1
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Chang WJ, Baker MS, Laritsky E, Gunasekara CJ, Maduranga U, Galliou JC, McFadden JW, Waltemyer JR, Berggren-Thomas B, Tate BN, Zhang H, Rosen BD, Van Tassell CP, Liu GE, Coarfa C, Ren YA, Waterland RA. Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans. Genome Biol 2024; 25:185. [PMID: 39004763 PMCID: PMC11247883 DOI: 10.1186/s13059-024-03307-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 06/13/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND We recently identified ~ 10,000 correlated regions of systemic interindividual epigenetic variation (CoRSIVs) in the human genome. These methylation variants are amenable to population studies, as DNA methylation measurements in blood provide information on epigenetic regulation throughout the body. Moreover, establishment of DNA methylation at human CoRSIVs is labile to periconceptional influences such as nutrition. Here, we analyze publicly available whole-genome bisulfite sequencing data on multiple tissues of each of two Holstein cows to determine whether CoRSIVs exist in cattle. RESULTS Focusing on genomic blocks with ≥ 5 CpGs and a systemic interindividual variation index of at least 20, our approach identifies 217 cattle CoRSIVs, a subset of which we independently validate by bisulfite pyrosequencing. Similar to human CoRSIVs, those in cattle are strongly associated with genetic variation. Also as in humans, we show that establishment of DNA methylation at cattle CoRSIVs is particularly sensitive to early embryonic environment, in the context of embryo culture during assisted reproduction. CONCLUSIONS Our data indicate that CoRSIVs exist in cattle, as in humans, suggesting these systemic epigenetic variants may be common to mammals in general. To the extent that individual epigenetic variation at cattle CoRSIVs affects phenotypic outcomes, assessment of CoRSIV methylation at birth may become an important tool for optimizing agriculturally important traits. Moreover, adjusting embryo culture conditions during assisted reproduction may provide opportunities to tailor agricultural outcomes by engineering CoRSIV methylation profiles.
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Affiliation(s)
- Wen-Jou Chang
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Maria S Baker
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Eleonora Laritsky
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Chathura J Gunasekara
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Uditha Maduranga
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Justine C Galliou
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Joseph W McFadden
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | | | | | - Brianna N Tate
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Hanxue Zhang
- Department of Animal Science, Cornell University, Ithaca, NY, United States
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD, United States
| | - Cristian Coarfa
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, United States
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States
| | - Yi Athena Ren
- Department of Animal Science, Cornell University, Ithaca, NY, United States.
| | - Robert A Waterland
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States.
- Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, United States.
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2
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Nair VD, Pincas H, Smith GR, Zaslavsky E, Ge Y, Amper MAS, Vasoya M, Chikina M, Sun Y, Raja AN, Mao W, Gay NR, Esser KA, Smith KS, Zhao B, Wiel L, Singh A, Lindholm ME, Amar D, Montgomery S, Snyder MP, Walsh MJ, Sealfon SC. Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures. CELL GENOMICS 2024; 4:100421. [PMID: 38697122 PMCID: PMC11228891 DOI: 10.1016/j.xgen.2023.100421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/07/2023] [Accepted: 09/12/2023] [Indexed: 05/04/2024]
Abstract
Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.
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Affiliation(s)
- Venugopalan D Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hanna Pincas
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gregory R Smith
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Anne S Amper
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mital Vasoya
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maria Chikina
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yifei Sun
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Weiguang Mao
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicole R Gay
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Karyn A Esser
- Department of Physiology and Aging, University of Florida, Gainesville, FL 32610, USA
| | - Kevin S Smith
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Bingqing Zhao
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Laurens Wiel
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Aditya Singh
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Malene E Lindholm
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - David Amar
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Stephen Montgomery
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Martin J Walsh
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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3
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Kuraz Abebe B, Wang J, Guo J, Wang H, Li A, Zan L. A review of the role of epigenetic studies for intramuscular fat deposition in beef cattle. Gene 2024; 908:148295. [PMID: 38387707 DOI: 10.1016/j.gene.2024.148295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/23/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
Intramuscular fat (IMF) deposition profoundly influences meat quality and economic value in beef cattle production. Meanwhile, contemporary developments in epigenetics have opened new outlooks for understanding the molecular basics of IMF regulation, and it has become a key area of research for world scholars. Therefore, the aim of this paper was to provide insight and synthesis into the intricate relationship between epigenetic mechanisms and IMF deposition in beef cattle. The methodology involves a thorough analysis of existing literature, including pertinent books, academic journals, and online resources, to provide a comprehensive overview of the role of epigenetic studies in IMF deposition in beef cattle. This review summarizes the contemporary studies in epigenetic mechanisms in IMF regulation, high-resolution epigenomic mapping, single-cell epigenomics, multi-omics integration, epigenome editing approaches, longitudinal studies in cattle growth, environmental epigenetics, machine learning in epigenetics, ethical and regulatory considerations, and translation to industry practices from perspectives of IMF deposition in beef cattle. Moreover, this paper highlights DNA methylation, histone modifications, acetylation, phosphorylation, ubiquitylation, non-coding RNAs, DNA hydroxymethylation, epigenetic readers, writers, and erasers, chromatin immunoprecipitation followed by sequencing, whole genome bisulfite sequencing, epigenome-wide association studies, and their profound impact on the expression of crucial genes governing adipogenesis and lipid metabolism. Nutrition and stress also have significant influences on epigenetic modifications and IMF deposition. The key findings underscore the pivotal role of epigenetic studies in understanding and enhancing IMF deposition in beef cattle, with implications for precision livestock farming and ethical livestock management. In conclusion, this review highlights the crucial significance of epigenetic pathways and environmental factors in affecting IMF deposition in beef cattle, providing insightful information for improving the economics and meat quality of cattle production.
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Affiliation(s)
- Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; Department of Animal Science, Werabe University, P.O. Box 46, Werabe, Ethiopia
| | - Jianfang Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Juntao Guo
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China; National Beef Cattle Improvement Center, Northwest A&F University, Yangling, Shaanxi 712100, People's Republic of China.
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4
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Wang M, Bissonnette N, Laterrière M, Dudemaine PL, Gagné D, Roy JP, Sirard MA, Ibeagha-Awemu EM. DNA methylation haplotype block signatures responding to Staphylococcus aureus subclinical mastitis and association with production and health traits. BMC Biol 2024; 22:65. [PMID: 38486242 PMCID: PMC10941392 DOI: 10.1186/s12915-024-01843-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 02/09/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND DNA methylation has been documented to play vital roles in diseases and biological processes. In bovine, little is known about the regulatory roles of DNA methylation alterations on production and health traits, including mastitis. RESULTS Here, we employed whole-genome DNA methylation sequencing to profile the DNA methylation patterns of milk somatic cells from sixteen cows with naturally occurring Staphylococcus aureus (S. aureus) subclinical mastitis and ten healthy control cows. We observed abundant DNA methylation alterations, including 3,356,456 differentially methylated cytosines and 153,783 differential methylation haplotype blocks (dMHBs). The DNA methylation in regulatory regions, including promoters, first exons and first introns, showed global significant negative correlations with gene expression status. We identified 6435 dMHBs located in the regulatory regions of differentially expressed genes and significantly correlated with their corresponding genes, revealing their potential effects on transcriptional activities. Genes harboring DNA methylation alterations were significantly enriched in multiple immune- and disease-related pathways, suggesting the involvement of DNA methylation in regulating host responses to S. aureus subclinical mastitis. In addition, we found nine discriminant signatures (differentiates cows with S. aureus subclinical mastitis from healthy cows) representing the majority of the DNA methylation variations related to S. aureus subclinical mastitis. Validation of seven dMHBs in 200 cows indicated significant associations with mammary gland health (SCC and SCS) and milk production performance (milk yield). CONCLUSIONS In conclusion, our findings revealed abundant DNA methylation alterations in milk somatic cells that may be involved in regulating mammary gland defense against S. aureus infection. Particularly noteworthy is the identification of seven dMHBs showing significant associations with mammary gland health, underscoring their potential as promising epigenetic biomarkers. Overall, our findings on DNA methylation alterations offer novel insights into the regulatory mechanisms of bovine subclinical mastitis, providing further avenues for the development of effective control measures.
