Ost, A. | bioRxiv Science

bioRxiv2021

Seqpac: A New Framework for small RNA analysis in R using Sequence-Based Counts

Small RNA sequencing (sRNA-seq) has become important for studying regulatory mechanisms in many cellular processes. Data analysis remains challenging, mainly because each class of sRNA--such as miRNA, piRNA, tRNA- and rRNA-derived fragments (tRFs/rRFs)--needs special considerations. Analysis therefore involves complex workflows across multiple programming languages, which can produce research bottlenecks and transparency issues. To make analysis of sRNA more accessible and transparent we present seqpac: a tool for advanced group-based analysis of sRNA completely integrated in R. This opens advanced sRNA analysis for Windows users--from adaptor trimming to visualization. Seqpac provides a framework of functions for analyzing a PAC object, which contains 3 standardized tables: sample phenotypic information (P), sequence annotations (A), and a counts table with unique sequences across the experiment (C). By applying a sequence-based counting strategy that maintains the integrity of the fastq sequence, seqpac increases flexibility and transparency compared to other workflows. It also contains an innovative targeting system allowing sequence counts to be summarized and visualized across sample groups and sequence classifications. Reanalyzing published data, we show that seqpacs fastq trimming performs equal to standard software outside R and demonstrate how sequence-based counting detects previously unreported bias. Applying seqpac to new experimental data, we discovered a novel rRF that was down-regulated by RNA pol I inhibition (anticancer treatment), and up-regulated in previously published data from tumor positive patients. Seqpac is available on github (https://github.com/Danis102/seqpac), runs on multiple platforms (Windows/Linux/Mac), and is provided with a step-by-step vignette on how to analyze sRNA-seq data.

bioinformatics↗

bioRxiv2020

5'XP sRNA-seq: A simple sequencing method to identify small RNA with and without 5' phosphorylation in a single library from low input samples

Small RNA (sRNA) sequencing has been critical for our understanding of many cellular processes, including gene regulation. Nonetheless, the varying biochemical properties of sRNA, such as 5 nucleotide modifications, makes many sRNA subspecies incompatible with common protocols for sRNA sequencing. Here we describe 5XP-seq that outlines a novel strategy that solves this problem. By tagging 5P sRNA during library preparation, 5XP-seq combines an open approach that includes all types of 5-terminal modifications (5X), with a selective approach for 5-phosphorylated sRNA (5P). We show that 5XP-seq not only enriches phosphorylated miRNA and piRNA but successfully discriminates these sRNA from all other sRNA species. We further demonstrate the importance of this strategy by successful inter-species validation of sRNAs that would have otherwise failed, including human to insect translation of several tRNA (tRFs) and rRNA (rRFs) fragments. By combining 5 insensitive library strategies with 5 sensitive tagging, we have solved an intrinsic bias in modern sRNA sequencing that will help us reveal the true complexity and the evolutionary significance of the sRNA world.

molecular biology↗