Minor C allele of the SNP rs7873784 associated with rheumatoid arthritis and type-2 diabetes mellitus binds PU.1 and enhances TLR4 expression

Methods for Functional Characterization of Genetic Polymorphisms of Non-Coding Regulatory Regions of the Human Genome

Currently, numerous associations between genetic polymorphisms and various diseases have been characterized through the Genome-Wide Association Studies. Majority of the clinically significant polymorphisms are localized in non-coding regions of the genome. While modern bioinformatic resources make it possible to predict molecular mechanisms that explain influence of the non-coding polymorphisms on gene expression, such hypotheses require experimental verification. This review discusses the methods for elucidating molecular mechanisms underlying dependence of the disease pathogenesis on specific genetic variants within the non-coding sequences. A particular focus is on the methods for identification of transcription factors with binding efficiency dependent on polymorphic variations. Despite remarkable progress in bioinformatic resources enabling prediction of the impact of polymorphisms on the disease pathogenesis, there is still the need for experimental approaches to investigate this issue.

Pathogen recognition pathway gene variants and inflammasome sensors gene expression in tuberculosis patients under treatment

BACKGROUND

Several epidemiological studies have suggested that genetic variations in encoding pattern recognition receptors (PRRs) genes such as Toll Like Receptors (TLRs) and their signaling products, may influence the susceptibility, severity and outcome of tuberculosis (TB). After sensing a pathogen, the cell responds producing an inflammatory response, to restrain the pathogen's successful course of infection. Herein we assessed single nucleotide polymorphisms (SNP) and gene expression from pathogen recognition and inflammasome pathways in Brazilian TB patients.

METHODS AND RESULTS

For genetic association analysis we included MYD88 and TLR4, PRRs sensing proteins. Allele distribution for MYD88 rs6853 (A > G) and TLR4 rs7873784 (C > G) presented conserved among the tested samples with statistically differential distribution in TB patients versus controls. However, when testing according to sample ethnicity (African or Caucasian-derived individuals) we identified that the rs6853 G/G genotype was associated with a lower susceptibility to TB in Caucasian population. Meanwhile, the rs7873784 G/G genotype was associated with a higher TB susceptibility in Afro-descendant ethnicity individuals. We also aimed to verify MYD88 and the inflammasome genes NLRP1 and NLRC4 expression in order to connect to active TB and/or clinical aspects.

CONCLUSIONS

We identified that inflammasome gene expression in TB patients under treatment display a similar pattern as in healthy controls, indicating that TB treatment impairs NLRP1 inflammasome activation.

Adversary of DNA integrity: A long non-coding RNA stimulates driver oncogenic chromosomal rearrangement in human thyroid cells

The flurry of publications devoted to the functions of long non-coding RNAs (lncRNAs) published in the last decade leaves no doubt about the exceptional importance of lncRNAs in various areas including tumor biology. However, contribution of lncRNAs to the early stages of oncogenesis remains poorly understood. In this study we explored a new role for lncRNAs: stimulation of specific chromosomal rearrangements upon DNA damage. We demonstrated that lncRNA CASTL1 (ENSG00000269945) stimulates the formation of the CCDC6-RET inversion (RET/PTC1) in human thyroid cells subjected to radiation or chemical DNA damage. Facilitation of chromosomal rearrangement requires lncRNA to contain regions complementary to the introns of both CCDC6 and RET genes as deletion of these regions deprives CASTL1 of the ability to stimulate the gene fusion. We found that CASTL1 expression is elevated in tumors with CCDC6-RET fusion which is the most frequent rearrangement in papillary thyroid carcinoma. Our results open a new venue for the studies of early oncogenesis in various tumor types, especially those associated with physical or chemical DNA damage.

The role of a key transcription factor PU.1 in autoimmune diseases

PU.1, a transcription factor member of the E26 transformation-specific family, affects the function of a variety of immune cells in several physiological and pathological conditions. Previous studies studying the role of PU.1 in pathological conditions have mainly focused on immune system-related cancers, and a series of articles have confirmed that PU.1 mutation can induce a variety of immune cell-related malignancies. The underlying mechanism has also been extensively validated. However, the role of PU.1 in other major immune system-related diseases, namely, systemic autoimmune diseases, is still unclear. It was only in recent years that researchers began to gradually realize that PU.1 also played an important role in a variety of autoimmune diseases, such as rheumatoid arthritis (RA), experimental autoimmune encephalomyelitis (EAE) and systemic lupus erythematosus (SLE). This review article summarizes the findings of recent studies that investigated the role of PU.1 in various autoimmune diseases and the related underlying mechanisms. Furthermore, it presents new ideas and provides insight into the role of PU.1 as a potential treatment target for autoimmune diseases and highlights existing research problems and future research directions in related fields.

