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Tuggle CK, Clarke JL, Murdoch BM, Lyons E, Scott NM, Beneš B, Campbell JD, Chung H, Daigle CL, Das Choudhury S, Dekkers JCM, Dórea JRR, Ertl DS, Feldman M, Fragomeni BO, Fulton JE, Guadagno CR, Hagen DE, Hess AS, Kramer LM, Lawrence-Dill CJ, Lipka AE, Lübberstedt T, McCarthy FM, McKay SD, Murray SC, Riggs PK, Rowan TN, Sheehan MJ, Steibel JP, Thompson AM, Thornton KJ, Van Tassell CP, Schnable PS. Current challenges and future of agricultural genomes to phenomes in the USA. Genome Biol 2024; 25:8. [PMID: 38172911 PMCID: PMC10763150 DOI: 10.1186/s13059-023-03155-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024] Open
Abstract
Dramatic improvements in measuring genetic variation across agriculturally relevant populations (genomics) must be matched by improvements in identifying and measuring relevant trait variation in such populations across many environments (phenomics). Identifying the most critical opportunities and challenges in genome to phenome (G2P) research is the focus of this paper. Previously (Genome Biol, 23(1):1-11, 2022), we laid out how Agricultural Genome to Phenome Initiative (AG2PI) will coordinate activities with USA federal government agencies expand public-private partnerships, and engage with external stakeholders to achieve a shared vision of future the AG2PI. Acting on this latter step, AG2PI organized the "Thinking Big: Visualizing the Future of AG2PI" two-day workshop held September 9-10, 2022, in Ames, Iowa, co-hosted with the United State Department of Agriculture's National Institute of Food and Agriculture (USDA NIFA). During the meeting, attendees were asked to use their experience and curiosity to review the current status of agricultural genome to phenome (AG2P) work and envision the future of the AG2P field. The topic summaries composing this paper are distilled from two 1.5-h small group discussions. Challenges and solutions identified across multiple topics at the workshop were explored. We end our discussion with a vision for the future of agricultural progress, identifying two areas of innovation needed: (1) innovate in genetic improvement methods development and evaluation and (2) innovate in agricultural research processes to solve societal problems. To address these needs, we then provide six specific goals that we recommend be implemented immediately in support of advancing AG2P research.
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Sosa-Madrid BS, Maniatis G, Ibáñez-Escriche N, Avendaño S, Kranis A. Genetic Variance Estimation over Time in Broiler Breeding Programmes for Growth and Reproductive Traits. Animals (Basel) 2023; 13:3306. [PMID: 37958060 PMCID: PMC10649193 DOI: 10.3390/ani13213306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 11/15/2023] Open
Abstract
Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring changes in genetic variation have typically used long-term data from small experimental populations selected for a handful of traits. Here, we used a large dataset from a commercial breeding line spread over a period of twenty-three years. A total of 2,059,869 records and 2,062,112 animals in the pedigree were used for the estimations of variance components for the traits: body weight (BWT; 2,059,869 records) and hen-housed egg production (HHP; 45,939 records). Data were analysed with three estimation approaches: sliding overlapping windows, under frequentist (restricted maximum likelihood (REML)) and Bayesian (Gibbs sampling) methods; expected variances using coefficients of the full relationship matrix; and a "double trait covariances" analysis by computing correlations and covariances between the same trait in two distinct consecutive windows. The genetic variance showed marginal fluctuations in its estimation over time. Whereas genetic, maternal permanent environmental, and residual variances were similar for BWT in both the REML and Gibbs methods, variance components when using the Gibbs method for HHP were smaller than the variances estimated when using REML. Large data amounts were needed to estimate variance components and detect their changes. For Gibbs (REML), the changes in genetic variance from 1999-2001 to 2020-2022 were 82.29 to 93.75 (82.84 to 93.68) for BWT and 76.68 to 95.67 (98.42 to 109.04) for HHP. Heritability presented a similar pattern as the genetic variance estimation, changing from 0.32 to 0.36 (0.32 to 0.36) for BWT and 0.16 to 0.15 (0.21 to 0.18) for HHP. On the whole, genetic parameters tended slightly to increase over time. The expected variance estimates were lower than the estimates when using overlapping windows. That indicates the low effect of the drift-selection process on the genetic variance, or likely, the presence of genetic variation sources compensating for the loss. Double trait covariance analysis confirmed the maintenance of variances over time, presenting genetic correlations >0.86 for BWT and >0.82 for HHP. Monitoring genetic variance in broiler breeding programmes is important to sustain genetic progress. Although the genetic variances of both traits fluctuated over time, in some windows, particularly between 2003 and 2020, increasing trends were observed, which warrants further research on the impact of other factors, such as novel mutations, operating on the dynamics of genetic variance.
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Affiliation(s)
- Bolívar Samuel Sosa-Madrid
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
- Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 2201, 46071 Valencia, Spain;
| | | | - Noelia Ibáñez-Escriche
- Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 2201, 46071 Valencia, Spain;
| | | | - Andreas Kranis
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
- Aviagen Ltd., Newbridge, Edinburgh EH28 8SZ, UK; (G.M.); (S.A.)
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Wang Z, Doekes H, Bijma P. Towards genetic improvement of social behaviours in livestock using large-scale sensor data: data simulation and genetic analysis. Genet Sel Evol 2023; 55:67. [PMID: 37770844 PMCID: PMC10537099 DOI: 10.1186/s12711-023-00840-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/11/2023] [Indexed: 09/30/2023] Open
Abstract
BACKGROUND Harmful social behaviours, such as injurious feather pecking in poultry and tail biting in swine, reduce animal welfare and production efficiency. While these behaviours are heritable, selective breeding is still limited due to a lack of individual phenotyping methods for large groups and proper genetic models. In the near future, large-scale longitudinal data on social behaviours will become available, e.g. through computer vision techniques, and appropriate genetic models will be needed to analyse such data. In this paper, we investigated prospects for genetic improvement of social traits recorded in large groups by (1) developing models to simulate and analyse large-scale longitudinal data on social behaviours, and (2) investigating required sample sizes to obtain reasonable accuracies of estimated genetic parameters and breeding values (EBV). RESULTS Latent traits were defined as representing tendencies of individuals to be engaged in social interactions by distinguishing between performer and recipient effects. Animal movement was assumed random and without genetic variation, and performer and recipient interaction effects were assumed constant over time. Based on the literature, observed-scale heritabilities ([Formula: see text]) of performer and recipient effects were both set to 0.05, 0.1, or 0.2, and the genetic correlation ([Formula: see text]) between those effects was set to - 0.5, 0, or 0.5. Using agent-based modelling, we simulated ~ 200,000 interactions for 2000 animals (~ 1000 interactions per animal) with a half-sib family structure. Variance components and breeding values were estimated with a general linear mixed model. The estimated genetic parameters did not differ significantly from the true values. When all individuals and interactions were included in the analysis, the accuracy of EBV was 0.61, 0.70, and 0.76 for [Formula: see text] = 0.05, 0.1, and 0.2, respectively (for [Formula: see text]= 0). Including 2000 individuals each with only ~ 100 interactions, already yielded promising accuracies of 0.47, 0.60, and 0.71 for [Formula: see text] = 0.05, 0.1, and 0.2, respectively (with [Formula: see text] = 0). Similar results were found with [Formula: see text] of - 0.5 or 0.5. CONCLUSIONS We developed models to simulate and genetically analyse social behaviours for animals that are kept in large groups, anticipating the availability of large-scale longitudinal data in the near future. We obtained promising accuracies of EBV with ~ 100 interactions per individual, which would correspond to a few weeks of recording. Therefore, we conclude that animal breeding can be a promising strategy to improve social behaviours in livestock.
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Affiliation(s)
- Zhuoshi Wang
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH Wageningen, The Netherlands
| | - Harmen Doekes
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH Wageningen, The Netherlands
| | - Piter Bijma
- Animal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH Wageningen, The Netherlands
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Simianer H, Heise J, Rensing S, Pook T, Geibel J, Reimer C. How economic weights translate into genetic and phenotypic progress, and vice versa. Genet Sel Evol 2023; 55:38. [PMID: 37291496 DOI: 10.1186/s12711-023-00807-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/27/2023] [Indexed: 06/10/2023] Open
Abstract
BACKGROUND This paper highlights the relationships between economic weights, genetic progress, and phenotypic progress in genomic breeding programs that aim at generating genetic progress in complex, i.e., multi-trait, breeding objectives via a combination of estimated breeding values for different trait complexes. RESULTS Based on classical selection index theory in combination with quantitative genetic models, we provide a methodological framework for calculating expected genetic and phenotypic progress for all components of a complex breeding objective. We further provide an approach to study the sensitivity of the system to modifications, e.g. to changes in the economic weights. We propose a novel approach to derive the covariance structure of the stochastic errors of estimated breeding values from the observed correlations of estimated breeding values. We define 'realized economic weights' as those weights that would coincide with the observed composition of the genetic trend and show, how they can be calculated. The suggested methodology is illustrated with an index that aims at achieving a breeding goal composed of six trait complexes, that was applied in German Holstein cattle breeding until 2021. CONCLUSIONS Based on the presented results, the main conclusions are (i) the composition of the observed genetic progress matches the expectations well, with predictions being slightly better when the covariance of estimation errors is taken into account; (ii) the composition of the expected phenotypic trend deviates significantly from the expected genetic trend due to the differences in trait heritabilities; and (iii) the realized economic weights derived from the observed genetic trend deviate substantially from the predefined ones, in one case even with a reversed sign. Further results highlight the implications of the change to a modified breeding goal based on the example of a new index comprising eight, partly new, trait complexes, which is used since 2021 in the German Holstein breeding program. The proposed framework and the analytical tools and software provided will be useful to define more rational and generally accepted breeding objectives in the future.
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Affiliation(s)
- Henner Simianer
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany.
| | - Johannes Heise
- IT Solutions for Animal Production (vit), Heinrich-Schröder-Weg 1, 27283, Verden/Aller, Germany
| | - Stefan Rensing
- IT Solutions for Animal Production (vit), Heinrich-Schröder-Weg 1, 27283, Verden/Aller, Germany
| | - Torsten Pook
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Animal Breeding and Genomics Group, Wageningen University & Research, PO Box 338, 6700 AH, Wageningen, The Netherlands
| | - Johannes Geibel
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Friedrich-Loeffler-Institut, Division of Farm Animal Genetics, Höltystraße 10, 31535, Neustadt, Germany
| | - Christian Reimer
- Animal Breeding Group, Department of Animal Sciences, Center for Integrated Breeding Research, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Göttingen, Germany
- Friedrich-Loeffler-Institut, Division of Farm Animal Genetics, Höltystraße 10, 31535, Neustadt, Germany
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Hernández-Delgado P, Felix-Portillo M, Martínez-Quintana JA. ADAMTS Proteases: Importance in Animal Reproduction. Genes (Basel) 2023; 14:1181. [PMID: 37372361 DOI: 10.3390/genes14061181] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Many reproductive physiological processes, such as folliculogenesis, ovulation, implantation, and fertilization, require the synthesis, remodeling, and degradation of the extracellular matrix (ECM). The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin Motifs) family genes code for key metalloproteinases in the remodeling process of different ECM. Several genes of this family encode for proteins with important functions in reproductive processes; in particular, ADAMTS1, 4, 5 and 9 are genes that are differentially expressed in cell types and the physiological stages of reproductive tissues. ADAMTS enzymes degrade proteoglycans in the ECM of the follicles so that the oocytes can be released and regulate follicle development during folliculogenesis, favoring the action of essential growth factors, such as FGF-2, FGF-7 and GDF-9. The transcriptional regulation of ADAMTS1 and 9 in preovulatory follicles occurs because of the gonadotropin surge in preovulatory follicles, via the progesterone/progesterone receptor complex. In addition, in the case of ADAMTS1, pathways involving protein kinase A (PKA), extracellular signal regulated protein kinase (ERK1/2) and the epidermal growth factor receptor (EGFR) might contribute to ECM regulation. Different Omic studies indicate the importance of genes of the ADAMTS family from a reproductive aspect. ADAMTS genes could serve as biomarkers for genetic improvement and contribute to enhance fertility and animal reproduction; however, more research related to these genes, the synthesis of proteins encoded by these genes, and regulation in farm animals is needed.
