Abstract

BackgroundFeedback loops are the simplest building blocks of transcriptional regulatory networks and therefore their behavior in the course of evolution is of prime interest.MethodologyWe address the question of enrichment of the number of autoregulatory feedback loops in higher organisms. First, based on predicted autoregulatory binding sites we count the number of autoregulatory loops. We compare it to estimates obtained either by assuming that each (conserved) gene has the same chance to be a target of a given factor or by assuming that each conserved sequence position has an equal chance to be a binding site of the factor.ConclusionsWe demonstrate that the numbers of putative autoregulatory loops conserved between human and fugu, danio or chicken are significantly higher than expected. Moreover we show, that conserved autoregulatory binding sites cluster close to the factors' starts of transcription. We conclude, that transcriptional autoregulatory feedback loops constitute a core transcriptional network motif and their conservation has been maintained in higher vertebrate organism evolution.

Highlights

  • Network motifs are small patterns of interactions from which transcription regulation networks are built [1]

  • We demonstrate that the numbers of putative autoregulatory loops conserved between human and fugu, danio or chicken are significantly higher than expected

  • That transcriptional autoregulatory feedback loops constitute a core transcriptional network motif and their conservation has been maintained in higher vertebrate organism evolution

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Summary

Conclusions

We demonstrate that the numbers of putative autoregulatory loops conserved between human and fugu, danio or chicken are significantly higher than expected. That conserved autoregulatory binding sites cluster close to the factors’ starts of transcription. That transcriptional autoregulatory feedback loops constitute a core transcriptional network motif and their conservation has been maintained in higher vertebrate organism evolution

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