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Choudhary RK, Kumar B. V. S, Sekhar Mukhopadhyay C, Kashyap N, Sharma V, Singh N, Salajegheh Tazerji S, Kalantari R, Hajipour P, Singh Malik Y. Animal Wellness: The Power of Multiomics and Integrative Strategies: Multiomics in Improving Animal Health. Vet Med Int 2024; 2024:4125118. [PMID: 39484643 PMCID: PMC11527549 DOI: 10.1155/2024/4125118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/01/2024] [Accepted: 09/05/2024] [Indexed: 11/03/2024] Open
Abstract
The livestock industry faces significant challenges, with disease outbreaks being a particularly devastating issue. These diseases can disrupt the food supply chain and the livelihoods of those involved in the sector. To address this, there is a growing need to enhance the health and well-being of livestock animals, ultimately improving their performance while minimizing their environmental impact. To tackle the considerable challenge posed by disease epidemics, multiomics approaches offer an excellent opportunity for scientists, breeders, and policymakers to gain a comprehensive understanding of animal biology, pathogens, and their genetic makeup. This understanding is crucial for enhancing the health of livestock animals. Multiomic approaches, including phenomics, genomics, epigenomics, metabolomics, proteomics, transcriptomics, microbiomics, and metaproteomics, are widely employed to assess and enhance animal health. High-throughput phenotypic data collection allows for the measurement of various fitness traits, both discrete and continuous, which, when mathematically combined, define the overall health and resilience of animals, including their ability to withstand diseases. Omics methods are routinely used to identify genes involved in host-pathogen interactions, assess fitness traits, and pinpoint animals with disease resistance. Genome-wide association studies (GWAS) help identify the genetic factors associated with health status, heat stress tolerance, disease resistance, and other health-related characteristics, including the estimation of breeding value. Furthermore, the interaction between hosts and pathogens, as observed through the assessment of host gut microbiota, plays a crucial role in shaping animal health and, consequently, their performance. Integrating and analyzing various heterogeneous datasets to gain deeper insights into biological systems is a challenging task that necessitates the use of innovative tools. Initiatives like MiBiOmics, which facilitate the visualization, analysis, integration, and exploration of multiomics data, are expected to improve prediction accuracy and identify robust biomarkers linked to animal health. In this review, we discuss the details of multiomics concerning the health and well-being of livestock animals.
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Affiliation(s)
- Ratan Kumar Choudhary
- Department of Bioinformatics, Animal Stem Cells Laboratory, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Sunil Kumar B. V.
- Department of Animal Biotechnology, Proteomics & Metabolomics Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Chandra Sekhar Mukhopadhyay
- Department of Bioinformatics, Genomics Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Neeraj Kashyap
- Department of Bioinformatics, Genomics Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Vishal Sharma
- Department of Animal Biotechnology, Reproductive Biotechnology Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Nisha Singh
- Department of Bioinformatics, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
| | - Sina Salajegheh Tazerji
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Roozbeh Kalantari
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Pouneh Hajipour
- Department of Avian Diseases, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran
- Department of Clinical Science, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Yashpal Singh Malik
- Department of Microbial and Environmental Biotechnology, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana 141004, Punjab, India
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Botelho ME, Lopes MS, Mathur PK, Knol EF, e Silva FF, Lopes PS, Gimarães SEF, Marques DB, Veroneze R. Weighted genome-wide association study reveals new candidate genes related to boar taint compounds 1. Livest Sci 2022. [DOI: 10.1016/j.livsci.2022.104845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Ibeagha-Awemu EM, Yu Y. Consequence of epigenetic processes on animal health and productivity: is additional level of regulation of relevance? Anim Front 2021; 11:7-18. [PMID: 34934525 PMCID: PMC8683131 DOI: 10.1093/af/vfab057] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, Canada
| | - Ying Yu
- Department of Animal Breeding and Genetics, College of Animal Sciences and Technology, China Agricultural University, Beijing, China
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Rabaglino MB, Bojsen-Møller Secher J, Sirard MA, Hyttel P, Kadarmideen HN. Epigenomic and transcriptomic analyses reveal early activation of the HPG axis in in vitro-produced male dairy calves. FASEB J 2021; 35:e21882. [PMID: 34460963 DOI: 10.1096/fj.202101067r] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/03/2021] [Accepted: 08/12/2021] [Indexed: 12/13/2022]