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Sharman P, Wilson AJ. Genetic improvement of speed across distance categories in thoroughbred racehorses in Great Britain. Heredity (Edinb) 2023:10.1038/s41437-023-00623-8. [PMID: 37244934 DOI: 10.1038/s41437-023-00623-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/29/2023] Open
Abstract
Several studies over recent decades have reported a lack of contemporary improvement in thoroughbred racehorse speed, despite apparent additive genetic variance and putatively strong selection. More recently, it has been shown that some phenotypic improvement is ongoing, but rates are low in general and particularly so over longer distances. Here we used pedigree-based analysis of 692,534 records from 76,960 animals to determine whether these phenotypic trends are underpinned by genetic selection responses, and to evaluate the potential for more rapid improvement. We show that thoroughbred speed in Great Britain is only weakly heritable across sprint (h2 = 0.124), middle-distance (h2 = 0.122) and long-distance races (h2 = 0.074), but that mean predicted breeding values are nonetheless increasing across cohorts born between 1995 and 2012 (and racing from 1997 to 2014). For all three race distance categories, estimated rates of genetic improvement are statistically significant and also greater than can be explained by drift. Taken together our results show genetic improvement for thoroughbred speed is ongoing but slow, likely due to a combination of long generation times and low heritabilities. Additionally, estimates of realised selection intensities raises the possibility that the contemporary selection emerging from the collective actions of horse breeders is weaker than previously assumed, particularly over long distances. We suggest that unmodelled common environment effects may have upwardly biased estimates of heritability, and thus expected selection response, previously.
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Affiliation(s)
- Patrick Sharman
- Centre for Ecology and Conservation, University of Exeter (Penryn Campus), Cornwall, TR10 9FE, UK.
| | - Alastair J Wilson
- Centre for Ecology and Conservation, University of Exeter (Penryn Campus), Cornwall, TR10 9FE, UK
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Pocrnic I, Obšteter J, Gaynor RC, Wolc A, Gorjanc G. Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study. Front Genet 2023; 14:1168212. [PMID: 37234871 PMCID: PMC10206274 DOI: 10.3389/fgene.2023.1168212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/02/2023] [Indexed: 05/28/2023] Open
Abstract
Nucleus-based breeding programs are characterized by intense selection that results in high genetic gain, which inevitably means reduction of genetic variation in the breeding population. Therefore, genetic variation in such breeding systems is typically managed systematically, for example, by avoiding mating the closest relatives to limit progeny inbreeding. However, intense selection requires maximum effort to make such breeding programs sustainable in the long-term. The objective of this study was to use simulation to evaluate the long-term impact of genomic selection on genetic mean and variance in an intense layer chicken breeding program. We developed a large-scale stochastic simulation of an intense layer chicken breeding program to compare conventional truncation selection to genomic truncation selection optimized with either minimization of progeny inbreeding or full-scale optimal contribution selection. We compared the programs in terms of genetic mean, genic variance, conversion efficiency, rate of inbreeding, effective population size, and accuracy of selection. Our results confirmed that genomic truncation selection has immediate benefits compared to conventional truncation selection in all specified metrics. A simple minimization of progeny inbreeding after genomic truncation selection did not provide any significant improvements. Optimal contribution selection was successful in having better conversion efficiency and effective population size compared to genomic truncation selection, but it must be fine-tuned for balance between loss of genetic variance and genetic gain. In our simulation, we measured this balance using trigonometric penalty degrees between truncation selection and a balanced solution and concluded that the best results were between 45° and 65°. This balance is specific to the breeding program and depends on how much immediate genetic gain a breeding program may risk vs. save for the future. Furthermore, our results show that the persistence of accuracy is better with optimal contribution selection compared to truncation selection. In general, our results show that optimal contribution selection can ensure long-term success in intensive breeding programs using genomic selection.
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Affiliation(s)
- Ivan Pocrnic
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, United Kingdom
| | - Jana Obšteter
- Agricultural Institute of Slovenia, Ljubljana, Slovenia
| | - R. Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, United Kingdom
| | - Anna Wolc
- Department of Animal Science, Iowa State University, Ames, IA, United States
- Hy-Line International, Dallas Center, IA, United States
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, United Kingdom
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Gajaweera C, Kang DH, Lee DH, Kim YK, Park BH, Chang SS, Kim UH, Lee SH, Chung KY. Development of nutrigenomic based precision management model for Hanwoo steers. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2023; 65:596-610. [PMID: 37332286 PMCID: PMC10271920 DOI: 10.5187/jast.2023.e38] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/25/2023] [Accepted: 04/13/2023] [Indexed: 06/20/2023]
Abstract
Focusing high marble deposition, Hanwoo feedlot system uses high-energy diet over the prolonged fattening period. However, due to the individual genetic variation, around 40% of them are graded into inferior quality grades (QG), despite they utilized the same resources. Therefore, focusing on development of a nutrigenomic based precision management model, this study was to evaluated the response to the divergent selection on genetic merit for marbling score (MS), under different dietary total digestible nutrient (TDN) levels. Total of 111 calves were genotyped and initially grouped according to estimated breeding value (high and low) for marbling score (MS-EBV). Subsequently, managed under two levels of feed TDN%, over the calf period, early, middle, and final fattening periods following 2 × 2 factorial arrangement. Carcasses were evaluated for MS, Back fat thickness (BFT) and Korean beef quality grading standard. As the direct response to the selection was significant, the results confirmed the importance of initial genetic grouping of Hanwoo steers for MS-EBV. However, dietary TDN level did not show an effect (p > 0.05) on the MS. Furthermore, no genetic-by-nutrition interaction for MS (p > 0.05) was also observed. The present results showed no correlation response on BFT (p > 0.05), which indicates that the selection based on MS-EBV can be used to enhance the MS without undesirable effect on BFT. Ultimate turnover of the Hanwoo feedlot operation is primarily determined by the QGs. The present model shows that the initial grouping for MS-EBV increased the proportion of carcasses graded for higher QGs (QG1++ and QG1+) by approximately 20%. Moreover, there appear to be a potential to increase the proportion of QG 1++ animals among the high-genetic group by further increasing the dietary energy content. Overall, this precision management strategy suggests the importance of adopting an MS based initial genetic grouping system for Hanwoo steers with a subsequent divergent management based on dietary energy level.
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Affiliation(s)
- Chandima Gajaweera
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
- Department of Animal Science, Faculty of Agriculture, University of Ruhuna, Matara 81100, Sri Lanka
| | - Dong Hun Kang
- Department of Livestock, Korea National University of Agriculture and Fisheries, Jeonju 54874, Korea
| | - Doo Ho Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Yeong-Kuk Kim
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Bo Hye Park
- Department of Livestock, Korea National University of Agriculture and Fisheries, Jeonju 54874, Korea
| | - Sun Sik Chang
- Hanwoo Research Institute, National Institute of Animal Science, RDA, Pyeongchang 25340, Korea
| | - Ui Hyung Kim
- Hanwoo Research Institute, National Institute of Animal Science, RDA, Pyeongchang 25340, Korea
| | - Seung Hwan Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Ki Yong Chung
- Department of Livestock, Korea National University of Agriculture and Fisheries, Jeonju 54874, Korea
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Lafontaine S, Labrecque R, Blondin P, Cue RI, Sirard MA. Comparison of cattle derived from in vitro fertilization, multiple ovulation embryo transfer, and artificial insemination for milk production and fertility traits. J Dairy Sci 2023; 106:4380-4396. [PMID: 37028966 DOI: 10.3168/jds.2022-22736] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/19/2022] [Indexed: 04/09/2023]
Abstract
The use of assisted-reproduction technologies such as in vitro fertilization (IVF) is increasing, particularly in dairy cattle. The question of consequences in later life has not yet been directly addressed by studies on large animal populations. Studies on rodents and early data from humans and cattle suggest that in vitro manipulation of gametes and embryos could result in long-term alteration of metabolism, growth, and fertility. Our goal was to better describe these presumed consequences in the population of dairy cows produced by IVF in Québec (Canada) and to compare them to animals conceived by artificial insemination (AI) or multiple ovulation embryo transfer (MOET). To do so, we leveraged a large phenotypic database (2.5 million animals and 4.5 million lactations) from milk records in Québec aggregated by Lactanet (Sainte-Anne-de-Bellevue, QC, Canada) and spanning 2012 to 2019. We identified 304,163, 12,993, and 732 cows conceived by AI, MOET, and IVF, respectively, for a total of 317,888 Holstein animals from which we retrieved information for 576,448, 24,192, and 1,299 lactations (total = 601,939), respectively. Genetic energy-corrected milk yield (GECM) and Lifetime Performance Index (LPI) of the parents of cows were used to normalize for genetic potential across animals. When compared with the general Holstein population, MOET and IVF cows outperformed AI cows. However, when comparing those same MOET and IVF cows with only herdmates and accounting for their higher GECM in the models, we found no statistical difference between the conception methods for milk production across the first 3 lactations. We also found that the rate of Lifetime Performance Index improvement of the IVF population during the 2012 to 2019 period was less than the rate observed in the AI population. Fertility analysis revealed that MOET and IVF cows also scored 1 point lower than their parents on the daughter fertility index and had a longer interval from first service to conception, with an average of 35.52 d compared with 32.45 for MOET and 31.87 for AI animals. These results highlight the challenges of elite genetic improvement while attesting to the progress the industry has made in minimizing epigenetic disturbance during embryo production. Nonetheless, additional work is required to ensure that IVF animals can maintain their performance and fertility potential.
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Affiliation(s)
- Simon Lafontaine
- Centre de recherche en reproduction, développement et santé intergénérationnelle (CRDSI), Département des Sciences Animales, Faculté des sciences de l'agriculture et de l'alimentation, Université Laval, Québec, QC G1K 7P4, Canada
| | - Rémi Labrecque
- SEMEX Boviteq, 3450 Rue Sicotte, Saint-Hyacinthe, QC J2S 2M2, Canada
| | - Patrick Blondin
- SEMEX Boviteq, 3450 Rue Sicotte, Saint-Hyacinthe, QC J2S 2M2, Canada
| | - Roger I Cue
- Department of Animal Science, McGill University, Montréal, QC H9X 3V9, Canada
| | - Marc-André Sirard
- Centre de recherche en reproduction, développement et santé intergénérationnelle (CRDSI), Département des Sciences Animales, Faculté des sciences de l'agriculture et de l'alimentation, Université Laval, Québec, QC G1K 7P4, Canada.
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Weller JI, Gershoni M, Ezra E. Breeding Dairy Cattle for Female Fertility and Production in the Age of Genomics. Vet Sci 2022; 9:vetsci9080434. [PMID: 36006349 PMCID: PMC9416766 DOI: 10.3390/vetsci9080434] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/01/2022] [Accepted: 08/06/2022] [Indexed: 11/16/2022] Open
Abstract
Phenotypic and genetic changes for female fertility and production traits in the Israeli Holstein population over the last three decades were studied in order to determine if long term selection has resulted in reduced heritability and negative genetic correlations. Annual means for conception status, defined as the inverse of the number of inseminations to conception in percent, decreased from 55.6 for cows born in 1983 to 46.5 for cows born in 2018. Mean estimated breeding values increased by 1.8% for cow born in 1981 to cows born in 2018. Phenotypic records from 1988 to 2016 for the nine Israeli breeding index traits were divided into three time periods for multi-trait REML analysis by the individual animal model. For all traits, heritabilities increased or stayed the same for the later time periods. Heritability for conception status was 0.05. The first parity genetic correlation between conception status and protein yield was −0.38. Heritabilities decreased with the increase in parity for protein but remained the same for conception status. Realized genetic trends were greater than expected for cows born from 2008 through 2016 for somatic cell score, conception status and herd-life, and lower than expected for the production traits.
