DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics

A Deep Dive into Statistical Modeling of RNA Splicing QTLs Reveals New Variants that Explain Neurodegenerative Disease

Genome-wide association studies (GWAS) have identified thousands of putative disease causing variants with unknown regulatory effects. Efforts to connect these variants with splicing quantitative trait loci (sQTLs) have provided functional insights, yet sQTLs reported by existing methods cannot explain many GWAS signals. We show current sQTL modeling approaches can be improved by considering alternative splicing representation, model calibration, and covariate integration. We then introduce MAJIQTL, a new pipeline for sQTL discovery. MAJIQTL includes two new statistical methods: a weighted multiple testing approach for sGene discovery and a model for sQTL effect size inference to improve variant prioritization. By applying MAJIQTL to GTEx, we find significantly more sGenes harboring sQTLs with functional significance. Notably, our analysis implicates the novel variant rs582283 in Alzheimer's disease. Using antisense oligonucleotides, we validate this variant's effect by blocking the implicated YBX3 binding site, leading to exon skipping in the gene MS4A3.

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.

Cellular senescence induced by down-regulation of PTBP1 correlates with exon skipping of mitochondrial-related gene NDUFV3

As the most prevalent type of alternative splicing in animal cells, exon skipping plays an important role in expanding the diversity of transcriptome and proteome, thereby participating in the regulation of diverse physiological and pathological processes such as development, aging, and cancer. Cellular senescence serving as an anti-cancer mechanism could also contribute to individual aging. Although the dynamic changes of exon skipping during cellular senescence were revealed, its biological consequence and upstream regulator remain poorly understood. Here, by using human foreskin fibroblasts (HFF) replicative senescence as a model, we discovered that splicing factor PTBP1 was an important contributor for global exon skipping events during senescence. Down-regulated expression of PTBP1 induced senescence-associated phenotypes and related mitochondrial functional changes. Mechanistically, PTBP1 binds to the third exon of mitochondrial complex I subunit coding gene NDUFV3 and protects the exon from skipping. We further confirmed that exon skipping of NDUFV3 correlates with and partially contributes to cellular senescence and related mitochondrial functional changes upon PTBP1 knockdown. Together, we revealed for the first time that mitochondrial-related gene NDUFV3 is a new downstream target for PTBP1-regulated exon skipping to mediate cellular senescence and mitochondrial functional changes.

Transcriptome analyses in infertile men reveal germ cell-specific expression and splicing patterns

The process of spermatogenesis-when germ cells differentiate into sperm-is tightly regulated, and misregulation in gene expression is likely to be involved in the physiopathology of male infertility. The testis is one of the most transcriptionally rich tissues; nevertheless, the specific gene expression changes occurring during spermatogenesis are not fully understood. To better understand gene expression during spermatogenesis, we generated germ cell-specific whole transcriptome profiles by systematically comparing testicular transcriptomes from tissues in which spermatogenesis is arrested at successive steps of germ cell differentiation. In these comparisons, we found thousands of differentially expressed genes between successive germ cell types of infertility patients. We demonstrate our analyses' potential to identify novel highly germ cell-specific markers (TSPY4 and LUZP4 for spermatogonia; HMGB4 for round spermatids) and identified putatively misregulated genes in male infertility (RWDD2A, CCDC183, CNNM1, SERF1B). Apart from these, we found thousands of genes showing germ cell-specific isoforms (including SOX15, SPATA4, SYCP3, MKI67). Our approach and dataset can help elucidate genetic and transcriptional causes for male infertility.

Magnetique: an interactive web application to explore transcriptome signatures of heart failure

Background

Despite a recent increase in the number of RNA-seq datasets investigating heart failure (HF), accessibility and usability remain critical issues for medical researchers. We address the need for an intuitive and interactive web application to explore the transcriptional signatures of heart failure with this work.

Methods

We reanalysed the Myocardial Applied Genomics Network RNA-seq dataset, one of the largest publicly available datasets of left ventricular RNA-seq samples from patients with dilated (DCM) or hypertrophic (HCM) cardiomyopathy, as well as unmatched non-failing hearts (NFD) from organ donors and patient characteristics that allowed us to model confounding factors. We analyse differential gene expression, associated pathway signatures and reconstruct signaling networks based on inferred transcription factor activities through integer linear programming. We additionally focus, for the first time, on differential RNA transcript isoform usage (DTU) changes and predict RNA-binding protein (RBP) to target transcript interactions using a Global test approach. We report results for all pairwise comparisons (DCM, HCM, NFD).

