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Several studies have shown that cancer cells can be "phenotypically reversed", thus achieving a "tumor reversion", by losing malignant hallmarks as migrating and invasive capabilities. These findings suggest that genome activity can switch to assume a different functional configuration, i.e. a different Gene Regulatory Network pattern. Indeed, once "destabilized", cancer cells enter into a critical transition phase that can be adequately "oriented" by yet unidentified morphogenetic factors - acting on both cells and their microenvironment - that trigger an orchestrated array of structural and epigenetic changes. Such process can bypass genetic abnormalities, through rerouting cells toward a benign phenotype. Oocytes and embryonic tissues, obtained by animals and humans, display such "reprogramming" capability, as a number of yet scarcely identified embryo-derived factors can revert the malignant phenotype of several types of tumors. Mechanisms involved in the reversion process include the modification of cell-microenvironment cross talk (mostly through cytoskeleton reshaping), chromatin opening, demethylation, and epigenetic changes, modulation of biochemical pathways, comprising TCTP-p53, PI3K-AKT, FGF, Wnt, and TGF-β-dependent cascades. Results herein discussed promise to open new perspectives not only in the comprehension of cancer biology but also toward different therapeutic options, as suggested by a few preliminary clinical studies.

In this review, we examine the role of microRNAs in the development of the prefrontal cortex (PFC) in adolescence and in individual differences in vulnerability to mental illness. We describe results from clinical and preclinical research indicating that adolescence coincides with drastic changes in local microRNA expression, including microRNAs that control gene networks involved in PFC and cognitive refinement. We highlight that altered levels of microRNAs in the PFC are associated with psychopathologies of adolescent onset, notably depression and schizophrenia. We show that microRNAs can be measured non-invasively in peripheral samples and could serve as longitudinal physiological readouts of brain expression and psychiatric risk in youth.

Wheat leaf senescence is a developmental process that involves expressional changes in thousands of genes that ultimately impact grain protein content (GPC), grain yield (GY), and nitrogen use efficiency. The onset and rate of senescence are strongly influenced by plant hormones and environmental factors e.g. nitrogen availability. At maturity, decrease in nitrogen uptake could enhance N remobilization from leaves and stem to grain, eventually leading to leaf senescence. Early senescence is related to high GPC and somewhat low yield whereas late senescence is often related to high yield and somewhat low GPC. Early or late senescence is principally regulated by up and down-regulation of senescence associated genes. Integration of external and internal factors together with genotypic variation influence senescence associated genes in a developmental age dependent manner. Although regulation of genes involved in senescence has been studied in rice, Arabidopsis, maize, and currently in wheat, there are genotype-specific variations yet to explore. A major effort is needed to understand the interaction of positive and negative senescence regulators in determining the onset of senescence. In wheat, increasing attention has been paid to understand the role of positive senescence regulator, e.g. GPC-1, regulated gene network during early senescence time course. Recently, gene regulatory network involved early to late senescence time course revealed important senescence regulators. However, the known negative senescence regulator TaNAC-S gene has not been extensively studied in wheat and little is known about its value in breeding. Existing data on senescence-related transcriptome studies and gene regulatory network could effectively be used for functional study in developing nitrogen efficient wheat varieties.

Background. It has been reported that there may be a potential link between hernia and dementia. However, the exact mechanisms of their association have not been established. This study is aimed at constructing miRNA-mRNA networks to elucidate on the potential link between dementia and hernia. Methods. Gene expression profiles for dementia, herniation, and skeletal muscle were downloaded from the GEO database after which differentially expressed mRNAs and miRNAs were obtained. In addition, fascia tissue samples were obtained during surgery. A total of 41 patients were recruited in this study, and expression levels of candidate genes were examined using quantitative RT-PCR. Luciferase reporter gene assays were used to identify potential miRNA-mRNA regulatory pathways. Results. Differentially expressed mRNAs and miRNAs were screened. A potential miRNA-mRNA network revealing the crosstalk mechanism between herniation and dementia was identified. Single cell analysis revealed that PI16 was highly enriched in adipose tissues, skeletal muscles, and in the skin. GSEA enrichment analysis showed that PI16 is involved in adipose metabolism, muscle functions, and energy metabolism. In clinical samples, PI16 was found to be upregulated in hernia, while miR-4451 was found to be downregulated. The luciferase reporter gene assay revealed that downregulation of circulating miR-4451 may be responsible for the upregulated PI16 expression in hernia sacs. Conclusions. We constructed an miRNA-mRNA network that shows the potential association between dementia and hernia. We also found that miR-4451 regulates the PI16 expression, which may be a key target and biomarker for hernia pathogenesis and dementia crosstalk.

The signal mediated by leptin hormone and its receptor is a major regulator of body weight, food intake and metabolism. In mammals and many teleost fish species, leptin has an anorexigenic role and inhibits food intake by influencing the appetite centres in the hypothalamus. However, the regulatory connections between leptin and downstream genes mediating its appetite-regulating effects are still not fully explored in teleost fish. In this study, we used a loss of function leptin receptor zebrafish mutant and real-time quantitative PCR to assess brain expression patterns of several previously identified anorexigenic genes downstream of leptin signal under different feeding conditions (normal feeding, 7-day fasting, 2 and 6-h refeeding). These downstream factors include members of cart genes, crhb and gnrh2, as well as selected genes co-expressed with them based on a zebrafish co-expression database. Here, we found a potential gene expression network (GRN) comprising the abovementioned genes by a stepwise approach of identifying co-expression modules and predicting their upstream regulators. Among the transcription factors (TFs) predicted as potential upstream regulators of this GRN, we found expression pattern of sp3a to be correlated with transcriptional changes of the downstream gene network. Interestingly, the expression and transcriptional activity of Sp3 orthologous gene in mammals have already been implicated to be under the influence of leptin signal. These findings suggest a potentially conserved regulatory connection between leptin and sp3a, which is predicted to act as a transcriptional driver of a downstream gene network in the zebrafish brain.

GM-CSF produced by autoreactive CD4-positive T helper cells is involved in the pathogenesis of autoimmune diseases, such as multiple sclerosis. However, the molecular regulators that establish and maintain the features of GM-CSF-positive CD4 T cells are unknown. In order to identify these regulators, we isolated human GM-CSF-producing CD4 T cells from human peripheral blood by using a cytokine capture assay. We compared these cells to the corresponding GM-CSF-negative fraction, and furthermore, we studied naïve CD4 T cells, memory CD4 T cells, and bulk CD4 T cells from the same individuals as additional control cell populations. As a result, we provide a rich resource of integrated chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from these primary human CD4 T cell subsets and we show that the identified signatures are associated with human autoimmune diseases, especially multiple sclerosis. By combining information about mRNA expression, DNA accessibility, and predicted transcription factor binding, we reconstructed directed gene regulatory networks connecting transcription factors to their targets, which comprise putative key regulators of human GM-CSF-positive CD4 T cells as well as memory CD4 T cells. Our results suggest potential therapeutic targets to be investigated in the future in human autoimmune disease.

