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Gudra D, Valdovska A, Jonkus D, Kairisa D, Galina D, Ustinova M, Viksne K, Fridmanis D, Kalnina I. Genetic characterization of the Latvian local goat breed and genetic traits associated with somatic cell count. Animal 2024; 18:101154. [PMID: 38703755 DOI: 10.1016/j.animal.2024.101154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/27/2024] [Accepted: 04/04/2024] [Indexed: 05/06/2024] Open
Abstract
The Latvian local goat (LVK) breed represents the only native domestic goat breed in Latvia, but its limited population places it within the endangered category. However, the LVK breed has not yet undergone a comprehensive genetic characterization. Therefore, we completed whole genome sequencing to reveal the genetic foundation of the LVK breed while identifying genetic traits linked to the somatic cell count (SCC) levels. The study included 40 genomes of LVK goats sequenced to acquire at least 35x or 10x coverage. A Principal component analysis, a genetic distance tree, and an admixture analysis showed LVK's similarity to some European breeds, such as Finnish Landrace, Alpine, and Saanen, which aligns with the breed's history. An analysis of genome-wide heterozygosity, nucleotide diversity, and LD analysis indicated that the LVK population exhibits substantial levels of genetic diversity. LVK genome was dominated by short runs of homozygosity (ROHs, ≤ 500 kb) with a median length of 25 kb. With FROH 2.49%, average inbreeding levels were low; however, FROH ranged broadly from 0.13 to 12.2%. With the exception of one pure-blood breeding buck exhibiting FROH of 9.3% and FSNP of 8.5%, animals with at least 66% LVK ancestry showed moderate or no inbreeding. Overall, this study demonstrated that the LVK goats can be differentiated from imported breeds, although the population has a complex genetic structure. We were able to identify potential genetic traits associated with SCC levels, although the kinship of the animals and the heterogenic substructure of the population might have largely influenced the association analysis. We identified 26 genetic variants associated with SCC levels, which included the potentially relevant SNP rs662053371 in the OSBPL8 gene, indicating a potential signal linked to lipid metabolism in goats. To conclude, these findings present valuable insight into the genetic structure of the LVK breed for the conservation of local genetic resources.
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Affiliation(s)
- D Gudra
- Human Genetics and Disease Mechanisms Department, Latvian Biomedical Research and Study Centre, Rātsupītes iela 1 K-1, LV-1067 Riga, Latvia
| | - A Valdovska
- Faculty of Veterinary Medicine, Latvia University of Life Sciences and Technologies, Helmana iela 8 K, LV-3004 Jelgava, Latvia; Scientific Laboratory of Biotechnology, Latvia University of Life Sciences and Technologies, Lielā iela 2, LV-3001 Jelgava, Latvia.
| | - D Jonkus
- Faculty of Agriculture, Latvia University of Life Sciences and Technologies, Lielā iela 2, LV-3001 Jelgava, Latvia
| | - D Kairisa
- Faculty of Agriculture, Latvia University of Life Sciences and Technologies, Lielā iela 2, LV-3001 Jelgava, Latvia
| | - D Galina
- Faculty of Veterinary Medicine, Latvia University of Life Sciences and Technologies, Helmana iela 8 K, LV-3004 Jelgava, Latvia; Scientific Laboratory of Biotechnology, Latvia University of Life Sciences and Technologies, Lielā iela 2, LV-3001 Jelgava, Latvia
| | - M Ustinova
- Human Genetics and Disease Mechanisms Department, Latvian Biomedical Research and Study Centre, Rātsupītes iela 1 K-1, LV-1067 Riga, Latvia
| | - K Viksne
- Human Genetics and Disease Mechanisms Department, Latvian Biomedical Research and Study Centre, Rātsupītes iela 1 K-1, LV-1067 Riga, Latvia
| | - D Fridmanis
- Human Genetics and Disease Mechanisms Department, Latvian Biomedical Research and Study Centre, Rātsupītes iela 1 K-1, LV-1067 Riga, Latvia
| | - I Kalnina
- Human Genetics and Disease Mechanisms Department, Latvian Biomedical Research and Study Centre, Rātsupītes iela 1 K-1, LV-1067 Riga, Latvia
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Colombi D, Rovelli G, Luigi-Sierra MG, Ceccobelli S, Guan D, Perini F, Sbarra F, Quaglia A, Sarti FM, Pasquini M, Amills M, Lasagna E. Population structure and identification of genomic regions associated with productive traits in five Italian beef cattle breeds. Sci Rep 2024; 14:8529. [PMID: 38609445 PMCID: PMC11014930 DOI: 10.1038/s41598-024-59269-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/09/2024] [Indexed: 04/14/2024] Open
Abstract
Italy has a long history in beef production, with local breeds such as Marchigiana, Chianina, Romagnola, Maremmana, and Podolica which produce high-quality meat. Selection has improved meat production, precocity, growth ability and muscle development, but the genetic determinism of such traits is mostly unknown. Using 33K SNPs-data from young bulls (N = 4064) belonging to these five Italian breeds, we demonstrated that the Maremmana and Podolica rustic breeds are closely related, while the specialised Marchigiana, Chianina, and Romagnola breeds are more differentiated. A genome-wide association study for growth and muscle development traits (average daily gain during the performance test, weight at 1 year old, muscularity) was conducted in the five Italian breeds. Results indicated a region on chromosome 2, containing the myostatin gene (MSTN), which displayed significant genome-wide associations with muscularity in Marchigiana cattle, a breed in which the muscle hypertrophy phenotype is segregating. Moreover, a significant SNP on chromosome 14 was associated, in the Chianina breed, to muscularity. The identification of diverse genomic regions associated with conformation traits might increase our knowledge about the genomic basis of such traits in Italian beef cattle and, eventually, such information could be used to implement marker-assisted selection of young bulls tested in the performance test.
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Affiliation(s)
- Daniele Colombi
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
| | - Giacomo Rovelli
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
| | - Maria Gracia Luigi-Sierra
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
| | - Simone Ceccobelli
- Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, 60131, Ancona, Italy
| | - Dailu Guan
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
- Department of Animal Science, University of California, Davis, CA, 2251, USA
| | - Francesco Perini
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020, Legnaro, Italy
| | - Fiorella Sbarra
- National Association of Italian Beef-Cattle Breeders (ANABIC), 06132, San Martino in Colle, Perugia, Italy
| | - Andrea Quaglia
- National Association of Italian Beef-Cattle Breeders (ANABIC), 06132, San Martino in Colle, Perugia, Italy
| | - Francesca Maria Sarti
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
| | - Marina Pasquini
- Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, 60131, Ancona, Italy
| | - Marcel Amills
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain.
- Department of Animal and Food Science, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
| | - Emiliano Lasagna
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy.
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Lin C, Wang W, Zhang D, Huang K, Zhang Y, Li X, Zhao Y, Zhao L, Wang J, Zhou B, Cheng J, Xu D, Li W, Zhang X, Zheng W. Analysis of liver miRNA in Hu sheep with different residual feed intake. Front Genet 2023; 14:1113411. [PMID: 37928243 PMCID: PMC10620975 DOI: 10.3389/fgene.2023.1113411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Feed efficiency (FE), an important economic trait in sheep production, is indirectly assessed by residual feed intake (RFI). However, RFI in sheep is varied, and the molecular processes that regulate RFI are unclear. It is thus vital to investigate the molecular mechanism of RFI to developing a feed-efficient sheep. The miRNA-sequencing (RNA-Seq) was utilized to investigate miRNAs in liver tissue of 6 out of 137 sheep with extreme RFI phenotypic values. In these animals, as a typical metric of FE, RFI was used to distinguish differentially expressed miRNAs (DE_miRNAs) between animals with high (n = 3) and low (n = 3) phenotypic values. A total of 247 miRNAs were discovered in sheep, with four differentially expressed miRNAs (DE_miRNAs) detected. Among these DE_miRNAs, three were found to be upregulated and one was downregulated in animals with low residual feed intake (Low_RFI) compared to those with high residual feed intake (High_RFI). The target genes of DE_miRNAs were primarily associated with metabolic processes and biosynthetic process regulation. Furthermore, they were also considerably enriched in the FE related to glycolysis, protein synthesis and degradation, and amino acid biosynthesis pathways. Six genes were identified by co-expression analysis of DE_miRNAs target with DE_mRNAs. These results provide a theoretical basis for us to understand the sheep liver miRNAs in RFI molecular regulation.
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Affiliation(s)
- Changchun Lin
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
- Institute of Animal Husbandry Quality Standards, Xinjiang Academy of Animal Sciences, Urumqi, Xinjiang, China
| | - Weimin Wang
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Deyin Zhang
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Kai Huang
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Yukun Zhang
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Xiaolong Li
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Yuan Zhao
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Liming Zhao
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Jianghui Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Bubo Zhou
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Jiangbo Cheng
- The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, Gansu, China
| | - Dan Xu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Wenxin Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Xiaoxue Zhang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Wenxin Zheng
- Institute of Animal Husbandry Quality Standards, Xinjiang Academy of Animal Sciences, Urumqi, Xinjiang, China
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Chessari G, Criscione A, Tolone M, Bordonaro S, Rizzuto I, Riggio S, Macaluso V, Moscarelli A, Portolano B, Sardina MT, Mastrangelo S. High-density SNP markers elucidate the genetic divergence and population structure of Noticiana sheep breed in the Mediterranean context. Front Vet Sci 2023; 10:1127354. [PMID: 37205231 PMCID: PMC10185747 DOI: 10.3389/fvets.2023.1127354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 04/13/2023] [Indexed: 05/21/2023] Open
Abstract
Among livestock species, sheep have played an early major role in the Mediterranean area. Italy has a long history of sheep breeding and, despite a dramatic contraction in numbers, still raise several local populations that may represent a unique source of genetic diversity. The Noticiana is a breed of the south-eastern part of Sicily appreciated both for its dairy products and for its resistance to harsh environment. In this study, the high-density Illumina Ovine SNP600K BeadChip array was used for the first genome-wide characterization of 48 individuals of Noticiana sheep to investigate its diversity, the genome structure and the relationship within the context of worldwide and Italian breeds. Moreover, the runs of homozygosity (ROH) pattern and the pairwise FST-outliers were examined. Noticiana reported moderate levels of genetic diversity. The high percentage of short and medium length ROH segments (93% under 4 Mb) is indicative of a within breed relatedness dating back to ancient times, despite the absence of management for the mating plans and the reduced population size. In the worldwide context, the Southern Italian, Spanish and Albanian breeds overlapped in a macro cluster which also included the Noticiana sheep. The results highlighted ancestral genetic components of Noticiana shared with Comisana breed, and showed the clear separation from the other Italian sheep. This is likely the consequence of the combined effects of genetic drift, small population size and reproductive isolation. ROH islands and FST-outliers approaches in Noticiana identified genes and QTLs involved in milk and meat production, as well as related to the local adaptation, and therefore are consistent with the phenotypic traits of the studied breed. Although a wider sampling could be useful to deepen the genomic survey on Noticiana, these results represent a crucial starting point for the characterization of an important local genetic resource, with a view of supporting the local economy and preserving the biodiversity of the sheep species.
