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Enrico Purisima

Publications and source records attributed to Enrico Purisima.

2 recordsLinked to original sources

MicroRNAs preferentially target the genes with high transcriptional regulation complexity

Over the past few years, microRNAs (miRNAs) have emerged as a new prominent class of gene regulatory factors that negatively regulate expression of approximately one-third of the genes in animal genomes at post-transcriptional level. However, it is still unclear why some genes are regulated by miRNAs but others are not, i.e. what principles govern miRNA regulation in animal genomes. In this study, we systematically analyzed the relationship between transcription factors (TFs) and miRNAs in gene regulation. We found that the genes with more TF-binding sites have a higher probability of being targeted by miRNAs and have more miRNA-binding sites on average. This observation reveals that the genes with higher cis-regulation complexity are more coordinately regulated by TFs at the transcriptional level and by miRNAs at the post-transcriptional level. This is a potentially novel discovery of mechanism for coordinated regulation of gene expression. Gene ontology analysis further demonstrated that such coordinated regulation is more popular in the developmental genes.

q-bio.GN

Self-organization of gene regulatory network motifs enriched with short transcript's half-life transcription factors

Network motifs, the recurring regulatory structural patterns in networks, are able to self-organize to produce networks. Three major motifs, feedforward loop, single input modules and bi-fan are found in gene regulatory networks. The large ratio of genes to transcription factors (TFs) in genomes leads to a sharing of TFs by motifs and is sufficient to result in network self-organization. We find a common design principle of these motifs: short transcript's half-life (THL) TFs are significantly enriched in motifs and hubs. This enrichment becomes one of the driving forces for the emergence of the network scale-free topology and allows the network to quickly adapt to environmental changes. Most feedforward loops and bi-fans contain at least one short THL TF, which can be seen as a criterion for self-assembling these motifs. We have classified the motifs according to their short THL TF content. We show that the percentage of the different motif subtypes varies in different cellular conditions.

q-bio.MN