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Sallam M, Wilson PW, Andersson B, Schmutz M, Benavides C, Dominguez-Gasca N, Sanchez-Rodriguez E, Rodriguez-Navarro AB, Dunn IC, De Koning DJ, Johnsson M. Genetic markers associated with bone composition in Rhode Island Red laying hens. Genet Sel Evol 2023; 55:44. [PMID: 37386416 DOI: 10.1186/s12711-023-00818-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 06/20/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND Bone damage has welfare and economic impacts on modern commercial poultry and is known as one of the major challenges in the poultry industry. Bone damage is particularly common in laying hens and is probably due to the physiological link between bone and the egg laying process. Previous studies identified and validated quantitative trait loci (QTL) for bone strength in White Leghorn laying hens based on several measurements, including bone composition measurements on the cortex and medulla of the tibia bone. In a previous pedigree-based analysis, bone composition measurements showed heritabilities ranging from 0.18 to 0.41 and moderate to strong genetic correlations with tibia strength and density. Bone composition was measured using infrared spectroscopy and thermogravimetry. The aim of this study was to combine these bone composition measurements with genotyping data via a genome-wide association study (GWAS) to investigate genetic markers that contribute to genetic variance in bone composition in Rhode Island Red laying hens. In addition, we investigated the genetic correlations between bone composition and bone strength. RESULTS We found novel genetic markers that are significantly associated with cortical lipid, cortical mineral scattering, medullary organic matter, and medullary mineralization. Composition of the bone organic matter showed more significant associations than bone mineral composition. We also found interesting overlaps between the GWAS results for tibia composition traits, particularly for cortical lipid and tibia strength. Bone composition measurements by infrared spectroscopy showed more significant associations than thermogravimetry measurements. Based on the results of infrared spectroscopy, cortical lipid showed the highest genetic correlations with tibia density, which was negative (- 0.20 ± 0.04), followed by cortical CO3/PO4 (0.18 ± 0.04). Based on the results of thermogravimetry, medullary organic matter% and mineral% showed the highest genetic correlations with tibia density (- 0.25 ± 0.04 and 0.25 ± 0.04, respectively). CONCLUSIONS This study detected novel genetic associations for bone composition traits, particularly those involving organic matter, that could be used as a basis for further molecular genetic investigations. Tibia cortical lipids displayed the strongest genetic associations of all the composition measurements, including a significantly high genetic correlation with tibia density and strength. Our results also highlighted that cortical lipid may be a key measurement for further avian bone studies.
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Affiliation(s)
- Moh Sallam
- Swedish University of Agricultural Sciences, 75651, Uppsala, Sweden.
| | - Peter W Wilson
- Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, Scotland, UK
| | | | | | - Cristina Benavides
- Departamento de Mineralogia y Petrologia, Universidad de Granada, 18002, Granada, Spain
| | | | | | | | - Ian C Dunn
- Roslin Institute, University of Edinburgh, Edinburgh, EH25 9RG, Scotland, UK
| | | | - Martin Johnsson
- Swedish University of Agricultural Sciences, 75651, Uppsala, Sweden
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Disentangling clustering configuration intricacies for divergently selected chicken breeds. Sci Rep 2023; 13:3319. [PMID: 36849504 PMCID: PMC9971033 DOI: 10.1038/s41598-023-28651-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/23/2023] [Indexed: 03/01/2023] Open
Abstract
Divergently selected chicken breeds are of great interest not only from an economic point of view, but also in terms of sustaining diversity of the global poultry gene pool. In this regard, it is essential to evaluate the classification (clustering) of varied chicken breeds using methods and models based on phenotypic and genotypic breed differences. It is also important to implement new mathematical indicators and approaches. Accordingly, we set the objectives to test and improve clustering algorithms and models to discriminate between various chicken breeds. A representative portion of the global chicken gene pool including 39 different breeds was examined in terms of an integral performance index, i.e., specific egg mass yield relative to body weight of females. The generated dataset was evaluated within the traditional, phenotypic and genotypic classification/clustering models using the k-means method, inflection points clustering, and admixture analysis. The latter embraced SNP genotype datasets including a specific one focused on the performance-associated NCAPG-LCORL locus. The k-means and inflection points analyses showed certain discrepancies between the tested models/submodels and flaws in the produced cluster configurations. On the other hand, 11 core breeds were identified that were shared between the examined models and demonstrated more adequate clustering and admixture patterns. These findings will lay the foundation for future research to improve methods for clustering as well as genome- and phenome-wide association/mediation analyses.
