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Keele JW, Foraker BA, Boldt R, Kemp C, Kuehn LA, Woerner DR. Genetic parameters for carcass traits of progeny of beef bulls mated to dairy cows. J Anim Sci 2024; 102:skae075. [PMID: 38489760 PMCID: PMC10989647 DOI: 10.1093/jas/skae075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 03/14/2024] [Indexed: 03/17/2024] Open
Abstract
Beef × dairy crossbred cattle (n = 615) were used to evaluate the effect of preharvest indicator traits and genotypes on the accuracy of estimated breeding values (EBVs) of seedstock candidates for selection. Genotypes for 100,000 single nucleotide polymorphisms were provided by the American Simmental Association of purebred and crossbred seedstock animals (n = 2,632). Five hundred and ninety-five of the 615 beef × dairy cattle had carcass camera and ultrasound data. Phenotypes were not used for any of the seedstock animals even though some may have had performance and ultrasound data. We estimated the genomic relationship matrix among 3,247 animals including both phenotyped and unphenotyped animals. We computed genetic parameters among 37 traits using 666 bivariate restricted maximum likelihood analyses. The accuracy of EBV depends on heritability. For the sake of brevity, we report accuracy for marbling as a proxy for other traits with similar heritability. We focus on accuracy for marbling because marbling is the primary determinant of carcass value. We computed EBV for all 3,247 animals for marbling based on camera data postharvest using best linear unbiased prediction. We report evidence of overlap in causative genes among postharvest carcass traits; marbling, ribeye area, yield grade, fat thickness, and hot carcass weight (HCW) based on genetic correlations. Genetic correlations range from -0.73 to 0.89. Several live animal traits (frame size, body weight and ultrasound fat thickness and ribeye area) were genetically correlated with postharvest traits; including HCW, ribeye area, yield grade, fat thickness, and marbling. Genetic correlations between pre- and postharvest traits ranged from -0.53 to 0.95. Accuracy for marbling ranged from 0.64 to 0.80 for animals with marbling recorded, and from 0.09 to 0.60 for animals without marbling recorded. The accuracy of animals without phenotypes was related to the genomic relationship between animals with phenotype and those without. Live animal traits were useful for predicting economically important carcass traits based on genetic correlations. The accuracy of EBV for seedstock animals that were not phenotyped was low, but this is consistent with theory, and accuracy is expected to increase with the addition of genotypes and carcass data from beef × dairy animals.
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Affiliation(s)
- John W Keele
- U. S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Blake A Foraker
- Department of Animal Sciences, Washington State University, Pullman, WA 99164, USA
| | - Ryan Boldt
- American Simmental Association, Bozeman, MT 59718, USA
| | - Chip Kemp
- American Simmental Association, Bozeman, MT 59718, USA
| | - Larry A Kuehn
- U. S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Dale R Woerner
- Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX 79409, USA
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Park J, Do KT, Park KD, Lee HK. Genome-wide association study using a single-step approach for teat number in Duroc, Landrace and Yorkshire pigs in Korea. Anim Genet 2023; 54:743-751. [PMID: 37814452 DOI: 10.1111/age.13357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 07/25/2023] [Accepted: 09/01/2023] [Indexed: 10/11/2023]
Abstract
We investigated the genetic basis of teat number in sows, which is an important factor in their reproductive performance. We collected genotyping data from 20 353 pigs of three breeds (Duroc, Landrace and Yorkshire) using the Porcine SNP60K Bead Chip, and analyzed phenotypic data from 240 603 pigs. The heritability values of total teat number were 0.33 ± 0.02, 0.51 ± 0.01 and 0.50 ± 0.01 in Duroc, Landrace and Yorkshire pigs, respectively. A genome-wide association study was used to identify significant chromosomal regions associated with teat number in SSC7 and SSC9 in Duroc pig, SSC3, SSC7 and SSC18 in Landrace pig, and SSC7, SSC8 and SSC10 in Yorkshire pig. Among the markers, MARC0038565, located between the vertnin (VRTN) and synapse differentiation-inducing 1-like (SYNDIG1L) genes, showed the strongest association in the Duroc pig and was significant in all breeds. In Landrace and Yorkshire pigs, the most significant markers were located within the apoptosis resistant E3 ubiquitin protein ligase 1 (AREL1) and latent transforming growth factor beta-binding protein 2 (LTBP2) genes in SSC7, respectively. VRTN is a candidate gene regulating the teat number. Most markers were located in SSC7, indicating their significance in determining teat number and their potential as valuable genomic selection targets for improving this trait. Extensive linkage disequilibrium blocks were identified in SSC7, supporting their use in genomic selection strategies. Our study provides valuable insights into the genetic architecture of teat numbers in pigs, and helps identify candidate genes and genomic regions that may contribute to this economically important trait.
