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Haque MA, Lee YM, Ha JJ, Jin S, Park B, Kim NY, Won JI, Kim JJ. Genome-wide association study identifies genomic regions associated with key reproductive traits in Korean Hanwoo cows. BMC Genomics 2024; 25:496. [PMID: 38778305 PMCID: PMC11112828 DOI: 10.1186/s12864-024-10401-3] [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: 12/15/2023] [Accepted: 05/09/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Conducting genome-wide association studies (GWAS) for reproductive traits in Hanwoo cattle, including age at first calving (AFC), calving interval (CI), gestation length (GL), and number of artificial inseminations per conception (NAIPC), is of paramount significance. These analyses provided a thorough exploration of the genetic basis of these traits, facilitating the identification of key markers for targeted trait improvement. Breeders can optimize their selection strategies, leading to more efficient and sustainable breeding programs, by incorporating genetic insights. This impact extends beyond individual traits and contributes to the overall productivity and profitability of the Hanwoo beef cattle industry. Ultimately, GWAS is essential in ensuring the long-term genetic resilience and adaptability of Hanwoo cattle populations. The primary goal of this study was to identify significant single nucleotide polymorphisms (SNPs) or quantitative trait loci (QTLs) associated with the studied reproductive traits and subsequently map the underlying genes that hold promise for trait improvement. RESULTS A genome-wide association study of reproductive traits identified 68 significant single nucleotide polymorphisms (SNPs) distributed across 29 Bos taurus autosomes (BTA). Among them, BTA14 exhibited the highest number of identified SNPs (25), whereas BTA6, BTA7, BTA8, BTA10, BTA13, BTA17, and BTA20 exhibited 8, 5, 5, 3, 8, 2, and 12 significant SNPs, respectively. Annotation of candidate genes within a 500 kb region surrounding the significant SNPs led to the identification of ten candidate genes relevant to age at first calving. These genes were: FANCG, UNC13B, TESK1, TLN1, and CREB3 on BTA8; FAM110B, UBXN2B, SDCBP, and TOX on BTA14; and MAP3K1 on BTA20. Additionally, APBA3, TCF12, and ZFR2, located on BTA7 and BTA10, were associated with the calving interval; PAX1, SGCD, and HAND1, located on BTA7 and BTA13, were linked to gestation length; and RBM47, UBE2K, and GPX8, located on BTA6 and BTA20, were linked to the number of artificial inseminations per conception in Hanwoo cows. CONCLUSIONS The findings of this study enhance our knowledge of the genetic factors that influence reproductive traits in Hanwoo cattle populations and provide a foundation for future breeding strategies focused on improving desirable traits in beef cattle. This research offers new evidence and insights into the genetic variants and genome regions associated with reproductive traits and contributes valuable information to guide future efforts in cattle breeding.
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Affiliation(s)
- Md Azizul Haque
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Korea
| | - Yun-Mi Lee
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Korea
| | - Jae-Jung Ha
- Gyeongbuk Livestock Research Institute, Yeongju, 36052, Korea
| | - Shil Jin
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, 25340, Korea
| | - Byoungho Park
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, 25340, Korea
| | - Nam-Young Kim
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, 25340, Korea
| | - Jeong-Il Won
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang, 25340, Korea.
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, 38541, Korea.
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Zhang Y, Zhuang Z, Liu Y, Huang J, Luan M, Zhao X, Dong L, Ye J, Yang M, Zheng E, Cai G, Wu Z, Yang J. Genomic prediction based on preselected single-nucleotide polymorphisms from genome-wide association study and imputed whole-genome sequence data annotation for growth traits in Duroc pigs. Evol Appl 2024; 17:e13651. [PMID: 38362509 PMCID: PMC10868536 DOI: 10.1111/eva.13651] [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: 12/11/2022] [Revised: 10/31/2023] [Accepted: 01/13/2024] [Indexed: 02/17/2024] Open
Abstract
The use of whole-genome sequence (WGS) data is expected to improve genomic prediction (GP) power of complex traits because it may contain mutations that in strong linkage disequilibrium pattern with causal mutations. However, a few previous studies have shown no or small improvement in prediction accuracy using WGS data. Incorporating prior biological information into GP seems to be an attractive strategy that might improve prediction accuracy. In this study, a total of 6334 pigs were genotyped using 50K chips and subsequently imputed to the WGS level. This cohort includes two prior discovery populations that comprise 294 Landrace pigs and 186 Duroc pigs, as well as two validation populations that consist of 3770 American Duroc pigs and 2084 Canadian Duroc pigs. Then we used annotation information and genome-wide association study (GWAS) from the WGS data to make GP for six growth traits in two Duroc pig populations. Based on variant annotation, we partitioned different genomic classes, such as intron, intergenic, and untranslated regions, for imputed WGS data. Based on GWAS results of WGS data, we obtained trait-associated single-nucleotide polymorphisms (SNPs). We then applied the genomic feature best linear unbiased prediction (GFBLUP) and genomic best linear unbiased prediction (GBLUP) models to estimate the genomic estimated breeding values for growth traits with these different variant panels, including six genomic classes and trait-associated SNPs. Compared with 50K chip data, GBLUP with imputed WGS data had no increase in prediction accuracy. Using only annotations resulted in no increase in prediction accuracy compared to GBLUP with 50K, but adding annotation information into the GFBLUP model with imputed WGS data could improve the prediction accuracy with increases of 0.00%-2.82%. In conclusion, a GFBLUP model that incorporated prior biological information might increase the advantage of using imputed WGS data for GP.
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Affiliation(s)
- Yuling Zhang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Yiyi Liu
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Jinyan Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Menghao Luan
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Linsong Dong
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Jian Ye
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Ming Yang
- College of Animal Science and TechnologyZhongkai University of Agriculture and EngineeringGuangzhouChina
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
- Guangdong Zhongxin Breeding Technology Co., LtdGuangzhouChina
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine IndustrySouth China Agricultural UniversityGuangzhouChina
- Guangdong Provincial Key Laboratory of Agro‐animal Genomics and Molecular BreedingSouth China Agricultural UniversityGuangzhouChina
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3
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Davoudi P, Do DN, Colombo S, Rathgeber B, Sargolzaei M, Plastow G, Wang Z, Hu G, Valipour S, Miar Y. Genome-wide association studies for economically important traits in mink using copy number variation. Sci Rep 2024; 14:24. [PMID: 38167844 PMCID: PMC10762091 DOI: 10.1038/s41598-023-50497-3] [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: 10/04/2023] [Accepted: 12/20/2023] [Indexed: 01/05/2024] Open
Abstract
Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
- Select Sires Inc., Plain City, OH, USA
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Shafagh Valipour
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
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Nayak SS, Panigrahi M, Rajawat D, Ghildiyal K, Sharma A, Parida S, Bhushan B, Mishra BP, Dutt T. Comprehensive selection signature analyses in dairy cattle exploiting purebred and crossbred genomic data. Mamm Genome 2023; 34:615-631. [PMID: 37843569 DOI: 10.1007/s00335-023-10021-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 09/24/2023] [Indexed: 10/17/2023]
Abstract
The main objective of the current research was to locate, annotate, and highlight specific areas of the bovine genome that are undergoing intense positive selection. Here, we are analyzing selection signatures in crossbred (Bos taurus X Bos indicus), taurine (Bos taurus), and indicine (Bos indicus) cattle breeds. Indicine cattle breeds found throughout India are known for their higher heat tolerance and disease resilience. More breeds and more methods can provide a better understanding of the selection signature. So, we have worked on nine distinct cattle breeds utilizing seven different summary statistics, which is a fairly extensive approach. In this study, we carried out a thorough genome-wide investigation of selection signatures using bovine 50K SNP data. We have included the genotyped data of two taurine, two crossbreds, and five indicine cattle breeds, for a total of 320 animals. During the 1950s, these indicine (cebuine) cattle breeds were exported with the aim of enhancing the resilience of taurine breeds in Western countries. For this study, we employed seven summary statistics, including intra-population, i.e., Tajima's D, CLR, iHS, and ROH and inter-population statistics, i.e., FST, XP-EHH, and Rsb. The NCBI database, PANTHER 17.0, and CattleQTL database were used for annotation after finding the important areas under selection. Some genes, including EPHA6, CTNNA2, NPFFR2, HS6ST3, NPR3, KCNIP4, LIPK, SDCBP, CYP7A1, NSMAF, UBXN2B, UGDH, UBE2K, and DAB1, were shown to be shared by three or more different approaches. Therefore, it gives evidence of the most intense selection in these areas. These genes are mostly linked to milk production and adaptability traits. This study also reveals selection regions that contain genes which are crucial to numerous biological functions, including those associated with milk production, coat color, glucose metabolism, oxidative stress response, immunity and circadian rhythms.
