Genomic selection (GS) is a promising tool in the field of breeding especially in the era where genomic data is becoming cheaper. But its potential has been understated due to the limited adaptation in various crops. Marker assisted selection (MAS) has been the method of choice for plant breeders while using the genomic information in breeding pipeline. MAS, however, fails to capture vital minor gene effects while focussing only on the major genes. Ignoring majority of the genes involved in a trait, especially quantitative trait such as yield, is not ideal for breeding advancement. The main aim of statistical methodologies coming under the umbrella of GS on using the whole genome information is to predict potential candidates for breeding advancement while optimizing the use of resources such as land, manpower, and most importantly time. Lack of proper understanding of the methods and its applications is one of the reasons why breeders shy away from this tool.
The book targets biologists, especially breeders and provides a comprehensive knowledge in statistical methodologies used in GS, guidance on the choice of GS models and the design of datasets. The book also encourages readers to adopt GS by demonstrating the current scenarios of these models in some of the important crops in the genera of oilseeds, vegetables, legumes, tuber crops, and cereals. Having an understanding about the GS models and going through the success stories are not enough, however, to implement those by a breeder. Therefore, the book also provides hands-on scripts on GS data design and modelling in a popular and free statistical program for the breeders to use. Additionally, prospective in GS model development and thereby enhancement in crop improvement programs are discussed.
About the Author: Ani A. Elias is a recipient of the prestigious Ramalingaswami fellowship. She is working at Department of Botany, University of Delhi. Earlier, she received her PhD from Purdue University, USA with specialization in statistical genetics and gained postdoctoral experience in genomic selection (GS) from Cornell University, USA. She has worked extensively on GS and other genomic prediction models in maize, sorghum, cassava, and safflower both in private and public sectors.
Shailendra Goel is a Professor at Department of Botany, University of Delhi from where he received his PhD. He is involved in genetics and genomics studies of complex and important traits in various crops. He has extensively worked on an important but elusive trait, apomixis. He is also known for his work on evolution of sex in seabuckthorn, a plant with nutritious and medicinal plant from cold deserts of Ladakh, India. He has developed a comprehensive program on safflower, another promising native oil seed crop. His national and international collaborations, publications in major journals, and editorial services to publishers such as Oxford, Springer & Elsevier are evidences of his research credential.