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Yin H, Feng Y, Wang Y, Jiang Q, Zhang J, Zhao J, Chen Y, Wang Y, Peng R, Wang Y, Zhao T, Zheng C, Xu L, Gao X, Gao H, Li J, Wang Z, Zhang L. Genome-Wide Scans for Selection Signatures in Ningxia Angus Cattle Reveal Genetic Variants Associated with Economic and Adaptive Traits. Animals (Basel) 2024; 15:58. [PMID: 39795001 PMCID: PMC11718920 DOI: 10.3390/ani15010058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2024] [Revised: 12/26/2024] [Accepted: 12/27/2024] [Indexed: 01/13/2025] Open
Abstract
The genetic improvement of beef cattle breeds is crucial for the advancement of the beef cattle industry. Whole-genome resequencing technology has been widely applied in genetic breeding as well as research on selection signatures in beef cattle. In this study, 20× whole-genome resequencing was performed on 282 Angus cattle from the Ningxia region, and a high-quality dataset encompassing extensive genomic variations across the entire genome was constructed. The iHS test identified 495 selection signal regions, which included pregnancy-associated glycoprotein (PAG) family genes and immune-related genes such as UL16-binding protein 21 (ULBP21), CD1b molecule (CD1B), and tumor necrosis factor ligand superfamily member 11 (TNFSF11). A quantitative trait locus (QTL) enrichment analysis revealed that several economic traits, including longissimus muscle area, marbling score, carcass weight, average daily gain, and milk yield, were significantly enriched in cattle with these selection signatures. Although the enrichment of QTLs for health traits was low, immune-related genes may indirectly contribute to improvements in production performance. These findings show the genetic basis of economic and adaptive traits in Ningxia Angus cattle, providing a theoretical foundation and guidance for further genetic improvement and breeding strategies.
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Affiliation(s)
- Haiqi Yin
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Yuan Feng
- Ningxia Autonomous Region Animal Husbandry Workstation, Yinchuan 750004, China; (Y.F.); (Y.W.); (Q.J.); (J.Z.)
| | - Yu Wang
- Ningxia Autonomous Region Animal Husbandry Workstation, Yinchuan 750004, China; (Y.F.); (Y.W.); (Q.J.); (J.Z.)
| | - Qiufei Jiang
- Ningxia Autonomous Region Animal Husbandry Workstation, Yinchuan 750004, China; (Y.F.); (Y.W.); (Q.J.); (J.Z.)
| | - Juan Zhang
- School of Animal Science and Technology, Ningxia University, Yinchuan 750021, China;
| | - Jie Zhao
- Ningxia Autonomous Region Animal Husbandry Workstation, Yinchuan 750004, China; (Y.F.); (Y.W.); (Q.J.); (J.Z.)
| | - Yafei Chen
- Yinchuan Animal Husbandry Technology Extension Service Center, Yinchuan 750021, China;
| | - Yaxuan Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Ruiqi Peng
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Yahui Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Tong Zhao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Caihong Zheng
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Lingyang Xu
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Xue Gao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Huijiang Gao
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Junya Li
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Zezhao Wang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
| | - Lupei Zhang
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (H.Y.); (Y.W.); (R.P.); (Y.W.); (T.Z.); (C.Z.); (L.X.); (X.G.); (H.G.); (J.L.)