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Affiliation(s)
- Giorgio Chessari
- Dipartimento Agricoltura, Alimentazione e Ambiente, University of Catania, Catania, Italy
| | - Andrea Criscione
- Dipartimento Agricoltura, Alimentazione e Ambiente, University of Catania, Catania, Italy
| | - Marco Tolone
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Salvatore Bordonaro
- Dipartimento Agricoltura, Alimentazione e Ambiente, University of Catania, Catania, Italy
| | - Ilaria Rizzuto
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Silvia Riggio
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Vito Macaluso
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Angelo Moscarelli
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Baldassare Portolano
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Maria Teresa Sardina
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
| | - Salvatore Mastrangelo
- Dipartimento Scienze Agrarie, Alimentari e Forestali, University of Palermo, Palermo, Italy
- *Correspondence: Salvatore Mastrangelo,
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Ribeiro G, Baldi F, Cesar ASM, Alexandre PA, Peripolli E, Ferraz JBS, Fukumasu H. Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle. BMC Genomics 2022; 23:774. [PMID: 36434498 PMCID: PMC9700932 DOI: 10.1186/s12864-022-08958-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 10/20/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Potential functional variants (PFVs) can be defined as genetic variants responsible for a given phenotype. Ultimately, these are the best DNA markers for animal breeding and selection, especially for polygenic and complex phenotypes. Herein, we described the identification of PFVs for complex phenotypes (in this case, Feed Efficiency in beef cattle) using a systems-biology driven approach based on RNA-seq data from physiologically relevant organs. RESULTS The systems-biology coupled with deep molecular phenotyping by RNA-seq of liver, muscle, hypothalamus, pituitary, and adrenal glands of animals with high and low feed efficiency (FE) measured by residual feed intake (RFI) identified 2,000,936 uniquely variants. Among them, 9986 variants were significantly associated with FE and only 78 had a high impact on protein expression and were considered as PFVs. A set of 169 significant uniquely variants were expressed in all five organs, however, only 27 variants had a moderate impact and none of them a had high impact on protein expression. These results provide evidence of tissue-specific effects of high-impact PFVs. The PFVs were enriched (FDR < 0.05) for processing and presentation of MHC Class I and II mediated antigens, which are an important part of the adaptive immune response. The experimental validation of these PFVs was demonstrated by the increased prediction accuracy for RFI using the weighted G matrix (ssGBLUP+wG; Acc = 0.10 and b = 0.48) obtained in the ssGWAS in comparison to the unweighted G matrix (ssGBLUP; Acc = 0.29 and b = 1.10). CONCLUSION Here we identified PFVs for FE in beef cattle using a strategy based on systems-biology and deep molecular phenotyping. This approach has great potential to be used in genetic prediction programs, especially for polygenic phenotypes.
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Affiliation(s)
- Gabriela Ribeiro
- grid.11899.380000 0004 1937 0722Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Sao Paulo, 13635-900 Brazil
| | - Fernando Baldi
- grid.410543.70000 0001 2188 478XDepartment of Animal Science, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil
| | - Aline S. M. Cesar
- grid.11899.380000 0004 1937 0722Escola Superior de Agricultura “Luiz de Queiroz”, University of Sao Paulo, Piracicaba, São Paulo, Brazil
| | - Pâmela A. Alexandre
- grid.11899.380000 0004 1937 0722Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Sao Paulo, 13635-900 Brazil ,CSIRO Agriculture & Food, 306 Carmody Rd., St. Lucia, Brisbane, QLD 4067 Australia
| | - Elisa Peripolli
- grid.11899.380000 0004 1937 0722Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Sao Paulo, 13635-900 Brazil ,grid.410543.70000 0001 2188 478XDepartment of Animal Science, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil
| | - José B. S. Ferraz
- grid.11899.380000 0004 1937 0722Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Sao Paulo, 13635-900 Brazil
| | - Heidge Fukumasu
- grid.11899.380000 0004 1937 0722Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Sao Paulo, 13635-900 Brazil
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Passamonti MM, Somenzi E, Barbato M, Chillemi G, Colli L, Joost S, Milanesi M, Negrini R, Santini M, Vajana E, Williams JL, Ajmone-Marsan P. The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock. Animals (Basel) 2021; 11:2833. [PMID: 34679854 PMCID: PMC8532622 DOI: 10.3390/ani11102833] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/21/2021] [Accepted: 09/23/2021] [Indexed: 12/14/2022] Open
Abstract
Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.
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Affiliation(s)
- Matilde Maria Passamonti
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
| | - Elisa Somenzi
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
| | - Mario Barbato
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
| | - Giovanni Chillemi
- Department for Innovation in Biological, Agro-Food and Forest Systems–DIBAF, Università Della Tuscia, Via S. Camillo de Lellis snc, 01100 Viterbo, Italy; (G.C.); (M.M.)
| | - Licia Colli
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
- Research Center on Biodiversity and Ancient DNA—BioDNA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; (S.J.); (E.V.)
| | - Marco Milanesi
- Department for Innovation in Biological, Agro-Food and Forest Systems–DIBAF, Università Della Tuscia, Via S. Camillo de Lellis snc, 01100 Viterbo, Italy; (G.C.); (M.M.)
| | - Riccardo Negrini
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
| | - Monia Santini
- Impacts on Agriculture, Forests and Ecosystem Services (IAFES) Division, Fondazione Centro Euro-Mediterraneo Sui Cambiamenti Climatici (CMCC), Viale Trieste 127, 01100 Viterbo, Italy;
| | - Elia Vajana
- Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; (S.J.); (E.V.)
| | - John Lewis Williams
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
| | - Paolo Ajmone-Marsan
- Department of Animal Science, Food and Nutrition—DIANA, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy; (M.M.P.); (E.S.); (M.B.); (L.C.); (R.N.); (J.L.W.)
- Nutrigenomics and Proteomics Research Center—PRONUTRIGEN, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, 29122 Piacenza, Italy
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Expression of candidate genes for residual feed intake in tropically adapted Bos taurus and Bos indicus bulls under thermoneutral and heat stress environmental conditions. J Therm Biol 2021; 99:102998. [PMID: 34420630 DOI: 10.1016/j.jtherbio.2021.102998] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/14/2021] [Accepted: 05/16/2021] [Indexed: 01/17/2023]
Abstract
The objectives of this study were to measure the relative expression of the ATP1A1, NR3C1, POMC, NPY, and LEP genes in Caracu (Bos taurus) and Nelore (Bos indicus) bulls submitted to feed efficiency tests at high environmental temperatures, and to evaluate differences in adaptability to tropical conditions between breeds. Thirty-five Caracu and 30 Nelore bulls were submitted to a feed efficiency test using automated feeding stations. At the end of the test, the animals were subjected to thermoneutral (TN) and heat stress (HS) conditions. Blood samples were collected after the exposure to the TN and HS conditions and the relative expression of genes was measured by qPCR. The bulls exhibited lower expression of ATP1A1 in the HS condition than in the TN condition (1.98 ± 0.27 and 2.86 ± 0.26, P = 0.02), while the relative expression of NR3C1, POMC, and LEP did not differ (P > 0.05) between climatic conditions. The breed and feed intake influenced NPY and LEP expression levels (P < 0.05). Different climate conditions associated with residual feed intake can modify the gene expression patterns of ATP1A1 and NPY. The association observed among all genes studied shows that they are involved in appetite control. Bos taurus and Bos indicus bulls exhibited similar adaptability to tropical climate conditions.
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Chen W, Alexandre PA, Ribeiro G, Fukumasu H, Sun W, Reverter A, Li Y. Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data. Front Genet 2021; 12:619857. [PMID: 33664767 PMCID: PMC7921797 DOI: 10.3389/fgene.2021.619857] [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: 10/21/2020] [Accepted: 01/15/2021] [Indexed: 12/22/2022] Open
Abstract
Machine learning (ML) methods have shown promising results in identifying genes when applied to large transcriptome datasets. However, no attempt has been made to compare the performance of combining different ML methods together in the prediction of high feed efficiency (HFE) and low feed efficiency (LFE) animals. In this study, using RNA sequencing data of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle, and pituitary) from nine HFE and nine LFE Nellore bulls, we evaluated the prediction accuracies of five analytical methods in classifying FE animals. These included two conventional methods for differential gene expression (DGE) analysis (t-test and edgeR) as benchmarks, and three ML methods: Random Forests (RFs), Extreme Gradient Boosting (XGBoost), and combination of both RF and XGBoost (RX). Utility of a subset of candidate genes selected from each method for classification of FE animals was assessed by support vector machine (SVM). Among all methods, the smallest subsets of genes (117) identified by RX outperformed those chosen by t-test, edgeR, RF, or XGBoost in classification accuracy of animals. Gene co-expression network analysis confirmed the interactivity existing among these genes and their relevance within the network related to their prediction ranking based on ML. The results demonstrate a great potential for applying a combination of ML methods to large transcriptome datasets to identify biologically important genes for accurately classifying FE animals.
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Affiliation(s)
- Weihao Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,CSIRO Agriculture and Food, St Lucia, QLD, Australia
| | | | - Gabriela Ribeiro
- School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Heidge Fukumasu
- School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Wei Sun
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China.,Institute of Agriculture Science and Technology Development, Yangzhou University, Yangzhou, China.,Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
| | | | - Yutao Li
- CSIRO Agriculture and Food, St Lucia, QLD, Australia
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9
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Li W, Zheng M, Zhao G, Wang J, Liu J, Wang S, Feng F, Liu D, Zhu D, Li Q, Guo L, Guo Y, Liu R, Wen J. Identification of QTL regions and candidate genes for growth and feed efficiency in broilers. Genet Sel Evol 2021; 53:13. [PMID: 33549052 PMCID: PMC7866652 DOI: 10.1186/s12711-021-00608-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 01/26/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array. RESULTS Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34-2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27-92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI. CONCLUSIONS We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.
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Affiliation(s)
- Wei Li
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Maiqing Zheng
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Wang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Shunli Wang
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Furong Feng
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Dawei Liu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Dan Zhu
- Foshan Gaoming Xinguang Agricultural and Animal Industrials Corporation, Foshan, 528515 China
| | - Qinghe Li
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Liping Guo
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Yuming Guo
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
| | - Jie Wen
- State Key Laboratory of Animal Nutrition; Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193 China
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Torkamaneh D, Laroche J, Valliyodan B, O'Donoughue L, Cober E, Rajcan I, Vilela Abdelnoor R, Sreedasyam A, Schmutz J, Nguyen HT, Belzile F. Soybean (Glycine max) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:324-334. [PMID: 32794321 DOI: 10.1101/534578] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 07/24/2020] [Accepted: 08/07/2020] [Indexed: 05/27/2023]
Abstract
Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.
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Affiliation(s)
- Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec City, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC, Canada
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Jérôme Laroche
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC, Canada
| | - Babu Valliyodan
- National Center for Soybean Biotechnology and Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - Louise O'Donoughue
- CÉROM, Centre de recherche Sur Les Grains Inc., Saint-Mathieu de Beloeil, QC, Canada
| | - Elroy Cober
- Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Ricardo Vilela Abdelnoor
- Brazilian Corporation of Agricultural Research (Embrapa Soja), Warta County, PR, Brazil
- Londrina State University (UEL), Londrina, PR, Brazil
| | | | - Jeremy Schmutz
- Institute for Biotechnology, HudsonAlpha, Huntsville, AL, USA
- Department of Energy, Joint Genome Institute, Walnut Creek, CA, USA
| | - Henry T Nguyen
- National Center for Soybean Biotechnology and Division of Plant Sciences, University of Missouri, Columbia, MO, USA
| | - François Belzile
- Département de Phytologie, Université Laval, Québec City, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC, Canada
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11
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Torkamaneh D, Laroche J, Valliyodan B, O’Donoughue L, Cober E, Rajcan I, Vilela Abdelnoor R, Sreedasyam A, Schmutz J, Nguyen HT, Belzile F. Soybean (Glycine max) Haplotype Map (GmHapMap): a universal resource for soybean translational and functional genomics. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:324-334. [PMID: 32794321 PMCID: PMC7868971 DOI: 10.1111/pbi.13466] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 07/24/2020] [Accepted: 08/07/2020] [Indexed: 05/10/2023]
Abstract
Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole-genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single-nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1-Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene-centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss-of-function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.
