Global Gene Regulatory Networks Research Articles

Global gene regulatory network underlying miR165a in Arabidopsis shoot apical meristem

Arabidopsis microRNA165a (miR165a) targets Class III Homeodomain Leucine-Zipper (HD-ZIPIII) transcription factors to regulate various aspects of plant development and stress response. Over-expression of miR165a mimics the loss-of-function phenotype of HD-ZIPIII genes and leading to ectopic organ formation, shoot apical meristem (SAM) termination, loss of leaf polarity, and defective vasculature development. However, the molecular mechanisms underlying these phenotypes remain unresolved. Here, we over-expressed miR165a in a dexamethasone inducible manner and identified differentially expressed genes in the SAM through RNA-Seq. Simultaneously, using multi-channel FACS combined with RNA-Seq approach, we characterized global transcriptome patterns in miR165a expressing cell-types compared to HD-ZIPIII expressing cell-types and other cell-types in SAM. By integrating our results we identified sets of genes which are up-regulated by miR165a as well have enriched expression in miR165a cell-types, and vice-versa. Known plant development related genes such as HD-ZIPIII and their targets LITTLE ZIPPERs, Like AUXIN RESISTANT 2, BEL1-like homeodomain 6, ROTUNDIFOLIA like 16 were found to be down-regulated. Among the up-regulated genes, GIBBERELLIN 2-OXIDASEs, various elemental transporters (YSL3, ZIFL1, SULTR), and other transporter genes were prominent. Thus, the genes identified in this study help to unravel the molecular mechanism of miR165a and HD-ZIPIII regulated plant development and stress response.

Targeting hnRNPC suppresses thyroid follicular epithelial cell apoptosis and necroptosis through m6A-modified ATF4 in autoimmune thyroid disease

Both environmental and genetic factors contribute to the etiology of autoimmune thyroid disease (AITD) including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT). However, the exact pathogenesis and interactions that occur between environmental factors and genes remain unclear, and therapeutic targets require further investigation due to limited therapeutic options. To solve such problems, this study utilized single-cell transcriptome, whole transcriptome, full-length transcriptome (Oxford nanopore technology), and metabolome sequencing to examine thyroid lesion tissues from 2 HT patients and 2 GD patients as well as healthy thyroid tissue from 1 control subject. HT patients had increased ATF4-positive thyroid follicular epithelial (ThyFoEp) cells, which significantly increased endoplasmic reticulum stress. The enhanced sustained stress resulted in cell death mainly including apoptosis and necroptosis. The ATF4-based global gene regulatory network and experimental validation revealed that N6-methyladenosine (m6A) reader hnRNPC promoted the transcriptional activity, synthesis, and translation of ATF4 through mediating m6A modification of ATF4. Increased ATF4 expression initiated endoplasmic reticulum stress signaling, which when sustained, caused apoptosis and necroptosis in ThyFoEp cells, and mediated HT development. Targeting hnRNPC and ATF4 notably decreased ThyFoEp cell death, thus ameliorating disease progression. Collectively, this study reveals the mechanisms by which microenvironmental cells in HT and GD patients trigger and amplify the thyroid autoimmune cascade response. Furthermore, we identify new therapeutic targets for the treatment of autoimmune thyroid disease, hoping to provide a potential way for targeted therapy.

Spatially resolved gene regulatory networks in Asian rice (Oryza sativa cv. Nipponbare) leaves.

Transcriptome profiles in plants are heterogenous at every level of morphological organization. Even within organs, cells of the same type can have different patterns of gene expression depending on where they are positioned within tissues. This heterogeneity is associated with non-uniform distribution of biological processes within organs. The regulatory mechanisms that establish and sustain the spatial heterogeneity are unknown. Here, we identify regulatory modules that support functional specialization of different parts of Oryza sativa cv. Nipponbare leaves by leveraging transcriptome data, transcription factor binding motifs and global gene regulatory network prediction algorithms. We generated a global gene regulatory network in which we identified six regulatory modules that were active in different parts of the leaf. The regulatory modules were enriched for genes involved in spatially relevant biological processes, such as cell wall deposition, environmental sensing and photosynthesis. Strikingly, more than 86.9% of genes in the network were regulated by members of only five transcription factor families. We also generated targeted regulatory networks for the large MYB and bZIP/bHLH families to identify interactions that were masked in the global prediction. This analysis will provide a baseline for future single cell and array-based spatial transcriptome studies and for studying responses to environmental stress and demonstrates the extent to which seven coarse spatial transcriptome analysis can provide insight into the regulatory mechanisms supporting functional specialization within leaves.

Using single cell atlas data to reconstruct regulatory networks.

Inference of global gene regulatory networks from omics data is a long-term goal of systems biology. Most methods developed for inferring transcription factor (TF)-gene interactions either relied on a small dataset or used snapshot data which is not suitable for inferring a process that is inherently temporal. Here, we developed a new computational method that combines neural networks and multi-task learning to predict RNA velocity rather than gene expression values. This allows our method to overcome many of the problems faced by prior methods leading to more accurate and more comprehensive set of identified regulatory interactions. Application of our method to atlas scale single cell data from 6 HuBMAP tissues led to several validated and novel predictions and greatly improved on prior methods proposed for this task.

A Systemic and Integrated Analysis of p63-Driven Regulatory Networks in Mouse Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common malignancy of the oral cavity and is linked to tobacco exposure, alcohol consumption, and human papillomavirus infection. Despite therapeutic advances, a lack of molecular understanding of disease etiology, and delayed diagnoses continue to negatively affect survival. The identification of oncogenic drivers and prognostic biomarkers by leveraging bulk and single-cell RNA-sequencing datasets of OSCC can lead to more targeted therapies and improved patient outcomes. However, the generation, analysis, and continued utilization of additional genetic and genomic tools are warranted. Tobacco-induced OSCC can be modeled in mice via 4-nitroquinoline 1-oxide (4NQO), which generates a spectrum of neoplastic lesions mimicking human OSCC and upregulates the oncogenic master transcription factor p63. Here, we molecularly characterized established mouse 4NQO treatment-derived OSCC cell lines and utilized RNA and chromatin immunoprecipitation-sequencing to uncover the global p63 gene regulatory and signaling network. We integrated our p63 datasets with published bulk and single-cell RNA-sequencing of mouse 4NQO-treated tongue and esophageal tumors, respectively, to generate a p63-driven gene signature that sheds new light on the role of p63 in murine OSCC. Our analyses reveal known and novel players, such as COTL1, that are regulated by p63 and influence various oncogenic processes, including metastasis. The identification of new sets of potential biomarkers and pathways, some of which are functionally conserved in human OSCC and can prognosticate patient survival, offers new avenues for future mechanistic studies.

Inferring and perturbing cell fate regulomes in human brain organoids.

Self-organizing neural organoids grown from pluripotent stem cells1-3 combined with single-cell genomic technologies provide opportunities to examine gene regulatory networks underlying human brain development. Here we acquire single-cell transcriptome and accessible chromatin data over a dense time course in human organoids covering neuroepithelial formation, patterning, brain regionalization and neurogenesis, and identify temporally dynamic and brain-region-specific regulatory regions. We developed Pando-a flexible framework that incorporates multi-omic data and predictions of transcription-factor-binding sites to infer a global gene regulatory network describing organoid development. We use pooled genetic perturbation with single-cell transcriptome readout to assess transcription factor requirement for cell fate and state regulation in organoids. We find that certain factors regulate the abundance of cell fates, whereas other factors affect neuronal cell states after differentiation. We show that the transcription factor GLI3 is required for cortical fate establishment in humans, recapitulating previous research performed in mammalian model systems. We measure transcriptome and chromatin accessibility in normal or GLI3-perturbed cells and identify two distinct GLI3 regulomes that are central to telencephalic fate decisions: one regulating dorsoventral patterning with HES4/5 as direct GLI3 targets, and one controlling ganglionic eminence diversification later in development. Together, we provide a framework for how human model systems and single-cell technologies can be leveraged to reconstruct human developmental biology.

