Genomic selection of parents and crosses beyond the native gene pool of a breeding program

Abstract

Genomic selection has become a valuable tool for selecting cultivar candidates in many plant breeding programs. Genomic selection of elite parents and crossing combinations with germplasm developed outside a breeding program has, however, hardly been explored until now. The aim of this study was to assess the potential of this method for commonly ranking and selecting elite germplasm developed within and beyond a given breeding program. A winter wheat (Triticum aestivum L.) population consisting of 611 in-house and 87 externally developed lines was used to compare training population compositions and statistical models for genomically predicting baking quality in this framework. Augmenting training populations with lines from other breeding programs had a larger influence on the prediction ability than adding in-house generated lines when aiming to commonly rank both germplasm sets. Exploiting preexisting information of secondary correlated traits resulted likewise in more accurate predictions both in empirical analyses and simulations. Genotyping germplasm developed beyond a given breeding program is moreover a convenient way to clarify its relationships with a breeder's own germplasm because pedigree information is oftentimes not available for this purpose. Genomic predictions can thus support a more informed diversity management, especially when integrating simply to phenotype correlated traits to partly circumvent resource reallocations for a costly phenotyping of germplasm from other programs.

Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat

“…Efforts to estimate the GEBVs of 147 genebank lines from the genomic prediction model trained with 272 breeding lines did not show any significant improvement, and the highest prediction accuracy was only 0.18 for FLA. The higher genetic dissimilarity coupled with strong population structure probably contributed to a low genomic prediction accuracy when the two populations used as independent training and test sets as supported in previous studies (Lozada et al 2019 ; Michel et al 2021 ; Norman et al 2018 ). Pre-selection of SNP markers through trait-dependent linked SNPs with GWAS and trait-independent haplotype-tagging did not show a promising improvement in prediction accuracy across the two populations, and genetic relatedness remains the key factor for a successful genomic prediction model.…”

Assessment of environmental carrying capacity of ecotourism in the Yellow River estuary

“…It is one of the most biodiverse ecosystems in nature and one of the most important environments for human survival [3][4][5]. It is known as the "cradle of life", "birthplace of civilization" and "gene pool of species" [6][7][8][9][10], with ecological and social service functions such as water conservation, climate regulation, environmental purification, provision of resources, and leisure and tourism sites.…”