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Zhang L, Xie Q, Chang S, Ai Y, Dong K, Zhang H. Epigenetic Factor MicroRNAs Likely Mediate Vaccine Protection Efficacy against Lymphomas in Response to Tumor Virus Infection in Chickens through Target Gene Involved Signaling Pathways. Vet Sci 2024; 11:139. [PMID: 38668407 PMCID: PMC11053969 DOI: 10.3390/vetsci11040139] [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: 02/21/2024] [Revised: 03/16/2024] [Accepted: 03/20/2024] [Indexed: 04/29/2024] Open
Abstract
Epigenetic factors, including microRNAs (miRNAs), play an important role in affecting gene expression and, therefore, are involved in various biological processes including immunity protection against tumors. Marek's disease (MD) is a highly contagious disease of chickens caused by the MD virus (MDV). MD has been primarily controlled by vaccinations. MD vaccine efficacy might, in part, be dependent on modulations of a complex set of factors including host epigenetic factors. This study was designed to identify differentially expressed miRNAs in the primary lymphoid organ, bursae of Fabricius, in response to MD vaccination followed by MDV challenge in two genetically divergent inbred lines of White Leghorns. Small RNA sequencing and bioinformatic analyses of the small RNA sequence reads identified hundreds of miRNAs among all the treatment groups. A small portion of the identified miRNAs was differentially expressed within each of the four treatment groups, which were HVT or CVI988/Rispens vaccinated line 63-resistant birds and line 72-susceptible birds. A direct comparison between the resistant line 63 and susceptible line 72 groups vaccinated with HVT followed by MDV challenge identified five differentially expressed miRNAs. Gene Ontology analysis of the target genes of those five miRNAs revealed that those target genes, in addition to various GO terms, are involved in multiple signaling pathways including MAPK, TGF-β, ErbB, and EGFR1 signaling pathways. The general functions of those pathways reportedly play important roles in oncogenesis, anti-cancer immunity, cancer cell migration, and metastatic progression. Therefore, it is highly likely that those miRNAs may, in part, influence vaccine protection through the pathways.
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Affiliation(s)
- Lei Zhang
- U.S. Department of Agriculture, Agricultural Research Service, U.S. National Poultry Research Center, Athens, GA 30605, USA;
- Institute of Special Wild Economic Animal and Plant Science, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Qingmei Xie
- College of Animal Science, South China Agricultural University, Guangzhou 510642, China;
| | - Shuang Chang
- College of Veterinary Medicine, Shandong Agricultural University, Tai’an 271018, China;
| | - Yongxing Ai
- College of Animal Science, Jilin University, Changchun 130062, China;
| | - Kunzhe Dong
- Department of Pharmacology and Toxicology, Augusta University, Augusta, GA 30912, USA;
| | - Huanmin Zhang
- U.S. Department of Agriculture, Agricultural Research Service, U.S. National Poultry Research Center, Athens, GA 30605, USA;
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He Y, Taylor RL, Bai H, Ashwell CM, Zhao K, Li Y, Sun G, Zhang H, Song J. Transgenerational epigenetic inheritance and immunity in chickens that vary in Marek's disease resistance. Poult Sci 2023; 102:103036. [PMID: 37832188 PMCID: PMC10568563 DOI: 10.1016/j.psj.2023.103036] [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: 05/15/2023] [Revised: 07/31/2023] [Accepted: 08/11/2023] [Indexed: 10/15/2023] Open
Abstract
Marek's disease virus (MDV), a naturally oncogenic, highly contagious alpha herpesvirus, induces a T cell lymphoma in chickens that causes severe economic loss. Marek's disease (MD) outcome in an individual is attributed to genetic and environmental factors. Further investigation of the host-virus interaction mechanisms that impact MD resistance is needed to achieve greater MD control. This study analyzed genome-wide DNA methylation patterns in 2 highly inbred parental lines 63 and 72 and 5 recombinant congenic strains (RCS) C, L, M, N, and X strains from those parents. Lines 63 and 72, are MD resistant and susceptible, respectively, whereas the RCS have different combinations of 87.5% Line 63 and 12.5% Line 72. Our DNA methylation cluster showed a strong association with MD incidence. Differentially methylated regions (DMRs) between the parental lines and the 5 RCS were captured. MD-resistant and MD-susceptible markers of DNA methylation were identified as transgenerational epigenetic inheritable. In addition, the growth of v-src DNA tumors and antibody response against sheep red blood cells differed among the 2 parental lines and the RCS. Overall, our results provide very solid evidence that DNA methylation patterns are transgenerational epigenetic inheritance (TEI) in chickens and also play a vital role in MD tumorigenesis and other immune responses; the specific methylated regions may be important modulators of general immunity.
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Affiliation(s)
- Yanghua He
- Department of Human Nutrition, Food and Animal Sciences, University of Hawaii at Manoa, Honolulu, HI, 96822 USA; Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742 USA
| | - Robert L Taylor
- Division of Animal and Nutritional Sciences West Virginia University, Morgantown, WV 26508 USA
| | - Hao Bai
- Department of Joint International Research Laboratory of Agriculture and Agri-Product Safety, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou 225009, China
| | - Christopher M Ashwell
- Division of Animal and Nutritional Sciences West Virginia University, Morgantown, WV 26508 USA
| | - Keji Zhao
- Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute, NIH, Bethesda, MD, USA
| | - Yaokun Li
- College of Animal Science, South China Agricultural University, Guangzhou, GD 510642, China
| | - Guirong Sun
- College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou, China
| | - Huanmin Zhang
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, MI 48823, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742 USA.
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Han L, Wu S, Zhang T, Peng W, Zhao M, Yue C, Wen W, Cai W, Li M, Wallny HJ, Avila DW, Mwangi W, Nair V, Ternette N, Guo Y, Zhao Y, Chai Y, Qi J, Liang H, Gao GF, Kaufman J, Liu WJ. A Wider and Deeper Peptide-Binding Groove for the Class I Molecules from B15 Compared with B19 Chickens Correlates with Relative Resistance to Marek's Disease. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2023; 210:668-680. [PMID: 36695776 PMCID: PMC7614295 DOI: 10.4049/jimmunol.2200211] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 12/19/2022] [Indexed: 01/26/2023]
Abstract
The chicken MHC is known to confer decisive resistance or susceptibility to various economically important pathogens, including the iconic oncogenic herpesvirus that causes Marek's disease (MD). Only one classical class I gene, BF2, is expressed at a high level in chickens, so it was relatively easy to discern a hierarchy from well-expressed thermostable fastidious specialist alleles to promiscuous generalist alleles that are less stable and expressed less on the cell surface. The class I molecule BF2*1901 is better expressed and more thermostable than the closely related BF2*1501, but the peptide motif was not simpler as expected. In this study, we confirm for newly developed chicken lines that the chicken MHC haplotype B15 confers resistance to MD compared with B19. Using gas phase sequencing and immunopeptidomics, we find that BF2*1901 binds a greater variety of amino acids in some anchor positions than does BF2*1501. However, by x-ray crystallography, we find that the peptide-binding groove of BF2*1901 is narrower and shallower. Although the self-peptides that bound to BF2*1901 may appear more various than those of BF2*1501, the structures show that the wider and deeper peptide-binding groove of BF2*1501 allows stronger binding and thus more peptides overall, correlating with the expected hierarchies for expression level, thermostability, and MD resistance. Our study provides a reasonable explanation for greater promiscuity for BF2*1501 compared with BF2*1901, corresponding to the difference in resistance to MD.
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Affiliation(s)
- Lingxia Han
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, China
- National Poultry Laboratory Animal Resource Center, Harbin 150001, China
- Heilongjiang Provincial Key Laboratory of Laboratory Animal and Comparative Medicine, Harbin 150069, China
| | - Shaolian Wu
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, China
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Ting Zhang
- Biosafety Level-3 Laboratory, Life Sciences Institute & Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application, Guangxi Medical University, Nanning, Guangxi 530021, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
| | - Weiyu Peng
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
| | - Min Zhao
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Can Yue
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing 100052, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wanxin Wen
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, China
| | - Wenbo Cai
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, China
| | - Min Li
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
| | | | - David W. Avila
- The Basel Institute for Immunology, Basel CH4001, Switzerland
| | - William Mwangi
- The Pirbright Institute, Pirbright GU24 0NF, United Kingdom
| | - Venugopal Nair
- The Pirbright Institute, Pirbright GU24 0NF, United Kingdom
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, United Kingdom
| | - Nicola Ternette
- Nuffield Department of Medicine, University of Oxford, Headington OX37BN, United Kingdom
| | - Yaxin Guo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing 100052, China
| | - Yingze Zhao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing 100052, China
| | - Yan Chai
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Hao Liang
- Biosafety Level-3 Laboratory, Life Sciences Institute & Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - George F. Gao
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing 100052, China
| | - Jim Kaufman
- The Basel Institute for Immunology, Basel CH4001, Switzerland
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, United Kingdom
- Department of Veterinary Science, University of Cambridge, Cambridge CB3 0ES, United Kingdom
- Institute for Immunology and Infection Research, University of Edinburgh, Edinburgh EH9 3FL, United Kingdom
| | - William J. Liu
- Biosafety Level-3 Laboratory, Life Sciences Institute & Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application, Guangxi Medical University, Nanning, Guangxi 530021, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100052, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses, Chinese Academy of Medical Sciences, Beijing 100052, China
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Lukacs M, Nymo IH, Madslien K, Våge J, Veiberg V, Rolandsen CM, Bøe CA, Sundaram AYM, Grimholt U. Functional immune diversity in reindeer reveals a high Arctic population at risk. Front Ecol Evol 2023. [DOI: 10.3389/fevo.2022.1058674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Climate changes the geographic range of both species as well as pathogens, causing a potential increase in the vulnerability of populations or species with limited genetic diversity. With advances in high throughput sequencing (HTS) technologies, we can now define functional expressed genetic diversity of wild species at a larger scale and identify populations at risk. Previous studies have used genomic DNA to define major histocompatibility complex (MHC) class II diversity in reindeer. Varying numbers of expressed genes found in many ungulates strongly argues for using cDNA in MHC typing strategies to ensure that diversity estimates relate to functional genes. We have used available reindeer genomes to identify candidate genes and established an HTS approach to define expressed MHC class I and class II diversity. To capture a broad diversity we included samples from wild reindeer from Southern Norway, semi-domesticated reindeer from Northern Norway and reindeer from the high Artic archipelago Svalbard. Our data show a medium MHC diversity in semi-domesticated and wild Norwegian mainland reindeer, and low MHC diversity reindeer in Svalbard reindeer. The low immune diversity in Svalbard reindeer provides a potential risk if the pathogenic pressure changes in response to altered environmental conditions due to climate change, or increased human-related activity.
