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Yi M, Asgenbaatar N, Wang X, Ulaangerel T, Shen Y, Wen X, Du M, Dong X, Dugarjav M, Bou G. Different expression patterns of DNA methyltransferases during horse testis development. Gene 2024; 920:148531. [PMID: 38705424 DOI: 10.1016/j.gene.2024.148531] [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: 02/22/2024] [Revised: 04/28/2024] [Accepted: 05/02/2024] [Indexed: 05/07/2024]
Abstract
DNA methyltransferases (DNMTs) are important epigenetic modification during spermatogenesis. To further evaluate the pattern of DNMTs in horse testes during development, we investigated the expression and localization of DNMT1, DNMT3a and DNMT3b at different time points. The qRT-PCR results showed that DNMT1 expression was maintained in testes tissue from 6-month-old (0.5y) to 2-year-old (2y) of age and decreased after 3-year-old (3y) (P < 0.01). The expression levels of DNMT3a and DNMT3b peaked in testes tissue at 3y (P < 0.01). At 4-year-old (4y), the expression of DNMT3a and DNMT3b was decreased and became similar to that at 0.5y. Immunofluorescence of DNMT1, DNMT3a and DNMT3b on testis samples confirmed the differential expression and localization of these three DNA methylation transferases during horse development. Further molecular biological studies are needed to understand the implications of the expression patterns of these DNMTs in horse testes.
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Affiliation(s)
- Minna Yi
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China
| | - Nairag Asgenbaatar
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China; Da Bei Nong group rumination technology rumination acadamy Haidian District, Beijing, China
| | - Xisheng Wang
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China; Collaborative Innovation Center for Birth Defect Research and Transformation of Shandong Province, Jining Medical University, Jining, China
| | - Tseweendolmaa Ulaangerel
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China
| | - Yingchao Shen
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China
| | - Xin Wen
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China
| | - Ming Du
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China
| | - Xiaoling Dong
- Da Bei Nong group rumination technology rumination acadamy Haidian District, Beijing, China; China Agricultural University, Beijing, China
| | - Manglai Dugarjav
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China.
| | - Gerelchimeg Bou
- Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot, China.
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Semik-Gurgul E, Pawlina-Tyszko K, Gurgul A, Szmatoła T, Rybińska J, Ząbek T. In search of epigenetic hallmarks of different tissues: an integrative omics study of horse liver, lung, and heart. Mamm Genome 2024:10.1007/s00335-024-10057-0. [PMID: 39143382 DOI: 10.1007/s00335-024-10057-0] [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: 05/17/2024] [Accepted: 08/01/2024] [Indexed: 08/16/2024]
Abstract
DNA methylation and microRNA (miRNA) expression are epigenetic mechanisms essential for regulating tissue-specific gene expression and metabolic processes. However, high-resolution transcriptome, methylome, or miRNAome data is only available for a few model organisms and selected tissues. Up to date, only a few studies have reported on gene expression, DNA methylation, or miRNA expression in adult equine tissues at the genome-wide level. In the present study, we used RNA-Seq, miRNA-seq, and reduced representation bisulfite sequencing (RRBS) data from the heart, lung, and liver tissues of healthy cold-blooded horses to identify differentially expressed genes (DEGs), differentially expressed miRNA (DE miRNA) and differentially methylated sites (DMSs) between three types of horse tissues. Additionally, based on integrative omics analysis, we described the observed interactions of epigenetic mechanisms with tissue-specific gene expression alterations. The obtained data allowed identification from 4067 to 6143 DMSs, 9733 to 11,263 mRNAs, and 155 to 185 microRNAs, differentially expressed between various tissues. We pointed out specific genes whose expression level displayed a negative correlation with the level of CpG methylation and miRNA expression and revealed biological processes that they enrich. Furthermore, we confirmed and validated the accuracy of the Next-Generation Sequencing (NGS) results with bisulfite sequencing PCR (BSP) and quantitative PCR (qPCR). This comprehensive analysis forms a strong foundation for exploring the epigenetic mechanisms involved in tissue differentiation, especially the growth and development of the equine heart, lungs, and liver.
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Affiliation(s)
- Ewelina Semik-Gurgul
- Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1 St, Balice, 32-083, Poland.
| | - Klaudia Pawlina-Tyszko
- Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1 St, Balice, 32-083, Poland
| | - Artur Gurgul
- Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Redzina 1c, Krakow, 30-248, Poland
| | - Tomasz Szmatoła
- Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1 St, Balice, 32-083, Poland
- Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Redzina 1c, Krakow, 30-248, Poland
| | - Justyna Rybińska
- Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1 St, Balice, 32-083, Poland
| | - Tomasz Ząbek
- Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1 St, Balice, 32-083, Poland
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3
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Dutta S, Goodrich JM, Dolinoy DC, Ruden DM. Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research. Genes (Basel) 2023; 15:16. [PMID: 38275598 PMCID: PMC10815440 DOI: 10.3390/genes15010016] [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: 11/27/2023] [Revised: 12/14/2023] [Accepted: 12/20/2023] [Indexed: 01/27/2024] Open
Abstract
Biological clock technologies are designed to assess the acceleration of biological age (B-age) in diverse cell types, offering a distinctive opportunity in toxicogenomic research to explore the impact of environmental stressors, social challenges, and unhealthy lifestyles on health impairment. These clocks also play a role in identifying factors that can hinder aging and promote a healthy lifestyle. Over the past decade, researchers in epigenetics have developed testing methods that predict the chronological and biological age of organisms. These methods rely on assessing DNA methylation (DNAm) levels at specific CpG sites, RNA levels, and various biomolecules across multiple cell types, tissues, and entire organisms. Commonly known as 'biological clocks' (B-clocks), these estimators hold promise for gaining deeper insights into the pathways contributing to the development of age-related disorders. They also provide a foundation for devising biomedical or social interventions to prevent, reverse, or mitigate these disorders. This review article provides a concise overview of various epigenetic clocks and explores their susceptibility to environmental stressors.