Pan-Cancer Analysis Reveals a Distinct Neutrophil Extracellular Trap-Associated Regulatory Pattern.

BackgroundNeutrophils form extracellular net-like structures called neutrophil extracellular traps (NETs). Emerging evidence has shown that cancer can induce NET formation; however, it is not fully understood how NETs influence cancer biology, and no consensus has been reached on their pro- or antitumor effects. A comprehensive analysis of the global NET-associated gene regulatory network is currently unavailable and is urgently needed.MethodsWe systematically explored and discussed NET enrichment, NET-associated gene regulatory patterns, and the prognostic implications of NETs in approximately 8,000 patients across 22 major human cancer types. We identified NET-associated regulatory gene sets that we then screened for NET-associated regulatory patterns that might affect patient survival. We functionally annotated the NET-associated regulatory patterns to compare the biological differences between NET-related survival subgroups.ResultsA gene set variation analysis (GSVA) based on 23 major component genes was used to calculate a metric called the NET score. We found that the NET score was closely associated with many important cancer hallmarks, particularly inflammatory responses and epithelial-to-mesenchymal transition (EMT)-induced metastasis. Higher NET scores were related to poor immunotherapy response. Survival analysis revealed that NETs had diverse prognostic impacts among various cancer types. The NET-associated regulatory patterns linked to shorter or longer cancer patient survival were distinct from each other. Functional analysis revealed that more of the NET-associated regulatory genes linked to poor cancer survival were associated with extracellular matrix (ECM) remodeling and pan-cancerous risk factors. SPP1 was found to be highly expressed and correlated with NET formation in cancers with poor survival. We also found that the co-upregulation of NET formation and SPP1 expression was closely linked to increased EMT and poor survival, that SPP1 influenced NET-induced malignant capacity, and that SPP1 overproduction induced a robust formation of metastatic-promoting NETs.ConclusionNETs were common across cancers but displayed a diverse regulatory pattern and outcome readouts in different cancer types. SPP1 is potentially the key to NET-related poor outcomes.

A spatial-temporal understanding of gene regulatory networks and NtARF-mediated regulation of potassium accumulation in tobacco.

After tobacco topping, changes in the auxin content could affect K+ uptake by inhibiting the activity of K+ uptake-related genes through the NtARF genes, thus causing changes in K+ content. Tobacco (Nicotiana tabacum) is a valuable industrial and commercial crop, and the leaf is its primary product. Topping (removing apical buds) is a common agronomic practice that significantly improves the yield of tobacco leaves. Potassium (K+) plays an important physiological role in tobacco growth and leaf traits, including combustibility, aroma, and safety in cigarette products, and its levels are significantly decreased after topping. Here, to present global spatial-temporal gene expression profiles and gene regulatory networks of the core elements of K+ uptake, leaves and roots from topped and untopped plants at short- and long-term time points after topping were sampled for transcriptome analysis. We found that the wounding response was initiated in leaves in the early stages after topping. Then, in the long term, processes related to metabolism and transcription regulation, as well as ion binding and transport, were altered. The expression profiles showed that core elements of K+ uptake and xylem loading were drastically suppressed in roots after topping. Finally, transient expression experiments confirmed that changes in the auxin content could affect K+ uptake by inhibiting the activity of K+ uptake-related genes through the tobacco auxin response factor (NtARF) genes, thus causing changes in the K+ content. These results suggest that some ARFs could be selected as targets to enhance the expressions of K+ uptake transporters, leading to increment of K+ contents and improvement of leaf quality in tobacco breeding.

Gene Regulatory Networks of Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 Inferred by a Computational Biology Approach.

Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 are well-known cellulase fungal producers. However, few studies addressing global mechanisms for gene regulation of these two important organisms are available so far. A recent finding that the 2HH wild-type is closely related to P. oxalicum leads to a combined study of these two species. Firstly, we provide a global gene regulatory network for P. echinulatum 2HH and P. oxalicum 114-2, based on TF-TG orthology relationships, considering three related species with well-known regulatory interactions combined with TFBSs prediction. The network was then analyzed in terms of topology, identifying TFs as hubs, and modules. Based on this approach, we explore numerous identified modules, such as the expression of cellulolytic and xylanolytic systems, where XlnR plays a key role in positive regulation of the xylanolytic system. It also regulates positively the cellulolytic system by acting indirectly through the cellodextrin induction system. This remarkable finding suggests that the XlnR-dependent cellulolytic and xylanolytic regulatory systems are probably conserved in both P. echinulatum and P. oxalicum. Finally, we explore the functional congruency on the genes clustered in terms of communities, where the genes related to cellular nitrogen, compound metabolic process and macromolecule metabolic process were the most abundant. Therefore, our approach allows us to confer a degree of accuracy regarding the existence of each inferred interaction.

Globally learning gene regulatory networks based on hidden atomic regulators from transcriptomic big data

BackgroundGenes are regulated by various types of regulators and most of them are still unknown or unobserved. Current gene regulatory networks (GRNs) reverse engineering methods often neglect the unknown regulators and infer regulatory relationships in a local and sub-optimal manner.ResultsThis paper proposes a global GRNs inference framework based on dictionary learning, named dlGRN. The method intends to learn atomic regulators (ARs) from gene expression data using a modified dictionary learning (DL) algorithm, which reflects the whole gene regulatory system, and predicts the regulation between a known regulator and a target gene in a global regression way. The modified DL algorithm fits the scale-free property of biological network, rendering dlGRN intrinsically discern direct and indirect regulations.ConclusionsExtensive experimental results on simulation and real-world data demonstrate the effectiveness and efficiency of dlGRN in reverse engineering GRNs. A novel predicted transcription regulation between a TF TFAP2C and an oncogene EGFR was experimentally verified in lung cancer cells. Furthermore, the real application reveals the prevalence of DNA methylation regulation in gene regulatory system. dlGRN can be a standalone tool for GRN inference for its globalization and robustness.

Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments.

Understanding how gene expression programs are controlled requires identifying regulatory relationships between transcription factors and target genes. Gene regulatory networks are typically constructed from gene expression data acquired following genetic perturbation or environmental stimulus. Single-cell RNA sequencing (scRNAseq) captures the gene expression state of thousands of individual cells in a single experiment, offering advantages in combinatorial experimental design, large numbers of independent measurements, and accessing the interaction between the cell cycle and environmental responses that is hidden by population-level analysis of gene expression. To leverage these advantages, we developed a method for scRNAseq in budding yeast (Saccharomyces cerevisiae). We pooled diverse transcriptionally barcoded gene deletion mutants in 11 different environmental conditions and determined their expression state by sequencing 38,285 individual cells. We benchmarked a framework for learning gene regulatory networks from scRNAseq data that incorporates multitask learning and constructed a global gene regulatory network comprising 12,228 interactions.

Whole Transcriptome Analysis of Obese Adipose Tissue Suggests u001kfc.1 as a Potential Regulator to Glucose Homeostasis.

