Search

Background: Sexual precocity is a common biological phenomenon in animal species. A large number of precocity individuals were identified in Chinese mitten crab Eriocheir sinensis, which caused huge economic loss annually. However, the underlying genetic basis of precocity in E. sinensis remains unclear to date., Results: In this study, morphological and histological observation and comparative transcriptome analysis were conducted among different stages of precocious one-year-old and normal two-year-old sexually mature E. sinensis. The expression profiles of the ovary, hepatopancreas, and eyestalk tissues were presented and compared. Genes associated with lipid metabolic process, lipid transport, vitelline membrane formation, vitelline synthesis, and neuropeptide hormone-related genes were upregulated in the ovary, hepatopancreas, and eyestalk of precocious E. sinensis. Our results indicated that the eyestalk was involved in the neuroendocrine system providing neuropeptide hormones that may induce vitellogenesis in the hepatopancreas and further stimulate ovary development. The hepatopancreas is a site for energy storage and vitellogenin synthesis, and it may assist oogenesis through lipid transport in precocious E. sinensis., Conclusion: We provided not only an effective and convenient phenotype measurement method for the identification of potential precocious E. sinensis detection but also valuable genetic resources and novel insights into the molecular mechanism of precocity in E. sinensis. The genetic basis of precocity in E. sinensis is an integrated gene regulatory network of eyestalk, hepatopancreas, and ovary tissues.

The TMPRSS2-ERG gene fusion were frequently found in prostate cancer, and thought to play some fundamental mechanisms for the development of prostate cancer. However, until now, the clinical and prognostic significance of TMPRSS2-ERG gene fusion was not fully understood. In this study, based on the 281 prostate cancers that constructed from a historical watchful waiting cohort, the statistically significant associations between TMPRSS2-ERG gene fusion and clinicopathologic characteristics were identified. In addition, the Elastic Net algorithm was used to predict the patients with TMPRSS2-ERG fusion status, and good predictive results were obtained, indicating that this algorithm was suitable to this prediction problem. The differential gene network was constructed from the network, and the KEGG enrichment analysis demonstrated that the module genes were significantly enriched in several important pathways., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Protein-protein interaction (PPI) networks are emerging as valuable prototypes to study important problems in molecular cellular biology and systems biomedicine. An analysis of the topological properties of a PPI network is very helpful for understanding the function and structure of networks. In this study, we analyzed the topological patterns in the BioPlex network containing interactions among 10,961 proteins; most interactions were previously undocumented. The BioPlex network is a comprehensive map of human protein interactions and represents the first phase of a long-term effort to profile the entire human ORFEOME collection. Similar to other biological networks, we observed that the BioPlex network has several topological properties. We also quantified correlations profiles for the BioPlex network and compared them to randomized versions of the same network. We found that for the BioPlex network, edges between proteins with intermediate degrees were strongly suppressed, whereas edges between low-connected proteins were favored. Finally, the degrees of essential genes were compared with the degrees of non-essential genes and randomly selected proteins. There were no significant differences between the groups., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Essential genes are those that are indispensable for the survival and propagation of an organism. TATA-containing genes are associated with responses to various stresses and are highly regulated. Although both essential genes and TATA genes are very important in the function of biological systems, their relationship remains unclear because they have typically been researched independently. In this study, to investigate the relationship between essential genes and TATA genes, S. cerevisiae genes were classified as: essential TATA-containing, non-essential TATA-containing, essential non-TATA, and non-essential non-TATA genes. Network-based methods were applied to analyze these four gene categories in the S. cerevisiae perturbation sensitivity (PS) network, which was created from the transcriptional profiling of hundreds of different gene disruptions. All of the topological properties were found to be statistically discriminative among the four gene categories, and the non-essential TATA-containing genes had the most important roles in the yeast PS network., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Motivation: miRNAs play crucial roles in human diseases and newly discovered could be targeted by small molecule (SM) drug compounds. Thus, the identification of small molecule drug compounds (SM) that target dysregulated miRNAs in cancers will provide new insight into cancer biology and accelerate drug discovery for cancer therapy., Results: In this study, we aimed to develop a novel computational method to comprehensively identify associations between SMs and miRNAs. To this end, exploiting multiple molecular interaction databases, we first established an integrated SM-miRNA association network based on 690 561 SM to SM interactions, 291 600 miRNA to miRNA associations, as well as 664 known SM to miRNA targeting pairs. Then, by performing Random Walk with Restart algorithm on the integrated network, we prioritized the miRNAs associated to each of the SMs. By validating our results utilizing an independent dataset we obtained an area under the ROC curve greater than 0.7. Furthermore, comparisons indicated our integrated approach significantly improved the identification performance of those simple modeled methods. This computational framework as well as the prioritized SM-miRNA targeting relationships will promote the further developments of targeted cancer therapies., Contact: yxli@sibs.ac.cn, lixia@hrbmu.edu.cn or jiangwei@hrbmu.edu.cn, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The global insight into the relationships between miRNAs and their regulatory influences remains poorly understood. And most of complex diseases may be attributed to certain local areas of pathway (subpathway) instead of the entire pathway. Here, we reviewed the studies on miRNA regulations to pathways and constructed a bipartite miRNAs and subpathways network for systematic analyzing the miRNA regulatory influences to subpathways. We found that a small fraction of miRNAs were global regulators, environmental information processing pathways were preferentially regulated by miRNAs, and miRNAs had synergistic effect on regulating group of subpathways with similar function. Integrating the disease states of miRNAs, we also found that disease miRNAs regulated more subpathways than nondisease miRNAs, and for all miRNAs, the number of regulated subpathways was not in proportion to the number of the related diseases. Therefore, the study not only provided a global view on the relationships among disease, miRNA and subpathway, but also uncovered the function aspects of miRNA regulations and potential pathogenesis of complex diseases. A web server to query, visualize and download for all the data can be freely accessed at http://bioinfo.hrbmu.edu.cn/miR2Subpath.

