Probing chromatin accessibility with small molecule DNA intercalation and nanopore sequencing.

Genome-wide identification of chromatin organization and structure has been generally probed by measuring accessibility of the underlying DNA to nucleases or methyltransferases. These methods either only observe the positioning of a single nucleosome or rely on large enzymes to modify or cleave the DNA. We developed adduct sequencing (Add-seq), a method to probe chromatin accessibility by treating chromatin with the small molecule angelicin, which preferentially intercalates into DNA not bound to core nucleosomes. We show that Nanopore sequencing of the angelicin-modified DNA is possible and allows visualization and analysis of long single molecules with distinct chromatin structure. The angelicin modification can be detected from the Nanopore current signal data using a neural network model trained on unmodified and modified chromatin-free DNA. Applying Add-seq to Saccharomyces cerevisiae nuclei, we identified expected patterns of accessibility around annotated gene loci in yeast. We also identify individual clusters of single molecule reads displaying different chromatin structure at specific yeast loci, which demonstrates heterogeneity in the chromatin structure of the yeast population. Thus, using Add-seq, we are able to profile DNA accessibility in the yeast genome across long molecules.

MET exon 14 skipping is overexpressed in an allele-specific manner in lung adenocarcinoma primary samples.

MET exon 14 skipping ( METΔ14 ) is a well-characterized oncogene in the Ras-MAPK pathway driving lung adenocarcinoma (LUAD). Previous studies on METΔ14 revealed this aberrantly spliced oncogene is expressed in LUAD primary samples and is associated with heterozygous somatic mutations and deletions near exon 14 splice sites. Upon further examination of DNA and RNA sequencing data from primary samples, we highlight that METΔ14 is overexpressed in an allele-specific manner. These data suggest that dose-dependence of METΔ14 may be critical to oncogenesis.

DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.

Time-lapse microscopy is the only method that can directly capture the dynamics and heterogeneity of fundamental cellular processes at the single-cell level with high temporal resolution. Successful application of single-cell time-lapse microscopy requires automated segmentation and tracking of hundreds of individual cells over several time points. However, segmentation and tracking of single cells remain challenging for the analysis of time-lapse microscopy images, in particular for widely available and non-toxic imaging modalities such as phase-contrast imaging. This work presents a versatile and trainable deep-learning model, termed DeepSea, that allows for both segmentation and tracking of single cells in sequences of phase-contrast live microscopy images with higher precision than existing models. We showcase the application of DeepSea by analyzing cell size regulation in embryonic stem cells.

Detecting haplotype-specific transcript variation in long reads with FLAIR2.

Background: RNA-Seq has brought forth significant discoveries regarding aberrations in RNA processing, implicating these RNA variants in a variety of diseases. Aberrant splicing and single nucleotide variants in RNA have been demonstrated to alter transcript stability, localization, and function. In particular, the upregulation of ADAR, an enzyme which mediates adenosine-to-inosine editing, has been previously linked to an increase in the invasiveness of lung ADC cells and associated with splicing regulation. Despite the functional importance of studying splicing and SNVs, short read RNA-Seq has limited the community's ability to interrogate both forms of RNA variation simultaneously. Results: We employed long-read technology to obtain full-length transcript sequences, elucidating cis-effects of variants on splicing changes at a single molecule level. We have developed a computational workflow that augments FLAIR, a tool that calls isoform models expressed in long-read data, to integrate RNA variant calls with the associated isoforms that bear them. We generated nanopore data with high sequence accuracy of H1975 lung adenocarcinoma cells with and without knockdown of ADAR. We applied our workflow to identify key inosine-isoform associations to help clarify the prominence of ADAR in tumorigenesis. Conclusions: Ultimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns.

Full-length transcript alterations in human bronchial epithelial cells with U2AF1 S34F mutations.

U2AF1 is one of the most recurrently mutated splicing factors in lung adenocarcinoma and has been shown to cause transcriptome-wide pre-mRNA splicing alterations; however, the full-length altered mRNA isoforms associated with the mutation are largely unknown. To better understand the impact U2AF1 has on full-length isoform fate and function, we conducted high-throughput long-read cDNA sequencing from isogenic human bronchial epithelial cells with and without a U2AF1 S34F mutation. We identified 49,366 multi-exon transcript isoforms, more than half of which did not match GENCODE or short-read-assembled isoforms. We found 198 transcript isoforms with significant expression and usage changes relative to WT, only 68% of which were assembled by short reads. Expression of isoforms from immune-related genes is largely down-regulated in mutant cells and without observed splicing changes. Finally, we reveal that isoforms likely targeted by nonsense-mediated decay are down-regulated in U2AF1 S34F cells, suggesting that isoform changes may alter the translational output of those affected genes. Altogether, our work provides a resource of full-length isoforms associated with U2AF1 S34F in lung cells.

An expression-based variant impact phenotyping protocol to predict the impact of gene variants in cell lines.

