Dataset Information

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps.

ABSTRACT:

Background

The progress in mapping RNA-protein and RNA-RNA interactions at the transcriptome-wide level paves the way to decipher possible combinatorial patterns embedded in post-transcriptional regulation of gene expression.

Results

Here we propose an innovative computational tool to extract clusters of mRNA trans-acting co-regulators (RNA binding proteins and non-coding RNAs) from pairwise interaction annotations. In addition the tool allows to analyze the binding site similarity of co-regulators belonging to the same cluster, given their positional binding information. The tool has been tested on experimental collections of human and yeast interactions, identifying modules that coordinate functionally related messages.

Conclusions

This tool is an original attempt to uncover combinatorial patterns using all the post-transcriptional interaction data available so far. PTRcombiner is available at http://disi.unitn.it/~passerini/software/PTRcombiner/.

SUBMITTER: Corrado G

PROVIDER: S-EPMC4234518 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Publications

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps.

Corrado Gianluca G Tebaldi Toma T Bertamini Giulio G Costa Fabrizio F Quattrone Alessandro A Viero Gabriella G Passerini Andrea A

BMC genomics 20140423

<h4>Background</h4>The progress in mapping RNA-protein and RNA-RNA interactions at the transcriptome-wide level paves the way to decipher possible combinatorial patterns embedded in post-transcriptional regulation of gene expression.<h4>Results</h4>Here we propose an innovative computational tool to extract clusters of mRNA trans-acting co-regulators (RNA binding proteins and non-coding RNAs) from pairwise interaction annotations. In addition the tool allows to analyze the binding site similarit ...[more]

PMID: 24758252

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Project description:Atrial fibrillation (AF) is the most common cardiac arrhythmia at the clinic. Recent GWAS identified several variants associated with AF, but they account for <10% of heritability. Gene-gene interaction is assumed to account for a significant portion of missing heritability. Among GWAS loci for AF, only three were replicated in the Chinese Han population, including SNP rs2106261 (G/A substitution) in ZFHX3, rs2200733 (C/T substitution) near PITX2c, and rs3807989 (A/G substitution) in CAV1. Thus, we analyzed the interaction among these three AF loci. We demonstrated significant interaction between rs2106261 and rs2200733 in three independent populations and combined population with 2,020 cases/5,315 controls. Compared to non-risk genotype GGCC, two-locus risk genotype AATT showed the highest odds ratio in three independent populations and the combined population (OR=5.36 (95% CI 3.87-7.43), P=8.00×10-24). The OR of 5.36 for AATT was significantly higher than the combined OR of 3.31 for both GGTT and AACC, suggesting a synergistic interaction between rs2106261 and rs2200733. Relative excess risk due to interaction (RERI) analysis also revealed significant interaction between rs2106261 and rs2200733 when exposed two copies of risk alleles (RERI=2.87, P<1.00×10-4) or exposed to one additional copy of risk allele (RERI=1.29, P<1.00×10-4). The INTERSNP program identified significant genotypic interaction between rs2106261 and rs2200733 under an additive by additive model (OR=0.85, 95% CI: 0.74-0.97, P=0.02). Mechanistically, PITX2c negatively regulates expression of miR-1, which negatively regulates expression of ZFHX3, resulting in a positive regulation of ZFHX3 by PITX2c; ZFHX3 positively regulates expression of PITX2C, resulting in a cyclic loop of cross-regulation between ZFHX3 and PITX2c. Both ZFHX3 and PITX2c regulate expression of NPPA, TBX5 and NKX2.5. These results suggest that cyclic cross-regulation of gene expression is a molecular basis for gene-gene interactions involved in genetics of complex disease traits.

Dataset Information

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps.

Background

Results

Conclusions

Publications

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps.

Similar Datasets

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