Navigating the hydroxymethylome: experimental biases and quality control tools for the tandem bisulfite and oxidative bisulfite Illumina microarrays

Aim: Tandem bisulfite (BS) and oxidative bisulfite (oxBS) conversion on DNA followed by hybridization to Infinium HumanMethylation BeadChips allows nucleotide resolution of 5-hydroxymethylcytosine genome-wide. Here, the authors compared data quality acquired from BS-treated and oxBS-treated samples. Materials & methods: Raw BeadArray data from 417 pairs of samples across 12 independent datasets were included in the study. Probe call rates were compared between paired BS and oxBS treatments controlling for technical variables. Results: oxBS-treated samples had a significantly lower call-rate. Among technical variables, DNA-specific extraction kits performed better with higher call rates after oxBS conversion. Conclusion: The authors emphasize the importance of quality control during oxBS conversion to minimize information loss and recommend using a DNA-specific extraction kit for DNA extraction and an oxBSQC package for data preprocessing.

Systematic identification of NF90 target RNAs by iCLIP analysis

RNA-binding proteins (RBPs) interact with and determine the fate of many cellular RNAs directing numerous essential roles in cellular physiology. Nuclear Factor 90 (NF90) is an RBP encoded by the interleukin enhancer-binding factor 3 (ILF3) gene that has been found to influence RNA metabolism at several levels, including pre-RNA splicing, mRNA turnover, and translation. To systematically identify the RNAs that interact with NF90, we carried out iCLIP (individual-nucleotide resolution UV crosslinking and immunoprecipitation) analysis in the human embryonic fibroblast cell line HEK-293. Interestingly, many of the identified RNAs encoded proteins involved in the response to viral infection and RNA metabolism. We validated a subset of targets and investigated the impact of NF90 on their expression levels. Two of the top targets, IRF3 and IRF9 mRNAs, encode the proteins IRF3 and IRF9, crucial regulators of the interferon pathway involved in the SARS-CoV-2 immune response. Our results support a role for NF90 in modulating key genes implicated in the immune response and offer insight into the immunological response to the SARS-CoV-2 infection.

MethylScore, a pipeline for accurate and context-aware identification of differentially methylated regions from population-scale plant WGBS data

Whole-genome bisulfite sequencing (WGBS) is the standard method for profiling DNA methylation at single-nucleotide resolution. Many WGBS-based studies aim to identify biologically relevant loci that display differential methylation between genotypes, treatment groups, tissues, or developmental stages. Over the years, different tools have been developed to extract differentially methylated regions (DMRs) from whole-genome data. Often, such tools are built upon assumptions from mammalian data and do not consider the substantially more complex and variable nature of plant DNA methylation. Here, we present MethylScore, a pipeline to analyze WGBS data and to account for plant-specific DNA methylation properties. MethylScore processes data from genomic alignments to DMR output and is designed to be usable by novice and expert users alike. It uses an unsupervised machine learning approach to segment the genome by classification into states of high and low methylation, substantially reducing the number of necessary statistical tests while increasing the signal-to-noise ratio and the statistical power. We show how MethylScore can identify DMRs from hundreds of samples and how its data-driven approach can stratify associated samples without prior information. We identify DMRs in the A. thaliana 1001 Genomes dataset to unveil known and unknown genotype-epigenotype associations. MethylScore is an accessible pipeline for plant WGBS data, with unprecedented features for DMR calling in small- and large-scale datasets; it is built as a Nextflow pipeline and its source code is available at https://github.com/Computomics/MethylScore.

Identifying proximal RNA interactions from cDNA-encoded crosslinks with ShapeJumper

SHAPE-JuMP is a concise strategy for identifying close-in-space interactions in RNA molecules. Nucleotides in close three-dimensional proximity are crosslinked with a bi-reactive reagent that covalently links the 2’-hydroxyl groups of the ribose moieties. The identities of crosslinked nucleotides are determined using an engineered reverse transcriptase that jumps across crosslinked sites, resulting in a deletion in the cDNA that is detected using massively parallel sequencing. Here we introduce ShapeJumper, a bioinformatics pipeline to process SHAPE-JuMP sequencing data and to accurately identify through-space interactions, as observed in complex JuMP datasets. ShapeJumper identifies proximal interactions with near-nucleotide resolution using an alignment strategy that is optimized to tolerate the unique non-templated reverse-transcription profile of the engineered crosslink-traversing reverse-transcriptase. JuMP-inspired strategies are now poised to replace adapter-ligation for detecting RNA-RNA interactions in most crosslinking experiments.

iMUT-seq: high-resolution mapping of DSB mutational landscapes reveals new insights into the mutagenic mechanisms of DSB repair

DNA double-strand breaks (DSBs) are the most mutagenic form of DNA damage, and play a significant role in cancer biology, neurodegeneration and aging. However, studying DSB-induced mutagenesis is currently limited by the tools available for mapping these mutations. Here, we describe iMUT-seq, a technique that profiles DSB-induced mutations at high-sensitivity and single-nucleotide resolution around endogenous DSBs spread across the genome. By depleting 20 different DSB-repair factors we defined their mutational signatures in detail, revealing remarkable insights into the mechanisms of DSB-induced mutagenesis. We find that homologous-recombination (HR) is mutagenic in nature, displaying high levels of base substitutions and mononucleotide deletions due to DNA-polymerase errors, but simultaneously reduced translocation events, suggesting the primary role of HR is the specific suppression of genomic rearrangements. The results presented here offer new fundamental insights into DSB-induced mutagenesis and have significant implications for our understanding of cancer biology and the development of DDR-targeting chemotherapeutics.

