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Colombi D, Rovelli G, Luigi-Sierra MG, Ceccobelli S, Guan D, Perini F, Sbarra F, Quaglia A, Sarti FM, Pasquini M, Amills M, Lasagna E. Population structure and identification of genomic regions associated with productive traits in five Italian beef cattle breeds. Sci Rep 2024; 14:8529. [PMID: 38609445 PMCID: PMC11014930 DOI: 10.1038/s41598-024-59269-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/09/2024] [Indexed: 04/14/2024] Open
Abstract
Italy has a long history in beef production, with local breeds such as Marchigiana, Chianina, Romagnola, Maremmana, and Podolica which produce high-quality meat. Selection has improved meat production, precocity, growth ability and muscle development, but the genetic determinism of such traits is mostly unknown. Using 33K SNPs-data from young bulls (N = 4064) belonging to these five Italian breeds, we demonstrated that the Maremmana and Podolica rustic breeds are closely related, while the specialised Marchigiana, Chianina, and Romagnola breeds are more differentiated. A genome-wide association study for growth and muscle development traits (average daily gain during the performance test, weight at 1 year old, muscularity) was conducted in the five Italian breeds. Results indicated a region on chromosome 2, containing the myostatin gene (MSTN), which displayed significant genome-wide associations with muscularity in Marchigiana cattle, a breed in which the muscle hypertrophy phenotype is segregating. Moreover, a significant SNP on chromosome 14 was associated, in the Chianina breed, to muscularity. The identification of diverse genomic regions associated with conformation traits might increase our knowledge about the genomic basis of such traits in Italian beef cattle and, eventually, such information could be used to implement marker-assisted selection of young bulls tested in the performance test.
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Affiliation(s)
- Daniele Colombi
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
| | - Giacomo Rovelli
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
| | - Maria Gracia Luigi-Sierra
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
| | - Simone Ceccobelli
- Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, 60131, Ancona, Italy
| | - Dailu Guan
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain
- Department of Animal Science, University of California, Davis, CA, 2251, USA
| | - Francesco Perini
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, 35020, Legnaro, Italy
| | - Fiorella Sbarra
- National Association of Italian Beef-Cattle Breeders (ANABIC), 06132, San Martino in Colle, Perugia, Italy
| | - Andrea Quaglia
- National Association of Italian Beef-Cattle Breeders (ANABIC), 06132, San Martino in Colle, Perugia, Italy
| | - Francesca Maria Sarti
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
| | - Marina Pasquini
- Department of Agricultural, Food and Environmental Sciences (D3A), Università Politecnica delle Marche, 60131, Ancona, Italy
| | - Marcel Amills
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autonòma de Barcelona, Carrer de la Vall Moronta, 08193, Bellaterra de Cerdanyola del Vallés, Spain.
- Department of Animal and Food Science, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
| | - Emiliano Lasagna
- Department of Agricultural, Food and Environmental Sciences (DSA3), University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy.
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Ristanic M, Zorc M, Glavinic U, Stevanovic J, Blagojevic J, Maletic M, Stanimirovic Z. Genome-Wide Analysis of Milk Production Traits and Selection Signatures in Serbian Holstein-Friesian Cattle. Animals (Basel) 2024; 14:669. [PMID: 38473054 DOI: 10.3390/ani14050669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/05/2024] [Accepted: 02/14/2024] [Indexed: 03/14/2024] Open
Abstract
To improve the genomic evaluation of milk-related traits in Holstein-Friesian (HF) cattle it is essential to identify the associated candidate genes. Novel SNP-based analyses, such as the genetic mapping of inherited diseases, GWAS, and genomic selection, have led to a new era of research. The aim of this study was to analyze the association of each individual SNP in Serbian HF cattle with milk production traits and inbreeding levels. The SNP 60 K chip Axiom Bovine BovMDv3 was deployed for the genotyping of 334 HF cows. The obtained genomic results, together with the collected phenotypic data, were used for a GWAS. Moreover, the identification of ROH segments was performed and served for inbreeding coefficient evaluation and ROH island detection. Using a GWAS, a polymorphism, rs110619097 (located in the intron of the CTNNA3 gene), was detected to be significantly (p < 0.01) associated with the milk protein concentration in the first lactation (adjusted to 305 days). The average genomic inbreeding value (FROH) was 0.079. ROH islands were discovered in proximity to genes associated with milk production traits and genomic regions under selection pressure for other economically important traits of dairy cattle. The findings of this pilot study provide useful information for a better understanding of the genetic architecture of milk production traits in Serbian HF dairy cows and can be used to improve lactation performances in Serbian HF cattle breeding programs.
