Potential Regulatory Interactions Research Articles

Correlation of Prognostic Factors of Invasive Lobular Carcinoma and Invasive Ductal Carcinoma

One of the biggest risks facing women in the twenty-first century is breast cancer. Invasion lobular carcinoma and invasion ductal carcinoma are the two main categories into which it is divided. Omics data is used to identify predictive biomarker signatures for clinical applications to detect breast cancer. Predictive performance has significantly improved because of recent advancements in machine learning techniques. Here, we are using an approach built on symbolic regression called the QLattice on a variety of clinical omics data sets. Through the identification of potential regulatory interactions between biomolecules, this method creates efficient, high-performing models that can forecast and explain the results of a specific omics experiment. The models have the potential to make it easier to find new biomarker signatures due to their clarity and obvious functional shape, which make them simple and easy to comprehend. A comprehensive experimental investigation was conducted to assess the machine learning model's efficacy in terms of the Area under the Curve (AUC) for breast cancer. The outcomes, which were contrasted with other approaches, demonstrate the suggested framework's efficacy and capacity to beat the alternative algorithms in terms of AUC, which is 0.66. Here, we profiled breast tumors in detail, including ductal carcinoma, mixed carcinoma, and invasive lobular carcinoma, by using the Gaussian method and TNXB gene.

Genome-wide identification of salinity stress-associated lncRNAs in Nile tilapia

Long noncoding RNAs (lncRNAs) are increasingly recognized as key players in various biological processes, yet their role in fish's response to salinity changes remains largely unexplored. This study undertakes a genome-wide analysis of lncRNAs in Nile tilapia (Oreochromis niloticus), examining their response to salinity stress across a substantial dataset of 98 RNA-seq samples from nine different tissues. We identified 28,819 high-confidence lncRNA candidates, which are characterized by a shorter average length of 788 nucleotides and fewer exons (average 1.84) compared to mRNAs. Specifically, in the gills exposed to salinity 27 for three and a half months, we found 846 differentially expressed lncRNAs (DElncRNAs), including 342 upregulated and 504 downregulated transcripts. The study also highlighted 220 significant DElncRNA-mRNA pairs, indicating potential regulatory interactions. Notably, in response to acute salinity stress, we identified 989 DElncRNAs, with 414 upregulated and 575 downregulated in gills. An analysis of these DElncRNAs revealed 348 high-confidence pairs, with Gene Ontology (GO) and KEGG pathway analyses indicating a prominent role in immune-inflammatory responses for most target genes, such as trim7, trim35, trim47, cd225. Crucially, two DElncRNAs (ENSONIT00000076723 and MSTRG.18195.2) were found to co-localize with QTL intervals associated with salinity tolerance, situated near three significant SNPs. Additionally, a notable cis-acting pair, consisting of mRNA ENSONIT00000087370 (apold1a) and lncRNA ENSONIT00000076723, demonstrated a strong correlation under both acute and chronic hypo-osmotic stress. Our findings significantly broaden the understanding of lncRNAs in salinity stress adaptation and suggest their novel roles as key regulators in the osmoregulatory mechanisms of Nile tilapia.

N-cadherin and β1 integrin coordinately regulate growth plate cartilage architecture.

Spatial and temporal regulation of chondrocyte maturation in the growth plate drives growth of many bones. One essential event to generate the ordered cell array characterizing growth plate cartilage is the formation of chondrocyte columns in the proliferative zone via 90-degree rotation of daughter cells to align with the long axis of the bone. Previous studies have suggested crucial roles for cadherins and integrin β1 in column formation. The purpose of this study was to determine the relative contributions of cadherin- and integrin-mediated cell adhesion in column formation. Here we present new mechanistic insights generated by application of live time-lapse confocal microscopy of cranial base explant cultures, robust genetic mouse models, and new quantitative methods to analyze cell behavior. We show that conditional deletion of either the cell-cell adhesion molecule Cdh2 or the cell-matrix adhesion molecule Itgb1 disrupts column formation. Compound mutants were used to determine a potential reciprocal regulatory interaction between the two adhesion surfaces and identified that defective chondrocyte rotation in a N-cadherin mutant was restored by a heterozygous loss of integrin β1. Our results support a model for which integrin β1, and not N-cadherin, drives chondrocyte rotation and for which N-cadherin is a potential negative regulator of integrin β1 function.