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Affiliation(s)
- Mengqi Wang
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada
- Department of Animal Science, Laval University, Quebec, QC, Canada
| | - Nathalie Bissonnette
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada
| | - Mario Laterrière
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec, QC, Canada
| | - Pier-Luc Dudemaine
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada
| | - David Gagné
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec, QC, Canada
| | - Jean-Philippe Roy
- Department of Clinical Sciences, Université de Montréal, St-Hyacinthe, QC, Canada
| | | | - Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada.
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5
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Chen S, Liu S, Shi S, Yin H, Tang Y, Zhang J, Li W, Liu G, Qu K, Ding X, Wang Y, Liu J, Zhang S, Fang L, Yu Y. Cross-Species Comparative DNA Methylation Reveals Novel Insights into Complex Trait Genetics among Cattle, Sheep, and Goats. Mol Biol Evol 2024; 41:msae003. [PMID: 38266195 PMCID: PMC10834038 DOI: 10.1093/molbev/msae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 12/28/2023] [Accepted: 01/04/2024] [Indexed: 01/26/2024] Open
Abstract
The cross-species characterization of evolutionary changes in the functional genome can facilitate the translation of genetic findings across species and the interpretation of the evolutionary basis underlying complex phenotypes. Yet, this has not been fully explored between cattle, sheep, goats, and other mammals. Here, we systematically characterized the evolutionary dynamics of DNA methylation and gene expression in 3 somatic tissues (i.e. brain, liver, and skeletal muscle) and sperm across 7 mammalian species, including 3 ruminant livestock species (cattle, sheep, and goats), humans, pigs, mice, and dogs, by generating and integrating 160 DNA methylation and transcriptomic data sets. We demonstrate dynamic changes of DNA hypomethylated regions and hypermethylated regions in tissue-type manner across cattle, sheep, and goats. Specifically, based on the phylo-epigenetic model of DNA methylome, we identified a total of 25,074 hypomethylated region extension events specific to cattle, which participated in rewiring tissue-specific regulatory network. Furthermore, by integrating genome-wide association studies of 50 cattle traits, we provided novel insights into the genetic and evolutionary basis of complex phenotypes in cattle. Overall, our study provides a valuable resource for exploring the evolutionary dynamics of the functional genome and highlights the importance of cross-species characterization of multiomics data sets for the evolutionary interpretation of complex phenotypes in cattle livestock.
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Affiliation(s)
- Siqian Chen
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shuli Liu
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Shaolei Shi
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Hongwei Yin
- Agriculture Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Yongjie Tang
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jinning Zhang
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Wenlong Li
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Liu
- National Animal Husbandry Service, Beijing 100125, China
| | - Kaixing Qu
- Academy of Science and Technology, Chuxiong Normal University, Chuxiong 675000, China
| | - Xiangdong Ding
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yachun Wang
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jianfeng Liu
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shengli Zhang
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics (QGG), Aarhus University, Aarhus, Denmark
| | - Ying Yu
- National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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6
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Liu Y, Han B, Zheng W, Peng P, Yang C, Jiang G, Ma Y, Li J, Ni J, Sun D. Identification of genetic associations and functional SNPs of bovine KLF6 gene on milk production traits in Chinese holstein. BMC Genom Data 2023; 24:72. [PMID: 38017423 PMCID: PMC10685595 DOI: 10.1186/s12863-023-01175-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/13/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Our previous research identified the Kruppel like factor 6 (KLF6) gene as a prospective candidate for milk production traits in dairy cattle. The expression of KLF6 in the livers of Holstein cows during the peak of lactation was significantly higher than that during the dry and early lactation periods. Notably, it plays an essential role in activating peroxisome proliferator-activated receptor α (PPARα) signaling pathways. The primary aim of this study was to further substantiate whether the KLF6 gene has significant genetic effects on milk traits in dairy cattle. RESULTS Through direct sequencing of PCR products with pooled DNA, we totally identified 12 single nucleotide polymorphisms (SNPs) within the KLF6 gene. The set of SNPs encompasses 7 located in 5' flanking region, 2 located in exon 2 and 3 located in 3' untranslated region (UTR). Of these, the g.44601035G > A is a missense mutation that resulting in the replacement of arginine (CGG) with glutamine (CAG), consequently leading to alterations in the secondary structure of the KLF6 protein, as predicted by SOPMA. The remaining 7 regulatory SNPs significantly impacted the transcriptional activity of KLF6 following mutation (P < 0.005), manifesting as changes in transcription factor binding sites. Additionally, 4 SNPs located in both the UTR and exons were predicted to influence the secondary structure of KLF6 mRNA using the RNAfold web server. Furthermore, we performed the genotype-phenotype association analysis using SAS 9.2 which found all the 12 SNPs were significantly correlated to milk yield, fat yield, fat percentage, protein yield and protein percentage within both the first and second lactations (P < 0.0001 ~ 0.0441). Also, with Haploview 4.2 software, we found the 12 SNPs linked closely and formed a haplotype block, which was strongly associated with five milk traits (P < 0.0001 ~ 0.0203). CONCLUSIONS In summary, our study represented the KLF6 gene has significant impacts on milk yield and composition traits in dairy cattle. Among the identified SNPs, 7 were implicated in modulating milk traits by impacting transcriptional activity, 4 by altering mRNA secondary structure, and 1 by affecting the protein secondary structure of KLF6. These findings provided valuable molecular insights for genomic selection program of dairy cattle.
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Affiliation(s)
- Yanan Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Bo Han
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Weijie Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Peng Peng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China
| | - Chendong Yang
- Hebei Province Animal Husbandry and Fine Breeds Work Station, No. 7 Xuefu Road, Changan District, Shijiazhuang, 050000, China
| | - Guie Jiang
- Hebei Province Animal Husbandry and Fine Breeds Work Station, No. 7 Xuefu Road, Changan District, Shijiazhuang, 050000, China
| | - Yabin Ma
- Hebei Province Animal Husbandry and Fine Breeds Work Station, No. 7 Xuefu Road, Changan District, Shijiazhuang, 050000, China
| | - Jianming Li
- Hebei Province Animal Husbandry and Fine Breeds Work Station, No. 7 Xuefu Road, Changan District, Shijiazhuang, 050000, China
| | - Junqing Ni
- Hebei Province Animal Husbandry and Fine Breeds Work Station, No. 7 Xuefu Road, Changan District, Shijiazhuang, 050000, China.
| | - Dongxiao Sun
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.
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7
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Hu Z, Boschiero C, Li CJ, Connor EE, Baldwin RL, Liu GE. Unraveling the Genetic Basis of Feed Efficiency in Cattle through Integrated DNA Methylation and CattleGTEx Analysis. Genes (Basel) 2023; 14:2121. [PMID: 38136943 PMCID: PMC10742843 DOI: 10.3390/genes14122121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023] Open
Abstract
Feed costs can amount to 75 percent of the total overhead cost of raising cows for milk production. Meanwhile, the livestock industry is considered a significant contributor to global climate change due to the production of greenhouse gas emissions, such as methane. Indeed, the genetic basis of feed efficiency (FE) is of great interest to the animal research community. Here, we explore the epigenetic basis of FE to provide base knowledge for the development of genomic tools to improve FE in cattle. The methylation level of 37,554 CpG sites was quantified using a mammalian methylation array (HorvathMammalMethylChip40) for 48 Holstein cows with extreme residual feed intake (RFI). We identified 421 CpG sites related to 287 genes that were associated with RFI, several of which were previously associated with feeding or digestion issues. Activator of transcription and developmental regulation (AUTS2) is associated with digestive disorders in humans, while glycerol-3-phosphate dehydrogenase 2 (GPD2) encodes a protein on the inner mitochondrial membrane, which can regulate glucose utilization and fatty acid and triglyceride synthesis. The extensive expression and co-expression of these genes across diverse tissues indicate the complex regulation of FE in cattle. Our study provides insight into the epigenetic basis of RFI and gene targets to improve FE in dairy cattle.