T-cell activation induces context-specific gene expression programs that promote energy generation and biosynthesis, progression through the cell cycle and ultimately cell differentiation. The aim of this study was to apply the omni ATAC-seq method to characterize the landscape of chromatin changes induced by T-cell activation in mature naïve CD4+ T-cells. Using a well-established ex vivo protocol of canonical T-cell receptor signaling, we generated genome-wide chromatin maps of naïve T-cells from pediatric donors in quiescent or recently activated states. We identified thousands of individual chromatin accessibility peaks that are associated with T-cell activation, the majority of which were annotated intronic and intergenic enhancer regions. A core set of 3268 gene promoters underwent chromatin remodeling and concomitant changes in gene expression in response to activation, and were enriched in multiple pathways controlling cell cycle regulation, metabolism, inflammatory response genes and cell survival. Leukemia inhibitory factor (LIF) was among those factors that gained the highest accessibility and expression, in addition to IL2-STAT5 dependent chromatin remodeling in the T-cell activation response. Using publicly available data we found the chromatin response was far more dynamic at 24-h compared with 72-h post-activation. In total 546 associations were reproduced at both time-points with similar strength of evidence and directionality of effect. At the pathways level, the IL2-STAT5, KRAS signalling and UV response pathways were replicable at both time-points, although differentially modulated from 24 to 72 h post-activation.

Airway smooth muscle (ASM) is known for its role in asthma exacerbations characterized by acute bronchoconstriction and remodeling. The molecular mechanisms underlying multiple gene interactions regulating gene expression in asthma remain elusive. Herein, we explored the regulatory relationship between ASM genes to uncover the putative mechanism underlying asthma in humans. To this end, the gene expression from human ASM was measured with RNA-Seq in non-asthmatic and asthmatic groups. The gene network for the asthmatic and non-asthmatic group was constructed by prioritizing differentially expressed genes (DEGs) (121) and transcription factors (TFs) (116). Furthermore, we identified differentially connected or co-expressed genes in each group. The asthmatic group showed a loss of gene connectivity due to the rewiring of major regulators. Notably, TFs such as ZNF792, SMAD1, and SMAD7 were differentially correlated in the asthmatic ASM. Additionally, the DEGs, TFs, and differentially connected genes over-represented in the pathways involved with herpes simplex virus infection, Hippo and TGF-β signaling, adherens junctions, gap junctions, and ferroptosis. The rewiring of major regulators unveiled in this study likely modulates the expression of gene-targets as an adaptive response to asthma. These multiple gene interactions pointed out novel targets and pathways for asthma exacerbations.

FOXM1 transcription factor is an oncogene and a master regulator of chemoresistance in multiple cancers. Pharmacological inhibition of FOXM1 is a promising approach but has proven to be challenging. We performed a network-centric transcriptomic analysis to identify a novel compound STL427944 that selectively suppresses FOXM1 by inducing the relocalization of nuclear FOXM1 protein to the cytoplasm and promoting its subsequent degradation by autophagosomes. Human cancer cells treated with STL427944 exhibit increased sensitivity to cytotoxic effects of conventional chemotherapeutic treatments (platinum-based agents, 5-fluorouracil, and taxanes). RNA-seq analysis of STL427944-induced gene expression changes revealed prominent suppression of gene signatures characteristic for FOXM1 and its downstream targets but no significant changes in other important regulatory pathways, thereby suggesting high selectivity of STL427944 toward the FOXM1 pathway. Collectively, the novel autophagy-dependent mode of FOXM1 suppression by STL427944 validates a unique pathway to overcome tumor chemoresistance and improve the efficacy of treatment with conventional cancer drugs.

Background Gene Regulatory Networks (GRN) produce powerful insights into transcriptional regulation in cells. The power of GRNs has been underutilized in malaria research. The Arboreto library was incorporated into a user-friendly web-based application for malaria researchers (http://malboost.bi.up.ac.za). This application will assist researchers with gaining an in depth understanding of transcriptomic datasets. Methods The web application for MALBoost was built in Python-Flask with Redis and Celery workers for queue submission handling, which execute the Arboreto suite algorithms. A submission of 5–50 regulators and total expression set of 5200 genes is permitted. The program runs in a point-and-click web user interface built using Bootstrap4 templates. Post-analysis submission, users are redirected to a status page with run time estimates and ultimately a download button upon completion. Result updates or failure updates will be emailed to the users. Results A web-based application with an easy-to-use interface is presented with a use case validation of AP2-G and AP2-I. The validation set incorporates cross-referencing with ChIP-seq and transcriptome datasets. For AP2-G, 5 ChIP-seq targets were significantly enriched with seven more targets presenting with strong evidence of validated targets. Conclusion The MALBoost application provides the first tool for easy interfacing and efficiently allows gene regulatory network construction for Plasmodium. Additionally, access is provided to a pre-compiled network for use as reference framework. Validation for sexually committed ring-stage parasite targets of AP2-G, suggests the algorithm was effective in resolving “traditionally” low-level signatures even in bulk RNA datasets.

Plant glandular secretory trichomes (GSTs) produce various specialized metabolites. Increasing GST density represents a strategy to enhance the yield of these chemicals; however, the gene regulatory network that controls GST initiation remains unclear. In a previous study of Artemisia annua L., we found that a HD-ZIP IV transcription factor, AaHD1, promotes GST initiation by directly regulating AaGSW2. Here, we identified two AaHD1-interacting transcription factors, namely AaMIXTA-like 2 (AaMYB16) and AaMYB5. Through the generation and characterization of transgenic plants, we found that AaMYB16 is a positive regulator of GST initiation, whereas AaMYB5 has the opposite effect. Notably, neither of them regulates GST formation independently. Rather, they act competitively, by interacting and modulating AaHD1 promoter binding activity. Additionally, the phytohormone jasmonic acid (JA) was shown to be associated with the AaHD1-AaMYB16/AaMYB5 regulatory network through transcriptional regulation via a JASMONATE-ZIM DOMAIN (JAZ) protein repressor. These results bring new insights into the mechanism of GST initiation through regulatory complexes, which appear to have similar functions in a range of vascular plant taxa.

Alzheimer's disease (AD), vascular dementia (VD), and Parkinson's disease (PD) exert increasingly lethal or disabling effects on humans, but the associations among these diseases at the molecular level remain unclear. In our research, lists of genes related to these three diseases were acquired from public databases. We constructed gene-gene networks of the lists of disease-related genes using the STRING database and selected the plug-in MCODE as the most suitable method to divide the three disease-associated networks into modules through an entropy calculation. Notably, 1173 AD-related, 203 VD-related, and 722 PD-related genes as well as 72 overlapping genes were observed among the three diseases. By dividing the modules from the gene network, we divided the AD-related gene network into 27 modules, the VD-related gene network into 8 modules, and the PD-related gene network into 17 modules. After the enrichment analysis of each disease-related gene, 146 overlapping biological processes and 32 overlapping pathways were identified. Ultimately, through similarity analysis of the genes, biological processes, and pathways, we found that AD and VD were the most closely related at the biological process and pathway levels, with similarity coefficients of 0.2784 and 0.3626, respectively. After analyzing the overlapping gene network, we found that INS might play an important role in the network and that insulin and its signaling pathways may play a key role in these neurodegenerative diseases. Our research illustrates a new method for in-depth research on the three diseases, which may accelerate the progress of developing new therapeutics and may be applied to prevent neurodegenerative diseases.

