Dataset Information

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings.

ABSTRACT: High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2).

SUBMITTER: Rioualen C

PROVIDER: S-EPMC5614607 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings.

Rioualen Claire C Da Costa Quentin Q Chetrit Bernard B Charafe-Jauffret Emmanuelle E Ginestier Christophe C Bidaut Ghislain G

PloS one 20170926 9

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein- ...[more]

PMID: 28949986

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Project description:Quantitative high throughput screening (qHTS) assays use cells or tissues to screen thousands of compounds in a short period of time. Data generated from qHTS assays are then evaluated using nonlinear regression models, such as the Hill model, and decisions regarding toxicity are made using the estimates of the parameters of the model. For any given compound, the variability in the observed response may either be constant across dose groups (homoscedasticity) or vary with dose (heteroscedasticity). Since thousands of compounds are simultaneously evaluated in a qHTS assay, it is not practically feasible for an investigator to perform residual analysis to determine the variance structure before performing statistical inferences on each compound. Since it is well-known that the variance structure plays an important role in the analysis of linear and nonlinear regression models it is therefore important to have practically useful and easy to interpret methodology which is robust to the variance structure. Furthermore, given the number of chemicals that are investigated in the qHTS assay, outliers and influential observations are not uncommon. In this article we describe preliminary test estimation (PTE) based methodology which is robust to the variance structure as well as any potential outliers and influential observations. Performance of the proposed methodology is evaluated in terms of false discovery rate (FDR) and power using a simulation study mimicking a real qHTS data. Of the two methods currently in use, our simulations studies suggest that one is extremely conservative with very small power in comparison to the proposed PTE based method whereas the other method is very liberal. In contrast, the proposed PTE based methodology achieves a better control of FDR while maintaining good power. The proposed methodology is illustrated using a data set obtained from the National Toxicology Program (NTP). Additional information, simulation results, data and computer code are available online as supplementary materials.

Project description:Ticks and tick-borne diseases (TBDs) represent a burden for human and animal health worldwide. Currently, vaccines constitute the safest and most effective approach to control ticks and TBDs. Subolesin (SUB) has been identified as a vaccine antigen for the control of tick infestations and pathogen infection and transmission. The characterization of the molecular function of SUB and the identification of tick proteins interacting with SUB may provide the basis for the discovery of novel antigens and for the rational design of novel anti-tick vaccines. In the present study, we used the yeast two-hybrid system (Y2H) as an unbiased approach to identify tick SUB-interacting proteins in an Ixodes ricinus cDNA library, and studied the possible role of SUB as a chromatin remodeler through direct interaction with histones. The Y2H screening identified Importin-α as a potential SUB-interacting protein, which was confirmed in vitro in a protein pull-down assay. The sub gene expression levels in tick midgut and fat body were significantly higher in unfed than fed female ticks, however, the importin-α expression levels did not vary between unfed and fed ticks but tended to be higher in the ovary when compared to those in other organs. The effect of importin-α RNAi was characterized in I. ricinus under artificial feeding conditions. Both sub and importin-α gene knockdown was observed in all tick tissues and, while tick weight was significantly lower in sub RNAi-treated ticks than in controls, importin-α RNAi did not affect tick feeding or oviposition, suggesting that SUB is able to exert its function in the absence of Importin-α. Furthermore, SUB was shown to physically interact with histone 4, which was corroborated by protein pull-down and western blot analysis. These results confirm that by interacting with numerous tick proteins, SUB is a key cofactor of the tick interactome and regulome. Further studies are needed to elucidate the nature of the SUB-Importin-α interaction and the biological processes and functional implications that this interaction may have.

Dataset Information

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings.

Publications

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings.

Similar Datasets

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