Long non-coding RNA (LncRNAs) are newly highlighted key factors controlling brown adipogenesis and development, but their regulatory effect to white adipocyte is still merely understood. Deciphering their underlying mechanism could be a novel way to discovering potential targets of obesity. Therefore, we conducted a whole transcriptome analysis in white adipose tissue from obese patients for the first time. Six obese patients and five control subjects were selected for microarray assay. Differentially expressed coding genes (DEGs), targets of lncRNAs, and alternatively spliced genes in obesity group were systematically compared in a functional framework based on a global gene regulatory network. It was demonstrated that all the three kinds of transcripts were enriched in pathways related to glucose metabolism while only DEGs showed closer proximity to neuro-endocrine-immune system. Thus, a lncRNA-regulated core network was constructed by a stepwise strategy using DEGs as seed nodes. From the core network, we identified a decreased lncRNA, uc001kfc.1, as potential cis-regulator for phosphatase and tensin homolog (PTEN) to enhance insulin sensitivity of white adipocytes in obese patients. We further validated the down-regulation of uc001kfc.1 and PTEN in an independent testing sample set enrolling 22 subjects via qRT-PCR. Although whether the decreased uc001kfc.1 correlated with low risk of diabetes deserved to be examined in an expanded cohort with long-term follow-up visit, the present study highlighted the potential of lncRNA regulating glucose homeostasis in human adipose tissue from a global perspective. With further improvement, such network-based analyzing protocol proposed in this study could be applied to interpreting function of more lncRNAs from other whole transcriptome data.

Reconstruction of the Global Neural Crest Gene Regulatory Network InVivo.

SummaryPrecise control of developmental processes is encoded in the genome in the form of gene regulatory networks (GRNs). Such multi-factorial systems are difficult to decode in vertebrates owing to their complex gene hierarchies and dynamic molecular interactions. Here we present a genome-wide in vivo reconstruction of the GRN underlying development of the multipotent neural crest (NC) embryonic cell population. By coupling NC-specific epigenomic and transcriptional profiling at population and single-cell levels with genome/epigenome engineering in vivo, we identify multiple regulatory layers governing NC ontogeny, including NC-specific enhancers and super-enhancers, novel trans-factors, and cis-signatures allowing reverse engineering of the NC-GRN at unprecedented resolution. Furthermore, identification and dissection of divergent upstream combinatorial regulatory codes has afforded new insights into opposing gene circuits that define canonical and neural NC fates early during NC ontogeny. Our integrated approach, allowing dissection of cell-type-specific regulatory circuits in vivo, has broad implications for GRN discovery and investigation.

Lateral Root and Nodule Transcriptomes of Soybean

Symbiotic legume nodules and lateral roots arise away from the root meristem via dedifferentiation events. While these organs share some morphological and developmental similarities, whether legume nodules are modified lateral roots is an open question. We dissected emerging nodules, mature nodules, emerging lateral roots and young lateral roots, and constructed strand-specific RNA sequencing (RNAseq) libraries using polyA-enriched RNA preparations. Root sections above and below these organs, devoid of any lateral organs, were used to construct respective control tissue libraries. High sequence quality, predominant mapping to coding sequences, and consistency between replicates indicated that the RNAseq libraries were of a very high quality. We identified genes enriched in emerging nodules, mature nodules, emerging lateral roots and young lateral roots in soybean by comparing global gene expression profiles between each of these organs and adjacent root segments. Potential uses for this high quality transcriptome data set include generation of global gene regulatory networks to identify key regulators; metabolic pathway analyses and comparative analyses of key gene families to discover organ-specific biological processes; and identification of organ-specific alternate spliced transcripts. When combined with other similar datasets, especially from leguminous plants, these analyses can help answer questions on the evolutionary origins of root nodules and relationships between the development of different plant lateral organs.

Influence of global gene regulatory networks on single cell heterogeneity of green fluorescent protein production in Bacillus subtilis

BackgroundGram-positive bacterium Bacillus subtilis has been extensively studied as a microbial cell factory for high-level producing a wide range of interesting products. Green fluorescent protein (GFP) is commonly used as a marker for determining the strength of a given promoter or for the subcellular localization of a fusion protein. However, the inherent heterogeneity of GFP expression among individual cells that can arise from global regulation differences in the expression host, has not yet been systematically assessed. B. subtilis strains with single mutation(s) in the two major transcriptional regulators CcpA and/or CodY were earlier found to improve overall heterologous protein production levels. Here, we investigate the dynamic production performance of GFP in the reporter strains with chromosomally integrated Physpank-sfGFP(Sp).ResultsThe mutation R214C in the DNA-binding domain of CodY effectively enhances GFP production at the population level relative to two other strains, i.e. wildtype (WT) and CcpAT19S. During the late stationary phase, the high- and low-level GFP-producing cells coexist in the WT population, while the CodYR214C population at the single-cell level shows higher phenotypic homogeneity of fluorescence signals.ConclusionExpression of GFP is prominently heterogeneous in the WT B. subtilis cells, and this phenotypic heterogeneity can be significantly reduced by CodYR214C mutation. The rates of production heterogeneity show a high correlation to the overall GFP yields. Moreover, the toolkit of flow cytometry and fluorescence microscopy that can achieve real-time profiles of GFP production performance in various strains may facilitate the further use of B. subtilis as a cell factory.

