Biology subjects

Volden, R.

Publications and source records attributed to Volden, R..

7 recordsLinked to original sources

bioRxiv2025

Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma.

Ewing sarcoma (EwS) is a fusion-driven malignancy, peaking in adolescence. Although EwS tumors are driven uniquely by EWS::FLI1 and related fusions, patient outcomes vary greatly. If and how tumor plasticity of EWS::FLI1-regulated transcriptional signatures contribute to disease progression is not known. To address this, we utilized a single-cell co-assay of RNA and chromatin accessibility (ATAC) sequencing to identify gene regulatory networks in EwS. By comprehensively characterizing regulatory elements across cell lines, we identified multiple unique modules of gene regulation. Differential usage and prevalence of these modules was evident across cell lines, associated with distinct epigenetic and transcriptomic signatures, and in specific cases, modifiable by exogenous TGF-{beta}. When we examined primary EwS patient tumors, we observed these same regulatory modules were variably enriched both across and within tumors, highlighting the existence of intratumoral heterogeneity in gene regulatory networks. Our findings demonstrate that multiple, co-existing transcriptional programs shape the phenotypic diversity of EwS and suggest that the balance between these networks may have important implications for clinical outcomes and targeted therapy development. SummaryMultimodal transcriptional analysis reveal how Ewing sarcoma tumors use distinct gene programs, including one linked to TGF-{beta}, to drive cancer behavior and progression.

genomics↗

bioRxiv2023

Detecting haplotype-specific transcript variation in long reads with FLAIR2

BackgroundRNA-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 communitys ability to interrogate both forms of RNA variation simultaneously. ResultsWe 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. ConclusionsUltimately, we find that a long-read approach provides valuable insight toward characterizing the relationship between RNA variants and splicing patterns. HighlightsO_LIFLAIR2 has improved transcript isoform detection and incorporates sequence variants for haplotype-specific transcript detection. C_LIO_LIIn addition to haplotype-specific variant detection, it identifies transcript-specific RNA editing C_LIO_LIAble to identify haplotype-specific transcript isoform bias in expression C_LIO_LILong-read sequencing identifies hyperedited transcripts that are missed from short-read sequencing methods for a more comprehensive identification of ADAR targets C_LI

bioinformatics↗

bioRxiv2022

Identifying and quantifying isoforms from accurate full-length transcriptome sequencing reads with Mandalorion

The Mandalorion tool, which we have continuously developed over the last 5 years, identifies and quantifies high-confidence isoforms from accurate full-length transcriptome sequencing reads produced by methods like PacBio Iso-Seq and ONT-based R2C2. In this manuscript, we introduce and benchmark Mandalorion v4 which further improves upon the already strong performance of Mandalorion v3.6 used in the LRGASP consortium challenge. By processing real and simulated accurate full-length transcriptome sequencing data sets, we show three main features of Mandalorion: First, Mandalorion-based isoform identification has very high Precision and maintains high Recall even when used in the absence of any genome annotation. Second, isoform read counts as quantified by Mandalorion show high correlation with simulated read counts. Third, isoforms identified by Mandalorion closely reflect the full-length transcriptome sequencing data sets they are based on.

bioinformatics↗

bioRxiv2020

Highly Multiplexed Single-Cell Full-Length cDNA Sequencing of human immune cells with 10X Genomics and R2C2

Single cell transcriptome analysis elucidates facets of cell biology that have been previously out of reach. However, the high-throughput analysis of thousands of single cell transcriptomes has been limited by sample preparation and sequencing technology. High-throughput single cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5 or 3 end. These cDNA pools are most often analyzed by short read Illumina sequencing which can identify the cellular origin of a transcript and what gene it was transcribed from. However, these methods fail to retrieve isoform information. In principle, cDNA pools prepared using these approaches can be analyzed with Pacific Biosciences and Oxford Nanopore long-read sequencers to retrieve isoform information but current implementations rely heavily on Illumina short-reads for analysis in addition to long reads. Here, we used R2C2 to sequence and demultiplex 12 million full-length cDNA molecules generated by the 10X Chromium platform from [~]3000 peripheral blood mononuclear cells (PBMCs). We used these reads to - independent from Illumina data - cluster cells into B cells, T cells, and Monocytes and generate isoform-level transcriptomes for these cell types. We also generated isoform-level transcriptomes for all single cells and used this information to identify a wide range of isoform diversity between genes. Finally, we also designed a computational workflow to extract paired adaptive immune receptors - T cell receptor and B cell receptor (TCR and BCR) - sequences unique to each T and B cell. This work represents a new, simple, and powerful approach that - using a single sequencing method - can extract an unprecedented amount of information from thousands of single cells.