The scarcity of accessible sites that are dynamic or cell type-specific in plants may be due in part to tissue heterogeneity in bulk studies. To assess the effects of tissue heterogeneity, we apply single-cell ATAC-seq to Arabidopsis thaliana roots and identify thousands of differentially accessible sites, sufficient to resolve all major cell types of the root. We find that the entirety of a cell’s regulatory landscape and its transcriptome independently capture cell type identity. We leverage this shared information on cell identity to integrate accessibility and transcriptome data to characterize developmental progression, endoreduplication and cell division. We further use the combined data to characterize cell type-specific motif enrichments of transcription factor families and link the expression of family members to changing accessibility at specific loci, resolving direct and indirect effects that shape expression. Our approach provides an analytical framework to infer the gene regulatory networks that execute plant development., Existing studies of the chromatin accessibility, the primary mark of regulatory DNA, in Arabidopsis are based mainly on bulk samples. Here, the authors report the regulatory landscape of Arabidopsis thaliana roots at single-cell resolution.

A comprehensive transcriptomic survey of pigs can provide a mechanistic understanding of tissue specialization processes underlying economically valuable traits and accelerate their use as a biomedical model. Here we characterize four transcript types (lncRNAs, TUCPs, miRNAs, and circRNAs) and protein-coding genes in 31 adult pig tissues and two cell lines. We uncover the transcriptomic variability among 47 skeletal muscles, and six adipose depots linked to their different origins, metabolism, cell composition, physical activity, and mitochondrial pathways. We perform comparative analysis of the transcriptomes of seven tissues from pigs and nine other vertebrates to reveal that evolutionary divergence in transcription potentially contributes to lineage-specific biology. Long-range promoter–enhancer interaction analysis in subcutaneous adipose tissues across species suggests evolutionarily stable transcription patterns likely attributable to redundant enhancers buffering gene expression patterns against perturbations, thereby conferring robustness during speciation. This study can facilitate adoption of the pig as a biomedical model for human biology and disease and uncovers the molecular bases of valuable traits., A comprehensive transcriptomic survey of the pig could enable mechanistic understanding of tissue specialization and accelerate its use as a biomedical model. Here the authors characterize four distinct transcript types in 31 adult pig tissues to dissect their distinct structural and transcriptional features and uncover transcriptomic variability related to tissue physiology.

Plants evolved different strategies to better adapt to the environmental conditions in which they live: the control of their body architecture and the timing of phase change are two important processes that can improve their fitness. As they age, plants undergo two major phase changes (juvenile to adult and adult to reproductive) that are a response to environmental and endogenous signals. These phase transitions are accompanied by alterations in plant morphology and also by changes in physiology and the behavior of gene regulatory networks. Six main pathways involving environmental and endogenous cues that crosstalk with each other have been described as responsible for the control of plant phase transitions: the photoperiod pathway, the autonomous pathway, the vernalization pathway, the temperature pathway, the GA pathway, and the age pathway. However, studies have revealed that sugar is also involved in phase change and the control of branching behavior. In this review, we discuss recent advances in plant biology concerning the genetic and molecular mechanisms that allow plants to regulate phase transitions in response to the environment. We also propose connections between phase transition and plant architecture control.

The fundamental understanding of how Cancer initiates, persists and then progresses is evolving. High-resolution technologies, including single-cell mutation and gene expression measurements, are now attainable, providing an ever-increasing insight into the molecular details. However, this higher resolution has shown that somatic mutation theory itself cannot explain the extraordinary resistance of cancer to extinction. There is a need for a more Systems-based framework of understanding cancer complexity, which in particular explains the regulation of gene expression during cell-fate decisions. Cancer displays a series of paradoxes. Here we attempt to approach them from the view-point of adaptive exploration of gene regulatory networks at the edge of order and chaos, where cell-fate is changed by oscillations between alternative regulators of cellular senescence and reprogramming operating through self-organisation. On this background, the role of polyploidy in accessing the phylogenetically pre-programmed "oncofetal attractor" state, related to unicellularity, and the de-selection of unsuitable variants at the brink of cell survival is highlighted. The concepts of the embryological and atavistic theory of cancer, cancer cell "life-cycle", and cancer aneuploidy paradox are dissected under this lense. Finally, we challenge researchers to consider that cancer "defects" are mostly the adaptation tools of survival programs that have arisen during evolution and are intrinsic of cancer. Recognition of these features should help in the development of more successful anti-cancer treatments.

Plant cells constantly alter their gene expression profiles to respond to environmental fluctuations. These continuous adjustments are regulated by multi-hierarchical networks of transcription factors. To understand how such gene regulatory networks (GRNs) have stabilized evolutionarily while allowing for species-specific responses, we compare the GRNs underlying salt response in the early-diverging and late-diverging plants Marchantia polymorpha and Arabidopsis thaliana. Salt-responsive GRNs, constructed on the basis of the temporal transcriptional patterns in the two species, share common trans-regulators but exhibit an evolutionary divergence in cis-regulatory sequences and in the overall network sizes. In both species, WRKY-family transcription factors and their feedback loops serve as central nodes in salt-responsive GRNs. The divergent cis-regulatory sequences of WRKY-target genes are probably associated with the expansion in network size, linking salt stress to tissue-specific developmental and physiological responses. The WRKY modules and highly linked WRKY feedback loops have been preserved widely in other plants, including rice, while keeping their binding-motif sequences mutable. Together, the conserved trans-regulators and the quickly evolving cis-regulatory sequences allow salt-responsive GRNs to adapt over a long evolutionary timescale while maintaining some consistent regulatory structure. This strategy may benefit plants as they adapt to changing environments.

Extensive alterations in gene regulatory networks are a typical characteristic of Huntington's disease (HD); these include alterations in protein-coding genes and poorly understood non-coding RNAs (ncRNAs), which are associated with pathology caused by mutant huntingtin. Long non-coding RNAs (lncRNAs) are an important class of ncRNAs involved in a variety of biological functions, including transcriptional regulation and post-transcriptional modification of many targets, and likely contributed to the pathogenesis of HD. While a number of changes in lncRNAs expression have been observed in HD, little is currently known about their functions. Here, we discuss their possible mechanisms and molecular functions, with a particular focus on their roles in transcriptional regulation. These findings give us a better insight into HD pathogenesis and may provide new targets for the treatment of this neurodegenerative disease.