Deciphering regulatory patterns in a mouse model of hyperoxia-induced acute lung injury.

Oxygen therapy plays a pivotal role in treating critically ill patients in the intensive care unit (ICU). However, excessive oxygen concentrations can precipitate hyperoxia, leading to damage in multiple organs, with a notable effect on the lungs. Hyperoxia condition may lead to hyperoxia-induced acute lung injury (HALI), deemed as a milder form of acute respiratory distress syndrome (ARDS). Given its clinical importance and practical implications, there is a compelling need to investigate the underlying pathogenesis and comprehensively understand the regulatory mechanisms implicated in the development of HALI. In this study, we conducted a mouse model with HALI and performed regulatory mechanism analysis using RNA-seq on both HALI and control group. Comprehensive analysis revealed 727 genes of significant differential expression, including 248 long non-coding RNAs (lncRNAs). Also, alternative splicing events were identified from sequencing results. Notably, we observed up-regulation or abnormal alternative splicing of genes associated with immune response and ferroptosis under hyperoxia conditions. Utilizing weighted gene co-expression network analysis (WGCNA), we ascertained that genes involved in immune response formed a distinct cluster, showcasing an up-regulated pattern in hyperoxia, consistent with previous studies. Furthermore, a competing endogenous RNA (ceRNA) network was constructed, including 78 differentially expressed mRNAs and six differentially expressed lncRNAs, including H19. These findings uncover the intricate interplay of multiple transcriptional regulatory mechanisms specifically tailored to the pulmonary defense against HALI, substantiating the importance of these non-coding RNAs in this disease context. Our results provide new insights into the potential mechanisms and underlying pathogenesis in the development of HALI at the post-transcriptional level. The findings of this study reveal potential regulatory interactions and biological roles of specific lncRNAs and genes, such as H19 and Sox9, encompassing driven gene expression patterns, alternative splicing events, and lncRNA-miRNA-mRNA ceRNA networks. These findings may pave the way for advancing therapeutic strategies and reducing the risk associated with oxygen treatment for patients.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks

ObjectiveThis study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA.MethodsMicroarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA.ResultsThe 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions.ConclusionThe findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.

Schwann Cells Are Key Regulators of Corneal Epithelial Renewal.

Corneal sensory nerves protect the cornea from injury. They are also thought to stimulate limbal stem cells (LSCs) to produce transparent epithelial cells constantly, enabling vision. In other organs, Schwann cells (SCs) associated with tissue-innervating axon terminals mediate tissue regeneration. This study defines the critical role of the corneal axon-ensheathing SCs in homeostatic and regenerative corneal epithelial cell renewal. SC localization in the cornea was determined by in situ hybridization and immunohistochemistry with SC markers. In vivo SC visualization and/or ablation were performed in mice with inducible corneal SC-specific expression of tdTomato and/or Diphtheria toxin, respectively. The relative locations of SCs and LSCs were observed with immunohistochemical analysis of harvested genetically SC-prelabeled mouse corneas with LSC-specific antibodies. The correlation between cornea-innervating axons and the appearance of SCs was ascertained using corneal denervation in rats. To determine the limbal niche cellular composition and gene expression changes associated with innervation-dependent epithelial renewal, single-cell RNA sequencing (scRNA-seq) of dissociated healthy, de-epithelized, and denervated cornea limbi was performed. We observed limbal enrichment of corneal axon-associated myelinating and non-myelinating SCs. Induced local genetic ablation of SCs, although leaving corneal sensory innervation intact, markedly inhibited corneal epithelial renewal. scRNA-seq analysis (1) highlighted the transcriptional heterogenicity of cells populating the limbal niche, and (2) identified transcriptional changes associated with corneal innervation and during wound healing that model potential regulatory paracrine interactions between SCs and LSCs. Limbal SCs are required for innervation-dependent corneal epithelial renewal.

Conjoint Analysis of Genome-Wide lncRNA and mRNA Expression during the Salicylic Acid Response in Populus × euramericana.