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Affiliation(s)
- Davoud Torkamaneh
- Département de PhytologieUniversité LavalQuébec CityQCCanada
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébec CityQCCanada
- Department of Plant AgricultureUniversity of GuelphGuelphONCanada
| | - Jérôme Laroche
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébec CityQCCanada
| | - Babu Valliyodan
- National Center for Soybean Biotechnology and Division of Plant SciencesUniversity of MissouriColumbiaMOUSA
| | - Louise O’Donoughue
- CÉROMCentre de recherche Sur Les Grains Inc.Saint‐Mathieu de BeloeilQCCanada
| | - Elroy Cober
- Agriculture and Agri‐Food CanadaOttawaONCanada
| | - Istvan Rajcan
- Department of Plant AgricultureUniversity of GuelphGuelphONCanada
| | - Ricardo Vilela Abdelnoor
- Brazilian Corporation of Agricultural Research (Embrapa Soja)Warta CountyPRBrazil
- Londrina State University (UEL)LondrinaPRBrazil
| | | | - Jeremy Schmutz
- Institute for BiotechnologyHudsonAlphaHuntsvilleALUSA
- Department of EnergyJoint Genome InstituteWalnut CreekCAUSA
| | - Henry T. Nguyen
- National Center for Soybean Biotechnology and Division of Plant SciencesUniversity of MissouriColumbiaMOUSA
| | - François Belzile
- Département de PhytologieUniversité LavalQuébec CityQCCanada
- Institut de Biologie Intégrative et des Systèmes (IBIS)Université LavalQuébec CityQCCanada
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12
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Berton MP, de Antunes Lemos MV, Seleguim Chud TC, Bonvino Stafuzza N, Kluska S, Amorim ST, Silva Ferlin Lopes L, Cravo Pereira AS, Bickhart D, Liu G, Galvão de Albuquerque L, Baldi F. Genome-wide association study between copy number variation regions and carcass- and meat-quality traits in Nellore cattle. ANIMAL PRODUCTION SCIENCE 2021. [DOI: 10.1071/an20275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Context
Indicine breeds are the main source of beef products in tropical and subtropical regions. However, genetic improvement for carcass- and meat-quality traits in zebu cattle have been limited and genomics studies concerning structural variations that influence these traits are essential.
Aim
The aim of this study was to perform a genome-wide association study between copy number variation regions (CNVRs) and carcass- and meat quality-traits in Nellore cattle.
Methods
In total, 3794 animals, males and females included, were genotyped using a 777962 single-nucleotide polymorphism platform of BovineHD BeadChip (777k; Illumina Inc.). Of these, 1751 Nellore bulls were slaughtered at 24 months of age for further carcass beef analysis. The following traits were studied: beef tenderness, marbling, rib-eye area, backfat thickness and meat colour (lightness, redness and yellowness). The CNV detection was conducted through PennCNV software. The association analyses were performed using CNVRuler software.
Key results
Several identified genomic regions were linked to quantitative trait loci associated with fat deposition (FABP7) and lipid metabolism (PPARA; PLA2 family; BCHE), extracellular matrix (INS; COL10A1), contraction (SLC34A3; TRDN) and muscle development (CAPZP). The gene-enrichment analyses highlighted biological mechanisms directly related to the metabolism and synthesis of lipids and fatty acids.
Conclusions
The large number of potential candidate genes identified within the CNVRs, as well as the functions and pathways identified, should help better elucidate the genetic mechanisms involved in the expression of beef and carcass traits in Nellore cattle. Several CNVRs harboured genes that might have a functional impact to improve the beef and carcass traits.
Implications
The results obtained contribute to upgrade the sensorial and organoleptic attributes of Nellore cattle and make feasible the genetic improvement of carcass- and meat-quality traits.
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13
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Brunes LC, Baldi F, Lopes FB, Narciso MG, Lobo RB, Espigolan R, Costa MFO, Magnabosco CU. Genomic prediction ability for feed efficiency traits using different models and pseudo-phenotypes under several validation strategies in Nelore cattle. Animal 2020; 15:100085. [PMID: 33573965 DOI: 10.1016/j.animal.2020.100085] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 09/09/2020] [Accepted: 09/15/2020] [Indexed: 10/22/2022] Open
Abstract
There is a growing interest to improve feed efficiency (FE) traits in cattle. The genomic selection was proposed to improve these traits since they are difficult and expensive to measure. Up to date, there are scarce studies about the implementation of genomic selection for FE traits in indicine cattle under different scenarios of pseudo-phenotypes, models, and validation strategies on a commercial large scale. Thus, the aim was to evaluate the feasibility of genomic selection implementation for FE traits in Nelore cattle applying different models and pseudo-phenotypes under validation strategies. Phenotypic and genotypic information from 4 329 and 3 467 animals were used, respectively, which were tested for residual feed intake, DM intake, feed efficiency, feed conversion ratio, residual BW gain, and residual intake and BW gain. Six prediction methods were used: single-step genomic best linear unbiased prediction, Bayes A, Bayes B, Bayes Cπ, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayes R. Phenotypes adjusted for fixed effects (Y*), estimated breeding value (EBV), and EBV deregressed (DEBV) were used as pseudo-phenotypes. The validation approaches used were: (1) random: the data was randomly divided into ten subsets and the validation was done in each subset at a time; (2) age: the partition into training and testing sets was based on year of birth and testing animals were born after 2016; and (3) EBV accuracy: the data was split into two groups, being animals with accuracy above 0.45 the training set; and below 0.45 the validation set. In the analyses that used the Y* as pseudo-phenotype, prediction ability (PA) was obtained by dividing the correlation between pseudo-phenotype and genomic EBV (GEBV) by the square root of the heritability of the trait. When EBV and DEBV were used as the pseudo-phenotype, the simple correlation of this quantity with the GEBV was considered as PA. The prediction methods show similar results for PA and bias. The random cross-validation presented higher PA (0.17) than EBV accuracy (0.14) and age (0.13). The PA was higher for Y* than for EBV and DEBV (30.0 and 34.3%, respectively). Random validation presented the highest PA, being indicated for use in populations composed mainly of young animals and traits with few generations of data recording. For high heritability traits, the validation can be done by age, enabling the prediction of the next-generation genetic merit. These results would support breeders to identify genomic approaches that are more viable for genomic prediction for FE-related traits.
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Affiliation(s)
- L C Brunes
- Animal Science Department, Goiás Federal University, 74690-900 Goiânia, GO, Brazil; Embrapa Rice and Beans, GO-462, km 12, 75375-000 Santo Antônio de Goiás, GO, Brazil.
| | - F Baldi
- Animal Science Department, São Paulo State University - Júlio de Mesquita Filho (UNESP), Prof. Paulo Donato Castelane, 14884-900 Jaboticabal, SP, Brazil
| | - F B Lopes
- Cobb-Vantress, Inc., 72761 Siloam Springs, AR, USA
| | - M G Narciso
- Embrapa Rice and Beans, GO-462, km 12, 75375-000 Santo Antônio de Goiás, GO, Brazil
| | - R B Lobo
- National Association of Breeders and Researchers, 14020-230 Ribeirão Preto, Brazil
| | - R Espigolan
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, 13635-900 Pirassununga, SP, Brazil
| | - M F O Costa
- Embrapa Rice and Beans, GO-462, km 12, 75375-000 Santo Antônio de Goiás, GO, Brazil
| | - C U Magnabosco
- Embrapa Cerrados, BR-020, 18 Sobradinho, 70770-901 Brasilia, DF, Brazil
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14
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Taussat S, Boussaha M, Ramayo-Caldas Y, Martin P, Venot E, Cantalapiedra-Hijar G, Hozé C, Fritz S, Renand G. Gene networks for three feed efficiency criteria reveal shared and specific biological processes. Genet Sel Evol 2020; 52:67. [PMID: 33167870 PMCID: PMC7653997 DOI: 10.1186/s12711-020-00585-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 10/27/2020] [Indexed: 12/26/2022] Open
Abstract
Background French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria. Results A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency. Conclusions The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.
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Affiliation(s)
- Sébastien Taussat
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France. .,Allice, 75012, Paris, France.
| | - Mekki Boussaha
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | | | - Pauline Martin
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | - Eric Venot
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
| | | | - Chris Hozé
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.,Allice, 75012, Paris, France
| | - Sébastien Fritz
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.,Allice, 75012, Paris, France
| | - Gilles Renand
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
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15
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Sikka P, Nath A, Paul SS, Andonissamy J, Mishra DC, Rao AR, Balhara AK, Chaturvedi KK, Yadav KK, Balhara S. Inferring Relationship of Blood Metabolic Changes and Average Daily Gain With Feed Conversion Efficiency in Murrah Heifers: Machine Learning Approach. Front Vet Sci 2020; 7:518. [PMID: 32984408 PMCID: PMC7492607 DOI: 10.3389/fvets.2020.00518] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 07/06/2020] [Indexed: 11/13/2022] Open
Abstract
Machine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.
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Affiliation(s)
- Poonam Sikka
- Animal Biochemistry, Division of Genetics and Breeding, Central Institute for Research on Buffaloes (ICAR), Hisar, India
| | - Abhigyan Nath
- Department of Biochemistry, Pt. Jawahar Lal Nehru Memorial Medical College, Pt. Deendayal Upadhyay Memorial Health Sciences and Ayush University of Chhatisgarh, Raipur, India
| | - Shyam Sundar Paul
- Poultry Nutrition, Directorate of Poultry Research (DPR), ICAR, Hyderabad, India
| | - Jerome Andonissamy
- Animal Biochemistry, Division of Genetics and Breeding, Central Institute for Research on Buffaloes (ICAR), Hisar, India
| | - Dwijesh Chandra Mishra
- Indian Agricultural Statistics Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Atmakuri Ramakrishna Rao
- Indian Agricultural Statistics Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Ashok Kumar Balhara
- Animal Biochemistry, Division of Genetics and Breeding, Central Institute for Research on Buffaloes (ICAR), Hisar, India
| | - Krishna Kumar Chaturvedi
- Indian Agricultural Statistics Research Institute, Indian Council of Agricultural Research, New Delhi, India
| | - Keerti Kumar Yadav
- Department of Bioinfromatics, School of Earth, Biological and Environmental Sciences, Central University of South Bihar, Patna, India
| | - Sunesh Balhara
- Animal Biochemistry, Division of Genetics and Breeding, Central Institute for Research on Buffaloes (ICAR), Hisar, India
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16
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Brunes LC, Baldi F, Lopes FB, Lôbo RB, Espigolan R, Costa MFO, Stafuzza NB, Magnabosco CU. Weighted single-step genome-wide association study and pathway analyses for feed efficiency traits in Nellore cattle. J Anim Breed Genet 2020; 138:23-44. [PMID: 32654373 DOI: 10.1111/jbg.12496] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 06/11/2020] [Accepted: 06/13/2020] [Indexed: 02/06/2023]
Abstract
The aim was to conduct a weighted single-step genome-wide association study to detect genomic regions and putative candidate genes related to residual feed intake, dry matter intake, feed efficiency (FE), feed conversion ratio, residual body weight gain, residual intake and weight gain in Nellore cattle. Several protein-coding genes were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for these traits. These genes were associated with insulin, leptin, glucose, protein and lipid metabolisms; energy balance; heat and oxidative stress; bile secretion; satiety; feed behaviour; salivation; digestion; and nutrient absorption. Enrichment analysis revealed functional pathways (p-value < .05) such as neuropeptide signalling (GO:0007218), negative regulation of canonical Wingless/Int-1 (Wnt) signalling (GO:0090090), bitter taste receptor activity (GO:0033038), neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction (bta0742) and glucagon signalling pathway (bta04922). The identification of these genes, pathways and their respective functions should contribute to a better understanding of the genetic and physiological mechanisms regulating Nellore FE-related traits.
