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Zhao Z, Wang S, Wang K, Ji X, Chen D, Shen Q, Yu Y, Cui S, Wang J, Chen Z, Tang G. Transcriptome analysis of liver and ileum reveals potential regulation of long non-coding RNA in pigs with divergent feed efficiency. Anim Biosci 2025; 38:588-599. [PMID: 39483020 PMCID: PMC11917451 DOI: 10.5713/ab.24.0434] [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: 06/25/2024] [Revised: 08/23/2024] [Accepted: 09/18/2024] [Indexed: 11/03/2024] Open
Abstract
OBJECTIVE Long non-coding RNA (LncRNA) plays a significant role in regulating feed efficiency. This study aims to explore the key lncRNAs, associated genes, and pathways in pigs with extreme feed efficiencies. METHODS We screened pigs with extremely high and low residual feed intake through a 12-week animal growth trial and then conducted transcriptome analysis on their liver and ileum tissues. We analyzed the differential expressed lncRNAs, microRNAs (miRNAs), and messenger RNAs through target gene prediction and functional analysis. And we identified key lncRNAs and their potential regulatory genes associated with feed efficiency through the construction of competitive endogenous RNA network. RESULTS Differentially expressed lncRNAs were pinpointed in the liver, revealing 23 crucial target genes primarily associated with guanosine triphosphate metabolism and glycolipid biosynthesis. In the ileum, a screening identified 92 pivotal target genes, mainly linked to lipid and small molecule metabolism. Moreover, LOC106504303 and LOC102160805 emerged as potentially significant lncRNAs respectively, playing roles in mitochondrial oxidative phosphorylation in the liver, and lipid and cholesterol metabolism in the ileum. CONCLUSION The lncRNAs regulate energy metabolism and biosynthesis in the liver, and the digestive absorption capacity in the small intestine, affecting the feed efficiency of pigs.
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Affiliation(s)
- Zhenjian Zhao
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Shujie Wang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Kai Wang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Xiang Ji
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Dong Chen
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Qi Shen
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Yang Yu
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Shendi Cui
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Junge Wang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Ziyang Chen
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
| | - Guoqing Tang
- Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130,
China
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130,
China
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Jilo DD, Abebe BK, Wang J, Guo J, Li A, Zan L. Long non-coding RNA (LncRNA) and epigenetic factors: their role in regulating the adipocytes in bovine. Front Genet 2024; 15:1405588. [PMID: 39421300 PMCID: PMC11484070 DOI: 10.3389/fgene.2024.1405588] [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: 03/23/2024] [Accepted: 09/02/2024] [Indexed: 10/19/2024] Open
Abstract
Investigating the involvement of long non-coding RNAs (lncRNAs) and epigenetic processes in bovine adipocytes can provide valuable new insights into controlling adipogenesis in livestock. Long non-coding RNAs have been associated with forming chromatin loops that facilitate enhancer-promoter interactions during adipogenesis, as well as regulating important adipogenic transcription factors like C/EBPα and PPARγ. They significantly influence gene expression regulation at the post-transcriptional level and are extensively researched for their diverse roles in cellular functions. Epigenetic modifications such as chromatin reorganization, histone alterations, and DNA methylation subsequently affect the activation of genes related to adipogenesis and the progression of adipocyte differentiation. By investigating how fat deposition is epigenetically regulated in beef cattle, scientists aim to unravel molecular mechanisms, identify key regulatory genes and pathways, and develop targeted strategies for modifying fat deposition to enhance desirable traits such as marbling and meat tenderness. This review paper delves into lncRNAs and epigenetic factors and their role in regulating bovine adipocytes while focusing on their potential as targets for genetic improvement to increase production efficiency. Recent genomics advancements, including molecular markers and genetic variations, can boost animal productivity, meeting global demands for high-quality meat products. This review establishes a foundation for future research on understanding regulatory networks linked to lncRNAs and epigenetic changes, contributing to both scholarly knowledge advancement and practical applications within animal agriculture.