Long noncoding RNAs (lncRNAs) participate in a wide range of biological processes, but lncRNAs in plants remain largely unknown; in particular, we lack a systematic identification of plant lncRNAs involved in hormone responses. To explore the molecular mechanism of the response of poplar to salicylic acid (SA), the changes in protective enzymes, which are closely related to plant resistance induced by exogenous SA, were studied, and the expression of mRNA and lncRNA were determined by high-throughput RNA sequencing. The results showed that the activities of phenylalanine ammonia lyase (PAL) and polyphenol oxidase (PPO), in the leaves of Populus × euramericana, were significantly increased by exogenous SA application. High-throughput RNA sequencing showed that 26,366 genes and 5690 lncRNAs were detected under the different treatment conditions: SA and H2O application. Among these, 606 genes and 49 lncRNAs were differentially expressed. According to target prediction, lncRNAs and target genes involved in light response, stress response, plant disease resistance, and growth and development, were differentially expressed in SA-treated leaves. Interaction analysis showed that lncRNA-mRNA interactions, following exogenous SA, were involved in the response of poplar leaves to the external environment. Our study provides a comprehensive view of Populus × euramericana lncRNAs and offers insights into the potential functions and regulatory interactions of SA-responsive lncRNAs, thus forming the foundation for future functional analysis of SA-responsive lncRNAs in Populus × euramericana.

Analysis of ancient and modern horse genomes reveals the critical impact of lncRNA-mediated epigenetic regulation on horse domestication.

Background: The domestication of horses has played critical roles in human civilizations. The excavation of ancient horse DNA provides crucial data for studying horse domestication. Studies of horse domestication can shed light on the general mechanisms of animal domestication. Objective: We wish to explore the gene transcription regulation by long noncoding RNAs (lncRNAs) that influence horse domestication. Methods: First, we assembled the ancient DNA sequences of multiple horses at different times and the genomes of horses, donkeys, and Przewalski horses. Second, we extracted sequences of lncRNA genes shared in ancient horses and sequences of lncRNA genes and the promoter regions of domestication-critical genes shared in modern horses, modern donkeys, and Przewalski horses to form two sample groups. Third, we used the LongTarget program to predict potential regulatory interactions between these lncRNAs and these domestication-critical genes and analyzed the differences between the regulation in ancient/modern horses and between horses/donkeys/Przewalski horses. Fourth, we performed functional enrichment analyses of genes that exhibit differences in epigenetic regulation. Results: First, genes associated with neural crest development and domestication syndrome are important targets of lncRNAs. Second, compared with undomesticated Przewalski horses, more lncRNAs participate in the epigenetic regulation in modern horses and donkeys, suggesting that domestication is linked to more epigenetic regulatory changes. Third, lncRNAs’ potential target genes in modern horses are mainly involved in two functional areas: 1) the nervous system, behavior, and cognition, and 2) muscle, body size, cardiac function, and metabolism. Conclusion: Domestication is linked to substantial epigenetic regulatory changes. Genes associated with neural crest development and domestication syndrome underwent noticeable lncRNA-mediated epigenetic regulation changes during horse domestication.

Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data.

Single-cell RNA sequencing (scRNA-seq) data provides unprecedented opportunities to reconstruct gene regulatory networks (GRNs) at fine-grained resolution. Numerous unsupervised or self-supervised models have been proposed to infer GRN from bulk RNA-seq data, but few of them are appropriate for scRNA-seq data under the circumstance of low signal-to-noise ratio and dropout. Fortunately, the surging of TF-DNA binding data (e.g. ChIP-seq) makes supervised GRN inference possible. We regard supervised GRN inference as a graph-based link prediction problem that expects to learn gene low-dimensional vectorized representations to predict potential regulatory interactions. In this paper, we present GENELink to infer latent interactions between transcription factors (TFs) and target genes in GRN using graph attention network. GENELink projects the single-cell gene expression with observed TF-gene pairs to a low-dimensional space. Then, the specific gene representations are learned to serve for downstream similarity measurement or causal inference of pairwise genes by optimizing the embedding space. Compared to eight existing GRN reconstruction methods, GENELink achieves comparable or better performance on seven scRNA-seq datasets with four types of ground-truth networks. We further apply GENELink on scRNA-seq of human breast cancer metastasis and reveal regulatory heterogeneity of Notch and Wnt signalling pathways between primary tumour and lung metastasis. Moreover, the ontology enrichment results of unique lung metastasis GRN indicate that mitochondrial oxidative phosphorylation (OXPHOS) is functionally important during the seeding step of the cancer metastatic cascade, which is validated by pharmacological assays. The code and data are available at https://github.com/zpliulab/GENELink. Supplementary data are available at Bioinformatics online.