We describe a bioinformatics protocol for eVIP2 (expression-based variant impact phenotyping). eVIP2 can predict a gene variant's functional impact by comparing gene expression signatures induced by introduction of wild-type versus mutant cDNAs in cell lines. The predicted functional outcomes of the variants include gain-of-function, loss-of-function, change-of-function, or neutral. eVIP2 improves upon eVIP by being applicable to RNA-seq data and providing pathway-level functional predictions for each mutation. Here, we detail how to run eVIP2 on RNA-seq data from two RNF43 variants. For complete details on the use and execution of this protocol, please refer to Thornton et al. (2021).

Mutant KRAS regulates transposable element RNA and innate immunity via KRAB zinc-finger genes.

RAS genes are the most frequently mutated oncogenes in cancer, yet the effects of oncogenic RAS signaling on the noncoding transcriptome remain unclear. We analyzed the transcriptomes of human airway and bronchial epithelial cells transformed with mutant KRAS to define the landscape of KRAS-regulated noncoding RNAs. We find that oncogenic KRAS signaling upregulates noncoding transcripts throughout the genome, many of which arise from transposable elements (TEs). These TE RNAs exhibit differential expression, are preferentially released in extracellular vesicles, and are regulated by KRAB zinc-finger (KZNF) genes, which are broadly downregulated in mutant KRAS cells and lung adenocarcinomas in vivo. Moreover, mutant KRAS induces an intrinsic IFN-stimulated gene (ISG) signature that is often seen across many different cancers. Our results indicate that mutant KRAS remodels the repetitive noncoding transcriptome, demonstrating the broad scope of intracellular and extracellular RNAs regulated by this oncogenic signaling pathway.

Cell Painting predicts impact of lung cancer variants.

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding genes is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance as impactful vs. neutral in an approach called expression-based variant-impact phenotyping. We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell's image, we found that cell morphological profiling (cmVIP) can predict variants' functional impact and, particularly at the single-cell level, reveals biological insights into variants that can be explored at our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

SRSF1 governs progenitor-specific alternative splicing to maintain adult epithelial tissue homeostasis and renewal.

Alternative splicing generates distinct mRNA variants and is essential for development, homeostasis, and renewal. Proteins of the serine/arginine (SR)-rich splicing factor family are major splicing regulators that are broadly required for organ development as well as cell and organism viability. However, how these proteins support adult organ function remains largely unknown. Here, we used the continuously growing mouse incisor as a model to dissect the functions of the prototypical SR family protein SRSF1 during tissue homeostasis and renewal. We identified an SRSF1-governed alternative splicing network that is specifically required for dental proliferation and survival of progenitors but dispensable for the viability of differentiated cells. We also observed a similar progenitor-specific role of SRSF1 in the small intestinal epithelium, indicating a conserved function of SRSF1 across adult epithelial tissues. Thus, our findings define a regulatory mechanism by which SRSF1 specifically controls progenitor-specific alternative splicing events to support adult tissue homeostasis and renewal.

eVIP2: Expression-based variant impact phenotyping to predict the function of gene variants.

While advancements in genome sequencing have identified millions of somatic mutations in cancer, their functional impact is poorly understood. We previously developed the expression-based variant impact phenotyping (eVIP) method to use gene expression data to characterize the function of gene variants. The eVIP method uses a decision tree-based algorithm to predict the functional impact of somatic variants by comparing gene expression signatures induced by introduction of wild-type (WT) versus mutant cDNAs in cell lines. The method distinguishes between variants that are gain-of-function, loss-of-function, change-of-function, or neutral. We present eVIP2, software that allows for pathway analysis (eVIP Pathways) and usage with RNA-seq data. To demonstrate the eVIP2 software and approach, we characterized two recurrent frameshift variants in RNF43, a negative regulator of Wnt signaling, frequently mutated in colorectal, gastric, and endometrial cancer. RNF43 WT, RNF43 R117fs, RNF43 G659fs, or GFP control cDNA were overexpressed in HEK293T cells. Analysis with eVIP2 predicted that the frameshift at position 117 was a loss-of-function mutation, as expected. The second frameshift at position 659 has been previously described as a passenger mutation that maintains the RNF43 WT function as a negative regulator of Wnt. Surprisingly, eVIP2 predicted G659fs to be a change-of-function mutation. Additional eVIP Pathways analysis of RNF43 G659fs predicted 10 pathways to be significantly altered, including TNF-α via NFκB signaling, KRAS signaling, and hypoxia, highlighting the benefit of a more comprehensive approach when determining the impact of gene variant function. To validate these predictions, we performed reporter assays and found that each pathway activated by expression of RNF43 G659fs, but not expression of RNF43 WT, was identified as impacted by eVIP2, supporting that RNF43 G659fs is a change-of-function mutation and its effect on the identified pathways. Pathway activation was further validated by Western blot analysis. Lastly, we show primary colon adenocarcinoma patient samples with R117fs and G659fs variants have transcriptional profiles similar to BRAF missense mutations with activated RAS/MAPK signaling, consistent with KRAS signaling pathways being GOF in both variants. The eVIP2 method is an important step towards overcoming the current challenge of variant interpretation in the implementation of precision medicine. eVIP2 is available at https://github.com/BrooksLabUCSC/eVIP2.

