Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding

Abstract

Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencing. These marker technologies have changed the entire scenario of marker applications and made the use of GS a routine work for crop improvement in both model and non-model crop species. The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding. But to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits. Moreover, the continuous decline in sequencing cost will make the WGS feasible and cost effective for GS in near future. Till that time matures the targeted sequencing seems to be more cost-effective option for large scale marker discovery and GS, particularly in case of large and un-decoded genomes.

Deciphering genetic factors that determine melon fruit‐quality traits using RNA‐Seq‐based high‐resolution QTL and eQTL mapping

“…The large-scale data generated by NGS, combined with powerful computational tools, enabled a major technological leap from low-resolution to high-resolution QTL mapping. This facilitated the gap-closing in gene-identification and breeding that is of special importance in non-model species (Xiao et al, 2013;Unamba et al, 2015;Bhat et al, 2016). Resequencing and genotyping-by-sequencing (GBS; Elshire et al, 2011) technologies have recently been employed for high-resolution QTL mapping in crop plants, such as rice and soybean (Huang et al, 2009;Gao et al, 2013;Spindel et al, 2013;Xu et al, 2013).…”

Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection

“…Genomic selection (GS) involves the prediction of breeding values and selection of parents based on markerestimated effects, enabling more cycles of selection and recombination per unit time than phenotypic recurrent selection (Bhat et al, 2016). Thus, GS will potentially shorten the breeding cycle of cassava and enable breeders to meet the growing need for improved varieties.…”

NGS-Based Genotyping, High-Throughput Phenotyping and Genome-Wide Association Studies Laid the Foundations for Next-Generation Breeding in Horticultural Crops

“…It is very likely that genomic selection (GS) strategies will replace GWAS in the next future [111]. Albeit, comparable to GWAS, GS relies on high-throughput genotyping and phenotyping of unrelated individuals in a population (i.e., training population; TP) and allows markers in strong LD with causal variants to be identified [112], it has singular features.…”