Autoria: SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; RESENDE JÚNIOR, M. F. R. de; ZAMBOLIM, L.

Resumo: The use of single nucleotide polymorphism (SNP) molecular markers has provided advances in selection methodologies used in breeding programs of different crops, reducing cost and time of cultivar release. Despite the great economic and social importance of Coffea arabica, studies with SNP markers are scarce and a small number of SNP are available for this species, when compared with other crops of agronomic mportance. Thus, the objective of this study was to identify and validate SNP molecular markers for the species Coffea arabica and to introduce these markers to genetic breeding by means of an accurate analysis of the diversity and genetic structure of breeding populations of this species. After quality filtering, 11,187 SNP markers were selected from the coffee population obtained from crosses between the genotypes Catuaí and Híbrido de Timor. A great number of markers were distributed in the 11 chromosomes, within transcribed regions, and were used to estimate the genetic dissimilarity among the individuals of the breeding population. Dendrogram analysis and a Bayesian approach demonstrated the formation of two groups and the discrimination of all genotypes evaluated. The expressive number of SNP molecular markers distributed throughout C. arabica genome was efficient to discriminate all the accessions evaluated in the experiment, clustering them according to their genealogies. This work identified mixtures within the progenies. The genotyping data also provided detailed information about the parental genotypes and led to the identification of new candidate parents to be introduced to the breeding program. The study discussed population structure and its consequence in obtaining improved varieties of C. arabica.

Ano de publicação: 2017

Tipo de publicação: Artigo de periódico

Unidade: Embrapa Café

Palavras-chave: Coffea arabica, Molecular breeding, Next-generation sequence