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Affiliation(s)
- Sudipta Dutta
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843, USA;
| | - Jaclyn M. Goodrich
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
| | - Dana C. Dolinoy
- Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA; (J.M.G.); (D.C.D.)
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas M. Ruden
- C. S. Mott Center for Human Health and Development, Department of Obstetrics and Gynecology, Institute of Environmental Health Sciences, Wayne State University, Detroit, MI 48202, USA
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4
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Horvath S, Haghani A, Zoller JA, Lu AT, Ernst J, Pellegrini M, Jasinska AJ, Mattison JA, Salmon AB, Raj K, Horvath M, Paul KC, Ritz BR, Robeck TR, Spriggs M, Ehmke EE, Jenkins S, Li C, Nathanielsz PW. Pan-primate studies of age and sex. GeroScience 2023; 45:3187-3209. [PMID: 37493860 PMCID: PMC10643767 DOI: 10.1007/s11357-023-00878-3] [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: 06/08/2023] [Accepted: 07/16/2023] [Indexed: 07/27/2023] Open
Abstract
Age and sex have a profound effect on cytosine methylation levels in humans and many other species. Here we analyzed DNA methylation profiles of 2400 tissues derived from 37 primate species including 11 haplorhine species (baboons, marmosets, vervets, rhesus macaque, chimpanzees, gorillas, orangutan, humans) and 26 strepsirrhine species (suborders Lemuriformes and Lorisiformes). From these we present here, pan-primate epigenetic clocks which are highly accurate for all primates including humans (age correlation R = 0.98). We also carried out in-depth analysis of baboon DNA methylation profiles and generated five epigenetic clocks for baboons (Olive-yellow baboon hybrid), one of which, the pan-tissue epigenetic clock, was trained on seven tissue types (fetal cerebral cortex, adult cerebral cortex, cerebellum, adipose, heart, liver, and skeletal muscle) with ages ranging from late fetal life to 22.8 years of age. Using the primate data, we characterize the effect of age and sex on individual cytosines in highly conserved regions. We identify 11 sex-related CpGs on autosomes near genes (POU3F2, CDYL, MYCL, FBXL4, ZC3H10, ZXDC, RRAS, FAM217A, RBM39, GRIA2, UHRF2). Low overlap can be observed between age- and sex-related CpGs. Overall, this study advances our understanding of conserved age- and sex-related epigenetic changes in primates, and provides biomarkers of aging for all primates.
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Affiliation(s)
- Steve Horvath
- Altos Labs, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
| | | | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Jason Ernst
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Anna J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and BiobehavioralSciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Julie A Mattison
- Translational Gerontology Branch, National Institute On Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Adam B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies, and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | | | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Beate R Ritz
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Todd R Robeck
- Corporate Zoological Operations, SeaWorld Parks, Orlando, FL, USA
| | - Maria Spriggs
- Busch Gardens Tampa, SeaWorld Parks, Tampa, FL, 33612, USA
| | | | - Susan Jenkins
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
| | - Cun Li
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
| | - Peter W Nathanielsz
- Texas Pregnancy & Life-Course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources Department, Laramie, WY, USA
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Le Clercq LS, Kotzé A, Grobler JP, Dalton DL. Biological clocks as age estimation markers in animals: a systematic review and meta-analysis. Biol Rev Camb Philos Soc 2023; 98:1972-2011. [PMID: 37356823 DOI: 10.1111/brv.12992] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 06/04/2023] [Accepted: 06/08/2023] [Indexed: 06/27/2023]
Abstract
Various biological attributes associated with individual fitness in animals change predictably over the lifespan of an organism. Therefore, the study of animal ecology and the work of conservationists frequently relies upon the ability to assign animals to functionally relevant age classes to model population fitness. Several approaches have been applied to determining individual age and, while these methods have proved useful, they are not without limitations and often lack standardisation or are only applicable to specific species. For these reasons, scientists have explored the potential use of biological clocks towards creating a universal age-determination method. Two biological clocks, tooth layer annulation and otolith layering have found universal appeal. Both methods are highly invasive and most appropriate for post-mortem age-at-death estimation. More recently, attributes of cellular ageing previously explored in humans have been adapted to studying ageing in animals for the use of less-invasive molecular methods for determining age. Here, we review two such methods, assessment of methylation and telomere length, describing (i) what they are, (ii) how they change with age, and providing (iii) a summary and meta-analysis of studies that have explored their utility in animal age determination. We found that both attributes have been studied across multiple vertebrate classes, however, telomere studies were used before methylation studies and telomere length has been modelled in nearly twice as many studies. Telomere length studies included in the review often related changes to stress responses and illustrated that telomere length is sensitive to environmental and social stressors and, in the absence of repair mechanisms such as telomerase or alternative lengthening modes, lacks the ability to recover. Methylation studies, however, while also detecting sensitivity to stressors and toxins, illustrated the ability to recover from such stresses after a period of accelerated ageing, likely due to constitutive expression or reactivation of repair enzymes such as DNA methyl transferases. We also found that both studied attributes have parentally heritable features, but the mode of inheritance differs among taxa and may relate to heterogamy. Our meta-analysis included more than 40 species in common for methylation and telomere length, although both analyses included at least 60 age-estimation models. We found that methylation outperforms telomere length in terms of predictive power evidenced from effect sizes (more than double that observed for telomeres) and smaller prediction intervals. Both methods produced age correlation models using similar sample sizes and were able to classify individuals into young, middle, or old age classes with high accuracy. Our review and meta-analysis illustrate that both methods are well suited to studying age in animals and do not suffer significantly from variation due to differences in the lifespan of the species, genome size, karyotype, or tissue type but rather that quantitative method, patterns of inheritance, and environmental factors should be the main considerations. Thus, provided that complex factors affecting the measured trait can be accounted for, both methylation and telomere length are promising targets to develop as biomarkers for age determination in animals.