A fundamental question in developmental biology is how the progeny of stem cells become differentiated tissues. The Arabidopsis root is a tractable model to address this question due to its simple organization and defined cell lineages. In particular, the zone of dividing cells at the root tip—the root apical meristem—presents an opportunity to map the gene regulatory networks underlying stem cell niche maintenance, tissue patterning, and cell identity acquisition. To identify molecular regulators of these processes, studies over the last 20 years employed global profiling of gene expression patterns. However, these technologies are prone to information loss due to averaging gene expression signatures over multiple cell types and/or developmental stages. Recently developed high-throughput methods to profile gene expression at single-cell resolution have been successfully applied to plants. Here, we review insights from the first published single-cell mRNA sequencing and chromatin accessibility datasets generated from Arabidopsis roots. These studies successfully reconstruct developmental trajectories, phenotype cell identity mutants at unprecedented resolution, and reveal cell type-specific responses to environmental stimuli. The experimental insight gained from Arabidopsis paves the way to profile roots from additional species.

Adventitious rooting of walnut species (Juglans L.) is known to be rather difficult, especially for mature trees. The adventitious root formation (ARF) capacities of mature trees can be significantly improved by rejuvenation. However, the underlying gene regulatory networks (GRNs) of rejuvenation remain largely unknown. To characterize such regulatory networks, we carried out the transcriptomic study using RNA samples of the cambia and peripheral tissues on the bottom of rejuvenated and mature walnut (Juglans hindsii × J. regia) cuttings during the ARF. The RNA sequencing data suggested that zeatin biosynthesis, energy metabolism and substance metabolism were activated by rejuvenation, whereas photosynthesis, fatty acid biosynthesis and the synthesis pathways for secondary metabolites were inhibited. The inter- and intra-module GRNs were constructed using differentially expressed genes. We identified 35 hub genes involved in five modules associated with ARF. Among these hub genes, particularly, beta-glucosidase-like (BGLs) family members involved in auxin metabolism were overexpressed at the early stage of the ARF. Furthermore, BGL12 from the cuttings of Juglans was overexpressed in Populus alba × P. glandulosa. Accelerated ARF and increased number of ARs were observed in the transgenic poplars. These results provide a high-resolution atlas of gene activity during ARF and help to uncover the regulatory modules associated with the ARF promoted by rejuvenation.

The pathogen Mycobacterium leprae is the root cause of the dire Hansen’s disease, commonly known as Leprosy. Mycobacterium leprae is a distinct species within the genus as it causes peripheral nerve damage. The microRNAs (miRNAs) can effectively regulate the transcripts at the stages of transcription and translation. Although authenticating the existence and roles of microRNAs in bacteria necessitate intensive research, a few reports on bacterial microRNAs were published. In this in silico study, the genome wide investigation of Mycobacterium leprae led to the identification of 30 putative mature microRNAs in the bacterium. Several reports manifest the transmittance of bacterial small RNAs to host cytoplasm and they subsequently target host cellular mRNA molecules. The mature microRNAs predicted in M. leprae might possibly degrade/ inhibit 297 mRNAs in human. Further, the target human genes were subjected to gene network analysis and functional annotation. It was evident that the central mediators of the target gene network were involved in host defence responses to pathogen. A few target genes executed the pivotal processes of nervous system, morphogenesis, homeostatsis, transcription factor binding, cell cycle and cell death.

The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.

Background Ankylosing spondylitis (AS) is a rare inflammatory disorder affecting the spinal joints. Although we know some of the genetic factors that are associated with the disease, the molecular basis of this illness has not yet been fully elucidated, and the genes involved in AS pathogenesis have not been entirely identified. The current study aimed at constructing a gene network that may serve as an AS gene signature and biomarker, both of which will help in disease diagnosis and the identification of therapeutic targets. Previously published gene expression profiles of 16 AS patients and 16 gender- and age-matched controls that were profiled on the Illumina HumanHT-12 V3.0 Expression BeadChip platform were mined. Patients were Portuguese, 21 to 64 years old, were diagnosed based on the modified New York criteria, and had Bath Ankylosing Spondylitis Disease Activity Index scores > 4 and Bath Ankylosing Spondylitis Functional Index scores > 4. All patients were receiving only NSAIDs and/or sulphasalazine. Functional enrichment and pathway analysis were performed to create an interaction network of differentially expressed genes. Results ITM2A, ICOS, VSIG10L, CD59, TRAC, and CTLA-4 were among the significantly differentially expressed genes in AS, but the most significantly downregulated genes were the HLA-DRB6, HLA-DRB5, HLA-DRB4, HLA-DRB3, HLA-DRB1, HLA-DQB1, ITM2A, and CTLA-4 genes. The genes in this study were mostly associated with the regulation of the immune system processes, parts of cell membrane, and signaling related to T cell receptor and antigen receptor, in addition to some overlaps related to the IL2 STAT signaling, as well as the androgen response. The most significantly over-represented pathways in the data set were associated with the “RUNX1 and FOXP3 which control the development of regulatory T lymphocytes (Tregs)” and the “GABA receptor activation” pathways. Conclusions Comprehensive gene analysis of differentially expressed genes in AS reveals a significant gene network that is involved in a multitude of important immune and inflammatory pathways. These pathways and networks might serve as biomarkers for AS and can potentially help in diagnosing the disease and identifying future targets for treatment.

Searching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is difficult to scale this approach up to larger networks and more complex functions. Here we tackle this problem by training a recurrent neural network (RNN) to perform the desired function. By developing a systematic perturbative method to interrogate the successfully trained RNNs, we are able to distill the underlying regulatory network among the biological elements (genes, proteins, etc.). Furthermore, we show several cases where the regulation networks found by RNN can achieve the desired biological function when its edges are expressed by more realistic response functions, such as the Hill-function. This method can be used to link topology and function by helping uncover the regulation logic and network topology for complex tasks., Networks are useful ways to describe interactions between molecules in a cell, but predicting the real topology of large networks can be challenging. Here, the authors use deep learning to predict the topology of networks that perform biologically-plausible functions.

Development has intrigued humanity since ancient times. Today, the main paradigm in developmental biology and evolutionary developmental biology (evo-devo) is the genetic program, in which development is explained by the interplay and interaction of genes, that is, by the action of gene regulatory networks (GRNs). However, it is not even clear that a GRN, no matter how complex, can be translated into a form. Therefore, the fundamental enigma of development still remains: how is a complex organism formed from a single cell? This question unfolded the historical drama and the dialectical tension between preformation and epigenesis. In order to shed light on these issues, I studied the development of crabs (infraorder Brachyura), as representative of the subphylum Crustacea, using network theory. The external morphology of the different phases of brachyuran metamorphosis were modeled as networks and their main characteristics analyzed. As one could expect, the parameters usually regarded as indicative of network complexity, such as modularity and hierarchy, increased during development. However, when more sophisticated complexity measures were tested, it was evidenced that whereas a group of complexity measures increased during development, another group decreased. This led to consider that two kinds of complexities were being measured. I called them intensive and extensive complexity. In view of these results, I propose that crab development involves a passage from an intensive to an extensive complexity. In other words, crab development can be interpreted as a process of unfolding of an intensive, preexistent complexity., Facultad de Ciencias Naturales y Museo

Transcription factors (TFs) act as powerful levers to regulate neural physiology and can be targeted to improve cellular responses to injury or disease. Because TFs often depend on cooperative activity, a major challenge is to identify and deploy optimal sets. Here we developed a bioinformatics pipeline, centered on TF co-occupancy of regulatory DNA, and used it to predict factors that potentiate the effects of pro-regenerative Klf6 in vitro. High content screens of neurite outgrowth identified cooperative activity by 12 candidates, and systematic testing in a mouse model of corticospinal tract (CST) damage substantiated three novel instances of pairwise cooperation. Combined Klf6 and Nr5a2 drove the strongest growth, and transcriptional profiling of CST neurons identified Klf6/Nr5a2-responsive gene networks involved in macromolecule biosynthesis and DNA repair. These data identify TF combinations that promote enhanced CST growth, clarify the transcriptional correlates, and provide a bioinformatics approach to detect TF cooperation., After injury to the nervous system, many neurons fail to initiate transcriptional programs needed for axon growth. Here the authors examine co-operative binding of factors to regulatory DNA to predict combinations that improve axon growth when ectopically co-expressed.