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Affiliation(s)
- Sonali Sonejita Nayak
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India.
| | - Divya Rajawat
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - Anurodh Sharma
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - Subhashree Parida
- Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
| | - B P Mishra
- ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana, 132001, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India
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5
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Lee DJ, Kim Y, Dinh PTN, Chung Y, Lee D, Kim Y, Lee SH, Choi I, Lee SH. Identification of Missense Variants Affecting Carcass Traits for Hanwoo Precision Breeding. Genes (Basel) 2023; 14:1839. [PMID: 37895191 PMCID: PMC10606632 DOI: 10.3390/genes14101839] [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: 09/06/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
This study aimed to identify causal variants associated with important carcass traits such as weight and meat quality in Hanwoo cattle. We analyzed missense mutations extracted from imputed sequence data (ARS-UCD1.2) and performed an exon-specific association test on the carcass traits of 16,970 commercial Hanwoo. We found 33, 2, 1, and 3 significant SNPs associated with carcass weight (CW), backfat thickness (BFT), eye muscle area (EMA), and marbling score (MS), respectively. In CW and EMA, the most significant missense SNP was identified at 19,524,263 on BTA14 and involved the PRKDC. A missense SNP in the ZFAND2B, located at 107,160,304 on BTA2 was identified as being involved in BFT. For MS, missense SNP in the ACVR2B gene, located at 11,849,704 in BTA22 was identified as the most significant marker. The contribution of the most significant missense SNPs to genetic variance was confirmed to be 8.47%, 2.08%, 1.73%, and 1.19% in CW, BFT, EMA, and MS, respectively. We generated favorable and unfavorable haplotype combinations based on the significant SNPs for CW. Significant differences in GEBV (Genomic Estimated Breeding Values) were observed between groups with each favorable and unfavorable haplotype combination. In particular, the missense SNPs in PRKDC, MRPL9, and ANKFN1 appear to significantly affect the protein's function and structure, making them strong candidates as causal mutations. These missense SNPs have the potential to serve as valuable markers for improving carcass traits in Hanwoo commercial farms.
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Affiliation(s)
- Dong Jae Lee
- Division of Animal & Dairy Science, Chungnam National University, Daejeon 34134, Republic of Korea; (D.J.L.); (Y.C.); (D.L.); (S.H.L.)
| | - Yoonsik Kim
- Department of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Republic of Korea; (Y.K.); (P.T.N.D.)
| | - Phuong Thanh N. Dinh
- Department of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Republic of Korea; (Y.K.); (P.T.N.D.)
| | - Yoonji Chung
- Division of Animal & Dairy Science, Chungnam National University, Daejeon 34134, Republic of Korea; (D.J.L.); (Y.C.); (D.L.); (S.H.L.)
| | - Dooho Lee
- Division of Animal & Dairy Science, Chungnam National University, Daejeon 34134, Republic of Korea; (D.J.L.); (Y.C.); (D.L.); (S.H.L.)
| | - Yeongkuk Kim
- Quantomic Research & Solution, Daejeon 34134, Republic of Korea;
| | - Soo Hyun Lee
- Division of Animal & Dairy Science, Chungnam National University, Daejeon 34134, Republic of Korea; (D.J.L.); (Y.C.); (D.L.); (S.H.L.)
| | - Inchul Choi
- Division of Animal & Dairy Science, Chungnam National University, Daejeon 34134, Republic of Korea; (D.J.L.); (Y.C.); (D.L.); (S.H.L.)
| | - Seung Hwan Lee
- Department of Bio-AI Convergence, Chungnam National University, Daejeon 34134, Republic of Korea; (Y.K.); (P.T.N.D.)
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Alam MZ, Haque MA, Iqbal A, Lee YM, Ha JJ, Jin S, Park B, Kim NY, Won JI, Kim JJ. Genome-Wide Association Study to Identify QTL for Carcass Traits in Korean Hanwoo Cattle. Animals (Basel) 2023; 13:2737. [PMID: 37685003 PMCID: PMC10486602 DOI: 10.3390/ani13172737] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.
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Affiliation(s)
- Mohammad Zahangir Alam
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea; (M.Z.A.); (M.A.H.); (A.I.); (Y.-M.L.)
| | - Md Azizul Haque
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea; (M.Z.A.); (M.A.H.); (A.I.); (Y.-M.L.)
| | - Asif Iqbal
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea; (M.Z.A.); (M.A.H.); (A.I.); (Y.-M.L.)
| | - Yun-Mi Lee
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea; (M.Z.A.); (M.A.H.); (A.I.); (Y.-M.L.)
| | - Jae-Jung Ha
- Gyeongbuk Livestock Research Institute, Yeongju 36052, Republic of Korea;
| | - Shil Jin
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang 25340, Republic of Korea; (S.J.); (B.P.); (N.-Y.K.)
| | - Byoungho Park
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang 25340, Republic of Korea; (S.J.); (B.P.); (N.-Y.K.)
| | - Nam-Young Kim
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang 25340, Republic of Korea; (S.J.); (B.P.); (N.-Y.K.)
| | - Jeong Il Won
- Hanwoo Research Institute, National Institute of Animal Science, Pyeongchang 25340, Republic of Korea; (S.J.); (B.P.); (N.-Y.K.)
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea; (M.Z.A.); (M.A.H.); (A.I.); (Y.-M.L.)
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Cha J, Jin D, Kim JH, Kim SC, Lim JA, Chai HH, Jung SA, Lee JH, Lee SH. Genome-wide association study revealed the genomic regions associated with skin pigmentation in an Ogye x White Leghorn F2 chicken population. Poult Sci 2023; 102:102720. [PMID: 37327746 PMCID: PMC10404675 DOI: 10.1016/j.psj.2023.102720] [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: 01/16/2023] [Revised: 04/03/2023] [Accepted: 04/10/2023] [Indexed: 06/18/2023] Open
Abstract
Skin color in chickens is an economically important trait that determines the first impression of a consumer toward a broiler and can ultimately affect consumer choice in the market. Therefore, identification of genomic regions associated with skin color is crucial for increasing the sales value of chickens. Although previous studies have attempted to reveal the genetic markers associated with the skin coloration in chickens, most were limited to investigations of candidate genes, such as melanin-related genes, and focused on case/control studies based on a single or small population. In this study, we performed a genome-wide association study (GWAS) on 770 F2 intercrosses produced by an experimental population of 2 chicken breeds, namely Ogye and White Leghorns, with different skin colors. The GWAS demonstrated that the L* value among the 3 skin color traits is highly heritable, and the genomic regions located on 2 chromosomes (20 and Z) were detected to harbor SNPs significantly associated with the skin color trait, accounting for most of the total genetic variance. Particular genomic regions spanning a ∼2.94 Mb region on GGA Z and a ∼3.58 Mb region on GGA 20 were significantly associated with skin color traits, and in these regions, certain candidate genes, including MTAP, FEM1C, GNAS, and EDN3, were found. Our findings could help elucidate the genetic mechanisms underlying chicken skin pigmentation. Furthermore, the candidate genes can be used to provide a valuable breeding strategy for the selection of specific chicken breeds with ideal skin coloration.