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Affiliation(s)
- Diba Dedacha Jilo
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Department of Animal Science, Bule Hora University, Bule Hora, Ethiopia
| | - Belete Kuraz Abebe
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Department of Animal Science, Werabe University, Werabe, Ethiopia
| | - Jianfang Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Juntao Guo
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Anning Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- National Beef Cattle Improvement Center, Northwest A&F University, Yangling, Shaanxi, China
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3
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Hofman B, Szyda J, Frąszczak M, Mielczarek M. Long non-coding RNA variability in porcine skeletal muscle. J Appl Genet 2024; 65:565-573. [PMID: 38539022 DOI: 10.1007/s13353-024-00860-5] [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: 11/05/2023] [Revised: 01/14/2024] [Accepted: 03/21/2024] [Indexed: 08/09/2024]
Abstract
Recently, numerous studies including various tissues have been carried out on long non-coding RNAs (lncRNAs), but still, its variability has not yet been fully understood. In this study, we characterised the inter-individual variability of lncRNAs in pigs, in the context of number, length and expression. Transcriptomes collected from muscle tissue belonging to six Polish Landrace boars (PL1-PL6), including half-brothers (PL1-PL3), were investigated using bioinformatics (lncRNA identification and functional analysis) and statistical (lncRNA variability) methods. The number of lncRNA ranged from 1289 to 3500 per animal, and the total number of common lncRNAs among all boars was 232. The number, length and expression of lncRNAs significantly varied between individuals, and no consistent pattern has been found between pairs of half-brothers. In detail, PL5 exhibits lower expression than the others, while PL4 has significantly higher expression than PL2-PL3 and PL5-PL6. Noteworthy, comparing the inter-individual variability of lncRNA and mRNA expression, they exhibited concordant patterns. The enrichment analysis for common lncRNA target genes determined a variety of biological processes that play fundamental roles in cell biology, and they were mostly related to whole-body homeostasis maintenance, energy and protein synthesis as well as dynamics of multiple nucleoprotein complexes. The high variability of lncRNA landscape in the porcine genome has been revealed in this study. The inter-individual differences have been found in the context of three aspects: the number, length and expression of lncRNAs, which contribute to a better understanding of its complex nature.
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Affiliation(s)
- Bartłomiej Hofman
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland
| | - Joanna Szyda
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland
| | - Magdalena Frąszczak
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland
| | - Magda Mielczarek
- Biostatistics Group, Department of Genetics, Wroclaw University of Environmental and Life Sciences, Kozuchowska 7, 51-631, Wroclaw, Poland.
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4
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Wang M, Bissonnette N, Laterrière M, Dudemaine PL, Gagné D, Roy JP, Sirard MA, Ibeagha-Awemu EM. Gene co-expression in response to Staphylococcus aureus infection reveals networks of genes with specific functions during bovine subclinical mastitis. J Dairy Sci 2023; 106:5517-5536. [PMID: 37291036 DOI: 10.3168/jds.2022-22757] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 02/08/2023] [Indexed: 06/10/2023]
Abstract
Staphylococcus aureus is one of the most prevalent contagious bacterial pathogen of bovine mastitis. The subclinical mastitis it causes has long-term economic implications and it is difficult to control. To further understanding of the genetic basis of mammary gland defense against S. aureus infection, the transcriptomes of milk somatic cells from 15 cows with persistent natural S. aureus infection (S. aureus-positive, SAP) and 10 healthy control cows (HC) were studied by deep RNA-sequencing technology. Comparing the transcriptomes of SAP to HC group revealed 4,077 differentially expressed genes (DEG; 1,616 up- and 2,461 downregulated). Functional annotation indicated enrichment of DEG in 94 Gene Ontology (GO) and 47 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Terms related to the immune response and disease processes were mostly enriched for by upregulated DEG, whereas biological process terms related to cell adhesion, cell movement and localization, and tissue development were mostly enriched for by downregulated DEG. Weighted gene co-expression network analysis grouped DEG into 7 modules, the most important module (colored turquoise by software and here referred to as Turquoise module) was positively significantly correlated with S. aureus subclinical mastitis. The 1,546 genes in the Turquoise module were significantly enriched in 48 GO terms and 72 KEGG pathways, with 80% of them being disease- and immune-related terms [e.g., immune system process (GO:0002376), cytokine-cytokine receptor interaction (bta04060) and S. aureus infection (bta05150)]. Some DEG such as IFNG, IL18, IL1B, NFKB1, CXCL8, and IL12B were enriched in immune and disease pathways suggesting their possible involvement in the regulation of the host response to S. aureus infection. Four modules (Yellow, Brown, Blue, and Red) were negatively correlated (significantly) with S. aureus subclinical mastitis, and were enriched in functional annotations involved in the regulation of cell migration, cell communication, metabolic process, and blood circulatory system development, respectively. Application of sparse partial least squares discriminant analysis to genes of the Turquoise module identified 5 genes (NR2F6, PDLIM5, RAB11FIP5, ACOT4, and TMEM53) capable of explaining the majority of the differences in the expression patterns between SAP and HC cows. In conclusion, this study has furthered understanding of the genetic changes in the mammary gland and the molecular mechanisms underlying S. aureus mastitis, as well as revealed a list of candidate discriminant genes with potential regulatory roles in response to S. aureus infection.