The primary root is critical for early seedling growth and survival. To understand the molecular mechanisms governing primary root development, we performed a dynamic transcriptome analysis of two maize (Zea mays) inbred lines with contrasting primary root length at nine time points over a 12-day period. A total of 18 702 genes were differentially expressed between two lines or different time points. Gene enrichment, phytohormone content determination, and metabolomics analysis showed that auxin biosynthesis and signal transduction, as well as the phenylpropanoid and flavonoid biosynthesis pathways, were associated with root development. Co-expression network analysis revealed that eight modules were associated with lines/stages, as well as primary or lateral root length. In root-related modules, flavonoid metabolism accompanied by auxin biosynthesis and signal transduction constituted a complex gene regulatory network during primary root development. Two candidate genes (rootless concerning crown and seminal roots, rtcs and Zm00001d012781) involved in auxin signaling and flavonoid biosynthesis were identified by co-expression network analysis, QTL-seq and functional annotation. These results increase our understanding of the regulatory network controlling the development of primary and lateral root length, and provide a valuable genetic resource for improvement of root performance in maize.

Sepsis-induced acute respiratory distress syndrome (ARDS) remains a major threat to human health without effective therapeutic drugs. Previous studies demonstrated the power of gene expression profiling to reveal pathological changes associated with sepsis-induced ARDS. However, there is still a lack of systematic data mining framework for identifying potential targets for treatment. In this study, we demonstrated the feasibility of druggable targets prediction based on gene expression data. Through the functional enrichment analysis of microarray-based expression profiles between sepsis-induced ARDS and non-sepsis ARDS samples, we revealed genes involved in anti-microbial infection immunity were significantly altered in sepsis-induced ARDS. Protein–protein interaction (PPI) network analysis highlighted TOP2A gene as the key regulator in the dysregulated gene network of sepsis-induced ARDS. We were also able to predict several therapeutic drug candidates for sepsis-induced ARDS using Connectivity Map (Cmap) database, among which doxorubicin was identified to interact with TOP2A with a high affinity similar to its endogenous ligand. Overall, our findings suggest that doxorubicin could be a potential therapeutic for sepsis-induced ARDS by targeting TOP2A, which requires further investigation and validation. The whole study relies on publicly available dataset and publicly accessible database or bioinformatic tools for data mining. Therefore, our study benchmarks a workflow for druggable target prediction which can be widely applicable in the search of targets in other pathological conditions., Graphical Abstract

Background Drug-induced glaucoma (DIG) is a kind of serious adverse drug reaction that can cause irreversible blindness. Up-to-date, the molecular mechanism of DIG largely remains unclear yet due to the medical complexity of glaucoma onset. Methods In this study, we conducted data mining of tremendous historical adverse drug events and genome-wide drug-regulated gene signatures to identify glaucoma-associated drugs. Upon these drugs, we carried out serial network analyses, including the weighted gene co-expression network analysis (WGCNA), to illustrate the gene interaction network underlying DIG. Furthermore, we applied pathogenic risk assessment to discover potential biomarker genes for DIG. Results As the results, we discovered 13 highly glaucoma-associated drugs, a glaucoma-related gene network, and 55 glaucoma-susceptible genes. These genes likely played central roles in triggering DIGs via an integrative mechanism of phototransduction dysfunction, intracellular calcium homeostasis disruption, and retinal ganglion cell death. Further pathogenic risk analysis manifested that a panel of nine genes, particularly OTOF gene, could serve as potential biomarkers for early-onset DIG prognosis. Conclusions This study elucidates the possible molecular basis underlying DIGs systematically for the first time. It also provides prognosis clues for early-onset glaucoma and thus assists in designing better therapeutic regimens.

Background Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results A total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened. Conclusions The present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

Reduced NREM sleep in humans is associated with AD neuropathology. Recent work has demonstrated a reduction in NREM sleep in preclinical AD, pointing to its potential utility as an early marker of dementia. We test the hypothesis that reduced NREM delta power and increased tauopathy are associated with shared underlying cortical molecular networks in preclinical AD. We integrate multi-omics data from two extensive public resources, a human Alzheimer’s disease cohort from the Mount Sinai Brain Bank (N = 125) reflecting AD progression and a (C57BL/6J × 129S1/SvImJ) F2 mouse population in which NREM delta power was measured (N = 98). Two cortical gene networks, including a CLOCK-dependent circadian network, are associated with NREM delta power and AD tauopathy progression. These networks were validated in independent mouse and human cohorts. Identifying gene networks related to preclinical AD elucidate possible mechanisms associated with the early disease phase and potential targets to alter the disease course.

Background Clinically relevant glioma subtypes, such as the glioma-CpG island methylator phenotype (G-CIMP), have been defined by epigenetics. In this study, the role of long non-coding RNAs in association with the poor-prognosis G-CMIP-low phenotype and the good-prognosis G-CMIP-high phenotype was investigated. Functional associations of lncRNAs with mRNAs and miRNAs were examined to hypothesize influencing factors of the aggressive phenotype. Methods RNA-seq data on 250 samples from TCGA’s Pan-Glioma study, quantified for lncRNA and mRNAs (GENCODE v28), were analyzed for differential expression between G-CIMP-low and G-CIMP-high phenotypes. Functional interpretation of the differential lncRNAs was performed by Ingenuity Pathway Analysis. Spearman rank order correlation estimates between lncRNA, miRNA, and mRNA nominated differential lncRNA with a likely miRNA sponge function. Results We identified 4371 differentially expressed features (mRNA = 3705; lncRNA = 666; FDR ≤ 5%). From these, the protein-coding gene TP53 was identified as an upstream regulator of differential lncRNAs PANDAR and PVT1 (p = 0.0237) and enrichment was detected in the “development of carcinoma” (p = 0.0176). Two lncRNAs (HCG11, PART1) were positively correlated with 342 mRNAs, and their correlation estimates diminish after adjusting for either of the target miRNAs: hsa-miR-490-3p, hsa-miR-129-5p. This suggests a likely sponge function for HCG11 and PART1. Conclusions These findings identify differential lncRNAs with oncogenic features that are associated with G-CIMP phenotypes. Further investigation with controlled experiments is needed to confirm the molecular relationships.

