Genomic Selection in Cereal Crops: Methods and Applications

Abstract

Most of the traits in plants are not controlled by single gene, but rather a cluster of genes. The variation in activity of chromosome is controlled by the recombination established by the series of balanced system that is called linked balanced polygenic complex. Regardless of the complexity of genetic material, breeders have developed advanced and precise approaches to overcome the problems faced in the crop improvement. Thus, using genomic selection (GS), we can achieve a constellation of genes attributed by the region of chromosome. They integrated phenotype data with the right bioinformatics tools, statistical tests, and huge amount of genomic data to target the selection of best line having superior phenotypes along with the absolute knowledge of genotype. With GS we can identify the minor-effect genes, QTLs, and markers. Since decades of population explosion, it has been a challenge to deliver breeding targets for developing best-quality crops having required grain yield. Earlier, breeding of crops involved a series of cycle of phenotypic evaluation and crossing followed by the selection of superior phenotype which consumed more time and manpower. In GS there is no need for repeated phenotyping to select the elite lines. Along with the integration of genomic information, bioinformatics tools, and statistical models, we cannot overlook marker-trait associations, variant calling at genome level, and population structure that provide comprehensive information of all elements necessary in crop improvement. However, it is still challenging for the plant breeders to develop crops capable to thrive successfully in tough climate. In this chapter, we will explore the factors affecting the selection of superior genotype, how we can design a suitable breeding pipeline along with the concept of statistical model, advantages, and applications. For decades, translating the complex genomic data has been a major challenge for crop improvement. GS is a remarkable approach for genetic gain as it consumes only one-third time compared to the traditional selection process.