Abstract
In cattle, several calves born after IVP ("in vitro" embryo production) present similar birthweight to those generated after MOET (multiple ovulation and embryo transfer). However, the underlying molecular patterns in organs involved in the developmental process are unknown and could indicate physiological programming. The objectives of this study were: (1) to compare epigenomic and transcriptomic modifications in the hypothalamus, pituitary, gonadal and adrenal organs between 3 months old ovum pick-up-IVP and MOET male calves (n = 4 per group) and (2) to use blood epigenomic data to proxy methylation of the inner organs. Extracted gDNA and RNA were sequenced through whole-genome bisulfite sequencing and RNA sequencing, respectively. Next, bioinformatic analyses determined differentially methylated cytosines (DMC) and differentially expressed genes (DEG) (FDR < 0.05) in IVP versus MOET samples and the KEGG pathways that were overrepresented by genes associated with DMC or DEG (FDR < 0.1). Pathways related to hypothalamus, pituitary, gonadal (HPG) axis activation (GnRH secretion in the hypothalamus, GnRH signaling in the pituitary, and steroidogenesis in the testicle) were enriched in IVP calves. Modeling the effect of the methylation levels and the group on the expression of all the genes involved in these pathways confirmed their upregulation in HPG organs in IVP calves. The application of the DIABLO method allowed the identification of 15 epigenetic and five transcriptomic biomarkers, which were able to predict the embryo origin using the epigenomic data from the blood. In conclusion, the use of an integrated epigenomic-transcriptomic approach suggested an early activation of the HPG axis in male IVP calves compared to MOET counterparts, and the identification of potential biomarkers allowed the use of blood samples to proxy methylation levels of the relevant internal organs.
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Affiliation(s)
- María B Rabaglino
- Quantitative Genetics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
| | | | - Marc-André Sirard
- Departement des Sciences Animales, Centre de Recherche en Reproduction, Développement et Santé Inter-générationnelle (CRDSI), Université Laval, Laval, Quebec, Canada
| | - Poul Hyttel
- Department of Veterinary Clinical Sciences, University of Copenhagen, Frederiksberg, Denmark
| | - Haja N Kadarmideen
- Quantitative Genetics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark
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Wang M, Ibeagha-Awemu EM. Impacts of Epigenetic Processes on the Health and Productivity of Livestock. Front Genet 2021; 11:613636. [PMID: 33708235 PMCID: PMC7942785 DOI: 10.3389/fgene.2020.613636] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 12/21/2020] [Indexed: 12/23/2022] Open
Abstract
The dynamic changes in the epigenome resulting from the intricate interactions of genetic and environmental factors play crucial roles in individual growth and development. Numerous studies in plants, rodents, and humans have provided evidence of the regulatory roles of epigenetic processes in health and disease. There is increasing pressure to increase livestock production in light of increasing food needs of an expanding human population and environment challenges, but there is limited related epigenetic data on livestock to complement genomic information and support advances in improvement breeding and health management. This review examines the recent discoveries on epigenetic processes due to DNA methylation, histone modification, and chromatin remodeling and their impacts on health and production traits in farm animals, including bovine, swine, sheep, goat, and poultry species. Most of the reports focused on epigenome profiling at the genome-wide or specific genic regions in response to developmental processes, environmental stressors, nutrition, and disease pathogens. The bulk of available data mainly characterized the epigenetic markers in tissues/organs or in relation to traits and detection of epigenetic regulatory mechanisms underlying livestock phenotype diversity. However, available data is inadequate to support gainful exploitation of epigenetic processes for improved animal health and productivity management. Increased research effort, which is vital to elucidate how epigenetic mechanisms affect the health and productivity of livestock, is currently limited due to several factors including lack of adequate analytical tools. In this review, we (1) summarize available evidence of the impacts of epigenetic processes on livestock production and health traits, (2) discuss the application of epigenetics data in livestock production, and (3) present gaps in livestock epigenetics research. Knowledge of the epigenetic factors influencing livestock health and productivity is vital for the management and improvement of livestock productivity.