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5
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Hu G, Do DN, Gray J, Miar Y. Selection for Favorable Health Traits: A Potential Approach to Cope with Diseases in Farm Animals. Animals (Basel) 2020; 10:E1717. [PMID: 32971980 PMCID: PMC7552752 DOI: 10.3390/ani10091717] [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: 09/08/2020] [Accepted: 09/21/2020] [Indexed: 12/17/2022] Open
Abstract
Disease is a global problem for animal farming industries causing tremendous economic losses (>USD 220 billion over the last decade) and serious animal welfare issues. The limitations and deficiencies of current non-selection disease control methods (e.g., vaccination, treatment, eradication strategy, genome editing, and probiotics) make it difficult to effectively, economically, and permanently eliminate the adverse influences of disease in the farm animals. These limitations and deficiencies drive animal breeders to be more concerned and committed to dealing with health problems in farm animals by selecting animals with favorable health traits. Both genetic selection and genomic selection contribute to improving the health of farm animals by selecting certain health traits (e.g., disease tolerance, disease resistance, and immune response), although both of them face some challenges. The objective of this review was to comprehensively review the potential of selecting health traits in coping with issues caused by diseases in farm animals. Within this review, we highlighted that selecting health traits can be applied as a method of disease control to help animal agriculture industries to cope with the adverse influences caused by diseases in farm animals. Certainly, the genetic/genomic selection solution cannot solve all the disease problems in farm animals. Therefore, management, vaccination, culling, medical treatment, and other measures must accompany selection solution to reduce the adverse impact of farm animal diseases on profitability and animal welfare.
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Affiliation(s)
| | | | | | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS B2N 5E3, Canada; (G.H.); (D.N.D.); (J.G.)
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6
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Smith J, Lipkin E, Soller M, Fulton JE, Burt DW. Mapping QTL Associated with Resistance to Avian Oncogenic Marek's Disease Virus (MDV) Reveals Major Candidate Genes and Variants. Genes (Basel) 2020; 11:genes11091019. [PMID: 32872585 PMCID: PMC7564597 DOI: 10.3390/genes11091019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 08/20/2020] [Accepted: 08/26/2020] [Indexed: 01/13/2023] Open
Abstract
Marek’s disease (MD) represents a significant global economic and animal welfare issue. Marek’s disease virus (MDV) is a highly contagious oncogenic and highly immune-suppressive α-herpes virus, which infects chickens, causing neurological effects and tumour formation. Though partially controlled by vaccination, MD continues to have a profound impact on animal health and on the poultry industry. Genetic selection provides an alternative and complementary method to vaccination. However, even after years of study, the genetic mechanisms underlying resistance to MDV remain poorly understood. The Major Histocompatability Complex (MHC) is known to play a role in disease resistance, along with a handful of other non-MHC genes. In this study, one of the largest to date, we used a multi-facetted approach to identify quantitative trait locus regions (QTLR) influencing resistance to MDV, including an F6 population from a full-sib advanced intercross line (FSIL) between two elite commercial layer lines differing in resistance to MDV, RNA-seq information from virus challenged chicks, and genome wide association study (GWAS) from multiple commercial lines. Candidate genomic elements residing in the QTLR were further tested for association with offspring mortality in the face of MDV challenge in eight pure lines of elite egg-layer birds. Thirty-eight QTLR were found on 19 chicken chromosomes. Candidate genes, microRNAs, long non-coding RNAs and potentially functional mutations were identified in these regions. Association tests were carried out in 26 of the QTLR, using eight pure lines of elite egg-layer birds. Numerous candidate genomic elements were strongly associated with MD resistance. Genomic regions significantly associated with resistance to MDV were mapped and candidate genes identified. Various QTLR elements were shown to have a strong genetic association with resistance. These results provide a large number of significant targets for mitigating the effects of MDV infection on both poultry health and the economy, whether by means of selective breeding, improved vaccine design, or gene-editing technologies.
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Affiliation(s)
- Jacqueline Smith
- The Roslin Institute and Royal (Dick) School of Veterinary Studies R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Ehud Lipkin
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem 91904, Israel
| | - Morris Soller
- Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem 91904, Israel
| | - Janet E Fulton
- Hy-Line International, P.O. Box 310, 2583 240th St., Dallas Center, IA 50063, USA
| | - David W Burt
- The Roslin Institute and Royal (Dick) School of Veterinary Studies R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
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Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs. Sci Rep 2020; 10:214. [PMID: 31937848 PMCID: PMC6959250 DOI: 10.1038/s41598-019-56903-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 12/10/2019] [Indexed: 11/08/2022] Open
Abstract
The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, five F2 populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to first flowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specific genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5 cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6 cM. Based on analysis of phenotyping data and genotyping data, 192 main effect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the five traits across the five populations. Major effect (PVE ≥ 10%) M-QTLs included 14 M-QTLs for SPC, 16 M-QTLs for SW, 17 M-QTLs for SY, 19 M-QTLs for GH and 24 M-QTLs for DFF. Also, 573 epistatic QTLs (E-QTLs) were detected with PVE ranging from 6.3 to 99.4% across traits and populations. Colocalization of M-QTLs and E-QTLs explained the genetic basis of the significant (P < 0.05) correlations of SPC with SW, SY, DFF and GH. The nature of genetic architecture of SPC and its relationship with agronomic traits suggest that genomics-assisted breeding targeting genome-wide variations would be effective for the simultaneous improvement of SPC and other important traits.
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8
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Contributions and perspectives of chicken genomics in Brazil: from biological model to export commodity. WORLD POULTRY SCI J 2019. [DOI: 10.1017/s004393390700164x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Affiliation(s)
- P.M. Hocking
- Roslin Institute, Roslin, Midlothian, Scotland, EH25 9PS
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10
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Romanov M, Sazanov A, Smirnov A. First century of chicken gene study and mapping – a look back and forward. WORLD POULTRY SCI J 2019. [DOI: 10.1079/wps20032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- M.N. Romanov
- Department of Microbiology and Molecular Genetics, 2209 Biomedical Physical Sciences, Michigan State University, East Lansing, MI 48824–4320, USA
| | - A.A. Sazanov
- All-Russian Institute of Animal Genetics and Breeding, Russian Academy of Agricultural Science, Moskovskoye shosse 55A, St Petersburg – Pushkin 189620, Russia
- Biological Research Institute, St Petersburg State University, Oranienbaumskoye shosse 2, St Petersburg – Stary Petergof 198504, Russia
| | - A.F. Smirnov
- All-Russian Institute of Animal Genetics and Breeding, Russian Academy of Agricultural Science, Moskovskoye shosse 55A, St Petersburg – Pushkin 189620, Russia
- Biological Research Institute, St Petersburg State University, Oranienbaumskoye shosse 2, St Petersburg – Stary Petergof 198504, Russia
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11
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Anacleto O, Cabaleiro S, Villanueva B, Saura M, Houston RD, Woolliams JA, Doeschl-Wilson AB. Genetic differences in host infectivity affect disease spread and survival in epidemics. Sci Rep 2019; 9:4924. [PMID: 30894567 PMCID: PMC6426847 DOI: 10.1038/s41598-019-40567-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 02/12/2019] [Indexed: 12/17/2022] Open
Abstract
Survival during an epidemic is partly determined by host genetics. While quantitative genetic studies typically consider survival as an indicator for disease resistance (an individual's propensity to avoid becoming infected or diseased), mortality rates of populations undergoing an epidemic are also affected by endurance (the propensity of diseased individual to survive the infection) and infectivity (i.e. the propensity of an infected individual to transmit disease). Few studies have demonstrated genetic variation in disease endurance, and no study has demonstrated genetic variation in host infectivity, despite strong evidence for considerable phenotypic variation in this trait. Here we propose an experimental design and statistical models for estimating genetic diversity in all three host traits. Using an infection model in fish we provide, for the first time, direct evidence for genetic variation in host infectivity, in addition to variation in resistance and endurance. We also demonstrate how genetic differences in these three traits contribute to survival. Our results imply that animals can evolve different disease response types affecting epidemic survival rates, with important implications for understanding and controlling epidemics.
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Affiliation(s)
- Osvaldo Anacleto
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
- Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil.
| | - Santiago Cabaleiro
- Centro Tecnológico del Cluster de la Acuicultura (CETGA), A Coruña, Spain
| | | | - María Saura
- Departamento de Mejora Genética Animal, INIA, Madrid, Spain
| | - Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - John A Woolliams
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Andrea B Doeschl-Wilson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
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12
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Chakraborty P, Kuo R, Vervelde L, Dutia BM, Kaiser P, Smith J. Macrophages from Susceptible and Resistant Chicken Lines have Different Transcriptomes following Marek's Disease Virus Infection. Genes (Basel) 2019; 10:genes10020074. [PMID: 30678299 PMCID: PMC6409778 DOI: 10.3390/genes10020074] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 01/10/2019] [Accepted: 01/21/2019] [Indexed: 12/12/2022] Open
Abstract
Despite successful control by vaccination, Marek’s disease (MD) has continued evolving to greater virulence over recent years. To control MD, selection and breeding of MD-resistant chickens might be a suitable option. MHC-congenic inbred chicken lines, 61 and 72, are highly resistant and susceptible to MD, respectively, but the cellular and genetic basis for these phenotypes is unknown. Marek’s disease virus (MDV) infects macrophages, B-cells, and activated T-cells in vivo. This study investigates the cellular basis of resistance to MD in vitro with the hypothesis that resistance is determined by cells active during the innate immune response. Chicken bone marrow-derived macrophages from lines 61 and 72 were infected with MDV in vitro. Flow cytometry showed that a higher percentage of macrophages were infected in line 72 than in line 61. A transcriptomic study followed by in silico functional analysis of differentially expressed genes was then carried out between the two lines pre- and post-infection. Analysis supports the hypothesis that macrophages from susceptible and resistant chicken lines display a marked difference in their transcriptome following MDV infection. Resistance to infection, differential activation of biological pathways, and suppression of oncogenic potential are among host defense strategies identified in macrophages from resistant chickens.