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Affiliation(s)
- Ludmilla C Brunes
- Department of Animal Science, Federal University of Goiás (UFG), Goiânia, Brazil.,Embrapa Rice and Beans, Santo Antônio de Goiás, Brazil
| | - Fernando Baldi
- Department of Animal Science, São Paulo State University (UNESP), Jaboticabal, Brazil
| | | | - Raysildo B Lôbo
- National Association of Breeders and Researchers (ANCP), Ribeirão Preto, Brazil
| | - Rafael Espigolan
- Department of Veterinary Medicine, Faculty of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Brazil
| | | | - Nedenia B Stafuzza
- Beef Cattle Research Center, Animal Science Institute, Sertãozinho, Brazil
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17
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Vieira Ventura R, Fonseca E Silva F, Manuel Yáñez J, Brito LF. Opportunities and challenges of phenomics applied to livestock and aquaculture breeding in South America. Anim Front 2020; 10:45-52. [PMID: 32368412 PMCID: PMC7189274 DOI: 10.1093/af/vfaa008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Ricardo Vieira Ventura
- Department of Animal Nutrition and Production, Faculty of Veterinary Medicine and Animal Science, University of São Paulo (FMVZ/USP), Pirassununga, SP, Brazil
| | | | - José Manuel Yáñez
- Faculty of Veterinary and Animal Sciences, University of Chile, Santa Rosa, La Pintana, Santiago, Chile
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN
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18
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An B, Xu L, Xia J, Wang X, Miao J, Chang T, Song M, Ni J, Xu L, Zhang L, Li J, Gao H. Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle. BMC Genet 2020; 21:32. [PMID: 32171250 PMCID: PMC7071762 DOI: 10.1186/s12863-020-0837-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 03/04/2020] [Indexed: 01/08/2023] Open
Abstract
Background Body size traits as one of the main breeding selection criteria was widely used to monitor cattle growth and to evaluate the selection response. In this study, body size was defined as body height (BH), body length (BL), hip height (HH), heart size (HS), abdominal size (AS), and cannon bone size (CS). We performed genome-wide association studies (GWAS) of these traits over the course of three growth stages (6, 12 and 18 months after birth) using three statistical models, single-trait GWAS, multi-trait GWAS and LONG-GWAS. The Illumina Bovine HD 770 K BeadChip was used to identify genomic single nucleotide polymorphisms (SNPs) in 1217 individuals. Results In total, 19, 29, and 10 significant SNPs were identified by the three models, respectively. Among these, 21 genes were promising candidate genes, including SOX2, SNRPD1, RASGEF1B, EFNA5, PTBP1, SNX9, SV2C, PKDCC, SYNDIG1, AKR1E2, and PRIM2 identified by single-trait analysis; SLC37A1, LAP3, PCDH7, MANEA, and LHCGR identified by multi-trait analysis; and P2RY1, MPZL1, LINGO2, CMIP, and WSCD1 identified by LONG-GWAS. Conclusions Multiple association analysis was performed for six growth traits at each growth stage. These findings offer valuable insights for the further investigation of potential genetic mechanism of growth traits in Simmental beef cattle.
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Affiliation(s)
| | | | - Jiangwei Xia
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, 310000, China
| | - Xiaoqiao Wang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Jian Miao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Tianpeng Chang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Meihua Song
- Zhuang Yuan Veterinary Station of Qixia city, Yantai, 265300, China
| | - Junqing Ni
- Heibei Livestock Breeding Workstation, Shijiazhuang, 050061, China
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China.
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19
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20
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Takeda M, Uemoto Y, Inoue K, Ogino A, Nozaki T, Kurogi K, Yasumori T, Satoh M. Genome-wide association study and genomic evaluation of feed efficiency traits in Japanese Black cattle using single-step genomic best linear unbiased prediction method. Anim Sci J 2019; 91:e13316. [PMID: 31769129 DOI: 10.1111/asj.13316] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 09/30/2019] [Accepted: 10/23/2019] [Indexed: 01/18/2023]
Abstract
The objectives of this study were to better understand the genetic architecture and the possibility of genomic evaluation for feed efficiency traits by (i) performing genome-wide association studies (GWAS), and (ii) assessing the accuracy of genomic evaluation for feed efficiency traits, using single-step genomic best linear unbiased prediction (ssGBLUP)-based methods. The analyses were performed in residual feed intake (RFI), residual body weight gain (RG), and residual intake and body weight gain (RIG) during three different fattening periods. The phenotypes from 4,578 Japanese Black steers, which were progenies of 362 progeny-tested bulls and the genotypes from the bulls were used in this study. The results of GWAS showed that a total of 16, 8, and 12 gene ontology terms were related to RFI, RG, and RIG, respectively, and the candidate genes identified in RFI and RG were involved in olfactory transduction and the phosphatidylinositol signaling system, respectively. The realized reliabilities of genomic estimated breeding values were low to moderate in the feed efficiency traits. In conclusion, ssGBLUP-based method can lead to understand some biological functions related to feed efficiency traits, even with small population with genotypes, however, an alternative strategy will be needed to enhance the reliability of genomic evaluation.
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Affiliation(s)
- Masayuki Takeda
- National Livestock Breeding Center, Fukushima, Japan.,Graduate School of Agricultural Science, Tohoku University, Miyagi, Japan
| | - Yoshinobu Uemoto
- Graduate School of Agricultural Science, Tohoku University, Miyagi, Japan
| | - Keiichi Inoue
- National Livestock Breeding Center, Fukushima, Japan
| | - Atushi Ogino
- Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Gunma, Japan
| | - Takayoshi Nozaki
- Cattle Breeding Department, Livestock Improvement Association of Japan, Inc, Tokyo, Japan
| | - Kazuhito Kurogi
- Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Gunma, Japan
| | - Takanori Yasumori
- Cattle Breeding Department, Livestock Improvement Association of Japan, Inc, Tokyo, Japan
| | - Masahiro Satoh
- Graduate School of Agricultural Science, Tohoku University, Miyagi, Japan
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21
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Zhang D, Zhang X, Li F, Li C, La Y, Mo F, Li G, Zhang Y, Li X, Song Q, Zhao Y, Wang W. Transcriptome Analysis Identifies Candidate Genes and Pathways Associated With Feed Efficiency in Hu Sheep. Front Genet 2019; 10:1183. [PMID: 31798641 PMCID: PMC6878960 DOI: 10.3389/fgene.2019.01183] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 10/24/2019] [Indexed: 12/20/2022] Open
Abstract
In the genetic improvement of livestock and poultry, residual feed intake (RFI) is an important economic trait. However, in sheep, the genetic regulatory mechanisms of RFI are unclear. In the present study, we measured the feed efficiency (FE)-related phenotypes of 137 male Hu lambs, and selected six lambs with very high (n = 3) and very low (n = 3) RFI values and analyzed their liver transcriptomes. A total of 101 differentially expressed genes were identified, of which 40 were upregulated and 61 were downregulated in the low-RFI group compared with that in the high-RFI group. The downregulated genes were mainly concentrated in immune function pathways, while the upregulated genes were mainly involved in energy metabolism pathways. Two differentially expressed genes, ADRA2A (encoding adrenoceptor alpha 2A) and RYR2 (ryanodine receptor 2), were selected as candidate genes for FE and subjected to single nucleotide polymorphism scanning and association analysis. Two synonymous mutations, ADRA2A g.1429 C > A and RYR2 g.1117 A > C, were detected, which were both significantly associated with the feed conversion rate. These findings provide a deeper understanding of the molecular mechanisms regulating FE, and reveal key genes and genetic variants that could be used to genetically improve FE in sheep.
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Affiliation(s)
- Deyin Zhang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Xiaoxue Zhang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China.,Engineering Laboratory of Sheep Breeding and Reproduction Biotechnology in Gansu Province, Minqin Zhongtian Sheep Industry Co. Ltd., Minqin, China
| | - Fadi Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China.,Engineering Laboratory of Sheep Breeding and Reproduction Biotechnology in Gansu Province, Minqin Zhongtian Sheep Industry Co. Ltd., Minqin, China.,The State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China
| | - Chong Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Yongfu La
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Futao Mo
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Guoze Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Yukun Zhang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Xiaolong Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Qizhi Song
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Yuan Zhao
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
| | - Weimin Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou, China
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22
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Zhu F, Cheng SR, Yang YZ, Hao JP, Yang FX, Hou ZC. Genome-Wide Association Study of Growth and Feeding Traits in Pekin Ducks. Front Genet 2019; 10:702. [PMID: 31404312 PMCID: PMC6676418 DOI: 10.3389/fgene.2019.00702] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 07/03/2019] [Indexed: 12/16/2022] Open
Abstract
Growth rate and feeding efficiency are the most important economic traits for meat animals. Pekin duck is one of the major global breeds of meat-type duck. This study aims to identify QTL for duck growth and feeding efficiency traits in order to assist artificial selection. In this study, the growth and feeding related phenotypes of 639 Pekin ducks were recorded, and each individual genotype was evaluated using a genotyping-by-sequencing (GBS) protocol. The genetic parameters for growth and feeding efficiency related traits were estimated. Genome-wide association analysis (GWAS) was then performed for these traits. In total, 15 non-overlapping QTLs for the measured traits and 12 significant SNPs for feed efficiency traits were discovered using a mixed linear model. The most significant loci of feed intake (FI) is located in a 182Mb region on Chr1, which is downstream of gene RNF17, and can explain 2.3% of the phenotypic variation. This locus is also significantly associated with residual feed intake (RFI), and can explain 3% of this phenotypic variation. Among 12 SNPs associated with the feed conversion ratio (FCR), the most significant SNP (P-value = 1.65E-06), which was located in the region between the 3rd and 4th exon of the SORCS1 gene on Chr6, explained 3% of the phenotypic variance. Using gene-set analysis, a total of two significant genes were detected be associated with RFI on Chr1. This study is the first GWAS for growth and feeding efficiency related traits in ducks. Our results provide a list of candidate genes for marker assisted selection for growth and feeding efficiency, and also help to better understand the genetic mechanisms of feed efficiency and growth in ducks.
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Affiliation(s)
- Feng Zhu
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, Department of Animal Genetics and Breeding, China Agricultural University, Beijing, China
| | - Si-Rui Cheng
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, Department of Animal Genetics and Breeding, China Agricultural University, Beijing, China
| | - Yu-Ze Yang
- Beijing Municipal General Station of Animal Science, Beijing, China
| | - Jin-Ping Hao
- Duck Industry Center, Beijing Golden Star Duck Inc., Beijing, China
| | - Fang-Xi Yang
- Duck Industry Center, Beijing Golden Star Duck Inc., Beijing, China
| | - Zhuo-Cheng Hou
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, Department of Animal Genetics and Breeding, China Agricultural University, Beijing, China
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23
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Fonseca LD, Eler JP, Pereira MA, Rosa AF, Alexandre PA, Moncau CT, Salvato F, Rosa-Fernandes L, Palmisano G, Ferraz JBS, Fukumasu H. Liver proteomics unravel the metabolic pathways related to Feed Efficiency in beef cattle. Sci Rep 2019; 9:5364. [PMID: 30926873 PMCID: PMC6441086 DOI: 10.1038/s41598-019-41813-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 03/19/2019] [Indexed: 12/11/2022] Open
Abstract
Improving nutrient utilization efficiency is essential for livestock, given the current scenario of increasing demand for animal protein and sustainable resource use. In this context, understanding the biology of feed efficiency (FE) in beef cattle allows the development of markers for identification and selection of best animals for animal production. Thus, 98 young Nellore bulls were evaluated for FE and at the end of the experiment liver samples from six High Feed Efficient (HFE) and six Low Feed Efficient (LFE) animals were collected for protein extraction, digestion and analysis by HPLC-MS/MS. Data were analyzed for differential abundant proteins (DAPs), protein networks, and functional enrichment. Serum endotoxin was also quantified. We found 42 DAPs and 3 protein networks significantly related to FE. The main pathways associated with FE were: microbial metabolism; biosynthesis of fatty acids, amino acids and vitamins; glycolysis/gluconeogenesis; xenobiotic metabolism and; antigen processing and presentation. Serum endotoxins were significantly higher in LFE animals supporting the results. Therefore, the findings presented here confirmed the altered hepatic metabolism and pronounced hepatic inflammation in LFE animals supporting that the increased bacterial load is at least in part responsible for the hepatic lesions and inflammation in LFE animals.
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Affiliation(s)
- Leydiana D Fonseca
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Joanir P Eler
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Mikaele A Pereira
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Alessandra F Rosa
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Pâmela A Alexandre
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Cristina T Moncau
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Fernanda Salvato
- Institute of Biology, State University of Campinas, Campinas, 13083-862, Brazil
| | - Livia Rosa-Fernandes
- Department of Parasitology, Biomedical Sciences Institute, University of São Paulo, São Paulo, 05508-900, Brazil
| | - Giuseppe Palmisano
- Department of Parasitology, Biomedical Sciences Institute, University of São Paulo, São Paulo, 05508-900, Brazil
| | - José B S Ferraz
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil
| | - Heidge Fukumasu
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635-900, Brazil.