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Affiliation(s)
- Jun Park
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju, Korea
| | - Kyoung-Tag Do
- Department of Animal Biotechnology, Jeju National University, Jeju, Korea
| | - Kyung-Do Park
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju, Korea
| | - Hak-Kyo Lee
- Department of Animal Biotechnology, Jeonbuk National University, Jeonju, Korea
- Department of Agricultural Convergence Technology, Jeonbuk National University, Jeonju, Korea
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3
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Berry DP, Spangler ML. Animal board invited review: Practical applications of genomic information in livestock. Animal 2023; 17:100996. [PMID: 37820404 DOI: 10.1016/j.animal.2023.100996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/08/2023] [Accepted: 09/11/2023] [Indexed: 10/13/2023] Open
Abstract
Access to high-dimensional genomic information in many livestock species is accelerating. This has been greatly aided not only by continual reductions in genotyping costs but also an expansion in the services available that leverage genomic information to create a greater return-on-investment. Genomic information on individual animals has many uses including (1) parentage verification and discovery, (2) traceability, (3) karyotyping, (4) sex determination, (5) reporting and monitoring of mutations conferring major effects or congenital defects, (6) better estimating inbreeding of individuals and coancestry among individuals, (7) mating advice, (8) determining breed composition, (9) enabling precision management, and (10) genomic evaluations; genomic evaluations exploit genome-wide genotype information to improve the accuracy of predicting an animal's (and by extension its progeny's) genetic merit. Genomic data also provide a huge resource for research, albeit the outcome from this research, if successful, should eventually be realised through one of the ten applications already mentioned. The process for generating a genotype all the way from sample procurement to identifying erroneous genotypes is described, as are the steps that should be considered when developing a bespoke genotyping panel for practical application.
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Affiliation(s)
- D P Berry
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Cork, Ireland.
| | - M L Spangler
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, United States
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4
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Zoda A, Ogawa S, Kagawa R, Tsukahara H, Obinata R, Urakawa M, Oono Y. Single-Step Genomic Prediction of Superovulatory Response Traits in Japanese Black Donor Cows. BIOLOGY 2023; 12:biology12050718. [PMID: 37237533 DOI: 10.3390/biology12050718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/11/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023]
Abstract
We assessed the performance of single-step genomic prediction of breeding values for superovulatory response traits in Japanese Black donor cows. A total of 25,332 records of the total number of embryos and oocytes (TNE) and the number of good embryos (NGE) per flush for 1874 Japanese Black donor cows were collected during 2008 and 2022. Genotype information on 36,426 autosomal single-nucleotide polymorphisms (SNPs) for 575 out of the 1,874 cows was used. Breeding values were predicted exploiting a two-trait repeatability animal model. Two genetic relationship matrices were used, one based on pedigree information (A matrix) and the other considering both pedigree and SNP marker genotype information (H matrix). Estimated heritabilities of TNE and NGE were 0.18 and 0.11, respectively, when using the H matrix, which were both slightly lower than when using the A matrix (0.26 for TNE and 0.16 for NGE). Estimated genetic correlations between the traits were 0.61 and 0.66 when using H and A matrices, respectively. When the variance components were the same in breeding value prediction, the mean reliability was greater when using the H matrix than when using the A matrix. This advantage seems more prominent for cows with low reliability when using the A matrix. The results imply that introducing single-step genomic prediction could boost the rate of genetic improvement of superovulatory response traits, but efforts should be made to maintain genetic diversity when performing selection.
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Affiliation(s)
- Atsushi Zoda
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
| | - Shinichiro Ogawa
- Division of Meat Animal and Poultry Research, Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO), Tsukuba 305-0901, Japan
| | - Rino Kagawa
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
| | - Hayato Tsukahara
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
| | - Rui Obinata
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
| | - Manami Urakawa
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
| | - Yoshio Oono
- Research and Development Group, Zen-noh Embryo Transfer Center, Kamishihoro 080-1407, Japan
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Kenny D, Berry DP, Pabiou T, Rafter P. Variation in the proportion of the segregating genome shared between full-sibling cattle and sheep. Genet Sel Evol 2023; 55:27. [PMID: 37072693 PMCID: PMC10111659 DOI: 10.1186/s12711-023-00802-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 04/06/2023] [Indexed: 04/20/2023] Open
Abstract
The construction of covariance matrices that account for the genetic relationships among individuals, using pedigree or genotype data, is integral to genetic evaluations, which are now routinely used in the field of animal breeding. The objective of the present study was to estimate the standard deviation in the proportion of the segregating genome that is shared between pairs of full-sibling cattle and sheep independently. Post edits, genotype data comprising 46,069 autosomal single nucleotide polymorphisms (SNPs) were available for 4532 unique full-sibling sheep pairs, as well as for their respective parents. Post edits, genotypes from 50,493 autosomal SNPs were also available for 10,000 unique full-sibling cattle pairs, as well as their respective parents. Genomic relationship matrices were constructed for the sheep and cattle populations, separately. After accounting for both parental genomic inbreeding and the genomic relationship between both parents, the standard deviation in full-sibling cattle and sheep genomic relationships was 0.040 and 0.037 units, respectively. In addition, the intercept value from a linear regression model which regressed each full-sibling genomic relationship on both sire and dam inbreeding, as well as the genomic relationship between the parents, was 0.499 (0.001) for sheep and 0.500 (0.001) for cattle, conforming to the expectation that full-siblings, on average, share 50% of their segregating genome.
