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Bai H, He Y, Ding Y, Chu Q, Lian L, Heifetz EM, Yang N, Cheng HH, Zhang H, Chen J, Song J. Genome-wide characterization of copy number variations in the host genome in genetic resistance to Marek's disease using next generation sequencing. BMC Genet 2020; 21:77. [PMID: 32677890 PMCID: PMC7364486 DOI: 10.1186/s12863-020-00884-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 07/05/2020] [Indexed: 11/13/2022] Open
Abstract
Background Marek’s disease (MD) is a highly neoplastic disease primarily affecting chickens, and remains as a chronic infectious disease that threatens the poultry industry. Copy number variation (CNV) has been examined in many species and is recognized as a major source of genetic variation that directly contributes to phenotypic variation such as resistance to infectious diseases. Two highly inbred chicken lines, 63 (MD-resistant) and 72 (MD-susceptible), as well as their F1 generation and six recombinant congenic strains (RCSs) with varied susceptibility to MD, are considered as ideal models to identify the complex mechanisms of genetic and molecular resistance to MD. Results In the present study, to unravel the potential genetic mechanisms underlying resistance to MD, we performed a genome-wide CNV detection using next generation sequencing on the inbred chicken lines with the assistance of CNVnator. As a result, a total of 1649 CNV regions (CNVRs) were successfully identified after merging all the nine datasets, of which 90 CNVRs were overlapped across all the chicken lines. Within these shared regions, 1360 harbored genes were identified. In addition, 55 and 44 CNVRs with 62 and 57 harbored genes were specifically identified in line 63 and 72, respectively. Bioinformatics analysis showed that the nearby genes were significantly enriched in 36 GO terms and 6 KEGG pathways including JAK/STAT signaling pathway. Ten CNVRs (nine deletions and one duplication) involved in 10 disease-related genes were selected for validation by using quantitative real-time PCR (qPCR), all of which were successfully confirmed. Finally, qPCR was also used to validate two deletion events in line 72 that were definitely normal in line 63. One high-confidence gene, IRF2 was identified as the most promising candidate gene underlying resistance and susceptibility to MD in view of its function and overlaps with data from previous study. Conclusions Our findings provide valuable insights for understanding the genetic mechanism of resistance to MD and the identified gene and pathway could be considered as the subject of further functional characterization.
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Affiliation(s)
- Hao Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Yangzhou, 225009, China.,Department of Animal & Avian Sciences, University of Maryland, College Park, MD, 20742, USA.,Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Yanghua He
- Department of Animal & Avian Sciences, University of Maryland, College Park, MD, 20742, USA.,Department of Human Nutrition, Food and Animal Sciences, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Yi Ding
- Department of Animal & Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Qin Chu
- Department of Animal & Avian Sciences, University of Maryland, College Park, MD, 20742, USA.,Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Ling Lian
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Eliyahu M Heifetz
- Faculty of Health Sciences, Jerusalem College of Technology, 9116001, Jerusalem, Israel
| | - Ning Yang
- Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hans H Cheng
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA
| | - Huanmin Zhang
- USDA, Agricultural Research Service, Avian Disease and Oncology Laboratory, East Lansing, MI, 48823, USA
| | - Jilan Chen
- Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jiuzhou Song
- Department of Animal & Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
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Khatri B, Kang S, Shouse S, Anthony N, Kuenzel W, Kong BC. Copy number variation study in Japanese quail associated with stress related traits using whole genome re-sequencing data. PLoS One 2019; 14:e0214543. [PMID: 30921419 PMCID: PMC6438477 DOI: 10.1371/journal.pone.0214543] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Accepted: 03/15/2019] [Indexed: 02/06/2023] Open
Abstract
Copy number variation (CNV) is a major driving factor for genetic variation and phenotypic diversity in animals. To detect CNVs and understand genetic components underlying stress related traits, we performed whole genome re-sequencing of pooled DNA samples of 20 birds each from High Stress (HS) and Low Stress (LS) Japanese quail lines using Illumina HiSeq 2×150 bp paired end method. Sequencing data were aligned to the quail genome and CNVnator was used to detect CNVs in the aligned data sets. The depth of coverage for the data reached to 41.4x and 42.6x for HS and LS birds, respectively. We identified 262 and 168 CNV regions affecting 1.6 and 1.9% of the reference genome that completely overlapped 454 and 493 unique genes in HS and LS birds, respectively. Ingenuity pathway analysis showed that the CNV genes were significantly enriched to phospholipase C signaling, neuregulin signaling, reelin signaling in neurons, endocrine and nervous development, humoral immune response, and carbohydrate and amino acid metabolisms in HS birds, whereas CNV genes in LS birds were enriched in cell-mediated immune response, and protein and lipid metabolisms. These findings suggest CNV genes identified in HS and LS birds could be candidate markers responsible for stress responses in birds.
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Affiliation(s)
- Bhuwan Khatri
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
| | - Seong Kang
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
| | - Stephanie Shouse
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
| | - Nicholas Anthony
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
| | - Wayne Kuenzel
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
| | - Byungwhi C. Kong
- Department of Poultry Science, Center of Excellence for Poultry Science, University of Arkansas, Fayetteville, AR, United States of America
- * E-mail:
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Bai H, Sun Y, Liu N, Liu Y, Xue F, Li Y, Xu S, Ni A, Ye J, Chen Y, Chen J. Genome-wide detection of CNVs associated with beak deformity in chickens using high-density 600K SNP arrays. Anim Genet 2018; 49:226-236. [PMID: 29642269 DOI: 10.1111/age.12652] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2018] [Indexed: 11/30/2022]
Abstract
Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing-You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome-wide CNV detection using Affymetrix chicken high-density 600K data on 48 deformed-beak and 48 normal birds using penncnv. As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed-beak and normal birds respectively. Further RT-qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed-beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed-beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT-qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.
