Tandem repeats discovery service (TReaDS) applied to finding novel cis-acting factors in repeat expansion diseases

<p>Abstract</p> <p>Background</p> <p>Tandem repeats are multiple duplications of substrings in the DNA that occur contiguously, or at a short distance, and may involve some mutations (such as substitutions, insertions, and deletions). Tandem repeats have been extensively studied also for their association with the class of repeat expansion diseases (mostly affecting the nervous system). Comparative studies on the output of different tools for finding tandem repeats highlighted significant differences among the sets of detected tandem repeats, while many authors pointed up how critical it is the right choice of parameters.</p> <p>Results</p> <p>In this paper we present <it>TReaDS - Tandem Repeats Discovery Service</it>, a <it>tandem repeat meta search engine</it>. <it>TReaDS </it>forwards user requests to several state of the art tools for finding tandem repeats and merges their outcome into a single report, providing a global, synthetic, and comparative view of the results. In particular, <it>TReaDS </it>allows the user to (<it>i</it>) simultaneously run different algorithms on the same data set, (<it>ii</it>) choose for each algorithm a different setting of parameters, and (<it>iii</it>) obtain a report that can be downloaded for further, off-line, investigations. We used <it>TReaDS </it>to investigate sequences associated with repeat expansion diseases.</p> <p>Conclusions</p> <p>By using the tool <it>TReaDS </it>we discover that, for 27 repeat expansion diseases out of a currently known set of 29, <it>long fuzzy tandem repeats </it>are covering the expansion loci. Tests with control sets confirm the specificity of this association. This finding suggests that long fuzzy tandem repeats can be a new class of cis-acting elements involved in the mechanisms leading to the expansion instability.</p> <p>We strongly believe that biologists can be interested in a tool that, not only gives them the possibility of using multiple search algorithm at the same time, with the same effort exerted in using just one of the systems, but also simplifies the burden of comparing and merging the results, thus expanding our capabilities in detecting important phenomena related to tandem repeats.</p

Bioinformatics in Italy: BITS2011, the Eighth Annual Meeting of the Italian Society of Bioinformatics

The BITS2011 meeting, held in Pisa on June 20-22, 2011, brought together more than 120 Italian researchers working in the field of Bioinformatics, as well as students in Bioinformatics, Computational Biology, Biology, Computer Sciences, and Engineering, representing a landscape of Italian bioinformatics research

Analysis Of DNA Motifs In The Human Genome

DNA motifs include repeat elements, promoter elements and gene regulator elements, and play a critical role in the human genome. This thesis describes a genome-wide computational study on two groups of motifs: tandem repeats and core promoter elements. Tandem repeats in DNA sequences are extremely relevant in biological phenomena and diagnostic tools. Computational programs that discover tandem repeats generate a huge volume of data, which can be difficult to decipher without further organization. A new method is presented here to organize and rank detected tandem repeats through clustering and classification. Our work presents multiple ways of expressing tandem repeats using the n-gram model with different clustering distance measures. Analysis of the clusters for the tandem repeats in the human genome shows that the method yields a well-defined grouping in which similarity among repeats is apparent. Our new, alignment-free method facilitates the analysis of the myriad of tandem repeats replete in the human genome. We believe that this work will lead to new discoveries on the roles, origins, and significance of tandem repeats. As with tandem repeats, promoter sequences of genes contain binding sites for proteins that play critical roles in mediating expression levels. Promoter region binding proteins and their co-factors influence timing and context of transcription. Despite the critical regulatory role of these non-coding sequences, computational methods to identify and predict DNA binding sites are extremely limited. The work reported here analyzes the relative occurrence of core promoter elements (CPEs) in and around transcription start sites. We found that out of all the data sets 49\%-63\% upstream regions have either TATA box or DPE elements. Our results suggest the possibility of predicting transcription start sites through combining CPEs signals with other promoter signals such as CpG islands and clusters of specific transcription binding sites