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Affiliation(s)
- Zhenbin Hu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - Erin E. Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716, USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA
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8
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Zhang J, Sheng H, Hu C, Li F, Cai B, Ma Y, Wang Y, Ma Y. Effects of DNA Methylation on Gene Expression and Phenotypic Traits in Cattle: A Review. Int J Mol Sci 2023; 24:11882. [PMID: 37569258 PMCID: PMC10419045 DOI: 10.3390/ijms241511882] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 07/20/2023] [Accepted: 07/22/2023] [Indexed: 08/13/2023] Open
Abstract
Gene expression in cells is determined by the epigenetic state of chromatin. Therefore, the study of epigenetic changes is very important to understand the regulatory mechanism of genes at the molecular, cellular, tissue and organ levels. DNA methylation is one of the most studied epigenetic modifications, which plays an important role in maintaining genome stability and ensuring normal growth and development. Studies have shown that methylation levels in bovine primordial germ cells, the rearrangement of methylation during embryonic development and abnormal methylation during placental development are all closely related to their reproductive processes. In addition, the application of bovine male sterility and assisted reproductive technology is also related to DNA methylation. This review introduces the principle, development of detection methods and application conditions of DNA methylation, with emphasis on the relationship between DNA methylation dynamics and bovine spermatogenesis, embryonic development, disease resistance and muscle and fat development, in order to provide theoretical basis for the application of DNA methylation in cattle breeding in the future.
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Affiliation(s)
- Junxing Zhang
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Hui Sheng
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
| | - Chunli Hu
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
| | - Fen Li
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
| | - Bei Cai
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
| | - Yanfen Ma
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
| | - Yachun Wang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular Cell Breeding of Ningxia Hui Autonomous Region, College of Animal Science and Technology, Ningxia University, Yinchuan 750021, China; (J.Z.); (H.S.); (C.H.); (F.L.); (B.C.); (Y.M.)
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9
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Wang M, Bissonnette N, Laterrière M, Gagné D, Dudemaine PL, Roy JP, Sirard MA, Ibeagha-Awemu EM. Genome-Wide DNA Methylation and Transcriptome Integration Associates DNA Methylation Changes with Bovine Subclinical Mastitis Caused by Staphylococcus chromogenes. Int J Mol Sci 2023; 24:10369. [PMID: 37373515 DOI: 10.3390/ijms241210369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023] Open
Abstract
Staphylococcus chromogenes (SC) is a common coagulase-negative staphylococcus described as an emerging mastitis pathogen and commonly found in dairy farms. This study investigated the potential involvement of DNA methylation in subclinical mastitis caused by SC. The whole-genome DNA methylation patterns and transcriptome profiles of milk somatic cells from four cows with naturally occurring SC subclinical mastitis (SCM) and four healthy cows were characterized by next-generation sequencing, bioinformatics, and integration analyses. Comparisons revealed abundant DNA methylation changes related to SCM, including differentially methylated cytosine sites (DMCs, n = 2,163,976), regions (DMRs, n = 58,965), and methylation haplotype blocks (dMHBs, n = 53,098). Integration of methylome and transcriptome data indicated a negative global association between DNA methylation at regulatory regions (promoters, first exons, and first introns) and gene expression. A total of 1486 genes with significant changes in the methylation levels of their regulatory regions and corresponding gene expression showed significant enrichment in biological processes and pathways related to immune functions. Sixteen dMHBs were identified as candidate discriminant signatures, and validation of two signatures in more samples further revealed the association of dMHBs with mammary gland health and production. This study demonstrated abundant DNA methylation changes with possible involvement in regulating host responses and potential as biomarkers for SCM.
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Affiliation(s)
- Mengqi Wang
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada
- Department of Animal Science, Université Laval, Québec, QC G1V 0A6, Canada
| | - Nathalie Bissonnette
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada
| | - Mario Laterrière
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec, QC G1V 2J3, Canada
| | - David Gagné
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec, QC G1V 2J3, Canada
| | - Pier-Luc Dudemaine
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada
| | - Jean-Philippe Roy
- Department of Clinical Sciences, Université de Montréal, Saint-Hyacinthe, QC H3T 1J4, Canada
| | - Marc-André Sirard
- Department of Animal Science, Université Laval, Québec, QC G1V 0A6, Canada
| | - Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada
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10
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Zhuo X, Hsu S, Purushotham D, Kuntala PK, Harrison JK, Du AY, Chen S, Li D, Wang T. Comparing genomic and epigenomic features across species using the WashU Comparative Epigenome Browser. Genome Res 2023; 33:824-835. [PMID: 37156621 PMCID: PMC10317122 DOI: 10.1101/gr.277550.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 05/03/2023] [Indexed: 05/10/2023]
Abstract
Genome browsers have become an intuitive and critical tool to visualize and analyze genomic features and data. Conventional genome browsers display data/annotations on a single reference genome/assembly; there are also genomic alignment viewer/browsers that help users visualize alignment, mismatch, and rearrangement between syntenic regions. However, there is a growing need for a comparative epigenome browser that can display genomic and epigenomic data sets across different species and enable users to compare them between syntenic regions. Here, we present the WashU Comparative Epigenome Browser. It allows users to load functional genomic data sets/annotations mapped to different genomes and display them over syntenic regions simultaneously. The browser also displays genetic differences between the genomes from single-nucleotide variants (SNVs) to structural variants (SVs) to visualize the association between epigenomic differences and genetic differences. Instead of anchoring all data sets to the reference genome coordinates, it creates independent coordinates of different genome assemblies to faithfully present features and data mapped to different genomes. It uses a simple, intuitive genome-align track to illustrate the syntenic relationship between different species. It extends the widely used WashU Epigenome Browser infrastructure and can be expanded to support multiple species. This new browser function will greatly facilitate comparative genomic/epigenomic research, as well as support the recent growing needs to directly compare and benchmark the T2T CHM13 assembly and other human genome assemblies.
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Affiliation(s)
- Xiaoyu Zhuo
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Silas Hsu
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Deepak Purushotham
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Prashant Kumar Kuntala
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Jessica K Harrison
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Alan Y Du
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Samuel Chen
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Daofeng Li
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA;
- The Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri 63110, USA
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11
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Shen S, Chen J, Li H, Jiang Y, Wei Y, Zhang R, Zhao Y, Chen F. Large-scale integration of the non-coding RNAs with DNA methylation in human cancers. Cell Rep 2023; 42:112261. [PMID: 36924495 DOI: 10.1016/j.celrep.2023.112261] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/24/2023] [Accepted: 02/27/2023] [Indexed: 03/17/2023] Open
Abstract
Characterizing influences of DNA methylation (DNAm) on non-coding RNAs (ncRNAs) is important to understand the mechanisms of gene regulation and cancer outcome. In our study, we describe the results of ncRNA quantitative trait methylation sites (ncQTM) analyses on 8,545 samples from The Cancer Genome Atlas (TCGA), 763 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and 516 samples from Genotype-Tissue Expression (GTEx) to identify the significant associations between DNAm sites and ncRNAs (miRNA, long non-coding RNA [lncRNA], small nuclear RNA [snRNA], small nucleolar RNA [snoRNA], and rRNA) across 32 cancer types. With more than 22 billion tests, we identify 302,764 cis-ncQTMs (6.28% of all tested) and 79,841,728 trans-ncQTMs (1.15% of all tested). Most DNAm sites (70.6% on average) are in trans association, while only 25.2% DNAm sites are in cis association. Further, we develop a subtype named ncmcluster based on cancer-specific ncRNAs thatis associated with tumor microenvironment, clinical outcome, and biological pathways. To comprehensively describe the ncQTM patterns, we developed a database named Pancan-ncQTM (http://bigdata.njmu.edu.cn/Pancan-ncQTM/).
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Affiliation(s)
- Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
| | - Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Hongru Li
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yunke Jiang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Biomedical Big Data of Nanjing Medical University, Nanjing 211166, China.
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
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12
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Liu L, Zhang Y, Ma H, Cao H, Liu W. Integrating genome-wide methylation and transcriptome-wide analyses to reveal the genetic mechanism of milk traits in Kazakh horses. Gene 2023; 856:147143. [PMID: 36574934 DOI: 10.1016/j.gene.2022.147143] [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: 07/28/2022] [Revised: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022]
Abstract
Horse Milk has important quantitative characteristics and high economic value. However, the DNA methylation regulators involved in horse milk traits have not been clarified. To explore the important role of genome-wide DNA methylation in regulating equine milk yield, this study systematically investigated the genome-wide DNA methylation profiles of Kazakh horse blood by comparing a high-production group (HP, average daily milk yield of 7.5 kg) and low-production group (LP, average daily milk yield of 3.2 kg) using deep whole-genome bisulfite sequencing. First, both groups showed similar proportions of methylation at CpG sites. Subsequently, we identified 26,677 differential methylated regions (DMRs) of CG, 15 DMRs of CHG, 480 DMRs of CHH and 8268 DMR-related genes (DMGs). GO and KEGG analyses revealed that some DMGs were involved in regulating milk and milk component formation. By combining the WGBS-seq and the previous RNA-seq data, a total of 94 overlapping genes were obtained. Finally, we found that 9 DMGs are likely involved in milk production by Kazakh horses.
