Genomic Selection with Allele Dosage in Panicum maximum Jacq.

Abstract

Genomic selection is an efficient approach to get shorter breeding cycles in recurrent selection programs and greater genetic gains with selection of superior individuals. Despite advances in genotyping techniques, genetic studies for polyploid species have been limited to a rough approximation of studies in diploid species. The major challenge is to distinguish the different types of heterozygotes present in polyploid populations. In this work, we evaluated different genomic prediction models applied to a recurrent selection population of 530 genotypes of Panicum maximum , an autotetraploid forage grass. We also investigated the effect of the allele dosage in the prediction, i.e. , considering tetraploid (GS-TD) or diploid (GS-DD) allele dosage. A longitudinal linear mixed model was fitted for each one of the six phenotypic traits, considering different covariance matrices for genetic and residual effects. A total of 41,424 genotyping-by-sequencing markers were obtained using 96-plex and Pst 1 restriction enzyme, and quantitative genotype calling was performed. Six predictive models were generalized to tetraploid species and predictive ability was estimated by a replicated fivefold cross-validation process. GS-TD and GS-DD models were performed considering 1,223 informative markers. Overall, GS-TD data yielded higher predictive abilities than with GS-DD data. However, different predictive models had similar predictive ability performance. In this work, we provide bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum .

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus)

“…TDM and LDM showed high broad-sense heritability (<0.5), followed by RC (0.3) and PLB (0.1), as shown in Table 1. Higher heritability values (<0.85) for LDM and RC and a value for PLB above 0.4 were recently reported in M. maximus (Lara et al, 2019), using the generalized heritability formula (Cullis et al, 2006). For this species, a greater amount (g/plant) of TDM and LDM in the progenies has been associated with considerable heritability from the most productive parents (Braz et al, 2013;Braz et al, 2017).…”

Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species

“…Owing to the complex nature of polyploids, genotype calling can be a challenge and "diploidization", i.e., considering a polyploid genome as diploid is usual (Bourke et al, 2018). Some studies have recently investigated the effect of accounting the ploidy level in prediction accuracy in polyploids (Endelman et al, 2018;Nyine et al, 2018;Amadeu et al, 2019;Lara et al, 2019;Zingaretti et al, 2019). As in these previous results (de Bem Oliveira et al, 2019;Zingaretti et al, 2019), here we found that "diploidization", in which all heterozygous genotypes are pooled, is as efficient and accurate as polyploid genotyping for prediction purposes, albeit it is trait dependent.…”

Breeding and biotechnological interventions for trait improvement: status and prospects

“…GS has also expanded its horizon towards underutilized or less studied crops for their improvement. de C. Lara et al ( 2019 ) have demonstrated the use of GS in an autotetraploid forage grass, Panicum maximum . Similarly, in miscanthus, Slavov et al ( 2019 ) have combined index selection and genomic prediction to achieve multiple breeding targets.…”