Biblioteca do Café
URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/1
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Resultados da Pesquisa
Item Assisted selection using molecular markers linked to rust resistance SH3 gene in Coffea arabica(Crop Breeding and Applied Biotechnology, 2023-10-25) Silva, Angelita Garbossi; Ariyoshi, Caroline; Shigueoka, Luciana Harumi; Pereira, Luiz Filipe Protasio; Sera, Gustavo HiroshiThe aim of this work was to validate markers linked to the SH3 gene of coffee leaf rust (CLR) resistance and use them in assisted selection. Initially, we validated the markers in genotypes already known to carry SH3. Next, we performed phenotype and genotype evaluation for resistance to CLR in coffee plants growing under field conditions. We used Arabica coffee progenies derived from BA-10, which carries the SH3 gene due to introgression of C. liberica. Three SCAR markers (SP-M16-SH3, BA-48-21O-f, and BA-124-12K-f) and one SSR marker (Sat244) linked to SH3 gene were used to amplify the coffee plants’ DNA. Our assessments of markers validation in resistant genotypes, SP-M16-SH3 and BA-124-12K-f, were efficient to identify the SH3 gene. These two markers were used to evaluate the progenies derived from BA-10 and were significantly linked to the phenotype evaluations. The SP-M16-SH3 marker was more efficient, with the advantage of being codominant.Item A new set of quantitative trait loci linked to lipid content in Coffea arabica(Crop Breeding and Applied Biotechnology, 2024-04-10) Muniz, Herison Victor Lima; Ariyoshi, Caroline; Ferreira, Rafaelle Vecchia; Felicio, Mariane Silva; Pereira, Luiz Filipe ProtasioLipids are compounds that play an important role in coffee bean development, contributing to beverage quality. Genome-wide association studies (GWAS) were conducted to pinpoint quantitative trait nucleotides (QTNs) linked to lipid metabolism in Coffea arabica. Genotyping by sequencing (GBS) and phenotyping data from 104 wild C. arabica accessions, Mundo Novo cultivar, and C. arabica var. Typica were utilized. GBS data were aligned to C. arabica Et039 reference genome, and both single-locus and multi-locus GWAS methods were employed. Methods were adjusted for kinship matrix, population structure, and principal component analysis. Of the 19 QTNs identified, 5 showed consistency across different population structure adjustments. The multi-locus methods mrMLM and FarmCPU proved more effective in identifying QTNs associated with lipid content. Four QTNs were situated near seven genes potentially involved in lipid metabolism. Higher frequencies of identified QTNs in accessions with elevated lipid content suggest their utility as markers for coffee plant breeding.