Balancing read length and sequencing depth: Optimizing Nanopore long-read sequencing for monocots with an emphasis on the Liliales

PREMISE

We present approaches used to generate long-read Nanopore sequencing reads for the Liliales and demonstrate how modifications to standard protocols directly impact read length and total output. The goal is to help those interested in generating long-read sequencing data determine which steps may be necessary for optimizing output and results.

METHODS

Four species of Calochortus (Liliaceae) were sequenced. Modifications made to sodium dodecyl sulfate (SDS) extractions and cleanup protocols included grinding with a mortar and pestle, using cut or wide-bore tips, chloroform cleaning, bead cleaning, eliminating short fragments, and using highly purified DNA.

RESULTS

Steps taken to maximize read length can decrease overall output. Notably, the number of pores in a flow cell is correlated with the overall output, yet we did not see an association between the pore number and the read length or the number of reads produced.

DISCUSSION

Many factors contribute to the overall success of a Nanopore sequencing run. We showed the direct impact that several modifications to the DNA extraction and cleaning steps have on the total sequencing output, read size, and number of reads generated. We show a tradeoff between read length and the number of reads and, to a lesser extent, the total sequencing output, all of which are important factors for successful de novo genome assembly.

Corrigendum: The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies

[This corrects the article DOI: 10.3389/fimmu.2022.1093242.].

The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies

Introduction

Over the last decade, the field of systems vaccinology has emerged, in which high throughput transcriptomics and other omics assays are used to probe changes of the innate and adaptive immune system in response to vaccination. The goal of this study was to benchmark key technical and analytical parameters of RNA sequencing (RNA-seq) in the context of a multi-site, double-blind randomized vaccine clinical trial.

Methods

We collected longitudinal peripheral blood mononuclear cell (PBMC) samples from 10 subjects before and after vaccination with a live attenuated Francisella tularensis vaccine and performed RNA-Seq at two different sites using aliquots from the same sample to generate two replicate datasets (5 time points for 50 samples each). We evaluated the impact of (i) filtering lowly-expressed genes, (ii) using external RNA controls, (iii) fold change and false discovery rate (FDR) filtering, (iv) read length, and (v) sequencing depth on differential expressed genes (DEGs) concordance between replicate datasets. Using synthetic mRNA spike-ins, we developed a method for empirically establishing minimal read-count thresholds for maintaining fold change accuracy on a per-experiment basis. We defined a reference PBMC transcriptome by pooling sequence data and established the impact of sequencing depth and gene filtering on transcriptome representation. Lastly, we modeled statistical power to detect DEGs for a range of sample sizes, effect sizes, and sequencing depths.

Results and Discussion

Our results showed that (i) filtering lowly-expressed genes is recommended to improve fold-change accuracy and inter-site agreement, if possible guided by mRNA spike-ins (ii) read length did not have a major impact on DEG detection, (iii) applying fold-change cutoffs for DEG detection reduced inter-set agreement and should be used with caution, if at all, (iv) reduction in sequencing depth had a minimal impact on statistical power but reduced the identifiable fraction of the PBMC transcriptome, (v) after sample size, effect size (i.e. the magnitude of fold change) was the most important driver of statistical power to detect DEG. The results from this study provide RNA sequencing benchmarks and guidelines for planning future similar vaccine studies.