NCAD and ITGB1 Coordinately Regulate Growth Plate Cartilage Architecture

Spatial and temporal regulation of chondrocyte maturation in the growth plate drives long bone growth. A notable feature of growth plate cartilage is the progression of progenitor resting chondrocytes into clonal columns of transit‐amplifying proliferative chondrocytes. Following division of proliferative chondrocytes, daughter cell pairs undergo a unique 90‐degree rearrangement to form columns. Our previous studies using a murine fluorescent membrane reporter system and time‐lapse imaging along with chemical inhibition of cell adhesion suggested a primary requirement for cadherin adhesion at the daughter cell interface in column formation. Studies designed to test the force generating mechanism at the cadherin dependent daughter cell interface produced a paradoxical result with activated myosin motor proteins enriched at the cell‐matrix interface, an observation that suggests integrin adhesion molecules might drive cell rearrangement. The purpose of the current work was to determine the relative contributions of cadherin and integrin mediated cell adhesion in chondrocyte column formation. As a first step, we used live cell imaging to compare the daughter cell rearrangement phenotype in growth plate explants from embryos containing a cartilage‐specific deletion of N‐cadherin (NCAD) or integrin β1 (ITGB1). Deletion of either gene produces similar disruption of column formation, even though the mutant phenotypes show differences in cell shape, rearrangement dynamics, and kinetics of daughter cell separation following rearrangement. The apparent requirement for both NCAD and ITGB1 suggested potential reciprocal regulatory interaction between the two adhesion surfaces. To test this hypothesis, we analyzed phenotypes of an allelic series. We found that chondrocytes mutant for ITGB1 show defects in cell rearrangement and column formation (n=37 embryos) regardless of the NCAD genotype as expected from single mutant studies. Surprisingly, chondrocytes mutant for NCAD and heterozygous for ITGB1 are phenotypically wildtype with organized columns and normal rearrangement (n=13 embryos). These results support a model for which ITGB1, and not NCAD, is the driver of chondrocyte rearrangement and suggest that failure to rearrange in NCAD mutants results from increased ITGB1 function. Thus, rearrangement requires a narrow range of cell‐matrix adhesion strength and NCAD potentially acts as a brake by restricting ITGB1 activity in non‐rearranging resting chondrocytes. Current studies aim to confirm these genetic findings using gene expression analysis and an innovative quantitative adhesion assay as well as identify upstream regulators that control strength of antagonism between the cell adhesion interfaces.

Network- and enrichment-based inference of phenotypes and targets from large-scale disease maps

Complex diseases are inherently multifaceted, and the associated data are often heterogeneous, making linking interactions across genes, metabolites, RNA, proteins, cellular functions, and clinically relevant phenotypes a high-priority challenge. Disease maps have emerged as knowledge bases that capture molecular interactions, disease-related processes, and disease phenotypes with standardized representations in large-scale molecular interaction maps. Various tools are available for disease map analysis, but an intuitive solution to perform in silico experiments on the maps in a wide range of contexts and analyze high-dimensional data is currently missing. To this end, we introduce a two-dimensional enrichment analysis (2DEA) approach to infer downstream and upstream elements through the statistical association of network topology parameters and fold changes from molecular perturbations. We implemented our approach in a plugin suite for the MINERVA platform, providing an environment where experimental data can be mapped onto a disease map and predict potential regulatory interactions through an intuitive graphical user interface. We show several workflows using this approach and analyze two RNA-seq datasets in the Atlas of Inflammation Resolution (AIR) to identify enriched downstream processes and upstream transcription factors. Our work improves the usability of disease maps and increases their functionality by facilitating multi-omics data integration and exploration.

