Identifying suitable tools for variant detection and differential gene expression using RNA-seq data

DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes

Although transcriptomics data is typically used to analyze mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g. healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, ie reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions. Here, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, vs. state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data. DifferentialRegulation is distributed as a Bioconductor R package.

DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes

Motivation

Although transcriptomics data is typically used to analyse mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g., healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, i.e., reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions.

Results

Here, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, versus state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data.

Availability and implementation

DifferentialRegulation is distributed as a Bioconductor R package.

Reversal of malignant ADAR1 splice isoform switching with Rebecsinib

Adenosine deaminase acting on RNA1 (ADAR1) preserves genomic integrity by preventing retroviral integration and retrotransposition during stress responses. However, inflammatory-microenvironment-induced ADAR1p110 to p150 splice isoform switching drives cancer stem cell (CSC) generation and therapeutic resistance in 20 malignancies. Previously, predicting and preventing ADAR1p150-mediated malignant RNA editing represented a significant challenge. Thus, we developed lentiviral ADAR1 and splicing reporters for non-invasive detection of splicing-mediated ADAR1 adenosine-to-inosine (A-to-I) RNA editing activation; a quantitative ADAR1p150 intracellular flow cytometric assay; a selective small-molecule inhibitor of splicing-mediated ADAR1 activation, Rebecsinib, which inhibits leukemia stem cell (LSC) self-renewal and prolongs humanized LSC mouse model survival at doses that spare normal hematopoietic stem and progenitor cells (HSPCs); and pre-IND studies showing favorable Rebecsinib toxicokinetic and pharmacodynamic (TK/PD) properties. Together, these results lay the foundation for developing Rebecsinib as a clinical ADAR1p150 antagonist aimed at obviating malignant microenvironment-driven LSC generation.

lncRNA-TCONS_00008552 expression in patients with pulmonary arterial hypertension due to congenital heart disease

Long noncoding RNAs (lncRNAs) are potential regulators of a variety of cardiovascular diseases. Therefore, there is a series of differentially expressed lncRNAs in pulmonary arterial hypertension (PAH) that may be used as markers to diagnose PAH and even predict the prognosis. However, their specific mechanisms remain largely unknown. Therefore, we investigated the biological role of lncRNAs in patients with PAH. First, we screened patients with PAH secondary to ventricular septal defect (VSD) and those with VSD without PAH to assess differences in lncRNA and mRNA expression between the two groups. Our results revealed the significant upregulation of 813 lncRNAs and 527 mRNAs and significant downregulation of 541 lncRNAs and 268 mRNAs in patients with PAH. Then, we identified 10 hub genes in a constructed protein-protein interaction network. Next, we performed bioinformatics analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis and subsequently constructed coding-noncoding co-expression networks. We screened lncRNA-TCONS_00008552 and lncRNA-ENST00000433673 as candidate genes and verified the expression levels of the lncRNAs using quantitative reverse-transcription PCR. Although expression levels of lncRNA-TCONS_00008552 in the plasma from the PAH groups were significantly increased compared with the control groups, there was no significant difference in the expression of lncRNA-ENST00000433673 between the two groups. This study bolsters our understanding of the role of lncRNA in PAH occurrence and development and indicates that lncRNA-TCONS_00008552 is a novel potential molecular marker for PAH.

A method for simultaneous detection of small and long RNA biotypes by ribodepleted RNA-Seq

RNA sequencing offers unprecedented access to the transcriptome. Key to this is the identification and quantification of many different species of RNA from the same sample at the same time. In this study we describe a novel protocol for simultaneous detection of coding and non-coding transcripts using modifications to the Ion Total RNA-Seq kit v2 protocol, with integration of QIASeq FastSelect rRNA removal kit. We report highly consistent sequencing libraries can be produced from both frozen high integrity mouse hippocampal tissue and the more challenging post-mortem human tissue. Removal of rRNA using FastSelect was extremely efficient, resulting in less than 1.5% rRNA content in the final library. We identified > 30,000 unique transcripts from all samples, including protein-coding genes and many species of non-coding RNA, in biologically-relevant proportions. Furthermore, the normalized sequencing read count for select genes significantly negatively correlated with Ct values from qRT-PCR analysis from the same samples. These results indicate that this protocol accurately and consistently identifies and quantifies a wide variety of transcripts simultaneously. The highly efficient rRNA depletion, coupled with minimized sample handling and without complicated and high-loss size selection protocols, makes this protocol useful to researchers wishing to investigate whole transcriptomes.

Handling multi-mapped reads in RNA-seq

Many eukaryotic genomes harbour large numbers of duplicated sequences, of diverse biotypes, resulting from several mechanisms including recombination, whole genome duplication and retro-transposition. Such repeated sequences complicate gene/transcript quantification during RNA-seq analysis due to reads mapping to more than one locus, sometimes involving genes embedded in other genes. Genes of different biotypes have dissimilar levels of sequence duplication, with long-noncoding RNAs and messenger RNAs sharing less sequence similarity to other genes than biotypes encoding shorter RNAs. Many strategies have been elaborated to handle these multi-mapped reads, resulting in increased accuracy in gene/transcript quantification, although separate tools are typically used to estimate the abundance of short and long genes due to their dissimilar characteristics. This review discusses the mechanisms leading to sequence duplication, the biotypes affected, the computational strategies employed to deal with multi-mapped reads and the challenges that still remain to be overcome.