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Affiliation(s)
- Joel Ira Weller
- Israel Cattle Breeders Association, Caesarea 38900, Israel
- Agricultural Research Organization, The Volcani Center, Rishon LeZion 15159, Israel
- Correspondence: ; Tel.: +972-506220430
| | - Moran Gershoni
- Agricultural Research Organization, The Volcani Center, Rishon LeZion 15159, Israel
| | - Ephraim Ezra
- Israel Cattle Breeders Association, Caesarea 38900, Israel
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Abstract
When Mendel’s work was rediscovered in 1900, and extended to establish classical genetics, it was initially seen in opposition to Darwin’s theory of evolution by natural selection on continuous variation, as represented by the biometric research program that was the foundation of quantitative genetics. As Fisher, Haldane, and Wright established a century ago, Mendelian inheritance is exactly what is needed for natural selection to work efficiently. Yet, the synthesis remains unfinished. We do not understand why sexual reproduction and a fair meiosis predominate in eukaryotes, or how far these are responsible for their diversity and complexity. Moreover, although quantitative geneticists have long known that adaptive variation is highly polygenic, and that this is essential for efficient selection, this is only now becoming appreciated by molecular biologists—and we still do not have a good framework for understanding polygenic variation or diffuse function.
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Wientjes YCJ, Bijma P, Calus MPL, Zwaan BJ, Vitezica ZG, van den Heuvel J. The long-term effects of genomic selection: 1. Response to selection, additive genetic variance, and genetic architecture. Genet Sel Evol 2022; 54:19. [PMID: 35255802 PMCID: PMC8900405 DOI: 10.1186/s12711-022-00709-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 02/10/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Genomic selection has revolutionized genetic improvement in animals and plants, but little is known about its long-term effects. Here, we investigated the long-term effects of genomic selection on response to selection, genetic variance, and the genetic architecture of traits using stochastic simulations. We defined the genetic architecture as the set of causal loci underlying each trait, their allele frequencies, and their statistical additive effects. We simulated a livestock population under 50 generations of phenotypic, pedigree, or genomic selection for a single trait, controlled by either only additive, additive and dominance, or additive, dominance, and epistatic effects. The simulated epistasis was based on yeast data.
Results
Short-term response was always greatest with genomic selection, while response after 50 generations was greater with phenotypic selection than with genomic selection when epistasis was present, and was always greater than with pedigree selection. This was mainly because loss of genetic variance and of segregating loci was much greater with genomic and pedigree selection than with phenotypic selection. Compared to pedigree selection, selection response was always greater with genomic selection. Pedigree and genomic selection lost a similar amount of genetic variance after 50 generations of selection, but genomic selection maintained more segregating loci, which on average had lower minor allele frequencies than with pedigree selection. Based on this result, genomic selection is expected to better maintain genetic gain after 50 generations than pedigree selection. The amount of change in the genetic architecture of traits was considerable across generations and was similar for genomic and pedigree selection, but slightly less for phenotypic selection. Presence of epistasis resulted in smaller changes in allele frequencies and less fixation of causal loci, but resulted in substantial changes in statistical additive effects across generations.
Conclusions
Our results show that genomic selection outperforms pedigree selection in terms of long-term genetic gain, but results in a similar reduction of genetic variance. The genetic architecture of traits changed considerably across generations, especially under selection and when non-additive effects were present. In conclusion, non-additive effects had a substantial impact on the accuracy of selection and long-term response to selection, especially when selection was accurate.
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13
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Weller JI. Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, the Dairy Cattle Case. Methods Mol Biol 2022; 2467:447-467. [PMID: 35451786 DOI: 10.1007/978-1-0716-2205-6_16] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In accordance with the infinitesimal model for quantitative traits, a very large number of genes affect nearly all economic traits. In only two cases has the causative polymorphism been determined for genes affecting economic traits in dairy cattle. Most current methods for genomic evaluation are based on the "two-step" method. Genetic evaluations are computed by the individual animal model, and functions of the evaluations of progeny-tested sires are the dependent variable for estimation of marker effects. With the adoption of genomic evaluation in 2008, annual rates of genetic gain in the US increased from ∼50-100% for yield traits and from threefold to fourfold for lowly heritable traits, including female fertility, herd-life and somatic cell concentration. Gradual elimination of the progeny test scheme has led to a reduction in the number of sires with daughter records and less genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and "environmentally friendly" production. Genetic variance for economic traits is maintained by increase in frequency of rare alleles, new mutations, and changes in selection goals and management.
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Affiliation(s)
- Joel Ira Weller
- Agricultural Research Organization, The Volcani Center, Rishon LeZion, Israel.
- Israel Cattle Breeders' Association, Caesarea Industrial Park, Israel.
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14
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Hayward LK, Sella G. Polygenic adaptation after a sudden change in environment. eLife 2022; 11:66697. [PMID: 36155653 PMCID: PMC9683794 DOI: 10.7554/elife.66697] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/18/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.
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Affiliation(s)
- Laura Katharine Hayward
- Department of Mathematics, Columbia UniversityNew YorkUnited States,Institute of Science and TechnologyMaria GuggingAustria
| | - Guy Sella
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States,Program for Mathematical Genomics, Columbia UniversityNew YorkUnited States
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15
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Hara H, Ogawa S, Ohnishi C, Ishii K, Uemoto Y, Satoh M. An attempt of using public ambient temperature data in swine genetic evaluation for litter-size traits at birth in Japan†. ANIMAL PRODUCTION SCIENCE 2022. [DOI: 10.1071/an21463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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16
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Lara LADC, Pocrnic I, Oliveira TDP, Gaynor RC, Gorjanc G. Temporal and genomic analysis of additive genetic variance in breeding programmes. Heredity (Edinb) 2022; 128:21-32. [PMID: 34912044 PMCID: PMC8733024 DOI: 10.1038/s41437-021-00485-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/24/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Genetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is therefore of high interest. Here, we extend a previously proposed framework for temporal analysis of genetic variance using the pedigree-based model, to a new framework for temporal and genomic analysis of genetic variance using marker-based models. To this end, we describe the theory of partitioning genetic variance into genic variance and within-chromosome and between-chromosome linkage-disequilibrium, and how to estimate these variance components from a marker-based model fitted to observed phenotype and marker data. The new framework involves three steps: (i) fitting a marker-based model to data, (ii) sampling realisations of marker effects from the fitted model and for each sample calculating realisations of genetic values and (iii) calculating the variance of sampled genetic values by time and genome partitions. Analysing time partitions indicates breeding programme sustainability, while analysing genome partitions indicates contributions from chromosomes and chromosome pairs and linkage-disequilibrium. We demonstrate the framework with a simulated breeding programme involving a complex trait. Results show good concordance between simulated and estimated variances, provided that the fitted model is capturing genetic complexity of a trait. We observe a reduction of genetic variance due to selection and drift changing allele frequencies, and due to selection inducing negative linkage-disequilibrium.
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Affiliation(s)
- Letícia A de C Lara
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK.
| | - Ivan Pocrnic
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK
| | - Thiago de P Oliveira
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK
| | - R Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK
| | - Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK
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17
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Douhard F, Douhard M, Gilbert H, Monget P, Gaillard J, Lemaître J. How much energetic trade-offs limit selection? Insights from livestock and related laboratory model species. Evol Appl 2021; 14:2726-2749. [PMID: 34950226 PMCID: PMC8674892 DOI: 10.1111/eva.13320] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 10/22/2021] [Accepted: 10/22/2021] [Indexed: 12/22/2022] Open
Abstract
Trade-offs between life history traits are expected to occur due to the limited amount of resources that organisms can obtain and share among biological functions, but are of least concern for selection responses in nutrient-rich or benign environments. In domestic animals, selection limits have not yet been reached despite strong selection for higher meat, milk or egg yields. Yet, negative genetic correlations between productivity traits and health or fertility traits have often been reported, supporting the view that trade-offs do occur in the context of nonlimiting resources. The importance of allocation mechanisms in limiting genetic changes can thus be questioned when animals are mostly constrained by their time to acquire and process energy rather than by feed availability. Selection for high productivity traits early in life should promote a fast metabolism with less energy allocated to self-maintenance (contributing to soma preservation and repair). Consequently, the capacity to breed shortly after an intensive period of production or to remain healthy should be compromised. We assessed those predictions in mammalian and avian livestock and related laboratory model species. First, we surveyed studies that compared energy allocation to maintenance between breeds or lines of contrasting productivity but found little support for the occurrence of an energy allocation trade-off. Second, selection experiments for lower feed intake per unit of product (i.e. higher feed efficiency) generally resulted in reduced allocation to maintenance, but this did not entail fitness costs in terms of survival or future reproduction. These findings indicate that the consequences of a particular selection in domestic animals are much more difficult to predict than one could anticipate from the energy allocation framework alone. Future developments to predict the contribution of time constraints and trade-offs to selection limits will be insightful to breed livestock in increasingly challenging environments.
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Affiliation(s)
| | - Mathieu Douhard
- Laboratoire de Biométrie & Biologie EvolutiveCNRSUMR 5558Université Lyon 1VilleurbanneFrance
| | - Hélène Gilbert
- GenPhySEINRAEENVTUniversité de ToulouseCastanet‐TolosanFrance
| | | | - Jean‐Michel Gaillard
- Laboratoire de Biométrie & Biologie EvolutiveCNRSUMR 5558Université Lyon 1VilleurbanneFrance
| | - Jean‐François Lemaître
- Laboratoire de Biométrie & Biologie EvolutiveCNRSUMR 5558Université Lyon 1VilleurbanneFrance
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18
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Lagarrigue S, Lorthiois M, Degalez F, Gilot D, Derrien T. LncRNAs in domesticated animals: from dog to livestock species. Mamm Genome 2021; 33:248-270. [PMID: 34773482 PMCID: PMC9114084 DOI: 10.1007/s00335-021-09928-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/19/2021] [Indexed: 11/29/2022]
Abstract
Animal genomes are pervasively transcribed into multiple RNA molecules, of which many will not be translated into proteins. One major component of this transcribed non-coding genome is the long non-coding RNAs (lncRNAs), which are defined as transcripts longer than 200 nucleotides with low coding-potential capabilities. Domestic animals constitute a unique resource for studying the genetic and epigenetic basis of phenotypic variations involving protein-coding and non-coding RNAs, such as lncRNAs. This review presents the current knowledge regarding transcriptome-based catalogues of lncRNAs in major domesticated animals (pets and livestock species), covering a broad phylogenetic scale (from dogs to chicken), and in comparison with human and mouse lncRNA catalogues. Furthermore, we describe different methods to extract known or discover novel lncRNAs and explore comparative genomics approaches to strengthen the annotation of lncRNAs. We then detail different strategies contributing to a better understanding of lncRNA functions, from genetic studies such as GWAS to molecular biology experiments and give some case examples in domestic animals. Finally, we discuss the limitations of current lncRNA annotations and suggest research directions to improve them and their functional characterisation.