Modeling the C. elegans germline stem cell genetic network using automated reasoning

Computational methods and tools are a powerful complementary approach to experimental work for studying regulatory interactions in living cells and systems. We demonstrate the use of formal reasoning methods as applied to the Caenorhabditis elegans germ line, which is an accessible system for stem cell research. The dynamics of the underlying genetic networks and their potential regulatory interactions are key for understanding mechanisms that control cellular decision-making between stem cells and differentiation. We model the “stem cell fate” versus entry into the “meiotic development” pathway decision circuit in the young adult germ line based on an extensive study of published experimental data and known/hypothesized genetic interactions. We apply a formal reasoning framework to derive predictive networks for control of differentiation. Using this approach we simultaneously specify many possible scenarios and experiments together with potential genetic interactions, and synthesize genetic networks consistent with all encoded experimental observations. In silico analysis of knock-down and overexpression experiments within our model recapitulate published phenotypes of mutant animals and can be applied to make predictions on cellular decision-making. A methodological contribution of this work is demonstrating how to effectively model within a formal reasoning framework a complex genetic network with a wealth of known experimental data and constraints. We provide a summary of the steps we have found useful for the development and analysis of this model and can potentially be applicable to other genetic networks. This work also lays a foundation for developing realistic whole tissue models of the C. elegans germ line where each cell in the model will execute a synthesized genetic network.

Integrated analysis of miRNA and mRNA expression profiles identifies potential regulatory interactions during sexual development of Pacific oyster Crassostrea gigas

One of the most important physiological process in the life cycle of most bivalves is the sexual reproduction required for species propagation. Understanding the molecular regulatory mechanisms of gender determination and gonad development have potential application in bivalve aquaculture, but there is still limited knowledge about this issue. The Pacific oyster Crassostrea gigas is a commercially important bivalve in aquaculture worldwide, as well as a representative specie to study the sexual development in bivalves for its complicated sexuality, including dioecy, sex change and rare hermaphroditism. In this study, an integrated analysis of miRNA and mRNA expression profiles of oyster gonads at different gametogenesis stages was performed to explore their possibly regulatory patterns in sexual development of C. gigas. Based on small RNA sequencing, a total of 122 miRNAs were identified, including 53 conserved and 69 novel miRNAs. Six miRNAs exhibited sex-specific pattern that expressed exclusively from either male or female gonads with increasing abundance throughout the gonadal development. Moreover, 287 putative targets of the six sex-biased miRNAs were predicted by combining previous transcriptome data. GO and KEGG enrichment analysis of target genes revealed that these sex-biased miRNAs might participate in the regulation of gametogenesis. Further, potential miRNA-mRNA interactions based on six sex-biased miRNAs were collected. The homolog of a key participator in testis development, meiotic recombination protein SPO11 in C. gigas (CgSPO11), was predicted as a target of female-biased miRNA lgi-miR-96a. This negative miRNA-mRNA expression relationship was validated in additional samples by quantitative real-time PCR (qRT-PCR) and the regulation of CgSPO11 by lgi-miR-96a was preliminarily confirmed by a dual-luciferase reporter assay. This study provides information regarding the gonad miRNAs of C. gigas and leads to the discovery of miRNA-mRNA interactions in gonad development, which will facilitate further investigations in molecular mechanisms of bivalve sex differentiation.

Identifying potential regulatory interactions of peroxiredoxin PRXQ

Peroxiredoxins (Prxs) are cysteine-based peroxide-reducing enzymes that have been extensively studied over the past two decades. The reduction of the Prx disulfide form is dependent on electron donating enzymes to shift the Prx back into a catalytically active state. However, this reaction is poorly understood and reductant enzymes for this reaction to reduce the Prx disulfide bond have received little attention. Prxs from the bacterium Xanthomonas campestris (XcPrxQ) were used to assess how reductants affect Prx turnover by identifying potential electron transfer interactions between Prxs and reductants, Glutaredoxins (Grxs) and Thioredoxins (Trxs). To examine potential interactions between PrxQ and reducing proteins, we used PrxQ, Grx, and Trx mutants to determine the effect of specific cysteines in each of the proteins. Mutant and wildtype proteins were expressed in E. coli and purified using anion-exchange and gel filtration chromatography and purity was verified by SDS-PAGE. The results clarified the role of the two cysteines in PrxQ, C48 and C84, which are thought to participate in the reduction reaction of hydrogen peroxide. They also show Trx and Grx proteins from the same bacterium are possible reductants for Prx turnover, as reactions with PrxQ have produced complex formation at a larger molecular weight, suggesting the reductant binding to PrxQ and reducing its disulfide bond. This study is significant because it reveals potential binding interactions between reductants and Prxs that regulate Prx turnover into a catalytically active state, allowing the enzyme to break down peroxide and prevent oxidative damage, as well as highlighting Trxs in bacteria as a potential drug target due to their regulation of hydrogen peroxide levels in pathogenic strains.