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Affiliation(s)
- Marko Ristanic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Minja Zorc
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1000 Ljubljana, Slovenia
| | - Uros Glavinic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Jevrosima Stevanovic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Jovan Blagojevic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Milan Maletic
- Department of Reproduction, Fertility and Artificial Insemination, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
| | - Zoran Stanimirovic
- Department of Biology, Faculty of Veterinary Medicine, University of Belgrade, Bul. Oslobodjenja 18, 11000 Belgrade, Serbia
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Hengwei Y, Raza SHA, Wang S, Khan R, Ayari-Akkari A, El Moneim Ahmed DA, Ahmad I, Shaoib M, Abd El-Aziz AH, Rahman SU, Jahejo AR, Zan L. The growth curve determination and economic trait correlation for Qinchuan bull population. Anim Biotechnol 2023; 34:2649-2656. [PMID: 35980325 DOI: 10.1080/10495398.2022.2111309] [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] [Indexed: 11/01/2022]
Abstract
Carcass weight, as a measure of meat yield, and body measurements are directly correlated traits in livestock. However, longitudinally collected phenotype records of local breeds are not comprehensive. The research was performed on Qinchuan bull population to understand their growth and development, and data from Qinchuan bull that was weighed and measured at birth, 6, 12, 18, and 24 months of age was analyzed. Furthermore, Logistic, Brody, Gompertz, and Bertallanffy were used to fit the growth curves for weight and body size traits. The results showed that the four curve models have good fitting degrees for the weight and body size (R2 > 0.99), and the Bertallanffy model exhibited a good fit to the measured data of body weight, and the model estimated the inflection point of body weight as (5.43 months of age, 122.01 kg). Particularly, the limited mature body weight can reach 557.8 kg by the Brody model. Body weight was significantly positively correlated with body height, hip height, body length, chest circumference, abdominal girth, and calf girth (p < 0.0001), and the correlation between body weight and body length was the highest (r = 0.975). The regression equation predicting body weight was Y = -275.691 + 3.28 X3 + 1.311 X4 - 0.397 X5.
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Affiliation(s)
- Yu Hengwei
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | | | - Sihu Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Rajwali Khan
- Department of Livestock Management, Breeding and Genetic, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Amel Ayari-Akkari
- Biology Department, College of Sciences, King Khaled University, Abha, Saudi Arabia
- Laboratory of Diversity, Management and Conservation of Biological Systems, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia
| | | | - Ijaz Ahmad
- Department of Livestock Management, Breeding and Genetic, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Muhammad Shaoib
- College of Veterinary Science, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Ayman H Abd El-Aziz
- Department of Animal and Poultry Production, Faculty of Agriculture, Damanhour University, Damanhour, Egypt
| | - Siddiq Ur Rahman
- Department of Computer science and Bioinformatics, Khushal Khan Khattak University, Karak, Pakistan
| | - Ali Raza Jahejo
- College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
- National Beef Cattle Improvement Center, Yangling, China
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Ballan M, Schiavo G, Bovo S, Schiavitto M, Negrini R, Frabetti A, Fornasini D, Fontanesi L. Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds. Anim Genet 2022; 53:849-862. [PMID: 36073189 PMCID: PMC9826494 DOI: 10.1111/age.13264] [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: 01/24/2022] [Revised: 07/01/2022] [Accepted: 08/25/2022] [Indexed: 01/11/2023]
Abstract
Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome.
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Affiliation(s)
- Mohamad Ballan
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Giuseppina Schiavo
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Samuele Bovo
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Michele Schiavitto
- Associazione Nazionale Coniglicoltori Italiani (ANCI), Contrada Giancola SncVolturara AppulaItaly
| | | | | | | | - Luca Fontanesi
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
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Ceccobelli S, Perini F, Trombetta MF, Tavoletti S, Lasagna E, Pasquini M. Effect of Myostatin Gene Mutation on Slaughtering Performance and Meat Quality in Marchigiana Bulls. Animals (Basel) 2022; 12:ani12040518. [PMID: 35203227 PMCID: PMC8868461 DOI: 10.3390/ani12040518] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 02/10/2022] [Accepted: 02/17/2022] [Indexed: 02/07/2023] Open
Abstract
Simple Summary The aim of this work was the evaluation of slaughtering performance in a sample of 78 Marchigiana bulls with different allelic situation at the myostatin locus; in addition, the qualitative composition of meat samples collected from Longissimus thoracis muscle was evaluated. At the myostatin gene, 67 homozygotes normal, 11 heterozygotes, and no double-muscled homozygote bulls were detected. Heterozygote bulls showed high values in final live weight and dressing yield; moreover, they were characterized by a low incidence of fat at steak dissection, as well as in meat chemical composition. A better muscular conformation in heterozygote bulls’ carcasses was highlighted, with a higher incidence of their carcasses in class E and evident convexity of round, back, and shoulder muscular masses compared to the carcasses of Marchigiana bulls which were normal at the myostatin gene. Abstract The myostatin gene also called Growth Differentiation Factor 8 gene (GDF8) is one of the most investigated loci that can be responsible for several quantitative and qualitative carcass and meat traits in double-muscled beef cattle. The objective of the study was to bring to light the effect of the myostatin polymorphism on slaughtering performance and meat quality in Marchigiana beef cattle. The experiment was carried out on 78 bulls reared according to the “cow-calf” extensive managing system. At the end of the fattening period, in vivo and carcass data were recorded. From each carcass, a steak of Longissimus thoracis was taken and used to determine the meat’s analytical composition and colorimetric properties. Finally, from each steak a sample of Longissimus thoracis was collected, then used for DNA extraction and genotyping at the myostatin locus. The heterozygous bulls showed slight superiority in the carcass data (e.g., hot carcass weight: 426.09 kg—heterozygotes vs. 405.32 kg—normal) and meat quality parameters, although not always with statistical significance. Only fat and ashes content were significantly affected by the myostatin genotype (heterozygotes: 2.01%, 1.26%; normal: 3.04%, 1.15%). The greater muscularity of heterozygous animals compared to normal ones could be a starting point to improving productive efficiency in Marchigiana beef cattle.