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Affiliation(s)
- Mengqi Wang
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada
- Department of Animal Science, Laval University, Quebec, QC, Canada
| | - Eveline M. Ibeagha-Awemu
- Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada
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Recent genetic advances on boar taint reduction as an alternative to castration: a review. J Appl Genet 2021; 62:137-150. [PMID: 33405214 PMCID: PMC7822767 DOI: 10.1007/s13353-020-00598-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 11/17/2020] [Accepted: 11/23/2020] [Indexed: 11/28/2022]
Abstract
Boar taint is an unpleasant odor in male pig meat, mainly caused by androstenone, skatole, and indole, which are deposited in the fat tissue. Piglet castration is the most common practice to prevent boar taint. However, castration is likely to be banished in a few years due to animal welfare concerns. Alternatives to castration, such as genetic selection, have been assessed. Androstenone and skatole have moderate to high heritability, which makes it feasible to select against these compounds. This review presents the latest results obtained on genetic selection against boar taint, on correlation with other traits, on differences in breeds, and on candidate genes related to boar taint. QTLs for androstenone and skatole have been reported mainly on chromosomes 6, 7, and 14. These chromosomes were reported to contain genes responsible for synthesis and degradation of androstenone and skatole. A myriad of work has been done to find markers or genes that can be used to select animals with lower boar taint. The selection against boar taint could decrease performance of some reproduction traits. However, a favorable response on production traits has been observed by selecting against boar taint. Selection results have shown that it is possible to reduce boar taint in few generations. In addition, modifications in diet and environment conditions could be associated with genetic selection to reduce boar taint. Nevertheless, costs to measure and select against boar taint should be rewarded with incentives from the market; otherwise, it would be difficult to implement genetic selection.
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Wang X, Hao D, Kadarmideen HN. GeneDMRs: An R Package for Gene-Based Differentially Methylated Regions Analysis. J Comput Biol 2020; 28:304-316. [PMID: 33185472 PMCID: PMC7994424 DOI: 10.1089/cmb.2020.0081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
DNA methylation in gene or gene body could influence gene transcription. Moreover, methylation in gene regions along with CpG island regions could modulate the transcription to undetectable gene expression levels. Therefore, it is necessary to investigate the methylation levels within the gene, gene body, CpG island regions, and their overlapped regions and then identify the gene-based differentially methylated regions (GeneDMRs). In this study, R package GeneDMRs aims to facilitate computing gene-based methylation rate using next-generation sequencing-based methylome data. The user-friendly GeneDMRs package is presented to analyze the methylation levels in each gene/promoter/exon/intron/CpG island/CpG island shore or each overlapped region (e.g., gene-CpG island/promoter-CpG island/exon-CpG island/intron-CpG island/gene-CpG island shore/promoter-CpG island shore/exon-CpG island shore/intron-CpG island shore). GeneDMRs can also interpret complex interplays between methylation levels and gene expression differences or similarities across physiological conditions or disease states. We used the public reduced representation bisulfite sequencing data of mouse (GSE62392) for evaluating software and revealing novel biologically significant results to supplement the previous research. In addition, the whole-genome bisulfite sequencing data of cattle (GSE106538) given the much larger size was used for further evaluation.
