Bioinformatic sequence analysis tools for the search for new short peptide in "non-coding" sequences.

LUCIANA INES ESCOBAR; DIAMBRA, L.

Buenos Aires

Conferencia; ISCB-Latin America Conference 2016 y 7mo CA2BC; 2016

International Society for Computational Biology

New massive sequencing technologies have revealed the existence of micro-RNA (miRNA) and non-coding RNA (ncRNA), thus adding complexity to the process of regulating the expression of genomes [1]. Distinguish between functional and non-functional transcripts is a difficult exercise that slows the identification of new genes [2,3]. However, in recent years there have been discovered numerous small functional peptides encoded by small ORF (sORF), many of which were originally considered noncoding [4,5]. Since the identification of candidates for functional sORF escapes the current bioinformatics protocols, it is necessary to develop new strategies capable of identifying them. In this work we analyzed ribosomal profiles of 5'UTR regions of transcripts derived from Drosophila melanogaster genome. Peviously, we worked with data embryos [6] and detected 129 new peptides that were analyzed in terms of their functionality and phylogenetic conservation. We are currently working in the identifcation of short peptides arising from potential sORF in samples of S2 cells [7]. We evaluated the quality of alignments using Bowtie and TopHat software; mapping transcripts to a reference genome to discover RNA splice sites de novo.Short peptide sequences constitutes a significant fraction of uncharacterized gene products encoded by a genome. the Ribosome Profiling technique infer novel peptide products derived from sequences previously considered non-coding [8]. Furthermore, the use of TopHat as a spliced aligner form RNA-sequence, combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments [9]. These techniques allows us to deepen analysis in the characterization of sORFs.