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Mota LFM, Carvajal AB, Silva Neto JB, Díaz C, Carabaño MJ, Baldi F, Munari DP. Assessment of inbreeding coefficients and inbreeding depression on complex traits from genomic and pedigree data in Nelore cattle. BMC Genomics 2024; 25:944. [PMID: 39379819 PMCID: PMC11460123 DOI: 10.1186/s12864-024-10842-w] [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: 03/25/2024] [Accepted: 09/26/2024] [Indexed: 10/10/2024] Open
Abstract
BACKGROUND Nelore cattle play a key role in tropical production systems due to their resilience to harsh conditions, such as heat stress and seasonally poor nutrition. Monitoring their genetic diversity is essential to manage the negative impacts of inbreeding. Traditionally, inbreeding and inbreeding depression are assessed by pedigree-based coefficients (F), but recently, genetic markers have been preferred for their precision in capturing the inbreeding level and identifying animals at risk of reduced productive and reproductive performance. Hence, we compared the inbreeding and inbreeding depression for productive and reproductive performance traits in Nelore cattle using different inbreeding coefficient estimation methods from pedigree information (FPed), the genomic relationship matrix (FGRM), runs of homozygosity (FROH) of different lengths (> 1 Mb (genome), between 1 and 2 Mb - FROH 1-2; 2-4 Mb FROH 2-4 or > 8 Mb FROH >8) and excess homozygosity (FSNP). RESULTS The correlation between FPed and FROH was lower when the latter was based on shorter segments (r = 0.15 with FROH 1-2, r = 0.20 with FROH 2-4 and r = 0.28 with FROH 4-8). Meanwhile, the FPed had a moderate correlation with FSNP (r = 0.47) and high correlation with FROH >8 (r = 0.58) and FROH-genome (r = 0.60). The FROH-genome was highly correlated with inbreeding based on FROH>8 (r = 0.93) and FSNP (r = 0.88). The FGRM exhibited a high correlation with FROH-genome (r = 0.55) and FROH >8 (r = 0.51) and a lower correlation with other inbreeding estimators varying from 0.30 for FROH 2-4 to 0.37 for FROH 1-2. Increased levels of inbreeding had a negative impact on the productive and reproductive performance of Nelore cattle. The unfavorable inbreeding effect on productive and reproductive traits ranged from 0.12 to 0.51 for FPed, 0.19-0.59 for FGRM, 0.21-0.58 for FROH-genome, and 0.19-0.54 for FSNP per 1% of inbreeding scaled on the percentage of the mean. When scaling the linear regression coefficients on the standard deviation, the unfavorable inbreeding effect varied from 0.43 to 1.56% for FPed, 0.49-1.97% for FGRM, 0.34-2.2% for FROH-genome, and 0.50-1.62% for FSNP per 1% of inbreeding. The impact of the homozygous segments on reproductive and performance traits varied based on the chromosomes. This shows that specific homozygous chromosome segments can be signs of positive selection due to their beneficial effects on the traits. CONCLUSIONS The low correlation observed between FPed and genomic-based inbreeding estimates suggests that the presence of animals with one unknown parent (sire or dam) in the pedigree does not account for ancient inbreeding. The ROH hotspots surround genes related to reproduction, growth, meat quality, and adaptation to environmental stress. Inbreeding depression has adverse effects on productive and reproductive traits in Nelore cattle, particularly on age at puberty in young bulls and heifer calving at 30 months, as well as on scrotal circumference and body weight when scaled on the standard deviation of the trait.
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Affiliation(s)
- Lucio F M Mota
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil.
| | - Alejandro B Carvajal
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil
| | - João B Silva Neto
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil
| | - Clara Díaz
- Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-C SIC), Madrid, 28040, Spain
| | - Maria J Carabaño
- Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-C SIC), Madrid, 28040, Spain
| | - Fernando Baldi
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil
- National Association of Breeders and Researchers, Rua João Godoy 463, Ribeirão Preto, 14020-230, SP, Brazil
| | - Danísio P Munari
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane, Jaboticabal, 14884-900, SP, Brazil
- National Council for Science and Technological Development (CNPq), Brasilia, 71605-001, DF, Brazil
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Kolpakov V, Ruchay A, Kosyan D, Bukareva E. Analysis of Runs of Homozygosity in Aberdeen Angus Cattle. Animals (Basel) 2024; 14:2153. [PMID: 39123679 PMCID: PMC11311081 DOI: 10.3390/ani14152153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 07/20/2024] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
A large number of cattle breeds have marked phenotypic differences. They are valuable models for studying genome evolution. ROH analysis can facilitate the discovery of genomic regions that may explain phenotypic differences between breeds affecting traits of economic importance. This paper investigates genome-wide ROH of 189 Aberdeen Angus bulls using the Illumina Bovine GGP HD Beadchip150K to structurally and functionally annotate genes located within or in close ROH of the Aberdeen Angus cattle genome. The method of sequential SNP detection was used to determine the ROH. Based on this parameter, two ROH classes were allocated. The total length of all ROH islands was 11,493 Mb. As a result of studying the genomic architecture of the experimental population of Aberdeen Angus bulls, nine ROH islands and 255 SNPs were identified. Thirteen of these overlapped with regions bearing 'selection imprints' previously identified in other breeds of cattle, and five of these regions were identified in other Aberdeen Angus populations. The total length of the ROH islands was 11,493 Mb. The size of individual islands ranged from 0.038 to 1.812 Mb. Structural annotation showed the presence of 87 genes within the identified ROH islets.