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Affiliation(s)
- David Kenny
- Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Ireland
| | - Donagh P Berry
- Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Ireland.
| | - Thierry Pabiou
- Sheep Ireland, Highfield House, Shinagh, Bandon, Ireland
- Irish Cattle Breeding Federation, Highfield House, Shinagh, Bandon, Ireland
| | - Pierce Rafter
- Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Ireland
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Bengtsson C, Stålhammar H, Thomasen JR, Fikse WF, Strandberg E, Eriksson S. Mating allocations in Holstein combining genomic information and linear programming optimization at the herd level. J Dairy Sci 2023; 106:3359-3375. [PMID: 37028963 DOI: 10.3168/jds.2022-22926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/19/2022] [Indexed: 04/08/2023]
Abstract
In this study, we explored mating allocation in Holstein using genomic information for 24,333 Holstein females born in Denmark, Finland, and Sweden. We used 2 data sets of bulls: the top 50 genotyped bulls and the top 25 polled genotyped bulls on the Nordic total merit scale. We used linear programming to optimize economic scores within each herd, considering genetic level, genetic relationship, semen cost, the economic impact of genetic defects, polledness, and β-casein. We found that it was possible to reduce genetic relationships and eliminate expression of genetic defects with minimal effect on the genetic level in total merit index. Compared with maximizing only Nordic total merit index, the relative frequency of polled offspring increased from 13.5 to 22.5%, and that of offspring homozygous for β-casein (A2A2) from 66.7 to 75.0% in one generation, without any substantial negative impact on other comparison criteria. Using only semen from polled bulls, which might become necessary if dehorning is banned, considerably reduced the genetic level. We also found that animals carrying the polled allele were less likely to be homozygous for β-casein (A2A2) and more likely to be carriers of the genetic defect HH1. Hence, adding economic value to a monogenic trait in the economic score used for mating allocation sometimes negatively affected another monogenetic trait. We recommend that the comparison criteria used in this study be monitored in a modern genomic mating program.
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Affiliation(s)
- C Bengtsson
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden; Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden.
| | - H Stålhammar
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden
| | - J R Thomasen
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden
| | - W F Fikse
- Växa Sverige, Växa Sverige, Box 288, 75105 Uppsala, Sweden
| | - E Strandberg
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden
| | - S Eriksson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden
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Berton MP, da Silva RP, Banchero G, Mourão GB, Ferraz JBS, Schenkel FS, Baldi F. Genomic integration to identify molecular biomarkers associated with indicator traits of gastrointestinal nematode resistance in sheep. J Anim Breed Genet 2022; 139:502-516. [PMID: 35535437 DOI: 10.1111/jbg.12682] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 04/21/2022] [Indexed: 12/19/2022]
Abstract
This study aimed to integrate GWAS and structural variants to propose possible molecular biomarkers related to gastrointestinal nematode resistance traits in Santa Inês sheep. The phenotypic records FAMACHA, haematocrit, white blood cell count, red blood cell count, haemoglobin, platelets and egg counts per gram of faeces were collected from 700 naturally infected animals, belonging to four Brazilian flocks. A total of 576 animals were genotyped using the Ovine SNP12k BeadChip and were imputed using a reference population with Ovine SNP50 BeadChip. The GWAS approaches were based on SNPs, haplotypes, CNVs and ROH. The overlapping between the significant genomic regions detected from all approaches was investigated, and the results were integrated using a network analysis. Genes related to the immune system were found, such as ABCB1, IL6, WNT5A and IRF5. Genomic regions containing candidate genes and metabolic pathways involved in immune responses, inflammatory processes and immune cells affecting parasite resistance traits were identified. The genomic regions, biological processes and candidate genes uncovered could lead to biomarkers for selecting more resilient sheep and improving herd welfare and productivity. The results obtained are the start point to identify molecular biomarkers related to indicator traits of gastrointestinal nematode resistance in Santa Inês sheep.