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Affiliation(s)
| | - Matthias Lorthiois
- Univ Rennes, CNRS, IGDR (Institut de Génétique et Développement de Rennes) - UMR 6290, 2 av Prof Leon Bernard, F-35000, Rennes, France
| | - Fabien Degalez
- INRAE, INSTITUT AGRO, PEGASE UMR 1348, 35590, Saint-Gilles, France
| | - David Gilot
- CLCC Eugène Marquis, INSERM, Université Rennes, UMR_S 1242, 35000, Rennes, France
| | - Thomas Derrien
- Univ Rennes, CNRS, IGDR (Institut de Génétique et Développement de Rennes) - UMR 6290, 2 av Prof Leon Bernard, F-35000, Rennes, France.
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19
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Abdelhafiz Y, Fernandes JMO, Larger S, Albanese D, Donati C, Jafari O, Nedoluzhko AV, Kiron V. Breeding Strategy Shapes the Composition of Bacterial Communities in Female Nile Tilapia Reared in a Recirculating Aquaculture System. Front Microbiol 2021; 12:709611. [PMID: 34566914 PMCID: PMC8461179 DOI: 10.3389/fmicb.2021.709611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/13/2021] [Indexed: 11/13/2022] Open
Abstract
In industrial animal production, breeding strategies are essential to produce offspring of better quality and vitality. It is also known that host microbiome has a bearing on its health. Here, we report for the first time the influence of crossbreeding strategy, inbreeding or outbreeding, on the buccal and intestinal bacterial communities in female Nile tilapia (Oreochromis niloticus). Crossbreeding was performed within a family and between different fish families to obtain the inbred and outbred study groups, respectively. The genetic relationship and structure analysis revealed significant genetic differentiation between the inbred and outbred groups. We also employed a 16S rRNA gene sequencing technique to understand the significant differences between the diversities of the bacterial communities of the inbred and outbred groups. The core microbiota composition in the mouth and the intestine was not affected by the crossbreeding strategy but their abundance varied between the two groups. Furthermore, opportunistic bacteria were abundant in the buccal cavity and intestine of the outbred group, whereas beneficial bacteria were abundant in the intestine of the inbred group. The present study indicates that crossbreeding can influence the abundance of beneficial bacteria, core microbiome and the inter-individual variation in the microbiome.
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Affiliation(s)
- Yousri Abdelhafiz
- Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway
| | | | - Simone Larger
- Unit of Computational Biology, Fondazione Edmund Mach, San Michele all'Adige, Italy
| | - Davide Albanese
- Unit of Computational Biology, Fondazione Edmund Mach, San Michele all'Adige, Italy
| | - Claudio Donati
- Unit of Computational Biology, Fondazione Edmund Mach, San Michele all'Adige, Italy
| | - Omid Jafari
- Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway.,International Sturgeon Research Institute, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization, Rasht, Iran
| | | | - Viswanath Kiron
- Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway
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20
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Dadousis C, Somavilla A, Ilska JJ, Johnsson M, Batista L, Mellanby RJ, Headon D, Gottardo P, Whalen A, Wilson D, Dunn IC, Gorjanc G, Kranis A, Hickey JM. A genome-wide association analysis for body weight at 35 days measured on 137,343 broiler chickens. Genet Sel Evol 2021; 53:70. [PMID: 34496773 PMCID: PMC8424881 DOI: 10.1186/s12711-021-00663-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 08/23/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Body weight (BW) is an economically important trait in the broiler (meat-type chickens) industry. Under the assumption of polygenicity, a "large" number of genes with "small" effects is expected to control BW. To detect such effects, a large sample size is required in genome-wide association studies (GWAS). Our objective was to conduct a GWAS for BW measured at 35 days of age with a large sample size. METHODS The GWAS included 137,343 broilers spanning 15 pedigree generations and 392,295 imputed single nucleotide polymorphisms (SNPs). A false discovery rate of 1% was adopted to account for multiple testing when declaring significant SNPs. A Bayesian ridge regression model was implemented, using AlphaBayes, to estimate the contribution to the total genetic variance of each region harbouring significant SNPs (1 Mb up/downstream) and the combined regions harbouring non-significant SNPs. RESULTS GWAS revealed 25 genomic regions harbouring 96 significant SNPs on 13 Gallus gallus autosomes (GGA1 to 4, 8, 10 to 15, 19 and 27), with the strongest associations on GGA4 at 65.67-66.31 Mb (Galgal4 assembly). The association of these regions points to several strong candidate genes including: (i) growth factors (GGA1, 4, 8, 13 and 14); (ii) leptin receptor overlapping transcript (LEPROT)/leptin receptor (LEPR) locus (GGA8), and the STAT3/STAT5B locus (GGA27), in connection with the JAK/STAT signalling pathway; (iii) T-box gene (TBX3/TBX5) on GGA15 and CHST11 (GGA1), which are both related to heart/skeleton development); and (iv) PLAG1 (GGA2). Combined together, these 25 genomic regions explained ~ 30% of the total genetic variance. The region harbouring significant SNPs that explained the largest portion of the total genetic variance (4.37%) was on GGA4 (~ 65.67-66.31 Mb). CONCLUSIONS To the best of our knowledge, this is the largest GWAS that has been conducted for BW in chicken to date. In spite of the identified regions, which showed a strong association with BW, the high proportion of genetic variance attributed to regions harbouring non-significant SNPs supports the hypothesis that the genetic architecture of BW35 is polygenic and complex. Our results also suggest that a large sample size will be required for future GWAS of BW35.
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Affiliation(s)
| | | | - Joanna J. Ilska
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - Martin Johnsson
- The Roslin Institute, University of Edinburgh, Midlothian, UK
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Lorena Batista
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | | | - Denis Headon
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - Paolo Gottardo
- Italian Brown Breeders Association, Loc. Ferlina 204, 37012 Bussolengo, Italy
| | - Andrew Whalen
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - David Wilson
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - Ian C. Dunn
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - Gregor Gorjanc
- The Roslin Institute, University of Edinburgh, Midlothian, UK
| | - Andreas Kranis
- The Roslin Institute, University of Edinburgh, Midlothian, UK
- Aviagen Ltd, Midlothian, UK
| | - John M. Hickey
- The Roslin Institute, University of Edinburgh, Midlothian, UK
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21
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Brito LF, Bedere N, Douhard F, Oliveira HR, Arnal M, Peñagaricano F, Schinckel AP, Baes CF, Miglior F. Review: Genetic selection of high-yielding dairy cattle toward sustainable farming systems in a rapidly changing world. Animal 2021; 15 Suppl 1:100292. [PMID: 34294547 DOI: 10.1016/j.animal.2021.100292] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 11/28/2022] Open
Abstract
The massive improvement in food production, as a result of effective genetic selection combined with advancements in farming practices, has been one of the greatest achievements of modern agriculture. For instance, the dairy cattle industry has more than doubled milk production over the past five decades, while the total number of cows has been reduced dramatically. This was achieved mainly through the intensification of production systems, direct genetic selection for milk yield and a limited number of related traits, and the use of modern technologies (e.g., artificial insemination and genomic selection). Despite the great betterment in production efficiency, strong drawbacks have occurred along the way. First, across-breed genetic diversity reduced dramatically, with the worldwide use of few common dairy breeds, as well as a substantial reduction in within-breed genetic diversity. Intensive selection for milk yield has also resulted in unfavorable genetic responses for traits related to fertility, health, longevity, and environmental sensitivity. Moving forward, the dairy industry needs to continue refining the current selection indexes and breeding goals to put greater emphasis on traits related to animal welfare, health, longevity, environmental efficiency (e.g., methane emission and feed efficiency), and overall resilience. This needs to be done through the definition of criteria (traits) that (a) represent well the biological mechanisms underlying the respective phenotypes, (b) are heritable, and (c) can be cost-effectively measured in a large number of animals and as early in life as possible. The long-term sustainability of the dairy cattle industry will also require diversification of production systems, with greater investments in the development of genetic resources that are resilient to perturbations occurring in specific farming systems with lesser control over the environment (e.g., organic, agroecological, and pasture-based, mountain-grazing farming systems). The conservation, genetic improvement, and use of local breeds should be integrated into the modern dairy cattle industry and greater care should be taken to avoid further genetic diversity losses in dairy cattle populations. In this review, we acknowledge the genetic progress achieved in high-yielding dairy cattle, closely related to dairy farm intensification, that reaches its limits. We discuss key points that need to be addressed toward the development of a robust and long-term sustainable dairy industry that maximize animal welfare (fundamental needs of individual animals and positive welfare) and productive efficiency, while also minimizing the environmental footprint, inputs required, and sensitivity to external factors.
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Affiliation(s)
- L F Brito
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN 47 907, USA.
| | - N Bedere
- INRAE, Institut Agro, PEGASE, 35 590 Saint-Gilles, France
| | - F Douhard
- GenPhySE, Université de Toulouse, INRAE, ENVT, F-31326 Castanet Tolosan, France
| | - H R Oliveira
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN 47 907, USA; Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1, Canada
| | - M Arnal
- GenPhySE, Université de Toulouse, INRAE, ENVT, F-31326 Castanet Tolosan, France; Institut de l'Elevage, Chemin de Borde Rouge, 31 326 Castanet-Tolosan cedex, France
| | - F Peñagaricano
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53 706, USA
| | - A P Schinckel
- Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, IN 47 907, USA
| | - C F Baes
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1, Canada; Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern 3 000, Switzerland
| | - F Miglior
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, Ontario N1G 2W1, Canada
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22
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Han J, Gondro C, Reid K, Steibel JP. Heuristic hyperparameter optimization of deep learning models for genomic prediction. G3-GENES GENOMES GENETICS 2021; 11:6129776. [PMID: 33993261 PMCID: PMC8495939 DOI: 10.1093/g3journal/jkab032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 01/23/2021] [Indexed: 11/17/2022]
Abstract
There is a growing interest among quantitative geneticists and animal breeders in the use of deep learning (DL) for genomic prediction. However, the performance of DL is affected by hyperparameters that are typically manually set by users. These hyperparameters do not simply specify the architecture of the model; they are also critical for the efficacy of the optimization and model-fitting process. To date, most DL approaches used for genomic prediction have concentrated on identifying suitable hyperparameters by exploring discrete options from a subset of the hyperparameter space. Enlarging the hyperparameter optimization search space with continuous hyperparameters is a daunting combinatorial problem. To deal with this problem, we propose using differential evolution (DE) to perform an efficient search of arbitrarily complex hyperparameter spaces in DL models, and we apply this to the specific case of genomic prediction of livestock phenotypes. This approach was evaluated on two pig and cattle datasets with real genotypes and simulated phenotypes (N = 7,539 animals and M = 48,541 markers) and one real dataset (N = 910 individuals and M = 28,916 markers). Hyperparameters were evaluated using cross-validation. We compared the predictive performance of DL models using hyperparameters optimized by DE against DL models with “best practice” hyperparameters selected from published studies and baseline DL models with randomly specified hyperparameters. Optimized models using DE showed a clear improvement in predictive performance across all three datasets. DE optimized hyperparameters also resulted in DL models with less overfitting and less variation in predictive performance over repeated retraining compared to non-optimized DL models.