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Affiliation(s)
- Lingling Liu
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Yunting Zhang
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Haiyu Ma
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Hang Cao
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
| | - Wujun Liu
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
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13
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Klughammer J, Romanovskaia D, Nemc A, Posautz A, Seid CA, Schuster LC, Keinath MC, Lugo Ramos JS, Kosack L, Evankow A, Printz D, Kirchberger S, Ergüner B, Datlinger P, Fortelny N, Schmidl C, Farlik M, Skjærven K, Bergthaler A, Liedvogel M, Thaller D, Burger PA, Hermann M, Distel M, Distel DL, Kübber-Heiss A, Bock C. Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species. Nat Commun 2023; 14:232. [PMID: 36646694 PMCID: PMC9842680 DOI: 10.1038/s41467-022-34828-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 11/08/2022] [Indexed: 01/18/2023] Open
Abstract
Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.
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Affiliation(s)
- Johanna Klughammer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Gene Center and Department of Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany.
| | - Daria Romanovskaia
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Amelie Nemc
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Annika Posautz
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Charlotte A Seid
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Linda C Schuster
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Juan Sebastian Lugo Ramos
- Max Planck Research Group Behavioral Genomics, Max Planck Institute for Evolutionary Biology, Plön, Germany
| | - Lindsay Kosack
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Ann Evankow
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Dieter Printz
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Stefanie Kirchberger
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Bekir Ergüner
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Paul Datlinger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Nikolaus Fortelny
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Christian Schmidl
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Matthias Farlik
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Andreas Bergthaler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,Medical University of Vienna, Center for Pathophysiology Infectiology and Immunology, Institute of Hygiene and Applied Immunology, Vienna, Austria
| | - Miriam Liedvogel
- Max Planck Research Group Behavioral Genomics, Max Planck Institute for Evolutionary Biology, Plön, Germany.,Institute of Avian Research, An der Vogelwarte, Wilhelmshaven, Germany
| | - Denise Thaller
- Department for Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Pamela A Burger
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Marcela Hermann
- Medical University of Vienna, Department of Medical Biochemistry, Vienna, Austria
| | - Martin Distel
- Children's Cancer Research Institute, St. Anna Kinderkrebsforschung, Vienna, Austria
| | - Daniel L Distel
- Ocean Genome Legacy Center, Northeastern University Marine Science Center, Nahant, USA
| | - Anna Kübber-Heiss
- Research Institute of Wildlife Ecology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria. .,Medical University of Vienna, Institute of Artificial Intelligence, Center for Medical Data Science, Vienna, Austria.
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14
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Chen S, Liu S, Shi S, Jiang Y, Cao M, Tang Y, Li W, Liu J, Fang L, Yu Y, Zhang S. Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits. BMC Biol 2022; 20:273. [PMID: 36482458 PMCID: PMC9730597 DOI: 10.1186/s12915-022-01459-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/07/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Insights into the genetic basis of complex traits and disease in both human and livestock species have been achieved over the past decade through detection of genetic variants in genome-wide association studies (GWAS). A majority of such variants were found located in noncoding genomic regions, and though the involvement of numerous regulatory elements (REs) has been predicted across multiple tissues in domesticated animals, their evolutionary conservation and effects on complex traits have not been fully elucidated, particularly in ruminants. Here, we systematically analyzed 137 epigenomic and transcriptomic datasets of six mammals, including cattle, sheep, goats, pigs, mice, and humans, and then integrated them with large-scale GWAS of complex traits. RESULTS Using 40 ChIP-seq datasets of H3K4me3 and H3K27ac, we detected 68,479, 58,562, 63,273, 97,244, 111,881, and 87,049 REs in the liver of cattle, sheep, goats, pigs, humans and mice, respectively. We then systematically characterized the dynamic functional landscapes of these REs by integrating multi-omics datasets, including gene expression, chromatin accessibility, and DNA methylation. We identified a core set (n = 6359) of ruminant-specific REs that are involved in liver development, metabolism, and immune processes. Genes with more complex cis-REs exhibited higher gene expression levels and stronger conservation across species. Furthermore, we integrated expression quantitative trait loci (eQTLs) and GWAS from 44 and 52 complex traits/diseases in cattle and humans, respectively. These results demonstrated that REs with different degrees of evolutionary conservation across species exhibited distinct enrichments for GWAS signals of complex traits. CONCLUSIONS We systematically annotated genome-wide functional REs in liver across six mammals and demonstrated the evolution of REs and their associations with transcriptional output and conservation. Detecting lineage-specific REs allows us to decipher the evolutionary and genetic basis of complex phenotypes in livestock and humans, which may benefit the discovery of potential biomedical models for functional variants and genes of specific human diseases.
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Affiliation(s)
- Siqian Chen
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shuli Liu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China ,grid.494629.40000 0004 8008 9315 School of Life Sciences, Westlake University, Hangzhou, China
| | - Shaolei Shi
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yifan Jiang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Mingyue Cao
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yongjie Tang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wenlong Li
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jianfeng Liu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lingzhao Fang
- grid.4305.20000 0004 1936 7988MRC Human Genetics Unit at the Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK ,grid.7048.b0000 0001 1956 2722Center for Quantitative Genetics and Genomics (QGG), Aarhus University, Aarhus, Denmark
| | - Ying Yu
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shengli Zhang
- grid.22935.3f0000 0004 0530 8290Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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15
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Zhou Y, Yang L, Han X, Han J, Hu Y, Li F, Xia H, Peng L, Boschiero C, Rosen BD, Bickhart DM, Zhang S, Guo A, Van Tassell CP, Smith TPL, Yang L, Liu GE. Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history. Genome Res 2022; 32:gr.276550.122. [PMID: 35977842 PMCID: PMC9435747 DOI: 10.1101/gr.276550.122] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 07/21/2022] [Indexed: 02/03/2023]
Abstract
A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lv Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaotao Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Jiazheng Han
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Fan Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Lingwei Peng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Clarissa Boschiero
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Derek M Bickhart
- Dairy Forage Research Center, ARS USDA, Madison, Wisconsin 53706, USA
| | - Shujun Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - Aizhen Guo
- The State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Timothy P L Smith
- U.S. Meat Animal Research Center, ARS USDA, Clay Center, Nebraska 68933, USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland 20705, USA
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16
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Kelly CJ, Chitko-McKown CG, Chuong EB. Ruminant-specific retrotransposons shape regulatory evolution of bovine immunity. Genome Res 2022; 32:gr.276241.121. [PMID: 35948370 PMCID: PMC9435751 DOI: 10.1101/gr.276241.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 05/05/2022] [Indexed: 02/03/2023]
Abstract
Cattle are an important livestock species, and mapping the genomic architecture of agriculturally relevant traits such as disease susceptibility is a major challenge in the bovine research community. Lineage-specific transposable elements (TEs) are increasingly recognized to contribute to gene regulatory evolution and variation, but this possibility has been largely unexplored in ruminant genomes. We conducted epigenomic profiling of the type II interferon (IFN) response in bovine cells and found thousands of ruminant-specific TEs including MER41_BT and Bov-A2 elements predicted to act as IFN-inducible enhancer elements. CRISPR knockout experiments in bovine cells established that critical immune factors including IFNAR2 and IL2RB are transcriptionally regulated by TE-derived enhancers. Finally, population genomic analysis of 38 individuals revealed that a subset of polymorphic TE insertions may function as enhancers in modern cattle. Our study reveals that lineage-specific TEs have shaped the evolution of ruminant IFN responses and potentially continue to contribute to immune gene regulatory differences across modern breeds and individuals. Together with previous work in human cells, our findings demonstrate that lineage-specific TEs have been independently co-opted to regulate IFN-inducible gene expression in multiple species, supporting TE co-option as a recurrent mechanism driving the evolution of IFN-inducible transcriptional networks.