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a new optimization procedure to identify the top network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression. [ABSTRACT FROM AUTHOR]

Biological circuits such as neural or gene regulation networks use internal states to map sensory input to an adaptive repertoire of behavior. Characterizing this mapping is a major challenge for systems biology. Though experiments that probe internal states are developing rapidly, organismal complexity presents a fundamental obstacle given the many possible ways internal states could map to behavior. Using C. elegans as an example, we propose a protocol for systematic perturbation of neural states that limits experimental complexity and could eventually help characterize collective aspects of the neural-behavioral map. We consider experimentally motivated small perturbations—ones that are most likely to preserve natural dynamics and are closer to internal control mechanisms—to neural states and their impact on collective neural activity. Then, we connect such perturbations to the local information geometry of collective statistics, which can be fully characterized using pairwise perturbations. Applying the protocol to a minimal model of C. elegans neural activity, we find that collective neural statistics are most sensitive to a few principal perturbative modes. Dominant eigenvalues decay initially as a power law, unveiling a hierarchy that arises from variation in individual neural activity and pairwise interactions. Highest-ranking modes tend to be dominated by a few, "pivotal" neurons that account for most of the system's sensitivity, suggesting a sparse mechanism of collective control. Author summary: The relationship between underlying biological circuitry and behavior is complex and difficult to probe experimentally. Part of the problem is that, for organisms of even modest size, there are an overwhelming number of possible combinations of interacting circuit components. We develop a theoretical framework to simplify this problem with experiments that change the system minimally with small perturbations. In the realm of small perturbations, not only does system behavior remain close to normal but the range of possible perturbations is greatly reduced to only pairs of experimental targets. We demonstrate such a perturbation using a minimal model of neural activity in the C. elegans worm. We find that a few combinations of "pivotal" neurons strongly affect the statistics of synchronous activity, suggesting they may be important for neural control of behavior. Our work suggests generalizable, feasible, and perturbative experiments to map how the physical components of an organism control emergent collective activity. [ABSTRACT FROM AUTHOR]

Background: Despite much improvement in the treatment for acute lymphoblastic leukemia (ALL), childhood ALLs with MLL -rearrangement (MLL -r) still have inferior dismal prognosis. Thus, defining mechanisms underlying MLL -r ALL maintenance is critical for developing effective therapy. Methods: GSE13159 and GSE28497 were selected via the Oncomine website. Differentially expressed genes (DEGs) between MLL -r ALLs and normal samples were identified by R software. Next, functional enrichment analysis of these DEGs were carried out by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Then, the key hub genes and modules were identified by Weighted Gene Co-expression Network Analysis (WGCNA). Therapeutically Applicable Research to Generate Effective Treatments (TARGET) ALL (Phase I) of UCSC Xena analysis, qPCR, and Kaplan-Meier analysis were conducted for validating the expression of key hub genes from bone marrow cells of childhood ALL patients or ALL cell lines. Results: A total of 1,045 DEGs were identified from GSE13159 and GSE28497. Through GO, KEGG, GSEA, and STRING analysis, we demonstrated that MLL -r ALLs were upregulating "nucleosome assembly" and "B cell receptor signal pathway" genes or proteins. WGCNA analysis found 18 gene modules using hierarchical clustering between MLL -r ALLs and normal. The Venn diagram was used to filter the 98 hub genes found in the key module with the 1,045 DEGs. We identified 18 hub genes from this process, 9 of which were found to be correlated with MLL -r status, using the UCSC Xena analysis. By using qPCR, we validated these 9 hub key genes to be upregulated in the MLL -r ALLs (RS4;11 and SEM) compared to the non- MLL -r ALL (RCH-ACV) cell lines. Three of these genes, BCL11A , GLT8D1 and NCBP2, were shown to be increased in MLL -r ALL patient bone marrows compared to the non- MLL -r ALL patient. Finally, Kaplan–Meier analysis indicated that childhood ALL patients with high BCL11A expression had significantly poor overall survival. Conclusion: These findings suggest that upregulated BCL11A gene expression in childhood ALLs may lead to MLL -r ALL development and BCL11A represents a new potential therapeutic target for childhood MLL -r ALL. [ABSTRACT FROM AUTHOR]

Motivation: Alzheimer’s disease (AD) is a severe neurodegenerative disease of the central nervous system that may be caused by perturbation of regulatory pathways rather than the dysfunction of a single gene. However, the pathology of AD has yet to be fully elucidated.Results: In this study, we systematically analyzed AD-related mRNA and miRNA expression profiles as well as curated transcription factor (TF) and miRNA regulation to identify active TF and miRNA regulatory pathways in AD. By mapping differentially expressed genes and miRNAs to the curated TF and miRNA regulatory network as active seed nodes, we obtained a potential active subnetwork in AD. Next, by using the breadth-first-search technique, potential active regulatory pathways, which are the regulatory cascade of TFs, miRNAs and their target genes, were identified. Finally, based on the known AD-related genes and miRNAs, the hypergeometric test was used to identify active pathways in AD. As a result, nine pathways were found to be significantly activated in AD. A comprehensive literature review revealed that eight out of nine genes and miRNAs in these active pathways were associated with AD. In addition, we inferred that the pathway hsa-miR-146a→STAT1→MYC, which is the source of all nine significantly active pathways, may play an important role in AD progression, which should be further validated by biological experiments. Thus, this study provides an effective approach to finding active TF and miRNA regulatory pathways in AD and can be easily applied to other complex diseases.Contact: lixia@hrbmu.edu.cn or lw2247@gmail.com.Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

mTOR is a typical and conserved serine/threonine protein kinase that regulates cell growth and metabolism of organisms. Molting is a fundamental biological process in Chinese mitten crab (Eriocheir sinensis) and is monitored by a series of genes and pathways. The structural and functional characteristics of EsmTOR was investigated to determine the role of mTOR in the molting process of. The intact CDS of EsmTOR is 7449 bp in length and encodes a polypeptide consisting of 2482 amino acids. EsmTOR was expressed in all eight tissues examined during the three molting stages (postmolt, intermolt andpremolt), with levels fluctuating significantly during the molting. RNA interference of EsmTOR significantly delayed molting, indicating that mTOR may be involved in the molting process of E. sinensis. Meanwhile, a substantial downregulation was observed for the expression of upstream genes involved in amino acid transport (EsSLC7A5 and EsVATB) and downstream genes promoting ribosomal protein synthesis (EsS6K1) in the mTOR signaling pathway, as well as typical molt-related genes (EsMIH and EsEcR) after EsmTOR RNAi treatment. In addition, EsRheb , a molecular marker for tissue growth, was also significantly down-regulated. This study suggests that EsmTOR plays a fundamental role in molting regulation through the SLC7A5-V-ATPase-mTORC1 gene network. [Display omitted] • mTOR of Chinese mitten crab is widely expressed in multiple tissues. • mTOR expression is elevated in Eyestalk during the Intermolt. • RNAi of mTOR leads to prolonged molt interval. • RNAi of mTOR leads to reduced expression of upstream genes, and molting-related genes. [ABSTRACT FROM AUTHOR]