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Affiliation(s)
- Mariana Piatto Berton
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, Brazil
| | - Rosiane Pereira da Silva
- Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, Pirassununga, Brazil
| | - Georgget Banchero
- Instituto Nacional de Investigación Agropecuária (INIA), Colonia, Uruguay
| | - Gerson Barreto Mourão
- Departamento de Zootecnia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo/ESALQ, Piracicaba, Brazil
| | | | | | - Fernando Baldi
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, Brazil
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Bengtsson C, Stålhammar H, Thomasen JR, Eriksson S, Fikse WF, Strandberg E. Mating allocations in Nordic Red Dairy Cattle using genomic information. J Dairy Sci 2021; 105:1281-1297. [PMID: 34799119 DOI: 10.3168/jds.2021-20849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/08/2021] [Indexed: 11/19/2022]
Abstract
In this study, we compared mating allocations in Nordic Red Dairy Cattle using genomic information. We used linear programming to optimize different economic scores within each herd, considering genetic level, semen cost, the economic impact of recessive genetic defects, and genetic relationships. We selected 9,841 genotyped females born in Denmark, Finland, or Sweden in 2019 for mating allocations. We used 2 different pedigree relationship coefficients, the first tracing the pedigree 3 generations back from the parents of the potential mating and the second based on all available pedigree information. We used 3 different genomic relationship coefficients, 1 SNP-by-SNP genomic relationship and 2 based on shared genomic segments. We found high correlations (≥0.83) between the pedigree and genomic relationship measures. The mating results showed that it was possible to reduce the different genetic relationships between parents with minimal effect on genetic level. Including the cost of known recessive genetic defects eliminated expression of genetic defects. It was possible to reduce genomic relationships between parents with pedigree measures, but it was best done with genomic measures. Linear programming maximized the economic score for all herds studied within seconds, which means that it is suitable for implementation in mating software to be used by advisors and farmers.
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Affiliation(s)
- C Bengtsson
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden; Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden.
| | - H Stålhammar
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden
| | - J R Thomasen
- VikingGenetics, VikingGenetics Sweden AB, 53294 Skara, Sweden
| | - S Eriksson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden
| | - W F Fikse
- Växa Sverige, Växa Sverige, Box 288, 75105 Uppsala, Sweden
| | - E Strandberg
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 75007 Uppsala, Sweden
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Moore KL, Vilela C, Kaseja K, Mrode R, Coffey M. Forensic use of the genomic relationship matrix to validate and discover livestock pedigrees. J Anim Sci 2019; 97:35-42. [PMID: 30329120 PMCID: PMC6313117 DOI: 10.1093/jas/sky407] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 10/11/2018] [Indexed: 11/15/2022] Open
Abstract
Correct pedigree is essential to produce accurate genetic evaluations of livestock populations. Pedigree validation has traditionally been undertaken using microsatellites and more recently, based on checks on opposing homozygotes using single nucleotide polymorphisms (SNPs). In this study, the genomic relationship matrix was examined to see whether it was a useful tool to forensically validate pedigree and discover unknown pedigree. Using 5,993 genotyped Limousin animals which were imputed to a core set of 38,907 SNPs, the genomic relationships between animals were assessed to validate the reported pedigree. Using already pedigree-verified animals, the genomic relationships between animals of different relationships were shown to be on average 0.58, 0.59, 0.32, 0.32, 0.19, and 0.14 between animals and their parents, full siblings, half siblings, grandparents, great grandparents, and great great grandparents, respectively. Threshold values were defined based on the minimum genomic relationship reported between already pedigree-verified animals; 0.46, 0.41, 0.17, 0.17, 0.07, and 0.05, respectively for animals and their parents, full siblings, half siblings, grandparents, great grandparents, and great great grandparents. Using the wider population and the above genomic relationship threshold values, potential pedigree conflicts were identified within each relationship type. Pedigree error rates of between 0.9% (animal and great great grandparent) and 4.0% (full siblings) were identified. A forensic genomic pedigree validation and discovery system was developed to enable pedigree to be verified for individual genotyped animals. This system verifies not just the parents, but also a wide number of other genotyped relatives and can therefore identify more potential errors in the pedigree than current conventional methods. A novel aspect to this algorithm is that it can also be used to discover closely related animals on the basis of their genomic relationships although they are not recorded as such in the pedigree. This functionality enables missing pedigree information to be discovered and corrected in the pedigree of livestock populations. The methods in this paper demonstrate that the genomic relationship matrix can be a useful tool in the validation and discovery of pedigree in livestock populations. However, the method does rely on being able to define threshold values appropriate to the specific livestock population, which will require sufficient number of animals to be genotyped and pedigree validated before it can be used.
