Methods to increase reproducibility in differential gene expression via meta-analysis

The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients ( network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease.

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Meta-Analysis of Parkinson's Disease Transcriptome Data Using TRAM Software: Whole Substantia Nigra Tissue and Single Dopamine Neuron Differential Gene Expression

PLoS ONE ◽

10.1371/journal.pone.0161567 ◽

2016 ◽

Vol 11 (9) ◽

pp. e0161567 ◽

Cited By ~ 27

Author(s):

Elisa Mariani ◽

Flavia Frabetti ◽

Andrea Tarozzi ◽

Maria Chiara Pelleri ◽

Fabrizio Pizzetti ◽

...

Keyword(s):

Gene Expression ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Substantia Nigra ◽

Differential Gene Expression ◽

Meta Analysis ◽

Dopamine Neuron ◽

Transcriptome Data ◽

Differential Gene

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Genomic meta-analysis of the interplay between 3D chromatin organization and gene expression programs under basal and stress conditions

10.1101/337766 ◽

2018 ◽

Author(s):

Idan Nurick ◽

Ron Shamir ◽

Ran Elkon

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Cell Lines ◽

Meta Analysis ◽

Cell Types ◽

Chromatin Organization ◽

Cell Type ◽

Differential Gene ◽

Different Cell Types

AbstractBackgroundOur appreciation of the critical role of the 3D organization of the genome in gene regulation is steadily increasing. Recent 3C-based deep sequencing techniques elucidated a hierarchy of structures that underlie the spatial organization of the genome in the nucleus. At the top of this hierarchical organization are chromosomal territories and the megabase-scale A/B compartments that correlate with transcriptional activity within cells. Below them are the relatively cell-type invariant topologically associated domains (TADs), characterized by high frequency of physical contacts between loci within the same TAD and are assumed to function as regulatory units. Within TADs, chromatin loops bring enhancers and target promoters to close spatial proximity. Yet, we still have only rudimentary understanding how differences in chromatin organization between different cell types affect cell-type specific gene expression programs that are executed under basal and challenged conditions.ResultsHere, we carried out a large-scale meta-analysis that integrated Hi-C data from thirteen different cell lines and dozens of ChIP-seq and RNA-seq datasets measured on these cells, either under basal conditions or after treatment. Pairwise comparisons between cell lines demonstrated the strong association between modulation of A/B compartmentalization, differential gene expression and transcription factor (TF) binding events. Furthermore, integrating the analysis of transcriptomes of different cell lines in response to various challenges, we show that 3D organization of cells under basal conditions constrains not only gene expression programs and TF binding profiles that are active under the basal condition but also those induced in response to treatment.ConclusionsOur results further elucidate the role of dynamic genome organization in regulation of differential gene expression between different cell types, and indicate the impact of intra-TAD enhancer-promoter interactions that are established under basal conditions on both the basal and treatment-induced gene expression programs.

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