Dissecting the chromatin interactome of microRNA genes

ALDOC regulated the biological function and immune infiltration of gastric cancer cells

BACKGROUND

The role of ALDOC which is an important regulator involved in tumor metabolic reprogramming and immune microenvironment in GC remains unclear. Therefore, we investigated the feasibility of ALDOC as a prognostic marker and therapeutic target.

METHODS

We verified the expression of ALDOC in GC and its effect on the prognosis of GC patients by analyzing clinical data. The regulation of ALDOC on the biological behavior of GC cells was confirmed by experiments. The potential mechanism of miRNA regulating GC immune cell infiltration by inhibiting ALDOC was explored by experiments and bioinformatic analysis. We further analyzed the effect of ALDOC on somatic mutations in gastric cancer, and constructed a prognostic model based on ALDOC and related immune molecules.

RESULTS

ALDOC is overexpressed in GC cells and tissues, which promotes malignant biological behavior of GC cells and is an independent risk factor for poor prognosis of GC patients. MiR-19a-5p promotes the expression of ALDOC by down-regulating ETS1, leading to poor prognosis in GC patients. ALDOC is significantly associated with immune infiltration in GC, regulates macrophage differentiation and promotes the progression of GC. ALDOC is significantly correlated with TMB and MSI of gastric cancer, and affects somatic mutation of gastric cancer. The prognostic model has good predictive efficiency.

CONCLUSIONS

ALDOC is a potential prognostic marker and therapeutic target with abnormal immune-mediated effects. The prognostic model based on ALDOC provides a reference for prognosis prediction and individualized treatment of GC patients.

A microRNA-microRNA crosstalk network inferred from genome-wide single nucleotide polymorphism variants in natural populations of Arabidopsis thaliana

To adapt to variable natural conditions, plants have evolved several strategies to respond to different environmental stresses. MicroRNA (miRNA)-mediated gene regulation is one of such strategies. Variants, e.g., single nucleotide polymorphisms (SNPs) within the mature miRNAs or their target sites may cause the alteration of regulatory networks and serious phenotype changes. In this study, we proposed a novel approach to construct a miRNA-miRNA crosstalk network in Arabidopsis thaliana based on the notion that two cooperative miRNAs toward common targets are under a strong pressure to be inherited together across ecotypes. By performing a genome-wide scan of the SNPs within the mature miRNAs and their target sites, we defined a "regulation fate profile" to describe a miRNA-target regulation being static (kept) or dynamic (gained or lost) across 1,135 ecotypes compared with the reference genome of Col-0. The cooperative miRNA pairs were identified by estimating the similarity of their regulation fate profiles toward the common targets. The reliability of the cooperative miRNA pairs was supported by solid expressional correlation, high PPImiRFS scores, and similar stress responses. Different combinations of static and dynamic miRNA-target regulations account for the cooperative miRNA pairs acting on various biological characteristics of miRNA conservation, expression, homology, and stress response. Interestingly, the targets that are co-regulated dynamically by both cooperative miRNAs are more likely to be responsive to stress. Hence, stress-related genes probably bear selective pressures in a certain group of ecotypes, in which miRNA regulations on the stress genes reprogram. Finally, three case studies showed that reprogramming miRNA-miRNA crosstalk toward the targets in specific ecotypes was associated with these ecotypes' climatic variables and geographical locations. Our study highlights the potential of miRNA-miRNA crosstalk as a genetic basis underlying environmental adaptation in natural populations.

Chromatin Hubs: A biological and computational outlook

This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.

Three-Dimensional Genome Organization in Breast and Gynecological Cancers: How Chromatin Folding Influences Tumorigenic Transcriptional Programs

A growing body of research on the transcriptome and cancer genome has demonstrated that many gynecological tumor-specific gene mutations are located in cis-regulatory elements. Through chromosomal looping, cis-regulatory elements interact which each other to control gene expression by bringing distant regulatory elements, such as enhancers and insulators, into close proximity with promoters. It is well known that chromatin connections may be disrupted in cancer cells, promoting transcriptional dysregulation and the expression of abnormal tumor suppressor genes and oncogenes. In this review, we examine the roles of alterations in 3D chromatin interactions. This includes changes in CTCF protein function, cancer-risk single nucleotide polymorphisms, viral integration, and hormonal response as part of the mechanisms that lead to the acquisition of enhancers or super-enhancers. The translocation of existing enhancers, as well as enhancer loss or acquisition of insulator elements that interact with gene promoters, is also revised. Remarkably, similar processes that modify 3D chromatin contacts in gene promoters may also influence the expression of non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), which have emerged as key regulators of gene expression in a variety of cancers, including gynecological malignancies.

