Training Set Optimization for Sparse Phenotyping in Genomic Selection: A Conceptual Overview

• DOI: 10.3389/fpls.2021.715910
• Publication Date: 2021-09-09T16:03:46Z
• Authors: Julio Isidro y Sá...; Deniz Akdemir
• Keywords: Genomic Selection

Genomic selection (GS) is becoming an essential tool in breeding programs due to its role increasing genetic gain per unit time. The design of the training set (TRS) GS one key steps implementation plant and animal mainly because (i) TRS optimization critical for efficiency effectiveness GS, (ii) breeders test genotypes multi-year multi-location trials select best-performing ones. In this framework, can help decrease number be tested and, therefore, reduce phenotyping cost time, (iii) we obtain better prediction accuracies from optimally selected than arbitrary TRS. Here, concentrate efforts on reviewing lessons learned studies their impact crop discuss important features success under different scenarios. article, review population plants major challenges associated with including size, relationship between (TS), update TRS, use packages algorithms GS. Finally, describe general guidelines improving rate improvement by maximizing framework.