CISREGLOGIC

Identifying and understanding the cis-regulatory modules that control the spatio-temporal transcription of genes in chordates

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 Obiettivo del progetto (Objective)

'A major challenge in deciphering the genome is to understand the genomic sequences which control the spatio-temporal expression of genes. Despite much progress, the rules by which these regions, the cis-regulatory modules (CRMs), control the transcription of a gene remain unclear. The objectives of this proposal are to develop an algorithm to detect novel CRMs, to analyze the identified CRMs, and to elucidate the logic by which CRMs control when a gene is transcribed and in what cells. This will be done by first developing an algorithm that integrates several recent breakthroughs in understanding CRM mechanisms and using a mid-throughput chordate model organism (Ciona intestinalis) for validation. Recent work has shown that many factors contribute to CRM activation in addition to the well-known clustering of transcription factor binding sites: the openness of the chromatin, 3D structure of the DNA, nucleosome positioning, and co-factor binding. Combining this understanding with previous prediction methods (evolutionary sequence conservation, binding-site clustering) will improve predictive power, which I will experimentally confirm. The CRMs will be refined to their essential sequences by comparing them to their orthologs in distant species that drive similar expression patterns. The identified CRMs will be used in a second step to analyze and classify the CRMs. Finally, combining the identified CRMs with known patterns of expression will provide a means to elucidate the rules by which CRMs operate. This work will impact fundamental biology and also contribute to identifying and understanding mutations with disease implications, as SNPs within a CRM have been shown to have effects in genetic diseases, such as cancer.'

Introduzione (Teaser)

The importance of the impact of the activation of genes at specific times and certain places in the genome is critical in disease development. A thorough examination of genomic and epigenomic data has revealed some interesting facts.

Descrizione progetto (Article)

In the tussle between gene expression or not, transcription factors (TFs) are key. Binding to specific regions of DNA, they control the transcription of genetic information from DNA to RNA. TFs use non-coding DNA docking stations called cis-regulatory modules (CRMs) to kick off the gene expression regulation levels.

One problem when working with CRMs is that they tend to vary in sequence composition. Although this doesn't affect their role in the cell, it interferes with identification of CRM sequences. Deciphering these codes will enable identification of new drug targets to modulate DNA expression.

The CISREGLOGIC project developed computational tools to identify orthologous CRMs, that is sequences derived from a common ancestor. An ingenious method weeded out the desired sequences.

Two distant relatives of the sea squirt class were subject to phylogenetic footprinting. These species were far enough apart to identify CRMs on the basis of non-coding alignment. Software then identified candidate CRMs for certain genes in each species and their approximate position in the genome.

To identify the TF binding sites, a new affinity scoring system was used. The researchers also devised a method to eliminate those binding sites that registered less than significant TF binding. Tools identified pairs of CRMs that could be considered orthologous.

The researchers showed that clusters of similar binding sites are shared between the two species in the area of early regulatory genes. Furthermore, clusters of similar binding sites are associated with genes of similar function.

Genomic data from the CISREGLOGIC project has provided a strong knowledge base for further research. Translation of the results into pharmaceutical products may lead to modulation of gene expression regulation that predisposes to a range of diseases.