Identifying differential features between conditions is a popular approach to understanding molecular features and their mechanisms underlying a biological process of particular interest. Although ...many tests for identifying differential expression of gene or gene sets have been proposed, there was limited success in developing methods for differential interactions of genes between conditions because of its computational complexity. We present a method for Evaluation of Dependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set of genes between two conditions. Unlike previous methods focused on differential expression of individual genes or correlation changes of individual gene-gene interactions, EDDY compares two conditions by evaluating the probability distributions of dependency networks from genes. The method has been evaluated and compared with other methods through simulation studies, and application to glioblastoma multiforme data resulted in informative cancer and glioblastoma multiforme subtype-related findings. The comparison with Gene Set Enrichment Analysis, a differential expression-based method, revealed that EDDY identifies the gene sets that are complementary to those identified by Gene Set Enrichment Analysis. EDDY also showed much lower false positives than Gene Set Co-expression Analysis, a method based on correlation changes of individual gene-gene interactions, thus providing more informative results. The Java implementation of the algorithm is freely available to noncommercial users. Download from: http://biocomputing.tgen.org/software/EDDY.
There has been a growing interest in using next-generation sequencing (NGS) to profile extracellular small RNAs from the blood and cerebrospinal fluid (CSF) of patients with neurological diseases, ...CNS tumors, or traumatic brain injury for biomarker discovery. Small sample volumes and samples with low RNA abundance create challenges for downstream small RNA sequencing assays. Plasma, serum, and CSF contain low amounts of total RNA, of which small RNAs make up a fraction. The purpose of this study was to maximize RNA isolation from RNA-limited samples and apply these methods to profile the miRNA in human CSF by small RNA deep sequencing. We systematically tested RNA isolation efficiency using ten commercially available kits and compared their performance on human plasma samples. We used RiboGreen to quantify total RNA yield and custom TaqMan assays to determine the efficiency of small RNA isolation for each of the kits. We significantly increased the recovery of small RNA by repeating the aqueous extraction during the phenol-chloroform purification in the top performing kits. We subsequently used the methods with the highest small RNA yield to purify RNA from CSF and serum samples from the same individual. We then prepared small RNA sequencing libraries using Illumina's TruSeq sample preparation kit and sequenced the samples on the HiSeq 2000. Not surprisingly, we found that the miRNA expression profile of CSF is substantially different from that of serum. To our knowledge, this is the first time that the small RNA fraction from CSF has been profiled using next-generation sequencing.
Motivation: Our goal is to construct a model for genetic regulatory networks such that the model class: (i) incorporates rule-based dependencies between genes; (ii) allows the systematic study of ...global network dynamics; (iii) is able to cope with uncertainty, both in the data and the model selection; and (iv) permits the quantification of the relative influence and sensitivity of genes in their interactions with other genes. Results: We introduce Probabilistic Boolean Networks (PBN) that share the appealing rule-based properties of Boolean networks, but are robust in the face of uncertainty. We show how the dynamics of these networks can be studied in the probabilistic context of Markov chains, with standard Boolean networks being special cases. Then, we discuss the relationship between PBNs and Bayesian networks—a family of graphical models that explicitly represent probabilistic relationships between variables. We show how probabilistic dependencies between a gene and its parent genes, constituting the basic building blocks of Bayesian networks, can be obtained from PBNs. Finally, we present methods for quantifying the influence of genes on other genes, within the context of PBNs. Examples illustrating the above concepts are presented throughout the paper. Contact: is@ieee.org
The dynamic regulation of endothelial pathophenotypes in pulmonary hypertension (PH) remains undefined. Cellular senescence is linked to PH with intracardiac shunts; however, its regulation across PH ...subtypes is unknown. Since endothelial deficiency of iron-sulfur (Fe-S) clusters is pathogenic in PH, we hypothesized that a Fe-S biogenesis protein, frataxin (FXN), controls endothelial senescence. An endothelial subpopulation in rodent and patient lungs across PH subtypes exhibited reduced FXN and elevated senescence. In vitro, hypoxic and inflammatory FXN deficiency abrogated activity of endothelial Fe-S-containing polymerases, promoting replication stress, DNA damage response, and senescence. This was also observed in stem cell-derived endothelial cells from Friedreich's ataxia (FRDA), a genetic disease of FXN deficiency, ataxia, and cardiomyopathy, often with PH. In vivo, FXN deficiency-dependent senescence drove vessel inflammation, remodeling, and PH, whereas pharmacologic removal of senescent cells in Fxn-deficient rodents ameliorated PH. These data offer a model of endothelial biology in PH, where FXN deficiency generates a senescent endothelial subpopulation, promoting vascular inflammatory and proliferative signals in other cells to drive disease. These findings also establish an endothelial etiology for PH in FRDA and left heart disease and support therapeutic development of senolytic drugs, reversing effects of Fe-S deficiency across PH subtypes.
Tricalcium oxy silicate (C
3
S) and dicalcium silicate (C
2
S) are the major constituents of cement. In this study, the reactivity of polymorphs of calcium silicates is quantitatively investigated ...using Density Functional Theory. The result of combining the DFT calculation and the Bader charge analysis elucidates that the main difference in reactivity between C
3
S and C
2
S is the presence of oxy ions in C
3
S which has smaller partial charge compared to that of other oxygen in the crystals. For the C
3
S, the reactivity of among different C
3
S polymorphs is decisively affected by the Bader charge of oxy ions. In contrast, total internal energy of C
2
S determines the quantitative chemical reactivity of C
2
S polymorphs. This result suggests that oxy ion has more dominant impact on the thermodynamic stability of calcium silicates. Furthermore, total energy can be used to estimate the chemical reactivity of calcium silicates, where there is no oxy ion exists.
Genomic analysis of drug response can provide unique insights into therapies that can be used to match the "right drug to the right patient." However, the process of discovering such therapeutic ...insights using genomic data is not straightforward and represents an area of active investigation. EDDY (Evaluation of Differential DependencY), a statistical test to detect differential statistical dependencies, is one method that leverages genomic data to identify differential genetic dependencies. EDDY has been used in conjunction with the Cancer Therapeutics Response Portal (CTRP), a dataset with drug-response measurements for more than 400 small molecules, and RNAseq data of cell lines in the Cancer Cell Line Encyclopedia (CCLE) to find potential drug-mediator pairs. Mediators were identified as genes that showed significant change in genetic statistical dependencies within annotated pathways between drug sensitive and drug non-sensitive cell lines, and the results are presented as a public web-portal (EDDY-CTRP). However, the interpretability of drug-mediator pairs currently hinders further exploration of these potentially valuable results.
In this study, we address this challenge by constructing evidence networks built with protein and drug interactions from the STITCH and STRING interaction databases. STITCH and STRING are sister databases that catalog known and predicted drug-protein interactions and protein-protein interactions, respectively. Using these two databases, we have developed a method to construct evidence networks to "explain" the relation between a drug and a mediator. RESULTS: We applied this approach to drug-mediator relations discovered in EDDY-CTRP analysis and identified evidence networks for ~70% of drug-mediator pairs where most mediators were not known direct targets for the drug. Constructed evidence networks enable researchers to contextualize the drug-mediator pair with current research and knowledge. Using evidence networks, we were able to improve the interpretability of the EDDY-CTRP results by linking the drugs and mediators with genes associated with both the drug and the mediator.
We anticipate that these evidence networks will help inform EDDY-CTRP results and enhance the generation of important insights to drug sensitivity that will lead to improved precision medicine applications.
Mechanical properties of synthesized sodium silicate mineral, Na-kanemite, was investigated by synchrotron-based high-pressure x-ray diffraction experiment and first-principles calculations. Under ...hydrostatic pressure, the 020 interlayer peak was substantially diffused while a new 011 peak formed at 0.4 GPa due to the reduction of Pbcn symmetry. Upon unloading, the diffused interlayer peak reappeared to its original position with a less peak intensity and the newly formed peak disappeared. This temporal but reversible phase instability related to the symmetry reduction, can be induced from the vibration effect of water molecules contained in interlayer region that can more significantly affect the structural response of crystals with poor crystallinity and stacking disorder. There is a good agreement of pressure response between experimental data and calculations using GGA functional. In addition, conducted analysis on bond variation revealed that contraction of thickness and distortion of Na layer under pressure which caused partial charge redistribution. Suggested elastic properties and charge data will be used to develop reliable force-field database for further molecular dynamics simulation and diagnose macroscopic impact from alkali-silicate reaction damaged structure.
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•Synthesized Na-kanemite, NaHSi2O5·3(H2O) showed reversible pressure instability.•Under pressure of 0.4 GPa, a new 011 peak formed while 020 interlayer peak was diffused due to the reduction of Pbcn symmetry.•Based on the good agreement between experiment and density functional theory based calculation, reliable elastic coefficients at low pressure have been proposed.•Applied pressure was dominantly absorbed by the space between silicate and Na layer.
Hyperdiploid multiple myeloma (H-MM) is the most common form of myeloma. In this gene expression profiling study, we show that H-MM is defined by a protein biosynthesis signature that is primarily ...driven by a gene dosage mechanism as a result of trisomic chromosomes. Within H-MM, four independently validated patient clusters overexpressing nonoverlapping sets of genes that form cognate pathways/networks that have potential biological importance in multiple myeloma were identified. One prominent cluster, cluster 1, is characterized by high expression of cancer testis antigen and proliferation-associated genes. Tumors from these patients were more proliferative than tumors in other clusters (median plasma cell labeling index, 3.8; P < 0.05). Another cluster, cluster 3, is characterized by genes involved in tumor necrosis factor/nuclear factor-kappaB signaling and antiapoptosis. These patients have better response to bortezomib as compared with patients within other clusters (70% versus 29%; P = 0.02). Furthermore, for a group of patients generally thought to have better prognosis, a cluster of patients with short survival (cluster 1; median survival, 27 months) could be identified. This analysis illustrates the heterogeneity within H-MM and the importance of defining specific cytogenetic prognostic factors. Furthermore, the signatures that defined these clusters may provide a basis for tailoring treatment to individual patients.
Adrenocortical carcinomas (ACC) are a rare tumor type with a poor five-year survival rate and limited treatment options.
Understanding of the molecular pathogenesis of this disease has been aided by ...genomic analyses highlighting alterations in TP53, WNT, and IGF signaling pathways. Further elucidation is needed to reveal therapeutically actionable targets in ACC.
In this study, global DNA methylation levels were assessed by the Infinium HumanMethylation450 BeadChip Array on 18 ACC tumors and 6 normal adrenal tissues. A new, non-linear correlation approach, the discretization method, assessed the relationship between DNA methylation/gene expression across ACC tumors.
This correlation analysis revealed epigenetic regulation of genes known to modulate TP53, WNT, and IGF signaling, as well as silencing of the tumor suppressor MARCKS, previously unreported in ACC.
DNA methylation may regulate genes known to play a role in ACC pathogenesis as well as known tumor suppressors.
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