Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens
Poultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortali...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-10-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.543890/full |
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| author | Georgios Banos Georgios Banos Georgios Banos Victoria Lindsay Takele T. Desta Judy Bettridge Judy Bettridge Judy Bettridge Enrique Sanchez-Molano Adriana Vallejo-Trujillo Oswald Matika Tadelle Dessie Paul Wigley Robert M. Christley Peter Kaiser Olivier Hanotte Olivier Hanotte Olivier Hanotte Androniki Psifidi Androniki Psifidi Androniki Psifidi |
| author_facet | Georgios Banos Georgios Banos Georgios Banos Victoria Lindsay Takele T. Desta Judy Bettridge Judy Bettridge Judy Bettridge Enrique Sanchez-Molano Adriana Vallejo-Trujillo Oswald Matika Tadelle Dessie Paul Wigley Robert M. Christley Peter Kaiser Olivier Hanotte Olivier Hanotte Olivier Hanotte Androniki Psifidi Androniki Psifidi Androniki Psifidi |
| author_sort | Georgios Banos |
| collection | DOAJ |
| description | Poultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortality and reduced productivity. Genomic selection for disease resistance offers a potentially sustainable solution but this requires sufficient numbers of individual birds with genomic and phenotypic data, which is often a challenge to collect in the small populations of indigenous chicken ecotypes. The use of information across-ecotypes presents an attractive possibility to increase the relevant numbers and the accuracy of genomic selection. In this study, we performed a joint analysis of two distinct Ethiopian indigenous chicken ecotypes to investigate the genomic architecture of important health and productivity traits and explore the feasibility of conducting genomic selection across-ecotype. Phenotypic traits considered were antibody response to Infectious Bursal Disease (IBDV), Marek’s Disease (MDV), Fowl Cholera (PM) and Fowl Typhoid (SG), resistance to Eimeria and cestode parasitism, and productivity [body weight and body condition score (BCS)]. Combined data from the two chicken ecotypes, Horro (n = 384) and Jarso (n = 376), were jointly analyzed for genetic parameter estimation, genome-wide association studies (GWAS), genomic breeding value (GEBVs) calculation, genomic predictions, whole-genome sequencing (WGS), and pathways analyses. Estimates of across-ecotype heritability were significant and moderate in magnitude (0.22–0.47) for all traits except for SG and BCS. GWAS identified several significant genomic associations with health and productivity traits. The WGS analysis revealed putative candidate genes and mutations for IBDV (TOLLIP, ANGPTL5, BCL9, THEMIS2), MDV (GRM7), SG (MAP3K21), Eimeria (TOM1L1) and cestodes (TNFAIP1, ATG9A, NOS2) parasitism, which warrant further investigation. Reliability of GEBVs increased compared to within-ecotype calculations but accuracy of genomic prediction did not, probably because the genetic distance between the two ecotypes offset the benefit from increased sample size. However, for some traits genomic prediction was only feasible in across-ecotype analysis. Our results generally underpin the potential of genomic selection to enhance health and productivity across-ecotypes. Future studies should establish the required minimum sample size and genetic similarity between ecotypes to ensure accurate joint genomic selection. |
| first_indexed | 2024-12-13T05:11:38Z |
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| id | doaj.art-3218635443904b20b045a3f57c2040e3 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-13T05:11:38Z |
| publishDate | 2020-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-3218635443904b20b045a3f57c2040e32022-12-21T23:58:31ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-10-011110.3389/fgene.2020.543890543890Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African ChickensGeorgios Banos0Georgios Banos1Georgios Banos2Victoria Lindsay3Takele T. Desta4Judy Bettridge5Judy Bettridge6Judy Bettridge7Enrique Sanchez-Molano8Adriana Vallejo-Trujillo9Oswald Matika10Tadelle Dessie11Paul Wigley12Robert M. Christley13Peter Kaiser14Olivier Hanotte15Olivier Hanotte16Olivier Hanotte17Androniki Psifidi18Androniki Psifidi19Androniki Psifidi20The Roslin Institute, The University of Edinburgh, Edinburgh, United KingdomScotland’s Rural College, Edinburgh, United KingdomCentre for Tropical Livestock Genetics and Health, Edinburgh, United KingdomRoyal Veterinary College, University of London, London, United KingdomSchool of Life Sciences, University of Nottingham, Nottingham, United KingdomInstitute of Infection and Global Health, University of Liverpool, Liverpool, United KingdomLiveGene – Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Addis Ababa, EthiopiaNatural Resources