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Affiliation(s)
- Louis-Stéphane Le Clercq
- South African National Biodiversity Institute, P.O. Box 754, Pretoria, 0001, South Africa
- Department of Genetics, University of the Free State, P.O. Box 339, Bloemfontein, 9300, South Africa
| | - Antoinette Kotzé
- South African National Biodiversity Institute, P.O. Box 754, Pretoria, 0001, South Africa
- Department of Genetics, University of the Free State, P.O. Box 339, Bloemfontein, 9300, South Africa
| | - J Paul Grobler
- Department of Genetics, University of the Free State, P.O. Box 339, Bloemfontein, 9300, South Africa
| | - Desiré Lee Dalton
- School of Health and Life Sciences, Teesside University, Middlesbrough, TS1 3BA, UK
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Mozhui K, Kim H, Villani F, Haghani A, Sen S, Horvath S. Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits. Epigenetics 2023; 18:2252631. [PMID: 37691384 PMCID: PMC10496549 DOI: 10.1080/15592294.2023.2252631] [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: 05/01/2023] [Revised: 07/31/2023] [Accepted: 08/16/2023] [Indexed: 09/12/2023] Open
Abstract
DNA methylation is influenced by genetic and non-genetic factors. Here, we chart quantitative trait loci (QTLs) that modulate levels of methylation at highly conserved CpGs using liver methylome data from mouse strains belonging to the BXD family. A regulatory hotspot on chromosome 5 had the highest density of trans-acting methylation QTLs (trans-meQTLs) associated with multiple distant CpGs. We refer to this locus as meQTL.5a. Trans-modulated CpGs showed age-dependent changes and were enriched in developmental genes, including several members of the MODY pathway (maturity onset diabetes of the young). The joint modulation by genotype and ageing resulted in a more 'aged methylome' for BXD strains that inherited the DBA/2J parental allele at meQTL.5a. Further, several gene expression traits, body weight, and lipid levels mapped to meQTL.5a, and there was a modest linkage with lifespan. DNA binding motif and protein-protein interaction enrichment analyses identified the hepatic nuclear factor, Hnf1a (MODY3 gene in humans), as a strong candidate. The pleiotropic effects of meQTL.5a could contribute to variations in body size and metabolic traits, and influence CpG methylation and epigenetic ageing that could have an impact on lifespan.
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Affiliation(s)
- Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Hyeonju Kim
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Flavia Villani
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Saunak Sen
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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Maciejewski E, Horvath S, Ernst J. Cross-species and tissue imputation of species-level DNA methylation samples across mammalian species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.26.568769. [PMID: 38076978 PMCID: PMC10705269 DOI: 10.1101/2023.11.26.568769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2023]
Abstract
DNA methylation data offers valuable insights into various aspects of mammalian biology. The recent introduction and large-scale application of the mammalian methylation array has significantly expanded the availability of such data across conserved sites in many mammalian species. In our study, we consider 13,245 samples profiled on this array encompassing 348 species and 59 tissues from 746 species-tissue combinations. While having some coverage of many different species and tissue types, this data captures only 3.6% of potential species-tissue combinations. To address this gap, we developed CMImpute (Cross-species Methylation Imputation), a method based on a Conditional Variational Autoencoder, to impute DNA methylation for non-profiled species-tissue combinations. In cross-validation, we demonstrate that CMImpute achieves a strong correlation with actual observed values, surpassing several baseline methods. Using CMImpute we imputed methylation data for 19,786 new species-tissue combinations. We believe that both CMImpute and our imputed data resource will be useful for DNA methylation analyses across a wide range of mammalian species.
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Affiliation(s)
- Emily Maciejewski
- Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095, 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, US
- Altos Labs, Cambridge, UK, WA14 2DT
| | - Jason Ernst
- Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, Los Angeles, CA 90095, 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 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
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8
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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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Reißmann M, Rajavel A, Kokov ZA, Schmitt AO. Identification of Differentially Expressed Genes after Endurance Runs in Karbadian Horses to Determine Candidates for Stress Indicators and Performance Capability. Genes (Basel) 2023; 14:1982. [PMID: 38002925 PMCID: PMC10671444 DOI: 10.3390/genes14111982] [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: 09/15/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 11/26/2023] Open
Abstract
RNA sequencing makes it possible to uncover genetic mechanisms that underlie certain performance traits. In order to gain a deeper insight into the genetic background and biological processes involved in endurance performance in horses, the changes in the gene expression profiles induced by endurance runs over long (70 km) and short (15 km) distances in the blood of Kabardian horses (Equus caballus) were analyzed. For the long-distance runs, we identified 1484 up- and 691 downregulated genes, while after short-distance runs, only 13 up- and 8 downregulated genes (FC > |1.5|; p < 0.05) were found. These differentially expressed genes (DEGs) are involved in processes and pathways that are primarily related to stress response (interleukin production, activation of inflammatory system) but also to metabolism (carbohydrate catabolic process, lipid biosynthesis, NADP metabolic process). The most important genes involved in these processes therefore represent good candidates for the monitoring and evaluation of the performance of horses in order to avoid excessive demands when endurance performance is required, like ACOD1, CCL5, CD40LG, FOS, IL1R2, IL20RA, and IL22RA2, on the one hand, and, on the other hand, for assessing the suitability of a horse for endurance races, like GATA2, GYG1, HIF1A, MOGAT1, PFKFB3, PLIN5, SIK1, and STBD1.
