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Li Z, He J, Yang F, Yin S, Gao Z, Chen W, Sun C, Tait RG, Bauck S, Guo W, Wu XL. A look under the hood of genomic-estimated breed compositions for brangus cattle: What have we learned? Front Genet 2023; 14:1080279. [PMID: 37056284 PMCID: PMC10086375 DOI: 10.3389/fgene.2023.1080279] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 03/14/2023] [Indexed: 04/05/2023] Open
Abstract
The Brangus cattle were developed to utilize the superior traits of Angus and Brahman cattle. Their genetic compositions are expected to be stabilized at 3/8 Brahman and 5/8 Angus. Previous studies have shown more than expected Angus lineage with Brangus cattle, and the reasons are yet to be investigated. In this study, we revisited the breed compositions for 3,605 Brangus cattle from three perspectives: genome-wise (GBC), per chromosomes (CBC), and per chromosome segments (SBC). The former (GBC) depicted an overall picture of the “mosaic” genome of the Brangus attributable to their ancestors, whereas the latter two criteria (CBC and SBC) corresponded to local ancestral contributions. The average GBC for the 3,605 Brangus cattle were 70.2% Angus and 29.8% Brahman. The K-means clustering supported the postulation of the mixture of 1/2 Ultrablack (UB) animals in Brangus. For the non-UB Brangus animals, the average GBC were estimated to be 67.4% Angus and 32.6% Brahman. The 95% confidence intervals of their overall GBC were 60.4%–73.5% Angus and 26.5%–39.6% Brahman. Possibly, genetic selection and drifting have resulted in an approximately 5% average deviation toward Angus lineage. The estimated ancestral contributions by chromosomes were heavily distributed toward Angus, with 27 chromosomes having an average Angus CBC greater than 62.5% but only two chromosomes (5 and 20) having Brahman CBC greater than 37.5%. The chromosomal regions with high Angus breed proportions were prevalent, tending to form larger blocks on most chromosomes. In contrast, chromosome segments with high Brahman breed proportion were relatively few and isolated, presenting only on seven chromosomes. Hence, genomic hitchhiking effects were strong where Angus favorable alleles resided but weak where Brahman favorable alleles were present. The functions of genes identified in the chromosomal regions with high (≥75%) Angus compositions were diverse yet may were related to growth and body development. In contrast, the genes identified in the regions with high (≥37.5%) Brahman compositions were primarily responsible for disease resistance. In conclusion, we have addressed the questions concerning the Brangus genetic make-ups. The results can help form a dynamic picture of the Brangus breed formation and the genomic reshaping.
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Affiliation(s)
- Zhi Li
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Jun He
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
- *Correspondence: Jun He, ; Xiao-Lin Wu,
| | - Fang Yang
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Shishu Yin
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Zhendong Gao
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Wenwu Chen
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, Hunan, China
| | - Chuanyu Sun
- Biostatistics and Bioinformatics, Neogen GeneSeek, Lincoln, NE, United States
| | - Richard G. Tait
- Biostatistics and Bioinformatics, Neogen GeneSeek, Lincoln, NE, United States
| | - Stewart Bauck
- Biostatistics and Bioinformatics, Neogen GeneSeek, Lincoln, NE, United States
| | - Wei Guo
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, United States
| | - Xiao-Lin Wu
- Department of Animal and Dairy Sciences, University of Wisconsin, Madison, WI, United States
- Council on Dairy Cattle Breeding, Bowie, MD, United States
- *Correspondence: Jun He, ; Xiao-Lin Wu,
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Grigoletto L, Ferraz JBS, Oliveira HR, Eler JP, Bussiman FO, Abreu Silva BC, Baldi F, Brito LF. Genetic Architecture of Carcass and Meat Quality Traits in Montana Tropical ® Composite Beef Cattle. Front Genet 2020; 11:123. [PMID: 32180796 PMCID: PMC7057717 DOI: 10.3389/fgene.2020.00123] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 02/03/2020] [Indexed: 12/16/2022] Open
Abstract
The Montana Tropical® Composite is a recently developed beef cattle population that is rapidly expanding in Brazil and other tropical countries. This is mainly due to its improved meat quality and adaptation to tropical climate conditions compared to Zebu and Taurine cattle breeds, respectively. This study aimed to investigate the genetic architecture of ultrasound-based carcass and meat quality traits in Montana Tropical® Composite beef cattle. Therefore, we estimated variance components and genetic parameters and performed genome-wide association studies using the weighted single-step Genomic Best Linear Unbiased Prediction (GBLUP) approach. A pedigree dataset containing 28,480 animals was used, in which 1,436 were genotyped using a moderate-density Single Nucleotide Polymorphism panel (30K; 30,105 SNPs). A total of 9,358, 5,768, 7,996, and 1,972 phenotypic records for the traits Longissimus muscle area (LMA), backfat thickness (BFT), rump fat thickness (RFT), and for marbling