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Affiliation(s)
- Kirsty Lee Moore
- Department of Animal and Veterinary Sciences, Scotland’s Rural College (SRUC), Easter Bush, Midlothian, Scotland, UK
- Corresponding author:
| | - Conrad Vilela
- Department of Animal and Veterinary Sciences, Scotland’s Rural College (SRUC), Easter Bush, Midlothian, Scotland, UK
| | - Karolina Kaseja
- Department of Animal and Veterinary Sciences, Scotland’s Rural College (SRUC), Easter Bush, Midlothian, Scotland, UK
| | - Raphael Mrode
- Department of Animal and Veterinary Sciences, Scotland’s Rural College (SRUC), Easter Bush, Midlothian, Scotland, UK
| | - Mike Coffey
- Department of Animal and Veterinary Sciences, Scotland’s Rural College (SRUC), Easter Bush, Midlothian, Scotland, UK
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Hardner CM, Hayes BJ, Kumar S, Vanderzande S, Cai L, Piaskowski J, Quero-Garcia J, Campoy JA, Barreneche T, Giovannini D, Liverani A, Charlot G, Villamil-Castro M, Oraguzie N, Peace CP. Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array. HORTICULTURE RESEARCH 2019; 6:6. [PMID: 30603092 PMCID: PMC6312542 DOI: 10.1038/s41438-018-0081-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 06/08/2018] [Accepted: 07/15/2018] [Indexed: 05/21/2023]
Abstract
The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.
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Affiliation(s)
- Craig M. Hardner
- University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Brisbane, QLD 4072 Australia
| | - Ben J. Hayes
- University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Brisbane, QLD 4072 Australia
| | - Satish Kumar
- The New Zealand Institute for Plant and Food Research Limited, Hawke’s Bay Research Centre, Hastings, 4130 New Zealand
| | - Stijn Vanderzande
- Department of Horticulture, Washington State University, Pullman, WA 99164 USA
| | - Lichun Cai
- Department of Horticulture, Michigan State University, East Lansing, MI 48824 USA
| | - Julia Piaskowski
- Department of Horticulture, Washington State University, Pullman, WA 99164 USA
| | - José Quero-Garcia
- UMR 1332 BFP, INRA, University of Bordeaux, 33140 Nouvelle-Aquitaine, France
| | - José Antonio Campoy
- UMR 1332 BFP, INRA, University of Bordeaux, 33140 Nouvelle-Aquitaine, France
| | - Teresa Barreneche
- UMR 1332 BFP, INRA, University of Bordeaux, 33140 Nouvelle-Aquitaine, France
| | - Daniela Giovannini
- Council for Agricultural Research and Economics (CREA), Fruit Unit of Forlì, Via la Canapona, 1 bis, 47121 Emilia-Romagna, Italy
| | - Alessandro Liverani
- Council for Agricultural Research and Economics (CREA), Fruit Unit of Forlì, Via la Canapona, 1 bis, 47121 Emilia-Romagna, Italy
| | - Gérard Charlot
- Centre Technique Interprofessionnel des Fruits et Légumes (CTIFL), 751 Chemin de Balandran, 30127 Bellegarde, France
| | - Miguel Villamil-Castro
- University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Brisbane, QLD 4072 Australia
| | - Nnadozie Oraguzie
- Department of Horticulture, Washington State University, Irrigated Agriculture Research and Extension Center, 24106N Bunn Road, Prosser, WA 99350 USA
| | - Cameron P. Peace
- Department of Horticulture, Washington State University, Pullman, WA 99164 USA
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11
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Herzig AF, Nutile T, Ruggiero D, Ciullo M, Perdry H, Leutenegger AL. Detecting the dominance component of heritability in isolated and outbred human populations. Sci Rep 2018; 8:18048. [PMID: 30575761 PMCID: PMC6303332 DOI: 10.1038/s41598-018-36050-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 11/10/2018] [Indexed: 11/21/2022] Open
Abstract
Inconsistencies between published estimates of dominance heritability between studies of human genetic isolates and human outbred populations incite investigation into whether such differences result from particular trait architectures or specific population structures. We analyse simulated datasets, characteristic of genetic isolates and of unrelated individuals, before analysing the isolate of Cilento for various commonly studied traits. We show the strengths of using genetic relationship matrices for variance decomposition over identity-by-descent based methods in a population isolate and that heritability estimates in isolates will avoid the downward biases that may occur in studies of samples of unrelated individuals; irrespective of the simulated distribution of causal variants. Yet, we also show that precise estimates of dominance in isolates are demonstrably problematic in the presence of shared environmental effects and such effects should be accounted for. Nevertheless, we demonstrate how studying isolates can help determine the existence or non-existence of dominance for complex traits, and we find strong indications of non-zero dominance for low-density lipoprotein level in Cilento. Finally, we recommend future study designs to analyse trait variance decomposition from ensemble data across multiple population isolates.
