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Certain concepts concerning EPO/EPOR action modes have been challenged by in vivo studies: Bcl-x levels are elevated in maturing erythroblasts, but not in their progenitors; truncated EPOR alleles that lack a major p85/PI3K recruitment site nonetheless promote polycythemia; and Erk1 disruption unexpectedly bolsters erythropoiesis. To discover novel EPO/EPOR action routes, global transcriptome analyses presently are applied to interrogate EPO/EPOR effects on primary bone marrow-derived CFUe-like progenitors. Overall, 160 EPO/EPOR target transcripts were significantly modulated 2-to 21.8-fold. A unique set of EPO-regulated survival factors included Lyl1, Gas5, Pim3, Pim1, Bim, Trib3 and Serpina 3g. EPO/EPOR-modulated cell cycle mediators included Cdc25a, Btg3, Cyclin-d2, p27-kip1, Cyclin-g2 and CyclinB1-IP-1. EPO regulation of signal transduction factors was also interestingly complex. For example, not only Socs3 plus Socs2 but also Spred2, Spred1 and Eaf1 were EPO-induced as negative-feedback components. Socs2, plus five additional targets, further proved to comprise new EPOR/Jak2/Stat5 response genes (which are important for erythropoiesis during anemia). Among receptors, an atypical TNF-receptor Tnfr-sf13c was up-modulated >5-fold by EPO. Functionally, Tnfr-sf13c ligation proved to both promote proerythroblast survival, and substantially enhance erythroblast formation. The EPOR therefore engages a sophisticated set of transcriptome response circuits, with Tnfr-sf13c deployed as one novel positive regulator of proerythroblast formation. © 2012 Singh et al.

Mestdagh P.,Ghent University | Hartmann N.,Novartis | Baeriswyl L.,Novartis | Andreasen D.,Exiqon | And 32 more authors.
Nature Methods | Year: 2014

micrornAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. several measurement platforms have been developed to determine relative mirnA abundance in biological samples using different technologies such as small rnA sequencing, reverse transcription- quantitative PCr (rt-qPCr) and (microarray) hybridization. in this study, we systematically compared 12 commercially available platforms for analysis of micrornA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference rnA, human brain rnA and titrations thereof, human serum samples and synthetic spikes from micrornA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specifcity and concordance of differential expression. the results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative micrornA gene expression platform for particular study goals. © 2014 Nature America, Inc. All rights reserved.

Hariharan R.,Strand Life science | Janakiraman A.,Strand Life science | Nilakantan R.,Strand Life science | Singh B.,Strand Life science | And 3 more authors.
Journal of Chemical Information and Modeling | Year: 2011

Several efficient correspondence graph-based algorithms for determining the maximum common substructure (MCS) of a pair of molecules have been published in the literature. The extension of the problem to three or more molecules is however nontrivial; heuristics used to increase the efficiency in the two-molecule case are either inapplicable to the many-molecule case or do not provide significant speedups.Our specific algorithmic contribution is two-fold. First, we show how the correspondence graph approach for the two-molecule case can be generalized to obtain an algorithm that is guaranteed to find the optimum connected MCS of multiple molecules, and that runs fast on most families of molecules using a new divide-and-conquer strategy that has hitherto not been reported in this context. Second, we provide a characterization of those compound families for which the algorithm might run slowly, along with a heuristic for speeding up computations on these families. We also extend the above algorithm to a heuristic algorithm to find the disconnected MCS of multiple molecules and to an algorithm for clustering molecules into groups, with each group sharing a substantial MCS. Our methods are flexible in that they provide exquisite control on various matching criteria used to define a common substructure. © 2011 American Chemical Society.