Comprehensive determination of transcription start sites derived from all RNA polymerases using ReCappable-seq

Determination of eukaryotic Transcription Start Sites (TSS) has been based on methods that require the cap structure at the 5-prime end of transcripts derived from Pol-II RNA polymerase. Consequently, these methods do not reveal TSS derived from the other RNA polymerases which also play critical roles in various cell functions. To address this limitation, we developed ReCappable-seq which comprehensively identifies TSS for both Pol-lI and non-Pol-II transcripts at single-nucleotide resolution. The method relies on specific enzymatic exchange of 5-prime m7G caps and 5-prime triphosphates with a selectable tag. When applied to human transcriptomes, ReCappable-seq identifies Pol-II TSS that are in agreement with orthogonal methods such as CAGE. Additionally, ReCappable-seq reveals a rich landscape of TSS associated with Pol-III transcripts which have not previously been amenable to study at genome-wide scale. Novel TSS from non-Pol-II transcription can be located in the nuclear and mitochondrial genomes. ReCappable-seq interrogates the regulatory landscape of coding and noncoding RNA concurrently and enables the classification of epigenetic profiles associated with Pol-lI and non-Pol-II TSS.

A chemical method to sequence 5-formylcytosine on RNA

Epitranscriptomic RNA modifications can regulate biological processes, but there remains a major gap in our ability to identify and measure individual modifications at nucleotide resolution. Here we present Mal-Seq, a chemical method to sequence 5-formylcytosine (f5C) modifications on RNA based upon selective and efficient malononitrile-mediated labeling of f5C residues to generate adducts that are read as C-to-T mutations upon reverse transcription and PCR amplification. We apply Mal-Seq to characterize the prevalence of f5C at the wobble position of mt-tRNA(Met) in different organisms and tissue types and find that high-level f5C modification is present in mammals but lacking in lower eukaryotes. Our work sheds light on mitochondrial tRNA modifications throughout eukaryotic evolution and provides a general platform for characterizing the f5C epitranscriptome.

Quantification of alternative 3′UTR isoforms from single cell RNA-seq data with scUTRquant

Although half of human genes use alternative polyadenylation (APA) to generate mRNA isoforms that encode the same protein but differ in their 3′UTRs, most single cell RNA-sequencing (scRNA-seq) pipelines only measure gene expression. Here, we describe an open-access pipeline, called scUTRquant (https://github.com/Mayrlab/scUTRquant), that measures gene and 3′UTR isoform expression from scRNA-seq data obtained from known cell types in any species. scUTRquant-derived gene and 3′UTR transcript counts were validated against standard methods which demonstrated their accuracy. 3′UTR isoform quantification was substantially more reproducible than previous methods. scUTRquant provides an atlas of high-confidence 3′ end cleavage sites at single-nucleotide resolution to allow APA comparison across mouse datasets. Analysis of 120 mouse cell types revealed that during differentiation genes either change their expression or they change their 3′UTR isoform usage. Therefore, we identified thousands of genes with 3′UTR isoform changes that have previously not been implicated in specific biological processes.

Simultaneous identification of viruses and SARS-CoV-2 variants with programmable DNA nanobait

Respiratory infections are the major cause of death from infectious disease worldwide. The clinical presentation of many respiratory viruses is indistinguishable; therefore, diagnostic approaches that can identify multiple pathogens are essential for patient management. We aimed to address this challenge with self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid read-out via nanopore sensing. Here, we show this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from SARS-CoV-2, respiratory syncytial virus (RSV), rhinovirus, influenza, and parainfluenza. Our nanobait could be reprogrammed to discriminate viral variants, and we identified several key SARS-CoV-2 variants with single-nucleotide resolution. We increased assay specificity with bespoke nanobait that could identify numerous short RNA targets in the same viral sample in a complex background of the human transcriptome. Notably, we found that the sequence position in the viral RNA secondary structure is critical for nanobait design. Lastly, we show that nanobait could discriminate between samples extracted from oropharyngeal swabs from negative and positive SARS-CoV-2 patients using programmable target cleavage without pre-amplification. Our system allows for multiplexed identification of native RNA molecules, providing a new scalable approach for diagnostics of multiple respiratory viruses in a single assay.