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Affiliation(s)
- Simone Ceccobelli
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, 60131 Ancona, Italy; (M.F.T.); (S.T.); (M.P.)
- Correspondence:
| | - Francesco Perini
- Dipartimento di Scienze Agrarie, Alimentari e Ambientali, University of Perugia, 06121 Perugia, Italy; (F.P.); (E.L.)
| | - Maria Federica Trombetta
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, 60131 Ancona, Italy; (M.F.T.); (S.T.); (M.P.)
| | - Stefano Tavoletti
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, 60131 Ancona, Italy; (M.F.T.); (S.T.); (M.P.)
| | - Emiliano Lasagna
- Dipartimento di Scienze Agrarie, Alimentari e Ambientali, University of Perugia, 06121 Perugia, Italy; (F.P.); (E.L.)
| | - Marina Pasquini
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, 60131 Ancona, Italy; (M.F.T.); (S.T.); (M.P.)
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Johnsson M, Jungnickel MK. Evidence for and localization of proposed causative variants in cattle and pig genomes. Genet Sel Evol 2021; 53:67. [PMID: 34461824 PMCID: PMC8404348 DOI: 10.1186/s12711-021-00662-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/20/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND This paper reviews the localization of published potential causative variants in contemporary pig and cattle reference genomes, and the evidence for their causality. In spite of the difficulties inherent to the identification of causative variants from genetic mapping and genome-wide association studies, researchers in animal genetics have proposed putative causative variants for several traits relevant to livestock breeding. RESULTS For this review, we read the literature that supports potential causative variants in 13 genes (ABCG2, DGAT1, GHR, IGF2, MC4R, MSTN, NR6A1, PHGK1, PRKAG3, PLRL, RYR1, SYNGR2 and VRTN) in cattle and pigs, and localized them in contemporary reference genomes. We review the evidence for their causality, by aiming to separate the evidence for the locus, the proposed causative gene and the proposed causative variant, and report the bioinformatic searches and tactics needed to localize the sequence variants in the cattle or pig genome. CONCLUSIONS Taken together, there is usually good evidence for the association at the locus level, some evidence for a specific causative gene at eight of the loci, and some experimental evidence for a specific causative variant at six of the loci. We recommend that researchers who report new potential causative variants use referenced coordinate systems, show local sequence context, and submit variants to repositories.
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Affiliation(s)
- Martin Johnsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden
| | - Melissa K. Jungnickel
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG Scotland, UK
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Genome-wide association study of trypanosome prevalence and morphometric traits in purebred and crossbred Baoulé cattle of Burkina Faso. PLoS One 2021; 16:e0255089. [PMID: 34351956 PMCID: PMC8341487 DOI: 10.1371/journal.pone.0255089] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 07/09/2021] [Indexed: 11/27/2022] Open
Abstract
In this study, single-SNP GWAS analyses were conducted to find regions affecting tolerance against trypanosomosis and morphometrics traits in purebred and crossbred Baoulé cattle of Burkina Faso. The trypanosomosis status (positive and negative) and a wide set of morphological traits were recorded for purebred Baoulé and crossbred Zebu x Baoulé cattle, and genotyped with the Illumina Bovine SNP50 BeadChip. After quality control, 36,203 SNPs and 619 animals including 343 purebred Baoulé and 279 crossbreds were used for the GWAS analyses. Several important genes were found that can influence morphological parameters. Although there were no genes identified with a reported strong connection to size traits, many of them were previously identified in various growth-related studies. A re-occurring theme for the genes residing in the regions identified by the most significant SNPs was pleiotropic effect on growth of the body and the cardiovascular system. Regarding trypanosomosis tolerance, two potentially important regions were identified in purebred Baoulé on chromosomes 16 and 24, containing the CFH, CRBN, TRNT1 and, IL5RA genes, and one additional genomic region in Baoulé, x Zebu crossbreds on chromosome 5, containing MGAT4C and NTS. Almost all of these regions and genes were previously related to the trait of interest, while the CRBN gene was to our knowledge presented in the context of trypanosomiasis tolerance for the first time.