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Affiliation(s)
- Jihye Cha
- Animal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, South Korea
| | - Daehyeok Jin
- Animal Genetic Resources Research Center, National Institute of Animal Science, Rural Development Administration, Hamyang 50000, South Korea
| | - Jae-Hwan Kim
- Animal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, South Korea
| | - Seung-Chang Kim
- Animal Genetic Resources Research Center, National Institute of Animal Science, Rural Development Administration, Hamyang 50000, South Korea
| | - Jin A Lim
- Animal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, South Korea
| | - Han-Ha Chai
- Animal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, South Korea
| | - Seul A Jung
- Animal Genome & Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju 55365, South Korea
| | - Jun-Heon Lee
- Department of Animal Science and Biotechnology, Chungnam National University, Daejeon 34134, South Korea
| | - Seung-Hwan Lee
- Department of Animal Science and Biotechnology, Chungnam National University, Daejeon 34134, South Korea.
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Dressler EA, Shaffer W, Bruno K, Krehbiel CR, Calvo-Lorenzo M, Richards CJ, Place SE, DeSilva U, Kuehn LA, Weaber RL, Bormann JM, Rolf MM. Heritability and variance component estimation for feed and water intake behaviors of feedlot cattle. J Anim Sci 2023; 101:skad386. [PMID: 37967310 DOI: 10.1093/jas/skad386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 11/14/2023] [Indexed: 11/17/2023] Open
Abstract
Feed and water intake are two important aspects of cattle production that greatly impact the profitability, efficiency, and sustainability of producers. Feed and, to a lesser degree, water intake have been studied previously; however, there is little research on their associated animal behaviors and there is a lack of standardized phenotypes for these behaviors. Feed and water intakes obtained with an Insentec system (Hokofarm Group, The Netherlands) from 830 crossbred steers were used to compute five intake behaviors for both feed and water: daily sessions (DS), intake rate (IR), session size (SS), time per session (TS), and session interval (SI). Variance components and heritabilities were estimated for each trait. Heritabilities for feed intake behaviors were 0.50 ± 0.12, 0.63 ± 0.12, 0.40 ± 0.13, 0.35 ± 0.12, and 0.60 ± 0.12 for DS, IR, SS, TS, and SI, respectively. Heritabilities for water intake behaviors were 0.56 ± 0.11, 0.88 ± 0.07, 0.70 ± 0.11, 0.54 ± 0.12, and 0.80 ± 0.10 for NS, IR, SS, TS, and SI, respectively. Daily dry matter intake (DDMI) and daily water intake (DWI) had heritabilities of 0.57 ± 0.11 and 0.44 ± 0.11. Phenotypic correlations varied between pairs of traits (-0.83 to 0.82). Genetic correlations between DDMI and feed intake behaviors were moderate to high, while genetic correlations between DWI and water intake behaviors were low to moderate. Several significant single nucleotide polymorphisms (SNP) were identified for the feed and water intake behaviors. Genes and previously reported quantitative trait loci near significant SNPs were evaluated. The results indicated that feed and water intake behaviors are influenced by genetic factors and are heritable, providing one additional route to evaluate or manipulate feed and water intake.
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Affiliation(s)
- Elizabeth A Dressler
- Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA
| | - William Shaffer
- Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA
| | - Kelsey Bruno
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
| | - Clint R Krehbiel
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
| | - Michelle Calvo-Lorenzo
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
- Farm Animal Business, Elanco Animal Health, Greenfield, IN 46140, USA
| | - Chris J Richards
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
| | - Sara E Place
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
- Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523, USA
| | - Udaya DeSilva
- Department of Animal Science, Oklahoma State University, Stillwater, OK 74078, USA
| | - Larry A Kuehn
- USDA, ARS, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Robert L Weaber
- Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA
| | - Jennifer M Bormann
- Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA
| | - Megan M Rolf
- Department of Animal Sciences and Industry, Kansas State University, Manhattan, KS 66506, USA
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9
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Exploring and Identifying Candidate Genes and Genomic Regions Related to Economically Important Traits in Hanwoo Cattle. Curr Issues Mol Biol 2022; 44:6075-6092. [PMID: 36547075 PMCID: PMC9777506 DOI: 10.3390/cimb44120414] [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: 09/19/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
The purpose of the current review was to explore and summarize different studies concerning the detection and characterization of candidate genes and genomic regions associated with economically important traits in Hanwoo beef cattle. Hanwoo cattle, the indigenous premium beef cattle of Korea, were introduced for their marbled fat, tenderness, characteristic flavor, and juiciness. To date, there has been a strong emphasis on the genetic improvement of meat quality and yields, such as backfat thickness (BFT), marbling score (MS), carcass weight (CW), eye muscle area (EMA), and yearling weight (YW), as major selection criteria in Hanwoo breeding programs. Hence, an understanding of the genetics controlling these traits along with precise knowledge of the biological mechanisms underlying the traits would increase the ability of the industry to improve cattle to better meet consumer demands. With the development of high-throughput genotyping, genomewide association studies (GWAS) have allowed the detection of chromosomal regions and candidate genes linked to phenotypes of interest. This is an effective and useful tool for accelerating the efficiency of animal breeding and selection. The GWAS results obtained from the literature review showed that most positional genes associated with carcass and growth traits in Hanwoo are located on chromosomes 6 and 14, among which LCORL, NCAPG, PPARGC1A, ABCG2, FAM110B, FABP4, DGAT1, PLAG1, and TOX are well known. In conclusion, this review study attempted to provide comprehensive information on the identified candidate genes associated with the studied traits and genes enriched in the functional terms and pathways that could serve as a valuable resource for future research in Hanwoo breeding programs.
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Kooverjee BB, Soma P, Van Der Nest MA, Scholtz MM, Neser FWC. Selection Signatures in South African Nguni and Bonsmara Cattle Populations Reveal Genes Relating to Environmental Adaptation. Front Genet 2022; 13:909012. [PMID: 35783284 PMCID: PMC9247466 DOI: 10.3389/fgene.2022.909012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/17/2022] [Indexed: 11/30/2022] Open
Abstract
Climate change is a major influencing factor in beef production. The greenhouse gases produced from livestock production systems contribute to the overall greenhouse gas emissions. The aim of this study was to identify selection signatures within and between Nguni and Bonsmara cattle in relation to production and adaptation. For this purpose, genomic 150 K single nucleotide polymorphism data from Nguni (n = 231) and Bonsmara (n = 252) cattle in South Africa were used. Extended haplotype homozygosity (EHH) based analysis was executed within each population using integrated haplotype score (iHS). The R package rehh was used for detecting selection signatures across the two populations with cross population EHH (XP-EHH). Total of 121 regions of selection signatures were detected (p < 0.0001) in the Bonsmara and Nguni populations. Several genes relating to DNA methylation, heat stress, feed efficiency and nitrogen metabolism were detected within and between each population. These regions also included QTLs associated with residual feed intake, residual gain, carcass weight, stature and body weight in the Bonsmara, while QTLs associated with conception rate, shear force, tenderness score, juiciness, temperament, heat tolerance, feed efficiency and age at puberty were identified in Nguni. Based on the results of the study it is recommended that the Nguni and Bonsmara be utilized in crossbreeding programs as they have beneficial traits that may allow them to perform better in the presence of climate change. Results of this study coincide with Nguni and Bonsmara breed characteristics and performance, and furthermore support informative crossbreeding programs to enhance livestock productivity in South Africa.