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Affiliation(s)
- Pankaj Chakraborty
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
- Chittagong Veterinary and Animal Sciences University, Khulshi, Chittagong 4225, Bangladesh
| | - Richard Kuo
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
| | - Lonneke Vervelde
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
| | - Bernadette M. Dutia
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
| | - Pete Kaiser
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
| | - Jacqueline Smith
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK; (P.C.); (R.K.); (L.V.); (B.M.D.)
- Correspondence: ; Tel.: +44-(0)131-6519155
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13
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Shi H, Zhou T, Wang X, Yang Y, Wu C, Liu S, Bao L, Li N, Yuan Z, Jin Y, Tan S, Wang W, Zhong X, Qin G, Geng X, Gao D, Dunham R, Liu Z. Genome-wide association analysis of intra-specific QTL associated with the resistance for enteric septicemia of catfish. Mol Genet Genomics 2018; 293:1365-1378. [PMID: 29967962 DOI: 10.1007/s00438-018-1463-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 06/19/2018] [Indexed: 02/07/2023]
Abstract
Disease resistance is one of the most important traits for aquaculture industry. For catfish industry, enteric septicemia of catfish (ESC), caused by the bacterial pathogen Edwardsiella ictaluri, is the most severe disease, causing enormous economic losses every year. In this study, we used three channel catfish families with 900 individuals (300 fish per family) and the 690K catfish SNP array, and conducted a genome-wide association study to detect the quantitative trait loci (QTL) associated with ESC resistance. Three significant QTL, with two of located on LG1 and one on LG26, and three suggestive QTL located on LG1, LG3, and LG21, respectively, were identified to be associated with ESC resistance. With a well-assembled- and -annotated reference genome sequence, genes around the involved QTL regions were identified. Among these genes, 37 genes had known functions in immunity, which may be involved in ESC resistance. Notably, nlrc3 and nlrp12 identified here were also found in QTL regions of ESC resistance in the channel catfish × blue catfish interspecific hybrid system, suggesting this QTL was operating within both intra-specific channel catfish populations and interspecific hybrid backcross populations. Many of the genes of the Class I MHC pathway, for mediated antigen processing and presentation, were found in the QTL regions. The positional correlation found in this study and the expressional correlation found in previous studies indicated that Class I MHC pathway was significantly associated with ESC resistance. This study validated one QTL previously identified using the second and fourth generation of the interspecific hybrid backcross progenies, and identified five additional QTL among channel catfish families. Taken together, it appears that there are only a few major QTL for ESC disease resistance, making marker-assisted selection an effective approach for genetic improvements of ESC resistance.
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Affiliation(s)
- Huitong Shi
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaozhu Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Chenglong Wu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Lisui Bao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ning Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Suxu Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Wenwen Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaoxiao Zhong
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Guyu Qin
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xin Geng
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- Department of Biology, College of Art and Sciences, Syracuse University, Syracuse, NY, 13244, USA.
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14
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Abstract
AbstractThe relations between genetic change in domestic livestock and infectious disease (including both its epidemiology and the animal's reaction to it) are examined. The overall picture is confusing because there are different, and seemingly unrelated, ways of considering the issue. An attempt is made to put these together into a more general framework. Four processes of particular interest are distinguished and discussed in more detail: (i) the way a population's genetic potential for immunocompetence can be changed by breeding, (ii) the way an animal's immunocompetence is influenced by that animal's production potential, in combination with the environmental resources that are available to it at a given time, (iii) the way the disease status of an animal (and a population of animals) is influenced by its immunocompetence, and (iv) the way the production level of an animal is influenced by activation of its immune system. Ultimately, all four processes influence the realised level of production.This comes down to four questions that need to be addressed: (i) can we use genetic variation in immunocompetence in animal breeding? (ii) does a higher production potential (today's direction of breeding) have a negative impact on immunocompetence? (iii) does improved immunocompetence result in improved health? and (iv) how large is the negative impact of disease on production?
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15
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Farhanah MI, Yasmin AR, Mat Isa N, Hair-Bejo M, Ideris A, Powers C, Oladapo O, Nair V, Khoo JS, Ghazali AK, Yee WY, Omar AR. Bursal transcriptome profiling of different inbred chicken lines reveals key differentially expressed genes at 3 days post-infection with very virulent infectious bursal disease virus. J Gen Virol 2018; 99:21-35. [PMID: 29058656 DOI: 10.1099/jgv.0.000956] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Infectious bursal disease is a highly contagious disease in the poultry industry and causes immunosuppression in chickens. Genome-wide regulations of immune response genes of inbred chickens with different genetic backgrounds, following very virulent infectious bursal disease virus (vvIBDV) infection are poorly characterized. Therefore, this study aims to analyse the bursal tissue transcriptome of six inbred chicken lines 6, 7, 15, N, O and P following infection with vvIBDV strain UK661 using strand-specific next-generation sequencing, by highlighting important genes and pathways involved in the infected chicken during peak infection at 3 days post-infection. All infected chickens succumbed to the infection without major variations among the different lines. However, based on the viral loads and bursal lesion scoring, lines P and 6 can be considered as the most susceptible lines, while lines 15 and N were regarded as the least affected lines. Transcriptome profiling of the bursa identified 4588 genes to be differentially expressed, with 2985 upregulated and 1642 downregulated genes, in which these genes were commonly or uniquely detected in all or several infected lines. Genes that were upregulated are primarily pro-inflammatory cytokines, chemokines and IFN-related. Various genes that are associated with B-cell functions and genes related to apoptosis were downregulated, together with the genes involved in p53 signalling. In conclusion, bursal transcriptome profiles of different inbred lines showed differential expressions of pro-inflammatory cytokines and chemokines, Th1 cytokines, JAK-STAT signalling genes, MAPK signalling genes, and their related pathways following vvIBDV infection.
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Affiliation(s)
- Mohd Isa Farhanah
- Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
| | - Abd Rahaman Yasmin
- Department of Veterinary Laboratory Diagnostic, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Selangor, Malaysia
| | - Nurulfiza Mat Isa
- Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
- Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Selangor, Malaysia
| | - Mohd Hair-Bejo
- Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
- Department of Veterinary Pathology and Microbiology, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Selangor, Malaysia
| | - Aini Ideris
- Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
- Department of Veterinary Clinical Studies, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Selangor, Malaysia
| | - Claire Powers
- Avian Viral Diseases, The Pirbright Institute, Pirbright, Woking, UK
| | | | - Venugopal Nair
- Avian Viral Diseases, The Pirbright Institute, Pirbright, Woking, UK
| | - Jia-Shiun Khoo
- Codon Genomics SB, Taman Dutamas, Balakong, Seri Kembangan, Selangor, Malaysia
| | - Ahmad-Kamal Ghazali
- Codon Genomics SB, Taman Dutamas, Balakong, Seri Kembangan, Selangor, Malaysia
| | - Wai-Yan Yee
- Codon Genomics SB, Taman Dutamas, Balakong, Seri Kembangan, Selangor, Malaysia
| | - Abdul Rahman Omar
- Laboratory of Vaccines and Immunotherapeutics, Institute of Bioscience, Universiti Putra Malaysia, Selangor, Malaysia
- Department of Veterinary Pathology and Microbiology, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Selangor, Malaysia
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16
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Dong K, Chang S, Xie Q, Black-Pyrkosz A, Zhang H. Comparative transcriptomics of genetically divergent lines of chickens in response to Marek's disease virus challenge at cytolytic phase. PLoS One 2017; 12:e0178923. [PMID: 28591220 PMCID: PMC5462384 DOI: 10.1371/journal.pone.0178923] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 05/22/2017] [Indexed: 11/30/2022] Open
Abstract
Marek's disease (MD), caused by Marek's disease virus (MDV), remains an economically significant threat to the poultry industry worldwide. Genetic resistance to MD is a promising alternative strategy to augment current control measures (vaccination and management). However, only a few functional genes reportedly conferring MD resistance have been identified. Here, we performed a comparative transcriptomics analysis of two highly inbred yet genetically divergent lines of chickens (line 63 and 72) that are resistant and susceptible to MD, respectively, in response to a very virulent plus strain of MDV (vv+MDV) challenge at cytolytic phase. A total of 203 DEGs in response to MDV challenge were identified in the two lines. Of these, 96 DEGs were in common for both lines, in addition to 36 and 71 DEGs that were specific for line 63 and 72, respectively. Functional enrichment analysis results showed the DEGs were significantly enriched in GO terms and pathways associated with immune response. Especially, the four DEGs, FGA, ALB, FN1, and F13A1 that reportedly facilitate virus invasion or immunosuppression, were found to be significantly up-regulated in the susceptible line 72 but down-regulated in the resistant line 63 birds. These results provide new resources for future studies to further elucidate the genetic mechanism conferring MD resistance.
