Repeat-element-aware profiling of plasma cell-free RNA
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ABSTRACT:
PROVIDER: PRJNA562932 | ENA |
REPOSITORIES: ENA
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Project description:Liquid biopsies provide a means for the profiling of cell-free RNAs secreted by cells throughout the body. Although well-annotated coding and noncoding transcripts in blood are readily detectable and can serve as biomarkers of disease, the overall diagnostic utility of the cell-free transcriptome remains unclear. Here we show that transposable elements and other repeat RNA elements are enriched in the cell-free transcriptome of patients with cancer, and that they serve as signatures for the accurate classification of the disease. We used repeat-element-aware sequencing and analysis technology and single-molecule nanopore sequencing to profile the cell-free transcriptome in plasma from patients with cancer and to examine millions of genomic features comprised of all annotated genes and of repeat elements throughout the genome. By aggregating individual repeat elements to the subfamily level, we found that samples with pancreatic cancer are enriched with specific Alu subfamilies, whereas other cancers exhibit their own characteristic cell-free RNA profile. Our findings show that repetitive RNA sequences are abundant in blood and can be used as disease-specific diagnostic biomarkers.
2023-09-01 | GSE136651 | GEO
Project description:In vertebrates, DNA methylation-mediated repression of retrotransposons is essential for the maintenance of genomic integrity. In the current study, we developed a technique termed HT-TREBS (High-Throughput Targeted Repeat Element Bisulfite Sequencing). This technique is designed to measure the DNA methylation levels of individual loci of any repeat families with next-generation sequencing approaches. To test the feasibility of HT-TREBS, we analyzed the DNA methylation levels of the IAPLTR family using a set of 12 different genomic DNA isolated from the brain, liver and kidney of 4 one-week-old littermates of the mouse strain C57BL/6N. This technique has successfully generated the CpG methylation data of 5,233 loci common in all the samples, representing more than 80% of the individual loci of the five targeted subtypes of the IAPLTR family. According to the results, approximately 5% of the IAPLTR loci have less than 80% average CpG methylation levels with no genomic position preference. Further analyses of the IAPLTR loci also revealed the presence of extensive DNA methylation variations between different tissues and individuals. Overall, these data demonstrate the efficiency and robustness of the new technique, HT-TREBS, and also provide new insights regarding the genome-wide DNA methylation patterns of the IAPLTR repeat elements. High-throughput, single-base resolution, singlicate DNA methylation profiles of IAPLTR retrotransposons in the brain, liver , and kidney of four 1-week-old mouse littemates using the developed technique, HT-TREBS.
2014-07-24 | E-GEOD-49222 | biostudies-arrayexpress
Project description:Reverse Transcriptase Inhibition Disrupts Repeat Element Life Cycle in Colorectal Cancer
| PRJNA818339 | ENA
Project description:In vertebrates, DNA methylation-mediated repression of retrotransposons is essential for the maintenance of genomic integrity. In the current study, we developed a technique termed HT-TREBS (High-Throughput Targeted Repeat Element Bisulfite Sequencing). This technique is designed to measure the DNA methylation levels of individual loci of any repeat families with next-generation sequencing approaches. To test the feasibility of HT-TREBS, we analyzed the DNA methylation levels of the IAPLTR family using a set of 12 different genomic DNA isolated from the brain, liver and kidney of 4 one-week-old littermates of the mouse strain C57BL/6N. This technique has successfully generated the CpG methylation data of 5,233 loci common in all the samples, representing more than 80% of the individual loci of the five targeted subtypes of the IAPLTR family. According to the results, approximately 5% of the IAPLTR loci have less than 80% average CpG methylation levels with no genomic position preference. Further analyses of the IAPLTR loci also revealed the presence of extensive DNA methylation variations between different tissues and individuals. Overall, these data demonstrate the efficiency and robustness of the new technique, HT-TREBS, and also provide new insights regarding the genome-wide DNA methylation patterns of the IAPLTR repeat elements.
