TDP-43 dysregulation of polyadenylation site selection is a defining feature of RNA misprocessing in ALS/FTD and related disorders.

Nuclear clearance and cytoplasmic aggregation of the RNA-binding protein TDP-43 are observed in many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and fronto- temporal dementia (FTD). Although TDP-43 dysregulation of splicing has emerged as a key event in these diseases, TDP-43 can also regulate polyadenylation; yet, this has not been adequately studied. Here, we applied the dynamic analysis of polyadenylation from RNA-seq (DaPars) tool to ALS/FTD transcriptome datasets, and report extensive alternative polyadenylation (APA) upon TDP-43 alteration in ALS/FTD cell models and postmortem ALS/FTD neuronal nuclei. Importantly, many identified APA genes highlight pathways implicated in ALS/FTD pathogenesis. To determine the functional significance of APA elicited by TDP-43 nuclear depletion, we examined microtubule affinity regulating kinase 3 (MARK3). Nuclear loss of TDP-43 yielded increased expression of MARK3 transcripts with longer 3'UTRs, resulting in greater transcript stability and elevated MARK3 protein levels, which promotes increased neuronal tau S262 phosphorylation. Our findings define changes in polyadenylation site selection as a previously unrecognized feature of TDP-43-driven disease pathology in ALS/FTD and highlight a potentially novel mechanistic link between TDP-43 dysfunction and tau regulation.

Single-cell transcriptomics of human traumatic brain injury reveals activation of endogenous retroviruses in oligodendroglia.

Traumatic brain injury (TBI) is a leading cause of chronic brain impairment and results in a robust, but poorly understood, neuroinflammatory response that contributes to the long-term pathology. We used single-nuclei RNA sequencing (snRNA-seq) to study transcriptomic changes in different cell populations in human brain tissue obtained acutely after severe, life-threatening TBI. This revealed a unique transcriptional response in oligodendrocyte precursors and mature oligodendrocytes, including the activation of a robust innate immune response, indicating an important role for oligodendroglia in the initiation of neuroinflammation. The activation of an innate immune response correlated with transcriptional upregulation of endogenous retroviruses in oligodendroglia. This observation was causally linked in vitro using human glial progenitors, implicating these ancient viral sequences in human neuroinflammation. In summary, this work provides insight into the initiating events of the neuroinflammatory response in TBI, which has therapeutic implications.

Nuclear RNA catabolism controls endogenous retroviruses, gene expression asymmetry, and dedifferentiation.

Endogenous retroviruses (ERVs) are remnants of ancient parasitic infections and comprise sizable portions of most genomes. Although epigenetic mechanisms silence most ERVs by generating a repressive environment that prevents their expression (heterochromatin), little is known about mechanisms silencing ERVs residing in open regions of the genome (euchromatin). This is particularly important during embryonic development, where induction and repression of distinct classes of ERVs occur in short temporal windows. Here, we demonstrate that transcription-associated RNA degradation by the nuclear RNA exosome and Integrator is a regulatory mechanism that controls the productive transcription of most genes and many ERVs involved in preimplantation development. Disrupting nuclear RNA catabolism promotes dedifferentiation to a totipotent-like state characterized by defects in RNAPII elongation and decreased expression of long genes (gene-length asymmetry). Our results indicate that RNA catabolism is a core regulatory module of gene networks that safeguards RNAPII activity, ERV expression, cell identity, and developmental potency.

Mobile genomics: tools and techniques for tackling transposons.

Next-generation sequencing approaches have fundamentally changed the types of questions that can be asked about gene function and regulation. With the goal of approaching truly genome-wide quantifications of all the interaction partners and downstream effects of particular genes, these quantitative assays have allowed for an unprecedented level of detail in exploring biological interactions. However, many challenges remain in our ability to accurately describe and quantify the interactions that take place in those hard to reach and extremely repetitive regions of our genome comprised mostly of transposable elements (TEs). Tools dedicated to TE-derived sequences have lagged behind, making the inclusion of these sequences in genome-wide analyses difficult. Recent improvements, both computational and experimental, allow for the better inclusion of TE sequences in genomic assays and a renewed appreciation for the importance of TE biology. This review will discuss the recent improvements that have been made in the computational analysis of TE-derived sequences as well as the areas where such analysis still proves difficult. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

TEsmall Identifies Small RNAs Associated With Targeted Inhibitor Resistance in Melanoma.

MicroRNAs (miRNAs) are small 21-22 nt RNAs that act to regulate the expression of mRNA target genes through direct binding to mRNA targets. While miRNAs typically dominate small RNA (sRNA) transcriptomes, many other classes are present including tRNAs, snoRNAs, snRNAs, Y-RNAs, piRNAs, and siRNAs. Interactions between processing machinery and targeting networks of these various sRNA classes remains unclear, largely because these sRNAs are typically analyzed separately. Here, we present TEsmall, a tool that allows for the simultaneous processing and analysis of sRNAs from each annotated class in a single integrated workflow. The pipeline begins with raw fastq reads and proceeds all the way to producing count tables formatted for differential expression analysis. Several interactive charts are also produced to look at overall distributions in length and annotation classes. We next applied the TEsmall pipeline to sRNA libraries generated from melanoma cells responding to targeted inhibitors of the MAPK pathway. Targeted oncogene inhibitors have emerged as way to tailor cancer therapies to the particular mutations present in a given tumor. While these targeted strategies are typically effective for short intervals, the emergence of resistance is extremely common, limiting the effectiveness of single-agent therapeutics and driving the need for a better understanding of resistance mechanisms. Using TEsmall, we identified several microRNAs and other sRNA classes that are enriched in inhibitor resistant melanoma cells in multiple melanoma cell lines and may be able to serve as markers of resistant populations more generally.

Single-cell RNA-seq analysis identifies markers of resistance to targeted BRAF inhibitors in melanoma cell populations.

Single-cell RNA-seq's (scRNA-seq) unprecedented cellular resolution at a genome-wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-seq data sets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present a single-cell RNA-seq analysis and klustering evaluation (SAKE), a robust method for scRNA-seq analysis that provides quantitative statistical metrics at each step of the analysis pipeline. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range of cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors (BRAFi). Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor-resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. These experimentally validated markers of BRAFi resistance share overlap with previous analyses in different melanoma cell lines, demonstrating the generality of these findings and highlighting the utility of single-cell analysis to elucidate mechanisms of BRAFi resistance.