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24
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Alexandre PA, Naval-Sanchez M, Porto-Neto LR, Ferraz JBS, Reverter A, Fukumasu H. Systems Biology Reveals NR2F6 and TGFB1 as Key Regulators of Feed Efficiency in Beef Cattle. Front Genet 2019; 10:230. [PMID: 30967894 PMCID: PMC6439317 DOI: 10.3389/fgene.2019.00230] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 03/04/2019] [Indexed: 11/20/2022] Open
Abstract
Systems biology approaches are used as strategy to uncover tissue-specific perturbations and regulatory genes related to complex phenotypes. We applied this approach to study feed efficiency (FE) in beef cattle, an important trait both economically and environmentally. Poly-A selected RNA of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle and pituitary) of eighteen young bulls, selected for high and low FE, were sequenced (Illumina HiSeq 2500, 100 bp, pared-end). From the 17,354 expressed genes considering all tissues, 1,335 were prioritized by five selection categories (differentially expressed, harboring SNPs associated with FE, tissue-specific, secreted in plasma and key regulators) and used for network construction. NR2F6 and TGFB1 were identified and validated by motif discovery as key regulators of hepatic inflammatory response and muscle tissue development, respectively, two biological processes demonstrated to be associated with FE. Moreover, we indicated potential biomarkers of FE, which are related to hormonal control of metabolism and sexual maturity. By using robust methodologies and validation strategies, we confirmed the main biological processes related to FE in Bos indicus and indicated candidate genes as regulators or biomarkers of superior animals.
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Affiliation(s)
- Pâmela A. Alexandre
- Department of Veterinary Medicine, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Marina Naval-Sanchez
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Laercio R. Porto-Neto
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - José Bento S. Ferraz
- Department of Veterinary Medicine, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Antonio Reverter
- Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia
| | - Heidge Fukumasu
- Department of Veterinary Medicine, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
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25
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Leão J, Coelho S, Machado F, Azevedo R, Lima J, Carneiro J, Lage C, Ferreira A, Pereira L, Tomich T, Campos M. Phenotypically divergent classification of preweaned heifer calves for feed efficiency indexes and their correlations with heat production and thermography. J Dairy Sci 2018. [DOI: 10.3168/jds.2017-14109] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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26
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Prospecting genes associated with navel length, coat and scrotal circumference traits in Canchim cattle. Livest Sci 2018. [DOI: 10.1016/j.livsci.2018.02.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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27
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Effect of dietary restriction and subsequent re-alimentation on the transcriptional profile of bovine jejunal epithelium. PLoS One 2018; 13:e0194445. [PMID: 29554113 PMCID: PMC5858768 DOI: 10.1371/journal.pone.0194445] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 03/02/2018] [Indexed: 11/19/2022] Open
Abstract
Compensatory growth (CG), an accelerated growth phenomenon which occurs following a period of dietary restriction is utilised worldwide in animal production systems as a management practise to lower feed costs. The objective of this study was to evaluate the contribution of jejunal epithelial to CG in cattle through transcriptional profiling following a period of dietary restriction as well as subsequent re-alimentation induced CG. Sixty Holstein Friesian bulls were separated into two groups; RES and ADLIB, with 30 animals in each. RES animals were offered a restricted diet for 125 days (Period 1) followed by ad libitum feeding for 55 days (Period 2). ADLIB animals had ad libitum access to feed across both periods 1 and 2. At the end of each period, 15 animals from each treatment group were slaughtered, jejunal epithelium collected and RNAseq analysis performed. Animals that were previously diet restricted underwent CG, gaining 1.8 times the rate of their non-restricted counterparts. Twenty-four genes were differentially expressed in RES compared to ADLIB animals at the end of Period 1, with only one gene, GSTA1, differentially expressed between the two groups at the end of Period 2. When analysed within treatment (RES, Period 2 v Period 1), 31 genes were differentially expressed between diet restricted and animals undergoing CG. Dietary restriction and subsequent re-alimentation were associated with altered expression of genes involved in digestion and metabolism as well as those involved in cellular division and growth. Compensatory growth was also associated with greater expression of genes involved in cellular protection and detoxification in jejunal epithelium. This study highlights some of the molecular mechanisms regulating the response to dietary restriction and subsequent re-alimentation induced CG in cattle; however the gene expression results suggest that most of the CG in jejunal epithelium had occurred by day 55 of re-alimentation.
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28
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Lu Y, Vandehaar MJ, Spurlock DM, Weigel KA, Armentano LE, Connor EE, Coffey M, Veerkamp RF, de Haas Y, Staples CR, Wang Z, Hanigan MD, Tempelman RJ. Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. J Dairy Sci 2018; 101:3140-3154. [PMID: 29395135 DOI: 10.3168/jds.2017-13364] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 11/27/2017] [Indexed: 11/19/2022]
Abstract
Genome-wide association (GWA) of feed efficiency (FE) could help target important genomic regions influencing FE. Data provided by an international dairy FE research consortium consisted of phenotypic records on dry matter intakes (DMI), milk energy (MILKE), and metabolic body weight (MBW) on 6,937 cows from 16 stations in 4 counties. Of these cows, 4,916 had genotypes on 57,347 single nucleotide polymorphism (SNP) markers. We compared a GWA analysis based on the more classical residual feed intake (RFI) model with one based on a previously proposed multiple trait (MT) approach for modeling FE using an alternative measure (DMI|MILKE,MBW). Both models were based on a single-step genomic BLUP procedure that allowed the use of phenotypes from both genotyped and nongenotyped cows. Estimated effects for single SNP markers were small and not statistically important but virtually identical for either FE measure (RFI vs. DMI|MILKE,MBW). However, upon further refining this analysis to develop joint tests within nonoverlapping 1-Mb windows, significant associations were detected between either measure of FE with a window on each of Bos taurus autosomes BTA12 and BTA26. There was, as expected, no overlap between detected genomic regions for DMI|MILKE,MBW and genomic regions influencing the energy sink traits (i.e., MILKE and MBW) because of orthogonal relationships clearly defined between the various traits. Conversely, GWA inferences on DMI can be demonstrated to be partly driven by genetic associations between DMI with these same energy sink traits, thereby having clear implications when comparing GWA studies on DMI to GWA studies on FE-like measures such as RFI.
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Affiliation(s)
- Y Lu
- Department of Animal Science, Michigan State University, East Lansing 48824
| | - M J Vandehaar
- Department of Animal Science, Michigan State University, East Lansing 48824
| | - D M Spurlock
- Department of Animal Science, Iowa State University, Ames 50011
| | - K A Weigel
- Department of Dairy Science, University of Wisconsin, Madison 53706
| | - L E Armentano
- Department of Dairy Science, University of Wisconsin, Madison 53706
| | - E E Connor
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705
| | - M Coffey
- Animal and Veterinary Sciences Group, Scotland's Rural College (SRUC), Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom
| | - R F Veerkamp
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH Wageningen, the Netherlands
| | - Y de Haas
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 6700 AH Wageningen, the Netherlands
| | - C R Staples
- Department of Animal Sciences, University of Florida, Gainesville 32611
| | - Z Wang
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5 Canada
| | - M D Hanigan
- Department of Dairy Science, Virginia Tech, Blacksburg 24061
| | - R J Tempelman
- Department of Animal Science, Michigan State University, East Lansing 48824.
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29
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Liu J, Liu R, Wang J, Zhang Y, Xing S, Zheng M, Cui H, Li Q, Li P, Cui X, Li W, Zhao G, Wen J. Exploring Genomic Variants Related to Residual Feed Intake in Local and Commercial Chickens by Whole Genomic Resequencing. Genes (Basel) 2018; 9:genes9020057. [PMID: 29364149 PMCID: PMC5852553 DOI: 10.3390/genes9020057] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 12/20/2017] [Accepted: 01/02/2018] [Indexed: 02/01/2023] Open
Abstract
Improving feed efficiency is a major goal in poultry production to reduce production costs and increase profitability. The genomic variants and possible molecular mechanisms responsible for residual feed intake (RFI) in chickens, however, remain poorly understood. In this study, using both local and commercial breeds, genome re-sequencing of low RFI and high RFI chickens was performed to elucidate the genomic variants underlying RFI. Results showed that 8,505,214 and 8,479,041 single nucleotide polymorphisms (SNPs) were detected in low and high RFI Beijing-You chickens, respectively; 8,352,008 and 8,372,769 SNPs were detected in low- and high-RFI Cobb chickens, respectively. Through a series of filtering processes, 3746 candidate SNPs assigned to 1137 genes in Beijing-You chickens and 575 candidate SNPs (448 genes) in Cobb chickens were found. The validation of the selected 191 SNPs showed that 46 SNPs were significantly associated with the RFI in an independent population of 779 Cobb chickens, suggesting that the method of screening associated SNPs with whole genome sequencing (WGS) strategy was reasonable. Functions annotation of RFI-related genes indicated that genes in Beijing-You were enriched in lipid and carbohydrate metabolism, as well as the phosphatase and tensin homolog (PTEN) signaling pathway. In Cobb, however, RFI-related genes were enriched in the feed behavior process and cAMP responsive element binding protein (CREB) signaling pathway. For both breeds, organismal development physiological processes were enriched. Correspondingly, NOS1, PHKG1, NEU3 and PIP5K1B were differentially expressed in Beijing-You, while CDC42, CSK, PIK3R3, CAMK4 and PLCB4 were differentially expressed in Cobb, suggesting that these might be key genes that contribute to RFI. The results of the present study identified numerous novel SNPs for RFI, which provide candidate biomarkers for use in the genetic selection for RFI. The study has improved knowledge of the genomic variants and potential biological pathways underlying RFI in chickens.
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Affiliation(s)
- Jie Liu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Ranran Liu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Jie Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Yonghong Zhang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- College of Animal Science, Jilin University, Changchun 130062, China.
| | - Siyuan Xing
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Maiqing Zheng
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Huanxian Cui
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Qinghe Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Peng Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Xiaoyan Cui
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Wei Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Guiping Zhao
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
| | - Jie Wen
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
- State Key Laboratory of Animal Nutrition, Beijing 100193, China.
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Genomic dissection and prediction of feed intake and residual feed intake traits using a longitudinal model in F2 chickens. Animal 2017; 12:1792-1798. [PMID: 29268803 DOI: 10.1017/s1751731117003354] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Feed efficiency traits (FETs) are important economic indicators in poultry production. Because feed intake (FI) is a time-dependent variable, longitudinal models can provide insights into the genetic basis of FET variation over time. It is expected that the application of longitudinal models as part of genome-wide association (GWA) and genomic selection (i.e. genome-wide selection (GS)) studies will lead to an increase in accuracy of selection. Thus, the objectives of this study were to evaluate the accuracy of estimated breeding values (EBVs) based on pedigree as well as high-density single nucleotide polymorphism (SNP) genotypes, and to conduct a GWA study on longitudinal FI and residual feed intake (RFI) in a total of 312 chickens with phenotype and genotype in the F2 population. The GWA and GS studies reported in this paper were conducted using β-spline random regression models for FI and RFI traits in a chicken F2 population, with FI and BW recorded for each bird weekly between 2 and 10 weeks of age. A single SNP regression approach was used on spline coefficients for weekly FI and RFI traits, with results showing that two significant SNPs for FI occur in the synuclein (SNCAIP) gene. Results also show that these regions are significantly associated with the spline coefficients (q 2) for 5- and 6-week-old birds, while GWA study results showed no SNP association with RFI in F2 chickens. Estimated breeding value predictions obtained using a pedigree-based best linear unbiased prediction (ABLUP) model were then compared with predictions based on genomic best linear unbiased prediction (GBLUP). The accuracy was measured as correlation between genomic EBV and EBV with the phenotypic value corrected for fixed effects divided by the square root of heritability. The regression of observed on predicted values was used to estimate bias of methods. Results show that prediction accuracies using GBLUP and ABLUP for the FI measured from 2nd to 10th week were between 0.06 and 0.46 and 0.03 and 0.37, respectively. These results demonstrate that genomic methods are able to increase the accuracy of predicted breeding values at later ages on the basis of both traits, and indicate that use of a longitudinal model can improve selection accuracy for the trajectory of traits in F2 chickens when compared with conventional methods.