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Affiliation(s)
- Monika Reißmann
- Thaer-Institute of Agricultural and Horticultural Sciences, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany;
| | - Abirami Rajavel
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany
| | - Zaur A. Kokov
- Institute of Physics and Mathematics, Kabardino-Balkarian State University, Chernyshevsky 173, Nalchik 360004, Russia;
| | - Armin O. Schmitt
- Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August University, Carl-Sprengel-Weg 1, 37075 Göttingen, Germany
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Naue J. Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications. Genes Genomics 2023; 45:1239-1261. [PMID: 37253906 PMCID: PMC10504122 DOI: 10.1007/s13258-023-01392-8] [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: 02/28/2023] [Accepted: 04/15/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND DNA analysis for forensic investigations has a long tradition with important developments and optimizations since its first application. Traditionally, short tandem repeats analysis has been the most powerful method for the identification of individuals. However, in addition, epigenetic changes, i.e., DNA methylation, came into focus of forensic DNA research. Chronological age prediction is one promising application to allow for narrowing the pool of possible individuals who caused a trace, as well as to support the identification of unknown bodies and for age verification of living individuals. OBJECTIVE This review aims to provide an overview of the current knowledge, possibilities, and (current) limitations about DNA methylation-based chronological age prediction with emphasis on forensic application. METHODS The development, implementation and application of age prediction tools requires a deep understanding about the biological background, the analysis methods, the age-dependent DNA methylation markers, as well as the mathematical models for age prediction and their evaluation. Furthermore, additional influences can have an impact. Therefore, the literature was evaluated in respect to these diverse topics. CONCLUSION The numerous research efforts in recent years have led to a rapid change in our understanding of the application of DNA methylation for chronological age prediction, which is now on the way to implementation and validation. Knowledge of the various aspects leads to a better understanding and allows a more informed interpretation of DNAm quantification results, as well as the obtained results by the age prediction tools.
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Affiliation(s)
- Jana Naue
- Institute of Forensic Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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11
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Cappelletti E, Piras FM, Sola L, Santagostino M, Petersen JL, Bellone RR, Finno CJ, Peng S, Kalbfleisch TS, Bailey E, Nergadze SG, Giulotto E. The localization of centromere protein A is conserved among tissues. Commun Biol 2023; 6:963. [PMID: 37735603 PMCID: PMC10514049 DOI: 10.1038/s42003-023-05335-7] [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: 04/18/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023] Open
Abstract
Centromeres are epigenetically specified by the histone H3 variant CENP-A. Although mammalian centromeres are typically associated with satellite DNA, we previously demonstrated that the centromere of horse chromosome 11 (ECA11) is completely devoid of satellite DNA. We also showed that the localization of its CENP-A binding domain is not fixed but slides within an about 500 kb region in different individuals, giving rise to positional alleles. These epialleles are inherited as Mendelian traits but their position can move in one generation. It is still unknown whether centromere sliding occurs during meiosis or during development. Here, we first improve the sequence of the ECA11 centromeric region in the EquCab3.0 assembly. Then, to test whether centromere sliding may occur during development, we map the CENP-A binding domains of ECA11 using ChIP-seq in five tissues of different embryonic origin from the four horses of the equine FAANG (Functional Annotation of ANimal Genomes) consortium. Our results demonstrate that the centromere is localized in the same region in all tissues, suggesting that the position of the centromeric domain is maintained during development.
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Affiliation(s)
| | - Francesca M Piras
- Department of Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Lorenzo Sola
- Department of Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Marco Santagostino
- Department of Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Jessica L Petersen
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Rebecca R Bellone
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
| | - Carrie J Finno
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
| | - Sichong Peng
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
| | - Ted S Kalbfleisch
- Gluck Equine Research Center, University of Kentucky, Lexington, KY, USA
| | - Ernest Bailey
- Gluck Equine Research Center, University of Kentucky, Lexington, KY, USA
| | - Solomon G Nergadze
- Department of Biology and Biotechnology, University of Pavia, Pavia, Italy
| | - Elena Giulotto
- Department of Biology and Biotechnology, University of Pavia, Pavia, Italy.
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12
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. NATURE AGING 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 64] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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13
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Haghani A, Li CZ, Robeck TR, Zhang J, Lu AT, Ablaeva J, Acosta-Rodríguez VA, Adams DM, Alagaili AN, Almunia J, Aloysius A, Amor NM, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter G, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chavez AS, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke S, Cook JA, Cooper LN, Cossette ML, Day J, DeYoung J, Dirocco S, Dold C, Dunnum JL, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Fei Z, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Goya RG, Grant MJ, Green CB, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Belmonte JCI, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaître JF, Levine AJ, Li X, Li C, Lim AR, Lin DTS, Lindemann DM, Liphardt SW, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Murphy WJ, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, Nyamsuren B, O’Brien JK, Ginn PO, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pedersen AB, Pellegrini M, Peters KJ, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Shafer AB, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmohammadi E, Spangler ML, Spriggs M, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Vu H, Wallingford MC, Wang N, Wilkinson GS, Williams RW, Yan Q, Yao M, Young BG, Zhang B, Zhang Z, Zhao Y, Zhao P, Zhou W, Zoller JA, Ernst J, Seluanov A, Gorbunova V, Yang XW, Raj K, Horvath S. DNA methylation networks underlying mammalian traits. Science 2023; 381:eabq5693. [PMID: 37561875 PMCID: PMC11180965 DOI: 10.1126/science.abq5693] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Using DNA methylation profiles (n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.