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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: 13] [Impact Index Per Article: 4.3] [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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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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10
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Manca E, Cesarani A, Gaspa G, Sorbolini S, Macciotta NP, Dimauro C. Use of the Multivariate Discriminant Analysis for Genome-Wide Association Studies in Cattle. Animals (Basel) 2020; 10:ani10081300. [PMID: 32751408 PMCID: PMC7460480 DOI: 10.3390/ani10081300] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/23/2020] [Accepted: 07/27/2020] [Indexed: 11/16/2022] Open
Abstract
Simple Summary In the traditional single marker regression approach for genome-wide association studies, if the number of involved individuals is small and the number of single nucleotide polymorphisms (SNPs) to be tested is very large, the probability of getting a significant association simply due to chance becomes enormous. Other techniques, such as the Bayesian methods, require several a priori assumptions, as an a priori posterior inclusion probability threshold, that can limit their effectiveness. In the present study, a multivariate algorithm able to partially overcome this problem was proposed. On simulated data, with 3000 individuals, only 13 and 3 quantitative trait loci (QTLs) were obtained with the single marker regression and the Bayesian approaches, respectively. On the other hand, the multivariate algorithm detected 65 QTLs in the same scenario. The gap between the single marker regression and the multivariate methods slowly decreased as the number of animals increased. This figure was also confirmed on real data. Abstract Genome-wide association studies (GWAS) are traditionally carried out by using the single marker regression model that, if a small number of individuals is involved, often lead to very few associations. The Bayesian methods, such as BayesR, have obtained encouraging results when they are applied to the GWAS. However, these approaches, require that an a priori posterior inclusion probability threshold be fixed, thus arbitrarily affecting the obtained associations. To partially overcome these problems, a multivariate statistical algorithm was proposed. The basic idea was that animals with different phenotypic values of a specific trait share different allelic combinations for genes involved in its determinism. Three multivariate techniques were used to highlight the differences between the individuals assembled in high and low phenotype groups: the canonical discriminant analysis, the discriminant analysis and the stepwise discriminant analysis. The multivariate method was tested both on simulated and on real data. The results from the simulation study highlighted that the multivariate GWAS detected a greater number of true associated single nucleotide polymorphisms (SNPs) and Quantitative trait loci (QTLs) than the single marker model and the Bayesian approach. For example, with 3000 animals, the traditional GWAS highlighted only 29 significantly associated markers and 13 QTLs, whereas the multivariate method found 127 associated SNPs and 65 QTLs. The gap between the two approaches slowly decreased as the number of animals increased. The Bayesian method gave worse results than the other two. On average, with the real data, the multivariate GWAS found 108 associated markers for each trait under study and among them, around 63% SNPs were also found in the single marker approach. Among the top 118 associated markers, 76 SNPs harbored putative candidate genes.
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Affiliation(s)
- Elisabetta Manca
- Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy; (E.M.); (A.C.); (S.S.); (N.P.P.M.)
| | - Alberto Cesarani
- Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy; (E.M.); (A.C.); (S.S.); (N.P.P.M.)
| | - Giustino Gaspa
- Dipartimento di Scienze Agrarie, Forestali e Ambientali, Università degli studi di Torino, 10095 Grugliasco, Italy;
| | - Silvia Sorbolini
- Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy; (E.M.); (A.C.); (S.S.); (N.P.P.M.)
| | - Nicolò P.P. Macciotta
- Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy; (E.M.); (A.C.); (S.S.); (N.P.P.M.)
| | - Corrado Dimauro
- Dipartimento di Agraria, Università degli Studi di Sassari, 07100 Sassari, Italy; (E.M.); (A.C.); (S.S.); (N.P.P.M.)
- Correspondence: ; Tel.: +39079229298
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11
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An B, Xu L, Xia J, Wang X, Miao J, Chang T, Song M, Ni J, Xu L, Zhang L, Li J, Gao H. Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle. BMC Genet 2020; 21:32. [PMID: 32171250 PMCID: PMC7071762 DOI: 10.1186/s12863-020-0837-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 03/04/2020] [Indexed: 01/08/2023] Open
Abstract
Background Body size traits as one of the main breeding selection criteria was widely used to monitor cattle growth and to evaluate the selection response. In this study, body size was defined as body height (BH), body length (BL), hip height (HH), heart size (HS), abdominal size (AS), and cannon bone size (CS). We performed genome-wide association studies (GWAS) of these traits over the course of three growth stages (6, 12 and 18 months after birth) using three statistical models, single-trait GWAS, multi-trait GWAS and LONG-GWAS. The Illumina Bovine HD 770 K BeadChip was used to identify genomic single nucleotide polymorphisms (SNPs) in 1217 individuals. Results In total, 19, 29, and 10 significant SNPs were identified by the three models, respectively. Among these, 21 genes were promising candidate genes, including SOX2, SNRPD1, RASGEF1B, EFNA5, PTBP1, SNX9, SV2C, PKDCC, SYNDIG1, AKR1E2, and PRIM2 identified by single-trait analysis; SLC37A1, LAP3, PCDH7, MANEA, and LHCGR identified by multi-trait analysis; and P2RY1, MPZL1, LINGO2, CMIP, and WSCD1 identified by LONG-GWAS. Conclusions Multiple association analysis was performed for six growth traits at each growth stage. These findings offer valuable insights for the further investigation of potential genetic mechanism of growth traits in Simmental beef cattle.
