Título:	Genomic Selection with Allele Dosage in Panicum maximum Jacq.
Autoria:	LARA, L. A. de C. SANTOS, M. F. JANK, L. CHIARI, L. VILELA, M. de M. AMADEU, R. R. SANTOS, J. P. R. dos SILVA, F. G. da ZENG, Z.-B. GARCIA, A. A. F.
Afiliação:	Letícia A. de C. Lara, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; MATEUS FIGUEIREDO SANTOS, CNPGC; LIANA JANK, CNPGC; LUCIMARA CHIARI, CNPGC; MARIANE DE MENDONCA VILELA, CNPGC; Rodrigo R. Amadeu, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; Jhonathan P. R. dos Santos, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ; FRANCISCO GUILHERME DA SILVA, CNPGL; Zhao-Bang Zeng, North Carolina State University - NCSU; Antonio Augusto F. Garcia, Universidade de São Paulo -USP/Faculdade de Agricultura Luiz de Queiroz - ESALQ.
Ano de publicação:	2019
Referência:	G3: Genes|Genomes|Genetics, v. 9, p. 2463-2475, August 2019.
Conteúdo:	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.
NAL Thesaurus:	Plant breeding Guinea Genotyping Polyploidy Genomics Prediction
Tipo do material:	Artigo de periódico
Acesso:	openAccess
Aparece nas coleções:	Artigo em periódico indexado (CNPGC)