Disease-associated genetic variants in the regulatory regions of human genes: mechanisms of action on transcription and genomic resources for dissecting these mechanisms

Whole genome and whole exome sequencing technologies play a very important role in the studies of the genetic aspects of the pathogenesis of various diseases. The ample use of genome-wide and exome-wide association study methodology (GWAS and EWAS) made it possible to identify a large number of genetic variants associated with diseases. This information is accumulated in the databases like GWAS central, GWAS catalog, OMIM, ClinVar, etc. Most of the variants identified by the GWAS technique are located in the noncoding regions of the human genome. According to the ENCODE project, the fraction of regions in the human genome potentially involved in transcriptional control is many times greater than the fraction of coding regions. Thus, genetic variation in noncoding regions of the genome can increase the susceptibility to diseases by disrupting various regulatory elements (promoters, enhancers, silencers, insulator regions, etc.). However, identification of the mechanisms of influence of pathogenic genetic variants on the diseases risk is difficult due to a wide variety of regulatory elements. The present review focuses on the molecular genetic mechanisms by which pathogenic genetic variants affect gene expression. At the same time, attention is concentrated on the transcriptional level of regulation as an initial step in the expression of any gene. A triggering event mediating the effect of a pathogenic genetic variant on the level of gene expression can be, for example, a change in the functional activity of transcription factor binding sites (TFBSs) or DNA methylation change, which, in turn, affects the functional activity of promoters or enhancers. Dissecting the regulatory roles of polymorphic loci have been impossible without close integration of modern experimental approaches with computer analysis of a growing wealth of genetic and biological data obtained using omics technologies. The review provides a brief description of a number of the most well-known public genomic information resources containing data obtained using omics technologies, including (1) resources that accumulate data on the chromatin states and the regions of transcription factor binding derived from ChIP-seq experiments; (2) resources containing data on genomic loci, for which allele-specific transcription factor binding was revealed based on ChIP-seq technology; (3) resources containing in silico predicted data on the potential impact of genetic variants on the transcription factor binding sites

Dysregulated translational factors and epigenetic regulations orchestrate in B cells contributing to autoimmune diseases

B cells play a crucial role in antigen presentation, antibody production and pro-/anti-inflammatory cytokine secretion in adaptive immunity. Several translational factors including transcription factors and cytokines participate in the regulation of B cell development, with the cooperation of epigenetic regulations. Autoimmune diseases are generally characterized with autoreactive B cells and high-level pathogenic autoantibodies. The success of B cell depletion therapy in mouse model and clinical trials has proven the role of B cells in pathogenesis of autoimmune diseases. The failure of B cell tolerance in immune checkpoints results in accumulated autoreactive naïve B (B_N) cells with aberrant B cell receptor signaling and dysregulated B cell response, contributing to self-antibody-mediated autoimmune reaction. Dysregulation of translational factors and epigenetic alterations in B cells has been demonstrated to correlate with aberrant B cell compartment in autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis, primary Sjögren's syndrome, multiple sclerosis, diabetes mellitus and pemphigus. This review is intended to summarize the interaction of translational factors and epigenetic regulations that are involved with development and differentiation of B cells, and the mechanism of dysregulation in the pathogenesis of autoimmune diseases.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Landscape of allele-specific transcription factor binding in the human genome

Sequence variants in gene regulatory regions alter gene expression and contribute to phenotypes of individual cells and the whole organism, including disease susceptibility and progression. Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Differential transcription factor binding in heterozygous genomic loci provides a natural source of information on such regulatory variants. We present a novel approach to call the allele-specific transcription factor binding events at single-nucleotide variants in ChIP-Seq data, taking into account the joint contribution of aneuploidy and local copy number variation, that is estimated directly from variant calls. We have conducted a meta-analysis of more than 7 thousand ChIP-Seq experiments and assembled the database of allele-specific binding events listing more than half a million entries at nearly 270 thousand single-nucleotide polymorphisms for several hundred human transcription factors and cell types. These polymorphisms are enriched for associations with phenotypes of medical relevance and often overlap eQTLs, making candidates for causality by linking variants with molecular mechanisms. Specifically, there is a special class of switching sites, where different transcription factors preferably bind alternative alleles, thus revealing allele-specific rewiring of molecular circuitry.

Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Here the authors present a meta-analysis empowered by a new statistical method covering thousands of ChIP-Seq experiments resulting in the identification of more than 500 thousand allele-specific binding (ASB) events in the human genome.