Genome-wide pQTL analysis of protein expression regulatory networks in the human liver

BackgroundPrevious expression quantitative trait loci (eQTL) studies have identified thousands of genetic variants to be associated with gene expression at the mRNA level in the human liver. However, protein expression often correlates poorly with mRNA levels. Thus, protein quantitative trait loci (pQTL) study is required to identify genetic variants that regulate protein expression in human livers.ResultsWe conducted a genome-wide pQTL study in 287 normal human liver samples and identified 900 local pQTL variants and 4026 distant pQTL variants. We further discovered 53 genome hotspots of pQTL variants. Transcriptional region mapping analysis showed that 1133 pQTL variants are in transcriptional regulatory regions. Genomic region enrichment analysis of the identified pQTL variants revealed 804 potential regulatory interactions among 595 predicted regulators (e.g., non-coding RNAs) and 394 proteins. Moreover, pQTL variants and trait-variant integration analysis implied several novel mechanisms underlying the relationships between protein expression and liver diseases, such as alcohol dependence. Notably, over 2000 of the identified pQTL variants have not been reported in previous eQTL studies, suggesting extensive involvement of genetic polymorphisms in post-transcriptional regulation of protein expression in human livers.ConclusionsWe have partially established protein expression regulation networks in human livers and generated a wealth of pQTL data that could serve as a valuable resource for the scientific community.

Time-resolved mRNA and miRNA expression profiling reveals crucial coregulation of molecular pathways involved in epithelial-pneumococcal interactions.

Streptococcus pneumoniae is a major causative agent of pneumonia worldwide and its complex interaction with the lung epithelium has not been thoroughly characterized. In this study, we exploited both RNA‐sequencing and microRNA (miRNA)‐sequencing approaches to monitor the transcriptional changes in human lung alveolar epithelial cells infected by S. pneumoniae in a time‐resolved manner. A total of 1330 differentially expressed (DE) genes and 45 DE miRNAs were identified in all comparisons during the infection process. Clustering analysis showed that all DE genes were grouped into six clusters, several of which were primarily involved in inflammatory or immune responses. In addition, target gene enrichment analyses identified 11 transcription factors that were predicted to link at least one of four clusters, revealing transcriptional coregulation of multiple processes or pathways by common transcription factors. Notably, pharmacological treatment suggested that phosphorylation of p65 is important for optimal transcriptional regulation of target genes in epithelial cells exposed to pathogens. Furthermore, network‐based clustering analysis separated the DE genes negatively regulated by DE miRNAs into two functional modules (M1 and M2), with an enrichment in immune responses and apoptotic signaling pathways for M1. Integrated network analyses of potential regulatory interactions in M1 revealed that multiple DE genes related to immunity and apoptosis were regulated by multiple miRNAs, indicating the coordinated regulation of multiple genes by multiple miRNAs. In conclusion, time‐series expression profiling of messenger RNA and miRNA provides a wealth of information for global transcriptional changes, and offers comprehensive insight into the molecular mechanisms underlying host–pathogen interactions.

Integrated analysis of lncRNA-associated ceRNA network identified potential regulatory interactions in osteosarcoma.