score (MARB), respectively, were used for the analyses. Moderate to high heritability estimates were obtained and ranged from 0.16 ± 0.03 (RFT) to 0.33 ± 0.05 (MARB). A high genetic correlation was observed between BFT and RFT (0.97 ± 0.02), suggesting that a similar set of genes affects both traits. The most relevant genomic regions associated with LMA, BFT, RFT, and MARB were found on BTA10 (5.4–5.8 Mb), BTA27 (25.2–25.5 Mb), BTA18 (60.6–61.0 Mb), and BTA21 (14.8–15.4 Mb). Two overlapping genomic regions were identified for RFT and MARB (BTA13:47.9–48.1 Mb) and for BFT and RFT (BTA13:61.5–62.3 Mb). Candidate genes identified in this study, including PLAG1, LYN, WWOX, and PLAGL2, were previously reported to be associated with growth, stature, skeletal muscle growth, fat thickness, and fatty acid composition. Our results indicate that ultrasound-based carcass and meat quality traits in the Montana Tropical® Composite beef cattle are heritable, and therefore, can be improved through selective breeding. In addition, various novel and already known genomic regions related to these traits were identified, which contribute to a better understanding of the underlying genetic background of LMA, BFT, RFT, and MARB in the Montana Tropical Composite population.
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Affiliation(s)
- Laís Grigoletto
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil.,Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - José B S Ferraz
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Joanir P Eler
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Fernando O Bussiman
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Barbara C Abreu Silva
- Department of Animal Sciences, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, Brazil
| | - Fernando Baldi
- Department of Animal Sciences, College of Agricultural and Veterinary Sciences, São Paulo State University, Jaboticabal, Brazil
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
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New world goat populations are a genetically diverse reservoir for future use. Sci Rep 2019; 9:1476. [PMID: 30728441 PMCID: PMC6365549 DOI: 10.1038/s41598-019-38812-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 10/30/2018] [Indexed: 01/02/2023] Open
Abstract
Western hemisphere goats have European, African and Central Asian origins, and some local or rare breeds are reported to be adapted to their environments and economically important. By-in-large these genetic resources have not been quantified. Using 50 K SNP genotypes of 244 animals from 12 goat populations in United States, Costa Rica, Brazil and Argentina, we evaluated the genetic diversity, population structure and selective sweeps documenting goat migration to the "New World". Our findings suggest the concept of breed, particularly among "locally adapted" breeds, is not a meaningful way to characterize goat populations. The USA Spanish goats were found to be an important genetic reservoir, sharing genomic composition with the wild ancestor and with specialized breeds (e.g. Angora, Lamancha and Saanen). Results suggest goats in the Americas have substantial genetic diversity to use in selection and promote environmental adaptation or product driven specialization. These findings highlight the importance of maintaining goat conservation programs and suggest an awaiting reservoir of genetic diversity for breeding and research while simultaneously discarding concerns about breed designations.
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Ali A, Al-Tobasei R, Kenney B, Leeds TD, Salem M. Integrated analysis of lncRNA and mRNA expression in rainbow trout families showing variation in muscle growth and fillet quality traits. Sci Rep 2018; 8:12111. [PMID: 30108261 PMCID: PMC6092380 DOI: 10.1038/s41598-018-30655-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 08/04/2018] [Indexed: 02/07/2023] Open
Abstract
Muscle yield and quality traits are important for the aquaculture industry and consumers. Genetic selection for these traits is difficult because they are polygenic and result from multifactorial interactions. To study the genetic architecture of these traits, phenotypic characterization of whole body weight (WBW), muscle yield, fat content, shear force and whiteness were measured in ~500 fish representing 98 families from a growth-selected line. RNA-Seq was used to sequence the muscle transcriptome of different families exhibiting divergent phenotypes for each trait. We have identified 240 and 1,280 differentially expressed (DE) protein-coding genes and long noncoding RNAs (lncRNAs), respectively, in fish families exhibiting contrasting phenotypes. Expression of many DE lncRNAs (n = 229) was positively correlated with overlapping, neighboring or distantly located protein-coding genes (n = 1,030), resulting in 3,392 interactions. Three DE antisense lncRNAs were co-expressed with sense genes known to impact muscle quality traits. Forty-four DE lncRNAs had potential sponge functions to miRNAs that affect muscle quality traits. This study (1) defines muscle quality associated protein-coding and noncoding genes and (2) provides insight into non-coding RNAs involvement in regulating growth and fillet quality traits in rainbow trout.