Small RNAs, Big Diseases

The past two decades have seen extensive research done to pinpoint the role of microRNAs (miRNAs) that have led to discovering thousands of miRNAs in humans. It is not, therefore, surprising to see many of them implicated in a number of common as well as rare human diseases. In this review article, we summarize the progress in our understanding of miRNA-related research in conjunction with different types of cancers and neurodegenerative diseases, as well as their potential in generating more reliable diagnostic and therapeutic approaches.

The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook

Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.

Epigenome-wide association study of DNA methylation and microRNA expression highlights novel pathways for human complex traits

DNA methylation (DNAm) and microRNAs (miRNAs) have been implicated in a wide-range of human diseases. While often studied in isolation, DNAm and miRNAs are not independent. We analyzed associations of expression of 283 miRNAs with DNAm at >400K CpG sites in whole blood obtained from 3565 individuals and identified 227 CpGs at which differential methylation was associated with the expression of 40 nearby miRNAs (cis-miR-eQTMs) at FDR<0.01, including 91 independent CpG sites at r² < 0.2. cis-miR-eQTMs were enriched for CpGs in promoter and polycomb-repressed state regions, and 60% were inversely associated with miRNA expression. Bidirectional Mendelian randomization (MR) analysis further identified 58 cis-miR-eQTMCpG-miRNA pairs where DNAm changes appeared to drive miRNA expression changes and opposite directional effects were unlikely. Integration of genetic variants in joint analyses revealed an average partial between cis-miR-eQTM CpGs and miRNAs of 2% after conditioning on site-specific genetic variation, suggesting that DNAm is an important epigenetic regulator of miRNA expression. Finally, two-step MR analysis was performed to identify putatively causal CpGs driving miRNA expression in relation to human complex traits. We found that an imprinted region on 14q32 that was previously identified in relation to age at menarche is enriched with cis-miR-eQTMs. Nine CpGs and three miRNAs at this locus tested causal for age at menarche, reflecting novel epigenetic-driven molecular pathways underlying this complex trait. Our study sheds light on the joint genetic and epigenetic regulation of miRNA expression and provides insights into the relations of miRNAs to their targets and to complex phenotypes.

Combinatorial epigenetic regulation of non-coding RNAs has profound effects on oncogenic pathways in breast cancer subtypes

Although systematic genomic studies have identified a broad spectrum of non-coding RNAs (ncRNAs) that are involved in breast cancer, our understanding of the epigenetic dysregulation of those ncRNAs remains limited. Here, we systematically analysed the epigenetic alterations of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in two breast cancer subtypes (luminal and basal). Widespread epigenetic alterations of miRNAs and lncRNAs were observed in both cancer subtypes. In contrast to protein-coding genes, the majority of epigenetically dysregulated ncRNAs were shared between subtypes, but a subset of transcriptomic and corresponding epigenetic changes occurred in a subtype-specific manner. In addition, our findings suggested that various types of epi-modifications might synergistically modulate ncRNA transcription. Our observations further highlighted the complementary dysregulation of epi-modifications, particularly of miRNA members within the same family, which produced the same directed alterations as a result of diverse epi-modifications. Functional enrichment analysis revealed that epigenetically dysregulated ncRNAs were significantly involved in several hallmarks of cancers. Finally, our analysis of epigenetic modification-mediated miRNA regulatory networks revealed that cancer progression was associated with specific miRNA-gene modules in two subtypes. This study enhances understanding of the aberrant epigenetic patterns of ncRNA expression and provides new insights into the functions of ncRNAs in breast cancer subtypes.

