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      Comparative transcriptomic profiling of myxomatous mitral valve disease in the cavalier King Charles spaniel

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          Abstract

          Background

          Almost all elderly dogs develop myxomatous mitral valve disease by the end of their life, but the cavalier King Charles spaniel (CKCS) has a heightened susceptibility, frequently resulting in death at a young age and suggesting that there is a genetic component to the condition in this breed. Transcriptional profiling can reveal the impact of genetic variation through differences in gene expression levels. The aim of this study was to determine whether expression patterns were different in mitral valves showing myxomatous degeneration from CKCS dogs compared to valves from non-CKCS dogs.

          Results

          Gene expression patterns in three groups of canine valves resulted in distinct separation of normal valves, diseased valves from CKCS and diseased valves from other breeds; the latter were more similar to the normal valves than were the valves from CKCS. Gene expression patterns in diseased valves from CKCS dogs were quite different from those in the valves from other dogs, both affected and normal. Patterns in all diseased valves (from CKCS and other breeds) were also somewhat different from normal non-diseased samples. Analysis of differentially expressed genes showed enrichment in GO terms relating to cardiac development and function and to calcium signalling canonical pathway in the genes down-regulated in the diseased valves from CKCS, compared to normal valves and to diseased valves from other breeds. F2 (prothrombin) (CKCS diseased valves compared to normal) and MEF2C pathway activation (CKCS diseased valves compared to non-CKCS diseased valves) had the strongest association with the gene changes. A large number of genes that were differentially expressed in the CKCS diseased valves compared with normal valves and diseased valves from other breeds were associated with cardiomyocytes including CASQ2, TNNI3 and RYR2.

          Conclusion

          Transcriptomic profiling identified gene expression changes in CKCS diseased valves that were not present in age and disease severity-matched non-CKCS valves. These genes are associated with cardiomyocytes, coagulation and extra-cellular matrix remodelling. Identification of genes that vary in the CKCS will allow exploration of genetic variation to understand the aetiology of the disease in this breed, and ultimately development of breeding strategies to eliminate this disease from the breed.

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          Most cited references48

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          Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks

          Background Biological processes are carried out by coordinated modules of interacting molecules. As clustering methods demonstrate that genes with similar expression display increased likelihood of being associated with a common functional module, networks of coexpressed genes provide one framework for assigning gene function. This has informed the guilt-by-association (GBA) heuristic, widely invoked in functional genomics. Yet although the idea of GBA is accepted, the breadth of GBA applicability is uncertain. Results We developed methods to systematically explore the breadth of GBA across a large and varied corpus of expression data to answer the following question: To what extent is the GBA heuristic broadly applicable to the transcriptome and conversely how broadly is GBA captured by a priori knowledge represented in the Gene Ontology (GO)? Our study provides an investigation of the functional organization of five coexpression networks using data from three mammalian organisms. Our method calculates a probabilistic score between each gene and each Gene Ontology category that reflects coexpression enrichment of a GO module. For each GO category we use Receiver Operating Curves to assess whether these probabilistic scores reflect GBA. This methodology applied to five different coexpression networks demonstrates that the signature of guilt-by-association is ubiquitous and reproducible and that the GBA heuristic is broadly applicable across the population of nine hundred Gene Ontology categories. We also demonstrate the existence of highly reproducible patterns of coexpression between some pairs of GO categories. Conclusion We conclude that GBA has universal value and that transcriptional control may be more modular than previously realized. Our analyses also suggest that methodologies combining coexpression measurements across multiple genes in a biologically-defined module can aid in characterizing gene function or in characterizing whether pairs of functions operate together.
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            Immune Cell Gene Signatures for Profiling the Microenvironment of Solid Tumors

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              Mechanistic insight into contextual TGF-β signaling

              Ying Zhang (2018)
              Transforming growth factor-β (TGF-β) controls a wide range of cellular functions by activating both SMADs and non-SMAD pathways. In different tissue or physiological environment, cellular responses to TGF-β can be diverse, even opposite. Complex regulations at the level of ligand mobilization, receptor presentation, and the network of intracellular signal transducers afford the TGF-β pathway with versatile means to induce precise cellular responses in accordance to specific contextual demands. This article summarizes recent development in how cells manage their responses to TGF-β through ligand activation, receptor abundance, as well as SMAD-dependent and SMAD-independent mechanisms.
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                Author and article information

                Contributors
                Brendan.Corcoran@ed.ac.uk
                Journal
                BMC Vet Res
                BMC Vet. Res
                BMC Veterinary Research
                BioMed Central (London )
                1746-6148
                23 September 2020
                23 September 2020
                2020
                : 16
                : 350
                Affiliations
                [1 ]GRID grid.482685.5, ISNI 0000 0000 9166 3715, The Roslin Institute, University of Edinburgh, ; Roslin Mid-Lothian, Roslin, Scotland, UK EH25 9RG
                [2 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Royal (Dick) School of Veterinary Studies, , University of Edinburgh, ; Roslin Mid-Lothian, Roslin, Scotland, UK EH25 9RG
                [3 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, Mater Research Institute-University of Queensland, ; 37 Kent St, Woolloongabba, QLD 4102 Australia
                Author information
                http://orcid.org/0000-0001-7453-9808
                Article
                2542
                10.1186/s12917-020-02542-w
                7509937
                32967675
                341b12f5-5114-410b-aef5-4a4b91762588
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 17 April 2020
                : 25 August 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/J004316/1
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Veterinary medicine
                genes expression,gene clustering,gene networks,myxomatous mitral valve disease,cavalier king charles spaniel

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