📊 Coffee QTL Mapping

Quantitative Trait Loci in Coffee

Comprehensive overview of quantitative trait loci (QTL) mapping studies in coffee, identifying genomic regions controlling yield, plant height, bean size, lipid content, and disease resistance to accelerate marker-assisted selection in breeding programs.

848 Markers in Linkage Map [1][2][3][5][8]
22 Linkage Groups [1][2][3][5][8]
3800 cM Total Map Length [1][2][3][5][8]
19 Lipid QTNs (2025) [10]
Arabica QTL Studies Robusta QTL Studies

The Role of QTL Mapping in Coffee Breeding

To breed a new variety of coffee (Coffea arabica) requires approximately 25 years due to the long generation time (5-6 years) of this perennial plant and the fact that it takes at least five generations of selection to obtain superior individuals [1][2][3][5][8].

One way to reduce the number of generations is to use marker-assisted selection (MAS). To implement MAS, it is necessary to develop a genetic map and to identify markers associated with quantitative trait loci (QTLs) governing traits of interest [1][2][3][5][8].

Quantitative trait loci are genomic regions associated with variation in complex traits that are controlled by multiple genes and environmental factors. In coffee, QTL mapping has been applied to:

  • Yield and productivity: Major QTLs for yield identified across multiple locations [1][2][3][5][8]
  • Plant architecture: Plant height and growth habit QTLs [1][2][3][5][6][8]
  • Bean quality: Bean size, lipid content, and biochemical traits [1][2][3][5][8][10]
  • Disease resistance: Coffee leaf rust (SH3, CC-NBS-LRR, RLK, QTL-GL2, GL5) and coffee berry disease (Ck-1) [7]
  • Vegetative growth: QTLs for primary branches, canopy width, internode length [6]

Recent advances in genotyping-by-sequencing (GBS) and high-density SNP arrays have enabled more precise QTL mapping and the identification of candidate genes underlying these traits [4][8][10].

Breeding Timeline

25 years (Traditional)
15-18 years (MAS)

Marker-assisted selection reduces the number of generations required for cultivar development [1][2][3][5][7][8].

Arabica Coffee QTL Mapping Study

A comprehensive QTL mapping study for yield, plant height, and bean size in Coffea arabica using an F₂ mapping population of 278 individuals from a cross between Caturra × CCC1046 [1][2][3][5][8].

Linkage Map Statistics
  • Mapping population: 278 Fâ‚‚ individuals (Caturra × CCC1046) [1][2][3][5][8]
  • Framework map: 338 SSR markers [1][2][3][5][8]
  • Integrated map: 848 SSR and SNP markers [1][2][3][5][8]
  • Linkage groups: 22 (corresponding to 11 chromosome pairs) [1][2][3][5][8]
  • Total map length: 3800 cM [1][2][3][5][8]
  • Software: R/qtl for marker integration [1][2][3][5][8]
QTLs Identified

Yield QTLs

  • Major yield QTL: Significant at two locations [1][2][3][5][8]
  • Second yield QTL: Significant at one location [1][2][3][5][8]

Plant Height QTLs

  • Two QTLs detected: For plant height [1][2][3][5][8]

Bean Size QTLs

  • Two QTLs detected: For bean size [1][2][3][5][8]

F₃ Progeny Evaluation

F₃ progenies of the mapping population were planted in five locations and evaluated for yield, plant height, and bean size, enabling detection of QTLs stable across environments [1][2][3][5][8].

Multi-location testing: The major yield QTL maintained significance across two different locations, indicating environmental stability and potential for marker-assisted selection [1][2][3][5][8].

Robusta Coffee QTL Studies

Vegetative Growth QTLs (2010)

Study using three C. canephora populations and six genetic maps developed using SSR and SNP markers [6].

Key Findings

  • Vegetative traits identified: 9 traits distributed over 7 linkage groups [6]
  • QTLs detected: 19 QTLs, consolidated to 12 unique QTLs [6]
  • Shared QTLs: 2 QTLs shared for multiple traits:
    • One involved for number/length of primary branches and width of canopy
    • One for length of internodes and width of canopy [6]

These two QTLs might determine the size of the tree canopy in this species [6].

Conilon Coffee Study (2025)

Assessment of 107 genotypes from the Incaper breeding program in Brazil evaluated for agronomic, physicochemical, sensory profiles, and molecular markers [9].

Key Findings

  • Genotypes: 107 Conilon coffee genotypes evaluated [9]
  • Traits examined: 30 traits including agronomic, physicochemical, and sensory [9]
  • Markers: 14 SSR markers examined [9]
  • Bioactive compounds: Chlorogenic acids (4.82%), caffeine (2.58%) [9]
  • High-quality genotypes: 34 genotypes scored ≥80 in sensory evaluation [9]
  • Markers for association mapping: 13 markers recommended for future QTL studies [9]

The progeny HS17 stood out as the most divergent in agronomic and genetic traits compared to other genotypes [9].