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Affiliation(s)
- Kunzhe Dong
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, Michigan, United States of America
- ORISE Fellow, USDA, Agriculture Research Service, Avian Disease and Oncology Laboratory, East Lansing, Michigan, United States of America
| | - Shuang Chang
- College of Veterinary Medicine, Shandong Agricultural University, Tai’an, Shandong, China
| | - Qingmei Xie
- College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Alexis Black-Pyrkosz
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, Michigan, United States of America
| | - Huanmin Zhang
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, Michigan, United States of America
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17
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Characterization of Copy Number Variation's Potential Role in Marek's Disease. Int J Mol Sci 2017; 18:ijms18051020. [PMID: 28486430 PMCID: PMC5454933 DOI: 10.3390/ijms18051020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 04/22/2017] [Accepted: 05/04/2017] [Indexed: 02/07/2023] Open
Abstract
Marek’s Disease (MD) is a highly contagious pathogenic and oncogenic disease primarily affecting chickens. Chicken Lines 63 and 72, as well as their recombinant congenic strains (RCS) with varied susceptibility to MD, are ideal models to study the complex mechanisms of genetic resistance to MD. In this study, we investigated copy number variation (CNV) in these inbred chicken lines using the Affymetrix Axiom HD 600 K SNP genotyping array. We detected 393 CNV segments across all ten chicken lines, of which 12 CNVs were specifically identified in Line 72. We then assessed genetic structure based on CNV and observed markedly different patterns. Finally, we validated two deletion events in Line 72 and correlated them with genes expression using qPCR and RNA-seq, respectively. Our combined results indicated that these two CNV deletions were likely to contribute to MD susceptibility.
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18
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Kaya M, Preeyanon L, Dodgson JB, Cheng HH. Validation of Alternative Transcript Splicing in Chicken Lines that Differ in Genetic Resistance to Marek's Disease. Anim Biotechnol 2017; 27:238-44. [PMID: 27565867 DOI: 10.1080/10495398.2016.1178139] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Utilizing RNA-seq data, 1,574 candidate genes with alternative splicing were previously identified between two chicken lines that differ in Marek's disease (MD) genetic resistance under control and Marek's disease virus infection conditions. After filtering out 1,530 genes with splice variants in the first or last exon, 44 genes were screened for possible exon loss or gain using PCR and gel electrophoresis. Consequently, 7 genes exhibited visually detectable differential expression of splice variants between lines 6 (MD resistant) and 7 (MD susceptible), and the resultant PCR products verified by DNA sequencing. Birds from inbred line 6 have transcripts that preferentially retain an exon compared to line 7 chickens for ITGB2, SGPL1, and COMMD5. Birds from inbred line 7 have alleles that preferentially retain an exon compared to line 6 for MOCS2. CCBL2 exon 1a is absent and ATAD1 exon 2 is truncated by 87 nucleotides in transcripts expressed by line 7 compared to those from line 6. For CHTF18, line 6 transcripts have an indel mutation with 7 additional nucleotides in exon 21 compared to line 7. The current study validates 7 genes with alternatively spliced isomers between the two chicken lines, which helps provide potential underlying mechanisms for the phenotypic differences.
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Affiliation(s)
- Muhammet Kaya
- a Eskişehir Osmangazi University, Faculty of Agriculture, Department of Agricultural Biotechnology , Eskisehir , Turkey.,b Michigan State University , East Lansing , Michigan , USA
| | | | | | - Hans H Cheng
- c USDA, ARS, Avian Disease & Oncology Laboratory , East Lansing , Michigan , USA
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19
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McPherson MC, Delany ME. Virus and host genomic, molecular, and cellular interactions during Marek's disease pathogenesis and oncogenesis. Poult Sci 2016; 95:412-29. [PMID: 26755654 PMCID: PMC4957504 DOI: 10.3382/ps/pev369] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Accepted: 11/09/2015] [Indexed: 01/16/2023] Open
Abstract
Marek's Disease Virus (MDV) is a chicken alphaherpesvirus that causes paralysis, chronic wasting, blindness, and fatal lymphoma development in infected, susceptible host birds. This disease and its protective vaccines are highly relevant research targets, given their enormous impact within the poultry industry. Further, Marek's disease (MD) serves as a valuable model for the investigation of oncogenic viruses and herpesvirus patterns of viral latency and persistence--as pertinent to human health as to poultry health. The objectives of this article are to review MDV interactions with its host from a variety of genomic, molecular, and cellular perspectives. In particular, we focus on cytogenetic studies, which precisely assess the physical status of the MDV genome in the context of the chicken host genome. Combined, the cytogenetic and genomic research indicates that MDV-host genome interactions, specifically integration of the virus into the host telomeres, is a key feature of the virus life cycle, contributing to the viral achievement of latency, transformation, and reactivation of lytic replication. We present a model that outlines the variety of virus-host interactions, at the multiple levels, and with regard to the disease states.
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Affiliation(s)
- M C McPherson
- Department of Animal Science, University of California, Davis, CA 95616
| | - M E Delany
- Department of Animal Science, University of California, Davis, CA 95616
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20
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Anacleto O, Garcia-Cortés LA, Lipschutz-Powell D, Woolliams JA, Doeschl-Wilson AB. A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission. Genetics 2015; 201:871-84. [PMID: 26405030 PMCID: PMC4649657 DOI: 10.1534/genetics.115.179853] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 09/17/2015] [Indexed: 11/18/2022] Open
Abstract
There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.
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Affiliation(s)
- Osvaldo Anacleto
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom
| | - Luis Alberto Garcia-Cortés
- Departamento de Mejora Genética, Instituto Nacional de Investigación Agraria, Ctra. de La Coruña km. 7.5, Madrid 28040, Spain
| | - Debby Lipschutz-Powell
- Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom
| | - John A Woolliams
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom
| | - Andrea B Doeschl-Wilson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, United Kingdom
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21
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Yan Y, Yang N, Cheng HH, Song J, Qu L. Genome-wide identification of copy number variations between two chicken lines that differ in genetic resistance to Marek's disease. BMC Genomics 2015; 16:843. [PMID: 26492869 PMCID: PMC4619206 DOI: 10.1186/s12864-015-2080-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 10/13/2015] [Indexed: 11/10/2022] Open
Abstract
Background Copy number variation (CNV) is a major source of genome polymorphism that directly contributes to phenotypic variation such as resistance to infectious diseases. Lines 63 and 72 are two highly inbred experimental chicken lines that differ greatly in susceptibility to Marek’s disease (MD), and have been used extensively in efforts to identify the genetic and molecular basis for genetic resistance to MD. Using next generation sequencing, we present a genome-wide assessment of CNVs that are potentially associated with genetic resistance to MD. Methods Three chickens randomly selected from each line were sequenced to an average depth of 20×. Two popular software, CNVnator and Pindel, were used to call genomic CNVs separately. The results were combined to obtain a union set of genomic CNVs in the two chicken lines. Results A total of 5,680 CNV regions (CNVRs) were identified after merging the two datasets, of which 1,546 and 1,866 were specific to the MD resistant or susceptible line, respectively. Over half of the line-specific CNVRs were shared by 2 or more chickens, reflecting the reduced diversity in both inbred lines. The CNVRs fixed in the susceptible lines were significantly enriched in genes involved in MAPK signaling pathway. We also found 67 CNVRs overlapping with 62 genes previously shown to be strong candidates of the underlying genes responsible for the susceptibility to MD. Conclusions Our findings provide new insights into the genetic architecture of the two chicken lines and additional evidence that MAPK signaling pathway may play an important role in host response to MD virus infection. The rich source of line-specific CNVs is valuable for future disease-related association studies in the two chicken lines. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2080-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yiyuan Yan
- Department of Animal Genetics and Breeding, College of Animal Science, China Agricultural University, Beijing, 100193, China.
| | - Ning Yang
- Department of Animal Genetics and Breeding, College of Animal Science, China Agricultural University, Beijing, 100193, China.
| | - Hans H Cheng
- USDA, ARS, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA.
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| | - Lujiang Qu
- Department of Animal Genetics and Breeding, College of Animal Science, China Agricultural University, Beijing, 100193, China.
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22
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Cheng HH, Perumbakkam S, Pyrkosz AB, Dunn JR, Legarra A, Muir WM. Fine mapping of QTL and genomic prediction using allele-specific expression SNPs demonstrates that the complex trait of genetic resistance to Marek's disease is predominantly determined by transcriptional regulation. BMC Genomics 2015; 16:816. [PMID: 26481588 PMCID: PMC4617451 DOI: 10.1186/s12864-015-2016-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2015] [Accepted: 10/04/2015] [Indexed: 11/30/2022] Open
Abstract
Background Marek’s disease (MD) is a lymphoproliferative disease of poultry induced by Marek’s disease virus (MDV), a highly oncogenic alphaherpesvirus. Identifying the underlying genes conferring MD genetic resistance is desired for more efficacious control measures including genomic selection, which requires accurately identified genetic markers throughout the chicken genome. Methods Hypothesizing that variants located in transcriptional regulatory regions are the main mechanism underlying this complex trait, a genome-wide association study was conducted by genotyping a ~1,000 bird MD resource population derived from experimental inbred layers with SNPs containing 1,824 previously identified allele-specific expression (ASE) SNPs in response to MDV infection as well as 3,097 random SNPs equally spaced throughout the chicken genome. Based on the calculated associations, genomic predictions were determined for 200 roosters and selected sires had their progeny tested for Marek’s disease incidence. Results Our analyses indicate that these ASE SNPs account for more than 83 % of the genetic variance and exhibit nearly all the highest associations. To validate these findings, 200 roosters had their genetic merit predicted from the ASE SNPs only, and the top 30 and bottom 30 ranked roosters were reciprocally mated to random hens. The resulting progeny showed that after only one generation of bidirectional selection, there was a 22 % difference in MD incidence and this approach gave a 125 % increase in accuracy compared to current pedigree-based estimates. Conclusions We conclude that variation in transcriptional regulation is the major driving cause for genetic resistance to MD, and ASE SNPs identify the underlying genes and are sufficiently linked to the causative polymorphisms that they can be used for accurate genomic prediction as well as help define the underlying molecular basis. Furthermore, this approach should be applicable to other complex traits. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2016-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hans H Cheng
- USDA, ARS, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA.