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Affiliation(s)
- Conor J Kelly
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Carol G Chitko-McKown
- USDA, ARS, Roman L. Hruska US Meat Animal Research Center (MARC), Clay Center, Nebraska 68933, USA
| | - Edward B Chuong
- Department of Molecular, Cellular, and Developmental Biology and BioFrontiers Institute, University of Colorado Boulder, Boulder, Colorado 80309, USA
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17
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Solodneva EV, Kuznetsov SB, Velieva AE, Stolpovsky YA. Molecular-Genetic Bases of Mammary Gland Development Using the Example of Cattle and Other Animal Species: I. Embryonic and Pubertal Developmental Stage. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422080087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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18
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Gong W, Pan X, Xu D, Ji G, Wang Y, Tian Y, Cai J, Li J, Zhang Z, Yuan X. Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals. Comput Struct Biotechnol J 2022; 20:4704-4716. [PMID: 36147684 PMCID: PMC9465269 DOI: 10.1016/j.csbj.2022.08.051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 08/22/2022] [Accepted: 08/22/2022] [Indexed: 01/10/2023] Open
Abstract
Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.
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Affiliation(s)
- Wentao Gong
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Xiangchun Pan
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Dantong Xu
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Guanyu Ji
- Shenzhen Gendo Health Technology CO,. Ltd, Shenzhen 518122, China
| | - Yifei Wang
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Yuhan Tian
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Jiali Cai
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Jiaqi Li
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
| | - Zhe Zhang
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
- Corresponding authors.
| | - Xiaolong Yuan
- Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
- Corresponding authors.
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19
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Dodlapati S, Jiang Z, Sun J. Completing Single-Cell DNA Methylome Profiles via Transfer Learning Together With KL-Divergence. Front Genet 2022; 13:910439. [PMID: 35938031 PMCID: PMC9353187 DOI: 10.3389/fgene.2022.910439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/25/2022] [Indexed: 11/13/2022] Open
Abstract
The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with very low coverage (below 2%). Transfer learning was used to leverage less sparse profiles that are typically available for different tissues for the same species, while KL divergence was employed to maximize the usage of information carried in the input data. A deep neural network was adopted to extract both DNA sequence and local methylation patterns for imputation. Our study of training models for completing methylome profiles of bovine oocytes and early embryos demonstrates the effectiveness of transfer learning and KL divergence, with individual increase of 29.98 and 29.43%, respectively, in prediction performance and 38.70% increase when the two were used together. The drastically increased data coverage (43.80-73.6%) after imputation powers downstream analyses involving methylomes that cannot be effectively done using the very low coverage profiles (0.06-1.47%) before imputation.
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Affiliation(s)
- Sanjeeva Dodlapati
- Department of Computer Science, Old Dominion University, Norfolk, VA, United States
| | - Zongliang Jiang
- School of Animal Sciences, AgCenter, Louisiana State University, Baton Rouge, LA, United States
| | - Jiangwen Sun
- Department of Computer Science, Old Dominion University, Norfolk, VA, United States
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20
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Li P, Chen J, Zhu C, Pan Z, Li Q, Wei H, Wang G, Cheng W, Fu B, Sun Y. DNA Methylation Difference between Female and Male Ussuri Catfish ( Pseudobagrus ussuriensis) in Brain and Gonad Tissues. LIFE (BASEL, SWITZERLAND) 2022; 12:life12060874. [PMID: 35743904 PMCID: PMC9228513 DOI: 10.3390/life12060874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/29/2022] [Accepted: 06/01/2022] [Indexed: 11/27/2022]
Abstract
DNA methylation has been found to be involved in sex determination and differentiation in many aquaculture species. The Ussuri catfish (Pseudobagrus ussuriensis) is a popular aquaculture fish in China with high economic value in which male-biased sex dimorphism was observed in terms of body size and body weight. In this study, DNA methylation-sensitive RAD sequencing (Methyl-RAD) was used to explore the epigenetic difference between adult male and female samples in brain and gonad tissues. In brain tissues, 5,442,496 methylated cytosine sites were found and 9.94% of these sites were from symmetric CCGG or CCWGG sites. Among these sites, 321 differential DNA methylation sites (DMSs) in 171 genes were identified, while in gonad tissues, 4,043,053 methylated cytosines sites were found in total and 11.70% of them were from CCGG or CCWGG. Among these sites, 78 differential DNA methylation sites were found which were located in 64 genes. We also found several sex-determination genes among these differential methylated genes, such as amh, gsdf and hsd11b2 in brain tissues and slco3a1, socs2 and trim47 in gonad tissues. These results provided evidence for understanding the function of DNA methylation in the sex differentiation in Pseudobagrus ussuriensis, which further deepens the relationship between gene regulation and epigenetics.
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Affiliation(s)
- Pei Li
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Jian Chen
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Chuankun Zhu
- Jiangsu Key Laboratory for Eco-Agriculture Biotechnology around Hongze Lake, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Jiangsu Engineering Laboratory for Breeding of Special Aquatic Organisms, Huaiyin Normal University, Huaian 223300, China; (C.Z.); (Z.P.)
| | - Zhengjun Pan
- Jiangsu Key Laboratory for Eco-Agriculture Biotechnology around Hongze Lake, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Jiangsu Engineering Laboratory for Breeding of Special Aquatic Organisms, Huaiyin Normal University, Huaian 223300, China; (C.Z.); (Z.P.)
| | - Qing Li
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Huijie Wei
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Guiying Wang
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Weiwei Cheng
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
| | - Beide Fu
- Ruibiao (Wuhan) Biotechnology Co., Ltd., Wuhan 430074, China;
| | - Yanhong Sun
- Fisheries Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430207, China; (P.L.); (J.C.); (Q.L.); (H.W.); wh (G.W.); (W.C.)
- Correspondence:
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21
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Ma L, Chen W, Li S, Qin M, Zeng Y. Identification and functional prediction of long non-coding RNAs related to skeletal muscle development in Duroc pigs. Anim Biosci 2022; 35:1512-1523. [PMID: 35507853 PMCID: PMC9449383 DOI: 10.5713/ab.22.0020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 03/23/2022] [Indexed: 12/04/2022] Open
Abstract
Objective The growth of pigs involves multiple regulatory mechanisms, and modern molecular breeding techniques can be used to understand the skeletal muscle growth and development to promote the selection process of pigs. This study aims to explore candidate lncRNAs and mRNAs related to skeletal muscle growth and development among Duroc pigs with different average daily gain (ADG). Methods A total of 8 pigs were selected and divided into two groups: H group (high-ADG) and L group (low-ADG). And followed by whole transcriptome sequencing to identify differentially expressed (DE) lncRNAs and mRNAs. Results In RNA-seq, 703 DE mRNAs (263 up-regulated and 440 down-regulated) and 74 DE lncRNAs (45 up-regulated and 29 down-regulated) were identified. In addition, 1,418 Transcription factors (TFs) were found. Compared with mRNAs, lncRNAs had fewer exons, shorter transcript length and open reading frame length. DE mRNAs and DE lncRNAs can form 417 lncRNA-mRNA pairs (antisense, cis and trans). DE mRNAs and target genes of lncRNAs were enriched in cellular processes, biological regulation, and regulation of biological processes. In addition, quantitative trait locus (QTL) analysis was used to detect the functions of DE mRNAs and lncRNAs, the most of DE mRNAs and target genes of lncRNAs were enriched in QTLs related to growth traits and skeletal muscle development. In single-nucleotide polymorphism/insertion-deletion (SNP/INDEL) analysis, 1,081,182 SNP and 131,721 INDEL were found, and transition was more than transversion. Over 60% of percentage were skipped exon events among alternative splicing events. Conclusion The results showed that different ADG among Duroc pigs with the same diet maybe due to the DE mRNAs and DE lncRNAs related to skeletal muscle growth and development.