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Affiliation(s)
- Mengqi Wang
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, J1MOC8, Canada; Department of Animal Science, Laval University, Quebec City, Quebec, G1V 0A6, Canada
| | - Nathalie Bissonnette
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, J1MOC8, Canada
| | - Mario Laterrière
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec City, Quebec, G1V 2J3, Canada
| | - Pier-Luc Dudemaine
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, J1MOC8, Canada
| | - David Gagné
- Quebec Research and Development Centre, Agriculture and Agri-Food Canada, Quebec City, Quebec, G1V 2J3, Canada
| | - Jean-Philippe Roy
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Université de Montréal, St-Hyacinthe, Quebec, H3T 1J4, Canada
| | - Marc-André Sirard
- Department of Animal Science, Laval University, Quebec City, Quebec, G1V 0A6, Canada
| | - Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, J1MOC8, Canada.
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5
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Samsing F, Wynne JW, Valenzuela-Muñoz V, Valenzuela-Miranda D, Gallardo-Escárate C, Alexandre PA. Competing endogenous RNA-networks reveal key regulatory microRNAs involved in the response of Atlantic salmon to a novel orthomyxovirus. DEVELOPMENTAL AND COMPARATIVE IMMUNOLOGY 2022; 132:104396. [PMID: 35304180 DOI: 10.1016/j.dci.2022.104396] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/10/2022] [Accepted: 03/10/2022] [Indexed: 06/14/2023]
Abstract
One of the most intriguing discoveries of the genomic era is that only a small fraction of the genome is dedicated to protein coding. The remaining fraction of the genome contains, amongst other elements, a number of non-coding transcripts that regulate the transcription of protein coding genes. Here we used transcriptome sequencing data to explore these gene regulatory networks using RNA derived from gill tissue of Atlantic salmon (Salmo salar) infected with Pilchard orthomyxovirus (POMV), but showing no clinical signs of disease. We examined fish sampled early during the challenge trial (8-12 days after infection) to uncover potential biomarkers of early infection and innate immunity, and fish sampled late during the challenge trial (19 dpi) to elucidate potential markers of resistance to POMV. We analysed total RNA-sequencing data to find differentially expressed messenger RNAs (mRNA) and identify new long-noncoding RNAs (lncRNAs). We also evaluated small RNA sequencing data to find differentially transcribed microRNAs (miRNAs) and explore their role in gene regulatory networks. Whole-genome expression data (both coding and non-coding transcripts) were used to explore the crosstalk between RNA molecules by constructing competing endogenous RNA networks (ceRNA). The teleost specific miR-462/miR-731 cluster was strongly induced in POMV infected fish and deemed a potential biomarker of early infection. Gene networks also identified a selenoprotein (selja), downregulated in fish sampled late during the challenge, which may be associated to viral clearance and the return to homeostasis after infection. This study provides the basis for further investigations using molecular tools to overexpress or inhibit miRNAs to confirm the functional impact of the interactions presented here on gene expression and their potential application at commercial level.
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Affiliation(s)
- Francisca Samsing
- CSIRO Agriculture and Food, Livestock and Aquaculture, Hobart, TAS, Australia
| | - James W Wynne
- CSIRO Agriculture and Food, Livestock and Aquaculture, Hobart, TAS, Australia.