| | - Sudeep Perumbakkam
- USDA, ARS, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA.,Microbiology & Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA
| | | | - John R Dunn
- USDA, ARS, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA
| | - Andres Legarra
- INRA, Animal Genetics, GenPhySE, Castanet Tolosan, 31326, France
| | - William M Muir
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA
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23
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Chappell P, Meziane EK, Harrison M, Magiera Ł, Hermann C, Mears L, Wrobel AG, Durant C, Nielsen LL, Buus S, Ternette N, Mwangi W, Butter C, Nair V, Ahyee T, Duggleby R, Madrigal A, Roversi P, Lea SM, Kaufman J. Expression levels of MHC class I molecules are inversely correlated with promiscuity of peptide binding. eLife 2015; 4:e05345. [PMID: 25860507 PMCID: PMC4420994 DOI: 10.7554/elife.05345] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2014] [Accepted: 04/10/2015] [Indexed: 11/13/2022] Open
Abstract
Highly polymorphic major histocompatibility complex (MHC) molecules are at the heart of adaptive immune responses, playing crucial roles in many kinds of disease and in vaccination. We report that breadth of peptide presentation and level of cell surface expression of class I molecules are inversely correlated in both chickens and humans. This relationship correlates with protective responses against infectious pathogens including Marek's disease virus leading to lethal tumours in chickens and human immunodeficiency virus infection progressing to AIDS in humans. We propose that differences in peptide binding repertoire define two groups of MHC class I molecules strategically evolved as generalists and specialists for different modes of pathogen resistance. We suggest that differences in cell surface expression level ensure the development of optimal peripheral T cell responses. The inverse relationship of peptide repertoire and expression is evidently a fundamental property of MHC molecules, with ramifications extending beyond immunology and medicine to evolutionary biology and conservation.
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Affiliation(s)
- Paul Chappell
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - El Kahina Meziane
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Michael Harrison
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Łukasz Magiera
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Clemens Hermann
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Laura Mears
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Antony G Wrobel
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Charlotte Durant
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Lise Lotte Nielsen
- Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Buus
- Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicola Ternette
- Target Discovery Institute, University of Oxford, Oxford, United Kingdom
| | | | | | | | - Trudy Ahyee
- Anthony Nolan Research Institute, The Royal Free Hospital, London, United Kingdom
| | - Richard Duggleby
- Anthony Nolan Research Institute, The Royal Free Hospital, London, United Kingdom
| | - Alejandro Madrigal
- Anthony Nolan Research Institute, The Royal Free Hospital, London, United Kingdom
| | - Pietro Roversi
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Susan M Lea
- Sir William Dunn School of Pathology, University of Oxford, Oxford, United Kingdom
| | - Jim Kaufman
- Department of Pathology, University of Cambridge, Cambridge, United Kingdom
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Gao C, Han L, Han J, Liu J, Jiang Q, Guo D, Qu L. Establishment of six homozygous MHC-B haplotype populations associated with susceptibility to Marek's disease in Chinese specific pathogen-free BWEL chickens. INFECTION GENETICS AND EVOLUTION 2014; 29:15-25. [PMID: 25445653 DOI: 10.1016/j.meegid.2014.10.031] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Revised: 10/23/2014] [Accepted: 10/29/2014] [Indexed: 10/24/2022]
Abstract
The highly polymorphic chicken major histocompatibility complex (MHC) is associated with different levels of immunologic responses to certain avian pathogens. MHC-B haplotype chickens are an important genetic resource for studying the genetic determination of pathogen resistance and susceptibility. The BWEL chicken population is the only specific pathogen-free (SPF) chickens bred and developed by the State Center of Poultry Genetic Resources of Laboratory Animals in China. In this study, we successfully established six homozygous MHC-B haplotype populations from the BWEL chickens using microsatellite marker technology, named as BW/G(1, 2, 3, 5, 6, 7) lines, and their molecular genotypes were matched to six serologically defined MHC-B haplotypes, B13, B15, B2, B5, B21 and B19, respectively. The sequences of BF genes exons 2 and 3 from four successive generations (F1-F4) of the BW/G(n) lines were completely consistent with those of serologically defined MHC-B haplotypes. Subsequently, six BW/G(n) line specific allo-antisera were prepared by immunization with red blood cells (RBCs) and hemagglutination tests results showed the BW/G(n) SPF chickens could be serologically differentiated. Additionally, susceptibility to Marek's disease (MD) in the BW/G3 (B2 haplotype) and BW/G7 (B19 haplotype) lines were determined by comparing mortality, macroscopic and histopathological lesions, and viral loads in feather pulp. The BW/G7 line showed greater genetic susceptibility to the very virulent MD virus (MDV) strain than the BW/G3 line. The establishment of MHC-B haplotype chicken populations associated with susceptibility to MD will be helpful for studying host immune responses and further developing the more effective vaccines in the context of MHC specificities, and they are also very useful for an understanding of MHC genes architecture and function.
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Affiliation(s)
- Caixia Gao
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China
| | - Lingxia Han
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China.
| | - Jianlin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100193, China
| | - Jiasen Liu
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China
| | - Qian Jiang
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China
| | - Dongchun Guo
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China
| | - Liandong Qu
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin 150001, China.
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Fan WL, Ng CS, Chen CF, Lu MYJ, Chen YH, Liu CJ, Wu SM, Chen CK, Chen JJ, Mao CT, Lai YT, Lo WS, Chang WH, Li WH. Genome-wide patterns of genetic variation in two domestic chickens. Genome Biol Evol 2013; 5:1376-92. [PMID: 23814129 PMCID: PMC3730349 DOI: 10.1093/gbe/evt097] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Domestic chickens are excellent models for investigating the genetic basis of phenotypic diversity, as numerous phenotypic changes in physiology, morphology, and behavior in chickens have been artificially selected. Genomic study is required to study genome-wide patterns of DNA variation for dissecting the genetic basis of phenotypic traits. We sequenced the genomes of the Silkie and the Taiwanese native chicken L2 at ∼23- and 25-fold average coverage depth, respectively, using Illumina sequencing. The reads were mapped onto the chicken reference genome (including 5.1% Ns) to 92.32% genome coverage for the two breeds. Using a stringent filter, we identified ∼7.6 million single-nucleotide polymorphisms (SNPs) and 8,839 copy number variations (CNVs) in the mapped regions; 42% of the SNPs have not found in other chickens before. Among the 68,906 SNPs annotated in the chicken sequence assembly, 27,852 were nonsynonymous SNPs located in 13,537 genes. We also identified hundreds of shared and divergent structural and copy number variants in intronic and intergenic regions and in coding regions in the two breeds. Functional enrichments of identified genetic variants were discussed. Radical nsSNP-containing immunity genes were enriched in the QTL regions associated with some economic traits for both breeds. Moreover, genetic changes involved in selective sweeps were detected. From the selective sweeps identified in our two breeds, several genes associated with growth, appetite, and metabolic regulation were identified. Our study provides a framework for genetic and genomic research of domestic chickens and facilitates the domestic chicken as an avian model for genomic, biomedical, and evolutionary studies.
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Affiliation(s)
- Wen-Lang Fan
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
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Van Eenennaam AL, Weigel KA, Young AE, Cleveland MA, Dekkers JCM. Applied animal genomics: results from the field. Annu Rev Anim Biosci 2013; 2:105-39. [PMID: 25384137 DOI: 10.1146/annurev-animal-022513-114119] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Genomic selection (GS) is the use of statistical methods to estimate the genetic merit of a genotyped animal based on prediction equations derived from large ancestral populations with both phenotypes and genotypes. It has revolutionized the dairy cattle breeding industry and has been implemented with varying degrees of success in other animal breeding programs, including swine, poultry, and beef cattle. The findings of empirical field studies applying GS to the breeding sectors of these main animal protein industries are reviewed. Several translational considerations must be addressed before implementing GS in genetic improvement programs. These include determining and obtaining economically relevant phenotypes and determining the optimal size of the training population, cost-effective genotyping strategies, the practicality of field implementation, and the relative costs versus the benefits of the realized rate of genetic gain. GS may additionally change the optimal breeding scheme design, and studies that address this consideration are also reviewed briefly.
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Transcriptional profiling of mEq-dependent genes in Marek's disease resistant and susceptible inbred chicken lines. PLoS One 2013; 8:e78171. [PMID: 24205146 PMCID: PMC3804455 DOI: 10.1371/journal.pone.0078171] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Accepted: 09/17/2013] [Indexed: 12/18/2022] Open
Abstract
Marek’s disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Marek’s disease virus (MDV). Understanding the genes and biological pathways that confer MD genetic resistance should lead towards the development of more disease resistant commercial poultry flocks or improved MD vaccines. MDV mEq, a bZIP transcription factor, is largely attributed to viral oncogenicity though only a few host target genes have been described, which has impeded our understanding of MDV-induced tumorigenesis. Given the importance of mEq in MDV-induced pathogenesis, we explored the role of mEq in genetic resistance to MDV. Using global transcriptome analysis and cells from MD resistant or susceptible birds, we compared the response to infection with either wild type MDV or a nononcogenic recombinant lacking mEq. As a result, we identified a number of specific genes and pathways associated with either MD resistance or susceptibility. Additionally, integrating prior information from ChIP-seq, microarray analysis, and SNPs exhibiting allele-specific expression (ASE) in response to MDV infection, we were able to provide evidence for 24 genes that are polymorphic within mEq binding sites are likely to account for gene expression in an allele-specific manner and potentially for the underlying genetic differences in MD incidence.
