Brief. Bioinformatics - Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks.

Tópicos

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Resumo

The revolution in high-throughput sequencing technologies has enabled the acquisition of gigabytes of RNA sequences in many different conditions and has highlighted an unexpected number of small RNAs (sRNAs) in bacteria. Ongoing exploitation of these data enables numerous applications for investigating bacterial transacting sRNA-mediated regulation networks. Focusing on sRNAs that regulate mRNA translation in trans, recent works have noted several sRNA-based regulatory pathways that are essential for key cellular processes. Although the number of known bacterial sRNAs is increasing, the experimental validation of their interactions with mRNA targets remains challenging and involves expensive and time-consuming experimental strategies. Hence, bioinformatics is crucial for selecting and prioritizing candidates before designing any experimental work. However, current software for target prediction produces a prohibitive number of candidates because of the lack of biological knowledge regarding the rules governing sRNA-mRNA interactions. Therefore, there is a real need to develop new approaches to help biologists focus on the most promising predicted sRNA-mRNA interactions. In this perspective, this review aims at presenting the advantages of mixing bioinformatics and visualization approaches for analyzing predicted sRNA-mediated regulatory bacterial networks.

Resumo Limpo

revolut highthroughput sequenc technolog enabl acquisit gigabyt rna sequenc mani differ condit highlight unexpect number small rnas srnas bacteria ongo exploit data enabl numer applic investig bacteri transact srnamedi regul network focus srnas regul mrna translat tran recent work note sever srnabas regulatori pathway essenti key cellular process although number known bacteri srnas increas experiment valid interact mrna target remain challeng involv expens timeconsum experiment strategi henc bioinformat crucial select priorit candid design experiment work howev current softwar target predict produc prohibit number candid lack biolog knowledg regard rule govern srnamrna interact therefor real need develop new approach help biologist focus promis predict srnamrna interact perspect review aim present advantag mix bioinformat visual approach analyz predict srnamedi regulatori bacteri network

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