Fung W.S.,University of Waterloo | Hariharan R.,Strand Life science | Harvey N.J.A.,University of Waterloo | Panigrahi D.,Massachusetts Institute of Technology
Proceedings of the Annual ACM Symposium on Theory of Computing | Year: 2011

We present a general framework for constructing cut sparsifiers in undirected graphs - weighted subgraphs for which every cut has the same weight as the original graph, up to a multiplicative factor of (1 ± ε). Using this framework, we simplify, unify and improve upon previous sparsification results. As simple instantiations of this framework, we show that sparsifiers can be constructed by sampling edges according to their strength (a result of Benczur and Karger), effective resistance (a result of Spielman and Srivastava), edge connectivity, or by sampling random spanning trees. Sampling according to edge connectivity is the most aggressive method, and the most challenging to analyze. Our proof that this method produces sparsifiers resolves an open question of Benczur and Karger. While the above results are interesting from a combinatorial standpoint, we also prove new algorithmic results. In particular, we develop techniques that give the first (optimal) O(m)-time sparsification algorithm for unweighted graphs. Our algorithm has a running time of O(m) + Õ(n/ε2) for weighted graphs, which is also linear unless the input graph is very sparse itself. In both cases, this improves upon the previous best running times (due to Benczur and Karger) of O(m log2 n) (for the unweighted case) and O(m log3 n) (for the weighted case) respectively. Our algorithm constructs sparsifiers that contain O(n log n/ε2) edges in expectation; the only known construction of sparsifiers with fewer edges is by a substantially slower algorithm running in O(n3 m / ε2) time. A key ingredient of our proofs is a natural generalization of Karger's bound on the number of small cuts in an undirected graph. Given the numerous applications of Karger's bound, we suspect that our generalization will also be of independent interest. © 2011 ACM.

Sosa M.X.,McKusick Nathans Institute of Genetic Medicine | Sivakumar I.K.A.,McKusick Nathans Institute of Genetic Medicine | Sivakumar I.K.A.,Johns Hopkins University | Maragh S.,McKusick Nathans Institute of Genetic Medicine | And 12 more authors.
PLoS Computational Biology | Year: 2012

We describe methods for rapid sequencing of the entire human mitochondrial genome (mtgenome), which involve long-range PCR for specific amplification of the mtgenome, pyrosequencing, quantitative mapping of sequence reads to identify sequence variants and heteroplasmy, as well as de novo sequence assembly. These methods have been used to study 40 publicly available HapMap samples of European (CEU) and African (YRI) ancestry to demonstrate a sequencing error rate <5.63×10-4, nucleotide diversity of 1.6×10-3 for CEU and 3.7×10-3 for YRI, patterns of sequence variation consistent with earlier studies, but a higher rate of heteroplasmy varying between 10% and 50%. These results demonstrate that next-generation sequencing technologies allow interrogation of the mitochondrial genome in greater depth than previously possible which may be of value in biology and medicine.

PubMed | IRD Montpellier, French Institute of Pondicherry and Strand Life science
Type: | Journal: Biodiversity data journal | Year: 2016

This paper describes a growing biodiversity platform, launched in 2008, which organizes knowledge on the biodiversity of India. The main objective and originality of the India Biodiversity Portal (IBP) is to aggregate curated biodiversity data of different kinds (e.g. distribution maps, temporal distribution or life history) in an integrated platform where amateurs and experts can easily interact.Since its launch, the platform has seen an exceptional increase in both user activity and biodiversity data. Currently the portal has descriptions of over 20,400 species, and has aggregated approximately 1,280,000 observations covering more than 30,000 species, which already constitutes a unique source of information for scientists and stakeholders in conservation. Over 8500 users have registered on the portal. The amount of data generated and to be generated in the next few years by this portal will certainly help the effective implementation of biodiversity conservation and management in one of the most ecologically diverse countries in the world.

PubMed | Health Integrated, Mazumdar Shaw Medical Center, Roswell Park Cancer Institute, Vellore Institute of Technology and Strand Life science
Type: Journal Article | Journal: PloS one | Year: 2016

The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment nave (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.

