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Improving the quality of African robustas: QTLs for yield- and quality-related traits in Coffea canephora

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Abstract

Coffea canephora breeding requires combining sustainable productivity with improved technological and cup quality characteristics. Beverage quality is a complex and subjective trait, and breeding for this trait is time consuming and depends on knowledge of the genetics of its components. A highly variable C. canephora progeny resulting from an intraspecific cross was assessed for 63 traits over 5 years. To identify quantitative trait loci (QTLs) controlling agronomic, technological, and quality-related traits, a genetic map comprising 236 molecular markers was constructed, and composite interval mapping was performed. Beverage quality was evaluated in relation to biochemical and cup tasting traits. QTLs were identified for almost half of the traits evaluated, with effects ranging from 6% to 80% of phenotypic variation. Most of them present a consistent detection over years. The strongest QTLs explained a high percentage of the variation for yield in 2006 (34% to 57%), bean size (25% to 35%), content of chlorogenic acids (22% to 35%), sucrose and trigonelline content (29% to 81%), and acidity and bitterness of coffee beverages (30% to 55%). Regions of the C. canephora genome influencing beverage quality were identified. Five QTL zones were co-localized with candidate genes related to the biosynthesis of the analyzed traits: two genes coding for caffeine biosynthesis, one gene implicated in the biosynthesis of chlorogenic acids, and two genes implicated in sugar metabolism. This is one of the first studies on the identification of QTLs combining agronomic and quality traits in coffee. The high variability of quality traits within C. canephora and the presence of consistent QTLs offer breeders a promising tool to improve coffee cup quality.

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Abbreviations

QTL:

Quantitative trait loci

MAS:

Marker-assisted selection

Y_200X :

Yield for the year 200X

CY_200X/Y :

Cumulated yield from year 200X to 200Y

BS:

Bean size

PB:

Rate of pea berries

CA:

Caffeine content

TR:

Trigonelline content

SU:

Sucrose content

3C:

3-Caffeoylquinic acid content (3-CQA)

4C:

4-Caffeoylquinic acid content (4-CQA)

5C:

5-Caffeoylquinic acid content (5-CQA)

5F:

5-Feruloylquinic acid content (5-FQA)

34dC:

3,4-Dicaffeoylquinic acid (3,4di-CQA)

35dC:

3,5-Dicaffeoylquinic acid (3,5di-CQA)

45dC:

4,5-Dicaffeoylquinic acid (4,5di-CQA)

FR:

Fragrance

AR:

Aroma

BO:

Body

FL:

Flavor

AC:

Acidity

BI:

Bitterness

AF:

Aftertaste

GL:

Global note

LG:

Linkage group

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Acknowledgments

This work was supported by EU grant ICA4-CT-2001-10068. The University of Trieste (Italy) kindly provided 16 SSR markers.

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Authors and Affiliations

  1. UMR AGAP, CIRAD, 34398, Montpellier, France

    Thierry Leroy, Fabien De Bellis, Pierre Charmetant, Philippe Cubry, Pierre Marraccini & David Pot

  2. UMR RPB, CIRAD, 34398, Montpellier, France

    Christophe Montagnon

  3. Centre National de Recherche Agronomique (CNRA), BP 808, Divo, Ivory Coast

    Hyacinthe Legnate

  4. National Agricultural Research Organisation (NARO), P.O. Box 185, Kituza, Mukono, Uganda

    Edmund Kananura

  5. Department of Analytical chemistry, University of Seville, 41012, Seville, Spain

    Gustavo Gonzales

  6. Instituto Agronomico do Paraná (IAPAR), LBI-AMG, CP 481, 86001–970, Londrina, Paraná, Brazil

    Luiz Felipe Pereira

  7. Laboratory of Molecular Genetics (LGM-NTBio), Embrapa Genetic Resources and Biotechnology, CP 02372, 70770–900, Brazilian Federal District, Brazil

    Alan Carvalho Andrade

  8. UMR DIADE, IRD, 34394, Montpellier, France

    Alexandre de Kochko

Authors
  1. Thierry Leroy
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  2. Fabien De Bellis
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  3. Hyacinthe Legnate
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  4. Edmund Kananura
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  5. Gustavo Gonzales
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  6. Luiz Felipe Pereira
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  7. Alan Carvalho Andrade
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  8. Pierre Charmetant
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  9. Christophe Montagnon
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  10. Philippe Cubry
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  11. Pierre Marraccini
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  12. David Pot
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  13. Alexandre de Kochko
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Corresponding author

Correspondence to Thierry Leroy.

Additional information

Communicated by D. Grattapaglia

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Table S1

Quantitative trait analysis: number of productive trees, mean, standard deviation (SD), minimum and maximum values for yield, technological, biochemical, and organoleptic traits. Means for parents are presented (XLS 31 kb)

Table S2

Phenotypic correlations for the 63 traits analyzed (Pearson’s correlation test). Only significant correlations are shown (**P<0.01 in gray; *P<0.05). (ns) not significant (XLS 89 kb)

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Leroy, T., De Bellis, F., Legnate, H. et al. Improving the quality of African robustas: QTLs for yield- and quality-related traits in Coffea canephora . Tree Genetics & Genomes 7, 781–798 (2011). https://doi.org/10.1007/s11295-011-0374-6

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