miRNA-miRNA crosstalk: from genomics to phenomics

The discovery of microRNA (miRNA)-miRNA crosstalk has greatly improved our understanding of complex gene regulatory networks in normal and disease-specific physiological conditions. Numerous approaches have been proposed for modeling miRNA-miRNA networks based on genomic sequences, miRNA-mRNA regulation, functional information and phenomics alone, or by integrating heterogeneous data. In addition, it is expected that miRNA-miRNA crosstalk can be reprogrammed in different tissues or specific diseases. Thus, transcriptome data have also been integrated to construct context-specific miRNA-miRNA networks. In this review, we summarize the state-of-the-art miRNA-miRNA network modeling methods, which range from genomics to phenomics, where we focus on the need to integrate heterogeneous types of omics data. Finally, we suggest future directions for studies of crosstalk of noncoding RNAs. This comprehensive summarization and discussion elucidated in this work provide constructive insights into miRNA-miRNA crosstalk.

Hedgehog signaling pathway: Epigenetic regulation and role in disease and cancer development

The evolutionarily conserved Hedgehog (Hh) signaling pathway have critical roles in development and homeostasis of tissues. Under physiological conditions, Hh is controlled at different levels via stem cell maintenance and tissue regeneration. Aberrant activation of this signaling pathway may occur in a wide range of human diseases including different types of cancer. In this review we present a concise overview on the key genes composing Hh signaling pathway and provide recent advances on the molecular mechanisms that regulate Hh signaling pathway from extracellular and receptors to the cytoplasmic and nuclear machinery with a highlight on the role of microRNAs. Furthermore, we focus on critical studies demonstrating dysregulation of the Hh pathway in human disease development, and potential therapeutic implications. Finally, we introduce recent therapeutic drugs acting as Shh signaling pathway inhibitors, including those in clinical trials and preclinical studies.

Drosophila Model for the Analysis of Genesis of LIM-kinase 1-Dependent Williams-Beuren Syndrome Cognitive Phenotypes: INDELs, Transposable Elements of the Tc1/Mariner Superfamily and MicroRNAs

Genomic disorders, the syndromes with multiple manifestations, may occur sporadically due to unequal recombination in chromosomal regions with specific architecture. Therefore, each patient may carry an individual structural variant of DNA sequence (SV) with small insertions and deletions (INDELs) sometimes less than 10 bp. The transposable elements of the Tc1/mariner superfamily are often associated with hotspots for homologous recombination involved in human genetic disorders, such as Williams Beuren Syndromes (WBS) with LIM-kinase 1-dependent cognitive defects. The Drosophila melanogaster mutant agnts3 has unusual architecture of the agnostic locus harboring LIMK1: it is a hotspot of chromosome breaks, ectopic contacts, underreplication, and recombination. Here, we present the analysis of LIMK1-containing locus sequencing data in agnts3 and three D. melanogaster wild-type strains-Canton-S, Berlin, and Oregon-R. We found multiple strain-specific SVs, namely, single base changes and small INDEls. The specific feature of agnts3 is 28 bp A/T-rich insertion in intron 1 of LIMK1 and the insertion of mobile S-element from Tc1/mariner superfamily residing ~460 bp downstream LIMK1 3'UTR. Neither of SVs leads to amino acid substitutions in agnts3 LIMK1. However, they apparently affect the nucleosome distribution, non-canonical DNA structure formation and transcriptional factors binding. Interestingly, the overall expression of miRNAs including the biomarkers for human neurological diseases, is drastically reduced in agnts3 relative to the wild-type strains. Thus, LIMK1 DNA structure per se, as well as the pronounced changes in total miRNAs profile, probably lead to LIMK1 dysregulation and complex behavioral dysfunctions observed in agnts3 making this mutant a simple plausible Drosophila model for WBS.

Deciphering Noncoding RNA and Chromatin Interactions: Multiplex Chromatin Interaction Analysis by Paired-End Tag Sequencing (mChIA-PET)

Genomic DNA is dynamically associated with protein factors and folded to form chromatin fibers. The 3-dimensional (3D) configuration of the chromatin will enable the distal genetic elements to come into close proximity, allowing transcriptional regulation. Noncoding RNA can mediate the 3D structure of chromatin. Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) is a valuable and powerful technique in molecular biology which allows the study of unbiased, genome-wide de novo chromatin interactions with paired-end tags. Here, we describe the standard version of ChIA-PET and a Multiplex ChIA-PET version.