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Affiliation(s)
- Bhaveni B. Kooverjee
- Department of Animal Breeding and Genetics, Animal Production, Agricultural Research Council, Pretoria, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
- *Correspondence: Bhaveni B. Kooverjee, ; Pranisha Soma,
| | - Pranisha Soma
- Department of Animal Breeding and Genetics, Animal Production, Agricultural Research Council, Pretoria, South Africa
- *Correspondence: Bhaveni B. Kooverjee, ; Pranisha Soma,
| | | | - Michiel M. Scholtz
- Department of Animal Breeding and Genetics, Animal Production, Agricultural Research Council, Pretoria, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - Frederick W. C. Neser
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
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11
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Alvarenga AB, Oliveira HR, Miller SP, Silva FF, Brito LF. Genetic Modeling and Genomic Analyses of Yearling Temperament in American Angus Cattle and Its Relationship With Productive Efficiency and Resilience Traits. Front Genet 2022; 13:794625. [PMID: 35444687 PMCID: PMC9014094 DOI: 10.3389/fgene.2022.794625] [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: 10/13/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
Cattle temperament has been considered by farmers as a key breeding goal due to its relevance for cattlemen's safety, animal welfare, resilience, and longevity and its association with many economically important traits (e.g., production and meat quality). The definition of proper statistical models, accurate variance component estimates, and knowledge on the genetic background of the indicator trait evaluated are of great importance for accurately predicting the genetic merit of breeding animals. Therefore, 266,029 American Angus cattle with yearling temperament records (1-6 score) were used to evaluate statistical models and estimate variance components; investigate the association of sex and farm management with temperament; assess the weighted correlation of estimated breeding values for temperament and productive, reproductive efficiency and resilience traits; and perform a weighted single-step genome-wide association analysis using 69,559 animals genotyped for 54,609 single-nucleotide polymorphisms. Sex and extrinsic factors were significantly associated with temperament, including conception type, age of dam, birth season, and additional animal-human interactions. Similar results were observed among models including only the direct additive genetic effect and when adding other maternal effects. Estimated heritability of temperament was equal to 0.39 on the liability scale. Favorable genetic correlations were observed between temperament and other relevant traits, including growth, feed efficiency, meat quality, and reproductive traits. The highest approximated genetic correlations were observed between temperament and growth traits (weaning weight, 0.28; yearling weight, 0.28). Altogether, we identified 11 genomic regions, located across nine chromosomes including BTAX, explaining 3.33% of the total additive genetic variance. The candidate genes identified were enriched in pathways related to vision, which could be associated with reception of stimulus and/or cognitive abilities. This study encompasses large and diverse phenotypic, genomic, and pedigree datasets of US Angus cattle. Yearling temperament is a highly heritable and polygenic trait that can be improved through genetic selection. Direct selection for temperament is not expected to result in unfavorable responses on other relevant traits due to the favorable or low genetic correlations observed. In summary, this study contributes to a better understanding of the impact of maternal effects, extrinsic factors, and various genomic regions associated with yearling temperament in North American Angus cattle.
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Affiliation(s)
- Amanda B Alvarenga
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
| | - Hinayah R Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States.,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Stephen P Miller
- American Angus Association, Angus Genetics Inc., St Joseph, MO, United States
| | - Fabyano F Silva
- Department of Animal Sciences, Federal University of Vicosa, Viçosa, Brazil
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, United States
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12
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Ogawa S, Matsuda H, Taniguchi Y, Watanabe T, Sugimoto Y, Iwaisaki H. Estimation of the autosomal contribution to total additive genetic variability of carcass traits in Japanese Black cattle. Anim Sci J 2022; 93:e13710. [PMID: 35416392 DOI: 10.1111/asj.13710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/18/2022] [Accepted: 03/18/2022] [Indexed: 11/29/2022]
Abstract
We attempted to estimate the additive genetic variance explained by each autosome, using genotype data of 33,657 single nucleotide polymorphism (SNP) markers in 2271 Japanese Black fattened steers. Traits were cold carcass weight, ribeye area, rib thickness, subcutaneous fat thickness, estimated yield percentage, and marbling score. Two mixed linear models were used: One is that (model 1) incorporating a genomic relationship matrix (G matrix) constructed by using all available SNPs, and another (model 2), incorporating two G matrices constructed by using the SNPs on one autosome and using those on the remaining autosomes. Genomic heritabilities estimated using model 1 were moderate to high. The sums of the proportions of the additive genetic variance explained by each autosome to the total genetic variance estimated by using model 2 were >90%. For carcass weight, the proportions explained by Bos taurus autosomes 6, 8, and 14 were higher than those explained by the remaining autosomes. In some cases, the estimated proportion was close to 0. The results obtained from model 2 could provide a novel insight into the genetic architecture, such as heritability per chromosome, of carcass traits in Japanese Black cattle, although further careful investigation would be required.
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Affiliation(s)
| | | | - Yukio Taniguchi
- Graduate School of Agriculture, Kyoto University, Kyoto, Japan
| | | | - Yoshikazu Sugimoto
- Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Tokyo, Japan
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13
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Bedhane M, van der Werf J, de las Heras-Saldana S, Lim D, Park B, Na Park M, Seung Hee R, Clark S. The accuracy of genomic prediction for meat quality traits in Hanwoo cattle when using genotypes from different SNP densities and preselected variants from imputed whole genome sequence. ANIMAL PRODUCTION SCIENCE 2022. [DOI: 10.1071/an20659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Context
Genomic prediction is the use of genomic data in the estimation of genomic breeding values (GEBV) in animal breeding. In beef cattle breeding programs, genomic prediction increases the rates of genetic gain by increasing the accuracy of selection at earlier ages.
Aims
The objectives of the study were to examine the effect of single-nucleotide polymorphism (SNP) density and to evaluate the effect of using SNPs preselected from imputed whole-genome sequence for genomic prediction.
Methods
Genomic and phenotypic data from 2110 Hanwoo steers were used to predict GEBV for marbling score (MS), meat texture (MT), and meat colour (MC) traits. Three types of SNP densities including 50k, high-density (HD), and whole-genome sequence data and preselected SNPs from genome-wide association study (GWAS) were used for genomic prediction analyses. Two scenarios (independent and dependent discovery populations) were used to select top significant SNPs. The accuracy of GEBV was assessed using random cross-validation. Genomic best linear unbiased prediction (GBLUP) was used to predict the breeding values for each trait.
Key results
Our result showed that very similar prediction accuracies were observed across all SNP densities used in the study. The prediction accuracy among traits ranged from 0.29±0.05 for MC to 0.46±0.04 for MS. Depending on the studied traits, up to 5% of prediction accuracy improvement was obtained when the preselected SNPs from GWAS analysis were included in the prediction analysis.
Conclusions
High SNP density such as HD and the whole-genome sequence data yielded a similar prediction accuracy in Hanwoo beef cattle. Therefore, the 50K SNP chip panel is sufficient to capture the relationships in a breed with a small effective population size such as the Hanwoo cattle population. Preselected variants improved prediction accuracy when they were included in the genomic prediction model.
Implications
The estimated genomic prediction accuracies are moderately accurate in Hanwoo cattle and for searching for SNPs that are more productive could increase the accuracy of estimated breeding values for the studied traits.
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14
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Niu Q, Zhang T, Xu L, Wang T, Wang Z, Zhu B, Gao X, Chen Y, Zhang L, Gao H, Li J, Xu L. Identification of Candidate Variants Associated With Bone Weight Using Whole Genome Sequence in Beef Cattle. Front Genet 2021; 12:750746. [PMID: 34912371 PMCID: PMC8667311 DOI: 10.3389/fgene.2021.750746] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 10/18/2021] [Indexed: 11/13/2022] Open
Abstract
Bone weight is critical to affect body conformation and stature in cattle. In this study, we conducted a genome-wide association study for bone weight in Chinese Simmental beef cattle based on the imputed sequence variants. We identified 364 variants associated with bone weight, while 350 of them were not included in the Illumina BovineHD SNP array, and several candidate genes and GO terms were captured to be associated with bone weight. Remarkably, we identified four potential variants in a candidate region on BTA6 using Bayesian fine-mapping. Several important candidate genes were captured, including LAP3, MED28, NCAPG, LCORL, SLIT2, and IBSP, which have been previously reported to be associated with carcass traits, body measurements, and growth traits. Notably, we found that the transcription factors related to MED28 and LCORL showed high conservation across multiple species. Our findings provide some valuable information for understanding the genetic basis of body stature in beef cattle.