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Affiliation(s)
- H Bai
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Y Sun
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - N Liu
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Y Liu
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - F Xue
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Y Li
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - S Xu
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - A Ni
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - J Ye
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Y Chen
- Beijing General Station of Animal Husbandry Service, Beijing, 102200, China
| | - J Chen
- Key Laboratory of Animal Genetics Breeding and Reproduction (Poultry), Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
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Rao YS, Li J, Zhang R, Lin XR, Xu JG, Xie L, Xu ZQ, Wang L, Gan JK, Xie XJ, He J, Zhang XQ. Copy number variation identification and analysis of the chicken genome using a 60K SNP BeadChip. Poult Sci 2016; 95:1750-6. [PMID: 27118864 DOI: 10.3382/ps/pew136] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/16/2016] [Indexed: 12/24/2022] Open
Abstract
Copy number variation (CNV) is an important source of genetic variation in organisms and a main factor that affects phenotypic variation. A comprehensive study of chicken CNV can provide valuable information on genetic diversity and facilitate future analyses of associations between CNV and economically important traits in chickens. In the present study, an F2 full-sib chicken population (554 individuals), established from a cross between Xinghua and White Recessive Rock chickens, was used to explore CNV in the chicken genome. Genotyping was performed using a chicken 60K SNP BeadChip. A total of 1,875 CNV were detected with the PennCNV algorithm, and the average number of CNV was 3.42 per individual. The CNV were distributed across 383 independent CNV regions (CNVR) and covered 41 megabases (3.97%) of the chicken genome. Seven CNVR in 108 individuals were validated by quantitative real-time PCR, and 81 of these individuals (75%) also were detected with the PennCNV algorithm. In total, 274 CNVR (71.54%) identified in the current study were previously reported. Of these, 147 (38.38%) were reported in at least 2 studies. Additionally, 109 of the CNVR (28.46%) discovered here are novel. A total of 709 genes within or overlapping with the CNVR was retrieved. Out of the 2,742 quantitative trait loci (QTL) collected in the chicken QTL database, 43 QTL had confidence intervals overlapping with the CNVR, and 32 CNVR encompassed one or more functional genes. The functional genes located in the CNVR are likely to be the QTG that are associated with underlying economic traits. This study considerably expands our insight into the structural variation in the genome of chickens and provides an important resource for genomic variation, especially for genomic structural variation related to economic traits in chickens.
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Affiliation(s)
- Y S Rao
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Biological Technology, Nanchang Normal University, Nanchang 330029, Jiangxi, China
| | - J Li
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - R Zhang
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - X R Lin
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - J G Xu
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China Department of Biological Technology, Nanchang Normal University, Nanchang 330029, Jiangxi, China
| | - L Xie
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China
| | - Z Q Xu
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - L Wang
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - J K Gan
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - X J Xie
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - J He
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
| | - X Q Zhang
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, Guangzhou 510642, Guangdong, China Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou 510642, Guangdong, China
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Reed KM, Mendoza KM, Settlage RE. Targeted capture enrichment and sequencing identifies extensive nucleotide variation in the turkey MHC-B. Immunogenetics 2016; 68:219-29. [DOI: 10.1007/s00251-015-0893-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Accepted: 12/16/2015] [Indexed: 02/08/2023]
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Schmid M, Smith J, Burt DW, Aken BL, Antin PB, Archibald AL, Ashwell C, Blackshear PJ, Boschiero C, Brown CT, Burgess SC, Cheng HH, Chow W, Coble DJ, Cooksey A, Crooijmans RPMA, Damas J, Davis RVN, de Koning DJ, Delany ME, Derrien T, Desta TT, Dunn IC, Dunn M, Ellegren H, Eöry L, Erb I, Farré M, Fasold M, Fleming D, Flicek P, Fowler KE, Frésard L, Froman DP, Garceau V, Gardner PP, Gheyas AA, Griffin DK, Groenen MAM, Haaf T, Hanotte O, Hart A, Häsler J, Hedges SB, Hertel J, Howe K, Hubbard A, Hume DA, Kaiser P, Kedra D, Kemp SJ, Klopp C, Kniel KE, Kuo R, Lagarrigue S, Lamont SJ, Larkin DM, Lawal RA, Markland SM, McCarthy F, McCormack HA, McPherson MC, Motegi A, Muljo SA, Münsterberg A, Nag R, Nanda I, Neuberger M, Nitsche A, Notredame C, Noyes H, O'Connor R, O'Hare EA, Oler AJ, Ommeh SC, Pais H, Persia M, Pitel F, Preeyanon L, Prieto Barja P, Pritchett EM, Rhoads DD, Robinson CM, Romanov MN, Rothschild M, Roux PF, Schmidt CJ, Schneider AS, Schwartz MG, Searle SM, Skinner MA, Smith CA, Stadler PF, Steeves TE, Steinlein C, Sun L, Takata M, Ulitsky I, Wang Q, Wang Y, Warren WC, Wood JMD, Wragg D, Zhou H. Third Report on Chicken Genes and Chromosomes 2015. Cytogenet Genome Res 2015; 145:78-179. [PMID: 26282327 PMCID: PMC5120589 DOI: 10.1159/000430927] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Michael Schmid
- Department of Human Genetics, University of Würzburg, Würzburg, Germany
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