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Jahanbin, M.

Publications and source records attributed to Jahanbin, M..

2 recordsLinked to original sources

Differential selective regimes identify categories of transposable elements with regulatory function

Transposable elements (TEs) are powerful drivers of genome evolution, in part through their ability to rapidly rewire the host regulatory network by creating transcription factor binding sites that can potentially be turned to the hosts advantage in a process called exaptation. However, the effects on the host phenotype vary widely among different TEs. Here, we classify TEs based on their contribution to the human host phenotypes at both molecular and macroscopic scales. TE contributions to chromatin accessibility, gene expression, and the heritability of complex traits are strongly correlated to each other, confirming that the main mechanism through which TEs affect the host phenotype is through the rewiring of the regulatory network. TE sequence and evolutionary features are able to explain a large fraction of the variance in phenotypic relevance, and in particular more than 50% of the variance of their contribution to the heritability of complex traits. A conspicuous exception to this pattern is represented by TEs of the ERV1 family, whose phenotypic impact cannot be explained by our model: In particular, this family includes a set of relatively young TEs whose phenotypic relevance is much larger than would be expected based on their sequence and evolutionary parameters. These TEs are involved in fast-evolving biological processes related to the interaction of the organism with its environment. In conclusion, our results confirm quantitatively that TE insertions affect the host phenotype mostly through the rewiring of its regulatory network; identify a signature of phenotypic relevance based on sequence and conservation properties; and highlight several TEs as promising candidates for functional studies.

genetics↗

Mixed data analysis detected Endocrine Fibroblast Growth Factors (FGF19, FGF21, and FGF23) as Prognostic and Diagnostic Markers of Colorectal Neoplasia and Carcinoma

BackgroundEndocrine fibroblast growth factors (eFGFs) play important roles in various cellular signaling processes such as development and differentiation. These genes were also found to be significantly related to several cancer. However, little is known about the role of eFGFs in colon neoplasia and colon adenocarcinoma (COAD). MethodsWe performed systematically and comprehensively investigated the gene expression, DNA methylation, prognostic significance, genetic alteration, co-expressed genes, protein-protein interaction, small molecules pathway, and drug interactions of eFGFs based on the TIMER2.0, GEPIA2, UALCAN, OncoDB, cBioPortal, LinkedOmics, STRING, SMPDB, htfTarget, mirTarBase, circBank and DGIdb databases. Ultimately, the correlations of eFGFs expressions between polyp and COAD tissues compared to normal mucosa were validated using qRT-PCR as a cross-sectional part of our study. ResultsThe results indicated that eFGFs are highly expressed in COAD, and abnormal gene expressions may be related to promoter methylation. In this matter, methylation analysis revealed promotor hypermethylation of FGF19 and FGF21. Conversely, FGF23 was shown to have a tendency for promotor hypomethylation. Moreover, hypermethylation of FGF21 and FGF23 and downregulation of FGF23 were found to be detrimental to the survival of COAD patients. KEGG pathway analyses indicated that the co-expressed genes of eFGF family members were mainly related to the regulation of the actin cytoskeleton and, more notably, in Ras signaling, PI3k-Akt signaling, Rap1 signaling, and cancer pathways. Based on qRT-PCR results, FGF21 was significantly overexpressed in the colon polyps compared to normal mucosa. Additionally, RNA expression of FGF21 and FGF23 was markedly elevated in adenomatous polyps as opposed to hyperplastic polyps. ConclusionCollectively, these findings reveal the critical roles of eFGFs in COAD tumorigenesis and suggest eFGF family members as promising prognostic and diagnostic markers for CRC as well as discriminating markers for high-risk from low-risk polyps.

bioinformatics↗