Carneiro Fernanda A, Rego Erica C.S., Aquino Sinara O., Costa Tatiana S., Lima E.A., Rocha Omar C., Rodrigues Gustavo Costa, Carvalho Milene Alves de Figueiredo, Veiga Adriano Delly, Guerra Antonio Fernando, Bartholo Gabriel Ferreira, Silva-Júnior O.B., Marraccini Pierre, Grattapaglia Dario, Andrade Alan Carvalho.
2015. Genome wide association study for drought tolerance and other agronomic traits of a Coffea canephora population.
In : The 12th Solanaceae Conference SOL2015 book of abstracts. INRA
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Résumé : Recent technological advancements and cost decreases on DNA-sequencing technologies allowed the completion of a reference sequence of the C. canephora genome. In due time, perhaps with some delay, in view of the economic and social importance of coffee worldwide as well as its perennial aspect (vis à vis annual crops), to provide the research power to face the challenges lying ahead, imposed by the real/potential climate changes impacts. Studies on a genome-wide scale are now being performed allowing researchers to narrow down some key molecular players that will certainly be applicable to fast and cost-effective molecular breeding programs. This work describes a Genome Wide Association Study (GWAS) for drought tolerance and other important agronomic traits such as yield of a C. canephora conilon population, cultivated in Planaltina-DF (1175m altitude) at the experimental field of Embrapa Cerrados. Phenotyping started in 2012, evaluating characteristics such as vigor, secondary branching, leaf-rust susceptibility, precocity and fruit load. Furthermore, the yield of each plant was measured for three consecutive years (2012-2014) and the predawn-leaf water potential (am) of 400 plants was also evaluated under field conditions (drought season of 2012/2013). Genotyping was performed using the nextRAD technique provided by SNPSaurus (http://snpsaurus.com/), yielding 11.230 SNPs with a call rate above 80%. Population structure was determined using the admixture model of the software STRUCURE. Marker-trait associations (MTAs) studies were conducted employing mixed linear model (MLM) analysis with optimum compression and kinship matrix (TASSEL). Significant MTAs were found and will be presented. (Texte intégral)
Classification Agris : F30 - Génétique et amélioration des plantes
H50 - Troubles divers des plantes
F60 - Physiologie et biochimie végétale
U10 - Informatique, mathématiques et statistiques
Auteurs et affiliations
- Carneiro Fernanda A, UFLA (BRA)
- Rego Erica C.S., UFLA (BRA)
- Aquino Sinara O., UFLA (BRA)
- Costa Tatiana S., UFLA (BRA)
- Lima E.A., UFLA (BRA)
- Rocha Omar C., UFLA (BRA)
- Rodrigues Gustavo Costa, UFLA (BRA)
- Carvalho Milene Alves de Figueiredo, UFLA (BRA)
- Veiga Adriano Delly, UFLA (BRA)
- Guerra Antonio Fernando, UFLA (BRA)
- Bartholo Gabriel Ferreira, UFLA (BRA)
- Silva-Júnior O.B., UFLA (BRA)
- Marraccini Pierre, CIRAD-BIOS-UMR AGAP (BRA) ORCID: 0000-0001-7637-6811
- Grattapaglia Dario, UFLA (BRA)
- Andrade Alan Carvalho, EMBRAPA (BRA)
Source : Cirad-Agritrop (https://agritrop.cirad.fr/579014/)
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