A Comprehensive Characterization of the Function of LincRNAs in Transcriptional Regulation Through Long-Range Chromatin Interactions

LincRNAs are emerging as important regulators with various cellular functions. However, the mechanisms behind their role in transcriptional regulation have not yet been fully explored. In this report, we proposed to characterize the diverse functions of lincRNAs in transcription regulation through an examination of their long-range chromatin interactions. We found that the promoter regions of lincRNAs displayed two distinct patterns of chromatin states, promoter-like and enhancer-like, indicating different regulatory functions for lincRNAs. Notably, the chromatin interactions between lincRNA genes and other genes suggested a potential mechanism for lincRNAs in the regulation of other genes at the RNA level because the transcribed lincRNAs could function at local spaces on other genes that interact with the lincRNAs at the DNA level. These results represent a novel way to predict the functions of lincRNAs. The GWAS-identification of SNPs within the lincRNAs revealed that some lincRNAs were disease-associated, and the chromatin interactions with those lincRNAs suggested that they were potential target genes of these lincRNA-associated SNPs. Our study provides new insights into the roles that lincRNAs play in transcription regulation.

MicroRNAs activate gene transcription epigenetically as an enhancer trigger

MicroRNAs (miRNAs) are small non-coding RNAs that function as negative gene expression regulators. Emerging evidence shows that, except for function in the cytoplasm, miRNAs are also present in the nucleus. However, the functional significance of nuclear miRNAs remains largely undetermined. By screening miRNA database, we have identified a subset of miRNA that functions as enhancer regulators. Here, we found a set of miRNAs show gene-activation function. We focused on miR-24-1 and found that this miRNA unconventionally activates gene transcription by targeting enhancers. Consistently, the activation was completely abolished when the enhancer sequence was deleted by TALEN. Furthermore, we found that miR-24-1 activates enhancer RNA (eRNA) expression, alters histone modification, and increases the enrichment of p300 and RNA Pol II at the enhancer locus. Our results demonstrate a novel mechanism of miRNA as an enhancer trigger.

Exploring the mechanisms of genome-wide long-range interactions: interpreting chromosome organization

Developments in chromosome conformation capture (3C) technologies have revealed that the three-dimensional organization of a genome leads widely separated functional elements to reside in close proximity. However, the mechanisms responsible for mediating long-range interactions are still not completely known. In this review, we firstly evaluate and compare the current seven 3C-based methods, summarize their advantages and discuss their limitations to our current understanding of genome structure. Then, software packages available to perform the analysis of 3C-based data are described. Moreover, we review the insights into the two main mechanisms of long-range interactions, which regulate gene expression by bringing together promoters and distal regulatory elements and by creating structural domains that contain functionally related genes with similar expression landscape. At last, we summarize what is known about the mediating factors involved in stimulation/repression of long-range interactions, such as transcription factors and noncoding RNAs.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).

Regulatory elements can target genes over large genomic distances through long-range chromatin interactions. These interactions arise as a result of the three-dimensional (3D) conformation of chromosomes in the cell nucleus. This 3D conformation can also result in the co-localization of co-regulated genes. To investigate this, we asked whether genome-wide chromatin interactions can predict co-expression patterns of genes. To address this question, we characterized 3D interactions between genes, captured by Hi-C measurements, by a network, termed chromatin interaction network (CIN). We applied scale-aware topological measures to the network to comprehensively characterize the chromatin interactions at different scales, ranging from direct interaction between gene pairs to chromatin compartment interactions. We then used multi-scale chromatin interactions to predict spatial co-expression patterns in the mouse cortex. The results show that the prediction performance improves when scale-aware topological measures of the multi-resolution chromatin interaction network are used.

Loregic: a method to characterize the cooperative logic of regulatory factors

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. We make Loregic available as a general-purpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcription-factor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic’s gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.

