Advances in genomics for the improvement of quality in coffee

Tran, Hue T.; Lee, L. Slade; Furtado, Agnelo; Smyth, Heather E.; Henry, Robert J.

doi:10.1002/jsfa.7692

Cited by 49 publications

(44 citation statements)

References 131 publications

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“…Brazil has held this position for the last 150 years (IOC 2016). The Coffea genus comprises hundreds of tropical species and the beverage popularly known as coffee is produced from grains of two species: Coffea arabica, which contributes to the aroma and sweet flavor; and Coffea canephora, with higher amounts of caffeine and soluble solids (Tran et al 2016). Global efforts have been made to increase production and quality of the final product.…”

Section: Introductionmentioning

confidence: 99%

A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora

Ferrão

Ferrão³

et al. 2017

Tree Genetics & Genomes

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Genomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and Communicated by: J. Beaulieu This article is part of the Topical Collection on Breeding Key Message: First insights into the Genotyping-by-Sequencing (GBS) in Coffea canephora and a genomic prediction model considering the theory about multiplicative mixed model to accommodate the interaction effects across sites and harvests genomic analysis was performed using a genotyping-bysequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodnessof-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10-17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops.

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Section: Introductionmentioning

confidence: 99%

A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora

Ferrão

Ferrão³

et al. 2017

Tree Genetics & Genomes

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“…Other low molecular sugars, for instance, glucose and fructose may also degrade or react with amino acids, but in green beans they represent only about 0.5% of the total. Sucrose content depends on the coffee genotype, with 7.4-11.1% in Arabica and 4.05-7.05% in Robusta (Tran, Slade Lee et al, , 2016). Shade was found to reduce sucrose significantly by delaying the peak of SUS and SPS enzyme activity and resulting in higher SUS2 transcripts in coffee endosperm.…”

Section: Chemical Attributesmentioning

confidence: 96%

Review on Genetic, Environment and Their Interaction (G x E) for Stability of Coffee Quality

2019

JBAH

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Coffee (Coffea arabica L.) is a highly valuable export commodity in the world. More than 50 developing countries, 25 of them in Africa. The labor intensive tree crop also provides much employment in rural areas. However, international market has always been fluctuating affected mainly by Genetic, environment and its' interaction. Diversity of coffee quality due to G x E, result from influences on the biochemical components of the coffee bean accumulated during seed development. Assessment of coffee quality is usually focused on factors that influence utilization of the final product with consumer preferences being assessed in three primary ways: physical (e.g. bean size), sensorial (cup quality) and chemical analysis. Previous studies on coffee have shown that there is a differential response of quality when grown under different conditions and environments. Nevertheless, further research is important with understanding of coffee metabolism, different genotypes or environment impacts on coffee metabolism and how gene, environment and their interaction affects coffee quality.

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“…Previous studies had mainly used the mining of expressed sequence tags (ESTs) or transcriptome data for SNP discovery (Combes et al, 2013;Kochko et al, 2010;Vidal et al, 2010;Yuyama et al, 2016;Zhou et al, 2016). QTL mapping for quality traits has been conducted for C. canephora only (reviewed by Tran et al, 2016). Such studies involved limited genetic variation contributed from two parents.…”

Section: Conclusion and Suggestionsmentioning

confidence: 99%

Genomic studies of biochemical compounds determining arabica coffee (Coffea arabica L.) quality

Tran¹

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Coffee is an important crop globally. Improving coffee quality is a primary breeding target that would benefit from understanding of trait inheritance and ancestral genetic information. However, comparatively little information exists on the genetics of quality and the relationships between wild and cultivated coffee genotypes, especially arabica coffee (Coffea arabica L.) which accounts for almost 60% of coffee production globally. The complex polyploidy genome and limited genomic information for C. arabica have impeded the progress of genetic studies. Arabica coffee is among the major organisms that do not have a reference genome. This project aimed to develop and utilise genomic resources in genetic studies of arabica coffee quality. The relationship between coffee species and the position of arabica within the Coffeeae tribe were investigated using complete chloroplast genome sequences to determine the value of these genetic resources in breeding. A draft genome sequence of arabica coffee was developed. Marker-trait associations were studied for caffeine and trigonelline, the two principal compounds known to be related to coffee quality, paving the way for developing new improved varieties with preferred levels of these compounds in the coffee beans.Chloroplast genomes of 16 coffee species were sequenced and their phylogeny constructed. Results support distinct Psilanthus and Coffea clades. It is likely that C. canephora is a hybrid that has a Psilanthus maternal genome but received much of its nuclear genome from Coffea. The maternal genomes of C. arabica and C. canephora are divergent. This result is in agreement with the fact that the chloroplast genome of arabica should be that of the maternal parent i.e. C. eugenioides. There were two species (C. humblotiana and C. tetragona) close to C. arabica and one species (P. ebracteolatus) close to C. canephora containing almost no caffeine. They could serve as important materials in arabica quality breeding and research.For the association study, 232 diverse arabica coffee accessions originating from 27 countries were harvested from the germplasm collection at CATIE (Tropical Agricultural Research and Higher Education Centre), Costa Rica. Substantial variation between genotypes was observed for bean morphology attributes. Non-volatiles including caffeine and trigonelline showed larger variation in range than was previously reported. Results of targeted analysis of 18 volatiles from 35 accessions also showed significant variation. No strong correlation was found between bean morphology and the levels of non-volatile or volatile compounds, implying that it is difficult to select for low or high non-volatile and volatile compounds based on bean physical characteristics. However, it also indicates that breeding for desirable combinations of traits (i.e. large bean size, low caffeine, high trigonelline, and favourable volatiles) is possible.ii The genome of the most popular arabica variety (K7) in Australia was sequenced. Genome assembly was performed using b...

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Advances in genomics for the improvement of quality in coffee

Cited by 49 publications

References 131 publications

A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora

A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora

Review on Genetic, Environment and Their Interaction (G x E) for Stability of Coffee Quality

Genomic studies of biochemical compounds determining arabica coffee (Coffea arabica L.) quality

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