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Affiliation(s)
- Anthony F Herzig
- Inserm, U946, Genetic variation and Human diseases, Paris, France. .,Université Paris-Diderot, Sorbonne Paris Cité, U946, Paris, France.
| | - Teresa Nutile
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, Italy
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, Italy.,IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Marina Ciullo
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, Italy. .,IRCCS Neuromed, Pozzilli, Isernia, Italy.
| | - Hervé Perdry
- Université Paris-Saclay, University. Paris-Sud, Inserm, CESP, Villejuif, France
| | - Anne-Louise Leutenegger
- Inserm, U946, Genetic variation and Human diseases, Paris, France.,Université Paris-Diderot, Sorbonne Paris Cité, U946, Paris, France
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Berton MP, de Oliveira Silva RM, Peripolli E, Stafuzza NB, Martin JF, Álvarez MS, Gavinã BV, Toro MA, Banchero G, Oliveira PS, Eler JP, Baldi F, Ferraz JBS. Genomic regions and pathways associated with gastrointestinal parasites resistance in Santa Inês breed adapted to tropical climate. J Anim Sci Biotechnol 2017; 8:73. [PMID: 28878894 PMCID: PMC5584554 DOI: 10.1186/s40104-017-0190-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Accepted: 06/12/2017] [Indexed: 12/26/2022] Open
Abstract
Background The aim of this study was to estimate variance components and to identify genomic regions and pathways associated with resistance to gastrointestinal parasites, particularly Haemonchus contortus, in a breed of sheep adapted to tropical climate. Phenotypes evaluations were performed to verify resistance to gastrointestinal parasites, and were divided into two categories: i) farm phenotypes, assessing body condition score (BCS), degree of anemia assessed by the famacha chart (FAM), fur score (FS) and feces consistency (FC); and ii) lab phenotypes, comprising blood analyses for hematocrit (HCT), white blood cell count (WBC), red blood cell count (RBC), hemoglobin (HGB), platelets (PLT) and transformed (log10) egg per gram of feces (EPGlog). A total of 576 animals were genotyped with the Ovine SNP12k BeadChip (Illumina, Inc.), that contains 12,785 bialleleic SNP markers. The variance components were estimated using a single trait model by single step genomic BLUP procedure. Results The overall linkage disequilibrium (LD) mean between pairs of markers measured by r2 was 0.23. The overall LD mean between markers considering windows up to 10 Mb was 0.07. The mean LD between adjacent SNPs across autosomes ranged from 0.02 to 0.10. Heritability estimates were low for EPGlog (0.11), moderate for RBC (0.18), PLT (0.17) HCT (0.20), HGB (0.16) and WBC (0.22), and high for FAM (0.35). A total of 22, 21, 23, 20, 26, 25 and 23 windows for EPGlog for FAM, WBC, RBC, PLT, HCT and HGB traits were identified, respectively. Among the associated windows, 10 were shown to be common to HCT and HGB traits on OAR1, OAR2, OAR3, OAR5, OAR8 and OAR15. Conclusion The traits indicating gastrointestinal parasites resistance presented an adequate genetic variability to respond to selection in Santa Inês breed, and it is expected a higher genetic gain for FAM trait when compared to the others. The level of LD estimated for markers separated by less than 1 Mb indicated that the Ovine SNP12k BeadChip might be a suitable tool for identifying genomic regions associated with traits related to gastrointestinal parasite resistance. Several candidate genes related to immune system development and activation, inflammatory response, regulation of lymphocytes and leukocytes proliferation were found. These genes may help in the selection of animals with higher resistance to parasites. Electronic supplementary material The online version of this article (doi:10.1186/s40104-017-0190-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Mariana Piatto Berton
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Via de acesso Prof. Paulo Donato Castellane, s/no, Jaboticabal, SP CEP 14884-900 Brazil
| | - Rafael Medeiros de Oliveira Silva
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Via de acesso Prof. Paulo Donato Castellane, s/no, Jaboticabal, SP CEP 14884-900 Brazil
| | - Elisa Peripolli
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Via de acesso Prof. Paulo Donato Castellane, s/no, Jaboticabal, SP CEP 14884-900 Brazil
| | - Nedenia Bonvino Stafuzza
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Via de acesso Prof. Paulo Donato Castellane, s/no, Jaboticabal, SP CEP 14884-900 Brazil
| | - Jesús Fernández Martin
- Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria INIA, Crta. de la Coruña, km 7,5 -, 28040 Madrid, Spain