Gene expression is controlled by various gene regulatory factors. Those factors work cooperatively forming a complex regulatory circuit genome wide. Corruptions of regulatory cooperativity may lead to abnormal gene expression activity such as cancer. Traditional experimental methods, however, can only identify small-scale regulatory activity. Thus, to systematically understand the cooperativity between and among different types of regulatory factors, we need the efficient and systematic computational methods. Regulatory circuits have been suggested to behave analogously to the electronic circuits in which a wide variety of electronic elements work coordinately to function correctly. Recently, an increasing amount of next generation sequencing data provides a great resource to study regulatory activity. Thus, we developed a general-purpose computational method using logic-circuit models from electronics and applied it to a human leukemia dataset, identifying the genome-wide cooperativity of transcription factors and microRNAs.

Genome-wide identification of microRNA expression quantitative trait loci

Identification of microRNA expression quantitative trait loci (miR-eQTL) can yield insights into regulatory mechanisms of microRNA transcription, and can help elucidate the role of microRNA as mediators of complex traits. Here we present a miR-eQTL mapping study of whole blood from 5239 individuals, and identify 5269 cis-miR-eQTLs for 76 mature microRNAs. Forty-nine percent of cis-miR-eQTLs are located 300–500kb upstream of their associated intergenic microRNAs, suggesting that distal regulatory elements may affect the interindividual variability in microRNA expression levels. We find that cis-miR-eQTLs are highly enriched for cis-mRNA-eQTLs and regulatory SNPs. Among 243 cis-miR-eQTLs that were reported to be associated with complex traits in prior genome-wide association studies, many cis-miR-eQTLs miRNAs display differential expression in relation to the corresponding trait (e.g., rs7115089, miR-125b-5p, and HDL cholesterol). Our study provides a roadmap for understanding the genetic basis of miRNA expression, and sheds light on miRNA involvement in a variety of complex traits.

microRNAs and Personalized Medicine: Evaluating Their Potential as Cancer Biomarkers

microRNA deregulations are often, if not invariably, associated with human malignancies, including cancers. Though most of these deregulations may not be functionally implicated in tumorigenesis, the fact that microRNA expression can be monitored in a variety of human specimens, including biological fluids, supports studies aimed at characterizing microRNA signatures able to detect various cancers (diagnosis), predict their outcome (prognosis), monitor their treatment (theranosis), and adapt therapy to a patient (precision medicine). Here, we review and discuss pros and cons of microRNA-based approaches that can support their exploitation as cancer biomarkers.

Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing technology and application

Background

Long-range chromatin interactions play an important role in transcription regulation. Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET) is an emerging technology that has unique advantages in chromatin interaction analysis, and thus provides insight into the study of transcription regulation.

Results

This article introduces the experimental protocol and data analysis process of ChIA-PET, as well as discusses some applications using this technology. It also unveils the direction of future studies based on this technology.

Conclusions

Overall we show that ChIA-PET is the cornerstone to explore the three-dimensional (3D) chromatin structure, and certainly will lead the forthcoming wave of 3D genomics studies.

Continuing analysis of microRNA origins: Formation from transposable element insertions and noncoding RNA mutations

MicroRNAs (miRs) are small noncoding RNAs that typically act as regulators of gene expression by base pairing with the 3' UTR of messenger RNAs (mRNAs) and either repressing their translation or initiating degradation. As of this writing over 24,500 distinct miRs have been identified, but the functions of the vast majority of these remain undescribed. This paper represents a summary of our in depth analysis of the genomic origins of miR loci, detailing the formation of 1,213 of the 7,321 recently identified miRs and thereby bringing the total number of miR loci with defined molecular origin to 3,605. Interestingly, our analyses also identify evidence for a second, novel mechanism of miR locus generation through describing the formation of 273 miR loci from mutations to other forms of noncoding RNAs. Importantly, several independent investigations of the genomic origins of miR loci have now supported the hypothesis that miR hairpins are formed by the adjacent genomic insertion of two complementary transposable elements (TEs) into opposing strands. While our results agree that subsequent transcription over such TE interfaces leads to the formation of the majority of functional miR loci, we now also find evidence suggesting that a subset of miR loci were actually formed by an alternative mechanism-point mutations in other structurally complex, noncoding RNAs (e.g., tRNAs and snoRNAs).