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Affiliation(s)
- Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ling Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianzhen Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zezhao Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xue Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yan Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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15
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Naserkheil M, Mehrban H, Lee D, Park MN. Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle. Front Genet 2021; 12:752424. [PMID: 34899840 PMCID: PMC8662546 DOI: 10.3389/fgene.2021.752424] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 11/02/2021] [Indexed: 12/30/2022] Open
Abstract
The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.
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Affiliation(s)
- Masoumeh Naserkheil
- Animal Breeding and Genetics Division, National Institute of Animal Science, Cheonan-si, South Korea
| | - Hossein Mehrban
- Department of Animal Science, Shahrekord University, Shahrekord, Iran
| | - Deukmin Lee
- Department of Animal Life and Environment Sciences, Hankyong National University, Anseong-si, South Korea
| | - Mi Na Park
- Animal Breeding and Genetics Division, National Institute of Animal Science, Cheonan-si, South Korea
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16
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McFarlane SE, Pemberton JM. Admixture mapping reveals loci for carcass mass in red deer x sika hybrids in Kintyre, Scotland. G3 (BETHESDA, MD.) 2021; 11:jkab274. [PMID: 34568926 PMCID: PMC8473967 DOI: 10.1093/g3journal/jkab274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/16/2021] [Indexed: 12/21/2022]
Abstract
We deployed admixture mapping on a sample of 386 deer from a hybrid swarm between native red deer (Cervus elaphus) and introduced Japanese sika (Cervus nippon) sampled in Kintyre, Scotland to search for quantitative trait loci (QTLs) underpinning phenotypic differences between the species. These two species are highly diverged genetically [Fst between pure species, based on 50K single nucleotide polymorphism (SNPs) = 0.532] and phenotypically: pure red have on average twice the carcass mass of pure sika in our sample (38.7 kg vs 19.1 kg). After controlling for sex, age, and population genetic structure, we found 10 autosomal genomic locations with QTL for carcass mass. Effect sizes ranged from 0.191 to 1.839 kg and as expected, in all cases the allele derived from sika conferred lower carcass mass. The sika population was fixed for all small carcass mass alleles, whereas the red deer population was typically polymorphic. GO term analysis of genes lying in the QTL regions are associated with oxygen transport. Although body mass is a likely target of selection, none of the SNPs marking QTL are introgressing faster or slower than expected in either direction.
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Affiliation(s)
- S Eryn McFarlane
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
- Department of Biology, Lund University, 22100 Lund, Sweden
| | - Josephine M Pemberton
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
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17
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Nwogwugwu CP, Kim Y, Cho S, Roh HJ, Cha J, Lee SH, Lee JH. Optimal population size to detect quantitative trait locus in Korean native chicken: a simulation study. Anim Biosci 2021; 35:511-516. [PMID: 34530512 PMCID: PMC8902204 DOI: 10.5713/ab.21.0195] [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: 04/23/2021] [Accepted: 08/16/2021] [Indexed: 11/27/2022] Open
Abstract
Objective A genomic region associated with a particular phenotype is called quantitative trait loci (QTL). To detect the optimal F2 population size associated with QTLs in native chicken, we performed a simulation study on F2 population derived from crosses between two different breeds. Methods A total of 15 males and 150 females were randomly selected from the last generation of each F1 population which was composed of different breed to create two different F2 populations. The progenies produced from these selected individuals were simulated for six more generations. Their marker genotypes were simulated with a density of 50K at three different heritability levels for the traits such as 0.1, 0.3, and 0.5. Our study compared 100, 500, 1,000 reference population (RP) groups to each other with three different heritability levels. And a total of 35 QTLs were used, and their locations were randomly created. Results With a RP size of 100, no QTL was detected to satisfy Bonferroni value at three different heritability levels. In a RP size of 500, two QTLs were detected when the heritability was 0.5. With a RP size of 1,000, 0.1 heritability was detected only one QTL, and 0.5 heritability detected five QTLs. To sum up, RP size and heritability play a key role in detecting QTLs in a QTL study. The larger RP size and greater heritability value, the higher the probability of detection of QTLs. Conclusion Our study suggests that the use of a large RP and heritability can improve QTL detection in an F2 chicken population.
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Affiliation(s)
| | - Yeongkuk Kim
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Sunghyun Cho
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Hee-Jong Roh
- Animal Genetic Resources Center, National Institute of Animal Science, RDA, Hamyang 50000, Korea
| | - Jihye Cha
- Animal Genomics and Bioinformatics Division, 1500, Kongjwipatjwi-ro, Iseo-myeon, Wanju-gun, Jeollabuk-do 55365, Korea
| | - Seung Hwan Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
| | - Jun Heon Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea
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Genome-Wide Association Study Identifies Candidate Genes Associated with Feet and Leg Conformation Traits in Chinese Holstein Cattle. Animals (Basel) 2021; 11:ani11082259. [PMID: 34438715 PMCID: PMC8388412 DOI: 10.3390/ani11082259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 07/24/2021] [Accepted: 07/28/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Feet and leg problems are among the major reasons for dairy cows leaving the herd, as well as having direct association with production and reproduction efficiency, health (e.g., claw disorders and lameness) and welfare. Hence, understanding the genetic architecture underlying feet and conformation traits in dairy cattle offers new opportunities toward the genetic improvement and long-term selection. Through a genome-wide association study on Chinese Holstein cattle, we identified several candidate genes associated with feet and leg conformation traits. These results could provide useful information about the molecular breeding basis of feet and leg traits, thus improving the longevity and productivity of dairy cattle. Abstract Feet and leg conformation traits are considered one of the most important economical traits in dairy cattle and have a great impact on the profitability of milk production. Therefore, identifying the single nucleotide polymorphisms (SNPs), genes and pathways analysis associated with these traits might contribute to the genomic selection and long-term plan selection for dairy cattle. We conducted genome-wide association studies (GWASs) using the fixed and random model circulating probability unification (FarmCPU) method to identify SNPs associated with bone quality, heel depth, rear leg side view and rear leg rear view of Chinese Holstein cows. Phenotypic measurements were collected from 1000 individuals of Chinese Holstein cattle and the GeneSeek Genomic Profiler Bovine 100 K SNP chip was utilized for individual genotyping. After quality control, 984 individual cows and 84,906 SNPs remained for GWAS work; as a result, we identified 20 significant SNPs after Bonferroni correction. Several candidate genes were identified within distances of 200 kb upstream or downstream to the significant SNPs, including ADIPOR2, INPP4A, DNMT3A, ALDH1A2, PCDH7, XKR4 and CADPS. Further bioinformatics analyses showed 34 gene ontology terms and two signaling pathways were significantly enriched (p ≤ 0.05). Many terms and pathways are related to biological quality, metabolism and development processes; these identified SNPs and genes could provide useful information about the genetic architecture of feet and leg traits, thus improving the longevity and productivity of Chinese Holstein dairy cattle.
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Niu Q, Zhang T, Xu L, Wang T, Wang Z, Zhu B, Zhang L, Gao H, Song J, Li J, Xu L. Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle. Genomics 2021; 113:3325-3336. [PMID: 34314829 DOI: 10.1016/j.ygeno.2021.07.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/05/2021] [Accepted: 07/22/2021] [Indexed: 11/18/2022]
Abstract
Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.
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Affiliation(s)
- Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ling Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Tianzhen Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Zezhao Wang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Jiuzhou Song
- Department of Animal and Avian Science, University of Maryland, College Park, USA
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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20
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Martinez-Castillero M, Then C, Altarriba J, Srihi H, López-Carbonell D, Díaz C, Martinez P, Hermida M, Varona L. Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed. Animals (Basel) 2021; 11:ani11061682. [PMID: 34200089 PMCID: PMC8227173 DOI: 10.3390/ani11061682] [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: 04/28/2021] [Revised: 05/25/2021] [Accepted: 06/02/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. We have developed a ssGWAS by backsolving the SNP effects after implementing a ssGBLUP. The results showed an apparent heterogeneity of the additive genetic variance across the genome. Some of the genomic regions explaining the most of this additive variance were shared across traits, indicating the presence of pleiotropic effects, which were reflected in their genetic correlations. Abstract The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: NCK1, MSTN, KCNA3, LCORL, NCAPG, and RIN3.