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Affiliation(s)
- Junjie Han
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA.,Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Cedric Gondro
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
| | - Kenneth Reid
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA.,Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
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23
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Flores-Encinas LA, Rodríguez-Almeida FA, Felix-Portillo M, Jahuey-Martínez FJ, Martínez-Quintana JA. A variant associated to IGF-1 mRNA and protein expression in sheep. Anim Biotechnol 2021; 33:1086-1094. [PMID: 33428515 DOI: 10.1080/10495398.2020.1869561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The insulin-like growth factor-1 (IGF-1), a key hormone in muscle development was investigated for single-nucleotide polymorphisms (SNPs) upstream of the IGF-1 gene and their effects upon its cognate mRNA and hormone levels in sheep. A 70 d feeding trial was conducted with 22 F1 (Dorper × Pelibuey) lambs, individually allocated and fed a diet with a forage-to-concentrate ratio of 36:64 and 17% crude protein. Sequence analyses of 265 bp upstream the IGF-1 gene revealed the variant NC_040254.1:g.[184028491G > C;184028493G > A]. These SNPs generate alleles A and B, with frequencies of 0.66 and 0.34 in F1 lambs and of 0.73 and 0.27 in 81 pure Dorper lambs, respectively. Females were grouped by genotype AA, AB and BB (n = 3). IGF-1 hormone concentrations at 14, 42 and 70 d were higher (p < 0.05) in AA lambs compared to AB + BB lambs. The IGF-1 mRNA level was 2.6-fold higher in AA animals (n = 5, p < 0.05) than in AB + BB lambs (n = 7). A DNA binding site for the Inhibitor of Growth family member 4 (ING4) was found in allele B but not in allele A, which could explain the lower mRNA and hormone expression levels for AB + BB animals. The variant reported here appears to function as an eQTL with a negative effect on the level of IGF-1.
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Affiliation(s)
- Luis A Flores-Encinas
- Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Chihuahua, Mexico
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Fessenden B, Weigel DJ, Osterstock J, Galligan DT, Di Croce F. Validation of genomic predictions for a lifetime merit selection index for the US dairy industry. J Dairy Sci 2020; 103:10414-10428. [PMID: 32921463 DOI: 10.3168/jds.2020-18502] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 06/26/2020] [Indexed: 12/12/2022]
Abstract
Selection indices are a critical component of many breeding programs. A common purpose of a selection index is to predict an animal's genetic potential for total economic merit. The objective of this study was to evaluate retrospectively whether a specific selection index comprising genomically-enhanced predicted transmitting abilities had the ability to predict observed lifetime profit in US Holstein animals. The selection index evaluated was dairy wellness profit (DWP$). In total, 2,185 animals were included in this study. Index values were used to rank and assign animals to quartiles (genetic groups: worst 25%, 26-50%, 51-75%, and best 25%). Generalized linear mixed effects models were applied to estimate the associations between index quartile and defined economic outcomes. Similar analyses were conducted to estimate associations between index quartile and observed phenotype to characterize the extent to which profitability outcomes were driven by economically relevant production and health traits. Differences in lifetime profit and annuity value between the best and worst genetic groups for DWP$ were $811 (±297) and $232 (±88), respectively. Significant differences were also observed between top and bottom quartiles for milk production (8,077 kg), fat production (336 kg), protein production (264 kg), live calves (0.5), time spent in the lactating herd (6.6 mo), and cow mortality (8.4%). Additionally, differences in disease incidence were significant between the best and worst DWP$ quartiles for metritis (5.2%), mastitis (14.9%), and lameness (15.9%). The observed results of this study demonstrated the ability of DWP$ predictions to predict lifetime profitability of Holstein animals and its potential utility as a tool to guide selection and breeding programs. Improving DWP$ through genetic selection, when combined with good management practices, provides an opportunity for dairy producers to improve overall herd profitability.
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Affiliation(s)
| | - Daniel J Weigel
- Zoetis Outcomes Research, 333 Portage Street, Kalamazoo, MI 49007
| | | | - David T Galligan
- University of Pennsylvania School of Veterinary Medicine, New Bolton Center 382 West Street Road, Kennett Square, PA 19348
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25
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Plate M, Bernstein R, Hoppe A, Bienefeld K. Long-Term Evaluation of Breeding Scheme Alternatives for Endangered Honeybee Subspecies. INSECTS 2020; 11:insects11070404. [PMID: 32629773 PMCID: PMC7412524 DOI: 10.3390/insects11070404] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/12/2020] [Accepted: 06/25/2020] [Indexed: 11/16/2022]
Abstract
Modern breeding structures are emerging for European honeybee populations. However, while genetic evaluations of honeybees are becoming increasingly well understood, little is known about how selection decisions shape the populations' genetic structures. We performed simulations evaluating 100 different selection schemes, defined by selection rates for dams and sires, in populations of 200, 500, or 1000 colonies per year and considering four different quantitative traits, reflecting different genetic parameters and numbers of influential loci. Focusing on sustainability, we evaluated genetic progress over 100 years and related it to inbreeding developments. While all populations allowed for sustainable breeding with generational inbreeding rates below 1% per generation, optimal selection rates differed and sustainable selection was harder to achieve in smaller populations and for stronger negative correlations of maternal and direct effects in the selection trait. In small populations, a third or a fourth of all candidate queens should be selected as dams, whereas this number declined to a sixth for larger population sizes. Furthermore, our simulations indicated that, particularly in small populations, as many sires as possible should be provided. We conclude that carefully applied breeding provides good prospects for currently endangered honeybee subspecies, since sustainable genetic progress improves their attractiveness to beekeepers.
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Affiliation(s)
- Manuel Plate
- Institute for Bee Research, Friedrich-Engels Str. 32, 16540 Hohen Neuendorf, Germany; (R.B.); (A.H.); (K.B.)
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt University of Berlin, 10099 Berlin, Germany
- Correspondence:
| | - Richard Bernstein
- Institute for Bee Research, Friedrich-Engels Str. 32, 16540 Hohen Neuendorf, Germany; (R.B.); (A.H.); (K.B.)
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt University of Berlin, 10099 Berlin, Germany
| | - Andreas Hoppe
- Institute for Bee Research, Friedrich-Engels Str. 32, 16540 Hohen Neuendorf, Germany; (R.B.); (A.H.); (K.B.)
| | - Kaspar Bienefeld
- Institute for Bee Research, Friedrich-Engels Str. 32, 16540 Hohen Neuendorf, Germany; (R.B.); (A.H.); (K.B.)
- Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt University of Berlin, 10099 Berlin, Germany
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Tiezzi F, Brito LF, Howard J, Huang YJ, Gray K, Schwab C, Fix J, Maltecca C. Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs. Front Genet 2020; 11:629. [PMID: 32695139 PMCID: PMC7338773 DOI: 10.3389/fgene.2020.00629] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/26/2020] [Indexed: 12/12/2022] Open
Abstract
Improving swine climatic resilience through genomic selection has the potential to minimize welfare issues and increase the industry profitability. The main objective of this study was to investigate the genetic and genomic determinism of tolerance to heat stress in four independent purebred populations of swine. Three female reproductive traits were investigated: total number of piglets born (TNB), number of piglets born alive (NBA) and average birth weight (ABW). More than 80,000 phenotypic and 12,000 genotyped individuals were included in this study. Genomic random-regression models were fitted regressing the phenotypes of interest on a set of 95 environmental covariates extracted from public weather station records. The models yielded estimates of (genomic) reactions norms for individual pigs, as indicator of heat tolerance. Heat tolerance is a heritable trait, although the heritabilities are larger under comfortable than heat-stress conditions (larger than 0.05 vs. 0.02 for TNB; 0.10 vs. 0.05 for NBA; larger than 0.20 vs. 0.10 for ABW). TNB showed the lowest genetic correlation (-38%) between divergent climatic conditions, being the trait with the strongest impact of genotype by environment interaction, while NBA and ABW showed values slightly negative or equal to zero reporting a milder impact of the genotype by environment interaction. After estimating genetic parameters, a genome-wide association study was performed based on the single-step GBLUP method. Heat tolerance was observed to be a highly polygenic trait. Multiple and non-overlapping genomic regions were identified for each trait based on the genomic breeding values for reproductive performance under comfortable or heat stress conditions. Relevant regions were found on chromosomes (SSC) 1, 3, 5, 6, 9, 11, and 12, although there were important regions across all autosomal chromosomes. The genomic region located on SSC9 appears to be of particular interest since it was identified for two traits (TNB and NBA) and in two independent populations. Heat tolerance based on reproductive performance indicators is a heritable trait and genetic progress for heat tolerance can be achieved through genetic or genomic selection. Various genomic regions and candidate genes with important biological functions were identified, which will be of great value for future functional genomic studies.
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Affiliation(s)
- Francesco Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC, United States
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Jeremy Howard
- Smithfield Premium Genetics, Rose Hill, NC, United States
| | - Yi Jian Huang
- Smithfield Premium Genetics, Rose Hill, NC, United States
| | - Kent Gray
- Smithfield Premium Genetics, Rose Hill, NC, United States
| | | | - Justin Fix
- The Maschhoffs LLC, Carlyle, IL, United States
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC, United States
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27
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Zhang H, Liang Q, Wang N, Wang Q, Leng L, Mao J, Wang Y, Wang S, Zhang J, Liang H, Zhou X, Li Y, Cao Z, Luan P, Wang Z, Yuan H, Wang Z, Zhou X, Lamont SJ, Da Y, Li R, Tian S, Du Z, Li H. Microevolutionary Dynamics of Chicken Genomes under Divergent Selection for Adiposity. iScience 2020; 23:101193. [PMID: 32554187 PMCID: PMC7303556 DOI: 10.1016/j.isci.2020.101193] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 04/19/2020] [Accepted: 05/19/2020] [Indexed: 01/01/2023] Open
Abstract
Decades of artificial selection have significantly improved performance and efficiency of animal production systems. However, little is known about the microevolution of genomes due to intensive breeding. Using whole-genome sequencing, we document dynamic changes of chicken genomes under divergent selection on adiposity over 19 generations. Directional selection reduced within-line but increased between-line genomic differences. We observed that artificial selection tended to result in recruitment of preexisting variations of genes related to adipose tissue growth. In addition, novel mutations contributed to divergence of phenotypes under selection but contributed significantly less than preexisting genomic variants. Integration of 15 generations genome sequencing, genome-wide association study, and multi-omics data further identified that genes involved in signaling pathways important to adipogenesis, such as autophagy and lysosome (URI1, MBL2), neural system (CHAT), and endocrine (PCSK1) pathways, were under strong selection. Our study provides insights into the microevolutionary dynamics of domestic animal genomes under artificial selection.
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Affiliation(s)
- Hui Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Qiqi Liang
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Ning Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Qigui Wang
- Chongqing Academy of Animal Science, Chongqing 402460, P. R. China
| | - Li Leng
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Jie Mao
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Yuxiang Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Jiyang Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Hao Liang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Xun Zhou
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Yumao Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhiping Cao
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Peng Luan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhipeng Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Hui Yuan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhiquan Wang
- Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2C8, Canada
| | - Xuming Zhou
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, P. R. China
| | - Susan J Lamont
- Department of Animal Science, Iowa State University, Ames 50011, USA
| | - Yang Da
- Department of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA
| | - Ruiqiang Li
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Shilin Tian
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China.
| | - Zhiqiang Du
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
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28
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Alexandre PA, Reverter A, Lehnert SA, Porto-Neto LR, Dominik S. In silico validation of pooled genotyping strategies for genomic evaluation in Angus cattle. J Anim Sci 2020; 98:5840748. [PMID: 32428206 DOI: 10.1093/jas/skaa170] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 05/14/2020] [Indexed: 01/21/2023] Open
Abstract
In this study, we aimed to assess the value of genotyping DNA pools as a strategy to generate accurate and cost-effective genomic estimated breeding values (GEBV) of sires in multi-sire mating systems. In order to do that, we used phenotypic records of 2,436 Australian Angus cattle from 174 sires, including yearling weight (YWT; N = 1,589 records), coat score (COAT; N = 2,026 records), and Meat Standards Australia marbling score (MARB; N = 1,304 records). Phenotypes were adjusted for fixed effects and age at measurement and pools of 2, 5, 10, 15, 20, and 25 animals were explored. Pools were created either by phenotype or at random. When pools were created at random, 10 replicates were examined to provide a measure of sampling variation. The relative accuracy of each pooling strategy was measured by the Pearson correlation coefficient between the sire's GEBV with pooled progeny and the GEBV using individually genotyped progeny. Random pools allow the computation of sire GEBV that are, on average, moderately correlated (i.e., r > 0.5 at pool sizes [PS] ≤ 10) with those obtained without pooling. However, for pools assigned at random, the difference between the best and the worst relative accuracy obtained out of the 10 replicates was as high as 0.41 for YWT, 0.36 for COAT, and 0.61 for MARB. This uncertainty associated with the relative accuracy of GEBV makes randomly assigning animals to pools an unreliable approach. In contrast, pooling by phenotype allowed the estimation of sires' GEBV with a relative accuracy ≥ 0.9 at PS < 10 for all three phenotypes. Moreover, even with larger PS, the lowest relative accuracy obtained was 0.88 (YWT, PS = 20). In agreement with results using simulated data, we conclude that pooling by phenotype is a robust approach to implementing genomic evaluation using commercial herd data, and PS larger than 10 individuals can be considered.