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Affiliation(s)
| | | | - Jiangwei Xia
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, 310000, China
| | - Xiaoqiao Wang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Jian Miao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Tianpeng Chang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Meihua Song
- Zhuang Yuan Veterinary Station of Qixia city, Yantai, 265300, China
| | - Junqing Ni
- Heibei Livestock Breeding Workstation, Shijiazhuang, 050061, China
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Lupei Zhang
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Junya Li
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China.
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12
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Martin P, Taussat S, Vinet A, Krauss D, Maupetit D, Renand G. Genetic parameters and genome-wide association study regarding feed efficiency and slaughter traits in Charolais cows. J Anim Sci 2019; 97:3684-3698. [PMID: 31436836 DOI: 10.1093/jas/skz240] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 07/15/2019] [Indexed: 12/14/2022] Open
Abstract
Residual energy intake (REI) on two successive diets (hay and maize based) and slaughter traits, including visceral organs, were phenotyped in 584 adult purebred Charolais cows. To investigate the relationships between these traits and their genetic determinism, we first estimated the genetic parameters, including correlations, using REML modeling under WOMBAT software. The animals were then genotyped on the BovineSNP50 SNPchip before being imputed to the 600K density and genome wide association study was performed with GCTA software. We found low heritability for REI (h2 = 0.12 in each of the diet phases). Although the phenotypic correlation between the two diet phases was moderate (0.36), the genetic correlation was high (0.83), indicating a common genetic determinism for feed efficiency regardless of the diet. Correlations between REI and slaughter traits were negative regarding muscle-related traits and positive for fat-related traits, indicating that efficient animals generally had a more muscular carcass. It was also seen that feed efficiency was genetically and phenotypically correlated with smaller organs when expressed as a proportion of their empty body weight. From the GWAS analysis, seven QTLs were found to be associated with a trait at the genome-wide level of significance and 18 others at the chromosome-wide level. One important QTL was detected in BTA 2, reflecting the essential effect of the myostatin gene on both carcass composition and relative organ weight. Three QTLs were detected for REI during the maize diet phase on BTA 13, 19, and 28, the latter being significant at the genome-wide level. The QTLs on BTA 19 mapped into the TANC2 gene and the QTLs on BTA 28 into the KIF1BP gene, which are both known to interact with the same protein (KIF1A). However, no obvious functional link between these genes and feed efficiency could be made. Among the other QTLs detected, one association on BTA 4 with liver proportion mapped to the candidate gene WASL, which has previously been shown to be differentially expressed in liver cells and linked to feed restriction or cancer development. No QTLs were found to be common between feed efficiency and any slaughter traits.
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Affiliation(s)
- Pauline Martin
- UMR1313 GABI, Institut National de la Recherche Agronomique, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
| | - Sébastien Taussat
- UMR1313 GABI, Institut National de la Recherche Agronomique, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France.,UE0332 Domaine Expérimental Bourges-La Sapinière, Allice, Paris, France
| | - Aurélie Vinet
- UMR1313 GABI, Institut National de la Recherche Agronomique, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
| | - Daniel Krauss
- UE0332 Domaine Expérimental Bourges-La Sapinière, Institut National de la Recherche Agronomique, Osmoy, France
| | - David Maupetit
- UE0332 Domaine Expérimental Bourges-La Sapinière, Institut National de la Recherche Agronomique, Osmoy, France
| | - Gilles Renand
- UMR1313 GABI, Institut National de la Recherche Agronomique, AgroParisTech, Université Paris-Saclay, Jouy-en-Josas, France
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13
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Ma X, Jia C, Chu M, Fu D, Lei Q, Ding X, Wu X, Guo X, Pei J, Bao P, Yan P, Liang C. Transcriptome and DNA Methylation Analyses of the Molecular Mechanisms Underlying with Longissimus dorsi Muscles at Different Stages of Development in the Polled Yak. Genes (Basel) 2019; 10:genes10120970. [PMID: 31779203 PMCID: PMC6947547 DOI: 10.3390/genes10120970] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 11/21/2019] [Accepted: 11/21/2019] [Indexed: 02/04/2023] Open
Abstract
DNA methylation modifications are implicated in many biological processes. As the most common epigenetic mechanism DNA methylation also affects muscle growth and development. The majority of previous studies have focused on different varieties of yak, but little is known about the epigenetic regulation mechanisms in different age groups of animals. The development of muscles in the different stages of yak growth remains unclear. In this study, we selected the longissimus dorsi muscle tissue at three different growth stages of the yak, namely, 90-day-old fetuses (group E), six months old (group M), and three years old (group A). Using RNA-Seq transcriptome sequencing and methyl-RAD whole-genome methylation sequencing technology, changes in gene expression levels and DNA methylation status throughout the genome were investigated during the stages of yak development. Each group was represented by three biological replicates. The intersections of expression patterns of 7694 differentially expressed genes (DEGs) were identified (padj < 0.01, |log2FC| > 1.2) at each of the three developmental periods. Time-series expression profile clustering analysis indicated that the DEGs were significantly arranged into eight clusters which could be divided into two classes (padj < 0.05), class I profiles that were downregulated and class II profiles that were upregulated. Based on this cluster analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that DEGs from class I profiles were significantly (padj < 0.05) enriched in 21 pathways, the most enriched pathway being the Axon guidance signaling pathway. DEGs from the class II profile were significantly enriched in 58 pathways, the pathway most strongly enriched being Metabolic pathway. After establishing the methylation profiles of the whole genomes, and using two groups of comparisons, the three combinations of groups (M-vs.-E, M-vs.-A, A-vs.-E) were found to have 1344, 822, and 420 genes, respectively, that were differentially methylated at CCGG sites and 2282, 3056, and 537 genes, respectively, at CCWGG sites. The two sets of data were integrated and the negative correlations between DEGs and differentially methylated promoters (DMPs) analyzed, which confirmed that TMEM8C, IGF2, CACNA1S and MUSTN1 were methylated in the promoter region and that expression of the modified genes was negatively correlated. Interestingly, these four genes, from what was mentioned above, perform vital roles in yak muscle growth and represent a reference for future genomic and epigenomic studies in muscle development, in addition to enabling marker-assisted selection of growth traits.