| | | | - Diego Valenzuela-Miranda
- Interdisciplinary Center for Aquaculture Research (INCAR), University of Concepción, Concepción, Chile
| | | | - Pâmela A Alexandre
- CSIRO Agriculture and Food, Livestock and Aquaculture, Brisbane, QLD, Australia
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Stamperna K, Giannoulis T, Cañon-Beltrán K, Dovolou E, Kalemkeridou M, Nanas I, Rizos D, Moutou KA, Mamuris Z, Amiridis GS. Oviductal epithelial cells transcriptome and extracellular vesicles characterization during thermoneutral and heat stress conditions in dairy cows. Theriogenology 2022; 187:152-163. [DOI: 10.1016/j.theriogenology.2022.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/12/2022] [Accepted: 04/17/2022] [Indexed: 10/18/2022]
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7
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Khan A, Singh K, Jaiswal S, Raza M, Jasrotia RS, Kumar A, Gurjar AKS, Kumari J, Nayan V, Iquebal MA, Angadi UB, Rai A, Datta TK, Kumar D. Whole-Genome-Based Web Genomic Resource for Water Buffalo (Bubalus bubalis). Front Genet 2022; 13:809741. [PMID: 35480326 PMCID: PMC9035531 DOI: 10.3389/fgene.2022.809741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 02/14/2022] [Indexed: 11/13/2022] Open
Abstract
Water buffalo (Bubalus bubalis), belonging to the Bovidae family, is an economically important animal as it is the major source of milk, meat, and drought in numerous countries. It is mainly distributed in tropical and subtropical regions with a global population of approximately 202 million. The advent of low cost and rapid sequencing technologies has opened a new vista for global buffalo researchers. In this study, we utilized the genomic data of five commercially important buffalo breeds, distributed globally, namely, Mediterranean, Egyptian, Bangladesh, Jaffrarabadi, and Murrah. Since there is no whole-genome sequence analysis of these five distinct buffalo breeds, which represent a highly diverse ecosystem, we made an attempt for the same. We report the first comprehensive, holistic, and user-friendly web genomic resource of buffalo (BuffGR) accessible at http://backlin.cabgrid.res.in/buffgr/, that catalogues 6028881 SNPs and 613403 InDels extracted from a set of 31 buffalo tissues. We found a total of 7727122 SNPs and 634124 InDels distributed in four breeds of buffalo (Murrah, Bangladesh, Jaffarabadi, and Egyptian) with reference to the Mediterranean breed. It also houses 4504691 SSR markers from all the breeds along with 1458 unique circRNAs, 37712 lncRNAs, and 938 miRNAs. This comprehensive web resource can be widely used by buffalo researchers across the globe for use of markers in marker trait association, genetic diversity among the different breeds of buffalo, use of ncRNAs as regulatory molecules, post-transcriptional regulations, and role in various diseases/stresses. These SNPs and InDelscan also be used as biomarkers to address adulteration and traceability. This resource can also be useful in buffalo improvement programs and disease/breed management.
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Affiliation(s)
- Aamir Khan
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Kalpana Singh
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mustafa Raza
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Rahul Singh Jasrotia
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Animesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anoop Kishor Singh Gurjar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Juli Kumari
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varij Nayan
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
- *Correspondence: Mir Asif Iquebal,
| | - U. B. Angadi
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | | | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
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Karimi P, Bakhtiarizadeh MR, Salehi A, Izadnia HR. Transcriptome analysis reveals the potential roles of long non-coding RNAs in feed efficiency of chicken. Sci Rep 2022; 12:2558. [PMID: 35169237 PMCID: PMC8847365 DOI: 10.1038/s41598-022-06528-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 02/02/2022] [Indexed: 12/13/2022] Open
Abstract
Feed efficiency is an important economic trait and reduces the production costs per unit of animal product. Up to now, few studies have conducted transcriptome profiling of liver tissue in feed efficiency-divergent chickens (Ross vs native breeds). Also, molecular mechanisms contributing to differences in feed efficiency are not fully understood, especially in terms of long non-coding RNAs (lncRNAs). Hence, transcriptome profiles of liver tissue in commercial and native chicken breeds were analyzed. RNA-Seq data along with bioinformatics approaches were applied and a series of lncRNAs and target genes were identified. Furthermore, protein-protein interaction network construction, co-expression analysis, co-localization analysis of QTLs and functional enrichment analysis were used to functionally annotate the identified lncRNAs. In total, 2,290 lncRNAs were found (including 1,110 annotated, 593 known and 587 novel), of which 53 (including 39 known and 14 novel), were identified as differentially expressed genes between two breeds. The expression profile of lncRNAs was validated by RT-qPCR. The identified novel lncRNAs showed a number of characteristics similar to those of known lncRNAs. Target prediction analysis showed that these lncRNAs have the potential to act in cis or trans mode. Functional enrichment analysis of the predicted target genes revealed that they might affect the differences in feed efficiency of chicken by modulating genes associated with lipid metabolism, carbohydrate metabolism, growth, energy homeostasis and glucose metabolism. Some gene members of significant modules in the constructed co-expression networks were reported as important genes related to feed efficiency. Co-localization analysis of QTLs related to feed efficiency and the identified lncRNAs suggested several candidates to be involved in residual feed intake. The findings of this study provided valuable resources to further clarify the genetic basis of regulation of feed efficiency in chicken from the perspective of lncRNAs.
