Eukaryotic CSTs

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The identified CSTs are currently being analyzed in a number of projects aimed to their functional evaluation by further computational characterization and, in collaboration with other groups, to evaluate their relevance for transcriptional regulation and their role in genetically transmitted diseases. The identified CSTs are currently being analyzed in a number of projects aimed to their functional evaluation by further computational characterization and, in collaboration with other groups, to evaluate their relevance for transcriptional regulation and their role in genetically transmitted diseases.
- +For example CSTs can provide very valuable information in selecting transcriptional regulatory elements. Sequence alone is not usually believed to be sufficient to identify true binding sites for transcription factors, which are typically very small, and degenerated. However, transcription 'enhancers' and 'silencers' are often organized as clusters of binding sites for transcriptional regulatory moleculs. As a consequence, as shown by other groups (Frith et al, Rebeiz et al, Berman et al), variations in the local density of binding sites are useful in many cases to distinguish between specific and random findings. The proposed approach is to identify transcriptionally active modules searching (within CSTs) for clusters recognized by more than one factor, followed by experimental validation, in close collaboration with other units from this project.

Revision as of 19:31, 20 June 2007

Comparative genomics offers the opportunity to identify sequences characterized by strong conservation between different species, and with a putative functional role. This mainly reflects the different selective pressure on sequences carrying functional elements compared to more 'neutral' sequences, which are allowed a higher number of random mutation events.

Along this line a large number of 'conserved sequence tags' (CSTs), characterized by a variable degree of conservation in other species, were identified in the human genome, and collected in two databases (DG-CST, originally produced in a collaborative effort with a small group of italian research institutes and currently maintained at CEINGE, and KINWEB, in collaboration with ITB, Milano).

Apart from coding sequences, the identified CSTs tend to include a relatively large number of functional elements, such as structural and regulatory non coding RNAs and DNA sequence elements involved in the control of gene expression. In fact, a large number of CSTs from intronic and intergenic areas, has no feature typical of coding sequences, and their functional roles should therefore be searched out of the context of protein coding: transcriptional control, scaffold attachment, splicing control or RNA stability are a few candidate areas worth exploring in these cases.

The identified CSTs are currently being analyzed in a number of projects aimed to their functional evaluation by further computational characterization and, in collaboration with other groups, to evaluate their relevance for transcriptional regulation and their role in genetically transmitted diseases.

For example CSTs can provide very valuable information in selecting transcriptional regulatory elements. Sequence alone is not usually believed to be sufficient to identify true binding sites for transcription factors, which are typically very small, and degenerated. However, transcription 'enhancers' and 'silencers' are often organized as clusters of binding sites for transcriptional regulatory moleculs. As a consequence, as shown by other groups (Frith et al, Rebeiz et al, Berman et al), variations in the local density of binding sites are useful in many cases to distinguish between specific and random findings. The proposed approach is to identify transcriptionally active modules searching (within CSTs) for clusters recognized by more than one factor, followed by experimental validation, in close collaboration with other units from this project.





Bioinformatics: Research Activity: Eukaryotic CSTs - Bacterial RNAs - Image processing
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