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Affiliation(s)
- Ali Ali
- Department of Biology and Molecular Biosciences Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, 35294-0022, USA
| | - Brett Kenney
- Division of Animal and Nutritional Science, West Virginia University, Morgantown, WV, 26506-6108, USA
| | - Timothy D Leeds
- The National Center for Cool and Cold Water Aquaculture, USDA Agricultural Research Service, Kearneysville, WV, 25430, USA
| | - Mohamed Salem
- Department of Biology and Molecular Biosciences Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA. .,Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA.
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Liu X, Usman T, Wang Y, Wang Z, Xu X, Wu M, Zhang Y, Zhang X, Li Q, Liu L, Shi W, Qin C, Geng F, Wang C, Tan R, Huang X, Liu A, Wu H, Tan S, Yu Y. Polymorphisms in epigenetic and meat quality related genes in fourteen cattle breeds and association with beef quality and carcass traits. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2015; 28:467-75. [PMID: 25656186 PMCID: PMC4341095 DOI: 10.5713/ajas.13.0837] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2013] [Revised: 02/21/2014] [Accepted: 08/14/2014] [Indexed: 01/19/2023]
Abstract
Improvement for carcass traits related to beef quality is the key concern in beef production. Recent reports found that epigenetics mediates the interaction of individuals with environment and nutrition. The present study was designed to analyze the genetic effect of single nucleotide polymorphisms (SNPs) in seven epigenetic-related genes (DNMT1, DNMT3a, DNMT3b, DNMT3L, Ago1, Ago2, and HDAC5) and two meat quality candidate genes (CAPN1 and PRKAG3) on fourteen carcass traits related to beef quality in a Snow Dragon beef population, and also to identify SNPs in a total of fourteen cattle populations. Sixteen SNPs were identified and genotyped in 383 individuals sampled from the 14 cattle breeds, which included 147 samples from the Snow Dragon beef population. Data analysis showed significant association of 8 SNPs within 4 genes related to carcass and/or meat quality traits in the beef populations. SNP1 (13154420A>G) in exon 17 of DNMT1 was significantly associated with rib-eye width and lean meat color score (p<0.05). A novel SNP (SNP4, 76198537A>G) of DNMT3a was significantly associated with six beef quality traits. Those individuals with the wild-type genotype AA of DNMT3a showed an increase in carcass weight, chilled carcass weight, flank thicknesses, chuck short rib thickness, chuck short rib score and in chuck flap weight in contrast to the GG genotype. Five out of six SNPs in DNMT3b gene were significantly associated with three beef quality traits. SNP15 (45219258C>T) in CAPN1 was significantly associated with chuck short rib thickness and lean meat color score (p<0.05). The significant effect of SNP15 on lean meat color score individually and in combination with each of other 14 SNPs qualify this SNP to be used as potential marker for improving the trait. In addition, the frequencies of most wild-type alleles were higher than those of the mutant alleles in the native and foreign cattle breeds. Seven SNPs were identified in the epigenetic-related genes. The SNP15 in CAPN1 could be used as a powerful genetic marker in selection programs for beef quality improvement in the Snow Dragon Beef population.
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Affiliation(s)
- Xuan Liu
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Tahir Usman
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China ; Department of Animal Health, The University of Agriculture, Peshawar, Peshawar 25000, Pakistan
| | - Yachun Wang
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Zezhao Wang
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xianzhou Xu
- Dalian Xuelong Industry Limited Group, Dalian 116001, China
| | - Meng Wu
- Dalian Xuelong Industry Limited Group, Dalian 116001, China
| | - Yi Zhang
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xu Zhang
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Qiang Li
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lin Liu
- Beijing Dairy Cattle Center, Beijing 100193, China
| | - Wanhai Shi
- Beijing Dairy Cattle Center, Beijing 100193, China
| | - Chunhua Qin
- Ningxia Sygen BioEngineering Research Center, Yinchuan 750000, China
| | - Fanjun Geng
- Dingyuan Seedstock Bulls Breeding Ltd. Company, Zhengzhou 450000, China
| | - Congyong Wang
- Dingyuan Seedstock Bulls Breeding Ltd. Company, Zhengzhou 450000, China
| | - Rui Tan
- Xinjiang General Livestock Service, Urumqi 830000, China
| | - Xixia Huang
- College of Animal Science, Xinjiang Agriculture University, Urumqi 830000 China
| | - Airong Liu
- Xiertala Breeding Farm, Hailaer Farm Buro, Hailaer 021008, China
| | - Hongjun Wu
- Hailaer Farm Buro, Hailaer 021008, China
| | - Shixin Tan
- Xinjiang Tianshan Animal Husbandry Bio-Eng. Co. Ltd, Urumqi 830000, China
| | - Ying Yu
- Key Laboratory of Agricultural Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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