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22
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Goldkamp AK, Li Y, Rivera RM, Hagen DE. Characterization of tRNA expression profiles in large offspring syndrome. BMC Genomics 2022; 23:273. [PMID: 35392796 PMCID: PMC8988405 DOI: 10.1186/s12864-022-08496-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 03/23/2022] [Indexed: 11/10/2022] Open
Abstract
Background Assisted Reproductive Technologies (ART) use can increase the risk of congenital overgrowth syndromes, such as large offspring syndrome (LOS) in ruminants. Epigenetic variations are known to influence gene expression and differentially methylated regions (DMRs) were previously determined to be associated with LOS in cattle. We observed DMRs overlapping tRNA clusters which could affect tRNA abundance and be associated with tissue specificity or overgrowth. Variations in tRNA expression have been identified in several disease pathways suggesting an important role in the regulation of biological processes. Understanding the role of tRNA expression in cattle offers an opportunity to reveal mechanisms of regulation at the translational level. We analyzed tRNA expression in the skeletal muscle and liver tissues of day 105 artificial insemination-conceived, ART-conceived with a normal body weight, and ART-conceived bovine fetuses with a body weight above the 97th percentile compared to Control-AI. Results Despite the centrality of tRNAs to translation, in silico predictions have revealed dramatic differences in the number of tRNA genes between humans and cattle (597 vs 1,659). Consistent with reports in human, only a fraction of predicted tRNA genes are expressed. We detected the expression of 474 and 487 bovine tRNA genes in the muscle and liver with the remainder being unexpressed. 193 and 198 unique tRNA sequences were expressed in all treatment groups within muscle and liver respectively. In addition, an average of 193 tRNA sequences were expressed within the same treatment group in different tissues. Some tRNA isodecoders were differentially expressed between treatment groups. In the skeletal muscle and liver, we categorized 11 tRNA isoacceptors with undetected expression as well as an isodecoder that was unexpressed in the liver (SerGGA). Our results identified variation in the proportion of tRNA gene copies expressed between tissues and differences in the highest contributing tRNA anticodon within an amino acid family due to treatment and tissue type. Out of all amino acid families, roughly half of the most highly expressed tRNA isoacceptors correlated to their most frequent codon in the bovine genome. Conclusion Although the number of bovine tRNA genes is nearly triple of that of the tRNA genes in human, there is a shared occurrence of transcriptionally inactive tRNA genes in both species. We detected differential expression of tRNA genes as well as tissue- and treatment- specific tRNA transcripts with unique sequence variations that could modulate translation during protein homeostasis or cellular stress, and give rise to regulatory products targeting genes related to overgrowth in the skeletal muscle and/or tumor development in the liver of LOS individuals. While the absence of certain isodecoders may be relieved by wobble base pairing, missing tRNA species could increase the likelihood of mistranslation or mRNA degradation. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08496-7.
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Affiliation(s)
- Anna K Goldkamp
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, USA
| | - Yahan Li
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Rocio M Rivera
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Darren E Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, OK, USA.
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23
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Nayan V, Singh K, Iquebal MA, Jaiswal S, Bhardwaj A, Singh C, Bhatia T, Kumar S, Singh R, Swaroop MN, Kumar R, Phulia SK, Bharadwaj A, Datta TK, Rai A, Kumar D. Genome-Wide DNA Methylation and Its Effect on Gene Expression During Subclinical Mastitis in Water Buffalo. Front Genet 2022; 13:828292. [PMID: 35368672 PMCID: PMC8965078 DOI: 10.3389/fgene.2022.828292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/31/2022] [Indexed: 11/20/2022] Open
Abstract
Subclinical mastitis (SCM) in buffalo is one of the most challenging paradoxes for the dairy sector with very significant milk production losses and poses an imminent danger to milch animal’s milk-producing ability. We present here the genome-wide methylation specific to SCM in water buffalo and its consequential effect on the gene expression landscape for the first time. Whole-genome DNA methylation profiles from peripheral blood lymphocytes and gene expression profiles from milk somatic cells of healthy and SCM cases were catalogued from the MeDIP-Seq and RNA-Seq data. The average methylation in healthy buffaloes was found to be higher than that in the SCM-infected buffaloes. DNA methylation was abundant in the intergenic region followed by the intronic region in both healthy control and SCM groups. A total of 3,950 differentially methylated regions (DMRs) were identified and annotated to 370 differentially methylated genes (DMGs), most of which were enriched in the promoter region. Several important pathways were activated due to hypomethylation and belonged to the Staphylococcus aureus infection, Th17 cell differentiation, and antigen processing and presentation pathways along with others of defense responses. DNA methylome was compared with transcriptome to understand the regulatory role of DNA methylation on gene expression specific to SCM in buffaloes. A total of 4,778 significant differentially expressed genes (DEGs) were extracted in response to SCM, out of which 67 DMGs were also found to be differentially expressed, suggesting that during SCM, DNA methylation could be one of the epigenetic regulatory mechanisms of gene expression. Genes like CSF2RB, LOC102408349, C3 and PZP like, and CPAMD8 were found to be downregulated in our study, which are known to be involved in the immune response to SCM. Association of DNA methylation with transposable elements, miRNAs, and lncRNAs was also studied. The present study reports a buffalo SCM web resource (BSCM2TDb) available at http://webtom.cabgrid.res.in/BSCM2TDb that catalogues all the mastitis-related information of the analyses results of this study in a single place. This will be of immense use to buffalo researchers to understand the host–pathogen interaction involving SCM, which is required in endeavors of mastitis control and management.
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Affiliation(s)
- Varij Nayan
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Kalpana Singh
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistical Research Institute, New Delhi, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistical Research Institute, New Delhi, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistical Research Institute, New Delhi, India
| | | | - Chhama Singh
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Tanvi Bhatia
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Sunil Kumar
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Rakshita Singh
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - M. N. Swaroop
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Rajesh Kumar
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - S. K. Phulia
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | | | - T. K. Datta
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistical Research Institute, New Delhi, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistical Research Institute, New Delhi, India
- *Correspondence: Dinesh Kumar,
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24
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Drouilhet L, Moreno C, Plisson-Petit F, Marcon D, Fabre S, Hazard D. Variability in Global DNA Methylation Rate Across Tissues and Over Time in Sheep. Front Genet 2022; 13:791283. [PMID: 35360841 PMCID: PMC8961874 DOI: 10.3389/fgene.2022.791283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 02/08/2022] [Indexed: 12/12/2022] Open
Abstract
Recent studies highlighted the influence of epigenetic marks in the variability of many complex traits, both in plants and animals. These studied focused only on specific sites of the genome having differentially methylated profiles among individuals and/or tissues. In contrast, we recently used the methylation rate of the entire genome as a unique measure considered as a novel quantitative phenotype in sheep. This phenotype named global DNA methylation rate (GDMR), measured by luminometric assay, integrates the methylation level of each CpG dinucleotide within the 6 million of CCGG sites along the ovine genome. GDMR measured in blood previously showed moderate heritability of 0.20 and provided evidence for a genetic determinism. The main objective of the present study was to better characterize the GDMR phenotype in various tissues and investigate its variability in several breeds of sheep reared in the same environment. GDMR was measured on blood samples collected monthly from 59 growing male and female lambs (24 Romane, 23 Blackbelly and 12 Charollais), between birth and 4 months of age. Blood GDMR was on average around 80% and was influenced by the sampling date (p < 0.001), the breed (p = 0.002) and the sex (p = 0.002). In addition, GDMR was determined in 12 somatic (frontal lobe, pituitary gland, heart, lung, sub cutaneous and perirenal adipose tissue, skeletal muscle, liver, spleen, adrenal gland, medulla and cortical kidney) and 6 reproductive tissues (ovary, oviduct, uterus, testis, epididymis and seminal vesicle). GDMR was on average 70% in somatic tissues but marked variation was observed depending on the tissue. The GDMR measured in blood was higher than that measured in other somatic tissues, and is not a good proxy of less accessible tissues. Female reproductive tissues had a 10% higher GDMR than male reproductive tissues. We demonstrated a significant influence of the breed on blood GDMR, certainly reflecting the influence of different genetic backgrounds. The effect of the breed on GDMR may be related to their specific abilities to adapt to and live in different conditions.
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Affiliation(s)
- Laurence Drouilhet
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
- *Correspondence: Laurence Drouilhet,
| | - Carole Moreno
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
| | | | | | - Stéphane Fabre
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
| | - Dominique Hazard
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
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25
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Arneson A, Haghani A, Thompson MJ, Pellegrini M, Kwon SB, Vu H, Maciejewski E, Yao M, Li CZ, Lu AT, Morselli M, Rubbi L, Barnes B, Hansen KD, Zhou W, Breeze CE, Ernst J, Horvath S. A mammalian methylation array for profiling methylation levels at conserved sequences. Nat Commun 2022; 13:783. [PMID: 35145108 PMCID: PMC8831611 DOI: 10.1038/s41467-022-28355-z] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 01/20/2022] [Indexed: 12/12/2022] Open
Abstract
Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development of epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others. Methods to probe DNA methylation in the majority of non-human mammals are lacking. Here the authors developed a Mammalian Methylation Array that includes 36k well-conserved CpGs in mammals which will facilitate cross-species comparisons. They annotate the conserved CpGs in > 200 species. The array allows one to measure methylation in all mammalian species including unsequenced ones.
