AUTHOR=Cuevas Jaime , Montesinos-López Osval A. , Martini J. W. R. , Pérez-Rodríguez Paulino , Lillemo Morten , Crossa Jose 

TITLE=Approximate Genome-Based Kernel Models for Large Data Sets Including Main Effects and Interactions

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.567757

DOI=10.3389/fgene.2020.567757

ISSN=1664-8021

ABSTRACT=The rapid development of molecular markers and sequencing technologies has made it possible to use genomic prediction (GP) and selection (GS) in animal and plant breeding. However, when the number of observations (n) is large (thousands or more), computational difficulties when handling these large genomic kernel relationship matrices (inverting and decomposing) increase exponentially. This problem increases when genomic × environment interaction and multi-trait kernels are included in the model. In this research we propose to select a low number of lines (observations) m (m