Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries
Breeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-11-01
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| Series: | JDS Communications |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666910221001411 |
| _version_ | 1797788497438834688 |
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| author | Owen Powell Raphael Mrode R. Chris Gaynor Martin Johnsson Gregor Gorjanc John M. Hickey |
| author_facet | Owen Powell Raphael Mrode R. Chris Gaynor Martin Johnsson Gregor Gorjanc John M. Hickey |
| author_sort | Owen Powell |
| collection | DOAJ |
| description | Breeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effects of animals' phenotypes. Genetic evaluations have been successful in advanced economies because of large data sets and strong genetic connectedness, provided by the widespread use of artificial insemination (AI) and accurate recording of pedigree information. In smallholder dairy production systems of many LMICs, the limited use of AI and small herd sizes results in a data structure with insufficient genetic connectedness between herds to facilitate genetic evaluations based on pedigree. Genomic information keeps track of shared haplotypes rather than shared relatives captured by pedigree records. Therefore, genomic information could capture “hidden” genetic relationships, that are not captured by pedigree information, to strengthen genetic connectedness in LMIC smallholder dairy data sets. This study's objective was to use simulation to quantify the power of genomic information to enable genetic evaluation using LMIC smallholder dairy data sets. The results from this study show that (1) genetic evaluations using genomic information were more accurate than those using pedigree information in populations with a high effective population size and weak genetic connectedness; and (2) genetic evaluations modeling herd as a random effect had higher or equal accuracy than those modeling herd as a fixed effect. This demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in situ records collected from herds of ≤4 cows. The establishment of routine genomic evaluations could allow the development of LMIC breeding programs comprising an informal set of nucleus animals distributed across many small herds within the target environment. These nucleus animals could be used for genetic evaluation, and the best animals could be disseminated to participating smallholder dairy farms. Together, this could increase the productivity, profitability, and sustainability of LMIC smallholder dairy production systems. |
| first_indexed | 2024-03-13T01:36:25Z |
| format | Article |
| id | doaj.art-f41db90dc2dd4c6a9ec07176dfd92843 |
| institution | Directory Open Access Journal |
| issn | 2666-9102 |
| language | English |
| last_indexed | 2024-03-13T01:36:25Z |
| publishDate | 2021-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | JDS Communications |
| spelling | doaj.art-f41db90dc2dd4c6a9ec07176dfd928432023-07-04T05:10:40ZengElsevierJDS Communications2666-91022021-11-0126366370Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countriesOwen Powell0Raphael Mrode1R. Chris Gaynor2Martin Johnsson3Gregor Gorjanc4John M. Hickey5The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, United Kingdom; Corresponding authorScotland's Rural College (SRUC), Easter Bush, Midlothian, EH25 9RG, United Kingdom; International Livestock Research Institute (ILRI), Nairobi 00100, KenyaThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, United KingdomThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, United Kingdom; Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07, Uppsala, SwedenThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, United KingdomThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, United KingdomBreeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effects of animals' phenotypes. Genetic evaluations have been successful in advanced economies because of large data sets and strong genetic connectedness, provided by the widespread use of artificial insemination (AI) and accurate recording of pedigree information. In smallholder dairy production systems of many LMICs, the limited use of AI and small herd sizes results in a data structure with insufficient genetic connectedness between herds to facilitate genetic evaluations based on pedigree. Genomic information keeps track of shared haplotypes rather than shared relatives captured by pedigree records. Therefore, genomic information could capture “hidden” genetic relationships, that are not captured by pedigree information, to strengthen genetic connectedness in LMIC smallholder dairy data sets. This study's objective was to use simulation to quantify the power of genomic information to enable genetic evaluation using LMIC smallholder dairy data sets. The results from this study show that (1) genetic evaluations using genomic information were more accurate than those using pedigree information in populations with a high effective population size and weak genetic connectedness; and (2) genetic evaluations modeling herd as a random effect had higher or equal accuracy than those modeling herd as a fixed effect. This demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in situ records collected from herds of ≤4 cows. The establishment of routine genomic evaluations could allow the development of LMIC breeding programs comprising an informal set of nucleus animals distributed across many small herds within the target environment. These nucleus animals could be used for genetic evaluation, and the best animals could be disseminated to participating smallholder dairy farms. Together, this could increase the productivity, profitability, and sustainability of LMIC smallholder dairy production systems.http://www.sciencedirect.com/science/article/pii/S2666910221001411 |
| spellingShingle | Owen Powell Raphael Mrode R. Chris Gaynor Martin Johnsson Gregor Gorjanc John M. Hickey Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries JDS Communications |
| title | Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries |
| title_full | Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries |
| title_fullStr | Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries |
| title_full_unstemmed | Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries |
| title_short | Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries |
| title_sort | genomic evaluations using data recorded on smallholder dairy farms in low to middle income countries |
| url | http://www.sciencedirect.com/science/article/pii/S2666910221001411 |
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