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Affiliation(s)
- Maria Martinez-Castillero
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
- Correspondence:
| | - Carlos Then
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Juan Altarriba
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Houssemeddine Srihi
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - David López-Carbonell
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
| | - Clara Díaz
- Instituto Nacional de Investigación y Tecnología Agraria (INIA), 28040 Madrid, Spain;
| | - Paulino Martinez
- Facultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, Spain; (P.M.); (M.H.)
| | - Miguel Hermida
- Facultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, Spain; (P.M.); (M.H.)
| | - Luis Varona
- Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, Spain; (C.T.); (J.A.); (H.S.); (D.L.-C.); (L.V.)
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21
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Lopez BIM, An N, Srikanth K, Lee S, Oh JD, Shin DH, Park W, Chai HH, Park JE, Lim D. Genomic Prediction Based on SNP Functional Annotation Using Imputed Whole-Genome Sequence Data in Korean Hanwoo Cattle. Front Genet 2021; 11:603822. [PMID: 33552124 PMCID: PMC7859490 DOI: 10.3389/fgene.2020.603822] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022] Open
Abstract
Whole-genome sequence (WGS) data are increasingly being applied into genomic predictions, offering a higher predictive ability by including causal mutations or single-nucleotide polymorphisms (SNPs) putatively in strong linkage disequilibrium with causal mutations affecting the trait. This study aimed to improve the predictive performance of the customized Hanwoo 50 k SNP panel for four carcass traits in commercial Hanwoo population by adding highly predictive variants from sequence data. A total of 16,892 Hanwoo cattle with phenotypes (i.e., backfat thickness, carcass weight, longissimus muscle area, and marbling score), 50 k genotypes, and WGS imputed genotypes were used. We partitioned imputed WGS data according to functional annotation [intergenic (IGR), intron (ITR), regulatory (REG), synonymous (SYN), and non-synonymous (NSY)] to characterize the genomic regions that will deliver higher predictive power for the traits investigated. Animals were assigned into two groups, the discovery set (7324 animals) used for predictive variant detection and the cross-validation set for genomic prediction. Genome-wide association studies were performed by trait to every genomic region and entire WGS data for the pre-selection of variants. Each set of pre-selected SNPs with different density (1000, 3000, 5000, or 10,000) were added to the 50 k genotypes separately and the predictive performance of each set of genotypes was assessed using the genomic best linear unbiased prediction (GBLUP). Results showed that the predictive performance of the customized Hanwoo 50 k SNP panel can be improved by the addition of pre-selected variants from the WGS data, particularly 3000 variants from each trait, which is then sufficient to improve the prediction accuracy for all traits. When 12,000 pre-selected variants (3000 variants from each trait) were added to the 50 k genotypes, the prediction accuracies increased by 9.9, 9.2, 6.4, and 4.7% for backfat thickness, carcass weight, longissimus muscle area, and marbling score compared to the regular 50 k SNP panel, respectively. In terms of prediction bias, regression coefficients for all sets of genotypes in all traits were close to 1, indicating an unbiased prediction. The strategy used to select variants based on functional annotation did not show a clear advantage compared to using whole-genome. Nonetheless, such pre-selected SNPs from the IGR region gave the highest improvement in prediction accuracy among genomic regions and the values were close to those obtained using the WGS data for all traits. We concluded that additional gain in prediction accuracy when using pre-selected variants appears to be trait-dependent, and using WGS data remained more accurate compared to using a specific genomic region.
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Affiliation(s)
- Bryan Irvine M Lopez
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Narae An
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Krishnamoorthy Srikanth
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Seunghwan Lee
- Department of Animal Science and Biotechnology, Chungnam National University, Daejeon, South Korea
| | - Jae-Don Oh
- Department of Animal Biotechnology, Chonbuk National University, Jeonju, South Korea
| | - Dong-Hyun Shin
- Department of Agricultural Convergence Technology, Chonbuk National University, Jeonju, South Korea
| | - Woncheoul Park
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Han-Ha Chai
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Jong-Eun Park
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Dajeong Lim
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
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22
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Yang L, Niu Q, Zhang T, Zhao G, Zhu B, Chen Y, Zhang L, Gao X, Gao H, Liu GE, Li J, Xu L. Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle. Genomics 2020; 113:812-820. [PMID: 33080318 DOI: 10.1016/j.ygeno.2020.10.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/21/2020] [Accepted: 10/05/2020] [Indexed: 11/25/2022]
Abstract
Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.
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Affiliation(s)
- Liu Yang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
| | - Qunhao Niu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Tianliu Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Guoyao Zhao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Bo Zhu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yan Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Lupei Zhang
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Xue Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Huijiang Gao
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD 20705, USA.
| | - Junya Li
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lingyang Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
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23
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Naserkheil M, Bahrami A, Lee D, Mehrban H. Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle. Animals (Basel) 2020; 10:ani10101836. [PMID: 33050182 PMCID: PMC7601430 DOI: 10.3390/ani10101836] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/02/2020] [Accepted: 10/06/2020] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. Gene set enrichment analysis indicated that the identified candidate genes were related to biological processes and functional terms that were involved in growth and lipid metabolism. In conclusion, these results suggest that the incorporation of GWAS results and network analysis can help us to better understand the genetic bases underlying growth and carcass traits. Abstract In recent years, studies on the biological mechanisms underlying complex traits have been facilitated by innovations in high-throughput genotyping technology. We conducted a weighted single-step genome-wide association study (WssGWAS) to evaluate backfat thickness, carcass weight, eye muscle area, marbling score, and yearling weight in a cohort of 1540 Hanwoo beef cattle using BovineSNP50 BeadChip. The WssGWAS uncovered thirty-three genomic regions that explained more than 1% of the additive genetic variance, mostly located on chromosomes 6 and 14. Among the identified window regions, seven quantitative trait loci (QTL) had pleiotropic effects and twenty-six QTL were trait-specific. Significant pathways implicated in the measured traits through Gene Ontology (GO) term enrichment analysis included the following: lipid biosynthetic process, regulation of lipid metabolic process, transport or localization of lipid, regulation of growth, developmental growth, and multicellular organism growth. Integration of GWAS results of the studied traits with pathway and network analyses facilitated the exploration of the respective candidate genes involved in several biological functions, particularly lipid and growth metabolism. This study provides novel insight into the genetic bases underlying complex traits and could be useful in developing breeding schemes aimed at improving growth and carcass traits in Hanwoo beef cattle.
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Affiliation(s)
- Masoumeh Naserkheil
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; (M.N.); (A.B.)
| | - Abolfazl Bahrami
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; (M.N.); (A.B.)
| | - Deukhwan Lee
- Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea
- Correspondence: ; Tel.: +82-31-670-5091
| | - Hossein Mehrban
- Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran;
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24
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de Las Heras-Saldana S, Lopez BI, Moghaddar N, Park W, Park JE, Chung KY, Lim D, Lee SH, Shin D, van der Werf JHJ. Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle. Genet Sel Evol 2020; 52:54. [PMID: 32993481 PMCID: PMC7525992 DOI: 10.1186/s12711-020-00574-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/18/2020] [Indexed: 12/21/2022] Open
Abstract
Background In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals. Results Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy. Conclusions Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.