Transcriptional Regulation in Archaea: From Individual Genes to Global Regulatory Networks.

Archaea are major contributors to biogeochemical cycles, possess unique metabolic capabilities, and resist extreme stress. To regulate the expression of genes encoding these unique programs, archaeal cells use gene regulatory networks (GRNs) composed of transcription factor proteins and their target genes. Recent developments in genetics, genomics, and computational methods used with archaeal model organisms have enabled the mapping and prediction of global GRN structures. Experimental tests of these predictions have revealed the dynamical function of GRNs in response to environmental variation. Here, we review recent progress made in this area, from investigating the mechanisms of transcriptional regulation of individual genes to small-scale subnetworks and genome-wide global networks. At each level, archaeal GRNs consist of a hybrid of bacterial, eukaryotic, and uniquely archaeal mechanisms. We discuss this theme from the perspective of the role of individual transcription factors in genome-wide regulation, how these proteins interact to compile GRN topological structures, and how these topologies lead to emergent, high-level GRN functions. We conclude by discussing how systems biology approaches are a fruitful avenue for addressing remaining challenges, such as discovering gene function and the evolution of GRNs.

Comparative transcriptomic analysis reveals the oncogenic fusion protein PAX3-FOXO1 globally alters mRNA and miRNA to enhance myoblast invasion.

Rhabdomyosarcoma, one of the most common childhood sarcomas, is comprised of two main subtypes, embryonal and alveolar (ARMS). ARMS, the more aggressive subtype, is primarily characterized by the t(2;13)(p35;p14) chromosomal translocation, which fuses two transcription factors, PAX3 and FOXO1 to generate the oncogenic fusion protein PAX3-FOXO1. Patients with PAX3-FOXO1-postitive tumors have a poor prognosis, in part due to the enhanced local invasive capacity of these cells, which leads to the increased metastatic potential for this tumor. Despite this knowledge, little is known about the role that the oncogenic fusion protein has in this increased invasive potential. In this report we use large-scale comparative transcriptomic analyses in physiologically relevant primary myoblasts to demonstrate that the presence of PAX3-FOXO1 is sufficient to alter the expression of 70 mRNA and 27 miRNA in a manner predicted to promote cellular invasion. In contrast the expression of PAX3 alters 60 mRNA and 23 miRNA in a manner predicted to inhibit invasion. We demonstrate that these alterations in mRNA and miRNA translate into changes in the invasive potential of primary myoblasts with PAX3-FOXO1 increasing invasion nearly 2-fold while PAX3 decreases invasion nearly 4-fold. Taken together, these results allow us to build off of previous reports and develop a more expansive molecular model by which the presence of PAX3-FOXO1 alters global gene regulatory networks to enhance the local invasiveness of cells. Further, the global nature of our observed changes highlights the fact that instead of focusing on a single-gene target, we must develop multi-faceted treatment regimens targeting multiple genes of a single oncogenic phenotype or multiple genes that target different oncogenic phenotypes for tumor progression.

Bioinformatic exploration of MTA1-regulated gene networks in colon cancer.