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Affiliation(s)
- Adriana Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.,Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Amin Haghani
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Michael J Thompson
- Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Matteo Pellegrini
- Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Soo Bin Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.,Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ha Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA.,Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Emily Maciejewski
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA.,Computer Science Department, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mingjia Yao
- Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Caesar Z Li
- Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Ake T Lu
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Marco Morselli
- Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Liudmilla Rubbi
- Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Bret Barnes
- Illumina, Inc, 5200 Illumina Way, San Diego, CA, 92122, USA
| | - Kasper D Hansen
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, USA
| | | | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, 90095, USA. .,Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA. .,Computer Science Department, University of California, Los Angeles, Los Angeles, CA, USA. .,Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, Los Angeles, CA, USA. .,Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA. .,Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA. .,Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Steve Horvath
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA. .,Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA. .,Altos Labs, San Diego, CA, USA.
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26
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Lu X, Zhang Y, Wang L, Wang L, Wang H, Xu Q, Xiang Y, Chen C, Kong F, Xia W, Lin Z, Ma S, Liu L, Wang X, Ni H, Li W, Guo Y, Xie W. Evolutionary epigenomic analyses in mammalian early embryos reveal species-specific innovations and conserved principles of imprinting. SCIENCE ADVANCES 2021; 7:eabi6178. [PMID: 34818044 PMCID: PMC8612685 DOI: 10.1126/sciadv.abi6178] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 10/06/2021] [Indexed: 05/24/2023]
Abstract
While mouse remains the most popular model, the conservation of parental-to-embryonic epigenetic transition across mammals is poorly defined. Through analysis of oocytes and early embryos in human, bovine, porcine, rat, and mouse, we revealed remarkable species-specific innovations as no single animal model fully recapitulates the human epigenetic transition. In rodent oocytes, transcription-dependent DNA methylation allows methylation of maternal imprints but not intergenic paternal imprints. Unexpectedly, prevalent DNA hypermethylation, paralleled by H3K36me2/3, also occurs in nontranscribed regions in porcine and bovine oocytes, except for megabase-long “CpG continents (CGCs)” where imprinting control regions preferentially reside. Broad H3K4me3 and H3K27me3 domains exist in nonhuman oocytes, yet only rodent H3K27me3 survives beyond genome activation. Coincidently, regulatory elements preferentially evade H3K27me3 in rodent oocytes, and failure to do so causes aberrant embryonic gene repression. Hence, the diverse mammalian innovations of parental-to-embryonic transition center on a delicate “to-methylate-or-not” balance in establishing imprints while protecting other regulatory regions.
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Affiliation(s)
- Xukun Lu
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yu Zhang
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Lijuan Wang
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
- College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China
| | - Leyun Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Huili Wang
- Institute of Animal Science, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Qianhua Xu
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yunlong Xiang
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Chaolei Chen
- College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China
| | - Feng Kong
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Weikun Xia
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Zili Lin
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Sinan Ma
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Science, Northeast Agricultural University, Harbin 150030, China
| | - Ling Liu
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Xiangguo Wang
- College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China
| | - Hemin Ni
- College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China
| | - Wei Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Yong Guo
- College of Animal Science and Technology, Beijing University of Agriculture, Beijing 102206, China
| | - Wei Xie
- Tsinghua-Peking Center for Life Sciences, Beijing 100084, China
- Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
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27
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Hayes BJ, Nguyen LT, Forutan M, Engle BN, Lamb HJ, Copley JP, Randhawa IAS, Ross EM. An Epigenetic Aging Clock for Cattle Using Portable Sequencing Technology. Front Genet 2021; 12:760450. [PMID: 34868240 PMCID: PMC8637324 DOI: 10.3389/fgene.2021.760450] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 10/29/2021] [Indexed: 02/05/2023] Open
Abstract
Extensively grazed cattle are often mustered only once a year. Therefore, birthdates are typically unknown or inaccurate. Birthdates would be useful for deriving important traits (growth rate; calving interval), breed registrations, and making management decisions. Epigenetic clocks use methylation of DNA to predict an individual's age. An epigenetic clock for cattle could provide a solution to the challenges of industry birthdate recording. Here we derived the first epigenetic clock for tropically adapted cattle using portable sequencing devices from tail hair, a tissue which is widely used in industry for genotyping. Cattle (n = 66) with ages ranging from 0.35 to 15.7 years were sequenced using Oxford Nanopore Technologies MinION and methylation was called at CpG sites across the genome. Sites were then filtered and used to calculate a covariance relationship matrix based on methylation state. Best linear unbiased prediction was used with 10-fold cross validation to predict age. A second methylation relationship matrix was also calculated that contained sites associated with genes used in the dog and human epigenetic clocks. The correlation between predicted age and actual age was 0.71 for all sites and 0.60 for dog and human gene epigenetic clock sites. The mean absolute deviation was 1.4 years for animals aged less than 3 years of age, and 1.5 years for animals aged 3-10 years. This is the first reported epigenetic clock using industry relevant samples in cattle.
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Affiliation(s)
- Ben J. Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | - Loan T. Nguyen
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | - Mehrnush Forutan
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | - Bailey N. Engle
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | - Harrison J. Lamb
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | - James P. Copley
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
| | | | - Elizabeth M. Ross
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St Lucia, QLD, Australia
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28
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Wang M, Bissonnette N, Dudemaine PL, Zhao X, Ibeagha-Awemu EM. Whole Genome DNA Methylation Variations in Mammary Gland Tissues from Holstein Cattle Producing Milk with Various Fat and Protein Contents. Genes (Basel) 2021; 12:1727. [PMID: 34828333 PMCID: PMC8618717 DOI: 10.3390/genes12111727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 10/22/2021] [Accepted: 10/22/2021] [Indexed: 12/20/2022] Open
Abstract
Milk fat and protein contents are among key elements of milk quality, and they are attracting more attention in response to consumers' demand for high-quality dairy products. To investigate the potential regulatory roles of DNA methylation underlying milk component yield, whole genome bisulfite sequencing was employed to profile the global DNA methylation patterns of mammary gland tissues from 17 Canada Holstein cows with various milk fat and protein contents. A total of 706, 2420 and 1645 differentially methylated CpG sites (DMCs) were found between high vs. low milk fat (HMF vs. LMF), high vs. low milk protein (HMP vs. LMP), and high vs. low milk fat and protein (HMFP vs. LMFP) groups, respectively (q value < 0.1). Twenty-seven, 56 and 67 genes harboring DMCs in gene regions (denoted DMC genes) were identified for HMF vs. LMF, HMP vs. LMP and HMFP vs. LMFP, respectively. DMC genes from HMP vs. LMP and HMFP vs. LMFP comparisons were significantly overrepresented in GO terms related to aerobic electron transport chain and/or mitochondrial ATP (adenosine triphosphate) synthesis coupled electron transport. A total of 83 (HMF vs. LMF), 708 (HMP vs. LMP) and 408 (HMFP vs. LMFP) DMCs were co-located with 87, 147 and 158 quantitative trait loci (QTL) for milk component and yield traits, respectively. In conclusion, the identified methylation changes are potentially involved in the regulation of milk fat and protein yields, as well as the variation in reported co-located QTLs.
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Affiliation(s)
- Mengqi Wang
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada; (M.W.); (N.B.); (P.-L.D.)
| | - Nathalie Bissonnette
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada; (M.W.); (N.B.); (P.-L.D.)
| | - Pier-Luc Dudemaine
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada; (M.W.); (N.B.); (P.-L.D.)
| | - Xin Zhao
- Department of Animal Science, McGill University, Ste-Anne-De-Bellevue, QC H9X 3V9, Canada;
| | - Eveline M. Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8, Canada; (M.W.); (N.B.); (P.-L.D.)
