ArticleFrontiers in veterinary science2023
Meta-analysis of RNA-Seq datasets highlights novel genes/pathways involved in fat deposition in fat-tail of sheep.
Article in Frontiers in veterinary science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- A meta-analysis approach for annotation and identification of lncRNAs controlling perirenal fat deposition in suckling lambs.Animal biotechnology · 2024Pooled it
- Single- and Multi-Trait GWASs Combined with Genetic Parameter Estimation Reveal Candidate Genes for Body Conformation Traits in Sika Deer (Animals : an open access journal from MDPI · 2026Article
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- Bulk RNA-seq datasets analysis integration identifies robust drought-responsive genes and functional networks inFrontiers in bioinformatics · 2026Article
- Genetic variation and mRNA expression of theAnimal biotechnology · 2025Article
- Selection signature analysis in chickens divergently selected for growth rate reveals novel candidate genes regulating fat deposition.BMC genomics · 2025Article
- Genomic insights into the recent evolution and biodiversity of Italian sheep breeds.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Article
- Energy Intake During the Transition Period Triggers Substantial Impacts on Body Weight, Milk Production Efficiency, Milk Composition and Blood Biochemical Constituents in Fat-Tailed Ewes.Veterinary medicine and science · 2025Article
- Whole-Genome Resequencing Identifies Candidate Genes for Tail Fat Deposition in Sheep.Animals : an open access journal from MDPI · 2025Article
- Mechanisms of Adipose Tissue Metabolism in Naturally Grazing Sheep at Different Growth Stages: Insights from mRNA and miRNA Profiles.International journal of molecular sciences · 2025Article
- Potential candidate genes influencing meat production phenotypic traits in sheep: a review.Frontiers in veterinary science · 2025Review
- Comparative Transcriptome Analysis of Bovine, Porcine, and Sheep Muscle Using Interpretable Machine Learning Models.Animals : an open access journal from MDPI · 2024Article
- Integrative Meta-Analysis: Unveiling Genetic Factors in Meat Sheep Growth and Muscular Development through QTL and Transcriptome Studies.Animals : an open access journal from MDPI · 2024Article
- Deciphering the role of alternative splicing as a potential regulator in fat-tail development of sheep: a comprehensive RNA-seq based study.Scientific reports · 2024Review
- Meta-analysis of retinal transcriptome profiling studies in animal models of myopia.Frontiers in medicine · 2024Article
- RNA-Seq based selection signature analysis for identifying genomic footprints associated with the fat-tail phenotype in sheep.Frontiers in veterinary science · 2024Article
- Fat-tail allele-specific expression genes may affect fat deposition in tail of sheep.PloS one · 2024Article
- Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes.Genetics, selection, evolution : GSE · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Fat-tail in sheep is considered as an important energy reservoir to provide energy as a survival buffer during harsh challenges. However, fat-tail is losing its importance in modern sheep industry systems and thin-tailed breeds are more desirable. Using comparative transcriptome analysis to compare fat-tail tissue between fat- and thin-tailed sheep breeds provides a valuable approach to study the complex genetic factors associated with fat-tail development. However, transcriptomic studies often suffer from issues with reproducibility, which can be improved by integrating multiple studies based on a meta-analysis. Methods: Hence, for the first time, an RNA-Seq meta-analysis on sheep fat-tail transcriptomes was performed using six publicly available datasets. Results and discussion: A total of 500 genes (221 up-regulated, 279 down-regulated) were identified as differentially expressed genes (DEGs). A jackknife sensitivity analysis confirmed the robustness of the DEGs. Moreover, QTL and functional enrichment analysis reinforced the importance of the DEGs in the underlying molecular mechanisms of fat deposition. Protein-protein interactions (PPIs) network analysis revealed the functional interactions among the DEGs and the subsequent sub-network analysis led to identify six functional sub-networks. According to the results of the network analysis, down-regulated DEGs in green and pink sub-networks (like collagen subunits IV, V, and VI, integrins 1 and 2,
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