| | - Maria Saura Álvarez
- Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria INIA, Crta. de la Coruña, km 7,5 -, 28040 Madrid, Spain
| | - Beatriz Villanueva Gavinã
- Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria INIA, Crta. de la Coruña, km 7,5 -, 28040 Madrid, Spain
| | - Miguel Angel Toro
- Departamento de Producción Agraria, School of Agricultural, Food and Byosystems Engineering, Universisdad Politécnica de Madrid, Campus Ciudad Universitaria Avda. Complutense 3 - Avda. Puerta Hierro, 28040 Madrid, Spain
| | - Georgget Banchero
- Instituto Nacional de Investigación Agropecuária (INIA), Ruta 50 Km. 12, Colonia, Uruguay
| | - Priscila Silva Oliveira
- Faculdade de Zootecnia e Engenharia de Alimentos, Nucleo de Apoio à Pesquisa em Melhoramento Animal, Biotecnologia e Transgenia, Universidade de São Paulo, Rua Duque de Caxias Norte, 225, Pirassununga, SP CEP 13635-900 Brazil
| | - Joanir Pereira Eler
- Faculdade de Zootecnia e Engenharia de Alimentos, Nucleo de Apoio à Pesquisa em Melhoramento Animal, Biotecnologia e Transgenia, Universidade de São Paulo, Rua Duque de Caxias Norte, 225, Pirassununga, SP CEP 13635-900 Brazil
| | - Fernando Baldi
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Via de acesso Prof. Paulo Donato Castellane, s/no, Jaboticabal, SP CEP 14884-900 Brazil
| | - José Bento Sterman Ferraz
- Faculdade de Zootecnia e Engenharia de Alimentos, Nucleo de Apoio à Pesquisa em Melhoramento Animal, Biotecnologia e Transgenia, Universidade de São Paulo, Rua Duque de Caxias Norte, 225, Pirassununga, SP CEP 13635-900 Brazil
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Al Abri MA, König von Borstel U, Strecker V, Brooks SA. Application of Genomic Estimation Methods of Inbreeding and Population Structure in an Arabian Horse Herd. J Hered 2017; 108:361-368. [DOI: 10.1093/jhered/esx025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 03/14/2017] [Indexed: 11/14/2022] Open
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Isik F, Bartholomé J, Farjat A, Chancerel E, Raffin A, Sanchez L, Plomion C, Bouffier L. Genomic selection in maritime pine. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2016; 242:108-119. [PMID: 26566829 DOI: 10.1016/j.plantsci.2015.08.006] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Revised: 08/04/2015] [Accepted: 08/13/2015] [Indexed: 05/05/2023]
Abstract
A two-generation maritime pine (Pinus pinaster Ait.) breeding population (n=661) was genotyped using 2500 SNP markers. The extent of linkage disequilibrium and utility of genomic selection for growth and stem straightness improvement were investigated. The overall intra-chromosomal linkage disequilibrium was r(2)=0.01. Linkage disequilibrium corrected for genomic relationships derived from markers was smaller (rV(2)=0.006). Genomic BLUP, Bayesian ridge regression and Bayesian LASSO regression statistical models were used to obtain genomic estimated breeding values. Two validation methods (random sampling 50% of the population and 10% of the progeny generation as validation sets) were used with 100 replications. The average predictive ability across statistical models and validation methods was about 0.49 for stem sweep, and 0.47 and 0.43 for total height and tree diameter, respectively. The sensitivity analysis suggested that prior densities (variance explained by markers) had little or no discernible effect on posterior means (residual variance) in Bayesian prediction models. Sampling from the progeny generation for model validation increased the predictive ability of markers for tree diameter and stem sweep but not for total height. The results are promising despite low linkage disequilibrium and low marker coverage of the genome (∼1.39 markers/cM).
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Affiliation(s)
- Fikret Isik
- INRA, UMR1202, BIOGECO, Cestas F-33610, France
| | - Jérôme Bartholomé
- INRA, UMR1202, BIOGECO, Cestas F-33610, France; Univ. Bordeaux, UMR1202, BIOGECO, Talence F-33170, France
| | - Alfredo Farjat
- Department of Statistics, North Carolina State University, Raleigh, NC, USA
| | - Emilie Chancerel
- INRA, UMR1202, BIOGECO, Cestas F-33610, France; Univ. Bordeaux, UMR1202, BIOGECO, Talence F-33170, France
| | - Annie Raffin
- INRA, UMR1202, BIOGECO, Cestas F-33610, France; Univ. Bordeaux, UMR1202, BIOGECO, Talence F-33170, France
| | | | - Christophe Plomion
- INRA, UMR1202, BIOGECO, Cestas F-33610, France; Univ. Bordeaux, UMR1202, BIOGECO, Talence F-33170, France
| | - Laurent Bouffier
- INRA, UMR1202, BIOGECO, Cestas F-33610, France; Univ. Bordeaux, UMR1202, BIOGECO, Talence F-33170, France.
