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

Abstract

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 seqpac's 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.

Dietary Sugar Shifts Mitochondrial Metabolism and Small RNA Biogenesis in Sperm

“…We then analyzed transcripts based on cut-sites using the bioinformatic package Seqpac (Skog et al, 2021 ) and with information about tRNA loop structure taken from tRNAscan-SE (Lowe and Chan, 2016 ). Five sub-types of tsRNA were defined: 5′-half, 5′-tsRNA, i′-tsRNA, 3′-tsRNA, and 3′-half ( Fig.…”

“…Data analysis was performed with Seqpac ver. 0.99.0 (Skog et al, 2021 ). Adaptor trimming, quality control, and mapping were all performed in Seqpac with make_counts and make_reanno workflow with evidence that an individual sequence should have at least 1 count in 2 separate samples.…”

Small non-coding RNA in early fly development : plasticity, interactions and improved bioinformatic tools

“…Annotation to reference genomes can then be performed much quicker, and all alignments can be retained alongside the read sequences. In Paper II, we implemented this later method (Skog et al, 2023).…”

Nutritional dependence of sperm mitochondrial metabolism and small RNA biogenesis

“…We next analysed the tsRNAs in both 30-and 300 g/L sugar diets with and without NAC (Figure 4, Table S6). First, all transcripts mapping to full-length tRNAs were classified based on cut-sites using the bioinformatic package-Seqpac (Skog et al, 2021) and with information about tRNA loop structure taken from tRNAscan-SE . Five sub-types of tsRNA were defined: 5′-half, 5′-tsRNA, i'-tsRNA, 3'-tsRNA and 3′-half (Figure 4A).…”

“…Data analysis was performed with Seqpac ver. 0.99.0 (Skog et al, 2021). Adaptor trimming, quality control and mapping were all performed in Seqpac with make_counts and make_reanno workflow with an evidence of that an individual sequence should have at least 1 count in 2 separate samples.…”