In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense

Basal stem rot caused by Ganoderma boninense is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for Ganoderma resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years' worth of data collected during pre-nursery tests revealed the quantitative nature of Ganoderma resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with Ganoderma when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of Ganoderma resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs.

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Main Authors: Daval, Aurélie, Pomiès, Virginie, Le Squin, Sandrine, Denis, Marie, Riou, Virginie, Breton, Frédéric, Nopariansyah, Bink, Marco, Cochard, Benoît, Jacob, Florence, Billotte, Norbert, Tisne, Sébastien
Format: article biblioteca
Language:eng
Subjects:H20 - Maladies des plantes, F30 - Génétique et amélioration des plantes, résistance aux maladies, maladie des plantes, sélection, Elaeis guineensis, locus des caractères quantitatifs, Ganoderma, pourriture, programme d'amélioration, http://aims.fao.org/aos/agrovoc/c_2328, http://aims.fao.org/aos/agrovoc/c_5962, http://aims.fao.org/aos/agrovoc/c_6951, http://aims.fao.org/aos/agrovoc/c_2509, http://aims.fao.org/aos/agrovoc/c_37974, http://aims.fao.org/aos/agrovoc/c_15973, http://aims.fao.org/aos/agrovoc/c_6667, http://aims.fao.org/aos/agrovoc/c_1d441805,
Online Access:http://agritrop.cirad.fr/599350/
http://agritrop.cirad.fr/599350/1/Daval_et_al-2021-Molecular_Breeding.pdf
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spelling dig-cirad-fr-5993502024-06-27T16:05:49Z http://agritrop.cirad.fr/599350/ http://agritrop.cirad.fr/599350/ In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense. Daval Aurélie, Pomiès Virginie, Le Squin Sandrine, Denis Marie, Riou Virginie, Breton Frédéric, Nopariansyah, Bink Marco, Cochard Benoît, Jacob Florence, Billotte Norbert, Tisne Sébastien. 2021. Molecular Breeding, 41 (9):53, 18 p.https://doi.org/10.1007/s11032-021-01246-9 <https://doi.org/10.1007/s11032-021-01246-9> In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense Daval, Aurélie Pomiès, Virginie Le Squin, Sandrine Denis, Marie Riou, Virginie Breton, Frédéric Nopariansyah, Bink, Marco Cochard, Benoît Jacob, Florence Billotte, Norbert Tisne, Sébastien eng 2021 Molecular Breeding H20 - Maladies des plantes F30 - Génétique et amélioration des plantes résistance aux maladies maladie des plantes sélection Elaeis guineensis locus des caractères quantitatifs Ganoderma pourriture programme d'amélioration http://aims.fao.org/aos/agrovoc/c_2328 http://aims.fao.org/aos/agrovoc/c_5962 http://aims.fao.org/aos/agrovoc/c_6951 http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_37974 http://aims.fao.org/aos/agrovoc/c_15973 http://aims.fao.org/aos/agrovoc/c_6667 http://aims.fao.org/aos/agrovoc/c_1d441805 Basal stem rot caused by Ganoderma boninense is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for Ganoderma resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years' worth of data collected during pre-nursery tests revealed the quantitative nature of Ganoderma resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with Ganoderma when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of Ganoderma resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/599350/1/Daval_et_al-2021-Molecular_Breeding.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1007/s11032-021-01246-9 10.1007/s11032-021-01246-9 info:eu-repo/semantics/altIdentifier/doi/10.1007/s11032-021-01246-9 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/s11032-021-01246-9 info:eu-repo/grantAgreement/EC/H2020/840383//(EU) Innovative Statistical modelling for a better Understanding of Longitudinal multivariate responses in relation to Omic datasets/ISULO
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic H20 - Maladies des plantes
F30 - Génétique et amélioration des plantes
résistance aux maladies
maladie des plantes
sélection
