Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.)
Genomic selection (GS) is a method of marker-assisted selection revolutionizing crop improvement, but it can still be optimized. For hybrid breeding between heterozygote parents of different populations or species, specific aspects can be considered to increase GS accuracy: (1) training population genotyping, i.e., only genotyping the hybrid parents or also a sample of hybrid individuals, and (2) marker effects modeling, i.e., using population-specific effects of single nucleotide polymorphism alleles model (PSAM) or across-population SNP genotype model (ASGM). Here, this was investigated empirically for the prediction of the performances of oil palm hybrids for yield traits. The GS model was trained on 352 hybrid crosses and validated on 213 independent hybrid crosses. The training and validation hybrid parents and 399 training hybrid individuals were genotyping by sequencing. Despite the small proportion of hybrid individuals genotyped and low parental heterozygosity, GS prediction accuracy increased on average by 5% (range 1.4–31.3%, depending on trait and model) when training was done using genomic data on hybrids and parents compared with only parental genomic data. With ASGM, GS prediction accuracy increased on average by 3% (− 10.2 to 40%, depending on trait and genotyping strategy) compared with PSAM. We conclude that the best GS strategy for oil palm is to aggregate genomic data of parents and hybrid individuals and to ignore the parental origin of marker alleles (ASGM). To gain a better insight into these results, future studies should examine the respective effect of capturing genetic variability within crosses and taking segregation distortion into account when genotyping hybrid individuals, and investigate the factors controlling the relative performances of ASGM and PSAM in hybrid crops.
id |
dig-cirad-fr-600292 |
---|---|
record_format |
koha |
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 |
F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 |
spellingShingle |
F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 Nyouma, Achille Bell, Joseph Martin Jacob, Florence Riou, Virginie Manez, Aurore Pomiès, Virginie Domonhedo, Hubert Arifiyanto, Deni Cochard, Benoît Durand-Gasselin, Tristan Cros, David Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
description |
Genomic selection (GS) is a method of marker-assisted selection revolutionizing crop improvement, but it can still be optimized. For hybrid breeding between heterozygote parents of different populations or species, specific aspects can be considered to increase GS accuracy: (1) training population genotyping, i.e., only genotyping the hybrid parents or also a sample of hybrid individuals, and (2) marker effects modeling, i.e., using population-specific effects of single nucleotide polymorphism alleles model (PSAM) or across-population SNP genotype model (ASGM). Here, this was investigated empirically for the prediction of the performances of oil palm hybrids for yield traits. The GS model was trained on 352 hybrid crosses and validated on 213 independent hybrid crosses. The training and validation hybrid parents and 399 training hybrid individuals were genotyping by sequencing. Despite the small proportion of hybrid individuals genotyped and low parental heterozygosity, GS prediction accuracy increased on average by 5% (range 1.4–31.3%, depending on trait and model) when training was done using genomic data on hybrids and parents compared with only parental genomic data. With ASGM, GS prediction accuracy increased on average by 3% (− 10.2 to 40%, depending on trait and genotyping strategy) compared with PSAM. We conclude that the best GS strategy for oil palm is to aggregate genomic data of parents and hybrid individuals and to ignore the parental origin of marker alleles (ASGM). To gain a better insight into these results, future studies should examine the respective effect of capturing genetic variability within crosses and taking segregation distortion into account when genotyping hybrid individuals, and investigate the factors controlling the relative performances of ASGM and PSAM in hybrid crops. |
format |
article |
topic_facet |
F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 |
author |
Nyouma, Achille Bell, Joseph Martin Jacob, Florence Riou, Virginie Manez, Aurore Pomiès, Virginie Domonhedo, Hubert Arifiyanto, Deni Cochard, Benoît Durand-Gasselin, Tristan Cros, David |
author_facet |
Nyouma, Achille Bell, Joseph Martin Jacob, Florence Riou, Virginie Manez, Aurore Pomiès, Virginie Domonhedo, Hubert Arifiyanto, Deni Cochard, Benoît Durand-Gasselin, Tristan Cros, David |
author_sort |
Nyouma, Achille |
title |
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
title_short |
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
title_full |
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
title_fullStr |
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
title_full_unstemmed |