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Wolc A, Arango J, Jankowski T, Settar P, Fulton JE, O'Sullivan NP, Fernando R, Garrick DJ, Dekkers JCM. Genome-wide association study for Marek's disease mortality in layer chickens. Avian Dis 2013; 57:395-400. [PMID: 23901752 DOI: 10.1637/10409-100312-reg.1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
A genome-wide association study (GWAS) using Bayesian variable selection was performed to determine genomic regions associated with mortality due to Marek's disease virus (MDV) infection in layers. Mortality (%) under experimental disease challenge (500 plaque-forming units of a very virulent plus MDV strain) was recorded for progeny groups (average 15.5 birds; range 3 to 30) of 253 genotyped sires from four generations of a brown-egg layer line. An additional generation of 43 sires with progeny data was used to validate results. Sires were genotyped with a 42K Illumina single-nucleotide polymorphism (SNP) chip. Methods BayesB (pi = 0.995) and BayesCpi, with or without weighting residuals by the size of progeny groups were applied. The proportion of genetic variance contributed by SNPs within each 1-megabase (Mb) genomic region was quantified. Average mortality was 33% but differed significantly between generations. Genetic markers explained about 11% of phenotypic variation in mortality. Correlations between genomic estimated breeding values and percentage of progeny mortality for the validation generation (sons of individuals in training) were 0.12, 0.17, 0.02, and 0.16 for BayesB, weighted BayesB, BayesCpi, and weighted BayesCpi, respectively, when using the whole genome, and 0.03, 0.20, -0.06, and 0.14, when using only SNP from the 10, 1-Mb regions, explaining the largest proportion of genetic variance according to each method. Results suggest that regions on chromosomes 2, 3, 4, 9, 15, 18, and 21 are associated with Marek's disease resistance and can be used for selection and that accounting for the size of progeny groups has a large impact on correct localization of such genomic regions.
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Affiliation(s)
- Anna Wolc
- Department of Genetic and Animal Breeding, Poznan University of Life Sciences, Wolynska Street 33, 60-637 Poznan, Poland.
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Fulton JE, Arango J, Arthur JA, Settar P, Kreager KS, O'Sullivan NP. Improving the outcome of a Marek's disease challenge in multiple lines of egg type chickens. Avian Dis 2013; 57:519-22. [PMID: 23901770 DOI: 10.1637/10408-100212-reg.1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
A challenge test following inoculation with a standard amount of a vv+ strain of the Marek's disease (MD) virus in multiple lines and multiple generations of egg type chicken and the corresponding phenotypic trend are described. This program significantly reduced mortality of progeny from selected sires for three to 11 generations in eight of the nine elite lines studied herein. In brown egg lines, a retrospective analysis of DNA indicated an association between the blood type B (major histocompatibility complex) of the sire and the MD mortality in the challenge of its progeny. As a result of the multigeneration stock amplification and crossbreeding processes used in the commercial breeding industry, improvement in survival after challenge at the elite level will translate to improved welfare for millions of birds at the commercial production level.
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Affiliation(s)
- J E Fulton
- Hy-Line International, P.O. Box 310, Dallas Center, 1A 50063, USA.
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Expression pattern of genes of RLR-mediated antiviral pathway in different-breed chicken response to Marek's disease virus infection. BIOMED RESEARCH INTERNATIONAL 2013; 2013:419256. [PMID: 23710447 PMCID: PMC3654640 DOI: 10.1155/2013/419256] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2012] [Accepted: 03/03/2013] [Indexed: 12/24/2022]
Abstract
It has been known that the chicken's resistance to disease was affected by chicken's genetic background. And RLR-mediated antiviral pathway plays an important role in detection of viral RNA. However, little is known about the interaction of genetic background with RLR-mediated antiviral pathway in chicken against MDV infection. In this study, we adopted economic line-AA broilers and native Erlang mountainous chickens for being infected with MDV. Upon infection with MDV, the expression of MDA-5 was upregulated in two-breed chickens at 4, 7, and 21 d.p.i. It is indicated that MDA-5 might be involved in detecting MDV in chicken. Interestingly, the expression of IRF-3 and IFN-β genes was decreased in spleen and thymus of broilers at 21 d.p.i, but it was upregulated in immune tissues of Erlang mountainous chickens. And the genome load of MDV in spleen of broiler is significantly higher than that in Erlang mountainous chickens. Meanwhile, we observed that the death of broiler mainly also occurred in this phase. Collectively, these present results demonstrated that the expression patters of IRF-3 and IFN-β genes in chicken against MDV infection might be affected by the genetic background which sequently influence the resistance of chicken response to MDV.
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31
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Genome-wide copy number variant analysis in inbred chickens lines with different susceptibility to Marek's disease. G3-GENES GENOMES GENETICS 2013; 3:217-23. [PMID: 23390598 PMCID: PMC3564982 DOI: 10.1534/g3.112.005132] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2012] [Accepted: 11/30/2012] [Indexed: 11/18/2022]
Abstract
Breeding of genetically resistant chickens to Marek’s disease (MD) is a vital strategy to poultry health. To find the markers underlying the genetic resistance to MD, copy number variation (CNV) was examined in inbred MD-resistant and -susceptible chicken lines. A total of 45 CNVs were found in four lines of chickens, and 28 were potentially involved in immune response and cell proliferation, etc. Importantly, two CNVs related with MD resistance were transmitted to descendent recombinant congenic lines that differ in susceptibility to MD. Our findings may lead to better strategies for genetic improvement of disease resistance in poultry.
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32
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Perumbakkam S, Muir WM, Black-Pyrkosz A, Okimoto R, Cheng HH. Comparison and contrast of genes and biological pathways responding to Marek's disease virus infection using allele-specific expression and differential expression in broiler and layer chickens. BMC Genomics 2013; 14:64. [PMID: 23363372 PMCID: PMC3599046 DOI: 10.1186/1471-2164-14-64] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2012] [Accepted: 01/22/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Marek's disease (MD) is a commercially important neoplastic disease of chickens caused by the Marek's disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Enhancing MD genetic resistance is desirable to augment current vaccines and other MD control measures. High throughput sequencing was used to profile splenic transcriptomes from individual F1 progeny infected with MDV at 4 days of age from both outbred broilers (meat-type) and inbred layer (egg-type) chicken lines that differed in MD genetic resistance. The resulting information was used to identify SNPs, genes, and biological pathways exhibiting allele-specific expression (ASE) in response to MDV infection in each type of chicken. In addition, we compared and contrasted the results of pathway analyses (ASE and differential expression (DE)) between chicken types to help inform on the biological response to MDV infection. RESULTS With 7 individuals per line and treatment group providing high power, we identified 6,132 single nucleotide polymorphisms (SNPs) in 4,768 genes and 4,528 SNPs in 3,718 genes in broilers and layers, respectively, that exhibited ASE in response to MDV infection. Furthermore, 548 and 434 genes in broilers and layers, respectively, were found to show DE following MDV infection. Comparing the datasets, only 72 SNPs and 850 genes for ASE and 20 genes for DE were common between the two bird types. Although the chicken types used in this study were genetically different, at the pathway level, both TLR receptor and JAK/STAT signaling pathways were enriched as well as exhibiting a high proportion of ASE genes, especially at the beginning of both above mentioned regulatory pathways. CONCLUSIONS RNA sequencing with adequate biological replicates is a powerful approach to identify high confidence SNPs, genes, and pathways that are associated with transcriptional response to MDV infection. In addition, the SNPs exhibiting ASE in response to MDV infection provide a strong foundation for determining the extent to which variation in expression influences MD incidence plus yield genetic markers for genomic selection. However, given the paucity of overlap among ASE SNP sets (broilers vs. layers), it is likely that separate screens need to be incorporated for each population. Finally, comparison of gene lists obtained between these two diverse chicken types indicate the TLR and JAK/STAT signaling are conserved when responding to MDV infection and may be altered by selection of genes exhibiting ASE found at the start of each pathway.
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Affiliation(s)
- Sudeep Perumbakkam
- Department of Animal Science, Purdue University, West Lafayette, IN, 47907, USA
| | - William M Muir
- Department of Animal Science, Purdue University, West Lafayette, IN, 47907, USA
| | | | - Ron Okimoto
- Cobb-Vantress, Siloam Springs, AR, 72761, USA
| | - Hans H Cheng
- Avian Diseases and Oncology Laboratory, USDA, ARS, East Lansing, MI, 48823, USA
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Cheng HH, Kaiser P, Lamont SJ. Integrated Genomic Approaches to Enhance Genetic Resistance in Chickens. Annu Rev Anim Biosci 2013; 1:239-60. [DOI: 10.1146/annurev-animal-031412-103701] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Hans H. Cheng
- Avian Disease and Oncology Laboratory, USDA, ARS, East Lansing, Michigan 48823;
| | - Pete Kaiser
- The Roslin Institute & Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, United Kingdom;
| | - Susan J. Lamont
- Department of Animal Science, Iowa State University, Ames, Iowa 50011;
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An assessment of opportunities to dissect host genetic variation in resistance to infectious diseases in livestock. Animal 2012; 3:415-36. [PMID: 22444313 DOI: 10.1017/s1751731108003522] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
This paper reviews the evidence for host genetic variation in resistance to infectious diseases for a wide variety of diseases of economic importance in poultry, cattle, pig, sheep and Atlantic salmon. Further, it develops a method of ranking each disease in terms of its overall impact, and combines this ranking with published evidence for host genetic variation and information on the current state of genomic tools in each host species. The outcome is an overall ranking of the amenability of each disease to genomic studies that dissect host genetic variation in resistance. Six disease-based assessment criteria were defined: industry concern, economic impact, public concern, threat to food safety or zoonotic potential, impact on animal welfare and threat to international trade barriers. For each category, a subjective score was assigned to each disease according to the relative strength of evidence, impact, concern or threat posed by that particular disease, and the scores were summed across categories. Evidence for host genetic variation in resistance was determined from available published data, including breed comparison, heritability studies, quantitative trait loci (QTL) studies, evidence of candidate genes with significant effects, data on pathogen sequence and on host gene expression analyses. In total, 16 poultry diseases, 13 cattle diseases, nine pig diseases, 11 sheep diseases and three Atlantic salmon diseases were assessed. The top-ranking diseases or pathogens, i.e. those most amenable to studies dissecting host genetic variation, were Salmonella in poultry, bovine mastitis, Marek's disease and coccidiosis, both in poultry. The top-ranking diseases or pathogens in pigs, sheep and Atlantic salmon were Escherichia coli, mastitis and infectious pancreatic necrosis, respectively. These rankings summarise the current state of knowledge for each disease and broadly, although not entirely, reflect current international research efforts. They will alter as more information becomes available and as genome tools become more sophisticated for each species. It is suggested that this approach could be used to rank diseases from other perspectives as well, e.g. in terms of disease control strategies.
