Evidence map›Paper›PMID 36946358›Full record

ArticleThe plant genome2024

Genomic-assisted breeding for climate-smart coffee.

Maria Amélia G Ferrão, Aymbire F A da Fonseca, Paulo S Volpi, Lucimara C de Souza, Marcone Comério, Abraão C Verdin Filho, Elaine M Riva-Souza, Patricio R Munoz, Romário G Ferrão, Luís Felipe V Ferrão

Open access · goldAbstract read
In one paragraph

Article in The plant genome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 24 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Maria Amélia G FerrãoInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Aymbire F A da FonsecaInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Paulo S VolpiInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Lucimara C de SouzaInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Marcone ComérioInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Abraão C Verdin FilhoInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Elaine M Riva-SouzaInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Patricio R MunozBlueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, USA.
Romário G FerrãoInstituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural-Incaper, ES, Brazil.
Luís Felipe V FerrãoBlueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, USA.ORCID https://orcid.org/0000-0002-9655-4838
Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural · BRBrazilian Agricultural Research Corporation · BRUniversity of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coffee is a universal beverage that drives a multi-industry market on a global basis. Today, the sustainability of coffee production is threatened by accelerated climate changes. In this work, we propose the implementation of genomic-assisted breeding for climate-smart coffee in Coffea canephora. This species is adapted to higher temperatures and is more resilient to biotic and abiotic stresses. After evaluating two populations, over multiple harvests, and under severe drought weather condition, we dissected the genetic architecture of yield, disease resistance, and quality-related traits. By integrating genome-wide association studies and diallel analyses, our contribution is four-fold: (i) we identified a set of molecular markers with major effects associated with disease resistance and post-harvest traits, while yield and plant architecture presented a polygenic background; (ii) we demonstrated the relevance of nonadditive gene actions and projected hybrid vigor when genotypes from different geographically botanical groups are crossed; (iii) we computed medium-to-large heritability values for most of the traits, representing potential for fast genetic progress; and (iv) we provided a first step toward implementing molecular breeding to accelerate improvements in C. canephora. Altogether, this work is a blueprint for how quantitative genetics and genomics can assist coffee breeding and support the supply chain in the face of the current global changes.

Indexed as

CoffeeGenome-Wide Association StudyDisease ResistanceGenomicsPlant BreedingCoffee

Identifiers

PMID36946358
PMCPMC12807177
OpenAlexW4353021273

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.