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Affiliation(s)
- Xiaoming Ma
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Congjun Jia
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Min Chu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Donghai Fu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Qinhui Lei
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xuezhi Ding
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoyun Wu
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xian Guo
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Jie Pei
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Pengjia Bao
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Ping Yan
- Animal Science Department, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China; (X.M.); (C.J.); (M.C.); (D.F.); (Q.L.); (X.D.); (X.W.); (X.G.); (J.P.); (P.B.)
- Correspondence: (P.Y.); (C.L.); Tel.: +86-0931-2115288 (P.Y.); +86-0931-2115271 (C.L.)
| | - Chunnian Liang
- Key Laboratory for Yak Genetics, Breeding, and Reproduction Engineering of Gansu Province, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
- Correspondence: (P.Y.); (C.L.); Tel.: +86-0931-2115288 (P.Y.); +86-0931-2115271 (C.L.)
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14
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Li Y, Lee YM, Kim YS, Park SP, Kim JJ. Identifying Loci Under Positive Selection in Yellow Korean Cattle (Hanwoo). Evol Bioinform Online 2019; 15:1176934319859001. [PMID: 35210744 PMCID: PMC8862131 DOI: 10.1177/1176934319859001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 05/23/2019] [Indexed: 11/21/2022] Open
Abstract
Jeju Black cattle is one of the aboriginal Korean cattle breeds that has been isolated in Jeju island for a long time, while Yellow Hanwoo cattle has been extensively selected for beef production traits for the last several decades. Aiming to investigate broader patterns of selection, we genotyped 352 Yellow Hanwoo and 169 Jeju Black cattle using a customized 150 K bovine chip. Our composite selection signals’ analysis to identify selection signatures (cross-population extended haplotype homozygosity [XP-EHH], ΔSAF, and FST) identified recent and strong signature of selection near many loci with mutations affecting the traits under strong selection as outlier in Yellow Hanwoo, including SCP2 (P = 8.41 × 10−10) that may be involved in the meat quality. We found nine candidate regions with significant clusters of selection signals, and further bioinformatics analyses of the genes located within these regions revealed mainly genes involved in G-protein coupled receptor signaling pathway (GO:0007186) or olfactory transduction (bta04740), which may be due to adaptation to natural environments in Jeju island. Based on the stronger correlation of Ne10/Ne100 ratio between Yellow Hanwoo (0.61) and Jeju Black (0.66) cattle, our results suggest that the difference of chromosomal regions of selection signature between the 2 cattle breeds was due to a consequence of selection processes to adapt to environmental differences between Jeju island and the main inland, Korean peninsula.
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Affiliation(s)
- Yi Li
- School of Statistics, Shanxi University of Finance and Economics, Taiyuan, China
| | - Yun-Mi Lee
- Department of Biotechnology, Yeungnam University, Gyeongsan, Republic of Korea
| | - You-Sam Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan, Republic of Korea
| | - Se-Pil Park
- Faculty of Biotechnology, Jeju National University, Jeju, Republic of Korea
| | - Jong-Joo Kim
- Department of Biotechnology, Yeungnam University, Gyeongsan, Republic of Korea
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15
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Elbers JP, Rogers MF, Perelman PL, Proskuryakova AA, Serdyukova NA, Johnson WE, Horin P, Corander J, Murphy D, Burger PA. Improving Illumina assemblies with Hi-C and long reads: An example with the North African dromedary. Mol Ecol Resour 2019; 19:1015-1026. [PMID: 30972949 PMCID: PMC6618069 DOI: 10.1111/1755-0998.13020] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 03/24/2019] [Accepted: 03/25/2019] [Indexed: 12/22/2022]
Abstract
Researchers have assembled thousands of eukaryotic genomes using Illumina reads, but traditional mate‐pair libraries cannot span all repetitive elements, resulting in highly fragmented assemblies. However, both chromosome conformation capture techniques, such as Hi‐C and Dovetail Genomics Chicago libraries and long‐read sequencing, such as Pacific Biosciences and Oxford Nanopore, help span and resolve repetitive regions and therefore improve genome assemblies. One important livestock species of arid regions that does not have a high‐quality contiguous reference genome is the dromedary (Camelus dromedarius). Draft genomes exist but are highly fragmented, and a high‐quality reference genome is needed to understand adaptation to desert environments and artificial selection during domestication. Dromedaries are among the last livestock species to have been domesticated, and together with wild and domestic Bactrian camels, they are the only representatives of the Camelini tribe, which highlights their evolutionary significance. Here we describe our efforts to improve the North African dromedary genome. We used Chicago and Hi‐C sequencing libraries from Dovetail Genomics to resolve the order of previously assembled contigs, producing almost chromosome‐level scaffolds. Remaining gaps were filled with Pacific Biosciences long reads, and then scaffolds were comparatively mapped to chromosomes. Long reads added 99.32 Mbp to the total length of the new assembly. Dovetail Chicago and Hi‐C libraries increased the longest scaffold over 12‐fold, from 9.71 Mbp to 124.99 Mbp and the scaffold N50 over 50‐fold, from 1.48 Mbp to 75.02 Mbp. We demonstrate that Illumina de novo assemblies can be substantially upgraded by combining chromosome conformation capture and long‐read sequencing.
