“…TIGER limits the analysis of non-host rDR to the kingdom level for counting, differential expression analysis and high-end analysis. Of note, some users may seek to avoid a defined host genome and map all quality reads to the provided non-host genome and library modules, as has been demonstrated by the exceRpt pipeline [21]. To perform this function with TIGER, define “search_host_genome = 0” during configuration.10.1080/20013078.2018.1506198-F0001Figure 1. Schematic of the TIGER sRNA-seq analysis workflow .…”
To comprehensively study extracellular small RNAs (sRNA) by sequencing (sRNA-seq), we developed a novel pipeline to overcome current limitations in analysis entitled, “Tools for Integrative Genome analysis of Extracellular sRNAs (TIGER)”. To demonstrate the power of this tool, sRNA-seq was performed on mouse lipoproteins, bile, urine and livers. A key advance for the TIGER pipeline is the ability to analyse both host and non-host sRNAs at genomic, parent RNA and individual fragment levels. TIGER was able to identify approximately 60% of sRNAs on lipoproteins and >85% of sRNAs in liver, bile and urine, a significant advance compared to existing software. Moreover, TIGER facilitated the comparison of lipoprotein sRNA signatures to disparate sample types at each level using hierarchical clustering, correlations, beta-dispersions, principal coordinate analysis and permutational multivariate analysis of variance. TIGER analysis was also used to quantify distinct features of exRNAs, including 5ʹ miRNA variants, 3ʹ miRNA non-templated additions and parent RNA positional coverage. Results suggest that the majority of sRNAs on lipoproteins are non-host sRNAs derived from bacterial sources in the microbiome and environment, specifically rRNA-derived sRNAs from Proteobacteria. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of extracellular RNA.
“…TIGER limits the analysis of non-host rDR to the kingdom level for counting, differential expression analysis and high-end analysis. Of note, some users may seek to avoid a defined host genome and map all quality reads to the provided non-host genome and library modules, as has been demonstrated by the exceRpt pipeline [21]. To perform this function with TIGER, define “search_host_genome = 0” during configuration.10.1080/20013078.2018.1506198-F0001Figure 1. Schematic of the TIGER sRNA-seq analysis workflow .…”
To comprehensively study extracellular small RNAs (sRNA) by sequencing (sRNA-seq), we developed a novel pipeline to overcome current limitations in analysis entitled, “Tools for Integrative Genome analysis of Extracellular sRNAs (TIGER)”. To demonstrate the power of this tool, sRNA-seq was performed on mouse lipoproteins, bile, urine and livers. A key advance for the TIGER pipeline is the ability to analyse both host and non-host sRNAs at genomic, parent RNA and individual fragment levels. TIGER was able to identify approximately 60% of sRNAs on lipoproteins and >85% of sRNAs in liver, bile and urine, a significant advance compared to existing software. Moreover, TIGER facilitated the comparison of lipoprotein sRNA signatures to disparate sample types at each level using hierarchical clustering, correlations, beta-dispersions, principal coordinate analysis and permutational multivariate analysis of variance. TIGER analysis was also used to quantify distinct features of exRNAs, including 5ʹ miRNA variants, 3ʹ miRNA non-templated additions and parent RNA positional coverage. Results suggest that the majority of sRNAs on lipoproteins are non-host sRNAs derived from bacterial sources in the microbiome and environment, specifically rRNA-derived sRNAs from Proteobacteria. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of extracellular RNA.
