Abstract: Major paradigm shift in plant breeding since the availability of molecular marker technology is that mapping and characterizing the genetic loci that control a trait will lead to improved breeding. Often, one of the rationales for cloning of QTL is to develop the “perfect marker” for MAS, perhaps based on a functional polymorphism. In contrast, an advantage of genomic selection is precisely its black box approach to exploiting genotyping technology to expedite genetic progress. This is an advantage in our view because it does not rely on a “breeding by design” engineering approach to cultivar development requiring knowledge of biological function before the creation of phenotypes. Breeders can therefore use genomic selection without the large upfront cost of obtaining that knowledge. In addition, genomic selection can maintain the creative nature of phenotypic selection which couple’s random mutation and recombination to sometimes arrive at solutions outside the engineer’s scope. Currently, the lion’s share of research on genomic selection has been performed in livestock breeding, where effective population size, extent of LD, breeding objectives, experimental design, and other characteristics of populations and breeding programs are quite different from those of crop species. Nevertheless, a great number of findings within this literature are very illuminating for genomic selection in crops and should be studied and built upon by crop geneticists and breeders. The application of powerful, relatively new statistical methods to the problem of high dimensional marker data for genomic selection has been nearly as important to the development of genomic selection as the creation of high-density marker platforms and greater computing power. The methods can be classified by what type of genetic architecture they try to capture.
Recommended citation: Shamshad, M., Sharma, A. (2018). In: Yelda Ozden C (eds), The usage of genomic selection strategy in plant breeding, In eds. Next Generation Plant breeding, Intech Publisher 2018, Pages 93-108 DOI: 10.5772/intechopen.76247.