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Abstract
BackgroundCurrent technologies for understanding the transcriptional reprogramming in cells include the transcription factor (TF) chromatin immunoprecipitation (ChIP) experiments and the TF knockout experiments. The ChIP experiments show the binding targets of TFs against which the antibody directs while the knockout techniques find the regulatory gene targets of the knocked-out TFs. However, it was shown that these two complementary results contain few common targets. Researchers have used the concept of TF functional redundancy to explain the low overlap between these two techniques. But the detailed molecular mechanisms behind TF functional redundancy remain unknown. Without knowing the possible molecular mechanisms, it is hard for biologists to fully unravel the cause of TF functional redundancy.ResultsTo mine out the molecular mechanisms, a novel algorithm to extract TF regulatory modules that help explain the observed TF functional redundancy effect was devised and proposed in this research. The method first searched for candidate TF sets from the TF binding data. Then based on these candidate sets the method utilized the modified Steiner Tree construction algorithm to construct the possible TF regulatory modules from protein-protein interaction data and finally filtered out the noise-induced results by using confidence tests. The mined-out regulatory modules were shown to correlate to the concept of functional redundancy and provided testable hypotheses of the molecular mechanisms behind functional redundancy. And the biological significance of the mined-out results was demonstrated in three different biological aspects: ontology enrichment, protein interaction prevalence and expression coherence. About 23.5% of the mined-out TF regulatory modules were literature-verified. Finally, the biological applicability of the proposed method was shown in one detailed example of a verified TF regulatory module for pheromone response and filamentous growth in yeast.ConclusionIn this research, a novel method that mined out the potential TF regulatory modules which elucidate the functional redundancy observed among TFs is proposed. The extracted TF regulatory modules not only correlate the molecular mechanisms to the observed functional redundancy among TFs, but also show biological significance in inferring TF functional binding target genes. The results provide testable hypotheses for biologists to further design subsequent research and experiments.
Highlights
Cells usually respond to environmental and physiological stress by reorganizing their DNA transcription programs, leading to correct spatial and temporal expression of different genes [1,2,3]
Candidate transcription factor (TF) sets that may be involved in the same modules were selected by integrating the binding data with the expression data adopted from the work of Ihmels et al, which consists of 1011 published expression experiments for different cellular conditions [21]
To reduce the effect of noises inherited from the high-throughput technologies of expression experiments and protein-protein interaction identification experiments, the Mann-Whitney U test [24] was applied to test the confidence of the extracted modules under the hypothesis that a true TF regulatory module should have statistically higher literature confidence than the literature confidence of the whole protein-protein interaction network
Summary
Cells usually respond to environmental and physiological stress by reorganizing their DNA transcription programs, leading to correct spatial and temporal expression of different genes [1,2,3]. Using the TF knockout experiments, the expression difference of genome-wide gene expression levels between the mutant-type and wildtype cell lysates generated by the knockout of certain TFs can be measured using the tiling arrays or highthroughput sequencing methods [2, 11] These TF knockout experiments can identify the direct and indirect regulatory target genes for the knocked-out TF. Since these two techniques convey different aspects for gene transcription regulation, different researches have been conducted to try to dig out the molecular mechanisms of TF regulation in gene transcription based on integrating these two experimental data and/or other different genome-wide datasets [12, 13]. Without knowing the possible molecular mechanisms, it is hard for biologists to fully unravel the cause of TF functional redundancy
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