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29
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Woźniak E, Reszka E, Jabłońska E, Michałowicz J, Huras B, Bukowska B. Glyphosate and AMPA Induce Alterations in Expression of Genes Involved in Chromatin Architecture in Human Peripheral Blood Mononuclear Cells (In Vitro). Int J Mol Sci 2021; 22:2966. [PMID: 33803994 PMCID: PMC7998550 DOI: 10.3390/ijms22062966] [Citation(s) in RCA: 9] [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: 02/12/2021] [Revised: 03/07/2021] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
We have determined the effect of glyphosate and aminomethylphosphonic acid (AMPA) on expression of genes involved in chromatin architecture in human peripheral blood mononuclear cells (PBMCs). The cells were incubated with glyphosate and AMPA in the concentrations ranging from 0.5 to 100 μM and from 0.5, to 250 μM, respectively. The expression profile of the following genes by quantitative Real-Time PCR was evaluated: Genes involved in the DNA methylation (DNMT1, DNMT3A) and DNA demethylation process (TET3) and those involved in chromatin remodeling: genes involved in the modification of histone methylation (EHMT1, EHMT2) and genes involved in the modification of histone deacetylation (HDAC3, HDAC5). Gene profiling showed that glyphosate changed the expression of DNMT1, DMNT3A, and HDAC3, while AMPA changed the expression of DNMT1 and HDAC3. The results also revealed that glyphosate at lower concentrations than AMPA upregulated the expression of the tested genes. Both compounds studied altered expression of genes, which are characteristic for the regulation of transcriptionally inactive chromatin. However, the unknown activity of many other proteins involved in chromatin structure regulation prevents to carry out an unambiguous evaluation of the effect of tested xenobiotics on the studied process. Undoubtedly, we have observed that glyphosate and AMPA affect epigenetic processes that regulate chromatin architecture.
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Affiliation(s)
- Ewelina Woźniak
- Department of Biophysics of Environmental Pollution, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland; (E.W.); (J.M.)
- Laboratory of Tissue Immunopharmacology, Department of Internal Diseases and Clinical Pharmacology, Medical University of Lodz, Kniaziewicza 1/5, 91-347 Lodz, Poland
| | - Edyta Reszka
- Department of Molecular Genetics and Epigenetics, Nofer Institute of Occupational Medicine, Teresy 8, 91-348 Lodz, Poland; (E.R.); (E.J.)
| | - Ewa Jabłońska
- Department of Molecular Genetics and Epigenetics, Nofer Institute of Occupational Medicine, Teresy 8, 91-348 Lodz, Poland; (E.R.); (E.J.)
| | - Jaromir Michałowicz
- Department of Biophysics of Environmental Pollution, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland; (E.W.); (J.M.)
| | - Bogumiła Huras
- Łukasiewicz Research Network, Institute of Industrial Organic Chemistry, Annopol 6 Str, 03-236 Warsaw, Poland;
| | - Bożena Bukowska
- Department of Biophysics of Environmental Pollution, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland; (E.W.); (J.M.)
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30
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Jeong DS, Kim MH, Lee J. Depletion of CTCF disrupts PSG gene expression in the human trophoblast cell line Swan 71. FEBS Open Bio 2021; 11:804-812. [PMID: 33452729 PMCID: PMC7931220 DOI: 10.1002/2211-5463.13087] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/25/2020] [Accepted: 01/13/2021] [Indexed: 11/24/2022] Open
Abstract
Pregnancy‐specific glycoproteins (PSGs) are fetal proteins secreted by the placenta during pregnancy. The PSG level in maternal serum is an indicator of risk for pregnancy complications. However, little is known about the molecular mechanisms underlying PSG gene expression. Recently, the importance of epigenetic regulation of placental genes has been emphasized in the study of developmental defects and placental disease. In this study, the role of the CCCTC‐binding factor (CTCF) in regulation of PSG expression was investigated to better understand the epigenetic regulatory mechanisms of the PSG genes. Inhibition of CTCF expression disturbed transcription of several PSG genes: PSG1, PSG2, PSG4, PSG5, PSG8, and PSG9 were upregulated and PSG6 and PSG11 were downregulated. These transcriptional changes were correlated with decreased CTCF binding and changes in histone modification at the PSG promoters. Our data demonstrate that CTCF is a potential mediator in the regulation of PSG gene expression.
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Affiliation(s)
- Da Som Jeong
- Department of AnatomyEmbryology LaboratoryYonsei University College of MedicineSeoulKorea
- Brain Korea 21 PLUS project for Medical ScienceYonsei University College of MedicineSeoulKorea
| | - Myoung Hee Kim
- Department of AnatomyEmbryology LaboratoryYonsei University College of MedicineSeoulKorea
- Brain Korea 21 PLUS project for Medical ScienceYonsei University College of MedicineSeoulKorea
| | - Ji‐Yeon Lee
- Department of AnatomyEmbryology LaboratoryYonsei University College of MedicineSeoulKorea
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31
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Zhu L, Marjani SL, Jiang Z. The Epigenetics of Gametes and Early Embryos and Potential Long-Range Consequences in Livestock Species-Filling in the Picture With Epigenomic Analyses. Front Genet 2021; 12:557934. [PMID: 33747031 PMCID: PMC7966815 DOI: 10.3389/fgene.2021.557934] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 02/04/2021] [Indexed: 12/31/2022] Open
Abstract
The epigenome is dynamic and forged by epigenetic mechanisms, such as DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA species. Increasing lines of evidence support the concept that certain acquired traits are derived from environmental exposure during early embryonic and fetal development, i.e., fetal programming, and can even be "memorized" in the germline as epigenetic information and transmitted to future generations. Advances in technology are now driving the global profiling and precise editing of germline and embryonic epigenomes, thereby improving our understanding of epigenetic regulation and inheritance. These achievements open new avenues for the development of technologies or potential management interventions to counteract adverse conditions or improve performance in livestock species. In this article, we review the epigenetic analyses (DNA methylation, histone modification, chromatin remodeling, and non-coding RNAs) of germ cells and embryos in mammalian livestock species (cattle, sheep, goats, and pigs) and the epigenetic determinants of gamete and embryo viability. We also discuss the effects of parental environmental exposures on the epigenetics of gametes and the early embryo, and evidence for transgenerational inheritance in livestock.
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Affiliation(s)
- Linkai Zhu
- AgCenter, School of Animal Sciences, Louisiana State University, Baton Rouge, LA, United States
| | - Sadie L Marjani
- Department of Biology, Central Connecticut State University, New Britain, CT, United States
| | - Zongliang Jiang
- AgCenter, School of Animal Sciences, Louisiana State University, Baton Rouge, LA, United States
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32
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Zhou Y, Liu S, Hu Y, Fang L, Gao Y, Xia H, Schroeder SG, Rosen BD, Connor EE, Li CJ, Baldwin RL, Cole JB, Van Tassell CP, Yang L, Ma L, Liu GE. Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biol 2020; 18:85. [PMID: 32631327 PMCID: PMC7339546 DOI: 10.1186/s12915-020-00793-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 05/12/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Efforts to improve animal health, and understand genetic bases for production, may benefit from a comprehensive analysis of animal genomes and epigenomes. Although DNA methylation has been well studied in humans and other model species, its distribution patterns and regulatory impacts in cattle are still largely unknown. Here, we present the largest collection of cattle DNA methylation epigenomic data to date. RESULTS Using Holstein cattle, we generated 29 whole genome bisulfite sequencing (WGBS) datasets for 16 tissues, 47 corresponding RNA-seq datasets, and 2 whole genome sequencing datasets. We did read mapping and DNA methylation calling based on two different cattle assemblies, demonstrating the high quality of the long-read-based assembly markedly improved DNA methylation results. We observed large differences across cattle tissues in the methylation patterns of global CpG sites, partially methylated domains (PMDs), hypomethylated regions (HMRs), CG islands (CGIs), and common repeats. We detected that each tissue had a distinct set of PMDs, which showed tissue-specific patterns. Similar to human PMD, cattle PMDs were often linked to a general decrease of gene expression and a decrease in active histone marks and related to long-range chromatin organizations, like topologically associated domains (TADs). We tested a classification of the HMRs based on their distributions relative to transcription start sites (TSSs) and detected tissue-specific TSS-HMRs and genes that showed strong tissue effects. When performing cross-species comparisons of paired genes (two opposite strand genes with their TSS located in the same HMR), we found out they were more consistently co-expressed among human, mouse, sheep, goat, yak, pig, and chicken, but showed lower consistent ratios in more divergent species. We further used these WGBS data to detect 50,023 experimentally supported CGIs across bovine tissues and found that they might function as a guard against C-to-T mutations for TSS-HMRs. Although common repeats were often heavily methylated, some young Bov-A2 repeats were hypomethylated in sperm and could affect the promoter structures by exposing potential transcription factor binding sites. CONCLUSIONS This study provides a comprehensive resource for bovine epigenomic research and enables new discoveries about DNA methylation and its role in complex traits.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Lingzhao Fang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Erin E. Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716 USA
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - John B. Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742 USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
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