Results

Focusing on the DCM versus HCM contrast (DCMvsHCM), we identified 201 differentially expressed genes, some of which can be clearly associated with changes in ERK1 and ERK2 signaling. Interestingly, the signs of the predicted activity for these two kinases have been inferred to be opposite to each other: In the DCMvsHCM contrast, we predict ERK1 to be consistently less activated in DCM while ERK2 was more activated in DCM. In the DCMvsHCM contrast, we identified 149 differently used transcripts. One of the top candidates is the O-linked N-acetylglucosamine (GlcNAc) transferase (OGT), which catalyzes a common post-translational modification known for its role in heart arrhythmias and heart hypertrophy. Moreover, we reconstruct RBP – target interaction networks and showcase the examples of CPEB1, which is differentially expressed in the DCMvsHCM contrast.

Conclusion

Magnetique (https://shiny.dieterichlab.org/app/magnetique) is the first online application to provide an interactive view of the HF transcriptome at the RNA isoform level and to include transcription factor signaling and RBP:RNA interaction networks. The source code for both the analyses (https://github.com/dieterich-lab/magnetiqueCode2022) and the web application (https://github.com/AnnekathrinSilvia/magnetique) is available to the public. We hope that our application will help users to uncover the molecular basis of heart failure.

Placental Gene Transcript Proportions are Altered in the Presence of In Utero Arsenic and Cadmium Exposures, Genetic Variants, and Birth Weight Differences

Background: In utero arsenic and cadmium exposures are linked with reduced birth weight as well as alterations in placental molecular features. However, studies thus far have focused on summarizing transcriptional activity at the gene level and do not capture transcript specification, an important resource during fetal development to enable adaptive responses to the rapidly changing in utero physiological conditions. In this study, we conducted a genome-wide analysis of the placental transcriptome to evaluate the role of differential transcript usage (DTU) as a potential marker of in utero arsenic and cadmium exposure and fetal growth restriction. Methods: Transcriptome-wide RNA sequencing was performed in placenta samples from the Rhode Island Child Health Study (RICHS, n = 199). Arsenic and cadmium levels were measured in maternal toenails using ICP-MS. Differential transcript usage (DTU) contrasting small (SGA) and appropriate (AGA) for gestational age infants as well as above vs. below median exposure to arsenic and cadmium were assessed using the DRIMSeq R package. Genetic variants that influence transcript usage were determined using the sQTLseeker R package. Results: We identified 82 genes demonstrating DTU in association with SGA status at an FDR <0.05. Among these, one gene, ORMDL1, also demonstrated DTU in association with arsenic exposure, and fifteen genes (CSNK1E, GBA, LAMTOR4, MORF4L1, PIGO, PSG1, PSG3, PTMA, RBMS1, SLC38A2, SMAD4, SPCS2, TUBA1B, UBE2A, YIPF5) demonstrated DTU in association with cadmium exposure. In addition to cadmium exposure and SGA status, proportions of the LAMTOR4 transcript ENST00000474141.5 also differed by genetic variants (rs10231604, rs12878, and rs3736591), suggesting a pathway by which an in utero exposure and genetic variants converge to impact fetal growth through perturbations of placental processes. Discussion: We report the first genome-wide characterization of placental transcript usage and associations with intrauterine metal exposure and fetal growth restriction. These results highlight the utility of interrogating the transcriptome at finer-scale transcript-level resolution to identify novel placental biomarkers of exposure-induced outcomes.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

The how and why of lncRNA function: An innate immune perspective

Next-generation sequencing has provided a more complete picture of the composition of the human transcriptome indicating that much of the "blueprint" is a vastness of poorly understood non-protein-coding transcripts. This includes a newly identified class of genes called long noncoding RNAs (lncRNAs). The lack of sequence conservation for lncRNAs across species meant that their biological importance was initially met with some skepticism. LncRNAs mediate their functions through interactions with proteins, RNA, DNA, or a combination of these. Their functions can often be dictated by their localization, sequence, and/or secondary structure. Here we provide a review of the approaches typically adopted to study the complexity of these genes with an emphasis on recent discoveries within the innate immune field. Finally, we discuss the challenges, as well as the emergence of new technologies that will continue to move this field forward and provide greater insight into the biological importance of this class of genes. This article is part of a Special Issue entitled: ncRNA in control of gene expression edited by Kotb Abdelmohsen.