Background In the field of movement disorders, what you see (phenotype) is seldom what you get (genotype). Whereas 1 phenotype was previously associated to 1 gene, the advent of next‐generation sequencing (NGS) has facilitated an exponential increase in disease‐causing genes and genotype–phenotype correlations, and the “one‐phenotype‐many‐genes” paradigm has become prominent. Objectives To highlight the “one‐phenotype‐many‐genes” paradigm by discussing the main challenges, perspectives on how to address them, and future directions. Methods We performed a scoping review of the various aspects involved in identifying the underlying molecular cause of a movement disorder phenotype. Results The notable challenges are (1) the lack of gold standards, overlap in clinical spectrum of different movement disorders, and variability in the interpretation of classification systems; (2) selecting which patients benefit from genetic tests and the choice of genetic testing; (3) problems in the variant interpretation guidelines; (4) the filtering of variants associated with disease; and (5) the lack of standardized, complete, and up‐to‐date gene lists. Perspectives to address these include (1) deep phenotyping and genotype–phenotype integration, (2) adherence to phenotype‐specific diagnostic algorithms, (3) implementation of current and complementary bioinformatic tools, (4) a clinical‐molecular diagnosis through close collaboration between clinicians and genetic laboratories, and (5) ongoing curation of gene lists and periodic reanalysis of genetic sequencing data. Conclusions Despite the rapidly emerging possibilities of NGS, there are still many steps to take to improve the genetic diagnostic yield. Future directions, including post‐NGS phenotyping and cohort analyses enriched by genotype–phenotype integration and gene networks, ought to be pursued to accelerate identification of disease‐causing genes and further improve our understanding of disease biology.

Human brain organoids are self-organizing three-dimensional structures that emerge from human pluripotent stem cells and mimic aspects of the cellular composition and functionality of the developing human brain. Despite their impressive self-organizing capacity, organoids lack the stereotypic structural anatomy of their in vivo counterpart, making conventional analysis techniques underpowered to assess cellular composition and gene network regulation in organoids. Advances in single cell transcriptomics have recently allowed characterization and improvement of organoid protocols, as they continue to evolve, by enabling identification of cell types and states along with their developmental origins. In this review, we summarize recent approaches, progresses and challenges in resolving brain organoid's complexity through single-cell transcriptomics. We then discuss emerging technologies that may complement single-cell RNA sequencing by providing additional readouts of cellular states to generate an organ-level view of developmental processes. Altogether, these integrative technologies will allow monitoring of global gene regulation in thousands of individual cells and will offer an unprecedented opportunity to investigate features of human brain development and disease across multiple cellular modalities and with cell-type resolution.

High night temperatures (HNT) are shown to significantly reduce rice (Oryza sativa L.) yield and quality. A better understanding of the genetic architecture of HNT tolerance will help rice breeders to develop varieties adapted to future warmer climates. In this study, a diverse indica rice panel displayed a wide range of phenotypic variability in yield and quality traits under control night (24 °C) and higher night (29 °C) temperatures. Genome-wide association analysis revealed 38 genetic loci associated across treatments (18 for control and 20 for HNT). Nineteen loci were detected with the relative changes in the traits between control and HNT. Positive phenotypic correlations and co-located genetic loci with previously cloned grain size genes revealed common genetic regulation between control and HNT, particularly grain size. Network-based predictive models prioritized 20 causal genes at the genetic loci based on known gene/s expression under HNT in rice. Our study provides important insights for future candidate gene validation and molecular marker development to enhance HNT tolerance in rice. Integrated physiological, genomic, and gene network-informed approaches indicate that the candidate genes for stay-green trait may be relevant to minimizing HNT-induced yield and quality losses during grain filling in rice by optimizing source-sink relationships.

Cardiomyocytes undergo significant structural and functional changes after birth, and these fundamental processes are essential for the heart to pump blood to the growing body. However, due to the challenges of isolating single postnatal/adult myocytes, how individual newborn cardiomyocytes acquire multiple aspects of the mature phenotype remains poorly understood. Here we implement large-particle sorting and analyze single myocytes from neonatal to adult hearts. Early myocytes exhibit wide-ranging transcriptomic and size heterogeneity that is maintained until adulthood with a continuous transcriptomic shift. Gene regulatory network analysis followed by mosaic gene deletion reveals that peroxisome proliferator-activated receptor coactivator-1 signaling, which is active in vivo but inactive in pluripotent stem cell-derived cardiomyocytes, mediates the shift. This signaling simultaneously regulates key aspects of cardiomyocyte maturation through previously unrecognized proteins, including YAP1 and SF3B2. Our study provides a single-cell roadmap of heterogeneous transitions coupled to cellular features and identifies a multifaceted regulator controlling cardiomyocyte maturation., Cardiomyocyte maturation and the acquisition of phenotypes is poorly understood at the single cell level. Here, the authors analyse the transcriptome of single cells from neonatal to adult heart and reveal that peroxisome proliferator-activated receptor coactivator-1 mediates the phenotypic shift.

Human stem-cell-derived models provide the promise of accelerating our understanding of brain disorders, but not knowing whether they possess the ability to mature beyond mid- to late-fetal stages potentially limits their utility. We leveraged a directed differentiation protocol to comprehensively assess maturation in vitro. Based on genome-wide analysis of the epigenetic clock and transcriptomics, as well as RNA editing, we observe that three-dimensional human cortical organoids reach postnatal stages between 250 and 300 days, a timeline paralleling in vivo development. We demonstrate the presence of several known developmental milestones, including switches in the histone deacetylase complex and NMDA receptor subunits, which we confirm at the protein and physiological levels. These results suggest that important components of an intrinsic in vivo developmental program persist in vitro. We further map neurodevelopmental and neurodegenerative disease risk genes onto in vitro gene expression trajectories to provide a resource and webtool (Gene Expression in Cortical Organoids, GECO) to guide disease modeling.

Genes related to the MAPK cascade, ethylene signaling pathway, Pi starvation response, and NAC TFs were differentially expressed between normal and abortive ovules. Receptor-mediated ethylene signal perception and transmission play an important role in regulating fruit and ovule development. Xanthoceras sorbifolium, a small to medium-sized tree endemic to northern China, is an emerging dedicated oilseed crop designed for applications in advanced biofuel, engine oil, and functional food, as well as for pharmaceutical and cosmetic applications. Despite the importance of Xanthoceras seed oil, low seed productivity has constricted commercial exploitation of the species. The abortion of developing seeds (ovules after fertilization) is a major factor limiting fruit and seed production in the plant. To increase fruit and seed yields, a better understanding of the mechanisms underlying the abortion of fertilized ovules is critical. This study revealed differences in nucellus degeneration, endosperm development, and starch grain content between normally and abnormally developing ovules after fertilization. We constructed 6 RNA-sequencing (RNA-seq) libraries from normally and abnormally developing ovules at the onset of their abortion process. Comparative transcriptome analysis between the normal and abnormal ovules identified 818 differentially expressed genes (DEGs). Among DEGs, many genes involved in mitogen-activated protein kinase (MAPK) cascades, ethylene signaling pathway, and NAC transcription factor genes showed up-regulated expression in abnormal ovules. The RNA-seq data were validated using quantitative reverse-transcription PCR. Using virus-induced gene silencing (VIGS) methods, evaluation of an ethylene receptor gene (XsERS) function indicated that the gene was closely related to early development of fruits and seeds. Based on the data presented here, we propose a model for a MAPK-ethylene signaling-NAC2 gene regulatory cascade that plays an important role in the regulation of the ovule abortion process in X. sorbifolium. The present study is imperative for understanding the mechanisms of ovule abortion after fertilization and identifying the critical genes and gene networks involved in determining the fate of ovule development.

