Hatzigeorgiou, A. G. | bioRxiv Science

bioRxiv2020

Cooperative action of miR-124 and ISX9 in instructing direct reprogramming of mouse astrocytes to induced-neurons in vitro and in vivo

The miRNA miR-124 has been employed supplementary to neurogenic TFs and other miRNAs to enhance direct neurogenic conversion by suppressing multiple non-neuronal targets. Aim of the study was to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced-neurons (iNs) on its own and elucidate its independent mechanism of reprogramming action. Our data show that miR-124 is a potent driver of the reprogramming switch of astrocytes towards an immature neuronal fate, by directly targeting the RNA-binding protein Zfp36l1 implicated in ARE-mediated mRNA decay and subsequently de-repressing Zfp36l1 neurogenic interactome. To this end miR-124 contribution in iNs production largely recapitulates endogenous neurogenesis pathways, being further enhanced upon addition of the neurogenic compound ISX9, which greatly improves both miR-124-induced reprogramming efficiency and iNs functional maturation. Importantly, miR-124 is potent to guide direct conversion of reactive astrocytes to immature iNs of cortical identity in vivo following cortical trauma, confirming its master reprogramming capacity within the injured cortical microenvironment, while ISX9 supplementation confers a survival advantage to newly produced iNs.

neuroscience↗

bioRxiv2019

Manatee: detection and quantification of small ncRNAs from next-generation sequencing data

Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq data analysis proved to be challenging due to non-unique genomic origin, short length and abundant post-transcriptional modifications of sRNA species. Here we present Manatee, an algorithm for quantification of sRNA classes and detection of uncharacterized expressed non-coding loci. Manatee adopts a novel approach for abundance estimation of genomic reads that combines sRNA annotation with reliable alignment density information and extensive reads salvation. Comparison of Manatee against state-of-the-art implementations using real/simulated data sets demonstrates its superior accuracy in quantification of diverse sRNA classes providing at the same time insights about unannotated expressed loci. It is user-friendly, easily embeddable in pipelines and provides a simplified output suitable for direct usage in downstream analyses and functional studies.

bioinformatics↗