Lipid Content QTLs in Arabica Coffee (2025)

Genome-wide association studies (GWAS) were conducted to pinpoint quantitative trait nucleotides (QTNs) linked to lipid metabolism in Coffea arabica [10].

Study Design

  • Accessions: 104 wild C. arabica accessions, Mundo Novo cultivar, and C. arabica var. Typica [10]
  • Genotyping: Genotyping by sequencing (GBS) aligned to C. arabica Et039 reference genome [10]
  • Methods: Both single-locus and multi-locus GWAS methods employed [10]
  • Adjustments: Methods adjusted for kinship matrix, population structure, and principal component analysis [10]

Key Results

  • Total QTNs identified: 19 QTNs associated with lipid content [10]
  • Consistent QTNs: 5 showed consistency across different population structure adjustments [10]
  • Effective methods: Multi-locus methods mrMLM and FarmCPU proved more effective [10]
  • Candidate genes: 4 QTNs situated near 7 genes potentially involved in lipid metabolism [10]

Breeding Implications

Higher frequencies of identified QTNs in accessions with elevated lipid content suggest their utility as markers for coffee plant breeding [10].

Lipids in Coffee Quality

Lipids are compounds that play an important role in coffee bean development, contributing to beverage quality [10].

QTNs identified: These markers can be used for marker-assisted selection to improve lipid content and ultimately beverage quality.

Disease Resistance QTLs and Gene Pyramiding

Recent research has identified molecular markers at loci associated with coffee leaf rust (CLR) and coffee berry disease (CBD) resistance [7].

Disease Genes/Loci Marker Type Source
Coffee Leaf Rust (CLR) SH3, CC-NBS-LRR, RLK, QTL-GL2, GL5 9 molecular markers [7]
Coffee Berry Disease (CBD) Ck-1 Gene-specific markers [7]

Gene Pyramiding Results

The application of marker-assisted selection in coffee breeding programs accelerates the identification and concentration of target alleles, being essential for developing cultivars resistant to multiple diseases [7].

Summary of Coffee QTL Studies

Species Population Markers Map Length Traits QTLs Identified Reference
C. arabica Caturra × CCC1046 F₂ (278 individuals) 848 SSR and SNP 3800 cM (22 LGs) Yield, plant height, bean size Yield (2), Plant height (2), Bean size (2) [1][2][3][5][8]
C. canephora Three populations SSR and SNP - Vegetative growth (9 traits) 12 unique QTLs (19 total) [6]
C. arabica Wild accessions (104) + cultivars GBS (aligned to Et039) - Lipid content 19 QTNs (5 stable) [10]
C. canephora 107 genotypes (Incaper breeding program) 14 SSR markers - 30 agronomic, physicochemical, sensory traits 13 markers recommended for association mapping [9]

SSR Markers for Future QTL Studies

From the Conilon coffee study, 13 SSR markers were recommended for future association mapping studies to identify QTLs influencing agronomic, physicochemical, and sensory traits [9].

Marker Set Number Application
SSR markers for association mapping 13 QTL identification for agronomic, physicochemical, and sensory traits [9]

The study revealed significant genetic variability among 107 genotypes, with most exhibiting medium June harvest cycle, uniform ripening, medium-sized beans, high processing yield, and a high percentage of flat and peaberry beans [9].

Physicochemical variables, total titratable acidity, and potassium leaching contributed significantly to the observed variability [9].

TropGeneDB: Coffee QTL Database

Comprehensive database containing data from studies on tropical plants for markers, QTLs, genotypes, phenotypes, and genetic maps [4].

Contents

  • Markers: tropgene_coffee_markers.txt
  • QTLs: tropgene_coffee_qtls.txt
  • Genetic maps: tropgene_coffee_genetic_maps.txt
  • Physical maps: tropgene_coffee_physical_maps.txt
  • Germplasm: tropgene_coffee_germplasms.txt
  • References: tropgene_coffee_references.txt [4]

Data Scope

  • Data produced: 2003-2021
  • Data types: Marker, QTL, genotype, genetic map, physical map, germplasm
  • Species: Coffee, banana, cocoa, coconut, cotton, oil palm, rice, rubber, sorghum, sugarcane [4]
Access TropGeneDB

QTL Mapping Methodology

Software Tools

  • R/qtl: Used for integrating SSR and SNP markers in Arabica mapping study [1][2][3][5][8]
  • mrMLM: Multi-locus GWAS method effective for lipid QTNs [10]
  • FarmCPU: Multi-locus GWAS method effective for lipid QTNs [10]