Glucosinolates (GSLs) are plant secondary metabolites consisting of sulfur and nitrogen, commonly found in Brassicaceae crops, such as Arabidopsis thaliana. These compounds are known for their roles in plant defense mechanisms against pests and pathogens. ‘Guilt-by-association’ (GBA) approach predicts genes encoding proteins with similar function tend to share gene expression pattern generated from high throughput sequencing data. Recent studies have successfully identified GSL genes using GBA approach, followed by targeted verification of gene expression and metabolite data. Therefore, a GSL co-expression network was constructed using known GSL genes obtained from our in-house database, SuCComBase. DPClusO was used to identify subnetworks of the GSL co-expression network followed by Fisher’s exact test leading to the discovery of a potential gene that encodes the ARIA-interacting double AP2-domain protein (ADAP) transcription factor (TF). Further functional analysis was performed using an effective gene silencing system known as CRES-T. By applying CRES-T, ADAP TF gene was fused to a plant-specific EAR-motif repressor domain (SRDX), which suppresses the expression of ADAP target genes. In this study, ADAP was proposed as a negative regulator in aliphatic GSL biosynthesis due to the over-expression of downstream aliphatic GSL genes (UGT74C1 and IPMI1) in ADAP-SRDX line. The significant over-expression of ADAP gene in the ADAP-SRDX line also suggests the behavior of the TF that negatively affects the expression of UGT74C1 and IPMI1 via a feedback mechanism in A. thaliana.

Melanoma is the most lethal skin malignancy, driven by genetic and epigenetic alterations in the complex tumour microenvironment. While large-scale molecular profiling of melanoma has identified molecular signatures associated with melanoma progression, comprehensive systems-level modeling remains elusive. This study builds up predictive gene network models of molecular alterations in primary melanoma by integrating large-scale bulk-based multi-omic and single-cell transcriptomic data. Incorporating clinical, epigenetic, and proteomic data into these networks reveals key subnetworks, cell types, and regulators underlying melanoma progression. Tumors with high immune infiltrates are found to be associated with good prognosis, presumably due to induced CD8+ T-cell cytotoxicity, via MYO1F-mediated M1-polarization of macrophages. Seventeen key drivers of the gene subnetworks associated with poor prognosis, including the transcription factor ZNF180, are tested for their pro-tumorigenic effects in vitro. The anti-tumor effect of silencing ZNF180 is further validated using in vivo xenografts. Experimentally validated targets of ZNF180 are enriched in the ZNF180 centered network and the known pathways such as melanoma cell maintenance and immune cell infiltration. The transcriptional networks and their critical regulators provide insights into the molecular mechanisms of melanomagenesis and pave the way for developing therapeutic strategies for melanoma., While the molecular profiling of melanoma progression has been extensively characterised by large-scale studies, there is still need for the comprehensive integration of such datasets. Here the authors construct predictive gene network models for prognostic and therapeutic purposes.

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex (DLPFC). We identified extensive layer-enriched expression signatures, and refined associations to previous laminar markers. We overlaid our laminar expression signatures onto large-scale single nuclei RNA sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially-defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions where morphological architecture is not as well-defined as cortical laminae. We lastly created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research (http://research.libd.org/spatialLIBD).

Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior., Connecting genotypes to complex social behaviour is challenging. Taylor et al. use machine learning to show a strong response of caste-associated gene expression to queen loss, wherein individual wasp’s expression profiles become intermediate between queen and worker states, even in the absence of behavioural changes.

This review comes from a themed issue on Development and regulation., Proper formation of adult insects requires the integration of spatial and temporal regulatory axes. Whereas spatial information confers identity to each tissue, organ and appendage, temporal information specifies at which stage of development the animal is. Regardless of the type of post-embryonic development, either hemimetabolous or holometabolous, temporal specificity is achieved through interactions between the temporal identity genes Kr-h1, E93 and Br-C, whose sequential expression is controlled by the two major developmental hormones, 20-hydroxyecdysone and Juvenile hormone. Given the intimate regulatory connection between these three factors to specify life stage identity, we dubbed the regulatory axis that comprises these genes as the Metamorphic Gene Network (MGN). In this review, we survey the molecular mechanisms underlying the control by the MGN of stage identity and progression in hemimetabolous and holometabolous insects., Support for this study was provided by the Spanish MINECO (grant PGC2018-098427-B-I00 to DM and XF-M) and by the Catalan Government (2017 SGR 01030 to DM and XF-M). The research has also benefited from FEDER, UE funds.

Although previous studies have explored the gene expression profiles of human oocytes and granulosa cells by single‐cell RNA sequencing (scRNA‐seq), the dynamic regulatory network at a single‐cell resolution during folliculogenesis remains largely unknown. We identified 10 functional modules by WGCNA, four of which were significantly correlated with primary/antral oocyte and antral/pre‐ovulatory granulosa cells. Functional enrichment analysis showed that the brown module, which was correlated with antral oocyte, was enriched in oocyte differentiation, and two core subnetworks identified by MCODE were involved in cell cycle (blue subnetwork) and oogenesis (red subnetwork). The cell‐specific network (CSN) analysis demonstrated a distinct gene network structure associated with the antral follicular stage, which was notably different from other developmental stages. To our knowledge, this is the first study to explore gene functions during folliculogenesis at single‐cell network level. We uncovered two potential gene subnetworks, which may play an important role in oocyte function beginning at the antral stage, and further established their rewiring process at intra‐network/whole transcriptome level. The findings provide crucial insights from a novel network perspective to be further explored in functional mechanistic studies.

In this research, seven diseases OB (Obesity), SC (Stomach Cancer), CC (Colorectal Cancer), PC (Pancreatic Cancer), PRC (Prostate Cancer), LK (Leukemia), MD (Metabolic Disorder) has been encountered to analyze the network. When one or few diseases among them affects human there will be a possibility for them to be affected by the other diseases. Previous studies indicate that there are large numbers of similar biological and genetic characteristics among the seven disease. Common gene network models among these diseases have been explored for this reason. The genes obtained were compared and number of the gene has been decreased by the preprocessing and filtering process. After the filtering process, 9 common genes among seven related disease has been extracted. Topological properties, protein interactions network, enrichment analysis, co-expression network analysis, gene regulatory network, and physical interaction network are analyzed in this research. The substantial hub proteins based on biological, genetic and biochemical relationships among common genes has been identified by this analysis. Drug signature suggestion implies the 9 hub proteins which has been identified by PPI, GRN, gene interaction protein network. Finally, Protein chemical interaction and gene-disease interaction network indicated 6 significant genes and 9 significant genes consecutively for drug design. Network Enrichment shows the 9 common hub proteins interaction with other related genes. This analysis helps us to identify drug design pathway with chemical interactions. By applying further examining and studies those gene structures, it may be able to notify us to take precautionary steps to reduce the risk of Stomach Cancer and Associated disease.