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Affiliation(s)
- Parastoo Karimi
- Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran
| | | | - Abdolreza Salehi
- Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran
| | - Hamid Reza Izadnia
- Animal Science Improvement Research Department, Agricultural and Natural Resources Research and Education Center, Safiabad AREEO, Dezful, Iran
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Emerging Roles of Non-Coding RNAs in the Feed Efficiency of Livestock Species. Genes (Basel) 2022; 13:genes13020297. [PMID: 35205343 PMCID: PMC8872339 DOI: 10.3390/genes13020297] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 01/27/2023] Open
Abstract
A global population of already more than seven billion people has led to an increased demand for food and water, and especially the demand for meat. Moreover, the cost of feed used in animal production has also increased dramatically, which requires animal breeders to find alternatives to reduce feed consumption. Understanding the biology underlying feed efficiency (FE) allows for a better selection of feed-efficient animals. Non-coding RNAs (ncRNAs), especially micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), play important roles in the regulation of bio-logical processes and disease development. The functions of ncRNAs in the biology of FE have emerged as they participate in the regulation of many genes and pathways related to the major FE indicators, such as residual feed intake and feed conversion ratio. This review provides the state of the art studies related to the ncRNAs associated with FE in livestock species. The contribution of ncRNAs to FE in the liver, muscle, and adipose tissues were summarized. The research gap of the function of ncRNAs in key processes for improved FE, such as the nutrition, heat stress, and gut–brain axis, was examined. Finally, the potential uses of ncRNAs for the improvement of FE were discussed.
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Lagarrigue S, Lorthiois M, Degalez F, Gilot D, Derrien T. LncRNAs in domesticated animals: from dog to livestock species. Mamm Genome 2021; 33:248-270. [PMID: 34773482 PMCID: PMC9114084 DOI: 10.1007/s00335-021-09928-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 10/19/2021] [Indexed: 11/29/2022]
Abstract
Animal genomes are pervasively transcribed into multiple RNA molecules, of which many will not be translated into proteins. One major component of this transcribed non-coding genome is the long non-coding RNAs (lncRNAs), which are defined as transcripts longer than 200 nucleotides with low coding-potential capabilities. Domestic animals constitute a unique resource for studying the genetic and epigenetic basis of phenotypic variations involving protein-coding and non-coding RNAs, such as lncRNAs. This review presents the current knowledge regarding transcriptome-based catalogues of lncRNAs in major domesticated animals (pets and livestock species), covering a broad phylogenetic scale (from dogs to chicken), and in comparison with human and mouse lncRNA catalogues. Furthermore, we describe different methods to extract known or discover novel lncRNAs and explore comparative genomics approaches to strengthen the annotation of lncRNAs. We then detail different strategies contributing to a better understanding of lncRNA functions, from genetic studies such as GWAS to molecular biology experiments and give some case examples in domestic animals. Finally, we discuss the limitations of current lncRNA annotations and suggest research directions to improve them and their functional characterisation.
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Affiliation(s)
| | - Matthias Lorthiois
- Univ Rennes, CNRS, IGDR (Institut de Génétique et Développement de Rennes) - UMR 6290, 2 av Prof Leon Bernard, F-35000, Rennes, France
| | - Fabien Degalez
- INRAE, INSTITUT AGRO, PEGASE UMR 1348, 35590, Saint-Gilles, France
| | - David Gilot
- CLCC Eugène Marquis, INSERM, Université Rennes, UMR_S 1242, 35000, Rennes, France
| | - Thomas Derrien
- Univ Rennes, CNRS, IGDR (Institut de Génétique et Développement de Rennes) - UMR 6290, 2 av Prof Leon Bernard, F-35000, Rennes, France.
