Dataset Information

Deciphering transcriptional regulations coordinating the response to environmental changes.

ABSTRACT: Gene co-expression evidenced as a response to environmental changes has shown that transcriptional activity is coordinated, which pinpoints the role of transcriptional regulatory networks (TRNs). Nevertheless, the prediction of TRNs based on the affinity of transcription factors (TFs) with binding sites (BSs) generally produces an over-estimation of the observable TF/BS relations within the network and therefore many of the predicted relations are spurious.We present LOMBARDE, a bioinformatics method that extracts from a TRN determined from a set of predicted TF/BS affinities a subnetwork explaining a given set of observed co-expressions by choosing the TFs and BSs most likely to be involved in the co-regulation. LOMBARDE solves an optimization problem which selects confident paths within a given TRN that join a putative common regulator with two co-expressed genes via regulatory cascades. To evaluate the method, we used public data of Escherichia coli to produce a regulatory network that explained almost all observed co-expressions while using only 19 % of the input TF/BS affinities but including about 66 % of the independent experimentally validated regulations in the input data. When all known validated TF/BS affinities were integrated into the input data the precision of LOMBARDE increased significantly. The topological characteristics of the subnetwork that was obtained were similar to the characteristics described for known validated TRNs.LOMBARDE provides a useful modeling scheme for deciphering the regulatory mechanisms that underlie the phenotypic responses of an organism to environmental challenges. The method can become a reliable tool for further research on genome-scale transcriptional regulation studies.

SUBMITTER: Acuna V

PROVIDER: S-EPMC4715341 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deciphering transcriptional regulations coordinating the response to environmental changes.

Acuña Vicente V Aravena Andrés A Guziolowski Carito C Eveillard Damien D Siegel Anne A Maass Alejandro A

BMC bioinformatics 20160116

<h4>Background</h4>Gene co-expression evidenced as a response to environmental changes has shown that transcriptional activity is coordinated, which pinpoints the role of transcriptional regulatory networks (TRNs). Nevertheless, the prediction of TRNs based on the affinity of transcription factors (TFs) with binding sites (BSs) generally produces an over-estimation of the observable TF/BS relations within the network and therefore many of the predicted relations are spurious.<h4>Results</h4>We p ...[more]

PMID: 26772805

Similar Datasets

Project description:Sheath blight (ShB) is one of the most serious diseases in rice, leading to severe yield losses globally. In our study, we evaluated a total of 63 rice genotypes for resistance against sheath blight disease by artificial inoculation over two seasons under field conditions and studied the weather parameters associated with disease incidence. Based on two years of testing, 23 genotypes were found moderately resistant, 38 were moderately susceptible, and 2 exhibited a susceptible reaction to sheath blight disease. Among the specific four genotypes (IC283139, IC283041, IC283038, and IC283023) of the moderately resistant group exhibited less disease reaction in comparison with check variety Tetep. Further, the correlation of percent disease index (PDI) with weather parameters revealed negative associations between PDI and maximum temperature, minimum temperature, low rainfall and the positive association with maximum relative humidity (RH) suggest that very low temperature or high precipitation might have a negative impact on pathogen establishment. In addition, the sheath blight-linked SSRs were assessed using distance and model-based approaches, results of both the models revealed that genotypes distinguished the resistant population from the susceptible one. From the output of two years of principal component analysis, two genotypes from each group of moderately resistant, moderately susceptible and susceptible were studied for their biochemical reaction against the sheath blight pathogen. The biochemical study revealed that the accumulation of defense and antioxidant enzymes, namely, polyphenol oxidase, peroxidase, total phenol, phenylalanine ammonia-lyase, catalase, and superoxide dismutase, were higher in moderately resistant genotypes, but was observed to be lower in moderately susceptible and susceptible genotypes. The statistical analysis revealed the enzyme activities (defense and antioxidant) exhibited a strong negative correlation with area under the disease progress curve (AUDPC) and influence of weather parameter RH. This demonstrates that the environment factor RH plays a major role in imparting the resistance mechanism by decreasing the enzymes activities and increasing PDI. This study found that the identified novel resistant genotype (IC283139) with purple stem base demonstrated improved resistance against sheath blight infection through a defense response and the use of antioxidant machinery.

Dataset Information

Deciphering transcriptional regulations coordinating the response to environmental changes.

Publications

Deciphering transcriptional regulations coordinating the response to environmental changes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets