Consensus molecular subtypes (CMSs) are emerging as critical factor for prognosis and treatment of colorectal cancer. Gene regulators, including chromatin regulator, RNA-binding protein and transcriptional factor, are critical modulators of cancer hallmark, yet little is known regarding the underlying functional mechanism in CMSs. Herein, we identified a core set of 235 functional gene regulators (FGRs) by integrating genome, epigenome, transcriptome and interactome of CMSs. FGRs exhibited significant multi-omics alterations and impacts on cell lines growth, as well as significantly enriched cancer driver genes and pathways. Moreover, common FGRs played different roles in the context of CMSs. In accordance with the immune characteristics of CMSs, we found that the anti-tumor immune pathways were mainly activated by FGRs (e.g. STAT1 and CREBBP) in CMS1, while inhibited by FGRs in CMS2-4. FGRs mediated aberrant expression of ligands, which bind to receptor on immune cells, and modulated tumor immune microenvironment of subtypes. Intriguingly, systematic exploration of datasets using genomic and transcriptome co-similarity reveals the coordinated manner in FGRs act in CMSs to orchestrate their pathways and patients\' prognosis. Expression signatures of the FGRs revealed an optimized CMS classifier, which demonstrated 88% concordance with the gold-standard classifier, but avoiding the influence of sample composition. Overall, our integrative analysis identified FGRs to regulate core tumorigenic processes/pathways across CMSs.

BACKGROUND: Analysis of gene expression data provides valuable insights into disease mechanism. Investigating relationship among co-expression modules of different stages is a meaningful tool to understand the way in which a disease progresses. Identifying topological preservation of modular structure also contributes to that understanding.
METHODS: HIV-1 disease provides a well-documented progression pattern through three stages of infection: acute, chronic and non-progressor. In this article, we have developed a novel framework to describe the relationship among the consensus (or shared) co-expression modules for each pair of HIV-1 infection stages. The consensus modules are identified to assess the preservation of network properties. We have investigated the preservation patterns of co-expression networks during HIV-1 disease progression through an eigengene-based approach.
RESULTS: We discovered that the expression patterns of consensus modules have a strong preservation during the transitions of three infection stages. In particular, it is noticed that between acute and non-progressor stages the preservation is slightly more than the other pair of stages. Moreover, we have constructed eigengene networks for the identified consensus modules and observed the preservation structure among them. Some consensus modules are marked as preserved in two pairs of stages and are analyzed further to form a higher order meta-network consisting of a group of preserved modules. Additionally, we observed that module membership (MM) values of genes within a module are consistent with the preservation characteristics. The MM values of genes within a pair of preserved modules show strong correlation patterns across two infection stages.
CONCLUSIONS: We have performed an extensive analysis to discover preservation pattern of co-expression network constructed from microarray gene expression data of three different HIV-1 progression stages. The preservation pattern is investigated through identification of consensus modules in each pair of infection stages. It is observed that the preservation of the expression pattern of consensus modules remains more prominent during the transition of infection from acute stage to non-progressor stage. Additionally, we observed that the module membership values of genes are coherent with preserved modules across the HIV-1 progression stages.

The O(R) regions from several lambdoid bacteriophages contain the three regulatory sites O(R)1, O(R)2 and O(R)3, to which the Cro and CI proteins can bind. These sites show imperfect dyad symmetry, have similar sequences, and generally lie on the same face of the DNA double helix. We have developed a computational method, which analyzes the O(R) regions of additional phages and predicts the location of these three sites. After tuning the method to predict known O(R) sites accurately, we used it to predict unknown sites, and ultimately compiled a database of 32 known and predicted O(R) binding site sets. We then identified sequences of the recognition helices (RH) for the cognate Cro proteins through manual inspection of multiple sequence alignments. Comparison of Cro RH and consensus O(R) half-site sequences revealed strong one-to-one correlations between two amino acids at each of three RH positions and two bases at each of three half-site positions (H1-->2, H3-->5 and H6-->6). In each of these three cases, one of the two amino acid/base-pairings corresponds to a contact observed in the crystal structure of a lambda Cro/consensus operator complex. The alternate amino acid/base combinations were rationalized using structural models. We suggest that the pairs of amino acid residues act as binary switches that efficiently modulate specificity for different consensus half-site variants during evolution. The observation of structurally reasonable amino acid-to-base correlations suggests that Cro proteins share some common rules of recognition despite their functional and structural diversity.

This paper introduces two exact algorithms for extracting conserved structured motifs from a set of DNA sequences. Structured motifs may be described as an ordered collection of p > or = 1 \"boxes\" (each box corresponding to one part of the structured motif), p substitution rates (one for each box) and p - 1 intervals of distance (one for each pair of successive boxes in the collection). The contents of the boxes--that is, the motifs themselves--are unknown at the start of the algorithm. This is precisely what the algorithms are meant to find. A suffix tree is used for finding such motifs. The algorithms are efficient enough to be able to infer site consensi, such as, for instance, promoter sequences or regulatory sites, from a set of unaligned sequences corresponding to the noncoding regions upstream from all genes of a genome. In particular, both algorithms time complexity scales linearly with N2n where n is the average length of the sequences and N their number. An application to the identification of promoter and regulatory consensus sequences in bacterial genomes is shown.

Three subtypes of alpha 2-adrenergic receptors (alpha 2A, alpha 2B and alpha 2C) have been described that differ in their primary sequence and tissue-specific expression and are encoded by three distinct genes. Previous work has shown that the human alpha 2A-adrenergic receptor gene promoter consists of a TATA-box (TATAAA), palindromic sequence (CCCACGTGGG) and GC-box (GGGGCGG) motif. Sequence analysis of the putative promoter region of the rat alpha 2A-adrenergic receptor gene showed that these promoter regions are conserved in their sequence and relative location. We analysed the transcriptional activity of these regions using RINm5F, a rat insulinoma cell line that expresses the endogenous alpha 2A-adrenergic receptor gene. These results showed that the region from -484 to -92 has a negative effect on transcription, as deletion of this region in alpha 2A-adrenergic receptor gene-chloramphenicol acetyltransferase reporter constructs increased reporter gene activity. This region included the GC-box sequence which is a consensus binding site for the nuclear factor SP1, which is a positive activator of transcription. Gel-mobility-shift assays and supershift assays with an antibody that recognizes SP1 showed binding of the SP1 nuclear factor as well as other nuclear factors to this GC-box region. Additional nuclear factors bind to the downstream palindromic region. We suggest that positive- and negative-acting nuclear factors contribute to the activity of the alpha 2-adrenergic receptor promoter.

The 5\' coding and promoter regions of the four coordinately regulated tubulin genes of Chlamydomonas reinhardi have been mapped and sequenced. DNA sequencing data shows that the predicted N-terminal amino acid sequences of Chlamydomonas alpha- and beta-tubulins closely match that of tubulins of other eucaryotes. Within the alpha 1- and alpha 2-tubulin gene set and the beta 1- and beta 2-tubulin gene set, both nucleotide sequence and intron placement are highly conserved. Transcription initiation sites have been located by primer extension analysis at 140, 141, 159, and 132 base pairs upstream of the translation initiator codon for the alpha 1-, alpha 2-, beta 1-, and beta 2-tubulin genes, respectively. Among the structures with potential regulatory significance, the most striking is a 16-base-pair consensus sequence [GCTC(G/C)AAGGC(G/T)(G/C)--(C/A)(C/A)G] which is found in multiple copies immediately upstream of the TATA box in each of the four genes. An unexpected discovery is the presence of pseudopromoter regions in two of the transcribed tubulin genes. One pseudopromoter region is located 400 base pairs upstream of the authentic alpha 2-tubulin gene promoter, whereas the other is located within the transcribed 5\' noncoding region of the beta 1-tubulin gene.

Immunoglobulin heavy chain gene transcription was studied using DNA transfection. The enhancer element identified in the mouse heavy chain locus was active in pre-B and plasmacytoma cell lines, but no activity was detected in two T cell lymphomas. However, even in the absence of the enhancer, cell type specificity of immunoglobulin gene transcription was still retained. We have used gene fusions to show that transcription cell type specificity is conferred by a VH gene promoter. Deletion analysis of this VH promoter indicates that a conserved octamer found 5\' of the TATA box in immunoglobulin V genes is a functional part of the tissue-specific promoter upstream element.

A hybrid gene in which the expression of an Escherichia coli beta-galactosidase gene was placed under the control of a Drosophila melanogaster 70,000-dalton heat shock protein (hsp70) gene promoter was constructed. Mutant derivatives of this hybrid gene which contained promoter sequences of different lengths were prepared, and their heat-induced expression was examined in D. melanogaster and COS-1 (African green monkey kidney) cells. Mutants with 5\' nontranscribed sequences of at least 90 and up to 1,140 base pairs were expressed strongly in both cell types. Mutants with shorter 5\' extensions (of at least 63 base pairs) were transcribed and translated efficiently in COS-1 but not at all in D. melanogaster cells. Thus, in contrast to the situation in COS-1 cells, the previously defined heat shock consensus sequence which is located between nucleotides 62 and 48 of the hsp70 gene 5\' nontranscribed DNA segment is not sufficient for the expression of the D. melanogaster gene in homologous cells. A second consensus-like element 69 to 85 nucleotides upstream from the cap site is postulated to be also involved in the heat-induced expression of the hsp70 gene in D. melanogaster cells.

From a human pituitary cDNA library, we have cloned 3 distinct human growth hormone (hGH) cDNAs, coding respectively for the 22 K hGH, the 20 K variant, and a yet unknown 17.5 K variant. S1 mapping analysis using human pituitary RNA confirms the existence of at least four distinct hGH mRNAs originating from alternative acceptor sites at the second intron of the primary transcript. We have analysed the hGH gene sequence to explain the high frequency of alternative splicings which occur only at this location. In this study we propose CTTGNNPyPyPy as an additional consensus sequence guiding the selection of the branched nucleotide.

Inspection of many proposed recognition signal sequences shows that TGTG/CACA, GAGA/TCTC or their triplet subsets, and TGA/TCA occur frequently. These repeated elements, conserved in recognition sequences from evolutionarily distant organisms, are likely to possess unique structural characteristics. Recurrence of these oligomers may aid in identification of further regulatory sequences in upstream or other regions. Another class of recognition sequences is GC-rich. At present there are only a few examples of this class. It is likely that these sequences function via a different mechanism.