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Gazal S, Génin E, Leutenegger AL. Relationship inference from the genetic data on parents or offspring: A comparative study. Theor Popul Biol 2015; 107:31-8. [PMID: 26431644 DOI: 10.1016/j.tpb.2015.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Revised: 09/16/2015] [Accepted: 09/17/2015] [Indexed: 02/08/2023]
Abstract
Relationship inference in a population is of interest for many areas of research from anthropology to genetics. It is possible to directly infer the relationship between the two individuals in a couple from their genetic data or to indirectly infer it from the genetic data of one of their offspring. For this reason, one can wonder if it is more advantageous to sample couples or single individuals to study relationships of couples in a population. Indeed, sampling two individuals is more informative than sampling one as we are looking at four haplotypes instead of two, but it also doubles the cost of the study and is a more complex sampling scheme. To answer this question, we performed simulations of 1000 trios from 10 different relationships using real human haplotypes to have realistic genome-wide genetic data. Then, we compared the genome sharing coefficients and the relationship inference obtained from either a pair of individuals or one of their offspring using both single-point and multi-point approaches. We observed that for relationships closer than 1st cousin, pairs of individuals were more informative than one of their offspring for relationship inference, and kinship coefficients obtained from single-point methods gave more accurate or equivalent genome sharing estimations. For more remote relationships, offspring were more informative for relationship inference, and inbreeding coefficients obtained from multi-point methods gave more accurate genome sharing estimations. In conclusion, relationship inference on a parental pair or on one of their offspring provides complementary information. When possible, sampling trios should be encouraged as it could allow spanning a wider range of potential relationships.
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Affiliation(s)
- Steven Gazal
- Inserm, UMR 1137, IAME, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, UMR 1137, Paris, France; Plateforme de Génétique constitutionnelle-Nord (PfGC-Nord), Paris, France
| | - Emmanuelle Génin
- Inserm, UMR 1078, Brest, France; Université Bretagne Occidentale, Brest, France; Centre Hospitalier Régional Universitaire, Brest, France
| | - Anne-Louise Leutenegger
- Inserm, U946, Genetic Variation and Human Diseases Lab, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d'Hématologie, UMR 946, Paris, France.
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Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications. Heredity (Edinb) 2015; 116:146-57. [PMID: 26328760 DOI: 10.1038/hdy.2015.78] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Revised: 07/03/2015] [Accepted: 07/22/2015] [Indexed: 12/28/2022] Open
Abstract
Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information.
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Lourenco DAL, Fragomeni BO, Tsuruta S, Aguilar I, Zumbach B, Hawken RJ, Legarra A, Misztal I. Accuracy of estimated breeding values with genomic information on males, females, or both: an example on broiler chicken. Genet Sel Evol 2015; 47:56. [PMID: 26133806 PMCID: PMC4487961 DOI: 10.1186/s12711-015-0137-1] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 06/22/2015] [Indexed: 11/12/2022] Open
Abstract
Background As more and more genotypes become available, accuracy of genomic evaluations can potentially increase. However, the impact of genotype data on accuracy depends on the structure of the genotyped cohort. For populations such as dairy cattle, the greatest benefit has come from genotyping sires with high accuracy, whereas the benefit due to adding genotypes from cows was smaller. In broiler chicken breeding programs, males have less progeny than dairy bulls, females have more progeny than dairy cows, and most production traits are recorded for both sexes. Consequently, genotyping both sexes in broiler chickens may be more advantageous than in dairy cattle. Methods We studied the contribution of genotypes from males and females using a real dataset with genotypes on 15 723 broiler chickens. Genomic evaluations used three training sets that included only males (4648), only females (8100), and both sexes (12 748). Realized accuracies of genomic estimated breeding values (GEBV) were used to evaluate the benefit of including genotypes for different training populations on genomic predictions of young genotyped chickens. Results Using genotypes on males, the average increase in accuracy of GEBV over pedigree-based EBV for males and females was 12 and 1 percentage points, respectively. Using female genotypes, this increase was 1 and 18 percentage points, respectively. Using genotypes of both sexes increased accuracies by 19 points for males and 20 points for females. For two traits with similar heritabilities and amounts of information, realized accuracies from cross-validation were lower for the trait that was under strong selection. Conclusions Overall, genotyping males and females improves predictions of all young genotyped chickens, regardless of sex. Therefore, when males and females both contribute to genetic progress of the population, genotyping both sexes may be the best option.
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Affiliation(s)
- Daniela A L Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
| | - Breno O Fragomeni
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
| | - Shogo Tsuruta
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
| | - Ignacio Aguilar
- Instituto Nacional de Investigacion Agropecuaria, Las Brujas, 90200, Uruguay.
| | | | | | - Andres Legarra
- Institut National de la Recherche Agronomique, UMR1388 GenPhySE, 31326, Castanet-Tolosan, France.
| | - Ignacy Misztal
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
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Abstract
Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.
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