Elaeis guineensis
locus des caractères quantitatifs
Ganoderma
pourriture
programme d'amélioration
http://aims.fao.org/aos/agrovoc/c_2328
http://aims.fao.org/aos/agrovoc/c_5962
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_15973
http://aims.fao.org/aos/agrovoc/c_6667
http://aims.fao.org/aos/agrovoc/c_1d441805
H20 - Maladies des plantes
F30 - Génétique et amélioration des plantes
résistance aux maladies
maladie des plantes
sélection
Elaeis guineensis
locus des caractères quantitatifs
Ganoderma
pourriture
programme d'amélioration
http://aims.fao.org/aos/agrovoc/c_2328
http://aims.fao.org/aos/agrovoc/c_5962
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_15973
http://aims.fao.org/aos/agrovoc/c_6667
http://aims.fao.org/aos/agrovoc/c_1d441805
spellingShingle H20 - Maladies des plantes
F30 - Génétique et amélioration des plantes
résistance aux maladies
maladie des plantes
sélection
Elaeis guineensis
locus des caractères quantitatifs
Ganoderma
pourriture
programme d'amélioration
http://aims.fao.org/aos/agrovoc/c_2328
http://aims.fao.org/aos/agrovoc/c_5962
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_15973
http://aims.fao.org/aos/agrovoc/c_6667
http://aims.fao.org/aos/agrovoc/c_1d441805
H20 - Maladies des plantes
F30 - Génétique et amélioration des plantes
résistance aux maladies
maladie des plantes
sélection
Elaeis guineensis
locus des caractères quantitatifs
Ganoderma
pourriture
programme d'amélioration
http://aims.fao.org/aos/agrovoc/c_2328
http://aims.fao.org/aos/agrovoc/c_5962
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_15973
http://aims.fao.org/aos/agrovoc/c_6667
http://aims.fao.org/aos/agrovoc/c_1d441805
Daval, Aurélie
Pomiès, Virginie
Le Squin, Sandrine
Denis, Marie
Riou, Virginie
Breton, Frédéric
Nopariansyah,
Bink, Marco
Cochard, Benoît
Jacob, Florence
Billotte, Norbert
Tisne, Sébastien
In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
description Basal stem rot caused by Ganoderma boninense is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for Ganoderma resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years' worth of data collected during pre-nursery tests revealed the quantitative nature of Ganoderma resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with Ganoderma when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of Ganoderma resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs.
format article
topic_facet H20 - Maladies des plantes
F30 - Génétique et amélioration des plantes
résistance aux maladies
maladie des plantes
sélection
Elaeis guineensis
locus des caractères quantitatifs
Ganoderma
pourriture
programme d'amélioration
http://aims.fao.org/aos/agrovoc/c_2328
http://aims.fao.org/aos/agrovoc/c_5962
http://aims.fao.org/aos/agrovoc/c_6951
http://aims.fao.org/aos/agrovoc/c_2509
http://aims.fao.org/aos/agrovoc/c_37974
http://aims.fao.org/aos/agrovoc/c_15973
http://aims.fao.org/aos/agrovoc/c_6667
http://aims.fao.org/aos/agrovoc/c_1d441805
author Daval, Aurélie
Pomiès, Virginie
Le Squin, Sandrine
Denis, Marie
Riou, Virginie
Breton, Frédéric
Nopariansyah,
Bink, Marco
Cochard, Benoît
Jacob, Florence
Billotte, Norbert
Tisne, Sébastien
author_facet Daval, Aurélie
Pomiès, Virginie
Le Squin, Sandrine
Denis, Marie
Riou, Virginie
Breton, Frédéric
Nopariansyah,
Bink, Marco
Cochard, Benoît
Jacob, Florence
Billotte, Norbert
Tisne, Sébastien
author_sort Daval, Aurélie
title In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
title_short In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
title_full In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
title_fullStr In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
title_full_unstemmed In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense
title_sort in silico qtl mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to ganoderma boninense
url http://agritrop.cirad.fr/599350/
http://agritrop.cirad.fr/599350/1/Daval_et_al-2021-Molecular_Breeding.pdf
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