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.

Virginie Merot-L'anthoene, Rémi Tournebize, Olivier Darracq, Vimel Rattina, Maud Lepelley, Laurence Bellanger, Christine Tranchant-Dubreuil, Manon Coulée, Marie Pégard, Sylviane Metairon, Coralie Fournier, Piet Stoffelen, Steven B. Janssens, Catherine Kiwuka, Pascal Musoli, Ucu Sumirat, Hyacinthe Legnaté, Jean Léon Kambale, João Ferreira da Costa Neto, Clara Revel & 4 others Alexandre de Kochko, Patrick Descombes, Dominique Crouzillat, Valérie Poncet*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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 (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 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 SNPs 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 SNPs (~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 SNPs 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.

Original languageEnglish
Pages (from-to)1418-1430
Number of pages13
JournalPlant Biotechnology Journal
Volume17
Issue number7
DOIs
Publication statusPublished - 1 Jul 2019

Fingerprint

Coffea
Coffee
Coffea arabica
single nucleotide polymorphism
chromosome mapping
Single Nucleotide Polymorphism
Genome
genome
Coffea canephora
cash crops
genes
Uganda
agronomic traits
molecular genetics
genetic background
Genes
tropics
diploidy
hybridization
Diploidy

Keywords

  • C. canephora
  • C. eugenioides
  • Coffea arabica origin
  • genetic map
  • single-nucleotide polymorphism
  • SNP array

Cite this

Merot-L'anthoene, Virginie ; Tournebize, Rémi ; Darracq, Olivier ; Rattina, Vimel ; Lepelley, Maud ; Bellanger, Laurence ; Tranchant-Dubreuil, Christine ; Coulée, Manon ; Pégard, Marie ; Metairon, Sylviane ; Fournier, Coralie ; Stoffelen, Piet ; Janssens, Steven B. ; Kiwuka, Catherine ; Musoli, Pascal ; Sumirat, Ucu ; Legnaté, Hyacinthe ; Kambale, Jean Léon ; Ferreira da Costa Neto, João ; Revel, Clara ; de Kochko, Alexandre ; Descombes, Patrick ; Crouzillat, Dominique ; Poncet, Valérie. / 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. In: Plant Biotechnology Journal. 2019 ; Vol. 17, No. 7. pp. 1418-1430.
@article{4e9329f1ad13447a8538afec4ae53866,
title = "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.",
abstract = "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 (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 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 SNPs 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 SNPs (~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 SNPs 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.",
keywords = "C. canephora, C. eugenioides, Coffea arabica origin, genetic map, single-nucleotide polymorphism, SNP array",
author = "Virginie Merot-L'anthoene and R{\'e}mi Tournebize and Olivier Darracq and Vimel Rattina and Maud Lepelley and Laurence Bellanger and Christine Tranchant-Dubreuil and Manon Coul{\'e}e and Marie P{\'e}gard and Sylviane Metairon and Coralie Fournier and Piet Stoffelen and Janssens, {Steven B.} and Catherine Kiwuka and Pascal Musoli and Ucu Sumirat and Hyacinthe Legnat{\'e} and Kambale, {Jean L{\'e}on} and {Ferreira da Costa Neto}, Jo{\~a}o and Clara Revel and {de Kochko}, Alexandre and Patrick Descombes and Dominique Crouzillat and Val{\'e}rie Poncet",
year = "2019",
month = "7",
day = "1",
doi = "10.1111/pbi.13066",
language = "English",
volume = "17",
pages = "1418--1430",
journal = "Plant Biotechnology Journal",
issn = "1467-7644",
publisher = "Wiley",
number = "7",

}

Merot-L'anthoene, V, Tournebize, R, Darracq, O, Rattina, V, Lepelley, M, Bellanger, L, Tranchant-Dubreuil, C, Coulée, M, Pégard, M, Metairon, S, Fournier, C, Stoffelen, P, Janssens, SB, Kiwuka, C, Musoli, P, Sumirat, U, Legnaté, H, Kambale, JL, Ferreira da Costa Neto, J, Revel, C, de Kochko, A, Descombes, P, Crouzillat, D & Poncet, V 2019, '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.', Plant Biotechnology Journal, vol. 17, no. 7, pp. 1418-1430. https://doi.org/10.1111/pbi.13066

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. / Merot-L'anthoene, Virginie; Tournebize, Rémi; Darracq, Olivier; Rattina, Vimel; Lepelley, Maud; Bellanger, Laurence; Tranchant-Dubreuil, Christine; Coulée, Manon; Pégard, Marie; Metairon, Sylviane; Fournier, Coralie; Stoffelen, Piet; Janssens, Steven B.; Kiwuka, Catherine; Musoli, Pascal; Sumirat, Ucu; Legnaté, Hyacinthe; Kambale, Jean Léon; Ferreira da Costa Neto, João; Revel, Clara; de Kochko, Alexandre; Descombes, Patrick; Crouzillat, Dominique; Poncet, Valérie.

In: Plant Biotechnology Journal, Vol. 17, No. 7, 01.07.2019, p. 1418-1430.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - 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.

AU - Merot-L'anthoene, Virginie

AU - Tournebize, Rémi

AU - Darracq, Olivier

AU - Rattina, Vimel

AU - Lepelley, Maud

AU - Bellanger, Laurence

AU - Tranchant-Dubreuil, Christine

AU - Coulée, Manon

AU - Pégard, Marie

AU - Metairon, Sylviane

AU - Fournier, Coralie

AU - Stoffelen, Piet

AU - Janssens, Steven B.

AU - Kiwuka, Catherine

AU - Musoli, Pascal

AU - Sumirat, Ucu

AU - Legnaté, Hyacinthe

AU - Kambale, Jean Léon

AU - Ferreira da Costa Neto, João

AU - Revel, Clara

AU - de Kochko, Alexandre

AU - Descombes, Patrick

AU - Crouzillat, Dominique

AU - Poncet, Valérie

PY - 2019/7/1

Y1 - 2019/7/1

N2 - 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 (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 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 SNPs 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 SNPs (~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 SNPs 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.

AB - 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 (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 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 SNPs 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 SNPs (~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 SNPs 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.

KW - C. canephora

KW - C. eugenioides

KW - Coffea arabica origin

KW - genetic map

KW - single-nucleotide polymorphism

KW - SNP array

U2 - 10.1111/pbi.13066

DO - 10.1111/pbi.13066

M3 - Article

VL - 17

SP - 1418

EP - 1430

JO - Plant Biotechnology Journal

JF - Plant Biotechnology Journal

SN - 1467-7644

IS - 7

ER -