exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling

Rozowsky, Joel; Kitchen, Robert; Park, Jonathan J.; Galeev, Timur R.; Diao, James A.; Warrell, Jonathan; Thistlethwaite, William; Subramanian, Sai Lakshmi; Milosavljevic, Aleksandar; Gerstein, Mark

doi:10.1016/j.cels.2019.03.004

Cited by 121 publications

(122 citation statements)

References 32 publications

(22 reference statements)

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“…Additional details on the data submission process are provided in STAR Methods. To minimize variability and facilitate integrative analyses across studies, all exRNA-seq data in the Atlas are uniformly processed using the extra-cellular RNA processing toolkit (exceRpt), an exRNA-seq processing pipeline created by members of the ERCC (Rozowsky et al, 2019). For Version 4P1 of the Atlas, a total of 23.43 billion reads from 2,270 RNA-seq sample profiles were processed through exceRpt.…”

Section: Results Exrna Atlas Resourcementioning

confidence: 99%

“…Output from exceRpt includes abundance estimates for the various RNA libraries and detailed mapping information for each read mapped for each library, as well as a variety of metrics such as read-length distribution and summaries of reads mapped to each library. A set of quality measures agreed upon by members of the ERCC (Rozowsky et al, 2019) are generated for each profile, and the small number of profiles not passing QC thresholds are denoted. After all sample files are processed and deployed, data and metadata become available through the exRNA Atlas website.…”

Section: Results Exrna Atlas Resourcementioning

confidence: 99%

“…The extra-cellular RNA processing toolkit (exceRpt) was developed for the processing and analysis of RNA-seq data generated to profile small exRNAs (Rozowsky et al, 2019). The pipeline is highly modular, allowing the user to define the libraries containing small RNA sequences that are used during RNA-seq read-mapping, and includes an option to provide a library of spike-in sequences to permit absolute quantitation of small-RNA molecules.…”

Section: Quantification and Statistical Analysis Excerpt Sequence Promentioning

confidence: 99%

“…This variability diminishes the power of individual exRNA profiling studies and the utility of the Atlas as a source of exRNA reference profiles for detecting disease-associated perturbations. In an attempt to minimize experimental variability, all exRNA-seq profiles were qualitycontrolled and uniformly processed using the exceRpt pipeline (Rozowsky et al, 2019). However, the uniform processing through exceRpt failed to explain a large amount of residual sample-to-sample and between-study variability.…”

Section: Introductionmentioning

confidence: 99%

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exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

Murillo

Thistlethwaite

Rozowsky

et al. 2019

Cell

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239

261

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Graphical Abstract Highlights d The exRNA Atlas provides access to human exRNA profiles and web-accessible tools d Atlas analysis reveals six exRNA cargo types present across five human biofluids d Five of the cargo types associate with specific vesicular and non-vesicular carriers d These findings and resources empower studies of extracellular RNA communication An extracellular RNA atlas from five human biofluids (serum, plasma, cerebrospinal fluid, saliva, and urine) reveals six extracellular RNA cargo types, including both vesicular and nonvesicular carriers. SUMMARY To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously.To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

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Section: Results Exrna Atlas Resourcementioning

confidence: 99%

Section: Results Exrna Atlas Resourcementioning

confidence: 99%

Section: Quantification and Statistical Analysis Excerpt Sequence Promentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

Murillo

Thistlethwaite

Rozowsky

et al. 2019

Cell

Self Cite

239

261

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“…The exogenous RNA content in the small RNA data was assessed using the exceRpt small RNAseq pipeline (v4.6.2) in the Genboree workbench with default settings 54 No mismatches were allowed during exogenous alignment. Raw read counts obtained from the Genboree workbench were further analyzed in R (v3.5.1) making use of tidyverse (v1.2.1).…”

Section: Exogenous Rna Characterizationmentioning

confidence: 99%

Charting extracellular transcriptomes in The Human Biofluid RNA Atlas

Hulstaert

Morlion

Cobos

et al. 2019

Preprint

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Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease.Where most studies focus on plasma or serum, other biofluids may contain more informative RNA molecules, depending on the type of disease. Here, we present an unprecedented atlas of messenger, circular and small RNA transcriptomes of a comprehensive collection of 20 different human biofluids. By means of synthetic spike-in controls, we compared RNA content across biofluids, revealing a more than 10 000-fold difference in RNA concentration. The circular RNA fraction is increased in nearly all biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. In addition, a subset of biofluids, including stool, sweat, saliva and sputum, contains high levels of bacterial RNAs. Our atlas enables a more informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Taken together, our results reveal novel insights in the RNA content of human biofluids and may serve as a valuable resource for future biomarker studies.

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Polyadenylation ligation‐mediated sequencing (PALM‐Seq) characterizes cell‐free coding and non‐coding RNAs in human biofluids

Liu

Wang

Yang

et al. 2022

Clinical & Translational Med

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exceRpt: A Comprehensive Analytic Platform for Extracellular RNA Profiling

Abstract: Highlights d exceRpt processes and analyzes exRNA profiling data d exceRpt generates quality control metrics, RNA abundance estimates, and reports d A user-friendly, browser-based graphical interface is available d exceRpt processes all RNA-seq datasets in the exRNA Atlas

Cited by 121 publications

References 32 publications

exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids

Charting extracellular transcriptomes in The Human Biofluid RNA Atlas

Polyadenylation ligation‐mediated sequencing (PALM‐Seq) characterizes cell‐free coding and non‐coding RNAs in human biofluids

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