MicroRNA Target Detection and Analysis for Genes Related to Breast Cancer Using MDLcompress

Abstract

We describe initial results of miRNA sequence analysis with the optimal symbol compression ratio (OSCR) algorithm and recast this grammar inference algorithm as an improved minimum description length (MDL) learning tool: MDLcompress. We apply this tool to explore the relationship between miRNAs, single nucleotide polymorphisms (SNPs), and breast cancer. Our new algorithm outperforms other grammar-based coding methods, such as DNA Sequitur, while retaining a two-part code that highlights biologically significant phrases. The deep recursion of MDLcompress, together with its explicit two-part coding, enables it to identify biologically meaningful sequence without needlessly restrictive priors. The ability to quantify cost in bits for phrases in the MDL model allows prediction of regions where SNPs may have the most impact on biological activity. MDLcompress improves on our previous algorithm in execution time through an innovative data structure, and in specificity of motif detection (compression) through improved heuristics. An MDLcompress analysis of 144 over expressed genes from the breast cancer cell line BT474 has identified novel motifs, including potential microRNA (miRNA) binding sites that are candidates for experimental validation.

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data

“…We can claim that MDL approach has achieved the most parsimonious explanation of the data, recovering the true underlying structure [8] [12][14] [18]. In at least this case, where the sentence was contrived as an excuse to use two names trice, MDL did recover the true underlying structure.…”

“…al. have proposed a method using data compression and the MDL principle that is capable of identifying motif sequences, some of which were discovered to be miRNA target sites implicated in breast cancer [12]. Moreover, the authors showed the generality of their ideas by applying them, unmodified, to the problem of network traffic anomalies [13].…”

MicroRNAs: Potential biomarkers in cancer

“…A recent study identified a polymorphism present in the seed region of miR125a that significantly inhibited the processing of pri-miRNA to pre-miRNA, resulting in reduced miRNA-mediated translational repression. Thus, a SNP can either abolish or weaken a miRNA target, or create a perfect sequence match to the seed of a miRNA that otherwise was not associated with the given mRNA (8,24). Although miRNA seed region polymorphisms can theoretically affect the expression of hundreds of genes, this prediction will require experimental validation.…”

Genetic variants at the miR-124 binding site on the cytoskeleton-organizing IQGAP1 gene confer differential predisposition to breast cancer

“…The first miRNA-target mRNA pair to be verified in vivo was let-7 miRNA and its target, lin-41; and the natural interaction between this miRNA and its target is one of the best understood (5). miRNAs suppress gene expression mainly by binding to the complementary sequences in the 3 untranslated regions (UTRs) of mRNA of their target genes (6), although some miRNAs have been shown to act as an enhancer element to increase gene expression (7). It is generally believed that nucleotides 2-8 from the 5' end of miRNA, called the 'seed region', are the most critical for miRNA binding (8).…”