Genomic Selection with Allele Dosage in Panicum maximum Jacq.

Letícia A. de C. Lara, Mateus F. Santos, Liana Jank, Lucimara Chiari, Mariane de M. Vilela, Rodrigo R. Amadeu, Jhonathan P. R. dos Santos, Guilherme da S. Pereira, Zhao-Bang Zeng, Antonio Augusto F. Garcia

Research output: Contribution to journalArticlepeer-review

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 genotypingby- sequencing markers were obtained using 96-plex and Pst1 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.
Original languageEnglish
JournalG3: Genes | Genomes | Genetics
DOIs
Publication statusPublished - 6 Jun 2019
Externally publishedYes

Keywords

  • Plant Breeding
  • Guinea Grass
  • Quantitative Genotyping
  • Polyploidy Genotyping-bysequencing (GBS) Recurrent
  • Genomic Selection
  • Genomic Prediction
  • GenPred
  • Shared Data Resources

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