Project description:Network analyses of structural connectivity in the brain have highlighted a set of highly connected hubs that are densely interconnected, forming a "rich-club" substrate in diverse species. Here, we demonstrate the existence of rich-club organization in functional brain networks of rats. Densely interconnected rich-club regions are found to be distributed in multiple brain modules, with the majority located within the putative default mode network. Rich-club members exhibit high wiring cost (as measured by connection distance) and high metabolic running cost (as surrogated by cerebral blood flow), which may have evolved to achieve high network communications to support efficient brain functions. Furthermore, by adopting a forepaw electrical stimulation paradigm, we find that the rich-club organization of the rat functional network remains almost the same as in the resting state, whereas path motif analysis reveals significant differences, suggesting the rat brain reorganizes its topological routes by increasing locally oriented shortcuts but reducing rich-club member-involved paths to conserve metabolic running cost during unimodal stimulation. Together, our results suggest that the neuronal system is organized and dynamically operated in an economic way to balance between cost minimization and topological/functional efficiency.
Project description:Aberrant stem cell-like gene regulatory networks are a feature of leukaemogenesis. The ETS-related gene (ERG), an important regulator of normal haematopoiesis, is also highly expressed in T-ALL and acute myeloid leukaemia (AML). However, the transcriptional regulation of ERG in leukaemic cells remains poorly understood. In order to discover transcriptional regulators of ERG, we employed a quantitative mass spectrometry-based method to identify factors binding the 321 bp ERG +85 stem cell enhancer region in MOLT-4 T-ALL and KG-1 AML cells. Using this approach, we identified a number of known binders of the +85 enhancer in leukaemic cells along with previously unknown binders, including ETV6 and IKZF1. We confirmed that ETV6 and IKZF1 were also bound at the +85 enhancer in both leukaemic cells and in healthy human CD34+ haematopoietic stem and progenitor cells. Knockdown experiments confirmed that ETV6 and IKZF1 are transcriptional regulators not just of ERG, but also of a number of genes regulated by a densely interconnected network of seven transcription factors. At last, we show that ETV6 and IKZF1 expression levels are positively correlated with expression of a number of heptad genes in AML and high expression of all nine genes confers poorer overall prognosis.
Project description:Cardiac regeneration may revolutionize treatment for heart failure but endogenous progenitor-derived cardiomyocytes in the adult mammalian heart are few and pre-existing adult cardiomyocytes divide only at very low rates. Although candidate genes that control cardiomyocyte cell cycle re-entry have been implicated, expression heterogeneity in the cardiomyocyte stress-response has never been explored. Here, we show by single nuclear RNA-sequencing of cardiomyocytes from both mouse and human failing, and non-failing adult hearts that sub-populations of cardiomyocytes upregulate cell cycle activators and inhibitors consequent to the stress-response in vivo. We characterize these subgroups by weighted gene co-expression network analysis and discover long intergenic non-coding RNAs (lincRNA) as key nodal regulators. KD of nodal lincRNAs affects expression levels of genes related to dedifferentiation and cell cycle, within the same gene regulatory network. Our study reveals that sub-populations of adult cardiomyocytes may have a unique endogenous potential for cardiac regeneration in vivo.Adult mammalian cardiomyocytes are predominantly binucleated and unable to divide. Using single nuclear RNA-sequencing of cardiomyocytes from mouse and human failing and non-failing adult hearts, See et al. show that some cardiomyocytes respond to stress by dedifferentiation and cell cycle re-entry regulated by lncRNAs.
Project description:Recent genome-wide association studies have identified many promising schizophrenia candidate genes and demonstrated that common polygenic variation contributes to schizophrenia risk. However, whether these genes represent perturbations to a common but limited set of underlying molecular processes (pathways) that modulate risk to schizophrenia remains elusive, and it is not known whether these genes converge on common biological pathways (networks) or represent different pathways. In addition, the theoretical and genetic mechanisms underlying the strong genetic heterogeneity of schizophrenia remain largely unknown. Using 4 well-defined data sets that contain top schizophrenia susceptibility genes and applying protein-protein interaction (PPI) network analysis, we investigated the interactions among proteins encoded by top schizophrenia susceptibility genes. We found proteins encoded by top schizophrenia susceptibility genes formed a highly significant interconnected network, and, compared with random networks, these PPI networks are statistically highly significant for both direct connectivity and indirect connectivity. We further validated these results using empirical functional data (transcriptome data from a clinical sample). These highly significant findings indicate that top schizophrenia susceptibility genes encode proteins that significantly directly interacted and formed a densely interconnected network, suggesting perturbations of common underlying molecular processes or pathways that modulate risk to schizophrenia. Our findings that schizophrenia susceptibility genes encode a highly interconnected protein network may also provide a novel explanation for the observed genetic heterogeneity of schizophrenia, ie, mutation in any member of this molecular network will lead to same functional consequences that eventually contribute to risk of schizophrenia.