PubMed | Amity University, Sir Ganga Ram Hospital and Strand Life science
Type: Journal Article | Journal: Medical oncology (Northwood, London, England) | Year: 2016

Mutation frequencies of common genetic alterations in colorectal cancer have been in the spotlight for many years. This study highlights few rare somatic mutations, which possess the attributes of a potential CRC biomarker yet are often neglected. Next-generation sequencing was performed over 112 tumor samples to detect genetic alterations in 31 rare genes in colorectal cancer. Mutations were detected in 26/31 (83.9%) uncommon genes, which together contributed toward 149 gene mutations in 67/112 (59.8%) colorectal cancer patients. The most frequent mutations include KDR (19.6%), PTEN (17%), FBXW7 (10.7%), SMAD4 (10.7%), VHL (8%), KIT (8%), MET (7.1%), ATM (6.3%), CTNNB1 (4.5%) and CDKN2A (4.5%). RB1, ERBB4 and ERBB2 mutations were persistent in 3.6% patients. GNAS, FGFR2 and FGFR3 mutations were persistent in 1.8% patients. Ten genes (EGFR, NOTCH1, SMARCB1, ABL1, STK11, SMO, RET, GNAQ, CSF1R and FLT3) were found mutated in 0.9% patients. Lastly, no mutations were observed in AKT, HRAS, MAP2K1, PDGFR and JAK2. Significant associations were observed between VHL with tumor site, ERBB4 and SMARCB1 with tumor invasion, CTNNB1 with lack of lymph node involvement and CTNNB1, FGFR2 and FGFR3 with TNM stage. Significantly coinciding mutation pairs include PTEN and SMAD4, PTEN and KDR, EGFR and RET, EGFR and RB1, FBXW7 and CTNNB1, KDR and FGFR2, FLT3 and CTNNB1, RET and RB1, ATM and SMAD4, ATM and CDKN2A, ERBB4 and SMARCB1. This study elucidates few potential colorectal cancer biomarkers, specifically KDR, PTEN, FBXW7 and SMAD4, which are found mutated in more than 10% patients.

PubMed | Institute of Bioinformatics and Applied Biotechnology, Mazumdar Shaw Medical Center, Mazumdar Shaw Center for Translational Research, Institute of Bioinformatics and Strand Life science
Type: | Journal: Proteomics. Clinical applications | Year: 2016

Sample processing protocols that enable compatible recovery of differentially expressed transcripts and proteins are necessary for integration of the multiomics data applied in the analysis of tumors. In this pilot study, we compared two different isolation methods for extracting RNA and protein from laryngopharyngeal tumor tissues and the corresponding adjacent normal sections. In Method 1, RNA and protein were isolated from a single tissue section sequentially and in Method 2, the extraction was carried out using two different sections and two independent and parallel protocols for RNA and protein. RNA and protein from both methods were subjected to RNA-seq and iTRAQ-based LC-MS/MS analysis, respectively. Analysis of data revealed that a higher number of differentially expressed transcripts and proteins were concordant in their regulation trends in Method 1 as compared to Method 2. Cross-method comparison of concordant entities revealed that RNA and protein extraction from the same tissue section (Method 1) recovered more concordant entities that are missed in the other extraction method (Method 2) indicating heterogeneity in distribution of these entities in different tissue sections. Method 1 could thus be the method of choice for integrated analysis of transcriptome and proteome data.

PubMed | Mazumdar Shaw Medical Center, Nizam's Institute of Medical Sciences, CSIR - Central Electrochemical Research Institute, Mazumdar Shaw Center for Translational Research and 2 more.
Type: | Journal: Scientific reports | Year: 2016

Diffuse astrocytoma (DA; WHO grade II) is a low-grade, primary brain neoplasm with high potential of recurrence as higher grade malignant form. We have analyzed differentially expressed membrane proteins from these tumors, using high-resolution mass spectrometry. A total of 2803 proteins were identified, 340 of them differentially expressed with minimum of 2 fold change and based on 2 unique peptides. Bioinformatics analysis of this dataset also revealed important molecular networks and pathways relevant to tumorigenesis, mTOR signaling pathway being a major pathway identified. Comparison of 340 differentially expressed proteins with the transcript data from Grade II diffuse astrocytomas reported earlier, revealed about 190 of the proteins correlate in their trends in expression. Considering progressive and recurrent nature of these tumors, we have mapped the differentially expressed proteins for their secretory potential, integrated the resulting list with similar list of proteins from anaplastic astrocytoma (WHO Grade III) tumors and provide a panel of proteins along with their proteotypic peptides, as a resource that would be useful for investigation as circulatory plasma markers for post-treatment surveillance of DA patients.

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