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Affiliation(s)
- Jean P Elbers
- Department of Integrative Biology and Evolution, Research Institute of Wildlife Ecology, Vetmeduni Vienna, Vienna, Austria
| | - Mark F Rogers
- Intelligent Systems Laboratory, University of Bristol, Bristol, UK
| | - Polina L Perelman
- Institute of Molecular and Cellular Biology, SB RAS and Novosibirsk State University, Novosibirsk, Russia
| | - Anastasia A Proskuryakova
- Institute of Molecular and Cellular Biology, SB RAS and Novosibirsk State University, Novosibirsk, Russia
| | - Natalia A Serdyukova
- Institute of Molecular and Cellular Biology, SB RAS and Novosibirsk State University, Novosibirsk, Russia
| | - Warren E Johnson
- The Walter Reed Biosystematics Unit, Smithsonian Institution, Museum Support Center MRC-534, Suitland, Maryland
| | - Petr Horin
- Department of Animal Genetics, Faculty of Veterinary Medicine, Ceitec VFU, RG Animal Immunogenomics, University of Veterinary and Pharmaceutical Sciences, Brno, Czech Republic
| | - Jukka Corander
- Department of Biostatistics, University of Oslo, Oslo, Norway.,Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - David Murphy
- Bristol Medical School: Translational Health Sciences, Molecular Neuroendocrinology Research Group, University of Bristol, Bristol, UK
| | - Pamela A Burger
- Department of Integrative Biology and Evolution, Research Institute of Wildlife Ecology, Vetmeduni Vienna, Vienna, Austria
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16
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Peripolli E, Metzger J, de Lemos MVA, Stafuzza NB, Kluska S, Olivieri BF, Feitosa FLB, Berton MP, Lopes FB, Munari DP, Lôbo RB, Magnabosco CDU, Di Croce F, Osterstock J, Denise S, Pereira ASC, Baldi F. Autozygosity islands and ROH patterns in Nellore lineages: evidence of selection for functionally important traits. BMC Genomics 2018; 19:680. [PMID: 30223795 PMCID: PMC6142381 DOI: 10.1186/s12864-018-5060-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 09/07/2018] [Indexed: 12/20/2022] Open
Abstract
Background The aim of this study was to assess genome-wide autozygosity in a Nellore cattle population and to characterize ROH patterns and autozygosity islands that may have occurred due to selection within its lineages. It attempts also to compare estimates of inbreeding calculated from ROH (FROH), genomic relationship matrix (FGRM), and pedigree-based coefficient (FPED). Results The average number of ROH per animal was 55.15 ± 13.01 with an average size of 3.24 Mb. The Nellore genome is composed mostly by a high number of shorter segments accounting for 78% of all ROH, although the proportion of the genome covered by them was relatively small. The genome autozygosity proportion indicates moderate to high inbreeding levels for classical standards, with an average value of 7.15% (178.70 Mb). The average of FPED and FROH, and their correlations (− 0.05 to 0.26) were low. Estimates of correlation between FGRM-FPED was zero, while the correlation (− 0.01 to − 0.07) between FGRM-FROH decreased as a function of ROH length, except for FROH > 8Mb (− 0.03). Overall, inbreeding coefficients were not high for the genotyped animals. Autozygosity islands were evident across the genome (n = 62) and their genomic location did not largely differ within lineages. Enriched terms (p < 0.01) associated with defense response to bacteria (GO:0042742), immune complex reaction (GO:0045647), pregnancy-associated glycoproteins genes (GO:0030163), and organism growth (GO:0040014) were described within the autozygotic islands. Conclusions Low FPED-FROH correlation estimates indicate that FPED is not the most suitable method for capturing ancient inbreeding when the pedigree does not extend back many generations and FROH should be used instead. Enriched terms (p < 0.01) suggest a strong selection for immune response. Non-overlapping islands within the lineages greatly explain the mechanism underlying selection for functionally important traits in Nellore cattle. Electronic supplementary material The online version of this article (10.1186/s12864-018-5060-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elisa Peripolli
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil.