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Affiliation(s)
| | - Bryan Irvine Lopez
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju, 55365, Republic of Korea
| | - Nasir Moghaddar
- School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia
| | - Woncheoul Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju, 55365, Republic of Korea
| | - Jong-Eun Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju, 55365, Republic of Korea
| | - Ki Y Chung
- Department of Beef Science, Korea National College of Agriculture and Fisheries, Jeonju, Republic of Korea
| | - Dajeong Lim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju, 55365, Republic of Korea.
| | - Seung H Lee
- Division of Animal and Dairy Science, Chungnam National University, Deajeon, 34148, Republic of Korea
| | - Donghyun Shin
- The Animal Molecular Genetics and Breeding Centre, Jeonbuk National University, Jeonju, 54896, Republic of Korea
| | - Julius H J van der Werf
- School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.
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25
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Raza SHA, Khan S, Amjadi M, Abdelnour SA, Ohran H, Alanazi KM, Abd El-Hack ME, Taha AE, Khan R, Gong C, Schreurs NM, Zhao C, Wei D, Zan L. Genome-wide association studies reveal novel loci associated with carcass and body measures in beef cattle. Arch Biochem Biophys 2020; 694:108543. [PMID: 32798459 DOI: 10.1016/j.abb.2020.108543] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 07/26/2020] [Accepted: 08/08/2020] [Indexed: 12/18/2022]
Abstract
Genomic selection has an essential role in the livestock economy by increasing selection productivity. Genomics provides a mechanism to increase the rate of genetic gain using marker-assisted selection. Various quantitative trait loci (QTL) associated with body, carcass and meat quality traits in beef cattle have been found. It is widely accepted that QTL traits in livestock species are regulated by several genes and factors from the environment. Genome-wide association studies (GWAS) are a powerful approach in identifying QTL and to establish genomic regions harboring the genes and polymorphisms associated with specific characteristics in beef cattle. Due to their impact on economic returns, growth, carcass and meat quality traits of cattle are frequently used as essential criteria in selection in breeding programs., GWAS has been used in beef cattle breeding and genetic program and some progress has been made. Furthermore, numerous genes and markers related to productivity traits in beef cattle have been found. This review summarizes the advances in the use of GWAS in beef cattle production and outlines the associations with growth, carcass, and meat quality.
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Affiliation(s)
- Sayed Haidar Abbas Raza
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China.
| | - Samiullah Khan
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming, Yunnan, 650201, China
| | - Motahareh Amjadi
- Department of Genetics, Eötvös Loránd University, Budapest, Hungary
| | - Sameh A Abdelnour
- Department of Animal Production, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
| | - Hussien Ohran
- Department of Physiology, University of Sarajevo, Veterinary Faculty, Zmajaod Bosne 90, 71000, Sarajevo, Bosnia and Herzegovina
| | - Khalid M Alanazi
- Zoology Department, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
| | - Mohamed E Abd El-Hack
- Department of Poultry, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
| | - Ayman E Taha
- Department of Animal Husbandry and Animal Wealth Development, Faculty of Veterinary Medicine, Alexandria University, Edfina, 22578, Egypt
| | - Rajwali Khan
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Cheng Gong
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Nicola M Schreurs
- Animal Science, School of Agriculture and Environment, Massey University, Palmerston North, New Zealand
| | - Chunping Zhao
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Dawei Wei
- School of Agriculture, Ningxia University, Yinchuan, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China; National Beef Cattle Improvement Center, Northwest A&F University, Yangling, 712100, China.
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26
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Lee SH, Seo D, Lee DH, Kang JM, Kim YK, Lee KT, Kim TH, Choi BH, Lee SH. Comparison of prediction accuracy for genomic estimated breeding
value using the reference pig population of single-breed and
admixed-breed. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2020; 62:438-448. [PMID: 32803176 PMCID: PMC7416156 DOI: 10.5187/jast.2020.62.4.438] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 06/18/2020] [Accepted: 06/18/2020] [Indexed: 11/20/2022]
Abstract
This study was performed to increase the accuracy of genomic estimated breeding
value (GEBV) predictions for domestic pigs using single-breed and admixed
reference populations (single-breed of Berkshire pigs [BS] with cross breed of
Korean native pigs and Landrace pigs [CB]). The principal component analysis
(PCA), linkage disequilibrium (LD), and genome-wide association study (GWAS)
were performed to analyze the population structure prior to genomic prediction.
Reference and test population data sets were randomly sampled 10 times each and
precision accuracy was analyzed according to the size of the reference
population (100, 200, 300, or 400 animals). For the BS population, prediction
accuracy was higher for all economically important traits with larger reference
population size. Prediction accuracy was ranged from −0.05 to 0.003, for
all traits except carcass weight (CWT), when CB was used as the reference
population and BS as the test. The accuracy of CB for backfat thickness (BF) and
shear force (SF) using admixed population as reference increased with reference
population size, while the results for CWT and muscle pH at 24 hours after
slaughter (pH) were equivocal with respect to the relationship between accuracy
and reference population size, although overall accuracy was similar to that
using the BS as the reference.
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Affiliation(s)
- Soo Hyun Lee
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Dongwon Seo
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Doo Ho Lee
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Ji Min Kang
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Yeong Kuk Kim
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
| | - Kyung Tai Lee
- Animal Genomics and Bioinformatics
Division, National Institute of Animal Science, RDA, Wanju
55365, Korea
| | - Tae Hun Kim
- Animal Genomics and Bioinformatics
Division, National Institute of Animal Science, RDA, Wanju
55365, Korea
| | - Bong Hwan Choi
- Animal Genomics and Bioinformatics
Division, National Institute of Animal Science, RDA, Wanju
55365, Korea
- Corresponding author: Bong Hwan Choi, Animal
Genomics & Bioinformatics Division, National Institute of Animal Science,
RDA, Wanju 55365, Korea. Tel: +82-63-238-7304 E-mail:
| | - Seung Hwan Lee
- Division of Animal and Dairy Science,
Chungnam National University, Daejeon 34134, Korea
- Corresponding author: Seung Hwan Lee, Division of
Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea.
Tel: +82-42-821-5772 E-mail:
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Srikanth K, Lee SH, Chung KY, Park JE, Jang GW, Park MR, Kim NY, Kim TH, Chai HH, Park WC, Lim D. A Gene-Set Enrichment and Protein-Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle. Genes (Basel) 2020; 11:E316. [PMID: 32188084 PMCID: PMC7140899 DOI: 10.3390/genes11030316] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 03/06/2020] [Accepted: 03/12/2020] [Indexed: 02/06/2023] Open
Abstract
Non-synonymous SNPs and protein coding SNPs within the promoter region of genes (regulatory SNPs) might have a significant effect on carcass traits. Imputed sequence level data of 10,215 Hanwoo bulls, annotated and filtered to include only regulatory SNPs (450,062 SNPs), were used in a genome-wide association study (GWAS) to identify loci associated with backfat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). A total of 15, 176, and 1 SNPs were found to be significantly associated (p < 1.11 × 10-7) with BFT, CWT, and EMA, respectively. The significant loci were BTA4 (CWT), BTA6 (CWT), BTA14 (CWT and EMA), and BTA19 (BFT). BayesR estimated that 1.1%~1.9% of the SNPs contributed to more than 0.01% of the phenotypic variance. So, the GWAS was complemented by a gene-set enrichment (GSEA) and protein-protein interaction network (PPIN) analysis in identifying the pathways affecting carcass traits. At p < 0.005 (~2,261 SNPs), 25 GO and 18 KEGG categories, including calcium signaling, cell proliferation, and folate biosynthesis, were found to be enriched through GSEA. The PPIN analysis showed enrichment for 81 candidate genes involved in various pathways, including the PI3K-AKT, calcium, and FoxO signaling pathways. Our finding provides insight into the effects of regulatory SNPs on carcass traits.
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Affiliation(s)
- Krishnamoorthy Srikanth
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Seung-Hwan Lee
- Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea;
| | - Ki-Yong Chung
- Department of Beef Science, Korea National College of Agriculture and Fisheries, Jeonju 54874, Korea;
| | - Jong-Eun Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Gul-Won Jang
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Mi-Rim Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Na Yeon Kim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Tae-Hun Kim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Han-Ha Chai
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Won Cheoul Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
| | - Dajeong Lim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju 55365, Korea (J.-E.P.); (G.-W.J.); (M.-R.P.); (N.Y.K.); (T.-H.K.); (H.-H.C.); (W.C.P.)