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Affiliation(s)
- Pâmela A Alexandre
- Commonwealth Scientific and Industrial Research Organization Agriculture and Food, Brisbane, QLD, Australia
| | - Antonio Reverter
- Commonwealth Scientific and Industrial Research Organization Agriculture and Food, Brisbane, QLD, Australia
| | - Sigrid A Lehnert
- Commonwealth Scientific and Industrial Research Organization Agriculture and Food, Brisbane, QLD, Australia
| | - Laercio R Porto-Neto
- Commonwealth Scientific and Industrial Research Organization Agriculture and Food, Brisbane, QLD, Australia
| | - Sonja Dominik
- Commonwealth Scientific and Industrial Research Organization Agriculture and Food, Armidale, NSW, Australia
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29
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Houston RD, Bean TP, Macqueen DJ, Gundappa MK, Jin YH, Jenkins TL, Selly SLC, Martin SAM, Stevens JR, Santos EM, Davie A, Robledo D. Harnessing genomics to fast-track genetic improvement in aquaculture. Nat Rev Genet 2020; 21:389-409. [PMID: 32300217 DOI: 10.1038/s41576-020-0227-y] [Citation(s) in RCA: 125] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2020] [Indexed: 12/12/2022]
Abstract
Aquaculture is the fastest-growing farmed food sector and will soon become the primary source of fish and shellfish for human diets. In contrast to crop and livestock production, aquaculture production is derived from numerous, exceptionally diverse species that are typically in the early stages of domestication. Genetic improvement of production traits via well-designed, managed breeding programmes has great potential to help meet the rising seafood demand driven by human population growth. Supported by continuous advances in sequencing and bioinformatics, genomics is increasingly being applied across the broad range of aquaculture species and at all stages of the domestication process to optimize selective breeding. In the future, combining genomic selection with biotechnological innovations, such as genome editing and surrogate broodstock technologies, may further expedite genetic improvement in aquaculture.
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Affiliation(s)
- Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK.
| | - Tim P Bean
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK
| | - Daniel J Macqueen
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK
| | - Manu Kumar Gundappa
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK
| | - Ye Hwa Jin
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK
| | - Tom L Jenkins
- Sustainable Aquaculture Futures, Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | | | | | - Jamie R Stevens
- Sustainable Aquaculture Futures, Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Eduarda M Santos
- Sustainable Aquaculture Futures, Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Andrew Davie
- Institute of Aquaculture, University of Stirling, Stirling, UK
| | - Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, UK
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30
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The Impact of Non-additive Effects on the Genetic Correlation Between Populations. G3-GENES GENOMES GENETICS 2020; 10:783-795. [PMID: 31857332 PMCID: PMC7003072 DOI: 10.1534/g3.119.400663] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Average effects of alleles can show considerable differences between populations. The magnitude of these differences can be measured by the additive genetic correlation between populations ([Formula: see text]). This [Formula: see text] can be lower than one due to the presence of non-additive genetic effects together with differences in allele frequencies between populations. However, the relationship between the nature of non-additive effects, differences in allele frequencies, and the value of [Formula: see text] remains unclear, and was therefore the focus of this study. We simulated genotype data of two populations that have diverged under drift only, or under drift and selection, and we simulated traits where the genetic model and magnitude of non-additive effects were varied. Results showed that larger differences in allele frequencies and larger non-additive effects resulted in lower values of [Formula: see text] In addition, we found that with epistasis, [Formula: see text] decreases with an increase of the number of interactions per locus. For both dominance and epistasis, we found that, when non-additive effects became extremely large, [Formula: see text] had a lower bound that was determined by the type of inter-allelic interaction, and the difference in allele frequencies between populations. Given that dominance variance is usually small, our results show that it is unlikely that true [Formula: see text] values lower than 0.80 are due to dominance effects alone. With realistic levels of epistasis, [Formula: see text] dropped as low as 0.45. These results may contribute to the understanding of differences in genetic expression of complex traits between populations, and may help in explaining the inefficiency of genomic trait prediction across populations.
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31
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Koltes JE, Cole JB, Clemmens R, Dilger RN, Kramer LM, Lunney JK, McCue ME, McKay SD, Mateescu RG, Murdoch BM, Reuter R, Rexroad CE, Rosa GJM, Serão NVL, White SN, Woodward-Greene MJ, Worku M, Zhang H, Reecy JM. A Vision for Development and Utilization of High-Throughput Phenotyping and Big Data Analytics in Livestock. Front Genet 2019; 10:1197. [PMID: 31921279 PMCID: PMC6934059 DOI: 10.3389/fgene.2019.01197] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/29/2019] [Indexed: 01/28/2023] Open
Abstract
Automated high-throughput phenotyping with sensors, imaging, and other on-farm technologies has resulted in a flood of data that are largely under-utilized. Drastic cost reductions in sequencing and other omics technology have also facilitated the ability for deep phenotyping of livestock at the molecular level. These advances have brought the animal sciences to a cross-roads in data science where increased training is needed to manage, record, and analyze data to generate knowledge and advances in Agriscience related disciplines. This paper describes the opportunities and challenges in using high-throughput phenotyping, “big data,” analytics, and related technologies in the livestock industry based on discussions at the Livestock High-Throughput Phenotyping and Big Data Analytics meeting, held in November 2017 (see: https://www.animalgenome.org/bioinfo/community/workshops/2017/). Critical needs for investments in infrastructure for people (e.g., “big data” training), data (e.g., data transfer, management, and analytics), and technology (e.g., development of low cost sensors) were defined by this group. Though some subgroups of animal science have extensive experience in predictive modeling, cross-training in computer science, statistics, and related disciplines are needed to use big data for diverse applications in the field. Extensive opportunities exist for public and private entities to harness big data to develop valuable research knowledge and products to the benefit of society under the increased demands for food in a rapidly growing population.
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Affiliation(s)
- James E Koltes
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - John B Cole
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, United States
| | - Roxanne Clemmens
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Ryan N Dilger
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Luke M Kramer
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Joan K Lunney
- Animal Parasitic Diseases Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Molly E McCue
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Stephanie D McKay
- Department of Animal and Veterinary Sciences, College of Agriculture and Life Sciences, University of Vermont, Burlington, VT, United States
| | - Raluca G Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Brenda M Murdoch
- Department of Animal and Veterinary Science, University of Idaho, Moscow, ID, United States
| | - Ryan Reuter
- Department of Animal and Food Sciences, College of Agricultural Sciences and Natural Resources, Oklahoma State University, Stillwater, OK, United States
| | - Caird E Rexroad
- Agricultural Research Service, United States Department of Agriculture, Washington D.C., DC, United States
| | - Guilherme J M Rosa
- Department of Dairy Science, University of Wisconsin-Madison, Madison, WI, United States
| | - Nick V L Serão
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Stephen N White
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA, United States.,Department of Veterinary Microbiology and Pathology, College of Veterinary Medicine, Washington State University, Pullman, WA, United States.,Center for Reproductive Biology, College of Veterinary Medicine, Washington State University, Pullman, WA, United States
| | - M Jennifer Woodward-Greene
- Agricultural Research Service, United States Department of Agriculture, Washington D.C., DC, United States
| | - Millie Worku
- Department of Animal Sciences, North Carolina Agricultural and Technical State University, Greensboro, NC, United States
| | - Hongwei Zhang
- Department of Electrical and Computer Engineering, College of Engineering, Iowa State University, Ames, IA, United States
| | - James M Reecy
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
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32
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Haas R, Horev G, Lipkin E, Kesten I, Portnoy M, Buhnik-Rosenblau K, Soller M, Kashi Y. Mapping Ethanol Tolerance in Budding Yeast Reveals High Genetic Variation in a Wild Isolate. Front Genet 2019; 10:998. [PMID: 31824552 PMCID: PMC6879558 DOI: 10.3389/fgene.2019.00998] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 09/18/2019] [Indexed: 01/08/2023] Open
Abstract
Ethanol tolerance, a polygenic trait of the yeast Saccharomyces cerevisiae, is the primary factor determining industrial bioethanol productivity. Until now, genomic elements affecting ethanol tolerance have been mapped only at low resolution, hindering their identification. Here, we explore the genetic architecture of ethanol tolerance, in the F6 generation of an Advanced Intercrossed Line (AIL) mapping population between two phylogenetically distinct, but phenotypically similar, S. cerevisiae strains (a common laboratory strain and a wild strain isolated from nature). Under ethanol stress, 51 quantitative trait loci (QTLs) affecting growth and 96 QTLs affecting survival, most of them novel, were identified, with high resolution, in some cases to single genes, using a High-Resolution Mapping Package of methodologies that provided high power and high resolution. We confirmed our results experimentally by showing the effects of the novel mapped genes: MOG1, MGS1, and YJR154W. The mapped QTLs explained 34% of phenotypic variation for growth and 72% for survival. High statistical power provided by our analysis allowed detection of many loci with small, but mappable effects, uncovering a novel “quasi-infinitesimal” genetic architecture. These results are striking demonstration of tremendous amounts of hidden genetic variation exposed in crosses between phylogenetically separated strains with similar phenotypes; as opposed to the more common design where strains with distinct phenotypes are crossed. Our findings suggest that ethanol tolerance is under natural evolutionary fitness-selection for an optimum phenotype that would tend to eliminate alleles of large effect. The study provides a platform for development of superior ethanol-tolerant strains using genome editing or selection.
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Affiliation(s)
- Roni Haas
- Faculty of Biotechnology and Food Engineering, Technion, Haifa, Israel
| | - Guy Horev
- Lorey I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion-Israel Institute of Technology, Haifa, Israel
| | - Ehud Lipkin
- Department of Genetics, Silberman Life Sciences Institute, The Hebrew University of Edmond Safra Campus, Jerusalem, Israel
| | - Inbar Kesten
- Faculty of Biotechnology and Food Engineering, Technion, Haifa, Israel
| | - Maya Portnoy
- Faculty of Biotechnology and Food Engineering, Technion, Haifa, Israel
| | | | - Morris Soller
- Department of Genetics, Silberman Life Sciences Institute, The Hebrew University of Edmond Safra Campus, Jerusalem, Israel
| | - Yechezkel Kashi
- Faculty of Biotechnology and Food Engineering, Technion, Haifa, Israel
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Mulder HA, Lee SH, Clark S, Hayes BJ, van der Werf JHJ. The Impact of Genomic and Traditional Selection on the Contribution of Mutational Variance to Long-Term Selection Response and Genetic Variance. Genetics 2019; 213:361-378. [PMID: 31431471 PMCID: PMC6781905 DOI: 10.1534/genetics.119.302336] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 07/19/2019] [Indexed: 01/23/2023] Open
Abstract
De novo mutations (DNM) create new genetic variance and are an important driver for long-term selection response. We hypothesized that genomic selection exploits mutational variance less than traditional selection methods such as mass selection or selection on pedigree-based breeding values, because DNM in selection candidates are not captured when the selection candidates' own phenotype is not used in genomic selection, DNM are not on SNP chips and DNM are not in linkage disequilibrium with the SNP on the chip. We tested this hypothesis with Monte Carlo simulation. From whole-genome sequence data, a subset of ∼300,000 variants was used that served as putative markers, quantitative trait loci or DNM. We simulated 20 generations with truncation selection based on breeding values from genomic best linear unbiased prediction without (GBLUP_no_OP) or with own phenotype (GBLUP_OP), pedigree-based BLUP without (BLUP_no_OP) or with own phenotype (BLUP_OP), or directly on phenotype. GBLUP_OP was the best strategy in exploiting mutational variance, while GBLUP_no_OP and BLUP_no_OP were the worst in exploiting mutational variance. The crucial element is that GBLUP_no_OP and BLUP_no_OP puts no selection pressure on DNM in selection candidates. Genetic variance decreased faster with GBLUP_no_OP and GBLUP_OP than with BLUP_no_OP, BLUP_OP or mass selection. The distribution of mutational effects, mutational variance, number of DNM per individual and nonadditivity had a large impact on mutational selection response and mutational genetic variance, but not on ranking of selection strategies. We advocate that more sustainable genomic selection strategies are required to optimize long-term selection response and to maintain genetic diversity.