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Atilano SR, Abedi S, Ianopol NV, Singh MK, Norman JL, Malik D, Falatoonzadeh P, Chwa M, Nesburn AB, Kuppermann BD, Kenney MC. Differential Epigenetic Status and Responses to Stressors between Retinal Cybrids Cells with African versus European Mitochondrial DNA: Insights into Disease Susceptibilities. Cells 2022; 11:2655. [PMID: 36078063 PMCID: PMC9454894 DOI: 10.3390/cells11172655] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/19/2022] [Accepted: 08/23/2022] [Indexed: 11/16/2022] Open
Abstract
Mitochondrial (mt) DNA can be classified into haplogroups, which represent populations with different geographic origins. Individuals of maternal African backgrounds (L haplogroup) are more prone to develop specific diseases compared those with maternal European-H haplogroups. Using a cybrid model, effects of amyloid-β (Amyβ), sub-lethal ultraviolet (UV) radiation, and 5-Aza-2'-deoxycytidine (5-aza-dC), a methylation inhibitor, were investigated. Amyβ treatment decreased cell metabolism and increased levels of reactive oxygen species in European-H and African-L cybrids, but lower mitochondrial membrane potential (ΔΨM) was found only in African-L cybrids. Sub-lethal UV radiation induced higher expression levels of CFH, EFEMP1, BBC3, and BCL2L13 in European-H cybrids compared to African-L cybrids. With respect to epigenetic status, the African-L cybrids had (a) 4.7-fold higher total global methylation levels (p = 0.005); (b) lower expression patterns for DNMT3B; and (c) elevated levels for HIST1H3F. The European-H and African-L cybrids showed different transcription levels for CFH, EFEMP1, CXCL1, CXCL8, USP25, and VEGF after treatment with 5-aza-dC. In conclusion, compared to European-H haplogroup cybrids, the African-L cybrids have different (i) responses to exogenous stressors (Amyβ and UV radiation), (ii) epigenetic status, and (iii) modulation profiles of methylation-mediated downstream complement, inflammation, and angiogenesis genes, commonly associated with various human diseases.
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Affiliation(s)
- Shari R. Atilano
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Sina Abedi
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Narcisa V. Ianopol
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Mithalesh K. Singh
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - J Lucas Norman
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Deepika Malik
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Payam Falatoonzadeh
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Marilyn Chwa
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - Anthony B. Nesburn
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
- Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Baruch D. Kuppermann
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
| | - M. Cristina Kenney
- Gavin Herbert Eye Institute, Ophthalmology Research Laboratory, University of California Irvine, Hewitt Hall, Room 2028, 843 Health Science Rd., Irvine, CA 92697, USA
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, CA 92697, USA
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Li Y, Liu X, Bai X, Wang Y, Leng L, Zhang H, Li Y, Cao Z, Luan P, Xiao F, Gao H, Sun Y, Wang N, Li H, Wang S. Genetic parameters estimation and genome‐wide association studies for internal organ traits in an F
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chicken population. J Anim Breed Genet 2022; 139:434-446. [DOI: 10.1111/jbg.12674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/24/2022] [Accepted: 02/12/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Yudong Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Xin Liu
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Xue Bai
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Yuxiang Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Li Leng
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Hui Zhang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Yumao Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Zhiping Cao
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Peng Luan
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Fan Xiao
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Haihe Gao
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Yuhang Sun
- Fujian Sunnzer Biotechnology Development Co., Ltd Guangze P.R. China
| | - Ning Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding Ministry of Agriculture and Rural Affairs Harbin P.R. China
- Key Laboratory of Animal Genetics, Breeding and Reproduction Education Department of Heilongjiang Province Harbin P.R. China
- College of Animal Science and Technology Northeast Agricultural University Harbin P.R. China
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Moreira GCM, Salvian M, Boschiero C, Cesar ASM, Reecy JM, Godoy TF, Ledur MC, Garrick D, Mourão GB, Coutinho LL. Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens. BMC Genomics 2019; 20:669. [PMID: 31438838 PMCID: PMC6704653 DOI: 10.1186/s12864-019-6040-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 08/16/2019] [Indexed: 02/07/2023] Open
Abstract
Background Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs. Results Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes. Conclusions The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders. Electronic supplementary material The online version of this article (10.1186/s12864-019-6040-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Mayara Salvian
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Clarissa Boschiero
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Aline Silva Mello Cesar
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - James M Reecy
- Department of Animal Science, Iowa State University (ISU), Ames, Iowa, USA
| | - Thaís Fernanda Godoy
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Dorian Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
| | - Gerson Barreto Mourão
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Luiz L Coutinho
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil.
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