Understanding Tissue-specific Gene Regulation

Abstract

Although all human tissues carry out common processes, tissues are distinguished by gene expres-sion patterns, implying that distinct regulatory programs control tissue-specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have higher tissue-specificity than network nodes (genes) and that regulating nodes (transcription factors) are less likely to be expressed in a tissue-specific manner as compared to their targets (genes). Gene set enrichment analysis of network targeting also indicates that regulation of tissue-specific function is largely independent of transcription factor expression. In addition, tissue-specific genes are not highly targeted in their corresponding tissue-network. However, they do assume bottleneck positions due to variability in transcription factor targeting and the influence of non-canonical regulatory interactions. These results suggest that tissue-specificity is driven by context-dependent regulatory paths, providing transcriptional control of tissue-specific processes.

Multi-level and lineage-specific interactomes of the Hox transcription factor Ubx contribute to its functional specificity

“…However, TFs do not only interact with other TFs but with a variety of proteins including chromatin associated proteins, histone modifiers, factors of the general transcriptional machinery or mRNA regulatory proteins [9][10][11][12][13] . Hence, it is thought that TFs promote cell type diversity by assembling protein interaction networks consisting of different types of proteins in a cell-type-specific manner 6,14,15 . However, as suitable approaches have been unavailable so far, this assumption still awaits approval.…”

miRinGO: Prediction of biological processes indirectly targeted by human microRNAs

“…First, for each miRNA, potential directly-targeted TFs were compiled from the TargetScan database v7.2 [22]. Second, computationally predicted tissuespecific TF-gene associations were collected from the resources website of (Sonawane et al, 2017) [23]. In case of multiple input miRNAs, we use the intersection of indirect targets of each miRNA.…”

“…Third, a hypergeometric test is conducted to find potential targeted biological processes. Computationally predicted tissue-specific TF targets were downloaded from the resources website of (Sonawane et al, 2017) [23]. These TF targets were predicted using the PANDA (Passing Attributes between Networks for Data Assimilation) algorithm [24].…”

Identification and characterization of developmental, tissue, and evolutionary transcription start sites in Bos taurus indicus

“…Tissues are distinguished by gene expression patterns, indicating distinct regulatory processes. Individual genes, or even sets of genes, in each tissue cannot adequately capture the diversity of structure and function that exist among different tissues 41 , and multiple regulatory elements, including transcription factors and TSSs, that work together with other genetic and environmental factors must control the transcription of genes and production of proteins 42 . Alternative TSSs can signi cantly alter the 5' UTR structure and therefore result in higher or lower rate of protein synthesis 43,44 .…”