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Affiliation(s)
- Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Caesar Z. Li
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Janssen Research & Development, Spring House, PA, USA
| | - Todd R. Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Joshua Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ake T. Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Julia Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Victoria A. Acosta-Rodríguez
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Danielle M. Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - Abdulaziz N. Alagaili
- Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Javier Almunia
- Loro Parque Fundacion, Avenida Loro Parque, Puerto de la Cruz, Tenerife, Spain
| | - Ajoy Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - Nabil M.S. Amor
- Laboratory of Biodiversity, Parasitology, and Ecology, University of Tunis El Manar, Tunis, Tunisia
| | - Reza Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Adriana Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C. Scott Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - Gareth Banks
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Science and Innovation Campus, Oxfordshire, UK
| | - Katherine Belov
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Nigel C. Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | - Daniel T. Blumstein
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- The Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - Eleanor K. Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | | | | | - Janine L. Brown
- Center for Species Survival, Smithsonian National Zoo and Conservation Biology, Front Royal, VA, USA
| | - Gerald Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Alex Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, Otago, New Zealand
| | - Julie M. Cavin
- Gulf World Marine Park - Dolphin Company, Panama City Beach, FL, USA
| | - Lisa Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Ioulia Chatzistamou
- Department of Pathology, Microbiology & Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - Andreas S. Chavez
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
- Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kaiyang Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Oi-Wa Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Shannon Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
| | - Joseph A. Cook
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | - Lisa N. Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Marie-Laurence Cossette
- Department of Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Joanna Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - Joseph DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Christopher Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Jonathan L. Dunnum
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | | | - Candice K. Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Stephan Emmrich
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Ebru Erbay
- Altos Labs, Bay Area Institute of Science, Redwood City, CA, USA
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | | | - Chris G. Faulkes
- School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Zhe Fei
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, CA, USA
| | - Steven H. Ferguson
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - Carrie J. Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - Jean-Michel Gaillard
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Eva Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Livia Gerber
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
- Australian National Wildlife Collection, CSIRO, Canberra, Australia
| | - Vadim N. Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Rodolfo G. Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Matthew J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Carla B. Green
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M. Bradley Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Daniel W. Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | | | - Andrew N. Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carolyn J. Hogg
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Timothy A. Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Taosheng Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | | | - Anna J. Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Division of Infectious Diseases, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Molecular Genetics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Gareth Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - Olga Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | | | | | - Vimala Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - Hippokratis Kiaris
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Michael S. Kobor
- Edwin S. H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Pawel Kordowitzki
- Institute of Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | | | - Michael Krützen
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
| | - Soo Bin Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Brenda Larison
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sang-Goo Lee
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Jean-François Lemaître
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Andrew J. Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xinmin Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Cun Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Andrea R. Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David T. S. Lin
- Centre for Molecular Medicine and Therapeutics, BC Children’s Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | - Thomas J. Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Julie A. Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - June Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - Jennifer J. Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin Madison, Madison, WI, USA
| | - Gisele A. Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Jason Munshi-South
- Louis Calder Center - Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
| | - Asieh Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Martina Nagy
- Museum fur Naturkunde, Leibniz-Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Pritika Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Peter W. Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Ngoc B. Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Christof Niehrs
- Institute of Molecular Biology (IMB), Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | | | - Justine K. O’Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | | | - Duncan T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Deutsches Krebsforschungszentrum, Division of Regulatory Genomics and Cancer Evolution, Heidelberg, Germany
| | | | | | - Elaine A. Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kim M. Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Kimberly C. Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Amy B. Pedersen
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Matteo Pellegrini
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Katharina J. Peters
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, New South Wales, Australia
| | | | - Darren W. Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - Gabriela M. Pinho
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jocelyn Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jesse R. Poganik
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Natalia A. Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - Pradeep Reddy
- Altos Labs, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Benjamin Rey
- University of Lyon, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - Beate R. Ritz
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | | | | | | | - Elena Rydkina
- Department of Biology, University of Rochester, Rochester, NY, USA
| | | | - Adam B. Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - Kyle M. Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Dennis Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | | | | | - Lawrence B. Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Karen E. Sears
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Aaron B.A. Shafer
- Department of Forensic Science, Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Anastasia V. Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM’S NMIMS University, Mumbai, India
| | - Ishani Sinha
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jesse Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - Russel G. Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Elham Soltanmohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | | | | | | | | | - Karen J. Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - Donald T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | | | - Balazs Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - Joseph S. Takahashi
- Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Masaki Takasugi
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Michael J. Thompson
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Bill Van Bonn
- Animal Care and Science Division, John G. Shedd Aquarium, Chicago, IL, USA
| | - Sonja C. Vernes
- School of Biology, The University of St. Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Diego Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Harry V. Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ha Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Nan Wang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Qi Yan
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Mingjia Yao
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Zhihui Zhang
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Yang Zhao
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Peng Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph A. Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrei Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Vera Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - X. William Yang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Altos Labs, Cambridge, UK
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14
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Wang X, Li W, Feng X, Li J, Liu GE, Fang L, Yu Y. Harnessing male germline epigenomics for the genetic improvement in cattle. J Anim Sci Biotechnol 2023; 14:76. [PMID: 37277852 PMCID: PMC10242889 DOI: 10.1186/s40104-023-00874-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 04/02/2023] [Indexed: 06/07/2023] Open
Abstract
Sperm is essential for successful artificial insemination in dairy cattle, and its quality can be influenced by both epigenetic modification and epigenetic inheritance. The bovine germline differentiation is characterized by epigenetic reprogramming, while intergenerational and transgenerational epigenetic inheritance can influence the offspring's development through the transmission of epigenetic features to the offspring via the germline. Therefore, the selection of bulls with superior sperm quality for the production and fertility traits requires a better understanding of the epigenetic mechanism and more accurate identifications of epigenetic biomarkers. We have comprehensively reviewed the current progress in the studies of bovine sperm epigenome in terms of both resources and biological discovery in order to provide perspectives on how to harness this valuable information for genetic improvement in the cattle breeding industry.
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Affiliation(s)
- Xiao Wang
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
- Konge Larsen ApS, Kongens Lyngby, 2800, Denmark
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Wenlong Li
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xia Feng
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Jianbing Li
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, Henry A. Wallace Beltsville Agricultural Research Center, USDA, Beltsville, MD, 20705, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, Denmark.
| | - Ying Yu
- Laboratory of Animal Genetics and Breeding, Ministry of Agriculture and Rural Affairs of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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15
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Li J, Han F, Yuan T, Li W, Li Y, Wu HX, Wei H, Niu S. The methylation landscape of giga-genome and the epigenetic timer of age in Chinese pine. Nat Commun 2023; 14:1947. [PMID: 37029142 PMCID: PMC10082083 DOI: 10.1038/s41467-023-37684-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 03/27/2023] [Indexed: 04/09/2023] Open
Abstract
Epigenetics has been revealed to play a crucial role in the long-term memory in plants. However, little is known about whether the epigenetic modifications occur with age progressively in conifers. Here, we present the single-base resolution DNA methylation landscapes of the 25-gigabase Chinese pine (Pinus tabuliformis) genome at different ages. The result shows that DNA methylation is closely coupled with the regulation of gene transcription. The age-dependent methylation profile with a linearly increasing trend is the most significant pattern of DMRs between ages. Two segments at the five-prime end of the first ultra-long intron in DAL1, a conservative age biomarker in conifers, shows a gradual decline of CHG methylation as the age increased, which is highly correlated with its expression profile. Similar high correlation is also observed in nine other age marker genes. Our results suggest that DNA methylation serves as an important epigenetic signature of developmental age in conifers.