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Li DF, Lian L, Qu LJ, Chen YM, Liu WB, Chen SR, Zheng JX, Xu GY, Yang N. A genome-wide SNP scan reveals two loci associated with the chicken resistance to Marek's disease. Anim Genet 2012; 44:217-22. [PMID: 22812605 DOI: 10.1111/j.1365-2052.2012.02395.x] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2012] [Indexed: 12/18/2022]
Abstract
Marek's disease (MD) is a neoplastic disease in chickens, caused by the Marek's disease virus (MDV). To investigate host genetic resistance to MD, we conducted a genome-wide association study (GWAS) on 67 MDV-infected chickens based on a case and control design, including 57 susceptible chickens in the case group and 10 resistant chickens as controls. After searching 38 655 valid genomic markers, two SNPs were found to be associated with host resistance to MD. One SNP, rs14527240, reaching chromosome-wide significance level (P < 0.01) was located in the SPARC-related modular calcium-binding 1 (SMOC1) gene on GGA5. The other one, GGaluGA156129, reaching genome-wide significance (P < 0.05), was located in the protein tyrosine phosphatase, non-receptor type 3 (PTPN3) gene on GGA2. In addition, expression patterns of these two genes in spleens were detected by qPCR. The expression of SMOC1 was significantly up-regulated (P < 0.05), whereas the expression of PTNP3 did not show significance when the case group was compared with the control group. Up-regulation of SMOC1 in susceptible spleens suggests its important roles in MD tumorigenesis. This is the first study to investigate MD-resistant loci, and it demonstrates the power of GWASs for mapping genes associated with MD resistance.
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Affiliation(s)
- D F Li
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Maceachern S, Muir WM, Crosby SD, Cheng HH. Genome-Wide Identification and Quantification of cis- and trans-Regulated Genes Responding to Marek's Disease Virus Infection via Analysis of Allele-Specific Expression. Front Genet 2012; 2:113. [PMID: 22303407 PMCID: PMC3268648 DOI: 10.3389/fgene.2011.00113] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2011] [Accepted: 12/29/2011] [Indexed: 11/17/2022] Open
Abstract
Marek’s disease (MD) is a commercially important neoplastic disease of chickens caused by Marek’s disease virus (MDV), a naturally occurring oncogenic alphaherpesvirus. Selecting for increased genetic resistance to MD is a control strategy that can augment vaccinal control measures. To identify high-confidence candidate MD resistance genes, we conducted a genome-wide screen for allele-specific expression (ASE) amongst F1 progeny of two inbred chicken lines that differ substantially in MD resistance. High throughput sequencing was initially used to profile transcriptomes from pools of uninfected and infected individuals at 4 days post-infection to identify any genes showing ASE in response to MDV infection. RNA sequencing identified 22,655 single nucleotide polymorphisms (SNPs) of which 5,360 in 3,773 genes exhibited significant allelic imbalance. Illumina GoldenGate assays were subsequently used to quantify regulatory variation controlled at the gene (cis) and elsewhere in the genome (trans) by examining differences in expression between F1 individuals and artificial F1 RNA pools over six time periods in 1,536 of the most significant SNPs identified by RNA sequencing. Allelic imbalance as a result of cis-regulatory changes was confirmed in 861 of the 1,233 GoldenGate assays successfully examined. Furthermore we have identified seven genes that display trans-regulation only in infected animals and ∼500 SNP that show a complex interaction between cis- and trans-regulatory changes. Our results indicate ASE analyses are a powerful approach to identify regulatory variation responsible for differences in transcript abundance in genes underlying complex traits. And the genes with SNPs exhibiting ASE provide a strong foundation to further investigate the causative polymorphisms and genetic mechanisms for MD resistance. Finally, the methods used here for identifying specific genes and SNPs have practical implications for applying marker-assisted selection to complex traits that are difficult to measure in agricultural species, when expression differences are expected to control a portion of the phenotypic variance.
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Affiliation(s)
- Sean Maceachern
- Avian Disease and Oncology Laboratory, Agricultural Research Service, United States Department of Agriculture East Lansing, MI, USA
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Smith J, Sadeyen JR, Paton IR, Hocking PM, Salmon N, Fife M, Nair V, Burt DW, Kaiser P. Systems analysis of immune responses in Marek's disease virus-infected chickens identifies a gene involved in susceptibility and highlights a possible novel pathogenicity mechanism. J Virol 2011; 85:11146-58. [PMID: 21865384 PMCID: PMC3194948 DOI: 10.1128/jvi.05499-11] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2011] [Accepted: 08/15/2011] [Indexed: 02/04/2023] Open
Abstract
Marek's disease virus (MDV) is a highly contagious oncogenic alphaherpesvirus that causes disease that is both a cancer model and a continuing threat to the world's poultry industry. This comprehensive gene expression study analyzes the host response to infection in both resistant and susceptible lines of chickens and inherent expression differences between the two lines following the infection of the host. A novel pathogenicity mechanism, involving the downregulation of genes containing HIC1 transcription factor binding sites as early as 4 days postinfection, was suggested from this analysis. HIC1 drives antitumor mechanisms, suggesting that MDV infection switches off genes involved in antitumor regulation several days before the expression of the MDV oncogene meq. The comparison of the gene expression data to previous QTL data identified several genes as candidates for involvement in resistance to MD. One of these genes, IRG1, was confirmed by single nucleotide polymorphism analysis to be involved in susceptibility. Its precise mechanism remains to be elucidated, although the analysis of gene expression data suggests it has a role in apoptosis. Understanding which genes are involved in susceptibility/resistance to MD and defining the pathological mechanisms of the disease gives us a much greater ability to try to reduce the incidence of this virus, which is costly to the poultry industry in terms of both animal welfare and economics.
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Affiliation(s)
- Jacqueline Smith
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, United Kingdom.
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Yu Y, Luo J, Mitra A, Chang S, Tian F, Zhang H, Yuan P, Zhou H, Song J. Temporal transcriptome changes induced by MDV in Marek's disease-resistant and -susceptible inbred chickens. BMC Genomics 2011; 12:501. [PMID: 21992110 PMCID: PMC3269463 DOI: 10.1186/1471-2164-12-501] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2011] [Accepted: 10/12/2011] [Indexed: 11/10/2022] Open
Abstract
Background Marek's disease (MD) is a lymphoproliferative disease in chickens caused by Marek's disease virus (MDV) and characterized by T cell lymphoma and infiltration of lymphoid cells into various organs such as liver, spleen, peripheral nerves and muscle. Resistance to MD and disease risk have long been thought to be influenced both by genetic and environmental factors, the combination of which contributes to the observed outcome in an individual. We hypothesize that after MDV infection, genes related to MD-resistance or -susceptibility may exhibit different trends in transcriptional activity in chicken lines having a varying degree of resistance to MD. Results In order to study the mechanisms of resistance and susceptibility to MD, we performed genome-wide temporal expression analysis in spleen tissues from MD-resistant line 63, susceptible line 72 and recombinant congenic strain M (RCS-M) that has a phenotype intermediate between lines 63 and 72 after MDV infection. Three time points of the MDV life cycle in chicken were selected for study: 5 days post infection (dpi), 10dpi and 21dpi, representing the early cytolytic, latent and late cytolytic stages, respectively. We observed similar gene expression profiles at the three time points in line 63 and RCS-M chickens that are both different from line 72. Pathway analysis using Ingenuity Pathway Analysis (IPA) showed that MDV can broadly influence the chickens irrespective of whether they are resistant or susceptible to MD. However, some pathways like cardiac arrhythmia and cardiovascular disease were found to be affected only in line 72; while some networks related to cell-mediated immune response and antigen presentation were enriched only in line 63 and RCS-M. We identified 78 and 30 candidate genes associated with MD resistance, at 10 and 21dpi respectively, by considering genes having the same trend of expression change after MDV infection in lines 63 and RCS-M. On the other hand, by considering genes with the same trend of expression change after MDV infection in lines 72 and RCS-M, we identified 78 and 43 genes at 10 and 21dpi, respectively, which may be associated with MD-susceptibility. Conclusions By testing temporal transcriptome changes using three representative chicken lines with different resistance to MD, we identified 108 candidate genes for MD-resistance and 121 candidate genes for MD-susceptibility over the three time points. Genes included in our resistance or susceptibility genes lists that are also involved in more than 5 biofunctions, such as CD8α, IL8, USP18, and CTLA4, are considered to be important genes involved in MD-resistance or -susceptibility. We were also able to identify several biofunctions related with immune response that we believe play an important role in MD-resistance.
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Affiliation(s)
- Ying Yu
- Department of Animal & Avian Sciences, University of Maryland, College Park, MD 20742, USA
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Meydan H, Yildiz M, Dodgson J, Cheng H. Allele-specific expression analysis reveals CD79B has a cis-acting regulatory element that responds to Marek's disease virus infection in chickens. Poult Sci 2011; 90:1206-11. [DOI: 10.3382/ps.2010-01295] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Abstract
It is more than a century since Marek's disease (MD) was first reported in chickens and since then there have been concerted efforts to better understand this disease, its causative agent and various approaches for control of this disease. Recently, there have been several outbreaks of the disease in various regions, due to the evolving nature of MD virus (MDV), which necessitates the implementation of improved prophylactic approaches. It is therefore essential to better understand the interactions between chickens and the virus. The chicken immune system is directly involved in controlling the entry and the spread of the virus. It employs two distinct but interrelated mechanisms to tackle viral invasion. Innate defense mechanisms comprise secretion of soluble factors as well as cells such as macrophages and natural killer cells as the first line of defense. These innate responses provide the adaptive arm of the immune system including antibody- and cell-mediated immune responses to be tailored more specifically against MDV. In addition to the immune system, genetic and epigenetic mechanisms contribute to the outcome of MDV infection in chickens. This review discusses our current understanding of immune responses elicited against MDV and genetic factors that contribute to the nature of the response.
