Genomic Selection in Plant Breeding: Methods, Models, and Perspectives

In recent years, the global climate has changed, resulting in drastic fluctuations in rainfall patterns and increasing temperature. Sudden climate changes can cause significant economic losses to countries worldwide. Genetic improvement of several economically important crops during the 20th century using phenotypic, pedigree, and performance data was very successful. However, signs of grain yield stagnation in some crops, especially in drought-stressed and semi-arid regions, are evident. Genomic selection offers the opportunity to increase grain production in less time. International Maize and Wheat Improvement Center (CIMMYT) maize breeding research in Sub-Saharan Africa, India, and Mexico has shown that genomic selection can reduce the breeding interval cycle to at least half the conventional time and produces lines that, in hybrid combinations, significantly increase grain yield performance over that of commercial checks. Public and private investment in crop genomic selection research should increase to successfully develop in less time germplasm that is adapted to sudden climate change. Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype × environment (G × E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype × environment (G × E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. the worth of an individual as estimated by the average performance of its progenies. high-throughput genotyping platform containing either genome-wide SNPs (SNP array) or coding variants (exome array). the amount of increase in performance that is achieved through genetic improvement programs between consecutive selection cycles. breeding value of an individual calculated using genome-wide marker data to capture small genetic effects dispersed over the genome. a type of breeding methodology that selects the best candidates as parents for the next selection cycle based on their predicted breeding values computed given: (i) their genotypes; and (ii) the phenotypes and genotypes of their relatives. a highly multiplex genotyping system that involves DNA digestion with enzymes followed by construction of a reduced representation library, which is sequenced using a next-generation sequencing platform. a group of genotypes, irrespective of their genetic relatedness, that display similar combining ability and heterotic response when crossed with genotypes from other genetically distinct germplasm of the same group. the nonrandom associations of alleles at two loci that can occur even if the two genes are unlinked. a process for selecting individuals based on trait-linked markers. a type of MAS that allows the simultaneous identification of associated alleles as well as the accumulation of superior alleles from both parents. a gene (DNA section also called locus) that is associated with variation in a phenotype.