On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops

Abstract

The breeding programs cross-pollinated crops develop thousands of lines that, when combined, generate single-crosses that need to be evaluated for their performance in different sites, making this step the most expensive in released new cultivars. The molecular markers have proved to be a powerful tool in improving economically essential crops to accelerate this process. Currently, there are several genotyping platforms capable of providing thousands of SNP (Single Nucleotide Polymorphism) for performing genomic studies. However, the adoption of modern genomic enhancement for crops that do not yet have a reference genome is limited. Genotyping by sequencing (GBS) has emerged as an alternative to make such technologies viable for orphan crops. Once with these data, it is possible to build a simulated genome to perform the SNP calling where the discovery of polymorphisms will be intrinsic to the population under study without using an external genome. The term “orphan” is derived from the condition of neglect and helplessness of these crops by the scientific community, despite having great food and nutritional potential. Therefore, our goals were to verify whether the source of SNP can influence the assessment of the population structure of parental lines; ascertain if the SNP source can affect the determination of heterotic groups and the prediction of single-crosses performance, and to test if using GBS and the mock genome efficiently performs the SNP calling in orphan crops, the ones that don’t have reference genome available. For this, maize was used as a model species, where 330 parental lines were genotyped by two standard genotyping platforms, SNP-array and GBS. GBS data were used for two purposes, to perform the SNP calling using the parental line B73 (GBS-B73) as a reference genome and to build a mock genome (GBS-Mock) to perform the SNP calling without needing an external genome, making three genotyping scenarios: SNP-array, GBS-B73, and GBS-Mock. These scenarios were used to conduct studies of population structure and genetic diversity among parental lines. After, we used phenotypic data of 751 single-crosses generated from the diallel of these parental lines. From there, genomic diallel analyses were performed to separate parental lines into heterotic groups and choose the best testers. Subsequently, an additive-dominant model was applied to predict the performance of single-crosses. The results showed that the GBS-Mock presented similar results to the standard population structure studies approach. The genotyping scenarios also did not differ in the division of heterotic groups and the definition of testers. In the genomic prediction study, GBS-Mock performed similarly to the SNP-array and GBS-B73. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an excellent strategy to support plant breeders in studies of diversity, population structure, the definition of heterotic groups, choice of testers, and genomic prediction in species that still do not have a reference genome available. Because it is an alternative to the rapid advance of orphan crop breeding, in this context, genotyping via GBS associated with the mock genome is an effective alternative for performing genomic studies in orphan crops, especially those that do not have a reference genome.