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High-throughput targeted genotyping using next-generation sequencing applied in Coffea canephora breeding

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The use of molecular markers to detect polymorphism at DNA level is one of the most significant developments in molecular biology techniques. With the development of new next-generation sequencing technologies,… Click to show full abstract

The use of molecular markers to detect polymorphism at DNA level is one of the most significant developments in molecular biology techniques. With the development of new next-generation sequencing technologies, the discovery of SNP became easier and faster, and the costs of data point were reduced. The development and use of SNP markers for coffee have provided new perspectives for the evaluation of genetic diversity and population structure via different statistical approaches. In this study, 72 Coffea canephora genotypes were analyzed to identify the SNP markers and apply them to genetic studies and selection of parents/hybrids in genetic breeding. As many as 117,450 SNP were identified using the RAPiD Genomics platform. After quality analyses, 33,485 SNP were validated for analyses of genetic diversity and population structure. Genotypes were separated based on their varietal groups, and Hybrids were differentiated using the clustering and Bayesian approach. Coffee accessions mistakenly identified in the germplasm and breeding program were detected. The Conilon varietal group presented the lowest genetic dissimilarity values, suggesting the introduction of new accessions in the germplasm bank. The highest genetic distances values were observed among genotypes of the heterotic groups (Conilon and Robusta). The markers were efficient in evaluating the genetic diversity and population structure of C. canephora. Promising crosses were selected within and between the varietal groups. Hybrids with greater genetic distances were selected, which were important for C. canephora breeding programs.

Keywords: snp; next generation; coffea canephora; canephora breeding; generation sequencing

Journal Title: Euphytica
Year Published: 2018

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