| | - Julia Metzger
- Institute for Animal Breeding and Genetics, University of Veterinary Medicine Hannover, 30559, Hannover, Germany
| | - Marcos Vinícius Antunes de Lemos
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Nedenia Bonvino Stafuzza
- Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Sabrina Kluska
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Bianca Ferreira Olivieri
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Fabieli Louise Braga Feitosa
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Mariana Piatto Berton
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Fernando Brito Lopes
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Danísio Prado Munari
- Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
| | - Raysildo Barbosa Lôbo
- Associação Nacional de Criadores e Pesquisadores (ANCP), Ribeirão Preto, 14020-230, Brazil
| | | | | | | | | | | | - Fernando Baldi
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP Univ Estadual Paulista Júlio de Mesquita Filho, Jaboticabal, 14884-900, Brazil
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17
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Edea Z, Jeoung YH, Shin SS, Ku J, Seo S, Kim IH, Kim SW, Kim KS. Genome-wide association study of carcass weight in commercial Hanwoo cattle. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2017; 31:327-334. [PMID: 29103288 PMCID: PMC5838337 DOI: 10.5713/ajas.17.0276] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Revised: 07/12/2017] [Accepted: 10/22/2017] [Indexed: 12/25/2022]
Abstract
Objective The objective of the present study was to validate genes and genomic regions associated with carcass weight using a low-density single nucleotide polymorphism (SNP) Chip in Hanwoo cattle breed. Methods Commercial Hanwoo steers (n = 220) were genotyped with 20K GeneSeek genomic profiler BeadChip. After applying the quality control of criteria of a call rate ≥90% and minor allele frequency (MAF) ≥0.01, a total of 15,235 autosomal SNPs were left for genome-wide association (GWA) analysis. The GWA tests were performed using single-locus mixed linear model. Age at slaughter was fitted as fixed effect and sire included as a covariate. The level of genome-wide significance was set at 3.28×10−6 (0.05/15,235), corresponding to Bonferroni correction for 15,235 multiple independent tests. Results By employing EMMAX approach which is based on a mixed linear model and accounts for population stratification and relatedness, we identified 17 and 16 loci significantly (p<0.001) associated with carcass weight for the additive and dominant models, respectively. The second most significant (p = 0.000049) SNP (ARS-BFGL-NGS-28234) on bovine chromosome 4 (BTA4) at 21 Mb had an allele substitution effect of 43.45 kg. Some of the identified regions on BTA2, 6, 14, 22, and 24 were previously reported to be associated with quantitative trait loci for carcass weight in several beef cattle breeds. Conclusion This is the first genome-wide association study using SNP chips on commercial Hanwoo steers, and some of the loci newly identified in this study may help to better DNA markers that determine increased beef production in commercial Hanwoo cattle. Further studies using a larger sample size will allow confirmation of the candidates identified in this study.
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Affiliation(s)
- Zewdu Edea
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
| | | | - Sung-Sub Shin
- Korea Institute for Animal products Quality Evaluation, Sejong 30100, Korea
| | - Jaeul Ku
- Biomedical Research Center, Turbosoft Inc. Cheongju 28161, Korea
| | - Sungbo Seo
- Biomedical Research Center, Turbosoft Inc. Cheongju 28161, Korea
| | - Il-Hoi Kim
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
| | - Sang-Wook Kim
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
| | - Kwan-Suk Kim
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Korea
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18
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Chillemi G, Bongiorni S, Gioiosa S, Flati T, Castrignanò T, Milanesi M, Ajmone Marsan P, Valentini A. Missense mutations of NCPAG gene affect calving ease in Piedmontese cattle: preliminary evidences. ITALIAN JOURNAL OF ANIMAL SCIENCE 2017. [DOI: 10.1080/1828051x.2017.1370362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Giovanni Chillemi
- SuperComputing Applications and Innovation Department, CINECA, SCAI, Roma, Italy
| | - Silvia Bongiorni
- Dipartimento per la Innovazione nei Sistemi Biologici, Agroalimentari e Forestali, Università della Tuscia, Viterbo, Italy
| | - Silvia Gioiosa
- SuperComputing Applications and Innovation Department, CINECA, SCAI, Roma, Italy
- Istituto di Biomembrane e Bioenergetica, Consiglio Nazionale delle Ricerche, Bari, Italy
| | - Tiziano Flati
- SuperComputing Applications and Innovation Department, CINECA, SCAI, Roma, Italy
- Istituto di Biomembrane e Bioenergetica, Consiglio Nazionale delle Ricerche, Bari, Italy
| | - Tiziana Castrignanò
- SuperComputing Applications and Innovation Department, CINECA, SCAI, Roma, Italy
| | - Marco Milanesi
- Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Piacenza (PC), Italy
| | - Paolo Ajmone Marsan
- Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Piacenza (PC), Italy
| | - Alessio Valentini
- Dipartimento per la Innovazione nei Sistemi Biologici, Agroalimentari e Forestali, Università della Tuscia, Viterbo, Italy
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