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Affiliation(s)
- Jiang Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, PR China
| | - Fangxu Han
- National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, PR China
| | - Tongqi Yuan
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, P. R. China
| | - Wei Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, PR China
| | - Yue Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, PR China
| | - Harry X Wu
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Linnaeus väg 6, SE-901 83, Umeå, Sweden
- CSIRO National Research Collection Australia, Black Mountain Laboratory, Canberra, ACT, 2601, Australia
| | - Hairong Wei
- College of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI, 49931, USA
| | - Shihui Niu
- National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, PR China.
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16
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Robeck TR, Haghani A, Fei Z, Lindemann DM, Russell J, Herrick KES, Montano G, Steinman KJ, Katsumata E, Zoller JA, Horvath S. Multi-tissue DNA methylation aging clocks for sea lions, walruses and seals. Commun Biol 2023; 6:359. [PMID: 37005462 PMCID: PMC10067968 DOI: 10.1038/s42003-023-04734-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 03/21/2023] [Indexed: 04/04/2023] Open
Abstract
Age determination of wild animals, including pinnipeds, is critical for accurate population assessment and management. For most pinnipeds, current age estimation methodologies utilize tooth or bone sectioning which makes antemortem estimations problematic. We leveraged recent advances in the development of epigenetic age estimators (epigenetic clocks) to develop highly accurate pinniped epigenetic clocks. For clock development, we applied the mammalian methylation array to profile 37,492 cytosine-guanine sites (CpGs) across highly conserved stretches of DNA in blood and skin samples (n = 171) from primarily three pinniped species representing the three phylogenetic families: Otariidae, Phocidae and Odobenidae. We built an elastic net model with Leave-One-Out-Cross Validation (LOOCV) and one with a Leave-One-Species-Out-Cross-Validation (LOSOCV). After identifying the top 30 CpGs, the LOOCV produced a highly correlated (r = 0.95) and accurate (median absolute error = 1.7 years) age estimation clock. The LOSOCV elastic net results indicated that blood and skin clock (r = 0.84) and blood (r = 0.88) pinniped clocks could predict age of animals from pinniped species not used for clock development to within 3.6 and 4.4 years, respectively. These epigenetic clocks provide an improved and relatively non-invasive tool to determine age in skin or blood samples from all pinniped species.
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Affiliation(s)
- Todd R Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA.
- Species Preservation Lab, SeaWorld Parks and Entertainment, San Diego, CA, USA.
| | - Amin Haghani
- Department of Human Genetics, Gonda Research Center, David Geffen School of Medicine, Los Angeles, CA, USA
- Altos Labs, San Diego, USA
| | - Zhe Fei
- Department of Biostatistics, School of Public Health, University of California-Los Angeles, Los Angeles, CA, USA
| | | | | | | | - Gisele Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
- Species Preservation Lab, SeaWorld Parks and Entertainment, San Diego, CA, USA
| | - Karen J Steinman
- Species Preservation Lab, SeaWorld Parks and Entertainment, San Diego, CA, USA
| | | | - Joseph A Zoller
- Department of Biostatistics, School of Public Health, University of California-Los Angeles, Los Angeles, CA, USA
| | - Steve Horvath
- Department of Human Genetics, Gonda Research Center, David Geffen School of Medicine, Los Angeles, CA, USA.
- Altos Labs, San Diego, USA.
- Department of Biostatistics, School of Public Health, University of California-Los Angeles, Los Angeles, CA, USA.
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17
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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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18
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DNA methylation-based profiling of horse archaeological remains for age-at-death and castration. iScience 2023; 26:106144. [PMID: 36843848 PMCID: PMC9950528 DOI: 10.1016/j.isci.2023.106144] [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: 09/27/2022] [Revised: 01/02/2023] [Accepted: 02/01/2023] [Indexed: 02/07/2023] Open
Abstract
Age profiling of archaeological bone assemblages can inform on past animal management practices, but is limited by the fragmentary nature of the fossil record and the lack of universal skeletal markers for age. DNA methylation clocks offer new, albeit challenging, alternatives for estimating the age-at-death of ancient individuals. Here, we take advantage of the availability of a DNA methylation clock based on 31,836 CpG sites and dental age markers in horses to assess age predictions in 84 ancient remains. We evaluate our approach using whole-genome sequencing data and develop a capture assay providing reliable estimates for only a fraction of the cost. We also leverage DNA methylation patterns to assess castration practice in the past. Our work opens for a deeper characterization of past husbandry and ritual practices and holds the potential to reveal age mortality profiles in ancient societies, once extended to human remains.
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19
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DeNotta S, McFarlane D. Immunosenescence and inflammaging in the aged horse. Immun Ageing 2023; 20:2. [PMID: 36609345 PMCID: PMC9817422 DOI: 10.1186/s12979-022-00325-5] [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: 11/28/2022] [Accepted: 12/21/2022] [Indexed: 01/09/2023]
Abstract
The equine population in the United States and worldwide now includes a higher percentage of geriatric horses than ever previously recorded, and as methods to treat and manage elderly equids are developed and refined, this aging population will likely continue to expand. A better understanding of how horses age and the effect of age on immunity and disease susceptibility is needed to enable targeted preventative healthcare strategies for aged horses. This review article outlines the current state of knowledge regarding the effect of aging on immunity, vaccine responsiveness, and disease risk in the horse, highlighting similarities and differences to what is observed in aged humans. Horses show similar but milder age-related alterations in immune function to those reported in people. Decreases in lymphocyte proliferation and antibody production and diminished response to vaccination have all been documented in elderly horses, however, increased risk of infectious disease is not commonly reported. Aged horses also show evidence of a proinflammatory state (inflammaging) yet appear less susceptible to the chronic diseases of people for which inflammation is a risk factor. Information is currently lacking as to why the horse does not experience the same risk of age-related disease (e.g., cancer, heart disease, neurodegeneration) as people, although a lack of negative lifestyle habits, differences in diet, exercise, genetics and physiology may all contribute to improved health outcomes in the older horse.
