedented demand for protein food worldwide, which is expected to rise further. Forage legumes form an important source of feed for livestock and have potential to provide a sustainable solution for food and protein security. Currently, alfalfa is a commercially grown source of forage and feed in many countries. However, soybean and cowpea also have the potential to provide quality forage and fodder for animal use. The cultivation of forage legumes is under threat from changing climatic conditions, indicating the need for breeding cultivars that can sustain and acclimatize to the negative effects of climate change. Recent progress in genetic and genomic tools have facilitated the identification of quantitative trait loci and genes/alleles that can aid in developing forage cultivars through genomics-assisted breeding. Furthermore, transgenic technology can be utilized to manipulate the genetic makeup of plants to improve forage digestibility for better animal performance. In this article, we assess the genetic potential of three important legume crops, alfalfa, soybean, and cowpea in supplying quality fodder and feed for livestock. In addition, we examine the impact of climate change on forage quality and discuss efforts made in enhancing the adaptation of the plant to the abiotic stress conditions. Subsequently, we suggest the application of integrative approaches to achieve adequate forage production amid the unpredictable climatic conditions.

Genome-wide generation and genotyping of informative SNPs to scan molecular signatures for seed yield in chickpea

We discovered 2150 desi and 2199 kabuli accessions-derived SNPs by cultivar-wise individual assembling of sequence-reads generated through genotyping-by-sequencing of 92 chickpea accessions. Subsequent large-scale validation and genotyping of these SNPs discovered 619 desi accessions-derived (DAD) SNPs, 531 kabuli accessions-derived (KAD) SNPs, 884 multiple accessions-derived (MAD) SNPs and 1083 two accessions (desi ICC 4958 and kabuli CDC Frontier)-derived (TAD) SNPs that were mapped on eight chromosomes. These informative SNPs were annotated in coding/non-coding regulatory sequence components of genes. The MAD-SNPs were efficient to detect high intra-specific polymorphic potential and wide natural allelic diversity level including high-resolution admixed-population genetic structure and precise phylogenetic relationship among 291 desi and kabuli accessions. This signifies their effectiveness in introgression breeding and varietal improvement studies targeting useful agronomic traits of chickpea. Six trait-associated genes with SNPs including quantitative trait nucleotides (QTNs) in combination explained 27.5% phenotypic variation for seed yield per plant (SYP). A pentatricopeptide repeat (PPR) gene with a synonymous-coding SNP/QTN significantly associated with SYP trait was found most-promising in chickpea. The essential information delineated can be of immense utility in genomics-assisted breeding applications to develop high-yielding chickpea cultivars.

First genetic linkage map of Lathyrus cicera based on RNA sequencing-derived markers: Key tool for genetic mapping of disease resistance

The Lathyrus cicera transcriptome was analysed in response to rust (Uromyces pisi) infection to develop novel molecular breeding tools with potential for genetic mapping of resistance in this robust orphan legume species. One RNA-seq library each was generated from control and rust-inoculated leaves from two L. cicera genotypes with contrasting quantitative resistance, de novo assembled into contigs and sequence polymorphisms were identified. In toto, 19,224 SNPs differentiate the susceptible from the partially resistant genotype’s transcriptome. In addition, we developed and tested 341 expressed E-SSR markers from the contigs, of which 60.7% varied between the two L. cicera genotypes. A first L. cicera linkage map was created using part of the developed markers in a RIL population from the cross of the two genotypes. This map contains 307 markers, covered 724.2 cM and is organised in 7 major and 2 minor linkage groups, with an average mapping interval of 2.4 cM. The genic markers also enabled us to compare their position in L. cicera map with the physical position of the same markers mapped on Medicago truncatula genome, highlighting a high macrosyntenic conservation between both species. This study provides a large new set of genic polymorphic molecular markers with potential for mapping rust resistances. It represents the first step towards genomics-assisted precision breeding in L. cicera.

Development of sequence-based markers for seed protein content in pigeonpea.

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F2 population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.

Advances in Wheat and Pathogen Genomics: Implications for Disease Control.