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Affiliation(s)
- Vladimir Kolpakov
- Federal Research Centre of Biological Systems and Agro-Technologies of the Russian Academy of Sciences, 460000 Orenburg, Russia; (V.K.); (D.K.); (E.B.)
- Department of Biotechnology of Animal Raw Materials and Aquaculture, Orenburg State University, 460000 Orenburg, Russia
| | - Alexey Ruchay
- Federal Research Centre of Biological Systems and Agro-Technologies of the Russian Academy of Sciences, 460000 Orenburg, Russia; (V.K.); (D.K.); (E.B.)
- Department of Information Security, South Ural State University, 454080 Chelyabinsk, Russia
- Department of Mathematics, Chelyabinsk State University, 454001 Chelyabinsk, Russia
| | - Dianna Kosyan
- Federal Research Centre of Biological Systems and Agro-Technologies of the Russian Academy of Sciences, 460000 Orenburg, Russia; (V.K.); (D.K.); (E.B.)
| | - Elena Bukareva
- Federal Research Centre of Biological Systems and Agro-Technologies of the Russian Academy of Sciences, 460000 Orenburg, Russia; (V.K.); (D.K.); (E.B.)
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Abebe BK, Wang H, Li A, Zan L. A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle. J Anim Breed Genet 2024; 141:235-256. [PMID: 38146089 DOI: 10.1111/jbg.12841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/27/2023]
Abstract
In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
- Department of Animal Science, Werabe University, Werabe, Ethiopia
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, People's Republic of China
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Machado PC, Brito LF, Martins R, Pinto LFB, Silva MR, Pedrosa VB. Genome-Wide Association Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems. Animals (Basel) 2022; 12:ani12243526. [PMID: 36552446 PMCID: PMC9774243 DOI: 10.3390/ani12243526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/06/2022] [Accepted: 12/10/2022] [Indexed: 12/15/2022] Open
Abstract
Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.
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Affiliation(s)
- Pamela C. Machado
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
| | - Luiz F. Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Rafaela Martins
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
| | - Luis Fernando B. Pinto
- Department of Animal Science, Federal University of Bahia, Av. Adhemar de Barros 500, Ondina, Salvador 40170-110, BA, Brazil
| | - Marcio R. Silva
- Melhore Animal and Katayama Agropecuaria Lda, Guararapes 16700-000, SP, Brazil
| | - Victor B. Pedrosa
- Department of Animal Sciences, State University of Ponta Grossa, Ponta Grossa 84030-900, PR, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
- Correspondence:
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Mulim HA, Brito LF, Pinto LFB, Ferraz JBS, Grigoletto L, Silva MR, Pedrosa VB. Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals. BMC Genomics 2022; 23:209. [PMID: 35291953 PMCID: PMC8925140 DOI: 10.1186/s12864-022-08384-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 02/10/2022] [Indexed: 01/12/2023] Open
Abstract
Background A decline in the level of genetic diversity in livestock can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, various metrics have been proposed to assess the level of genetic diversity in selected populations. Therefore, the main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses. Results A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four ROH islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (FHOM), uniting of gametes (FUNI), and genotype additive variance (FGRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (FROH). For the HER, 3576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system, indicating potential balancing selection. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data. Conclusions The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08384-0.
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Affiliation(s)
| | - Luiz F Brito
- Department of Animal Science, Purdue University, West Lafayette, Indiana, USA
| | | | - José Bento Sterman Ferraz
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | - Lais Grigoletto
- Department of Animal Science, Purdue University, West Lafayette, Indiana, USA.,Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | | | - Victor Breno Pedrosa
- Department of Animal Science, Federal University of Bahia, Salvador, Bahia, Brazil. .,Department of Animal Science, State University of Ponta Grossa, Av. General Carlos Cavalcanti, 4748 - Uvaranas, Ponta Grossa, PR, 84030-900, Brazil.
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