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Hardie L, VandeHaar M, Tempelman R, Weigel K, Armentano L, Wiggans G, Veerkamp R, de Haas Y, Coffey M, Connor E, Hanigan M, Staples C, Wang Z, Dekkers J, Spurlock D. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. J Dairy Sci 2017; 100:9061-9075. [DOI: 10.3168/jds.2017-12604] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 07/12/2017] [Indexed: 12/16/2022]
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32
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Dai P, Luan S, Lu X, Luo K, Kong J. Comparative transcriptome analysis of the Pacific White Shrimp (Litopenaeus vannamei) muscle reveals the molecular basis of residual feed intake. Sci Rep 2017; 7:10483. [PMID: 28874698 PMCID: PMC5585345 DOI: 10.1038/s41598-017-10475-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 08/10/2017] [Indexed: 01/29/2023] Open
Abstract
Feed efficiency is an economically important trait in genetic improvement programs of L. vannamei. Residual feed intake (RFI), an ideal measure of feed efficiency, is the difference between observed feed intake and expected feed requirement predicted from maintenance and production. Exploring the molecular basis of RFI is essential to facilitate the genetic breeding of feed efficiency in L. vannamei. However, few studies have been reported in this aspect. In this study, we sequenced muscle transcriptomes of a high-efficiency group, a low-efficiency group and a control group originating from two families, and compared the gene expression patterns between each extreme group and the control group. A total of 383 differentially expressed genes were identified, most of which were involved in cell proliferation, growth and signaling, glucose homeostasis, energy and nutrients metabolism. Functional enrichment analysis of these genes revealed 13 significantly enriched biological pathways, including signaling pathways such as PI3K-Akt signaling pathway, AMPK signaling pathway and mTOR signaling pathway, as well as some important pathways such as ubiquitin mediated proteolysis, cell cycle, pentose phosphate pathway and glycolysis/gluconeogenesis. These genes and pathways provide initial insight into the molecular mechanisms driving the feed efficiency in L. vannamei.
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Affiliation(s)
- Ping Dai
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266235, China
| | - Sheng Luan
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266235, China
| | - Xia Lu
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266235, China
| | - Kun Luo
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266235, China
| | - Jie Kong
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266235, China.
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Gilbert H, Billon Y, Brossard L, Faure J, Gatellier P, Gondret F, Labussière E, Lebret B, Lefaucheur L, Le Floch N, Louveau I, Merlot E, Meunier-Salaün MC, Montagne L, Mormede P, Renaudeau D, Riquet J, Rogel-Gaillard C, van Milgen J, Vincent A, Noblet J. Review: divergent selection for residual feed intake in the growing pig. Animal 2017; 11:1427-1439. [PMID: 28118862 PMCID: PMC5561440 DOI: 10.1017/s175173111600286x] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 12/13/2016] [Indexed: 12/22/2022] Open
Abstract
This review summarizes the results from the INRA (Institut National de la Recherche Agronomique) divergent selection experiment on residual feed intake (RFI) in growing Large White pigs during nine generations of selection. It discusses the remaining challenges and perspectives for the improvement of feed efficiency in growing pigs. The impacts on growing pigs raised under standard conditions and in alternative situations such as heat stress, inflammatory challenges or lactation have been studied. After nine generations of selection, the divergent selection for RFI led to highly significant (P<0.001) line differences for RFI (-165 g/day in the low RFI (LRFI) line compared with high RFI line) and daily feed intake (-270 g/day). Low responses were observed on growth rate (-12.8 g/day, P<0.05) and body composition (+0.9 mm backfat thickness, P=0.57; -2.64% lean meat content, P<0.001) with a marked response on feed conversion ratio (-0.32 kg feed/kg gain, P<0.001). Reduced ultimate pH and increased lightness of the meat (P<0.001) were observed in LRFI pigs with minor impact on the sensory quality of the meat. These changes in meat quality were associated with changes of the muscular energy metabolism. Reduced maintenance energy requirements (-10% after five generations of selection) and activity (-21% of time standing after six generations of selection) of LRFI pigs greatly contributed to the gain in energy efficiency. However, the impact of selection for RFI on the protein metabolism of the pig remains unclear. Digestibility of energy and nutrients was not affected by selection, neither for pigs fed conventional diets nor for pigs fed high-fibre diets. A significant improvement of digestive efficiency could likely be achieved by selecting pigs on fibre diets. No convincing genetic or blood biomarker has been identified for explaining the differences in RFI, suggesting that pigs have various ways to achieve an efficient use of feed. No deleterious impact of the selection on the sow reproduction performance was observed. The resource allocation theory states that low RFI may reduce the ability to cope with stressors, via the reduction of a buffer compartment dedicated to responses to stress. None of the experiments focussed on the response of pigs to stress or challenges could confirm this theory. Understanding the relationships between RFI and responses to stress and energy demanding processes, as such immunity and lactation, remains a major challenge for a better understanding of the underlying biological mechanisms of the trait and to reconcile the experimental results with the resource allocation theory.
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Affiliation(s)
- H. Gilbert
- GenPhySE, INRA, INP,
ENSAT, Université de Toulouse,
31326 Castanet-Tolosan, France
| | - Y. Billon
- GenESI, INRA, 17700
Surgères, France
| | - L. Brossard
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - J. Faure
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - P. Gatellier
- QuaPA, INRA, 63122 Saint
Genès-Champanelle, France
| | - F. Gondret
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - E. Labussière
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - B. Lebret
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - L. Lefaucheur
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - N. Le Floch
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - I. Louveau
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - E. Merlot
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | | | - L. Montagne
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - P. Mormede
- GenPhySE, INRA, INP,
ENSAT, Université de Toulouse,
31326 Castanet-Tolosan, France
| | - D. Renaudeau
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - J. Riquet
- GenPhySE, INRA, INP,
ENSAT, Université de Toulouse,
31326 Castanet-Tolosan, France
| | - C. Rogel-Gaillard
- GABI, INRA,
AgroParisTech, Université Paris-Saclay,
78350 Jouy-en-Josas Cedex, France
| | - J. van Milgen
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - A. Vincent
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
| | - J. Noblet
- PEGASE, INRA, Agrocampus
Ouest, 35590 Saint-Gilles, France
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Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle. BMC Genomics 2017; 18:386. [PMID: 28521758 PMCID: PMC5437562 DOI: 10.1186/s12864-017-3754-y] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2016] [Accepted: 05/03/2017] [Indexed: 11/13/2022] Open
Abstract
Background Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations. Results Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but < 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained). Conclusions Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3754-y) contains supplementary material, which is available to authorized users.
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Judge MM, Purfield DC, Sleator RD, Berry DP. The impact of multi-generational genotype imputation strategies on imputation accuracy and subsequent genomic predictions. J Anim Sci 2017; 95:1489-1501. [PMID: 28464096 DOI: 10.2527/jas.2016.1212] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The objective of the present study was to quantify, using simulations, the impact of successive generations of genotype imputation on genomic predictions. The impact of using a small reference population of true genotypes versus a larger reference population of imputed genotypes on the accuracy of genomic predictions was also investigated. After construction of a founder population, high-density (HD) genotypes ( = 43,500 single nucleotide polymorphisms, SNP) were simulated across 25 generations ( = 46,800 per generation); a low-density genotype panel ( = 3,000 SNP) was developed from these HD genotypes, which was then used to impute genotypes using 7 alternative imputation strategies. Both low (0.03) and moderately (0.35) heritable phenotypes were simulated. Direct genomic values (DGV) were estimated using imputed genotypes from the investigated scenarios and the accuracy of predicting the simulated true breeding values (TBV) were expressed relative to the accuracy when the true genotypes were used. Mean allele concordance rate and the rate of change in mean allele concordance per generation differed between the imputation strategies investigated. Imputation was most accurate when the true HD genotypes of sires and 50% of the dams of the generation being imputed were included in the reference population; the average allele concordance rate for this scenario across generations was 0.9707. The strongest correlation between the TBV and DGV of the last generation was when the reference population included sequentially imputed HD genotypes of all previous generations, plus the true HD genotypes of all sires of the previous generations (0.987 as efficient as when the true genotypes were used in the reference population). With a moderate heritability, the correlation between the TBV and the DGV using a small reference population of accurate genotypes were, on average, 0.07 units stronger compared to DGV generated using a larger population of imputed genotypes. When the heritability was low, the accuracy of genomic predictions benefited from a larger reference population, even if SNP were imputed. The impact on the accuracy of genomic predictions from the accumulation of imputation errors across generations indicates the need to routinely generate HD genotypes on influential animals to reduce the accumulation of imputation errors over generations.
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Liu T, Luo C, Wang J, Ma J, Shu D, Lund MS, Su G, Qu H. Assessment of the genomic prediction accuracy for feed efficiency traits in meat-type chickens. PLoS One 2017; 12:e0173620. [PMID: 28278209 PMCID: PMC5344482 DOI: 10.1371/journal.pone.0173620] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 02/23/2017] [Indexed: 11/19/2022] Open
Abstract
Feed represents the major cost of chicken production. Selection for improving feed utilization is a feasible way to reduce feed cost and greenhouse gas emissions. The objectives of this study were to investigate the efficiency of genomic prediction for feed conversion ratio (FCR), residual feed intake (RFI), average daily gain (ADG) and average daily feed intake (ADFI) and to assess the impact of selection for feed efficiency traits FCR and RFI on eviscerating percentage (EP), breast muscle percentage (BMP) and leg muscle percentage (LMP) in meat-type chickens. Genomic prediction was assessed using a 4-fold cross-validation for two validation scenarios. The first scenario was a random family sampling validation (CVF), and the second scenario was a random individual sampling validation (CVR). Variance components were estimated based on the genomic relationship built with single nucleotide polymorphism markers. Genomic estimated breeding values (GEBV) were predicted using a genomic best linear unbiased prediction model. The accuracies of GEBV were evaluated in two ways: the correlation between GEBV and corrected phenotypic value divided by the square root of heritability, i.e., the correlation-based accuracy, and model-based theoretical accuracy. Breeding values were also predicted using a conventional pedigree-based best linear unbiased prediction model in order to compare accuracies of genomic and conventional predictions. The heritability estimates of FCR and RFI were 0.29 and 0.50, respectively. The heritability estimates of ADG, ADFI, EP, BMP and LMP ranged from 0.34 to 0.53. In the CVF scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR were slightly higher than those for RFI. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.360, 0.284, 0.574 and 0.520, respectively, and the model-based theoretical accuracies were 0.420, 0.414, 0.401 and 0.382, respectively. In the CVR scenario, the correlation-based accuracy and the theoretical accuracy of genomic prediction for FCR was lower than RFI, which was different from the CVF scenario. The correlation-based accuracies for FCR, RFI, ADG and ADFI were 0.449, 0.593, 0.581 and 0.627, respectively, and the model-based theoretical accuracies were 0.577, 0.629, 0.631 and 0.638, respectively. The accuracies of genomic predictions were 0.371 and 0.322 higher than the conventional pedigree-based predictions for the CVF and CVR scenarios, respectively. The genetic correlations of FCR with EP, BMP and LMP were -0.427, -0.156 and -0.338, respectively. The correlations between RFI and the three carcass traits were -0.320, -0.404 and -0.353, respectively. These results indicate that RFI and FCR have a moderate accuracy of genomic prediction. Improving RFI and FCR could be favourable for EP, BMP and LMP. Compared with FCR, which can be improved by selection for ADG in typical meat-type chicken breeding programs, selection for RFI could lead to extra improvement in feed efficiency.
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Affiliation(s)
- Tianfei Liu
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangzhou, China
| | - Chenglong Luo
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangzhou, China
| | - Jie Wang
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangzhou, China
| | - Jie Ma
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- Guangdong Key Laboratory of Animal Breeding and Nutrition, Guangzhou, China
| | - Dingming Shu
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangzhou, China
| | - Mogens Sandø Lund
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Denmark
| | - Guosheng Su
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Denmark
| | - Hao Qu
- Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, China
- State Key Laboratory of Livestock and Poultry Breeding, Guangzhou, China
- * E-mail:
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Tizioto PC, Coutinho LL, Oliveira PSN, Cesar ASM, Diniz WJS, Lima AO, Rocha MI, Decker JE, Schnabel RD, Mourão GB, Tullio RR, Zerlotini A, Taylor JF, Regitano LCA. Gene expression differences in Longissimus muscle of Nelore steers genetically divergent for residual feed intake. Sci Rep 2016; 6:39493. [PMID: 28004777 PMCID: PMC5177880 DOI: 10.1038/srep39493] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Accepted: 11/24/2016] [Indexed: 12/18/2022] Open
Abstract
Residual feed intake (RFI), a measure of feed efficiency (FE), is defined as the difference between the observed and the predictable feed intake considering size and growth of the animal. It is extremely important to beef production systems due to its impact on the allocation of land areas to alternative agricultural production, animal methane emissions, food demand and cost of production. Global differential gene expression analysis between high and low RFI groups (HRFI and LRFI: less and more efficient, respectively) revealed 73 differentially expressed (DE) annotated genes in Longissimus thoracis (LT) muscle of Nelore steers. These genes are involved in the overrepresented pathways Metabolism of Xenobiotics by Cytochrome P450 and Butanoate and Tryptophan Metabolism. Among the DE transcripts were several proteins related to mitochondrial function and the metabolism of lipids. Our findings indicate that observed gene expression differences are primarily related to metabolic processes underlying oxidative stress. Genes involved in the metabolism of xenobiotics and antioxidant mechanisms were primarily down-regulated, while genes responsible for lipid oxidation and ketogenesis were up-regulated in HRFI group. By using LT muscle, this study reinforces our previous findings using liver tissue and reveals new genes and likely tissue-specific regulators playing key-roles in these processes.