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Barkova OU, Sazanova AL, Blagoveshenskiy IU, Fomichov KA, Malewski T, Sazanov AA. Design of a system for genotyping of Gallus gallus based on the rSNP (Regulatory single nucleotide polymorphism) alleles affecting the egg shell thickness. RUSS J GENET+ 2011. [DOI: 10.1134/s1022795411020049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Chang S, Dunn JR, Heidari M, Lee LF, Song J, Ernst CW, Ding Z, Bacon LD, Zhang H. Genetics and vaccine efficacy: host genetic variation affecting Marek's disease vaccine efficacy in White Leghorn chickens. Poult Sci 2010; 89:2083-91. [PMID: 20852098 DOI: 10.3382/ps.2010-00740] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Marek's disease (MD) is a T-cell lymphoma disease of domestic chickens induced by MD virus (MDV), a naturally oncogenic and highly contagious cell-associated α-herpesvirus. Earlier reports have shown that the MHC haplotype as well as non-MHC genes are responsible for genetic resistance to MD. The MHC was also shown to affect efficiency of vaccine response. Using specific-pathogen-free chickens from a series of 19 recombinant congenic strains and their 2 progenitor lines (lines 6(3) and 7(2)), vaccine challenge experiments were conducted to examine the effect of host genetic variation on vaccine efficacy. The 21 inbred lines of White Leghorns share the same B*2 MHC haplotype and the genome of each recombinant congenic strain differs by a random 1/8 sample of the susceptible donor line (7(2)) genome. Chickens from each of the lines were divided into 2 groups. One was vaccinated with turkey herpesvirus strain FC126 at the day of hatch and the other was treated as a nonvaccinated control. Chickens of both groups were inoculated with a very virulent plus strain of MDV on the fifth day posthatch. Analyses of the MD data showed that the genetic line significantly influenced MD incidence and days of survival post-MDV infection after vaccination of chickens (P<0.01). The protective indices against MD varied greatly among the lines with a range of 0 up to 84%. This is the first evidence that non-MHC host genetic variation significantly affects MD vaccine efficacy in chickens in a designed prospective study.
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Affiliation(s)
- S Chang
- Avian Disease and Oncology Laboratory, USDA, Agricultural Research Service, 3606 E. Mount Hope Road, East Lansing, MI 48823, USA
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Vallejo RL, Wiens GD, Rexroad CE, Welch TJ, Evenhuis JP, Leeds TD, Janss LLG, Palti Y. Evidence of major genes affecting resistance to bacterial cold water disease in rainbow trout using Bayesian methods of segregation analysis. J Anim Sci 2010; 88:3814-32. [PMID: 20833766 DOI: 10.2527/jas.2010-2951] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation for BCWD resistance in our rainbow trout population, and a family-based selection program to improve resistance was initiated at the National Center for Cool and Cold Water Aquaculture (NCCCWA). This study investigated evidence of major trait loci affecting BCWD resistance using only phenotypic data (without using genetic markers) and Bayesian methods of segregation analysis (BMSA). A total of 10,603 juvenile fish from 101 full-sib families corresponding to 3 generations (2005, 2007, and 2009 hatch years) of the NCCCWA population were challenged by intraperitoneal injection with Flavobacterium psychrophilum, the bacterium that causes BCWD. The results from single- and multiple-QTL models of BMSA suggest that 6 to 10 QTL explaining 83 to 89% of phenotypic variance with either codominant or dominant disease-resistant alleles plus polygenic effects may underlie the genetic architecture of BCWD resistance. This study also highlights the importance of polygenic background effects in the genetic variation of BCWD resistance. The polygenic heritability on the observed scale of survival status is slightly larger than that previously reported for rainbow trout BCWD resistance. These findings provide the basis for designing informative crosses for QTL mapping and carrying out genome scans for QTL affecting BCWD resistance in rainbow trout.
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Affiliation(s)
- R L Vallejo
- National Center for Cool and Cold Water Aquaculture, USDA/ARS, 11861 Leetown Rd., Kearneysville, WV 25430, USA.
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Santos VVAD, Costa APMD, Soares NKM, Pires JF, Ramalho HMM, Dimenstein R. Effect of storage on retinol concentration of Cobb and Ross strain chicken livers. Int J Food Sci Nutr 2009; 60 Suppl 1:220-31. [DOI: 10.1080/09637480902992862] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Chen M, Payne WS, Hunt H, Zhang H, Holmen SL, Dodgson JB. Inhibition of Marek's disease virus replication by retroviral vector-based RNA interference. Virology 2008; 377:265-72. [DOI: 10.1016/j.virol.2008.03.019] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2008] [Revised: 02/07/2008] [Accepted: 03/15/2008] [Indexed: 10/21/2022]
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Gimeno IM. Marek's disease vaccines: A solution for today but a worry for tomorrow? Vaccine 2008; 26 Suppl 3:C31-41. [DOI: 10.1016/j.vaccine.2008.04.009] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Mapping quantitative trait loci affecting susceptibility to Marek's disease virus in a backcross population of layer chickens. Genetics 2008; 177:2417-31. [PMID: 18073438 DOI: 10.1534/genetics.107.080002] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Marek's disease (MD), caused by the oncogenic MD avian herpes virus (MDV), is a major source of economic losses to the poultry industry. A reciprocal backcross (BC) population (total 2052 individuals) was generated by crossing two partially inbred commercial Leghorn layer lines known to differ in MDV resistance, measured as survival time after challenge with a (vv+) MDV. QTL affecting resistance were identified by selective DNA pooling using a panel of 198 microsatellite markers covering two-thirds of the chicken genome. Data for each BC were analyzed separately, and as a combined data set. Markers showing significant association with resistance generally appeared in blocks of two or three, separated by blocks of nonsignificant markers. Defined this way, 15 chromosomal regions (QTLR) affecting MDV resistance, distributed among 10 chromosomes (GGA 1, 2, 3, 4, 5, 7, 8, 9, 15, and Z), were identified. The identified QTLR include one gene and three QTL associated with resistance in previous studies of other lines, and three additional QTL associated with resistance in previous studies of the present lines. These QTL could be used in marker-assisted selection (MAS) programs for MDV resistance and as a platform for high-resolution mapping and positional cloning of the resistance genes.
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Mutations of Japanese Quail ( Coturnix japonica) and Recent Advances of Molecular Genetics for This Species. J Poult Sci 2008. [DOI: 10.2141/jpsa.45.159] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Cogburn LA, Porter TE, Duclos MJ, Simon J, Burgess SC, Zhu JJ, Cheng HH, Dodgson JB, Burnside J. Functional genomics of the chicken--a model organism. Poult Sci 2007; 86:2059-94. [PMID: 17878436 DOI: 10.1093/ps/86.10.2059] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Since the sequencing of the genome and the development of high-throughput tools for the exploration of functional elements of the genome, the chicken has reached model organism status. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scale. Systems biology attempts to integrate functional information derived from multiple high-content data sets into a holistic view of all biological processes within a cell or organism. Generation of a large collection ( approximately 600K) of chicken expressed sequence tags, representing most tissues and developmental stages, has enabled the construction of high-density microarrays for transcriptional profiling. Comprehensive analysis of this large expressed sequence tag collection and a set of approximately 20K full-length cDNA sequences indicate that the transcriptome of the chicken represents approximately 20,000 genes. Furthermore, comparative analyses of these sequences have facilitated functional annotation of the genome and the creation of several bioinformatic resources for the chicken. Recently, about 20 papers have been published on transcriptional profiling with DNA microarrays in chicken tissues under various conditions. Proteomics is another powerful high-throughput tool currently used for examining the dynamics of protein expression in chicken tissues and fluids. Computational analyses of the chicken genome are providing new insight into the evolution of gene families in birds and other organisms. Abundant functional genomic resources now support large-scale analyses in the chicken and will facilitate identification of transcriptional mechanisms, gene networks, and metabolic or regulatory pathways that will ultimately determine the phenotype of the bird. New technologies such as marker-assisted selection, transgenics, and RNA interference offer the opportunity to modify the phenotype of the chicken to fit defined production goals. This review focuses on functional genomics in the chicken and provides a road map for large-scale exploration of the chicken genome.
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Affiliation(s)
- L A Cogburn
- Department of Animal and Food Sciences, University of Delaware, Newark 19717, USA.
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de Koning DJ, Archibald A, Haley CS. Livestock genomics: bridging the gap between mice and men. Trends Biotechnol 2007; 25:483-9. [PMID: 17945371 DOI: 10.1016/j.tibtech.2007.07.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2007] [Revised: 07/25/2007] [Accepted: 07/31/2007] [Indexed: 10/22/2022]
Abstract
Dissecting the genetic control of variation in complex traits, such as disease resistance and agricultural-product quality, remains very challenging. Farm animals are now well placed to bridge the gap between human biology and traditional model species. Livestock species share with model species the benefits of controlled breeding, and their biology is often much closer to that of humans. Genetic research in model species focuses on differences between homogenous lines, whereas genetic research in humans focuses on genetic variation within populations. Livestock genetics has the strengths of both human and model-species genetics because researchers can exploit both the abundant genetic variation between divergent breeds and the variation that is segregating within breeds. Therefore, livestock genomics fills the void where the genetics of model species proves intractable or where model species are not a good proxy for human biology.
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Affiliation(s)
- Dirk-Jan de Koning
- Division of Genetics and Genomics, Roslin Institute, Roslin, Midlothian, EH25 9PS, UK.
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