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Affiliation(s)
- Sally DeNotta
- grid.15276.370000 0004 1936 8091Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL USA
| | - Dianne McFarlane
- grid.15276.370000 0004 1936 8091Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL USA
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20
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Cai Y, Song W, Li J, Jing Y, Liang C, Zhang L, Zhang X, Zhang W, Liu B, An Y, Li J, Tang B, Pei S, Wu X, Liu Y, Zhuang CL, Ying Y, Dou X, Chen Y, Xiao FH, Li D, Yang R, Zhao Y, Wang Y, Wang L, Li Y, Ma S, Wang S, Song X, Ren J, Zhang L, Wang J, Zhang W, Xie Z, Qu J, Wang J, Xiao Y, Tian Y, Wang G, Hu P, Ye J, Sun Y, Mao Z, Kong QP, Liu Q, Zou W, Tian XL, Xiao ZX, Liu Y, Liu JP, Song M, Han JDJ, Liu GH. The landscape of aging. SCIENCE CHINA. LIFE SCIENCES 2022; 65:2354-2454. [PMID: 36066811 PMCID: PMC9446657 DOI: 10.1007/s11427-022-2161-3] [Citation(s) in RCA: 101] [Impact Index Per Article: 50.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/05/2022] [Indexed: 02/07/2023]
Abstract
Aging is characterized by a progressive deterioration of physiological integrity, leading to impaired functional ability and ultimately increased susceptibility to death. It is a major risk factor for chronic human diseases, including cardiovascular disease, diabetes, neurological degeneration, and cancer. Therefore, the growing emphasis on "healthy aging" raises a series of important questions in life and social sciences. In recent years, there has been unprecedented progress in aging research, particularly the discovery that the rate of aging is at least partly controlled by evolutionarily conserved genetic pathways and biological processes. In an attempt to bring full-fledged understanding to both the aging process and age-associated diseases, we review the descriptive, conceptual, and interventive aspects of the landscape of aging composed of a number of layers at the cellular, tissue, organ, organ system, and organismal levels.
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Affiliation(s)
- Yusheng Cai
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Wei Song
- Frontier Science Center for Immunology and Metabolism, Medical Research Institute, College of Life Sciences, Wuhan University, Wuhan, 430071, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ying Jing
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chuqian Liang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Liyuan Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Xia Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Wenhui Zhang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Beibei Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Yongpan An
- Peking University International Cancer Institute, Peking University Health Science Center, Peking University, Beijing, 100191, China
| | - Jingyi Li
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Baixue Tang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Siyu Pei
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xueying Wu
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yuxuan Liu
- School of Pharmaceutical Sciences, Beijing Advanced Innovation Center for Structural Biology, Ministry of Education Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Tsinghua University, Beijing, 100084, China
| | - Cheng-Le Zhuang
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital Affiliated to Tongji University, Shanghai, 200072, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiaotong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Xuefeng Dou
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Fu-Hui Xiao
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
| | - Dingfeng Li
- Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ya Zhao
- Aging and Vascular Diseases, Human Aging Research Institute (HARI) and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Human Aging, Nanchang, 330031, China
| | - Yang Wang
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China
| | - Lihui Wang
- Institute of Ageing Research, Hangzhou Normal University, School of Basic Medical Sciences, Hangzhou, 311121, China
| | - Yujing Li
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Shuai Ma
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Si Wang
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- The Fifth People's Hospital of Chongqing, Chongqing, 400062, China.
| | - Xiaoyuan Song
- MOE Key Laboratory of Cellular Dynamics, Hefei National Research Center for Physical Sciences at the Microscale, CAS Key Laboratory of Brain Function and Disease, Neurodegenerative Disorder Research Center, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.
| | - Jie Ren
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Liang Zhang
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Jun Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Peking University Health Science Center, Peking University, Beijing, 100191, China.
| | - Jing Qu
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jianwei Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Ye Tian
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Gelin Wang
- School of Pharmaceutical Sciences, Beijing Advanced Innovation Center for Structural Biology, Ministry of Education Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Tsinghua University, Beijing, 100084, China.
| | - Ping Hu
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Colorectal Cancer Center/Department of Gastrointestinal Surgery, Shanghai Tenth People's Hospital Affiliated to Tongji University, Shanghai, 200072, China.
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, 510005, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiaotong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, 98195, USA.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Qing-Peng Kong
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Qiang Liu
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Xiao-Li Tian
- Aging and Vascular Diseases, Human Aging Research Institute (HARI) and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Human Aging, Nanchang, 330031, China.
| | - Zhi-Xiong Xiao
- Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resource and Eco-Environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610065, China.
| | - Yong Liu
- Frontier Science Center for Immunology and Metabolism, Medical Research Institute, College of Life Sciences, Wuhan University, Wuhan, 430071, China.
| | - Jun-Ping Liu
- Institute of Ageing Research, Hangzhou Normal University, School of Basic Medical Sciences, Hangzhou, 311121, China.
- Department of Immunology and Pathology, Monash University Faculty of Medicine, Prahran, Victoria, 3181, Australia.
