Comparison of three QTL detection models on biochemical, sensory, and yield characters in Coffea canephora

Mangin, Brigitte; Lefebvre-Pautigny, Florent; Jasson, Sylvain; Rigoreau, Michel; Husson, Jwanro; Lambot, Charles; Crouzillat, Dominique

doi:10.1007/s11295-014-0778-1

Cited by 12 publications

(15 citation statements)

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“…The high‐density Robusta genetic map generated from this study will not only be useful in ordering future genetic maps such as the one for Arabica, but also in providing a higher marker density than the previous one (Mérot‐L'Anthoëne et al ., ). It will aid in selecting appropriate markers for various molecular breeding applications and in tracking introgression within each linkage group.…”

Section: Discussionmentioning

confidence: 97%

“…The mapping of 1307 (15.2%) of the Coffee8.5K SNPs on the C. canephora map (BP409 X Q121) demonstrates the usefulness of the Coffee8.5K for developing high‐density genetic maps for this species. Combined with previously developed markers (Denoeud et al ., ; Mérot‐L'Anthoëne et al ., ), we obtained a reliable and accurate final map of 3039 markers, including 665 SNPs in coding regions, with only a low fraction of distorted markers. The total map length was 1370 cM with an average distance of 2.2 cM between markers.…”

Section: Discussionmentioning

confidence: 97%

“…The Robusta (BP409xQ121) genetic linkage map was built using JoinMap ® 4.1 software (Van Ooijen, ) with the regression mapping algorithm and the grouping and recombination settings as described in Mérot‐L'Anthoëne et al . (). The Kosambi mapping function was used to convert recombination frequencies into map distance and the linkage maps were drawn using MapChart 2.3 (Plant Research International, Wageningen, Netherlands).…”

Section: Methodsmentioning

confidence: 97%

“…Such maps have already been initiated for C. canephora (Denoeud et al ., ; Lefebvre‐Pautigny et al ., ; Leroy et al ., ), and C. arabica (Moncada et al ., ; Pearl et al ., ). Some of these maps were also used to identify QTLs for agronomic and quality‐related traits in C. canephora (Leroy et al ., ; Mérot‐L'Anthoëne et al ., ) and C. arabica (Moncada et al ., ). However, the use of SNP markers to generate denser maps has been poorly exploited so far.…”

Section: Introductionmentioning

confidence: 99%

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Development and evaluation of a genome‐wide Coffee 8.5K SNP array and its application for high‐density genetic mapping and for investigating the origin of Coffea arabica L.

Mérot-L’Anthoëne

Tournebize

Darracq

et al. 2019

Plant Biotechnology Journal

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Summary Coffee species such as Coffea canephora P. (Robusta) and C. arabica L. (Arabica) are important cash crops in tropical regions around the world. C. arabica is an allotetraploid (2 n = 4 x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2 n = 2 x = 22). Interestingly, these progenitor species harbour a greater level of genetic variability and are an important source of genes to broaden the narrow Arabica genetic base. Here, we describe the development, evaluation and use of a single‐nucleotide polymorphism ( SNP ) array for coffee trees. A total of 8580 unique and informative SNP s were selected from C. canephora and C. arabica sequencing data, with 40% of the SNP located in annotated genes. In particular, this array contains 227 markers associated to 149 genes and traits of agronomic importance. Among these, 7065 SNP s (~82.3%) were scorable and evenly distributed over the genome with a mean distance of 54.4 Kb between markers. With this array, we improved the Robusta high‐density genetic map by adding 1307 SNP markers, whereas 945 SNP s were found segregating in the Arabica mapping progeny. A panel of C. canephora accessions was successfully discriminated and over 70% of the SNP markers were transferable across the three species. Furthermore, the canephora‐derived subgenome of C. arabica was shown to be more closely related to C. canephora accessions from northern Uganda than to other current populations. These validated SNP markers and high‐density genetic maps will be useful to molecular genetics and for innovative approaches in coffee breeding.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Development and evaluation of a genome‐wide Coffee 8.5K SNP array and its application for high‐density genetic mapping and for investigating the origin of Coffea arabica L.

Mérot-L’Anthoëne

Tournebize

Darracq

et al. 2019

Plant Biotechnology Journal

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“…The good performance of the GS method highlights the importance of this tool in the Coffea genus. To the best of our knowledge, molecular studies have been reported in coffee; however, most of them are still based on traditional molecular approaches (Ferrão et al 2013;Cubry et al 2013;Mérot-L'Anthoëne et al 2014). Large-scale genotyping expands their utility.…”

Section: Discussionmentioning

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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Advances in genomics for the improvement of quality in coffee

et al. 2016

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Coffee is an important crop that provides a livelihood to millions of people living in developing countries. Production of genotypes with improved coffee quality attributes is a primary target of coffee genetic improvement programs. Advances in genomics are providing new tools for analysis of coffee quality at the molecular level. The recent report of a genomic sequence for robusta coffee, Coffea canephora, is a major development. However, a reference genome sequence for the genetically more complex arabica coffee (C. arabica) will also be required to fully define the molecular determinants controlling quality in coffee produced from this high quality coffee species. Genes responsible for control of the levels of the major biochemical components in the coffee bean that are known to be important in determining coffee quality can now be identified by association analysis. However, the narrow genetic base of arabica coffee suggests that genomics analysis of the wild relatives of coffee (Coffea spp.) may be required to find the phenotypic diversity required for effective association genetic analysis. The genomic resources available for the study of coffee quality are described and the potential for the application of next generation sequencing and association genetic analysis to advance coffee quality research are explored.Key words: Coffee quality, genetics, genomics, biochemical compounds, next generation sequencing, association studies.This article is protected by copyright. All rights reserved. Accepted Article GENERAL INTRODUCTIONCoffee is an important crop and the second most traded commodity in the world (after petroleum) providing a living to more than 125 million people .Commercial coffee production is dominated by only two species belonging to the Coffea genus: C. arabica and C. canephora (the latter generally referred to as robusta coffee). All coffee species are diploid (2n=2x=22) and generally self-incompatible, except for C. arabica which is a self-fertile tetraploid (2n=4x=44) derived from a spontaneous hybridization between C. canephora (as paternal progenitor) and C.eugenioides (as maternal progenitor) 8 9.Although C. arabica is considered to have better cupping quality than C. canephora, improving the quality of both commercial species remains a target for most coffee improvement programs. With advances in genomic and sequencing technology, it is feasible to understand the coffee genome and the molecular inheritance underlying coffee quality, thereby helping improve the efficiency of breeding programs.This review will discuss current knowledge regarding the genetics of those biochemical compounds which are considered quality determinants, for use as a foundation for improving coffee quality by breeding. Available genomic resources for the study of the genetics of biochemical compounds that are likely to be playing a role in coffee flavour will also be discussed. In addition, the potential value of the study of genetics of coffee This article is protected by copyright. All rights reserved.Ac...

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Comparison of three QTL detection models on biochemical, sensory, and yield characters in Coffea canephora

Cited by 12 publications

References 51 publications

Development and evaluation of a genome‐wide Coffee 8.5K SNP array and its application for high‐density genetic mapping and for investigating the origin of Coffea arabica L.

Development and evaluation of a genome‐wide Coffee 8.5K SNP array and its application for high‐density genetic mapping and for investigating the origin of Coffea arabica L.

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

Advances in genomics for the improvement of quality in coffee

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