This study aimed to identify potential therapeutic targets in osteosarcoma (OS) through the network analysis of competing endogenous RNAs (ceRNAs). The differentially expressed miRNAs (DEMIs) and mRNAs (DEMs) were identified between OS cell lines and human mesenchymal stem cells (hMSCs) from the data deposited under GSE70415 using limma package. Functional analysis of DEMs was performed using DAVID and clusterProfiler to identify significantly enriched Gene Ontology biological processes and KEGG pathways, respectively. The DEMI-DEM interaction network was constructed using Cytoscape. LncRNA–miRNA interactions were predicted using starBase database. The ceRNA regulatory network was constructed by integrating mRNAs, miRNAs, and lncRNAs, and functional enrichment analysis was performed for the genes involved. The analysis revealed a total of 326 DEMs and 54 DEMIs between OS cells and hMSCs. We identified several novel therapeutic targets involved in the progression and metastasis of OS, such as CBX7, RAD9A, SNHG7 and miR-34a-5p. The miRNA, miR-543 (target gene: CBX7) was found to be associated with the pathway Mucin type O-glycan biosynthesis. Using the ceRNA network, we established the following regulatory interactions: NEAT1/miR-543/CBX7, SNHG7/miR-34a-5p/RAD9A, and XIST/miR-34a-5p/RAD9A. CBX7, RAD9A, lncRNA SNHG7, miR-543, and miR-34a-5p may be explored as novel therapeutic targets for treatment of OS.

Predicting Phenotypic Diversity from Molecular and Genetic Data.

Despite the importance of complex phenotypes, an in-depth understanding of the combined molecular and genetic effects on a phenotype has yet to be achieved. Here, we introduce InPhenotype, a novel computational approach for complex phenotype prediction, where gene-expression data and genotyping data are integrated to yield quantitative predictions of complex physiological traits. Unlike existing computational methods, InPhenotype makes it possible to model potential regulatory interactions between gene expression and genomic loci without compromising the continuous nature of the molecular data. We applied InPhenotype to synthetic data, exemplifying its utility for different data parameters, as well as its superiority compared to current methods in both prediction quality and the ability to detect regulatory interactions of genes and genomic loci. Finally, we show that InPhenotype can provide biological insights into both mouse and yeast datasets.

Detailed Regulatory Interaction Map of the Human Heart Facilitates Gene Discovery for Cardiovascular Disease

Most disease-associated variants identified by population based genetic studies are non-coding, which compromises finding causative genes and mechanisms. Presumably they interact through looping with nearby genes to modulate transcription. Hi-C provides the most complete and unbiased method for genome-wide identification of potential regulatory interactions, but finding chromatin loops in Hi-C data remains difficult and tissue specific data are limited. We have generated Hi-C data from primary cardiac tissue and developed a method, peakHiC, for sensitive and quantitative loop calling to uncover the human heart regulatory interactome. We identify complex CTCF-dependent and -independent contact networks, with loops between coding and non-coding gene promoters, shared enhancers and repressive sites. Across the genome, enhancer interaction strength correlates with gene transcriptional output and loop dynamics follows CTCF, cohesin and H3K27Ac occupancy levels. Finally, we demonstrate that intersection of the human heart regulatory interactome with cardiovascular disease variants facilitates prioritizing disease-causative genes.

Insulin signalling's role in mediating tissue-specific nutritional plasticity and robustness in the horn-polyphenic beetle Onthophagus taurus.

Organisms cope with nutritional variation via developmental plasticity, adjusting trait size to nutrient availability for some traits while enabling others to develop in a nutritionally robust manner. Yet, the developmental mechanisms that regulate organ-specific growth across nutritional gradients remain poorly understood. We assessed the functions of members of the insulin/insulin-like signalling pathway (IIS) in the regulation of nutrition sensitivity and robustness in males of the horn-polyphenic beetle Onthophagus taurus, as well as potential regulatory interactions between IIS and two other growth-regulating pathways: Doublesex and Hedgehog signalling. Using RNA interference (RNAi), we experimentally knocked down both insulin receptors ( InR1 and InR2) and Foxo, a growth inhibitor. We then performed morphometric measurements on horns, a highly nutrition-sensitive trait, and genitalia, a largely nutrition-insensitive trait. Finally, we used quantitative real-time polymerase chain reaction to assess expression levels of doublesex and the Hedgehog signalling gene smoothened following IIS-RNAi. Our results suggest that nutrition responsiveness of both traits is regulated by different IIS components, which transduce nutritional conditions to both Doublesex and Hedgehog pathways, albeit via different IIS pathway members. Combined with previous studies, our findings suggest that separate origins of trait exaggeration among insect lineages were enabled through the independent co-option of IIS, yet via reliance on different components therein.