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Affiliation(s)
- Polyana C Tizioto
- Embrapa Pecuária Sudeste, São Carlos, SP, Brazil.,Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
| | | | - Aline S M Cesar
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
| | - Wellison J S Diniz
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Andressa O Lima
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Marina I Rocha
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.,Informatics Institute, University of Missouri, Columbia, Missouri, 65211, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.,Informatics Institute, University of Missouri, Columbia, Missouri, 65211, USA
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil
| | | | | | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA
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Olivieri BF, Mercadante MEZ, Cyrillo JNDSG, Branco RH, Bonilha SFM, de Albuquerque LG, Silva RMDO, Baldi F. Genomic Regions Associated with Feed Efficiency Indicator Traits in an Experimental Nellore Cattle Population. PLoS One 2016; 11:e0164390. [PMID: 27760167 PMCID: PMC5070821 DOI: 10.1371/journal.pone.0164390] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 09/23/2016] [Indexed: 01/18/2023] Open
Abstract
The objective of this study was to identify genomic regions and metabolic pathways associated with dry matter intake, average daily gain, feed efficiency and residual feed intake in an experimental Nellore cattle population. The high-density SNP chip (Illumina High-Density Bovine BeadChip, 777k) was used to genotype the animals. The SNP markers effects and their variances were estimated using the single-step genome wide association method. The (co)variance components were estimated by Bayesian inference. The chromosome segments that are responsible for more than 1.0% of additive genetic variance were selected to explore and determine possible quantitative trait loci. The bovine genome Map Viewer was used to identify genes. In total, 51 genomic regions were identified for all analyzed traits. The heritability estimated for feed efficiency was low magnitude (0.13±0.06). For average daily gain, dry matter intake and residual feed intake, heritability was moderate to high (0.43±0.05; 0.47±0.05, 0.18±0.05, respectively). A total of 8, 17, 14 and 12 windows that are responsible for more than 1% of the additive genetic variance for dry matter intake, average daily gain, feed efficiency and residual feed intake, respectively, were identified. Candidate genes GOLIM4, RFX6, CACNG7, CACNG6, CAPN8, CAPN2, AKT2, GPRC6A, and GPR45 were associated with feed efficiency traits. It was expected that the response to selection would be higher for residual feed intake than for feed efficiency. Genomic regions harboring possible QTL for feed efficiency indicator traits were identified. Candidate genes identified are involved in energy use, metabolism protein, ion transport, transmembrane transport, the olfactory system, the immune system, secretion and cellular activity. The identification of these regions and their respective candidate genes should contribute to the formation of a genetic basis in Nellore cattle for feed efficiency indicator traits, and these results would support the selection for these traits.
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Affiliation(s)
- Bianca Ferreira Olivieri
- Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Zootecnia, Via de acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil
| | - Maria Eugênia Zerlotti Mercadante
- Instituto de Zootecnia, Centro Avançado de Pesquisa Tecnológica do Agronegócio de Bovinos de Corte, Rodovia Carlos Tonanni, km 94, CEP 14.174-000, Sertãozinho, SP, Brazil
| | | | - Renata Helena Branco
- Instituto de Zootecnia, Centro Avançado de Pesquisa Tecnológica do Agronegócio de Bovinos de Corte, Rodovia Carlos Tonanni, km 94, CEP 14.174-000, Sertãozinho, SP, Brazil
| | - Sarah Figueiredo Martins Bonilha
- Instituto de Zootecnia, Centro Avançado de Pesquisa Tecnológica do Agronegócio de Bovinos de Corte, Rodovia Carlos Tonanni, km 94, CEP 14.174-000, Sertãozinho, SP, Brazil
| | - Lucia Galvão de Albuquerque
- Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Zootecnia, Via de acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil
| | - Rafael Medeiros de Oliveira Silva
- Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Zootecnia, Via de acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil
| | - Fernando Baldi
- Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Departamento de Zootecnia, Via de acesso Prof. Paulo Donato Castellane, s/no, CEP 14884-900 Jaboticabal, SP, Brazil
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Júnior GAF, Costa RB, de Camargo GMF, Carvalheiro R, Rosa GJM, Baldi F, Garcia DA, Gordo DGM, Espigolan R, Takada L, Magalhães AFB, Bresolin T, Feitosa FLB, Chardulo LAL, de Oliveira HN, de Albuquerque LG. Genome scan for postmortem carcass traits in Nellore cattle1. J Anim Sci 2016; 94:4087-4095. [DOI: 10.2527/jas.2016-0632] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
| | - R. B. Costa
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - G. M. F. de Camargo
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - R. Carvalheiro
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
- CNPq, Brasília, DF, Brazil
| | | | - F. Baldi
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
- CNPq, Brasília, DF, Brazil
| | - D. A. Garcia
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - D. G. M. Gordo
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - R. Espigolan
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - L. Takada
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - A. F. B. Magalhães
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - T. Bresolin
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - F. L. B. Feitosa
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
| | - L. A. L. Chardulo
- Faculdade de Medicina Veterinária e Zootecnia, UNESP, Botucatu, SP 18618-970, Brazil
- CNPq, Brasília, DF, Brazil
| | - H. N. de Oliveira
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
- CNPq, Brasília, DF, Brazil
| | - L. G. de Albuquerque
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, SP 14884-000, Brazil
- CNPq, Brasília, DF, Brazil
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40
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Xu Z, Ji C, Zhang Y, Zhang Z, Nie Q, Xu J, Zhang D, Zhang X. Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens. BMC Genomics 2016; 17:594. [PMID: 27506765 PMCID: PMC4979145 DOI: 10.1186/s12864-016-2861-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2016] [Accepted: 06/29/2016] [Indexed: 01/07/2023] Open
Abstract
Background Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in RFI in quality chickens are unclear. Therefore, a genome-wide association study (GWAS) and RNA sequencing were performed on RFI to identify genetic variants and potential candidate genes associated with energy improvement. Results A lower average daily feed intake was found in low-RFI birds compared to high-RFI birds. The heritability of RFI measured from 44 to 83 d of age was 0.35. GWAS showed that 32 of the significant single nucleotide polymorphisms (SNPs) associated with the RFI (P < 10−4) accounted for 53.01 % of the additive genetic variance. More than half of the effective SNPs were located in a 1 Mb region (16.3–17.3 Mb) of chicken (Gallus gallus) chromosome (GGA) 12. Thus, focusing on this region should enable a deeper understanding of energy utilization. RNA sequencing was performed to profile the liver transcriptomes of four male chickens selected from the high and low tails of the RFI. One hundred and sixteen unique genes were identified as differentially expressed genes (DEGs). Some of these genes were relevant to appetite, cell activities, and fat metabolism, such as CCKAR, HSP90B1, and PCK1. Some potential genes within the 500 Kb flanking region of the significant RFI-related SNPs detected in GWAS (i.e., MGP, HIST1H110, HIST1H2A4L3, OC3, NR0B2, PER2, ST6GALNAC2, and G0S2) were also identified as DEGs in chickens with divergent RFIs. Conclusions The GWAS findings showed that the 1 Mb narrow region of GGA12 should be important because it contained genes involved in energy-consuming processes, such as lipogenesis, social behavior, and immunity. Similar results were obtained in the transcriptome sequencing experiments. In general, low-RFI birds seemed to optimize energy employment by reducing energy expenditure in cell activities, immune responses, and physical activity compared to eating. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2861-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zhenqiang Xu
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.,Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Congliang Ji
- Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Yan Zhang
- Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Qinghua Nie
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Jiguo Xu
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China
| | - Dexiang Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.,Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu, 527400, China
| | - Xiquan Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642, Guangdong Province, China.
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de Almeida Santana MH, Junior GAO, Cesar ASM, Freua MC, da Costa Gomes R, da Luz E Silva S, Leme PR, Fukumasu H, Carvalho ME, Ventura RV, Coutinho LL, Kadarmideen HN, Ferraz JBS. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle. J Appl Genet 2016; 57:495-504. [PMID: 27001052 DOI: 10.1007/s13353-016-0344-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Revised: 01/20/2016] [Accepted: 03/02/2016] [Indexed: 10/22/2022]
Abstract
The use of genome-wide association results combined with other genomic approaches may uncover genes and metabolic pathways related to complex traits. In this study, the phenotypic and genotypic data of 1475 Nellore (Bos indicus) cattle and 941,033 single nucleotide polymorphisms (SNPs) were used for genome-wide association study (GWAS) and copy number variations (CNVs) analysis in order to identify candidate genes and putative pathways involved with the feed conversion ratio (FCR). The GWAS was based on the Bayes B approach analyzing genomic windows with multiple regression models to estimate the proportion of genetic variance explained by each window. The CNVs were detected with PennCNV software using the log R ratio and B allele frequency data. CNV regions (CNVRs) were identified with CNVRuler and a linear regression was used to associate CNVRs and the FCR. Functional annotation of associated genomic regions was performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) and the metabolic pathways were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG). We showed five genomic windows distributed over chromosomes 4, 6, 7, 8, and 24 that explain 12 % of the total genetic variance for FCR, and detected 12 CNVRs (chromosomes 1, 5, 7, 10, and 12) significantly associated [false discovery rate (FDR) < 0.05] with the FCR. Significant genomic regions (GWAS and CNV) harbor candidate genes involved in pathways related to energetic, lipid, and protein metabolism. The metabolic pathways found in this study are related to processes directly connected to feed efficiency in beef cattle. It was observed that, even though different genomic regions and genes were found between the two approaches (GWAS and CNV), the metabolic processes covered were related to each other. Therefore, a combination of the approaches complement each other and lead to a better understanding of the FCR.
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Affiliation(s)
- Miguel Henrique de Almeida Santana
- Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg, Denmark.,Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | | | | | - Mateus Castelani Freua
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | - Rodrigo da Costa Gomes
- Empresa Brasileira de Pesquisa Agropecuária, CNPGC/EMBRAPA, BR 262 km 4, 79002-970, Campo Grande, Brazil
| | - Saulo da Luz E Silva
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | - Paulo Roberto Leme
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | - Heidge Fukumasu
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | - Minos Esperândio Carvalho
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
| | - Ricardo Vieira Ventura
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil.,University of Guelph, 50 Stone Road East, Guelph, Ontario, N1G 2W1, Canada
| | - Luiz Lehmann Coutinho
- Escola Superior de Agricultura Luiz de Queiroz, University of São Paulo, 13418-900, Piracicaba, Brazil
| | - Haja N Kadarmideen
- Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg, Denmark
| | - José Bento Sterman Ferraz
- Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, 13635-900, Pirassununga, Brazil
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42
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Cohen-Zinder M, Asher A, Lipkin E, Feingersch R, Agmon R, Karasik D, Brosh A, Shabtay A. FABP4 is a leading candidate gene associated with residual feed intake in growing Holstein calves. Physiol Genomics 2016; 48:367-76. [PMID: 26993365 DOI: 10.1152/physiolgenomics.00121.2015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 03/09/2016] [Indexed: 01/08/2023] Open
Abstract
Ecological and economic concerns drive the need to improve feed utilization by domestic animals. Residual feed intake (RFI) is one of the most acceptable measures for feed efficiency (FE). However, phenotyping RFI-related traits is complex and expensive and requires special equipment. Advances in marker technology allow the development of various DNA-based selection tools. To assimilate these technologies for the benefit of RFI-based selection, reliable phenotypic measures are prerequisite. In the current study, we identified single nucleotide polymorphisms (SNPs) associated with RFI phenotypic consistency across different ages and diets (named RFI 1-3), using DNA samples of high or low RFI ranked Holstein calves. Using targeted sequencing of chromosomal regions associated with FE- and RFI-related traits, we identified 48 top SNPs significantly associated with at least one of three defined RFIs. Eleven of these SNPs were harbored by the fatty acid binding protein 4 (FABP4). While 10 significant SNPs found in FABP4 were common for RFI 1 and RFI 3, one SNP (FABP4_5; A<G substitution), in the promoter region of the gene, was significantly associated with all three RFIs. As the three RFI classes reflect changing diets and ages with concomitant RFI phenotypic consistency, the above polymorphisms and in particular FABP4_5, might be considered possible markers for RFI-based selection for FE in the Holstein breed, following a larger-scale validation.