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Affiliation(s)
- Herman A Mulder
- Wageningen University & Research Animal Breeding and Genomics, 6700 AH Wageningen, The Netherlands
| | - Sang Hong Lee
- School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, South Australia 5000, Australia
| | - Sam Clark
- School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia
| | - Ben J Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia 4067, Queensland, Australia
| | - Julius H J van der Werf
- School of Environmental and Rural Science, University of New England, Armidale, New South Wales 2351, Australia
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Sella G, Barton NH. Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies. Annu Rev Genomics Hum Genet 2019; 20:461-493. [DOI: 10.1146/annurev-genom-083115-022316] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Many traits of interest are highly heritable and genetically complex, meaning that much of the variation they exhibit arises from differences at numerous loci in the genome. Complex traits and their evolution have been studied for more than a century, but only in the last decade have genome-wide association studies (GWASs) in humans begun to reveal their genetic basis. Here, we bring these threads of research together to ask how findings from GWASs can further our understanding of the processes that give rise to heritable variation in complex traits and of the genetic basis of complex trait evolution in response to changing selection pressures (i.e., of polygenic adaptation). Conversely, we ask how evolutionary thinking helps us to interpret findings from GWASs and informs related efforts of practical importance.
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Affiliation(s)
- Guy Sella
- Department of Biological Sciences, Columbia University, New York, NY 10027, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
- Program for Mathematical Genomics, Columbia University, New York, NY 10032, USA
| | - Nicholas H. Barton
- Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria
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Giles T, Sakkas P, Belkhiri A, Barrow P, Kyriazakis I, Foster N. Differential immune response to Eimeria maxima infection in fast- and slow-growing broiler genotypes. Parasite Immunol 2019; 41:e12660. [PMID: 31230360 DOI: 10.1111/pim.12660] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 06/13/2019] [Accepted: 06/13/2019] [Indexed: 12/28/2022]
Abstract
Very little has been reported comparing resistance to coccidiosis in fast or slow growing broilers, the latter of which are becoming more prevalent in the broiler industry. We examined mRNA expression in the intestines of fast and slow growing broilers following Eimeria infection. We show that by day 13 post-infection (d pi) with 2500 or 7000 oocysts of Eimeria maxima, slower-growing (Ranger Classic) broilers significantly (P < 0.01) upregulated expression of proinflammatory cyclooxygenase genes (LTB4DH, PTSG1 and PTSG2) above that detected in fast growing (Ross 308) broilers. Expression of CD8α mRNA was downregulated in Ross 308 at day 6d pi with either 2500 or 7000 oocysts of E maxima (P < 0.05), compared to uninfected controls, but was not differentially expressed in Ranger Classic. CD4 genes were not differentially expressed in either chicken line infected with either infectious oocyst dose at d6 pi, compared to uninfected controls. However, at d13 pi, CD4 expression was significantly upregulated in both chicken lines infected with either infectious oocyst dose, compared to uninfected controls (P < 0.05) but this was significantly greater in Ranger Classic broilers compared to Ross 308 (P < 0.05). At d13 pi, expression of CD3 chains (required for T lymphocyte activation) was significantly increased in Ranger Classic compared to Ross 308, infected with either oocyst dose (P < 0.05-0.01). Expression of IL-2 and IL-15 mRNA, required for T lymphocyte proliferation was also significantly upregulated, or maintained longer, in Ranger Classic broilers compared to Ross 308. These differences in immune response to E maxima corresponded with a reduction in E maxima genome detected in the intestines of Ranger Classic compared to Ross 308.
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Affiliation(s)
- Tim Giles
- University of Nottingham, Sutton Bonington, UK
| | | | | | - Paul Barrow
- University of Nottingham, Sutton Bonington, UK
| | | | - Neil Foster
- University of Nottingham, Sutton Bonington, UK
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36
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We have entered the era of genome-edited farmed animals. Emerg Top Life Sci 2019; 3:645-649. [PMID: 33523167 DOI: 10.1042/etls20190057] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 06/17/2019] [Accepted: 07/01/2019] [Indexed: 11/17/2022]
Abstract
Genome editing technology provides a transformative approach to animal breeding. Otherwise difficult or impossible-to-access genetic variation can now be used in a given target population, with leading examples focussing on animal health and welfare. The race is on for the first food from genome-edited farm animals to reach the shops.
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37
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Schou MF, Hoffmann AA, Kristensen TN. Genetic correlations and their dependence on environmental similarity-Insights from livestock data. Evolution 2019; 73:1672-1678. [PMID: 31144765 DOI: 10.1111/evo.13762] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 05/11/2019] [Indexed: 11/27/2022]
Abstract
Genetic correlations for a trait across environments are predicted to decrease as environments diverge. However, estimates of genetic correlations from natural populations are typically defined across a limited environmental range and prone to very large standard errors, making it difficult to test this prediction. We address the importance of environmental distance on genetic correlations by employing data from domestic cattle in which abundant and accurate estimates are available from a wide range of environments. Three production traits related to milk yield show a clear decrease in genetic correlations with increasing environmental divergence. This pattern was also evident for growth traits and other yield traits but not for traits related to reproduction, morphology, physiology, or disease. We suspect that this reflects weaker selection on these latter trait classes compared to production traits, or alternatively the effects of selection are constrained by unfavorable genetic correlations between traits. The results support the notion that traits that historically have been under strong directional selection in a small range of frequently encountered environments will evolve high genetic correlations across these environments, while exposure to uncommon (and dissimilar) environments lead to a reranking of gene effects and a decrease in genetic correlations across environments.
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Affiliation(s)
- Mads F Schou
- Department of Chemistry and Bioscience, Aalborg University, DK-9220, Aalborg East, Denmark.,Department of Biology, Lund University, Lund, SE-22362, Sweden
| | - Ary A Hoffmann
- School of BioSciences, Bio21 Institute, The University of Melbourne, Melbourne, Victoria, Australia
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Plate M, Bernstein R, Hoppe A, Bienefeld K. Comparison of infinitesimal and finite locus models for long-term breeding simulations with direct and maternal effects at the example of honeybees. PLoS One 2019; 14:e0213270. [PMID: 30840680 PMCID: PMC6402681 DOI: 10.1371/journal.pone.0213270] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 02/19/2019] [Indexed: 01/01/2023] Open
Abstract
Stochastic simulation studies of animal breeding have mostly relied on either the infinitesimal genetic model or finite polygenic models. In this study, we investigated the long-term effects of the chosen model on honeybee breeding schemes. We implemented the infinitesimal model, as well as finite locus models, with 200 and 400 gene loci and simulated populations of 300 and 1000 colonies per year over the course of 100 years. The selection was of a directly and maternally influenced trait with maternal heritability of [Formula: see text], direct heritability of [Formula: see text], and a negative correlation between the effects of rmd = - 0.18. Another set of simulations was run with parameters [Formula: see text], [Formula: see text], and rmd = - 0.53. All models showed similar behavior for the first 20 years. Throughout the study, we observed a higher genetic gain in the direct than in the maternal effects and a smaller gain with a stronger negative covariance. In the long-term, however, only the infinitesimal model predicted sustainable linear genetic progress, while the finite locus models showed sublinear behavior and, after 100 years, only reached between 58% and 62% of the mean breeding values in the infinitesimal model. While the infinitesimal model suggested a reduction of genetic variance by 33% to 49% after 100 years, the finite locus models saw a more drastic loss of 76% to 92%. When designing sustainable breeding strategies, one should, therefore, not blindly trust the infinitesimal model as the predictions may be overly optimistic. Instead, the more conservative choice of the finite locus model should be favored.
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Affiliation(s)
- Manuel Plate
- Institute for Bee Research Hohen Neuendorf, Hohen Neuendorf, Germany
| | - Richard Bernstein
- Institute for Bee Research Hohen Neuendorf, Hohen Neuendorf, Germany
| | - Andreas Hoppe
- Institute for Bee Research Hohen Neuendorf, Hohen Neuendorf, Germany
| | - Kaspar Bienefeld
- Institute for Bee Research Hohen Neuendorf, Hohen Neuendorf, Germany
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39
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de Souza-Vilela J, Andrew NR, Ruhnke I. Insect protein in animal nutrition. ANIMAL PRODUCTION SCIENCE 2019. [DOI: 10.1071/an19255] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Global meat consumption per capita is expected to increase ~40% from 2019 to 2050. Over 30% of the total cropland worldwide is currently being used to produce either livestock and poultry feed or silage to meet the demand. One solution to reduce cropland use for animal feed is to increase the production of alternative protein sources. The primary protein sources for animal nutrition, including soybeans, peas and fish meal, are of increasing demand and are subsequently becoming more expensive, making their long-term use unsustainable. Insects such as the black soldier fly larvae (Hermetia illucens), crickets (Gryllus testaceus Walker) or mealworms (Tenebrio molitor) offer a viable addition to the feed sources and can provide valuable, high-quality energy, protein and fat to an animal’s diet. Here, we review the environmental benefits of insect feedstuff, current research findings related to the use of insects for animal nutrition, and outline additional products that can generate benefits to insect producers.
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40
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Differential gene response to coccidiosis in modern fast growing and slow growing broiler genotypes. Vet Parasitol 2018; 268:1-8. [PMID: 30981300 DOI: 10.1016/j.vetpar.2018.11.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 11/15/2018] [Accepted: 11/18/2018] [Indexed: 01/04/2023]
Abstract
We analysed intestinal tissues from groups of fast growing (Ross 308) broilers with natural or experimental coccidiosis, by genomic microarray. We identified genes that were differentially expressed (DE) in all groups and analysed expression of a panel of these, by qPCR, in Ross 308 and slow growing (Ranger classic) broilers, infected with 2500 or 7000 oocysts of Eimeria maxima for 6 or 13 days post-infection (dpi). Four genes (ADD3, MLLT10, NAV2 and PLXNA2) were upregulated (P <0.05) in Ross 308 but were not DE in Ranger Classic at 6 dpi with 2500 oocysts. Six genes (PTPRF, NCOR1, CSF3, SGK1, CROR and CD1B) were upregulated (P <0.05) in both Ross 308 and Ranger Classic infected with 2500 oocysts at 6 dpi but were not DE at 6 dpi with 7000 oocysts. At 13 dpi with 7000 oocysts, NAV2 and NCOR1 were upregulated in Ross 308 (P <0.05) and PTPRF was upregulated in both genotypes (P <0.05). DE of immune genes within the biomarker panel also occurred, with CSF3 upregulated in both genotypes infected with 2500 oocysts at 6 dpi and in Ranger Classic infected with 7000 oocysts, at 6 and 13 dpi (P <0.05). IL-22 was down-regulated in Ranger Classic infected with 2500 or 7000 oocysts at 6 dpi (P <0.05) but upregulated in both genotypes at 13 dpi (P <0.05). CD72 was down-regulated in Ranger Classic infected with 2500 oocysts at 6 dpi and with 7000 oocysts at 6 and 13 dpi (P <0.05). CD72 was upregulated in Ross 308 infected with 2500 oocysts at 6 dpi but was down-regulated following infection with 7000 oocysts at 13 dpi (P <0.05). In conclusion, differential gene expression occurs in fast and slow growing broiler genotypes with coccidiosis. In addition, we highlight a potential genetic biomarker panel for early diagnosis of coccidiosis.