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Affiliation(s)
- Xiao Wang
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Dan Hao
- College of Animal Science and Technology, Northwest A&F University, Yangling, China.,Department of Molecular Biology and Genetics, Aarhus University, Aarhus C, Denmark
| | - Haja N Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
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Pértille F, Ibelli AMG, Sharif ME, Poleti MD, Fröhlich AS, Rezaei S, Ledur MC, Jensen P, Guerrero-Bosagna C, Coutinho LL. Putative Epigenetic Biomarkers of Stress in Red Blood Cells of Chickens Reared Across Different Biomes. Front Genet 2020; 11:508809. [PMID: 33240310 PMCID: PMC7667380 DOI: 10.3389/fgene.2020.508809] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 09/11/2020] [Indexed: 12/19/2022] Open
Abstract
Production animals are constantly subjected to early adverse environmental conditions that influence the adult phenotype and produce epigenetic effects. CpG dinucleotide methylation in red blood cells (RBC) could be a useful epigenetic biomarker to identify animals subjected to chronic stress in the production environment. Here we compared a reduced fraction of the RBC methylome of chickens exposed to social isolation to non-exposed. These experiments were performed in two different locations: Brazil and Sweden. The aim was to identify stress-associated DNA methylation profiles in RBC across these populations, in spite of the variable conditions to which birds are exposed in each facility and their different lineages. Birds were increasingly exposed to a social isolation treatment, combined with food and water deprivation, at random periods of the day from weeks 1-4 after hatching. We then collected the RBC DNA from individuals and compared a reduced fraction of their methylome between the experimental groups using two bioinformatic approaches to identify differentially methylated regions (DMRs): one using fixed-size windows and another that preselected differential peaks with MACS2. Three levels of significance were used (P ≤ 0.05, P ≤ 0.005, and P ≤ 0.0005) to identify DMRs between experimental groups, which were then used for different analyses. With both of the approaches more DMRs reached the defined significance thresholds in BR individuals compared to SW. However, more DMRs had higher fold change values in SW compared to BR individuals. Interestingly, ChrZ was enriched above expectancy for the presence of DMRs. Additionally, when analyzing the locations of these DMRs in relation to the transcription starting site (TSS), we found three peaks with high DMR presence: 10 kb upstream, the TSS itself, and 20-40 kb downstream. Interestingly, these peaks had DMRs with a high presence (>50%) of specific transcription factor binding sites. Three overlapping DMRs were found between the BR and SW population using the most relaxed p-value (P ≤ 0.05). With the most stringent p-value (P ≤ 0.0005), we found 7 and 4 DMRs between treatments in the BR and SW populations, respectively. This study is the first approximation to identify epigenetic biomarkers of long-term exposure to stress in different lineages of production animals.
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Affiliation(s)
- Fábio Pértille
- Animal Biotechnology Laboratory, Animal Science and Pastures Department, University of São Paulo (USP)/"Luiz de Queiroz" College of Agriculture (ESALQ), Piracicaba, Brazil.,Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | | | - Maj El Sharif
- Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - Mirele Daiana Poleti
- Animal Science Program, Faculty of Animal Science and Food Engineering (FZEA), University of São Paulo (USP), Pirassununga, Brazil
| | - Anna Sophie Fröhlich
- Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - Shiva Rezaei
- Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | | | - Per Jensen
- Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden
| | - Carlos Guerrero-Bosagna
- Avian Behavioural Genomics and Physiology Group, IFM Biology, Linköping University, Linköping, Sweden.,Evolutionary Biology Centre, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Luiz Lehmann Coutinho
- Animal Biotechnology Laboratory, Animal Science and Pastures Department, University of São Paulo (USP)/"Luiz de Queiroz" College of Agriculture (ESALQ), Piracicaba, Brazil
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Wang X, Kadarmideen HN. Characterization of Global DNA Methylation in Different Gene Regions Reveals Candidate Biomarkers in Pigs with High and Low Levels of Boar Taint. Vet Sci 2020; 7:E77. [PMID: 32545802 PMCID: PMC7356388 DOI: 10.3390/vetsci7020077] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 06/09/2020] [Indexed: 12/11/2022] Open
Abstract
DNA methylation of different gene components, including different exons and introns, or different lengths of exons and introns is associated with differences in gene expression. To investigate the methylation of porcine gene components associated with the boar taint (BT) trait, this study used reduced representation bisulfite sequencing (RRBS) data from nine porcine testis samples in three BT groups (low, medium and high BT). The results showed that the methylation levels of the first exons and first introns were lower than those of the other exons and introns. The first exons/introns of CpG island regions had even lower levels of methylation. A total of 123 differentially methylated promoters (DMPs), 194 differentially methylated exons (DMEs) and 402 differentially methylated introns (DMIs) were identified, of which 80 DMPs (DMP-CpGis), 112 DMEs (DME-CpGis) and 166 DMIs (DMI-CpGis) were discovered in CpG islands. Importantly, GPX1 contained one each of DMP, DME, DMI, DMP-CpGi, DME-CpGi and DMI-CpGi. Gene-GO term relationships and pathways analysis showed DMP-CpGi-related genes are mainly involved in methylation-related biological functions. In addition, gene-gene interaction networks consisted of nodes that were hypo-methylated GPX1, hypo-methylated APP, hypo-methylated ATOX1, hyper-methylated ADRB2, hyper-methylated RPS6KA1 and hyper-methylated PNMT. They could be used as candidate biomarkers for reducing boar taint in pigs, after further validation in large cohorts.
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Affiliation(s)
| | - Haja N. Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark;
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