Mood disorders represent a major cause of morbidity and mortality worldwide but the brain-related molecular pathophysiology in mood disorders remains largely undefined. Because the anterior insula is reduced in volume in patients with mood disorders, RNA was extracted from the anterior insula postmortem anterior insula of mood disorder samples and compared with unaffected controls for RNA-sequencing identification of differentially expressed genes (DEGs) in (a) bipolar disorder (BD; n = 37) versus (vs.) controls (n = 33), and (b) major depressive disorder (MDD n = 30) vs. controls, and (c) low vs. high axis I comorbidity (a measure of cumulative psychiatric disease burden). Given the regulatory role of transcription factors (TFs) in gene expression via specific-DNA-binding domains (motifs), we used JASPAR TF binding database to identify TF-motifs. We found that DEGs in BD vs. controls, MDD vs. controls, and high vs. low axis I comorbidity were associated with TF-motifs that are known to regulate expression of toll-like receptor genes, cellular homeostatic-control genes, and genes involved in embryonic, cellular/organ, and brain development. Robust imaging-guided transcriptomics by using meta-analytic imaging results to guide independent postmortem dissection for RNA-sequencing was applied by targeting the gray matter volume reduction in the anterior insula in mood disorders, to guide independent postmortem identification of TF motifs regulating DEG. Our findings of TF-motifs that regulate the expression of immune, cellular homeostatic-control, and developmental genes provide novel information about the hierarchical relationship between gene regulatory networks, the TFs that control them, and proximate underlying neuroanatomical phenotypes in mood disorders.

Female puberty is subject to Polycomb Group (PcG)-dependent transcriptional repression. Kiss1, a puberty-activating gene, is a key target of this silencing mechanism. Using a gain-of-function approach and a systems biology strategy we now show that EED, an essential PcG component, acts in the arcuate nucleus of the hypothalamus to alter the functional organization of a gene network involved in the stimulatory control of puberty. A central node of this network is Kdm6b, which encodes an enzyme that erases the PcG-dependent histone modification H3K27me3. Kiss1 is a first neighbor in the network; genes encoding glutamatergic receptors and potassium channels are second neighbors. By repressing Kdm6b expression, EED increases H3K27me3 abundance at these gene promoters, reducing gene expression throughout a gene network controlling puberty activation. These results indicate that Kdm6b repression is a basic mechanism used by PcG to modulate the biological output of puberty-activating gene networks.

As changes occur in climate, abiotic stress to agricultural production is an inevitable threat to farmers’ ability to meet an increasing demand to feed people. Plants have developed a stress tolerance mechanism to reduce the effects of such environmental conditions by engaging various stress-responsive genes. Accordingly, various signal transduction networks are used to fabricate stress tolerance. Engineering of the phytohormone abscisic acid (ABA) could be a choice method for scientists to mitigate abiotic stress because of its widespread role in response to salt, drought, heat, and cold stresses including triggering stomatal regulation and leaf senescence. In addition, it plays a crucial role in seed maturation, seed dormancy, stomatal opening/closure and increases resistance against pathogens through callose depositions and regulates physiological strategies in stress signaling pathways through synchronizing of hormonal crosstalk. The transcriptional regulation can be achieved through ABA-dependent and ABA-independent signaling cascades. ABAI5 and RD29A genes are regulated in ABA-dependent and independent manners to mitigate stress tolerance. ABA regulatory components (RCARs) including pyrabactin resistance PYR/PYL genes, SnRK2 type protein kinases, transcription factors (WRKY, NAC, AREB1, bZIP, RGL2, and ABRE), reactive oxygen species, jasmonic acid and cytokinin hormones regulate ABA gene action in response to abiotic stresses.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high intratumoral heterogeneity. Recent studies revealed that TNBC patients might comprise cells with distinct molecular subtypes. In addition, gene regulatory networks (GRNs) constructed based on single-cell RNA sequencing (scRNA-seq) data have demonstrated the significance for decoding the key regulators. We performed a comprehensive analysis of the GRNs for the intrinsic subtypes of TNBC patients using scRNA-seq. The copy number variations (CNVs) were inferred from scRNA-seq data and identified 545 malignant cells. The subtypes of the malignant cells were assigned based on the PAM50 model. The cell-cell communication analysis revealed that the macrophage plays a dominant role in the tumor microenvironment. Next, the GRN for each subtype was constructed through integrating gene co-expression and enrichment of transcription-binding motifs. Then, we identified the critical genes based on the centrality metrics of genes. Importantly, the critical gene ETV6 was ubiquitously upregulated in all subtypes, but it exerted diverse roles in each subtype through regulating different target genes. In conclusion, the construction of GRNs based on scRNA-seq data could help us to dissect the intratumoral heterogeneity and identify the critical genes of TNBC., Graphical Abstract, Jiang and colleagues performed a comprehensive analysis of the GRNs for the intrinsic subtypes of TNBC patients using scRNA-seq. The cell-cell communication analysis revealed that the macrophage plays a dominant role in the tumor microenvironment. In addition, the critical gene ETV6 exerted diverse roles in each subtype through regulating different target genes.

Bioelectrical impulses intrinsically generated within the sinoatrial node (SAN) trigger the contraction of the heart in mammals. Though discovered over a century ago, the molecular and cellular features of the SAN that underpin its critical function in the heart are uncharted territory. Here, we identify four distinct transcriptional clusters by single-cell RNA sequencing in the mouse SAN. Functional analysis of differentially expressed genes identifies a core cell cluster enriched in the electrogenic genes. The similar cellular features are also observed in the SAN from both rabbit and cynomolgus monkey. Notably, Vsnl1, a core cell cluster marker in mouse, is abundantly expressed in SAN, but is barely detectable in atrium or ventricle, suggesting that Vsnl1 is a potential SAN marker. Importantly, deficiency of Vsnl1 not only reduces the beating rate of human induced pluripotent stem cell - derived cardiomyocytes (hiPSC-CMs) but also the heart rate of mice. Furthermore, weighted gene co-expression network analysis (WGCNA) unveiled the core gene regulation network governing the function of the SAN in mice. Overall, these findings reveal the whole transcriptome profiling of the SAN at single-cell resolution, representing an advance toward understanding of both the biology and the pathology of SAN., The spontaneous bioelectrical activity of pacemaker cells in sinoatrial node (SAN) triggers the heartbeats. Here, the authors perform single-cell RNA sequencing in the mouse SAN and identify molecular and cellular features of the SAN conserved in rabbit and cynomolgus monkey, identifying a new potential SAN marker.