“…It has a great potential to identify and deliver biomedically significant information about a person and their blood relatives, thus creating practical challenges in research and clinical applications . However, in terms of saliva, this field encountered several problems in the past due to the low abundance of RNA in saliva compared to other biofluids as well as problems in RNA isolation from saliva, cDNA library construction, quality controls (QCs), and data analysis . Specifically, the bioinformatic analysis of salivary RNA‐Seq data is not trivial.…”
Section: Reflects On Saliva Diagnosis’s Challengesmentioning
confidence: 99%
“…18 However, in terms of saliva, this field encountered several problems in the past due to the low abundance of RNA in saliva compared to other biofluids as well as problems in RNA isolation from saliva, cDNA library construction, quality controls (QCs), and data analysis. 19 Specifically, the bioinformatic analysis of salivary RNA-Seq data is not trivial. 19 have recently presented the first guidelines on how to process bioinformatically the RNA-Seq data from saliva as saliva differs from other biofluids, such as urine or blood, due to the high content of microbiota, thus requiring a different analytical approach.…”
Section: Recent Technological Advances In Saliva Diagnosismentioning
confidence: 99%
“…19 Specifically, the bioinformatic analysis of salivary RNA-Seq data is not trivial. 19 have recently presented the first guidelines on how to process bioinformatically the RNA-Seq data from saliva as saliva differs from other biofluids, such as urine or blood, due to the high content of microbiota, thus requiring a different analytical approach.…”
Section: Recent Technological Advances In Saliva Diagnosismentioning
Saliva is an emerging biofluid for personalized/precision medicine application. As it has recently become a major tool for biological research and biomarker discovery, it is of vital importance to develop and optimize the diagnostics standards to decipher the omics constituents in saliva in order to achieve better oral and systemic health. Although current variations in saliva sampling, study designs, and developmental methods of salivary biomarkers prevent direct comparisons of the data obtained from different studies, the lack of standardization and unification of the processing procedures undermines saliva's diagnostic potential. Thus, it motivated us to propose the idea of creating an International Scientific Foundation of Salivary Diagnosis (ISFSD) that could encourage collaborative efforts to establish international guidelines and standardized protocols for saliva collection and laboratorial processing as well as clinical diagnostics. The ISFSD can accelerate the validation of biomarkers in larger groups of patients, their regulatory approval, and implementation of saliva diagnostics into a real clinical practice. It will also result in identification of practical and achievable priorities, and will present policy initiatives critical to the implementation of oral health improvement programs. The establishment of ISFSD will be of great interest and influence in the fields of oral health, dentistry, and medicine.
“…Transcript Abundance and Differential Expression Estimates for long RNA Prior to mapping for transcript-level quantification, to assess sample integrity all fastq files from long-RNA sequencing runs were uploaded to the Genboree workbench and mapped to hg19 and all exogenous genomes using the exceRpt [v4.6.3] small RNAseq pipeline(Kaczor-Urbanowicz et al, 2018;Rozowsky et al, 2019). Data quality assessment and read clipping was performed using TrimGalore [v0.4.1] withCutAdapt [v1.15] and FastQC[v0.11.6] …”
Graphical AbstractHighlights d GBM EVs and growth factors promote angiogenesis by distinct pathways d EV-exposed endothelial cells show a footprint of gene regulation by EV miRNAs d The EV miRNA pathway explains failure of anti-angiogenic therapy for GBM d The results suggest an angiogenic pathway and liquid biopsy biomarkers for GBM SUMMARY Glioblastoma (GBM) is characterized by aberrant vascularization and a complex tumor microenvironment. The failure of anti-angiogenic therapies suggests pathways of GBM neovascularization, possibly attributable to glioblastoma stem cells (GSCs) and their interplay with the tumor microenvironment. It has been established that GSC-derived extracellular vesicles (GSC-EVs) and their cargoes are proangiogenic in vitro. To further elucidate EV-mediated mechanisms of neovascularization in vitro, we perform RNA-seq and DNA methylation profiling of human brain endothelial cells exposed to GSC-EVs. To correlate these results to tumors in vivo, we perform histoepigenetic analysis of GBM molecular profiles in the TCGA collection. Remarkably, GSC-EVs and normal vascular growth factors stimulate highly distinct gene regulatory responses that converge on angiogenesis. The response to GSC-EVs shows a footprint of post-transcriptional gene silencing by EV-derived miRNAs. Our results provide insights into targetable angiogenesis pathways in GBM and miRNA candidates for liquid biopsy biomarkers.
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