Institute, University of Greenwich, London, United KingdomThe Roslin Institute, The University of Edinburgh, Edinburgh, United KingdomSchool of Life Sciences, University of Nottingham, Nottingham, United KingdomThe Roslin Institute, The University of Edinburgh, Edinburgh, United KingdomLiveGene – Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Addis Ababa, EthiopiaInstitute of Infection and Global Health, University of Liverpool, Liverpool, United KingdomInstitute of Infection and Global Health, University of Liverpool, Liverpool, United KingdomThe Roslin Institute, The University of Edinburgh, Edinburgh, United KingdomCentre for Tropical Livestock Genetics and Health, Edinburgh, United KingdomSchool of Life Sciences, University of Nottingham, Nottingham, United KingdomLiveGene – Centre for Tropical Livestock Genetics and Health, International Livestock Research Institute, Addis Ababa, EthiopiaThe Roslin Institute, The University of Edinburgh, Edinburgh, United KingdomCentre for Tropical Livestock Genetics and Health, Edinburgh, United KingdomRoyal Veterinary College, University of London, London, United KingdomPoultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortality and reduced productivity. Genomic selection for disease resistance offers a potentially sustainable solution but this requires sufficient numbers of individual birds with genomic and phenotypic data, which is often a challenge to collect in the small populations of indigenous chicken ecotypes. The use of information across-ecotypes presents an attractive possibility to increase the relevant numbers and the accuracy of genomic selection. In this study, we performed a joint analysis of two distinct Ethiopian indigenous chicken ecotypes to investigate the genomic architecture of important health and productivity traits and explore the feasibility of conducting genomic selection across-ecotype. Phenotypic traits considered were antibody response to Infectious Bursal Disease (IBDV), Marek’s Disease (MDV), Fowl Cholera (PM) and Fowl Typhoid (SG), resistance to Eimeria and cestode parasitism, and productivity [body weight and body condition score (BCS)]. Combined data from the two chicken ecotypes, Horro (n = 384) and Jarso (n = 376), were jointly analyzed for genetic parameter estimation, genome-wide association studies (GWAS), genomic breeding value (GEBVs) calculation, genomic predictions, whole-genome sequencing (WGS), and pathways analyses. Estimates of across-ecotype heritability were significant and moderate in magnitude (0.22–0.47) for all traits except for SG and BCS. GWAS identified several significant genomic associations with health and productivity traits. The WGS analysis revealed putative candidate genes and mutations for IBDV (TOLLIP, ANGPTL5, BCL9, THEMIS2), MDV (GRM7), SG (MAP3K21), Eimeria (TOM1L1) and cestodes (TNFAIP1, ATG9A, NOS2) parasitism, which warrant further investigation. Reliability of GEBVs increased compared to within-ecotype calculations but accuracy of genomic prediction did not, probably because the genetic distance between the two ecotypes offset the benefit from increased sample size. However, for some traits genomic prediction was only feasible in across-ecotype analysis. Our results generally underpin the potential of genomic selection to enhance health and productivity across-ecotypes. Future studies should establish the required minimum sample size and genetic similarity between ecotypes to ensure accurate joint genomic selection.https://www.frontiersin.org/article/10.3389/fgene.2020.543890/fullGWASGEBVWGSindigenous chickensbody weightinfectious diseases |
| spellingShingle | Georgios Banos Georgios Banos Georgios Banos Victoria Lindsay Takele T. Desta Judy Bettridge Judy Bettridge Judy Bettridge Enrique Sanchez-Molano Adriana Vallejo-Trujillo Oswald Matika Tadelle Dessie Paul Wigley Robert M. Christley Peter Kaiser Olivier Hanotte Olivier Hanotte Olivier Hanotte Androniki Psifidi Androniki Psifidi Androniki Psifidi Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens Frontiers in Genetics GWAS GEBV WGS indigenous chickens body weight infectious diseases |
| title | Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens |
| title_full | Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens |
| title_fullStr | Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens |
| title_full_unstemmed | Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens |
| title_short | Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens |
| title_sort | integrating genetic and genomic analyses of combined health data across ecotypes to improve disease resistance in indigenous african chickens |
| topic | GWAS GEBV WGS indigenous chickens body weight infectious diseases |
| url | https://www.frontiersin.org/article/10.3389/fgene.2020.543890/full |
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