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Alexandre PA, Naval-Sánchez M, Menzies M, Nguyen LT, Porto-Neto LR, Fortes MRS, Reverter A. Chromatin accessibility and regulatory vocabulary across indicine cattle tissues. Genome Biol 2021; 22:273. [PMID: 34548076 PMCID: PMC8454054 DOI: 10.1186/s13059-021-02489-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 09/08/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Spatiotemporal changes in the chromatin accessibility landscape are essential to cell differentiation, development, health, and disease. The quest of identifying regulatory elements in open chromatin regions across different tissues and developmental stages is led by large international collaborative efforts mostly focusing on model organisms, such as ENCODE. Recently, the Functional Annotation of Animal Genomes (FAANG) has been established to unravel the regulatory elements in non-model organisms, including cattle. Now, we can transition from prediction to validation by experimentally identifying the regulatory elements in tropical indicine cattle. The identification of regulatory elements, their annotation and comparison with the taurine counterpart, holds high promise to link regulatory regions to adaptability traits and improve animal productivity and welfare. RESULTS We generate open chromatin profiles for liver, muscle, and hypothalamus of indicine cattle through ATAC-seq. Using robust methods for motif discovery, motif enrichment and transcription factor binding sites, we identify potential master regulators of the epigenomic profile in these three tissues, namely HNF4, MEF2, and SOX factors, respectively. Integration with transcriptomic data allows us to confirm some of their target genes. Finally, by comparing our results with Bos taurus data we identify potential indicine-specific open chromatin regions and overlaps with indicine selective sweeps. CONCLUSIONS Our findings provide insights into the identification and analysis of regulatory elements in non-model organisms, the evolution of regulatory elements within two cattle subspecies as well as having an immediate impact on the animal genetics community in particular for a relevant productive species such as tropical cattle.
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Affiliation(s)
- Pâmela A Alexandre
- CSIRO Agriculture & Food, 306 Carmody Rd., QLD, 4067, Brisbane, Australia.
| | - Marina Naval-Sánchez
- CSIRO Agriculture & Food, 306 Carmody Rd., QLD, 4067, Brisbane, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Moira Menzies
- CSIRO Agriculture & Food, 306 Carmody Rd., QLD, 4067, Brisbane, Australia
| | - Loan T Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, 4072, Australia
| | | | - Marina R S Fortes
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Antonio Reverter
- CSIRO Agriculture & Food, 306 Carmody Rd., QLD, 4067, Brisbane, Australia
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12
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Alexandre PA, Hudson NJ, Lehnert SA, Fortes MRS, Naval-Sánchez M, Nguyen LT, Porto-Neto LR, Reverter A. Genome-Wide Co-Expression Distributions as a Metric to Prioritize Genes of Functional Importance. Genes (Basel) 2020; 11:E1231. [PMID: 33092259 PMCID: PMC7593939 DOI: 10.3390/genes11101231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 10/15/2020] [Indexed: 12/17/2022] Open
Abstract
Genome-wide gene expression analysis are routinely used to gain a systems-level understanding of complex processes, including network connectivity. Network connectivity tends to be built on a small subset of extremely high co-expression signals that are deemed significant, but this overlooks the vast majority of pairwise signals. Here, we developed a computational pipeline to assign to every gene its pair-wise genome-wide co-expression distribution to one of 8 template distributions shapes varying between unimodal, bimodal, skewed, or symmetrical, representing different proportions of positive and negative correlations. We then used a hypergeometric test to determine if specific genes (regulators versus non-regulators) and properties (differentially expressed or not) are associated with a particular distribution shape. We applied our methodology to five publicly available RNA sequencing (RNA-seq) datasets from four organisms in different physiological conditions and tissues. Our results suggest that genes can be assigned consistently to pre-defined distribution shapes, regarding the enrichment of differential expression and regulatory genes, in situations involving contrasting phenotypes, time-series, or physiological baseline data. There is indeed a striking additional biological signal present in the genome-wide distribution of co-expression values which would be overlooked by currently adopted approaches. Our method can be applied to extract further information from transcriptomic data and help uncover the molecular mechanisms involved in the regulation of complex biological process and phenotypes.
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Affiliation(s)
- Pâmela A. Alexandre
- CSIRO Agriculture & Food, St Lucia, QLD 4067, Australia; (S.A.L.); (L.R.P.-N.); (A.R.)
| | - Nicholas J. Hudson
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia;
| | - Sigrid A. Lehnert
- CSIRO Agriculture & Food, St Lucia, QLD 4067, Australia; (S.A.L.); (L.R.P.-N.); (A.R.)
| | - Marina R. S. Fortes
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072, Australia;
| | - Marina Naval-Sánchez
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia;
| | - Loan T. Nguyen
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD 4072, Australia;
| | - Laercio R. Porto-Neto
- CSIRO Agriculture & Food, St Lucia, QLD 4067, Australia; (S.A.L.); (L.R.P.-N.); (A.R.)
| | - Antonio Reverter
- CSIRO Agriculture & Food, St Lucia, QLD 4067, Australia; (S.A.L.); (L.R.P.-N.); (A.R.)
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