Population Design

  • Fâ‚‚ populations: Used for initial QTL detection in Arabica [1][2][3][5][8]
  • F₃ progenies: Evaluated across multiple locations for environmental stability [1][2][3][5][8]
  • Wild accessions: Used for GWAS of lipid content [10]

Statistical Adjustments

  • Kinship matrix: Accounted for relatedness among individuals [10]
  • Population structure: Corrected for stratification [10]
  • Principal component analysis: Used for additional correction [10]

Marker Systems

  • SSR markers: 338 used for framework map, 14 evaluated in Conilon study [1][2][3][5][8][9]
  • SNP markers: Added for robust genetic map; 848 total markers [1][2][3][5][8]
  • GBS: Used for lipid QTN discovery [10]

Key Publications on Coffee QTL Mapping

A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size

Moncada M.P., Tovar E., Montoya J.C., González A., Spindel J., McCouch S. (2016). Tree Genetics & Genomes 12(1):5 [1][2][3][5][8]

848 SSR and SNP markers; 3800 cM map length; 22 linkage groups; QTLs for yield (2), plant height (2), and bean size (2).

View Abstract
A new set of quantitative trait loci linked to lipid content in Coffea arabica

Muniz H.V.L., Ariyoshi C., Ferreira R.V., Felicio M.S., Pereira L.F.P. (2025). Embrapa Café [10]

104 wild accessions + cultivars; GBS aligned to Et039; 19 QTNs identified; 5 stable across adjustments; 7 candidate genes for lipid metabolism.

View Abstract
Identification of Quantitative Trait Loci Determining Vegetative Growth Traits in Coffea Canephora

(2010). Nestlé R&D / ICCRI [6]

Three populations; 6 genetic maps; 9 vegetative traits; 19 QTLs (12 unique); 2 QTLs shared for multiple traits determining canopy size.

View Abstract
Quality of Conilon coffee based on agronomic, physicochemical, sensory profiles, and molecular markers

(2025). An Acad Bras Cienc 97(2):e20240084 [9]

107 genotypes; 30 traits; 14 SSR markers; 34 genotypes with sensory scores ≥80; 13 markers recommended for association mapping.

View Abstract
Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens

Mariz B.L., et al. (2025). Plants 14(3):391 [7]

SH3, CC-NBS-LRR, RLK, QTL-GL2, GL5 for CLR; Ck-1 for CBD; 98.6% resistance alleles; 29% 5-gene pyramiding.

View Abstract
TropGene Coffee Database

Hamelin C. (2024). CIRAD Dataverse [4]

QTL data from coffee studies 2003-2021; marker, genetic map, and germplasm information; open-access database.

Access Database
View All Publications →

References

Peer-reviewed sources and official reports cited in this research

[1] Moncada, M.P., Tovar, E., Montoya, J.C., González, A., Spindel, J., & McCouch, S. (2016). A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size. Tree Genetics & Genomes, 12(1), 5. AGRIS
[2] Moncada, M.P., Tovar, E., Montoya, J.C., González, A., Spindel, J., & McCouch, S. (2016). A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size. Tree Genetics & Genomes, 12(1), 5. INFONA
[3] Moncada, M.P., Tovar, E., Montoya, J.C., González, A., Spindel, J., & McCouch, S. (2016). A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size. Tree Genetics & Genomes, 12(1), 5. NU Find
[4] Hamelin, C. (2024). TropGene Coffee. CIRAD Dataverse. doi:10.18167/DVN1/BPI9YJ
[5] Moncada, M.P., Tovar, E., Montoya, J.C., González, A., Spindel, J., & McCouch, S. (2016). A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size. Tree Genetics & Genomes, 12(1), 5. Semantic Scholar
[6] Identification of Quantitative Trait Loci Determining Vegetative Growth Traits in Coffea Canephora. (2010). Nestlé R&D / ICCRI. CORE
[7] Mariz, B.L., Caixeta, E.T., Resende, M.D.V., Oliveira, A.C.B., Almeida, D.P., & Alves, D.R. (2025). Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs. Plants, 14(3), 391. OUCI
[8] Moncada, M.P., Tovar, E., Montoya, J.C., González, A., Spindel, J., & McCouch, S. (2016). A genetic linkage map of coffee (Coffea arabica L.) and QTL for yield, plant height, and bean size. Tree Genetics & Genomes, 12(1), 5. 中国地质图书馆
[9] Quality of Conilon coffee based on agronomic, physicochemical, sensory profiles, and molecular markers. (2025). Anais da Academia Brasileira de Ciências, 97(2), e20240084. VHL
[10] Muniz, H.V.L., Ariyoshi, C., Ferreira, R.V., Felicio, M.S., & Pereira, L.F.P. (2025). A new set of quantitative trait loci linked to lipid content in Coffea arabica. Embrapa Café. AGRIS

* Additional references available in the complete Publications Database. All sources have been peer-reviewed and are accessible through academic databases.