The homocysteine-inducible endoplasmic reticulum (ER) stress protein Herp counteracts mutant α-synuclein-induced ER stress via the homeostatic regulation of ER-resident calcium release channel proteins.

Endoplasmic reticulum (ER) stress has been implicated as an initiator or contributing factor in neurodegenerative diseases. The mechanisms that lead to ER stress and whereby ER stress contributes to the degenerative cascades remain unclear but their understanding is critical to devising effective therapies. Here we show that knockdown of Herp (Homocysteine-inducible ER stress protein), an ER stress-inducible protein with an ubiquitin-like (UBL) domain, aggravates ER stress-mediated cell death induced by mutant α-synuclein (αSyn) that causes an inherited form of Parkinson's disease (PD). Functionally, Herp plays a role in maintaining ER homeostasis by facilitating proteasome-mediated degradation of ER-resident Ca(2+) release channels. Deletion of the UBL domain or pharmacological inhibition of proteasomes abolishes the Herp-mediated stabilization of ER Ca(2+) homeostasis. Furthermore, knockdown or pharmacological inhibition of ER Ca(2+) release channels ameliorates ER stress, suggesting that impaired homeostatic regulation of Ca(2+) channels promotes a protracted ER stress with the consequent activation of ER stress-associated apoptotic pathways. Interestingly, sustained upregulation of ER stress markers and aberrant accumulation of ER Ca(2+) release channels were detected in transgenic mutant A53T-αSyn mice. Collectively, these data establish a causative link between impaired ER Ca(2+) homeostasis and chronic ER stress in the degenerative cascades induced by mutant αSyn and suggest that Herp is essential for the resolution of ER stress through maintenance of ER Ca(2+) homeostasis. Our findings suggest a therapeutic potential in PD for agents that increase Herp levels or its ER Ca(2+)-stabilizing action.

CTAT-LR-fusion: accurate fusion transcript identification from long and short read isoform sequencing at bulk or single cell resolution.

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.

High-throughput RNA isoform sequencing using programmed cDNA concatenation.

Full-length RNA-sequencing methods using long-read technologies can capture complete transcript isoforms, but their throughput is limited. We introduce multiplexed arrays isoform sequencing (MAS-ISO-seq), a technique for programmably concatenating complementary DNAs (cDNAs) into molecules optimal for long-read sequencing, increasing the throughput >15-fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. When applied to single-cell RNA sequencing of tumor-infiltrating T cells, MAS-ISO-seq demonstrated a 12- to 32-fold increase in the discovery of differentially spliced genes.

Integrative genotyping of cancer and immune phenotypes by long-read sequencing.

Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq Data.

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq), and introns are under lower purifying selection and thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. To further investigate ASE in the context of human disease, we applied our methods to a Parkinson's disease cohort of 94 individuals and show that ASE analysis had more power than eQTL analysis to identify significant SNP/gene pairs in our direct comparison of the two methods. Overall, we provide an end-to-end experimental and computational approach for future studies.

ESCRT-dependent STING degradation inhibits steady-state and cGAMP-induced signalling.

Stimulator of interferon genes (STING) is an intracellular sensor of cyclic di-nucleotides involved in the innate immune response against pathogen- or self-derived DNA. STING trafficking is tightly linked to its function, and its dysregulation can lead to disease. Here, we systematically characterize genes regulating STING trafficking and examine their impact on STING-mediated responses. Using proximity-ligation proteomics and genetic screens, we demonstrate that an endosomal sorting complex required for transport (ESCRT) complex containing HGS, VPS37A and UBAP1 promotes STING degradation, thereby terminating STING-mediated signaling. Mechanistically, STING oligomerization increases its ubiquitination by UBE2N, forming a platform for ESCRT recruitment at the endosome that terminates STING signaling via sorting in the lysosome. Finally, we show that expression of a UBAP1 mutant identified in patients with hereditary spastic paraplegia and associated with disrupted ESCRT function, increases steady-state STING-dependent type I IFN responses in healthy primary monocyte-derived dendritic cells and fibroblasts. Based on these findings, we propose that STING is subject to a tonic degradative flux and that the ESCRT complex acts as a homeostatic regulator of STING signaling.

Functionalized Lineage Tracing Can Enable the Development of Homogenization-Based Therapeutic Strategies in Cancer.

The therapeutic landscape across many cancers has dramatically improved since the introduction of potent targeted agents and immunotherapy. Nonetheless, success of these approaches is too often challenged by the emergence of therapeutic resistance, fueled by intratumoral heterogeneity and the immense evolutionary capacity inherent to cancers. To date, therapeutic strategies have attempted to outpace the evolutionary tempo of cancer but frequently fail, resulting in lack of tumor response and/or relapse. This realization motivates the development of novel therapeutic approaches which constrain evolutionary capacity by reducing the degree of intratumoral heterogeneity prior to treatment. Systematic development of such approaches first requires the ability to comprehensively characterize heterogeneous populations over the course of a perturbation, such as cancer treatment. Within this context, recent advances in functionalized lineage tracing approaches now afford the opportunity to efficiently measure multimodal features of clones within a tumor at single cell resolution, enabling the linkage of these features to clonal fitness over the course of tumor progression and treatment. Collectively, these measurements provide insights into the dynamic and heterogeneous nature of tumors and can thus guide the design of homogenization strategies which aim to funnel heterogeneous cancer cells into known, targetable phenotypic states. We anticipate the development of homogenization therapeutic strategies to better allow for cancer eradication and improved clinical outcomes.

Multifunctional barcoding with ClonMapper enables high-resolution study of clonal dynamics during tumor evolution and treatment.

Lineage-tracing methods have enabled characterization of clonal dynamics in complex populations, but generally lack the ability to integrate genomic, epigenomic and transcriptomic measurements with live-cell manipulation of specific clones of interest. We developed a functionalized lineage-tracing system, ClonMapper, which integrates DNA barcoding with single-cell RNA sequencing and clonal isolation to comprehensively characterize thousands of clones within heterogeneous populations. Using ClonMapper, we identified subpopulations of a chronic lymphocytic leukemia cell line with distinct clonal compositions, transcriptional signatures and chemotherapy survivorship trajectories; patterns that were also observed in primary human chronic lymphocytic leukemia. The ability to retrieve specific clones before, during and after treatment enabled direct measurements of clonal diversification and durable subpopulation transcriptional signatures. ClonMapper is a powerful multifunctional approach to dissect the complex clonal dynamics of tumor progression and therapeutic response.

Control of Lineage-Specific Gene Expression by Functionalized gRNA Barcodes.

Lineage tracking delivers essential quantitative insight into dynamic, probabilistic cellular processes, such as somatic tumor evolution and differentiation. Methods for high diversity lineage quantitation rely on sequencing a population of DNA barcodes. However, manipulation of specific individual lineages is not possible with this approach. To address this challenge, we developed a functionalized lineage tracing tool, Control of Lineages by Barcode Enabled Recombinant Transcription (COLBERT), that enables high diversity lineage tracing and lineage-specific manipulation of gene expression. This modular platform utilizes expressed barcode gRNAs to both track cell lineages and direct lineage-specific gene expression.