Human 5' UTR design and variant effect prediction from a massively parallel translation assay

“Human 5’ UTR design and variant effect prediction from a massively parallel translation assay” by Paul J. Sample, Ban Wang, David W. Reid, Vlad Presnyak, Iain McFadyen, David R. Morris, and Georg Seelig. https://doi.org/10.1101/310375 I selected this article for review for two reasons: I am excited to learn about applications of massively parallel reporter assays (MPRAs). I have a general interest in methods that use deep learning (in this case convolutional neural networks) with genomic data. »

Comprehensive catalog of dendritically localized mRNA isoforms from sub4 cellular sequencing of single mouse neurons

“Comprehensive catalog of dendritically localized mRNA isoforms from sub-cellular sequencing of single mouse neurons” Sarah A. Middleton, James Eberwine and Junhyong Kim https://doi.org/10.1101/278648 I selected this article for review for the following reasons: In neurons, RNA localization is a fundamental way to control protein expression. To my knowledge this is the first attempt to map dendritically localized RNAs at single cell resolution The findings reported are very intriguing, in particular the potential role of SINE elements in localization of RNA to dendrites. »

Active degradation of a regulator controls coordination of downstream genes

“Active degradation of a regulator controls coordination of downstream genes” by Nicholas A. Rossi, Thierry Mora, Aleksandra M. Walczak, and Mary J. Dunlop https://doi.org/10.1101/272120 In this article, Rossi and colleagues observed how noise develops in the expression of genes downstream of stress response activator gene MarA by manipulating MarA degradation and expression levels and then measuring variability in downstream gene expression in single cells. As the authors note, active degradation is rare in rapidly growing bacterial cells and imposes a significant fitness cost. »

Following biOverlay via social media

We’ve gotten a number of requests from people who would like to stay up to date with biOverlay posts via social media. We now post updates to twitter and facebook pages automatically, though there may at times be some delay. Our RSS feed or our website provide the fastest way to discover new posts. If you’d like us to push new post notifications via some other media, please reach out and let us know what we can do to make biOverlay easier to follow. »

Multi-Omics factor analysis - a framework for unsupervised integration of multi-omic data sets

“Multi-Omics factor analysis - a framework for unsupervised integration of multi-omic data sets” by Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C. Marioni, Wolfgang Huber, Florian Buettner, and Oliver Stegle. https://doi.org/10.1101/217554 I selected this article for review for two reasons: Methods integrating multiple types of ‘Omics data are in great demand, both in bulk tissues and at the single-cell level. I have an interest in methods that use factor analysis to capture biological and technical sources of variation. »