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28
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Bedhane M, van der Werf J, Gondro C, Duijvesteijn N, Lim D, Park B, Park MN, Hee RS, Clark S. Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data. Front Genet 2019; 10:1235. [PMID: 31850078 PMCID: PMC6895209 DOI: 10.3389/fgene.2019.01235] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 11/06/2019] [Indexed: 01/28/2023] Open
Abstract
The discovery of single nucleotide polymorphisms (SNP) and the subsequent genotyping of large numbers of animals have enabled large-scale analyses to begin to understand the biological processes that underpin variation in animal populations. In beef cattle, genome-wide association studies using genotype arrays have revealed many quantitative trait loci (QTL) for various production traits such as growth, efficiency and meat quality. Most studies regarding meat quality have focused on marbling, which is a key trait associated with meat eating quality. However, other important traits like meat color, texture and fat color have not commonly been studied. Developments in genome sequencing technologies provide new opportunities to identify regions associated with these traits more precisely. The objective of this study was to estimate variance components and identify significant variants underpinning variation in meat quality traits using imputed whole genome sequence data. Phenotypic and genomic data from 2,110 Hanwoo cattle were used. The estimated heritabilities for the studied traits were 0.01, 0.16, 0.31, and 0.49 for fat color, meat color, meat texture and marbling score, respectively. Marbling score and meat texture were highly correlated. The genome-wide association study revealed 107 significant SNPs located on 14 selected chromosomes (one QTL region per selected chromosome). Four QTL regions were identified on BTA2, 12, 16, and 24 for marbling score and two QTL regions were found for meat texture trait on BTA12 and 29. Similarly, three QTL regions were identified for meat color on BTA2, 14 and 24 and five QTL regions for fat color on BTA7, 10, 12, 16, and 21. Candidate genes were identified for all traits, and their potential influence on the given trait was discussed. The significant SNP will be an important inclusion into commercial genotyping arrays to select new breeding animals more accurately.
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Affiliation(s)
- Mohammed Bedhane
- School of Environmental and Rural Science, University of New England, Armidale, Australia
| | - Julius van der Werf
- School of Environmental and Rural Science, University of New England, Armidale, Australia
| | - Cedric Gondro
- College of Agriculture & Natural Resources, Michigan State University, East Lansing, MI, United States
| | - Naomi Duijvesteijn
- School of Environmental and Rural Science, University of New England, Armidale, Australia
| | - Dajeong Lim
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Byoungho Park
- Animal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea
| | - Mi Na Park
- Animal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea
| | - Roh Seung Hee
- Animal Genetic Improvement Division, National Institute of Animal Science, Rural Development Administration, Seonghwan, South Korea
| | - Samuel Clark
- School of Environmental and Rural Science, University of New England, Armidale, Australia
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29
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Riley D, Miller R, Nicholson K, Gill C, Herring A, Riggs P, Sawyer J, Savell J, Sanders J. Genome association of carcass and palatability traits from Bos indicus-Bos taurus crossbred steers within electrical stimulation status and correspondence with steer temperament 1. Carcass. Livest Sci 2019. [DOI: 10.1016/j.livsci.2019.09.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Genetic mapping of distal femoral, stifle, and tibial radiographic morphology in dogs with cranial cruciate ligament disease. PLoS One 2019; 14:e0223094. [PMID: 31622367 PMCID: PMC6797204 DOI: 10.1371/journal.pone.0223094] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2018] [Accepted: 09/14/2019] [Indexed: 11/19/2022] Open
Abstract
Cranial cruciate ligament disease (CCLD) is a complex trait. Ten measurements were made on orthogonal distal pelvic limb radiographs of 161 pure and mixed breed dogs with, and 55 without, cranial cruciate partial or complete ligament rupture. Dogs with CCLD had significantly smaller infrapatellar fat pad width, higher average tibial plateau angle, and were heavier than control dogs. The first PC weightings captured the overall size of the dog’s stifle and PC2 weightings reflected an increasing tibial plateau angle coupled with a smaller fat pad width. Of these dogs, 175 were genotyped, and 144,509 polymorphisms were used in a genome-wide association study with both a mixed linear and a multi-locus model. For both models, significant (pgenome <3.46×10−7 for the mixed and< 6.9x10-8 for the multilocus model) associations were found for PC1, tibial diaphyseal length and width, fat pad base length, and femoral and tibial condyle width at LCORL, a known body size-regulating locus. Other body size loci with significant associations were growth hormone 1 (GH1), which was associated with the length of the fat pad base and the width of the tibial diaphysis, and a region on CFAX near IRS4 and ACSL4 in the multilocus model. The tibial plateau angle was associated significantly with a locus on CFA10 in the linear mixed model with nearest candidate genes BET1 and MYH9 and on CFA08 near candidate genes WDHD1 and GCH1. MYH9 has a major role in osteoclastogenesis. Our study indicated that tibial plateau slope is associated with CCLD and a compressed infrapatellar fat pad, a surrogate for stifle osteoarthritis. Because of the association between tibial plateau slope and CCLD, and pending independent validation, these candidate genes for tibial plateau slope may be tested in breeds susceptible to CCLD before they develop disease or are bred.
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31
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Purfield DC, Evans RD, Berry DP. Reaffirmation of known major genes and the identification of novel candidate genes associated with carcass-related metrics based on whole genome sequence within a large multi-breed cattle population. BMC Genomics 2019; 20:720. [PMID: 31533623 PMCID: PMC6751660 DOI: 10.1186/s12864-019-6071-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 08/29/2019] [Indexed: 12/25/2022] Open
Abstract
Background The high narrow sense heritability of carcass traits suggests that the underlying additive genetic potential of an individual should be strongly correlated with both animal carcass quality and quantity, and therefore, by extension, carcass value. Therefore, the objective of the present study was to detect genomic regions associated with three carcass traits, namely carcass weight, conformation and fat cover, using imputed whole genome sequence in 28,470 dairy and beef sires from six breeds with a total of 2,199,926 phenotyped progeny. Results Major genes previously associated with carcass performance were identified, as well as several putative novel candidate genes that likely operate both within and across breeds. The role of MSTN in carcass performance was re-affirmed with the segregating Q204X mutation explaining 1.21, 1.11 and 5.95% of the genetic variance in carcass weight, fat and conformation, respectively in the Charolais population. In addition, a genomic region on BTA6 encompassing the NCAPG/LCORL locus, which is a known candidate locus associated with body size, was associated with carcass weight in Angus, Charolais and Limousin. Novel candidate genes identified included ZFAT in Angus, and SLC40A1 and the olfactory gene cluster on BTA15 in Charolais. Although the majority of associations were breed specific, associations that operated across breeds included SORCS1 on BTA26, MCTP2 on BTA21 and ARL15 on BTA20; these are of particular interest due to their potential informativeness in across-breed genomic evaluations. Genomic regions affecting all three carcass traits were identified in each of the breeds, although these were mainly concentrated on BTA2 and BTA6, surrounding MSTN and NCAPG/LCORL, respectively. This suggests that although major genes may be associated with all three carcass traits, the majority of genes containing significant variants (unadjusted p-value < 10− 4) may be trait specific associations of small effect. Conclusions Although plausible novel candidate genes were identified, the proportion of variance explained by these candidates was minimal thus reaffirming that while carcass performance may be affected by major genes in the form of MSTN and NCAPG/LCORL, the majority of variance is attributed to the additive (and possibly multiplicative) effect of many polymorphisms of small effect. Electronic supplementary material The online version of this article (10.1186/s12864-019-6071-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- D C Purfield
- Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland.
| | - R D Evans
- Irish Cattle Breeding Federation, Bandon, Co. Cork, Ireland
| | - D P Berry
- Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
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