Project description:BACKGROUND: Long non-coding RNAs (lncRNAs) are recognized as pivotal players during developmental ontogenesis and pathogenesis of cancer. The intronic microRNA (miRNA) clusters miR-99a?~?125b-2 and miR-100?~?125b-1 promote progression of acute megakaryoblastic leukemia (AMKL), an aggressive form of hematologic cancers. The function of the lncRNA hostgenes MIR99AHG (alias MONC) and MIR100HG within this ncRNA ensemble remained elusive. RESULTS: Here we report that lncRNAs MONC and MIR100HG are highly expressed in AMKL blasts. The transcripts were mainly localized in the nucleus and their expression correlated with the corresponding miRNA clusters. Knockdown of MONC or MIR100HG impeded leukemic growth of AMKL cell lines and primary patient samples. The development of a lentiviral lncRNA vector to ectopically express lncRNAs without perturbing their secondary structure due to improper termination of the viral transcript, allowed us to study the function of MONC independent of the miRNAs in cord blood hematopoietic stem and progenitor cells (HSPCs). We could show that MONC interfered with hematopoietic lineage decisions and enhanced the proliferation of immature erythroid progenitor cells. CONCLUSIONS: Our study reveals an unprecedented function of lncRNAs MONC and MIR100HG as regulators of hematopoiesis and oncogenes in the development of myeloid leukemia.
Project description:MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.
Project description:The human commensal and opportunistic pathogen Candida albicans can switch between two distinct, heritable cell types, named "white" and "opaque," which differ in morphology, mating abilities, and metabolic preferences and in their interactions with the host immune system. Previous studies revealed a highly interconnected group of transcriptional regulators that control switching between the two cell types. Here, we identify Ssn6, the C. albicans functional homolog of the Saccharomyces cerevisiae transcriptional corepressor Cyc8, as a new regulator of white-opaque switching. In A: or α mating type strains, deletion of SSN6 results in mass switching from the white to the opaque cell type. Transcriptional profiling of ssn6 deletion mutant strains reveals that Ssn6 represses part of the opaque cell transcriptional program in white cells and the majority of the white cell transcriptional program in opaque cells. Genome-wide chromatin immunoprecipitation experiments demonstrate that Ssn6 is tightly integrated into the opaque cell regulatory circuit and that the positions to which it is bound across the genome strongly overlap those bound by Wor1 and Wor2, previously identified regulators of white-opaque switching. This work reveals the next layer in the white-opaque transcriptional circuitry by integrating a transcriptional regulator that does not bind DNA directly but instead associates with specific combinations of DNA-bound transcriptional regulators.The most common fungal pathogen of humans, C. albicans, undergoes several distinct morphological transitions during interactions with its host. One such transition, between cell types named "white" and "opaque," is regulated in an epigenetic manner, in the sense that changes in gene expression are heritably maintained without any modification of the primary genomic DNA sequence. Prior studies revealed a highly interconnected network of sequence-specific DNA-binding proteins that control this switch. We report the identification of Ssn6, which defines an additional layer of transcriptional regulation that is critical for this heritable switch. Ssn6 is necessary to maintain the white cell type and to properly express the opaque cell transcriptional program. Ssn6 does not bind DNA directly but rather associates with specific combinations of DNA-bound transcriptional regulators to control the switch. This work is significant because it reveals a new level of regulation of an important epigenetic switch in the predominant fungal pathogen of humans.
Project description:Network analysis was used to examine how densely interconnected individual negative symptom domains are, whether some domains are more central than others, and whether sex influenced network structure. Participants included outpatients with schizophrenia (SZ; n = 201), a bipolar disorder (BD; n = 46) clinical comparison group, and healthy controls (CN; n = 27) who were rated on the Brief Negative Symptom Scale. The mutual information measure was used to construct negative symptom networks. Groups were compared on macroscopic network properties to evaluate overall network connectedness, and microscopic properties to determine which domains were most central. Macroscopic analyses indicated that patients with SZ had a less densely connected negative symptom network than BD or CN groups, and that males with SZ had less densely connected networks than females. Microscopic analyses indicated that alogia and avolition were most central in the SZ group, whereas anhedonia was most central in BD and CN groups. In addition, blunted affect, alogia, and asociality were most central in females with SZ, and alogia and avolition were most central in males with SZ. These findings suggest that negative symptoms may be highly treatment resistant in SZ because they are not very densely connected. Less densely connected networks may make treatments less likely to achieve global reductions in negative symptoms because individual domains function in isolation with little interaction. Sex differences in centralities suggest that the search for pathophysiological mechanisms and targeted treatment development should be focused on different sets of symptoms in males and females.
Project description:An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pairs of nodes and their maximal similar neighbors we find real communities. We show that the overall advantage of the proposed algorithm compared to the other community detection algorithms is its simple nature, low computational cost and its very high accuracy in detection communities of different sizes also in networks with blurred modularity structure consisting of poorly separated communities. All communities identified by the proposed method for facebook network and E-Coli transcriptional regulatory network have strong structural and functional coherence.
Project description:Chromodomain helicase DNA-binding protein 8 (CHD8) was identified as a leading autism spectrum disorder (ASD) candidate gene by whole-exome sequencing and subsequent targeted-sequencing studies. De novo loss-of-function mutations were identified in 12 individuals with ASD and zero controls, accounting for a highly significant association. Small interfering RNA-mediated knockdown of CHD8 in human neural progenitor cells followed by RNA sequencing revealed that CHD8 insufficiency results in altered expression of 1715 ?genes, including both protein-coding and noncoding RNAs. Among the 10 most changed transcripts, 4 (40%) were noncoding RNAs. The transcriptional changes among protein-coding genes involved a highly interconnected network of genes that are enriched in neuronal development and in previously identified ASD candidate genes. These results suggest that CHD8 insufficiency may be a central hub in neuronal development and ASD risk.