2014-07-24 | GSE49222 | GEO
Project description:Epigenomics of Prostate Cancer from Cell Free Plasma
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Project description:Epigenomics of Prostate Cancer from Cell Free Plasma
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Project description:Cell-free RNA (cfRNA) in plasma reflects gene expression profiles of both localized sites of cancer and at the systemic host response. Here we explore the diagnostic potential of cell-free transcriptomes by mRNA sequencing. We sequenced total cell-free plasma RNA from 90 plasma samples from two independent sample cohorts representing two cancer types, two pre-cancerous conditions and non-cancer donors. We identified distinct gene sets and built classification models that could distinguish cancer patients with specific cancer types from premalignant conditions and non-cancer individuals with high accuracy. Determination of multiple myeloma from its pre-cancerous monoclonal gammopathy of undetermined significance (MGUS) yielded an accuracy of 90% (17/19). Detection of primary liver cancer from its premalignant condition cirrhosis yielded an accuracy of 100% (12/12). This work lays the foundation for developing low cost assays by measuring mRNA transcript levels in plasma using a small panel of genes for detection that can distinguish the presence of cancer from pre-cancerous conditions and non-cancer individuals.
2022-04-25 | GSE182824 | GEO
Project description:We analyzed the transcriptome (RNA-seq) of mouse plasma cells (PC) expressing a human Ig light chain from a patient suffering light chain deposition disease (LCDD) as compared to control plasma cells (WT and DH-LMP2A, the latter producing no complete immunoglobulins, only free Ig light chains). Ig light chains causing LCDD present structural peculiarities leading to their aggregation and deposition into tissues and organs, mainly the kidney. We sought to determine if plasma cells producing these abnormal Ig could present specific phenotypes. The aim of the present study is to analyse the transcriptomic signature of plasma cells producing abnormal Ig free light chains.
2020-05-14 | GSE119048 | GEO
Project description:Cell-free RNAs in biofluids provide opportunities to monitor cancer in a non-invasive manner. Although extracellular microRNAs are extensively characterized, fragmented cell-free long RNAs are not well investigated. Here, we developed Detector-seq (depletion-assisted multiplexing cell-free total RNA sequencing) to enable the deciphering of the cell-free transcriptome. After demonstrating the superior performance of detecting fragmented cell-free long RNAs, we applied Detector-seq to compare cell-free RNAs in human plasma and its extracellular vesicle (EV). Distinct human and microbial RNA signatures were revealed. Structured circular RNA, tRNA, and Y RNA were enriched in plasma, while mRNA and srpRNA were enriched in EV. Meanwhile, cell-free RNAs derived from the virus were more enriched in plasma than in EV. We identified RNAs that showed a selective distribution between plasma and EV and uncovered their distinct functional pathways, that is RNA splicing, antimicrobial humoral response enriched in plasma and transcriptional activity, cell migration, and antigen receptor-mediated immune signals enriched in EV. Although distinctive cancer-relevant RNA signals were identified in plasma and EV, a comparable performance of distinguishing cancer patients from normal individuals could be achieved. Compared to human RNAs, microbe-derived RNA features enabled better classification between colorectal and lung cancer. And for these microbial RNAs, plasma RNAs outperformed EV RNAs for the discrimination of cancer types. Overall, our work provides insights into the unexplored difference of cell-free RNA signals between plasma and EV, thus offering practical guidance for proper selection (with/without EV enrichment) when launching an RNA-based liquid biopsy study. Furthermore, with the ability to capture understudied cell-free long RNA fragments, Detector-seq offers new possibilities for transcriptome-wide characterization of cell-free RNAs to facilitate the understanding of extracellular RNA biology and clinical advances of liquid biopsy.
2024-03-27 | GSE216561 | GEO
Project description:Cell-Free Plasma MicroRNAs that Identify Patients with Glioblastoma
| PRJNA764727 | ENA