Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep
[EN] The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk s...
| Autores: | , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/22877 |
| Acceso en línea: | https://www.sciencedirect.com/science/article/pii/S0022030222004726?via%3Dihub https://hdl.handle.net/10612/22877 |
| Access Level: | acceso abierto |
| Palabra clave: | Producción animal Cheese-making traits Dairy sheep Genetic evaluation Genomic selection 3109 Ciencias Veterinarias 3104 Producción Animal 3109.02 Genética |
| id |
ES_e8a625b6459942fdafb0627a0c8eb0aa |
|---|---|
| oai_identifier_str |
oai:buleria.unileon.es:10612/22877 |
| network_acronym_str |
ES |
| network_name_str |
España |
| repository_id_str |
|
| dc.title.none.fl_str_mv |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| title |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| spellingShingle |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep Marina García, Héctor Producción animal Cheese-making traits Dairy sheep Genetic evaluation Genomic selection 3109 Ciencias Veterinarias 3104 Producción Animal 3109.02 Genética |
| title_short |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| title_full |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| title_fullStr |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| title_full_unstemmed |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| title_sort |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep |
| dc.creator.none.fl_str_mv |
Marina García, Héctor Pelayo, Rocío Gutiérrez Gil, Beatriz Suárez Vega, Aroa Esteban Blanco, Cristina Reverter, Antonio Arranz Santos, Juan José |
| author |
Marina García, Héctor |
| author_facet |
Marina García, Héctor Pelayo, Rocío Gutiérrez Gil, Beatriz Suárez Vega, Aroa Esteban Blanco, Cristina Reverter, Antonio Arranz Santos, Juan José |
| author_role |
author |
| author2 |
Pelayo, Rocío Gutiérrez Gil, Beatriz Suárez Vega, Aroa Esteban Blanco, Cristina Reverter, Antonio Arranz Santos, Juan José |
| author2_role |
author author author author author author |
| dc.contributor.none.fl_str_mv |
Producción Animal Facultad de Veterinaria |
| dc.subject.none.fl_str_mv |
Producción animal Cheese-making traits Dairy sheep Genetic evaluation Genomic selection 3109 Ciencias Veterinarias 3104 Producción Animal 3109.02 Genética |
| topic |
Producción animal Cheese-making traits Dairy sheep Genetic evaluation Genomic selection 3109 Ciencias Veterinarias 3104 Producción Animal 3109.02 Genética |
| description |
[EN] The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://www.sciencedirect.com/science/article/pii/S0022030222004726?via%3Dihub https://hdl.handle.net/10612/22877 |
| url |
https://www.sciencedirect.com/science/article/pii/S0022030222004726?via%3Dihub https://hdl.handle.net/10612/22877 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
info:eu-repo/grantAgreement/AEI/Programa Estatal de I+D+i Orientada a los Retos de la Sociedad/RTI2018-093535-B-I00 |
| dc.rights.none.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Elsevier American Dairy Science Association |
| publisher.none.fl_str_mv |
Elsevier American Dairy Science Association |
| dc.source.none.fl_str_mv |
reponame:BULERIA. Repositorio Institucional de la Universidad de León instname:Universidad de León |
| instname_str |
Universidad de León |
| reponame_str |
BULERIA. Repositorio Institucional de la Universidad de León |
| collection |
BULERIA. Repositorio Institucional de la Universidad de León |
| repository.name.fl_str_mv |
|
| repository.mail.fl_str_mv |
|
| _version_ |
1869422959867723776 |
| spelling |
Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheepMarina García, HéctorPelayo, RocíoGutiérrez Gil, BeatrizSuárez Vega, AroaEsteban Blanco, CristinaReverter, AntonioArranz Santos, Juan JoséProducción animalCheese-making traitsDairy sheepGenetic evaluationGenomic selection3109 Ciencias Veterinarias3104 Producción Animal3109.02 Genética[EN] The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered hereSIThis research work was financially supported by the RTI2018-093535-B-I00 project funded by the “Agencia Estatal de Investigación” of the Spanish Ministry of Science and Innovation (Madrid, Spain; Assaf data), and the project LE249P18 (Churra data) funded by the Consejería de Educación of Junta de Castilla y León (Valladolid, Spain) and cofounded by the European Social Funds. H. Marina is funded by an FPU fellowship from the Ministry of Science, Innovation, and Universities (MICIU, Ref. FPU16/01161). This research has made use of the high-performance computing resources of the Castilla y León Supercomputing Center (SCAYLE, www.scayle.es ; León, Spain). We acknowledge the Consortium for the Promotion of Sheep (lechedeoveja.com), the National Churra Breeders Association (ANCHE; Palencia, Spain; http://anche.org ), and the National Association of Sheep Breeders of Assaf Breed (ASSAFE; Zamoa, Spain; http://assafe.es/ ) for providing access to their production databases. The authors have not stated any conflicts of interestElsevierAmerican Dairy Science AssociationProducción AnimalFacultad de Veterinaria2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.sciencedirect.com/science/article/pii/S0022030222004726?via%3Dihubhttps://hdl.handle.net/10612/22877reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónInglésinfo:eu-repo/grantAgreement/AEI/Programa Estatal de I+D+i Orientada a los Retos de la Sociedad/RTI2018-093535-B-I00http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/228772026-06-24T12:43:27Z |
| score |
15,812429 |