genomics↗

bioRxiv2019

Complete characterization of the human immune cell transcriptome using accurate full-length cDNA sequencing

The human immune system relies on highly complex and diverse transcripts and the proteins they encode. These include transcripts for Human Leukocyte Antigen (HLA) class I and II receptors which are essential for self/non-self discrimination by the immune system as well as transcripts encoding B cell and T cell receptors (BCR and TCR) which recognize, bind, and help eliminate foreign antigens.\n\nHLA genes are highly diverse within the human population with each individual possessing two of thousands of different alleles in each of the 9 major HLA genes. Determining which combination of alleles an individual possesses for each HLA gene (high-resolution HLA-typing) is essential to establish donor-recipient compatibility in organ and bone-marrow transplantations. BCR and TCR genes in turn are generated by recombining a diverse set of gene segments on the DNA level in each maturing B and T cell, respectively. This process generates adaptive immune receptor repertoires (AIRR) of composed of unique transcripts expressed by each B and T cells. These repertoires carry a vast amount of health relevant information. Both short-read RNA-seq based HLA-typing1 and adaptive immune receptor repertoire sequencing2-5 currently rely heavily on our incomplete knowledge of the genetic diversity at HLA6 and BCR/TCR loci7,8.\n\nHere we used our nanopore sequencing based Rolling Circle to Concatemeric Consensus (R2C2) protocol9 to generate over 10,000,000 full-length cDNA sequences at a median accuracy of 97.9%. We used this dataset to demonstrate that deep and accurate full-length cDNA sequencing can - in addition to providing isoform-level transcriptome analysis for over 9,000 loci - be used to generate accurate sequences of HLA alleles for HLA allele typing and discovery as well as detailed AIRR data for the analysis of the adaptive immune system without requiring specific knowledge of the diversity at HLA and BCR/TCR loci.

genomics↗

bioRxiv2019

Depletion of hemoglobin transcripts and long read sequencing improves the transcriptome annotation of the polar bear (Ursus maritimus)

Transcriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9 based depletion method (Depletion of Abundant Sequences by Hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in-vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears (Ursus maritimus). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion we discovered ~6,000 high-confidence isoforms and a number of novel genes. This indicates there is a high diversity of gene isoforms within Ursus maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic.

genomics↗

bioRxiv2018

R2C2: Improving nanopore read accuracy enables the sequencing of highly-multiplexed full-length single-cell cDNA

High-throughput short-read sequencing has revolutionized how transcriptomes are quantified and annotated. However, while Illumina short-read sequencers can be used to analyze entire transcriptomes down to the level of individual splicing events with great accuracy, they fall short of analyzing how these individual events are combined into complete RNA transcript isoforms. Because of this shortfall, long-read sequencing is required to complement short-read sequencing to analyze transcriptomes on the level of full-length RNA transcript isoforms. However, there are issues with both Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) long-read sequencing technologies that prevent their widespread adoption. Briefly, PacBio sequencers produce low numbers of reads with high accuracy, while ONT sequencers produce higher numbers of reads with lower accuracy. Here we introduce and validate a new long-read ONT based sequencing method. At the same cost, our Rolling Circle Amplification to Concatemeric Consensus (R2C2) method generates more accurate reads of full-length RNA transcript isoforms than any other available long-read sequencing method. These reads can then be used to generate isoform-level transcriptomes for both genome annotation and differential expression analysis in bulk or single cell samples.\n\nSignificance StatementSubtle changes in RNA transcript isoform expression can have dramatic effects on cellular behaviors in both health and disease. As such, comprehensive and quantitative analysis of isoform-level transcriptomes would open an entirely new window into cellular diversity in fields ranging from developmental to cancer biology. The R2C2 method we are presenting here is the first method with sufficient throughput and accuracy to make the comprehensive and quantitative analysis of RNA transcript isoforms in bulk and single cell samples economically feasible.

genomics↗