Inflammation drives alternative first exon usage to regulate immune genes including a novel iron-regulated isoform of Aim2.

Determining the layers of gene regulation within the innate immune response is critical to our understanding of the cellular responses to infection and dysregulation in disease. We identified a conserved mechanism of gene regulation in human and mouse via changes in alternative first exon (AFE) usage following inflammation, resulting in changes to the isoforms produced. Of these AFE events, we identified 95 unannotated transcription start sites in mice using a de novo transcriptome generated by long-read native RNA-sequencing, one of which is in the cytosolic receptor for dsDNA and known inflammatory inducible gene, Aim2. We show that this unannotated AFE isoform of Aim2 is the predominant isoform expressed during inflammation and contains an iron-responsive element in its 5'UTR enabling mRNA translation to be regulated by iron levels. This work highlights the importance of examining alternative isoform changes and translational regulation in the innate immune response and uncovers novel regulatory mechanisms of Aim2.

Reintroduction of the archaic variant of NOVA1 in cortical organoids alters neurodevelopment.

The evolutionarily conserved splicing regulator neuro-oncological ventral antigen 1 (NOVA1) plays a key role in neural development and function. NOVA1 also includes a protein-coding difference between the modern human genome and Neanderthal and Denisovan genomes. To investigate the functional importance of an amino acid change in humans, we reintroduced the archaic allele into human induced pluripotent cells using genome editing and then followed their neural development through cortical organoids. This modification promoted slower development and higher surface complexity in cortical organoids with the archaic version of NOVA1 Moreover, levels of synaptic markers and synaptic protein coassociations correlated with altered electrophysiological properties in organoids expressing the archaic variant. Our results suggest that the human-specific substitution in NOVA1, which is exclusive to modern humans since divergence from Neanderthals, may have had functional consequences for our species' evolution.

Proteasome inhibitor-induced modulation reveals the spliceosome as a specific therapeutic vulnerability in multiple myeloma.

Enhancing the efficacy of proteasome inhibitors (PI) is a central goal in myeloma therapy. We proposed that signaling-level responses after PI may reveal new mechanisms of action that can be therapeutically exploited. Unbiased phosphoproteomics after treatment with the PI carfilzomib surprisingly demonstrates the most prominent phosphorylation changes on splicing related proteins. Spliceosome modulation is invisible to RNA or protein abundance alone. Transcriptome analysis after PI demonstrates broad-scale intron retention, suggestive of spliceosome interference, as well as specific alternative splicing of protein homeostasis machinery components. These findings lead us to evaluate direct spliceosome inhibition in myeloma, which synergizes with carfilzomib and shows potent anti-tumor activity. Functional genomics and exome sequencing further support the spliceosome as a specific vulnerability in myeloma. Our results propose splicing interference as an unrecognized modality of PI mechanism, reveal additional modes of spliceosome modulation, and suggest spliceosome targeting as a promising therapeutic strategy in myeloma.

Full-length transcript characterization of SF3B1 mutation in chronic lymphocytic leukemia reveals downregulation of retained introns.

While splicing changes caused by somatic mutations in SF3B1 are known, identifying full-length isoform changes may better elucidate the functional consequences of these mutations. We report nanopore sequencing of full-length cDNA from CLL samples with and without SF3B1 mutation, as well as normal B cell samples, giving a total of 149 million pass reads. We present FLAIR (Full-Length Alternative Isoform analysis of RNA), a computational workflow to identify high-confidence transcripts, perform differential splicing event analysis, and differential isoform analysis. Using nanopore reads, we demonstrate differential 3' splice site changes associated with SF3B1 mutation, agreeing with previous studies. We also observe a strong downregulation of intron retention events associated with SF3B1 mutation. Full-length transcript analysis links multiple alternative splicing events together and allows for better estimates of the abundance of productive versus unproductive isoforms. Our work demonstrates the potential utility of nanopore sequencing for cancer and splicing research.

Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Author Correction: Nanopore native RNA sequencing of a human poly(A) transcriptome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Nanopore native RNA sequencing of a human poly(A) transcriptome.

High-throughput complementary DNA sequencing technologies have advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and modifications are not retained. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies. Our study generated 9.9 million aligned sequence reads for the human cell line GM12878, using thirty MinION flow cells at six institutions. These native RNA reads had a median length of 771 bases, and a maximum aligned length of over 21,000 bases. Mitochondrial poly(A) reads provided an internal measure of read-length quality. We combined these long nanopore reads with higher accuracy short-reads and annotated GM12878 promoter regions to identify 33,984 plausible RNA isoforms. We describe strategies for assessing 3' poly(A) tail length, base modifications and transcript haplotypes.

A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters.

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer.