Lilit Nersisyan

KEGGParser: parsing and editing KEGG pathway maps in Matlab

SUMMARY KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab. AVAILABILITY AND IMPLEMENTATION The source code is available at http://www.mathworks.com/matlabcentral/fileexchange/37561.

Computel: Computation of Mean Telomere Length from Whole-Genome Next-Generation Sequencing Data

Telomeres are the ends of eukaryotic chromosomes, consisting of consecutive short repeats that protect chromosome ends from degradation. Telomeres shorten with each cell division, leading to replicative cell senescence. Deregulation of telomere length homeostasis is associated with the development of various age-related diseases and cancers. A number of experimental techniques exist for telomere length measurement; however, until recently, the absence of tools for extracting telomere lengths from high-throughput sequencing data has significantly obscured the association of telomere length with molecular processes in normal and diseased conditions. We have developed Computel, a program in R for computing mean telomere length from whole-genome next-generation sequencing data. Computel is open source, and is freely available at https://github.com/lilit-nersisyan/computel. It utilizes a short-read alignment-based approach and integrates various popular tools for sequencing data analysis. We validated it with synthetic and experimental data, and compared its performance with the previously available software. The results have shown that Computel outperforms existing software in accuracy, independence of results from sequencing conditions, stability against inherent sequencing errors, and better ability to distinguish pure telomeric sequences from interstitial telomeric repeats. By providing a highly reliable methodology for determining telomere lengths from whole-genome sequencing data, Computel should help to elucidate the role of telomeres in cellular health and disease.

Genomic and transcriptomic heterogeneity of colorectal tumors arising in Lynch Syndrome

Colorectal cancer (CRC) arising in Lynch syndrome (LS) comprises tumours with constitutional mutations in DNA mismatch repair genes. There is still a lack of whole‐genome and transcriptome studies of LS‐CRC to address questions about similarities and differences in mutation and gene expression characteristics between LS‐CRC and sporadic CRC, about the molecular heterogeneity of LS‐CRC, and about specific mechanisms of LS‐CRC genesis linked to dysfunctional mismatch repair in LS colonic mucosa and the possible role of immune editing. Here, we provide a first molecular characterization of LS tumours and of matched tumour‐distant reference colonic mucosa based on whole‐genome DNA‐sequencing and RNA‐sequencing analyses. Our data support two subgroups of LS‐CRCs, G1 and G2, whereby G1 tumours show a higher number of somatic mutations, a higher amount of microsatellite slippage, and a different mutation spectrum. The gene expression phenotypes support this difference. Reference mucosa of G1 shows a strong immune response associated with the expression of HLA and immune checkpoint genes and the invasion of CD4+ T cells. Such an immune response is not observed in LS tumours, G2 reference and normal (non‐Lynch) mucosa, and sporadic CRC. We hypothesize that G1 tumours are edited for escape from a highly immunogenic microenvironment via loss of HLA presentation and T‐cell exhaustion. In contrast, G2 tumours seem to develop in a less immunogenic microenvironment where tumour‐promoting inflammation parallels tumourigenesis. Larger studies on non‐neoplastic mucosa tissue of mutation carriers are required to better understand the early phases of emerging tumours. Copyright

CyKEGGParser: tailoring KEGG pathways to fit into systems biology analysis workflows.

The KEGG pathway database is a widely accepted source for biomolecular pathway maps. In this paper we present the CyKEGGParser app ( http://apps.cytoscape.org/apps/cykeggparser) for Cytoscape 3 that allows manipulation with KEGG pathway maps. Along with basic functionalities for pathway retrieval, visualization and export in KGML and BioPAX formats, the app provides unique features for computer-assisted adjustment of inconsistencies in KEGG pathway KGML files and generation of tissue- and protein-protein interaction specific pathways. We demonstrate that using biological context-specific KEGG pathways created with CyKEGGParser makes systems biology analysis more sensitive and appropriate compared to original pathways.

Epigenetic Heterogeneity of B-Cell Lymphoma: Chromatin Modifiers

We systematically studied the expression of more than fifty histone and DNA (de)methylating enzymes in lymphoma and healthy controls. As a main result, we found that the expression levels of nearly all enzymes become markedly disturbed in lymphoma, suggesting deregulation of large parts of the epigenetic machinery. We discuss the effect of DNA promoter methylation and of transcriptional activity in the context of mutated epigenetic modifiers such as EZH2 and MLL2. As another mechanism, we studied the coupling between the energy metabolism and epigenetics via metabolites that act as cofactors of JmjC-type demethylases. Our study results suggest that Burkitts lymphoma and diffuse large B-cell Lymphoma differ by an imbalance of repressive and poised promoters, which is governed predominantly by the activity of methyltransferases and the underrepresentation of demethylases in this regulation. The data further suggest that coupling of epigenetics with the energy metabolism can also be an important factor in lymphomagenesis in the absence of direct mutations of genes in metabolic pathways. Understanding of epigenetic deregulation in lymphoma and possibly in cancers in general must go beyond simple schemes using only a few modes of regulation.

PSFC: a Pathway Signal Flow Calculator App for Cytoscape

Cell signaling pathways are sequences of biochemical reactions that propagate an input signal, such as a hormone binding to a cell-surface receptor, into the cell to trigger a reactive process. Assessment of pathway activities is crucial for determining which pathways play roles in disease versus normal conditions. To date various pathway flow/perturbation assessment tools are available, however they are constrained to specific algorithms and specific data types. There are no accepted standards for evaluation of pathway activities or simulation of flow propagation events in pathways, and the results of different software are difficult to compare. Here we present Pathway Signal Flow Calculator (PSFC), a Cytoscape app for calculation of a pathway signal flow based on the pathway topology and node input data. The app provides a rich framework for customization of different signal flow algorithms to allow users to apply various approaches within a single computational framework.

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles

Introduction Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms. Methods Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies. Results and conclusions The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

Cartography of Pathway Signal Perturbations Identifies Distinct Molecular Pathomechanisms in Malignant and Chronic Lung Diseases

Lung diseases are described by a wide variety of developmental mechanisms and clinical manifestations. Accurate classification and diagnosis of lung diseases are the bases for development of effective treatments. While extensive studies are conducted toward characterization of various lung diseases at molecular level, no systematic approach has been developed so far. Here we have applied a methodology for pathway-centered mining of high throughput gene expression data to describe a wide range of lung diseases in the light of shared and specific pathway activity profiles. We have applied an algorithm combining a Pathway Signal Flow (PSF) algorithm for estimation of pathway activity deregulation states in lung diseases and malignancies, and a Self Organizing Maps algorithm for classification and clustering of the pathway activity profiles. The analysis results allowed clearly distinguish between cancer and non-cancer lung diseases. Lung cancers were characterized by pathways implicated in cell proliferation, metabolism, while non-malignant lung diseases were characterized by deregulations in pathways involved in immune/inflammatory response and fibrotic tissue remodeling. In contrast to lung malignancies, chronic lung diseases had relatively heterogeneous pathway deregulation profiles. We identified three groups of interstitial lung diseases and showed that the development of characteristic pathological processes, such as fibrosis, can be initiated by deregulations in different signaling pathways. In conclusion, this paper describes the pathobiology of lung diseases from systems viewpoint using pathway centered high-dimensional data mining approach. Our results contribute largely to current understanding of pathological events in lung cancers and non-malignant lung diseases. Moreover, this paper provides new insight into molecular mechanisms of a number of interstitial lung diseases that have been studied to a lesser extent.

Application of MATLAB in -Omics and Systems Biology

Biological data analysis has dramatically changed since the introduction of highthroughput -omics technologies, such as microarrays and next-generation sequencing. The key advantage of obtaining thousands of measurements from a single sample soon became a bottleneck limiting transformation of generated data into knowledge. It has become apparent that traditional statistical approaches are not suited to solve problems in the new reality of “big biological data.” From the other side, traditional computing languages such as C/C++ and Java, are not flexible enough to allow for quick develop‐ ment and testing of new algorithms, while MATLAB provides a powerful computing environment and a variety of sophisticated toolboxes for performing complex bioinfor‐ matics calculations. We have used MATLAB to develop the pathway signal flow (PSF) algorithm for assessment of pathway activity changes based on high-throughput gene expression and pathway topologies. Additionally, we have created a KEGGParser tool for parsing, editing, and visualizing Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway maps. We have used these tools to obtain a collection of KEGG pathways and evaluate their activity changes in different clinical forms of pulmonary sarcoidosis (PS). The application of PSF provided an extended systems view on pathway deregulation states and implicated several new pathways in sarcoidosis that had not been identified using other analysis approaches.

Quantitative trait association study for mean telomere length in the South Asian genomes

MOTIVATION Mean telomere length (MTL) is associated with cancers and age-related diseases, which necessitates identification of genomic and environmental factors that impact telomere length dynamics. Here, we present a pilot genome wide association (GWA) study for MTL in South Asian population using publicly available next generation whole genome sequences (WGS), both for MTL and genotype calculations. RESULTS MTL in the studied population was not correlated with age, which is in accordance with previous reports. Further, we identified that individuals with Sikh religion had longer telomeres, which may be the result of complex interaction between genetic background and environmental factors. Finally, we identified 51 MTL-associated SNPs residing in five loci. The top ones were located in ADARB2 gene, which has previously been implicated with extreme old age. CONCLUSION Our results show that WGS data can be used in telomere length studies. In addition, we introduce novel loci implicated in MTL that may be worth considering in further telomere studies. CONTACT aarakelyan@sci.am SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.