Identification of SNP Markers and Candidate Genes Associated with Major Agronomic Traits in Coffea arabica

Author:

da Silva Ruane Alice1,Caixeta Eveline Teixeira12ORCID,Silva Letícia de Faria1,Sousa Tiago Vieira3,Barreiros Pedro Ricardo Rossi Marques1ORCID,Oliveira Antonio Carlos Baião de24,Pereira Antonio Alves4,Barreto Cynthia Aparecida Valiati5ORCID,Nascimento Moysés5ORCID

Affiliation:

1. Biotechnology Applied to Agriculture Institute (Bioagro), Federal University of Viçosa (UFV), Viçosa 36570-900, Brazil

2. Embrapa Coffee, Brazilian Agricultural Research Corporation (Embrapa), Brasília 70770-901, Brazil

3. Biological Sciences Center, Iturama University Campus, Universidade Federal do Triângulo Mineiro (UFTM), Iturama 38025-180, Brazil

4. Agricultural Research Company of Minas Gerais (EPAMIG), Viçosa 36571-000, Brazil

5. Laboratory of Intelligence Computational and Statistical Learning (LICAE), Department of Statistics, Federal University of Viçosa, Viçosa 36570-900, Brazil

Abstract

Genome-wide association studies (GWASs) allow for inferences about the relationships between genomic variants and phenotypic traits in natural or breeding populations. However, few have used this methodology in Coffea arabica. We aimed to identify chromosomal regions with significant associations between SNP markers and agronomic traits in C. arabica. We used a coffee panel consisting of 195 plants derived from 13 families in F2 generations and backcrosses of crosses between leaf rust-susceptible and -resistant genotypes. The plants were phenotyped for 18 agronomic markers and genotyped for 21,211 SNP markers. A GWAS enabled the identification of 110 SNPs with significant associations (p < 0.05) for several agronomic traits in C. arabica: plant height, plagiotropic branch length, number of vegetative nodes, canopy diameter, fruit size, cercosporiosis incidence, and rust incidence. The effects of each SNP marker associated with the traits were analyzed, such that they can be used for molecular marker-assisted selection. For the first time, a GWAS was used for these important agronomic traits in C. arabica, enabling applications in accelerated coffee breeding through marker-assisted selection and ensuring greater efficiency and time reduction. Furthermore, our findings provide preliminary knowledge to further confirm the genomic loci and potential candidate genes contributing to various structural and disease-related traits of C. arabica.

Funder

Brazilian Coffee Research and Development Consortium

Foundation for Research Support of the state of Minas Gerais

National Council of Scientific and Technological Development

National Institutes of Science and Technology of Coffee

Coordination for the Improvement of Higher Education Personnel

Publisher

MDPI AG

Reference51 articles.

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