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41
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Gorjanc G, Gaynor RC, Hickey JM. Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:1953-1966. [PMID: 29876589 PMCID: PMC6096640 DOI: 10.1007/s00122-018-3125-3] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 05/28/2018] [Indexed: 05/18/2023]
Abstract
Key message Optimal cross selection increases long-term genetic gain of two-part programs with rapid recurrent genomic selection. It achieves this by optimising efficiency of converting genetic diversity into genetic gain through reducing the loss of genetic diversity and reducing the drop of genomic prediction accuracy with rapid cycling. This study evaluates optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection. The two-part program reorganises a conventional breeding program into a population improvement component with recurrent genomic selection to increase the mean value of germplasm and a product development component with standard methods to develop new lines. Rapid recurrent genomic selection has a large potential, but is challenging due to genotyping costs or genetic drift. Here we simulate a wheat breeding program for 20 years and compare optimal cross selection against truncation selection in the population improvement component with one to six cycles per year. With truncation selection we crossed a small or a large number of parents. With optimal cross selection we jointly optimised selection, maintenance of genetic diversity, and cross allocation with AlphaMate program. The results show that the two-part program with optimal cross selection delivered the largest genetic gain that increased with the increasing number of cycles. With four cycles per year optimal cross selection had 78% (15%) higher long-term genetic gain than truncation selection with a small (large) number of parents. Higher genetic gain was achieved through higher efficiency of converting genetic diversity into genetic gain; optimal cross selection quadrupled (doubled) efficiency of truncation selection with a small (large) number of parents. Optimal cross selection also reduced the drop of genomic selection accuracy due to the drift between training and prediction populations. In conclusion optimal cross selection enables optimal management and exploitation of population improvement germplasm in two-part programs.
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Affiliation(s)
- Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK.
| | - R Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
| | - John M Hickey
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
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42
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Gorjanc G, Gaynor RC, Hickey JM. Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018. [PMID: 29876589 DOI: 10.1101/227215] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Key message Optimal cross selection increases long-term genetic gain of two-part programs with rapid recurrent genomic selection. It achieves this by optimising efficiency of converting genetic diversity into genetic gain through reducing the loss of genetic diversity and reducing the drop of genomic prediction accuracy with rapid cycling. This study evaluates optimal cross selection to balance selection and maintenance of genetic diversity in two-part plant breeding programs with rapid recurrent genomic selection. The two-part program reorganises a conventional breeding program into a population improvement component with recurrent genomic selection to increase the mean value of germplasm and a product development component with standard methods to develop new lines. Rapid recurrent genomic selection has a large potential, but is challenging due to genotyping costs or genetic drift. Here we simulate a wheat breeding program for 20 years and compare optimal cross selection against truncation selection in the population improvement component with one to six cycles per year. With truncation selection we crossed a small or a large number of parents. With optimal cross selection we jointly optimised selection, maintenance of genetic diversity, and cross allocation with AlphaMate program. The results show that the two-part program with optimal cross selection delivered the largest genetic gain that increased with the increasing number of cycles. With four cycles per year optimal cross selection had 78% (15%) higher long-term genetic gain than truncation selection with a small (large) number of parents. Higher genetic gain was achieved through higher efficiency of converting genetic diversity into genetic gain; optimal cross selection quadrupled (doubled) efficiency of truncation selection with a small (large) number of parents. Optimal cross selection also reduced the drop of genomic selection accuracy due to the drift between training and prediction populations. In conclusion optimal cross selection enables optimal management and exploitation of population improvement germplasm in two-part programs.
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Affiliation(s)
- Gregor Gorjanc
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK.
| | - R Chris Gaynor
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
| | - John M Hickey
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK
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43
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Bai Z, Ma W, Ma L, Velthof GL, Wei Z, Havlík P, Oenema O, Lee MRF, Zhang F. China's livestock transition: Driving forces, impacts, and consequences. SCIENCE ADVANCES 2018; 4:eaar8534. [PMID: 30035221 PMCID: PMC6051741 DOI: 10.1126/sciadv.aar8534] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2017] [Accepted: 06/12/2018] [Indexed: 05/21/2023]
Abstract
China's livestock industry has experienced a vast transition during the last three decades, with profound effects on domestic and global food provision, resource use, nitrogen and phosphorus losses, and greenhouse gas (GHG) emissions. We provide a comprehensive analysis of the driving forces around this transition and its national and global consequences. The number of livestock units (LUs) tripled in China in less than 30 years, mainly through the growth of landless industrial livestock production systems and the increase in monogastric livestock (from 62 to 74% of total LUs). Changes were fueled through increases in demand as well as, supply of new breeds, new technology, and government support. Production of animal source protein increased 4.9 times, nitrogen use efficiency at herd level tripled, and average feed use and GHG emissions per gram protein produced decreased by a factor of 2 between 1980 and 2010. In the same period, animal feed imports have increased 49 times, total ammonia and GHG emissions to the atmosphere doubled, and nitrogen losses to watercourses tripled. As a consequence, China's livestock transition has significant global impact. Forecasts for 2050, using the Shared Socio-economic Pathways scenarios, indicate major further changes in livestock production and impacts. On the basis of these possible trajectories, we suggest an alternative transition, which should be implemented by government, processing industries, consumers, and retailers. This new transition is targeted to increase production efficiency and environmental performance at system level, with coupling of crop-livestock production, whole chain manure management, and spatial planning as major components.
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Affiliation(s)
- Zhaohai Bai
- Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang 050021, Hebei, China
- Wageningen University, Department of Soil Quality, P.O. Box 47, 6700 AA Wageningen, Netherlands
| | - Wenqi Ma
- College of Resources and Environmental Sciences, Hebei Agricultural University, Baoding 071001, China
| | - Lin Ma
- Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang 050021, Hebei, China
- Corresponding author.
| | - Gerard L. Velthof
- Wageningen University, Environmental Research, P.O. Box 47, 6700 AA Wageningen, Netherlands
| | - Zhibiao Wei
- Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang 050021, Hebei, China
| | - Petr Havlík
- Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria
| | - Oene Oenema
- Wageningen University, Department of Soil Quality, P.O. Box 47, 6700 AA Wageningen, Netherlands
- Wageningen University, Environmental Research, P.O. Box 47, 6700 AA Wageningen, Netherlands
| | - Michael R. F. Lee
- Rothamsted Research, Sustainable Agriculture Sciences, North Wyke, Devon EX20 2SB, UK
- Bristol Veterinary School, Langford, Somerset BS40 5DU, UK
| | - Fusuo Zhang
- College of Resources and Environmental Sciences, China Agriculture University, Beijing 100193, China
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44
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Hill WG. "Conversion" of epistatic into additive genetic variance in finite populations and possible impact on long-term selection response. J Anim Breed Genet 2017; 134:196-201. [PMID: 28508485 DOI: 10.1111/jbg.12270] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 02/20/2017] [Indexed: 12/22/2022]
Abstract
The role of epistasis in understanding the genetic architecture and variation of quantitative traits and its role, if any, in artificial selection and livestock improvement more generally has a long and sometimes controversial history. Its presence has been clearly demonstrated in, for example, laboratory experiments, but the amount of variation it contributes is likely to be small in outbred populations. In a finite population, although additive x additive epistatic variance is lost by genetic drift, it also contributes by conversion to additive variance through drift sampling and therefore has a potential indirect role in medium and long-term selection response, with superficial similarity to and hard to distinguish from mutation. Whilst predictions of response require knowledge of genetic parameters, an infinitesimal model provides some analytic results. Otherwise there is little quantitative information relevant to animal populations on which to judge this potential role of epistasis and reach firm conclusions.
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Affiliation(s)
- W G Hill
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
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45
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Weller JI, Ezra E, Ron M. Invited review: A perspective on the future of genomic selection in dairy cattle. J Dairy Sci 2017; 100:8633-8644. [PMID: 28843692 DOI: 10.3168/jds.2017-12879] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 07/05/2017] [Indexed: 11/19/2022]
Abstract
Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.
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Affiliation(s)
- J I Weller
- Institute of Animal Sciences, Agricultural Research Organization, The Volcani Center, Rishon LeZion 7505101, Israel.
| | - E Ezra
- Israeli Cattle Breeders Association, Caesarea Industrial Park 3088900, Israel
| | - M Ron
- Institute of Animal Sciences, Agricultural Research Organization, The Volcani Center, Rishon LeZion 7505101, Israel
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46
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Tsuruta S, Lourenco DAL, Misztal I, Lawlor TJ. Genomic analysis of cow mortality and milk production using a threshold-linear model. J Dairy Sci 2017. [PMID: 28647327 DOI: 10.3168/jds.2017-12665] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The objective of this study was to investigate the feasibility of genomic evaluation for cow mortality and milk production using a single-step methodology. Genomic relationships between cow mortality and milk production were also analyzed. Data included 883,887 (866,700) first-parity, 733,904 (711,211) second-parity, and 516,256 (492,026) third-parity records on cow mortality (305-d milk yields) of Holsteins from Northeast states in the United States. The pedigree consisted of up to 1,690,481 animals including 34,481 bulls genotyped with 36,951 SNP markers. Analyses were conducted with a bivariate threshold-linear model for each parity separately. Genomic information was incorporated as a genomic relationship matrix in the single-step BLUP. Traditional and genomic estimated breeding values (GEBV) were obtained with Gibbs sampling using fixed variances, whereas reliabilities were calculated from variances of GEBV samples. Genomic EBV were then converted into single nucleotide polymorphism (SNP) marker effects. Those SNP effects were categorized according to values corresponding to 1 to 4 standard deviations. Moving averages and variances of SNP effects were calculated for windows of 30 adjacent SNP, and Manhattan plots were created for SNP variances with the same window size. Using Gibbs sampling, the reliability for genotyped bulls for cow mortality was 28 to 30% in EBV and 70 to 72% in GEBV. The reliability for genotyped bulls for 305-d milk yields was 53 to 65% to 81 to 85% in GEBV. Correlations of SNP effects between mortality and 305-d milk yields within categories were the highest with the largest SNP effects and reached >0.7 at 4 standard deviations. All SNP regions explained less than 0.6% of the genetic variance for both traits, except regions close to the DGAT1 gene, which explained up to 2.5% for cow mortality and 4% for 305-d milk yields. Reliability for GEBV with a moderate number of genotyped animals can be calculated by Gibbs samples. Genomic information can greatly increase the reliability of predictions not only for milk but also for mortality. The existence of a common region on Bos taurus autosome 14 affecting both traits may indicate a major gene with a pleiotropic effect on milk and mortality.
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Affiliation(s)
- S Tsuruta
- Animal and Dairy Science Department, University of Georgia, Athens 30602.
| | - D A L Lourenco
- Animal and Dairy Science Department, University of Georgia, Athens 30602
| | - I Misztal
- Animal and Dairy Science Department, University of Georgia, Athens 30602
| | - T J Lawlor
- Holstein Association USA Inc., Brattleboro, VT 05301
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