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Detection of long non-coding RNA homology, a comparative study on alignment and alignment-free metrics.

A new interesting article has been published in BMC Bioinformatics. 2018 Nov 6;19(1):407. doi: 10.1186/s12859-018-2441-6. and titled:

Detection of long non-coding RNA homology, a comparative study on alignment and alignment-free metrics.

Authors of this article are:

Noviello TMR, Di Liddo A, Ventola GM, Spagnuolo A, D’Aniello S, Ceccarelli M, Cerulo L.

A summary of the article is shown below:

BACKGROUND: Long non-coding RNAs (lncRNAs) represent a novel class of non-coding RNAs having a crucial role in many biological processes. The identification of long non-coding homologs among different species is essential to investigate such roles in model organisms as homologous genes tend to retain similar molecular and biological functions. Alignment-based metrics are able to effectively capture the conservation of transcribed coding sequences and then the homology of protein coding genes. However, unlike protein coding genes the poor sequence conservation of long non-coding genes makes the identification of their homologs a challenging task.RESULTS: In this study we compare alignment-based and alignment-free string similarity metrics and look at promoter regions as a possible source of conserved information. We show that promoter regions encode relevant information for the conservation of long non-coding genes across species and that such information is better captured by alignment-free metrics. We perform a genome wide test of this hypothesis in human, mouse, and zebrafish.CONCLUSIONS: The obtained results persuaded us to postulate the new hypothesis that, unlike protein coding genes, long non-coding genes tend to preserve their regulatory machinery rather than their transcribed sequence. All datasets, scripts, and the prediction tools adopted in this study are available at .

Check out the article’s website on Pubmed for more information:

This article is a good source of information and a good way to become familiar with topics such as:

Homology;Long ncRNA;String similarity


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