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) |
title_sort |
improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: a case study of oil palm (elaeis guineensis jacq.) |
url |
http://agritrop.cirad.fr/600292/ http://agritrop.cirad.fr/600292/7/600292.pdf |
work_keys_str_mv |
AT nyoumaachille improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT belljosephmartin improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT jacobflorence improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT riouvirginie improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT manezaurore improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT pomiesvirginie improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT domonhedohubert improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT arifiyantodeni improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT cochardbenoit improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT durandgasselintristan improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq AT crosdavid improvingtheaccuracyofgenomicpredictionsinanoutcrossingspecieswithhybridcultivarsbetweenheterozygoteparentsacasestudyofoilpalmelaeisguineensisjacq |
_version_ |
1792500306780618752 |
spelling |
dig-cirad-fr-6002922024-02-16T19:01:55Z http://agritrop.cirad.fr/600292/ http://agritrop.cirad.fr/600292/ Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.). Nyouma Achille, Bell Joseph Martin, Jacob Florence, Riou Virginie, Manez Aurore, Pomiès Virginie, Domonhedo Hubert, Arifiyanto Deni, Cochard Benoît, Durand-Gasselin Tristan, Cros David. 2022. Molecular Genetics and Genomics, 297 : 523-533.https://doi.org/10.1007/s00438-022-01867-5 <https://doi.org/10.1007/s00438-022-01867-5> Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: A case study of oil palm (Elaeis guineensis Jacq.) Nyouma, Achille Bell, Joseph Martin Jacob, Florence Riou, Virginie Manez, Aurore Pomiès, Virginie Domonhedo, Hubert Arifiyanto, Deni Cochard, Benoît Durand-Gasselin, Tristan Cros, David eng 2022 Molecular Genetics and Genomics F30 - Génétique et amélioration des plantes Elaeis guineensis sélection assistée par marqueurs hybride génotype modèle méthode d'amélioration génétique séquençage à haut débit technique génétique http://aims.fao.org/aos/agrovoc/c_2509 http://aims.fao.org/aos/agrovoc/c_394fd447 http://aims.fao.org/aos/agrovoc/c_3707 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_4881 http://aims.fao.org/aos/agrovoc/c_1079 http://aims.fao.org/aos/agrovoc/c_0a9daef1 http://aims.fao.org/aos/agrovoc/c_331008 Asie Inde Afrique Angola Côte d'Ivoire République démocratique du Congo Congo http://aims.fao.org/aos/agrovoc/c_666 http://aims.fao.org/aos/agrovoc/c_3825 http://aims.fao.org/aos/agrovoc/c_165 http://aims.fao.org/aos/agrovoc/c_417 http://aims.fao.org/aos/agrovoc/c_4027 http://aims.fao.org/aos/agrovoc/c_8500 http://aims.fao.org/aos/agrovoc/c_1811 Genomic selection (GS) is a method of marker-assisted selection revolutionizing crop improvement, but it can still be optimized. For hybrid breeding between heterozygote parents of different populations or species, specific aspects can be considered to increase GS accuracy: (1) training population genotyping, i.e., only genotyping the hybrid parents or also a sample of hybrid individuals, and (2) marker effects modeling, i.e., using population-specific effects of single nucleotide polymorphism alleles model (PSAM) or across-population SNP genotype model (ASGM). Here, this was investigated empirically for the prediction of the performances of oil palm hybrids for yield traits. The GS model was trained on 352 hybrid crosses and validated on 213 independent hybrid crosses. The training and validation hybrid parents and 399 training hybrid individuals were genotyping by sequencing. Despite the small proportion of hybrid individuals genotyped and low parental heterozygosity, GS prediction accuracy increased on average by 5% (range 1.4–31.3%, depending on trait and model) when training was done using genomic data on hybrids and parents compared with only parental genomic data. With ASGM, GS prediction accuracy increased on average by 3% (− 10.2 to 40%, depending on trait and genotyping strategy) compared with PSAM. We conclude that the best GS strategy for oil palm is to aggregate genomic data of parents and hybrid individuals and to ignore the parental origin of marker alleles (ASGM). To gain a better insight into these results, future studies should examine the respective effect of capturing genetic variability within crosses and taking segregation distortion into account when genotyping hybrid individuals, and investigate the factors controlling the relative performances of ASGM and PSAM in hybrid crops. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/600292/7/600292.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1007/s00438-022-01867-5 10.1007/s00438-022-01867-5 info:eu-repo/semantics/altIdentifier/doi/10.1007/s00438-022-01867-5 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/s00438-022-01867-5 |