Dataset Information

Analysis of Phosphorus Use Efficiency Traits in Coffea Genotypes Reveals Coffea arabica and Coffea canephora Have Contrasting Phosphorus Uptake and Utilization Efficiencies.

ABSTRACT:

Background and aims

Phosphate (Pi) is one of the most limiting nutrients for agricultural production in Brazilian soils due to low soil Pi concentrations and rapid fixation of fertilizer Pi by adsorption to oxidic minerals and/or precipitation by iron and aluminum ions. The objectives of this study were to quantify phosphorus (P) uptake and use efficiency in cultivars of the species Coffea arabica L. and Coffea canephora L., and group them in terms of efficiency and response to Pi availability.

Methods

Plants of 21 cultivars of C. arabica and four cultivars of C. canephora were grown under contrasting soil Pi availabilities. Biomass accumulation, tissue P concentration and accumulation and efficiency indices for P use were measured.

Key results

Coffee plant growth was significantly reduced under low Pi availability, and P concentration was higher in cultivars of C. canephora. The young leaves accumulated more P than any other tissue. The cultivars of C. canephora had a higher root/shoot ratio and were significantly more efficient in P uptake, while the cultivars of C. arabica were more efficient in P utilization. Agronomic P use efficiency varied among coffee cultivars and E16 Shoa, E22 Sidamo, Iêmen and Acaiá cultivars were classified as the most efficient and responsive to Pi supply. A positive correlation between P uptake efficiency and root to shoot ratio was observed across all cultivars at low Pi supply. These data identify Coffea genotypes better adapted to low soil Pi availabilities, and the traits that contribute to improved P uptake and use efficiency. These data could be used to select current genotypes with improved P uptake or utilization efficiencies for use on soils with low Pi availability and also provide potential breeding material and targets for breeding new cultivars better adapted to the low Pi status of Brazilian soils. This could ultimately reduce the use of Pi fertilizers in tropical soils, and contribute to more sustainable coffee production.

SUBMITTER: Neto AP

PROVIDER: S-EPMC4814561 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Analysis of Phosphorus Use Efficiency Traits in Coffea Genotypes Reveals Coffea arabica and Coffea canephora Have Contrasting Phosphorus Uptake and Utilization Efficiencies.

Neto Ana P AP Favarin José L JL Hammond John P JP Tezotto Tiago T Couto Hilton T Z HT

Frontiers in plant science 20160331

<h4>Background and aims</h4>Phosphate (Pi) is one of the most limiting nutrients for agricultural production in Brazilian soils due to low soil Pi concentrations and rapid fixation of fertilizer Pi by adsorption to oxidic minerals and/or precipitation by iron and aluminum ions. The objectives of this study were to quantify phosphorus (P) uptake and use efficiency in cultivars of the species Coffea arabica L. and Coffea canephora L., and group them in terms of efficiency and response to Pi availa ...[more]

PMID: 27066047

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Project description:BACKGROUND: Coffee is one of the world's most important crops; it is consumed worldwide and plays a significant role in the economy of producing countries. Coffea arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency. RESULTS: Assembling the expressed sequence tags (ESTs) of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. canephora. We detected different GC3 profiles between these species that are related to their genome structure and mating system. BLAST analysis revealed similarities between coffee and grape (Vitis vinifera) genes. Using KA/KS analysis, we identified coffee genes under purifying and positive selection. Protein domain and gene ontology analyses suggested differences between Coffea spp. data, mainly in relation to complex sugar synthases and nucleotide binding proteins. OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species. Among the interesting families annotated are new cystatins, glycine-rich proteins and RALF-like peptides. Hierarchical clustering was used to independently group C. arabica and C. canephora expression clusters according to expression data extracted from EST libraries, resulting in the identification of differentially expressed genes. Based on these results, we emphasize gene annotation and discuss plant defenses, abiotic stress and cup quality-related functional categories. CONCLUSION: We present the first comprehensive genome-wide transcript profile study of C. arabica and C. canephora, which can be freely assessed by the scientific community at http://www.lge.ibi.unicamp.br/coffea. Our data reveal the presence of species-specific/prevalent genes in coffee that may help to explain particular characteristics of these two crops. The identification of differentially expressed transcripts offers a starting point for the correlation between gene expression profiles and Coffea spp. developmental traits, providing valuable insights for coffee breeding and biotechnology, especially concerning sugar metabolism and stress tolerance.

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Dataset Information

Analysis of Phosphorus Use Efficiency Traits in Coffea Genotypes Reveals Coffea arabica and Coffea canephora Have Contrasting Phosphorus Uptake and Utilization Efficiencies.

Background and aims

Methods

Key results

Publications

Analysis of Phosphorus Use Efficiency Traits in Coffea Genotypes Reveals Coffea arabica and Coffea canephora Have Contrasting Phosphorus Uptake and Utilization Efficiencies.

Similar Datasets

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