Metastasis-associated gene 1 (MTA1) controls a series of biological processes in tumor progression. Tumor progression is a complex process regulated by a gene network. The global cancer gene regulatory network must be analyzed to determine the position of MTA1 in the molecular network and its cooperative genes by further exploring the biological functions of this gene. We used TCGA data sets and GeneCards database to screen MTA1-related genes. GO and KEGG pathway analyses were conducted with DAVID and gene network analysis via STRING and Cytoscape. Results showed that in the development of colon cancer, MTA1 is linked to certain signal pathways, such as Wnt/Notch/nucleotide excision repair pathways. The findings also suggested that MTA1 demonstrates the closest relationship in a coregulation process with the key molecules AKT1, EP300, CREBBP, SMARCA4, RHOA, and CAD. These results lead MTA1 exploration to an in-depth investigation in different directions, such as Wnt, Notch, and DNA repair.

Next-Generation Sequencing in the Understanding of Kaposi's Sarcoma-Associated Herpesvirus (KSHV) Biology.

Non-Sanger-based novel nucleic acid sequencing techniques, referred to as Next-Generation Sequencing (NGS), provide a rapid, reliable, high-throughput, and massively parallel sequencing methodology that has improved our understanding of human cancers and cancer-related viruses. NGS has become a quintessential research tool for more effective characterization of complex viral and host genomes through its ever-expanding repertoire, which consists of whole-genome sequencing, whole-transcriptome sequencing, and whole-epigenome sequencing. These new NGS platforms provide a comprehensive and systematic genome-wide analysis of genomic sequences and a full transcriptional profile at a single nucleotide resolution. When combined, these techniques help unlock the function of novel genes and the related pathways that contribute to the overall viral pathogenesis. Ongoing research in the field of virology endeavors to identify the role of various underlying mechanisms that control the regulation of the herpesvirus biphasic lifecycle in order to discover potential therapeutic targets and treatment strategies. In this review, we have complied the most recent findings about the application of NGS in Kaposi’s sarcoma-associated herpesvirus (KSHV) biology, including identification of novel genomic features and whole-genome KSHV diversities, global gene regulatory network profiling for intricate transcriptome analyses, and surveying of epigenetic marks (DNA methylation, modified histones, and chromatin remodelers) during de novo, latent, and productive KSHV infections.

Chronic binge alcohol administration dysregulates global regulatory gene networks associated with skeletal muscle wasting in simian immunodeficiency virus-infected macaques

BackgroundThere are more than 1 million persons living with HIV/AIDS (PLWHA) in the United States and approximately 40 % of them have a history of alcohol use disorders (AUD). Chronic heavy alcohol consumption and HIV/AIDS both result in reduced lean body mass and muscle dysfunction, increasing the incidence of comorbid conditions. Previous studies from our laboratory using rhesus macaques infected with Simian Immunodeficiency Virus (SIV) demonstrated that chronic binge alcohol (CBA) administration in the absence of antiretroviral therapy exacerbates skeletal muscle (SKM) wasting at end-stage SIV disease. The aim of this study was to characterize how CBA alters global gene regulatory networks that lead to SKM wasting at end-stage disease. Administration of intragastric alcohol or sucrose to male rhesus macaques began 3 months prior to SIV infection and continued throughout the duration of study. High-output array analysis was used to determine CBA-dependent changes in mRNA expression, miRNA expression, and promoter methylation status of SKM at end-stage disease (~10 months post-SIV) from healthy control (control), sucrose-administered, SIV-infected (SUC/SIV), and CBA-administered/SIV-infected (CBA/SIV) macaques.ResultsIn addition to previously reported effects on the extracellular matrix and the promotion of a pro-inflammatory environment, we found that CBA adversely affects gene regulatory networks that involve “universal” cellular functions, protein homeostasis, calcium and ion homeostasis, neuronal growth and signaling, and satellite cell growth and survival.ConclusionsThe results from this study provide an overview of the impact of CBA on gene regulatory networks involved in biological functions, including transcriptional and epigenetic processes, illustrating the genetic and molecular mechanisms associated with CBA-dependent SKM wasting at end-stage SIV infection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2329-z) contains supplementary material, which is available to authorized users.