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Affiliation(s)
- Miri Cohen-Zinder
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel;
| | - Aviv Asher
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel; Israeli Center for Interdisciplinary Research in Chronobiology, University of Haifa, Haifa, Israel
| | - Ehud Lipkin
- Department of Genetics, The Hebrew University of Jerusalem, Jerusalem, Israel; and
| | - Roi Feingersch
- Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Rotem Agmon
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - David Karasik
- Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Arieh Brosh
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Ariel Shabtay
- Beef cattle section, Newe-Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
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43
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Crispim AC, Kelly MJ, Guimarães SEF, e Silva FF, Fortes MRS, Wenceslau RR, Moore S. Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle. PLoS One 2015; 10:e0139906. [PMID: 26445451 PMCID: PMC4622042 DOI: 10.1371/journal.pone.0139906] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 09/18/2015] [Indexed: 12/16/2022] Open
Abstract
Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.
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Affiliation(s)
- Aline Camporez Crispim
- Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Matthew John Kelly
- Queensland Alliance for Agriculture & Food Innovation University of Queensland, Brisbane, Queensland, Australia
| | | | | | | | - Raphael Rocha Wenceslau
- Animal Science Institute, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Stephen Moore
- Queensland Alliance for Agriculture & Food Innovation University of Queensland, Brisbane, Queensland, Australia
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Torkamaneh D, Belzile F. Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data. PLoS One 2015; 10:e0131533. [PMID: 26161900 PMCID: PMC4498655 DOI: 10.1371/journal.pone.0131533] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 06/03/2015] [Indexed: 01/07/2023] Open
Abstract
Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data to assess the accuracy of the imputed data. Using a panel of 301 soybean accessions, we show that over 62,000 SNPs could be called when tolerating up to 80% missing data, a five-fold increase over the number called when tolerating up to 20% missing data. At all levels of missing data examined (between 20% and 80%), the resulting SNP datasets were of uniformly high accuracy (96-98%). We then used imputation to combine complementary SNP datasets derived from GBS and a SNP array (SoySNP50K). We thus produced an enhanced dataset of >100,000 SNPs and the genotypes at the previously untyped loci were again imputed with a high level of accuracy (95%). Of the >4,000,000 SNPs identified through resequencing 23 accessions (among the 301 used in the GBS analysis), 1.4 million tag SNPs were used as a reference to impute this large set of SNPs on the entire panel of 301 accessions. These previously untyped loci could be imputed with around 90% accuracy. Finally, we used the 100K SNP dataset (GBS + SoySNP50K) to perform a GWAS on seed oil content within this collection of soybean accessions. Both the number of significant marker-trait associations and the peak significance levels were improved considerably using this enhanced catalog of SNPs relative to a smaller catalog resulting from GBS alone at ≤20% missing data. Our results demonstrate that imputation can be used to fill in both missing genotypes and untyped loci with very high accuracy and that this leads to more powerful genetic analyses.
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Affiliation(s)
- Davoud Torkamaneh
- Département de Phytologie and Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
| | - Francois Belzile
- Département de Phytologie and Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
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45
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Santana MHA, Ventura RV, Utsunomiya YT, Neves HHR, Alexandre PA, Oliveira Junior GA, Gomes RC, Bonin MN, Coutinho LL, Garcia JF, Silva SL, Fukumasu H, Leme PR, Ferraz JBS. A genomewide association mapping study using ultrasound-scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle. J Anim Breed Genet 2015; 132:420-7. [PMID: 26016521 DOI: 10.1111/jbg.12167] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2014] [Accepted: 02/11/2015] [Indexed: 01/02/2023]
Abstract
The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.
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Affiliation(s)
- M H A Santana
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - R V Ventura
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil.,Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.,Beef Improvement Opportunties (BIO), Guelph, ON, Canada
| | - Y T Utsunomiya
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, Brazil
| | - H H R Neves
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, Brazil.,GenSys Consultores Associados S/C Ltda, Porto Alegre, Brazil
| | - P A Alexandre
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - G A Oliveira Junior
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - R C Gomes
- Empresa Brasileira de Pesquisa Agropecuária, CNPGC/EMBRAPA, Campo Grande, Brazil
| | - M N Bonin
- Empresa Brasileira de Pesquisa Agropecuária, CNPGC/EMBRAPA, Campo Grande, Brazil
| | - L L Coutinho
- Escola Superior de Agricultura Luiz de Queiroz, USP, Piracicaba, Brazil
| | - J F Garcia
- Faculdade de Ciências Agrárias e Veterinárias, UNESP, Jaboticabal, Brazil
| | - S L Silva
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - H Fukumasu
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - P R Leme
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
| | - J B S Ferraz
- Faculdade de Zootecnia e Engenharia de Alimentos - USP, Pirassununga, Brazil
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Tizioto PC, Coutinho LL, Decker JE, Schnabel RD, Rosa KO, Oliveira PSN, Souza MM, Mourão GB, Tullio RR, Chaves AS, Lanna DPD, Zerlotini-Neto A, Mudadu MA, Taylor JF, Regitano LCA. Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes. BMC Genomics 2015; 16:242. [PMID: 25887532 PMCID: PMC4381482 DOI: 10.1186/s12864-015-1464-x] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Accepted: 03/13/2015] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Efficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle. RESULTS Differential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism. CONCLUSIONS Our data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype.
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Affiliation(s)
- Polyana C Tizioto
- Embrapa Southeast Livestock, São Carlos, SP, Brazil. .,Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil.
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.
| | - Kamila O Rosa
- Department of Animal Science, State University of Sao Paulo, Jaboticabal, SP, Brazil.
| | - Priscila S N Oliveira
- Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil.
| | - Marcela M Souza
- Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil.
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil.
| | | | - Amália S Chaves
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil.
| | - Dante P D Lanna
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, São Paulo, Brazil.
| | | | | | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri Columbia, Columbia, MO, USA.
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He S, Zhao Y, Mette MF, Bothe R, Ebmeyer E, Sharbel TF, Reif JC, Jiang Y. Prospects and limits of marker imputation in quantitative genetic studies in European elite wheat (Triticum aestivum L.). BMC Genomics 2015; 16:168. [PMID: 25886991 PMCID: PMC4364688 DOI: 10.1186/s12864-015-1366-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2014] [Accepted: 02/20/2015] [Indexed: 11/26/2022] Open
Abstract
Background The main goal of our study was to investigate the implementation, prospects, and limits of marker imputation for quantitative genetic studies contrasting map-independent and map-dependent algorithms. We used a diversity panel consisting of 372 European elite wheat (Triticum aestivum L.) varieties, which had been genotyped with SNP arrays, and performed intensive simulation studies. Results Our results clearly showed that imputation accuracy was substantially higher for map-dependent compared to map-independent methods. The accuracy of marker imputation depended strongly on the linkage disequilibrium between the markers in the reference panel and the markers to be imputed. For the decay of linkage disequilibrium present in European wheat, we concluded that around 45,000 markers are needed for low cost, low-density marker profiling. This will facilitate high imputation accuracy, also for rare alleles. Genomic selection and diversity studies profited only marginally from imputing missing values. In contrast, the power of association mapping increased substantially when missing values were imputed. Conclusions Imputing missing values is especially of interest for an economic implementation of association mapping in breeding populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1366-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sang He
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
| | - M Florian Mette
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
| | | | | | - Timothy F Sharbel
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
| | - Yong Jiang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, D-06466 Stadt, Seeland, Germany.
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48
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He S, Wang S, Fu W, Ding X, Zhang Q. Imputation of missing genotypes from low- to high-density SNP panel in different population designs. Anim Genet 2014; 46:1-7. [PMID: 25431355 DOI: 10.1111/age.12236] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/10/2014] [Indexed: 01/28/2023]
Abstract
Imputation of missing genotypes, in particular from low density to high density, is an important issue in genomic selection and genome-wide association studies. Given the marker densities, the most important factors affecting imputation accuracy are the size of the reference population and the relationship between individuals in the reference (genotyped with high-density panel) and study (genotyped with low-density panel) populations. In this study, we investigated the imputation accuracies when the reference population (genotyped with Illumina BovineSNP50 SNP panel) contained sires, halfsibs, or both sires and halfsibs of the individuals in the study population (genotyped with Illumina BovineLD SNP panel) using three imputation programs (fimpute v2.2, findhap v2, and beagle v3.3.2). Two criteria, correlation between true and imputed genotypes and missing rate after imputation, were used to evaluate the performance of the three programs in different scenarios. Our results showed that fimpute performed the best in all cases, with correlations from 0.921 to 0.978 when imputing from sires to their daughters or between halfsibs. In general, the accuracies of imputing between halfsibs or from sires to their daughters were higher than were those imputing between non-halfsibs or from sires to non-daughters. Including both sires and halfsibs in the reference population did not improve the imputation performance in comparison with when only including halfsibs in the reference population for all the three programs.
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Affiliation(s)
- S He
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China; Department of Cytogenetics and Genome Analysis, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, 06466, Germany
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de Oliveira PSN, Cesar ASM, do Nascimento ML, Chaves AS, Tizioto PC, Tullio RR, Lanna DPD, Rosa AN, Sonstegard TS, Mourao GB, Reecy JM, Garrick DJ, Mudadu MA, Coutinho LL, Regitano LCA. Identification of genomic regions associated with feed efficiency in Nelore cattle. BMC Genet 2014; 15:100. [PMID: 25257854 PMCID: PMC4198703 DOI: 10.1186/s12863-014-0100-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Accepted: 09/10/2014] [Indexed: 01/17/2023] Open
Abstract
Background Feed efficiency is jointly determined by productivity and feed requirements, both of which are economically relevant traits in beef cattle production systems. The objective of this study was to identify genes/QTLs associated with components of feed efficiency in Nelore cattle using Illumina BovineHD BeadChip (770 k SNP) genotypes from 593 Nelore steers. The traits analyzed included: average daily gain (ADG), dry matter intake (DMI), feed-conversion ratio (FCR), feed efficiency (FE), residual feed intake (RFI), maintenance efficiency (ME), efficiency of gain (EG), partial efficiency of growth (PEG) and relative growth rate (RGR). The Bayes B analysis was completed with Gensel software parameterized to fit fewer markers than animals. Genomic windows containing all the SNP loci in each 1 Mb that accounted for more than 1.0% of genetic variance were considered as QTL region. Candidate genes within windows that explained more than 1% of genetic variance were selected by putative function based on DAVID and Gene Ontology. Results Thirty-six QTL (1-Mb SNP window) were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25 and 26 (UMD 3.1). The amount of genetic variance explained by individual QTL windows for feed efficiency traits ranged from 0.5% to 9.07%. Some of these QTL minimally overlapped with previously reported feed efficiency QTL for Bos taurus. The QTL regions described in this study harbor genes with biological functions related to metabolic processes, lipid and protein metabolism, generation of energy and growth. Among the positional candidate genes selected for feed efficiency are: HRH4, ALDH7A1, APOA2, LIN7C, CXADR, ADAM12 and MAP7. Conclusions Some genomic regions and some positional candidate genes reported in this study have not been previously reported for feed efficiency traits in Bos indicus. Comparison with published results indicates that different QTLs and genes may be involved in the control of feed efficiency traits in this Nelore cattle population, as compared to Bos taurus cattle. Electronic supplementary material The online version of this article (doi:10.1186/s12863-014-0100-0) contains supplementary material, which is available to authorized users.
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