- Hudson Institute of Medical Research, and Monash University Department of Molecular and Translational Science, Clayton, Victoria, 3168, Australia.
| | - Moshi Song
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology, Peking University, Beijing, 100871, China.
| | - Guang-Hui Liu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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21
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Ribeiro AMF, Sanglard LP, Wijesena HR, Ciobanu DC, Horvath S, Spangler ML. DNA methylation profile in beef cattle is influenced by additive genetics and age. Sci Rep 2022; 12:12016. [PMID: 35835812 PMCID: PMC9283455 DOI: 10.1038/s41598-022-16350-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/08/2022] [Indexed: 11/15/2022] Open
Abstract
DNA methylation (DNAm) has been considered a promising indicator of biological age in mammals and could be useful to increase the accuracy of phenotypic prediction in livestock. The objectives of this study were to estimate the heritability and age effects of site-specific DNAm (DNAm level) and cumulative DNAm across all sites (DNAm load) in beef cattle. Blood samples were collected from cows ranging from 217 to 3,192 days (0.6 to 8.7 years) of age (n = 136). All animals were genotyped, and DNAm was obtained using the Infinium array HorvathMammalMethylChip40. Genetic parameters for DNAm were obtained from an animal model based on the genomic relationship matrix, including the fixed effects of age and breed composition. Heritability estimates of DNAm levels ranged from 0.18 to 0.72, with a similar average across all regions and chromosomes. Heritability estimate of DNAm load was 0.45. The average age effect on DNAm level varied among genomic regions. The DNAm level across the genome increased with age in the promoter and 5′ UTR and decreased in the exonic, intronic, 3′ UTR, and intergenic regions. In addition, DNAm level increased with age in regions enriched in CpG and decreased in regions deficient in CpG. Results suggest DNAm profiles are influenced by both genetics and the environmental effect of age in beef cattle.
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Affiliation(s)
| | - Leticia P Sanglard
- Department of Animal Science, University of Nebraska, Lincoln, NE, 68583, USA
| | - Hiruni R Wijesena
- Department of Animal Science, University of Nebraska, Lincoln, NE, 68583, USA
| | - Daniel C Ciobanu
- Department of Animal Science, University of Nebraska, Lincoln, NE, 68583, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. .,Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA.
| | - Matthew L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, 68583, USA.
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22
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Kingsley NB, Sandmeyer L, Bellone RR. A review of investigated risk factors for developing equine recurrent uveitis. Vet Ophthalmol 2022; 26:86-100. [PMID: 35691017 DOI: 10.1111/vop.13002] [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: 03/03/2022] [Revised: 04/25/2022] [Accepted: 05/27/2022] [Indexed: 12/01/2022]
Abstract
Equine recurrent uveitis (ERU) is an ocular inflammatory disease that can be difficult to manage clinically. As such, it is the leading cause of bilateral blindness for horses. ERU is suspected to have a complex autoimmune etiology with both environmental and genetic risk factors contributing to onset and disease progression in some or all cases. Work in recent years has aimed at unraveling the primary triggers, such as infectious agents and inherited breed-specific risk factors, for disease onset, persistence, and progression. This review has aimed at encompassing those factors that have been associated, implicated, or substantiated as contributors to ERU, as well as identifying areas for which additional knowledge is needed to better understand risk for disease onset and progression. A greater understanding of the risk factors for ERU will enable earlier detection and better prognosis through prevention and new therapeutics.
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Affiliation(s)
- Nicole B Kingsley
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California - Davis, Davis, California, USA.,Department of Population Health and Reproduction, School of Veterinary Medicine, University of California - Davis, Davis, California, USA
| | - Lynne Sandmeyer
- Department of Small Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Rebecca R Bellone
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California - Davis, Davis, California, USA.,Department of Population Health and Reproduction, School of Veterinary Medicine, University of California - Davis, Davis, California, USA
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23
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Seale K, Horvath S, Teschendorff A, Eynon N, Voisin S. Making sense of the ageing methylome. Nat Rev Genet 2022; 23:585-605. [PMID: 35501397 DOI: 10.1038/s41576-022-00477-6] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2022] [Indexed: 12/22/2022]
Abstract
Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.
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Affiliation(s)
- Kirsten Seale
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Altos Labs, San Diego, CA, USA
| | - Andrew Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, China.,UCL Cancer Institute, University College London, London, UK
| | - Nir Eynon
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia.
| | - Sarah Voisin
- Institute for Health and Sport (iHeS), Victoria University, Footscray, Melbourne, Victoria, Australia.
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24
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Epigenetic clock and methylation studies in marsupials: opossums, Tasmanian devils, kangaroos, and wallabies. GeroScience 2022; 44:1825-1845. [PMID: 35449380 PMCID: PMC9213610 DOI: 10.1007/s11357-022-00569-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 04/10/2022] [Indexed: 11/13/2022] Open
Abstract
The opossum (Monodelphis domestica), with its sequenced genome, ease of laboratory care and experimental manipulation, and unique biology, is the most used laboratory marsupial. Using the mammalian methylation array, we generated DNA methylation data from n = 100 opossum samples from the ear, liver, and tail. We contrasted postnatal development and later aging effects in the opossum methylome with those in mouse (Mus musculus, C57BL/6 J strain) and other marsupial species such as Tasmanian devil, kangaroos, and wallabies. While the opossum methylome is similar to that of mouse during postnatal development, it is distinct from that shared by other mammals when it comes to the age-related gain of methylation at target sites of polycomb repressive complex 2. Our immunohistochemical staining results provide additional support for the hypothesis that PRC2 activity increases with later aging in mouse tissues but remains constant in opossum tissues. We present several epigenetic clocks for opossums that are distinguished by their compatibility with tissue type (pan-tissue and blood clock) and species (opossum and human). Two dual-species human-opossum pan-tissue clocks accurately measure chronological age and relative age, respectively. The human-opossum epigenetic clocks are expected to provide a significant boost to the attractiveness of opossum as a biological model. Additional epigenetic clocks for Tasmanian devil, red kangaroos and other species of the genus Macropus may aid species conservation efforts.
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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: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [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.
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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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