The gene pool of wheat and its wild and domesticated relatives contains a plethora of resistance genes that can be exploited to make wheat more resilient to pathogens. Only a few of these genes have been isolated and studied at the molecular level. In recent years, we have seen a shift from classical breeding to genomics-assisted breeding, which makes use of the enormous advancements in DNA sequencing and high-throughput molecular marker technologies for wheat improvement. These genomic advancements have the potential to transform wheat breeding in the near future and to significantly increase the speed and precision at which new cultivars can be bred. This review highlights the genomic improvements that have been made in wheat and its pathogens over the past years and discusses their implications for disease-resistance breeding.

First draft genome assembly of the Argane tree (Argania spinosa)

Background: The Argane tree (Argania spinosa L. Skeels) is an endemic tree of southwestern Morocco that plays an important socioeconomic and ecologic role for a dense human population in an arid zone. Several studies confirmed the importance of this species as a food and feed source and as a resource for both pharmaceutical and cosmetic compounds. Unfortunately, the argane tree ecosystem is facing significant threats from environmental changes (global warming, over-population) and over-exploitation. Limited research has been conducted, however, on argane tree genetics and genomics, which hinders its conservation and genetic improvement. Methods: Here, we present a draft genome assembly of A. spinosa. A reliable reference genome of A. spinosa was created using a hybrid de novo assembly approach combining short and long sequencing reads. Results: In total, 144 Gb Illumina HiSeq reads and 7.2 Gb PacBio reads were produced and assembled. The final draft genome comprises 75 327 scaffolds totaling 671 Mb with an N50 of 49 916 kb. The draft assembly is close to the genome size estimated by k-mers distribution and covers 89% of complete and 4.3 % of partial Arabidopsis orthologous groups in BUSCO. Conclusion: The A. spinosa genome will be useful for assessing biodiversity leading to efficient conservation of this endangered endemic tree. Furthermore, the genome may enable genome-assisted cultivar breeding, and provide a better understanding of important metabolic pathways and their underlying genes for both cosmetic and pharmacological purposes.

Trends in herbgenomics.

From Shen Nong's Herbal Classic (Shennong Bencao Jing) to the Compendium of Materia Medica (Bencao Gangmu) and the first scientific Nobel Prize for the mainland of China, each milestone in the historical process of the development of traditional Chinese medicine (TCM) involves screening, testing and integrating. After thousands of years of inheritance and development, herbgenomics (bencaogenomics) has bridged the gap between TCM and international advanced omics studies, promoting the application of frontier technologies in TCM. It is a discipline that uncovers the genetic information and regulatory networks of herbs to clarify their molecular mechanism in the prevention and treatment of human diseases. The main theoretical system includes genomics, functional genomics, proteomics, transcriptomics, metabolomics, epigenomics, metagenomics, synthetic biology, pharmacogenomics of TCM, and bioinformatics, among other fields. Herbgenomics is mainly applicable to the study of medicinal model plants, genomic-assisted breeding, herbal synthetic biology, protection and utilization of gene resources, TCM quality evaluation and control, and TCM drug development. Such studies will accelerate the application of cutting-edge technologies, revitalize herbal research, and strongly promote the development and modernization of TCM.

Genomics-Assisted Breeding in the CGIAR Research Program on Roots, Tubers and Bananas (RTB)

Breeding in the CGIAR Research Program on Roots, Tubers and Bananas (RTB) targets highly diverse biotic and abiotic constraints, whilst meeting complex end-user quality preferences to improve livelihoods of beneficiaries in developing countries. Achieving breeding targets and increasing the rate of genetic gains for these vegetatively propagated crops, with long breeding cycles, and genomes with high heterozygosity and different ploidy levels, is challenging. Cheaper sequencing opens possibilities to apply genomics tools for complex traits, such as yield, climate resilience, and quality traits. Therefore, across the RTB program, genomic resources and approaches, including sequenced draft genomes, SNP discovery, quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS), are at different stages of development and implementation. For some crops, marker-assisted selection (MAS) is being implemented, and GS has passed the proof-of-concept stage. Depending on the traits being selected for using prediction models, breeding schemes will most likely have to incorporate both GS and phenotyping for other traits into the workflows leading to varietal development.