Protocol to analyze circulating small non-coding RNAs by high-throughput RNA sequencing from human plasma samples.
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ABSTRACT:
SUBMITTER: Grieco GE
PROVIDER: S-EPMC8219884 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There are several protocols and kits for the extraction of circulating RNAs from plasma with a following quantification of specific genes via RT-qPCR. Due to the marginal amount of cell-free RNA in plasma samples, the total RNA yield is insufficient to perform Next-Generation Sequencing (NGS), the state-of-the-art technology in massive parallel sequencing that enables a comprehensive characterization of the whole transcriptome. Screening the transcriptome for biomarker signatures accelerates progress in biomarker profiling for molecular diagnostics, early disease detection or food safety. Therefore, the aim was to optimize a method that enables the extraction of sufficient amounts of total RNA from bovine plasma to generate good-quality small RNA Sequencing (small RNA-Seq) data. An increased volume of plasma (9 ml) was processed using the Qiagen miRNeasy Serum/Plasma Kit in combination with the QIAvac24 Plus system, a vacuum manifold that enables handling of high volumes during RNA isolation. 35 ng of total RNA were passed on to cDNA library preparation followed by small RNA high-throughput sequencing analysis on the Illumina HiSeq2000 platform. Raw sequencing reads were processed by a data analysis pipeline using different free software solutions. Seq-data was trimmed, quality checked, gradually selected for miRNAs/piRNAs and aligned to small RNA reference annotation indexes. Mapping to human reference indexes resulted in 4.8±2.8% of mature miRNAs and 1.4±0.8% of piRNAs and of 5.0±2.9% of mature miRNAs for bos taurus.
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Project description:MicroRNAs hold great promise as biomarkers of disease. However, there are few efficient and robust methods for measuring microRNAs from low input samples. Here, we develop a high-throughput sequencing protocol that efficiently captures small RNAs while minimizing inherent biases associated with library production. The protocol is based on early barcoding such that all downstream manipulations can be performed on a pool of many samples thereby reducing reagent usage and workload. We show that the optimization of adapter concentrations along with the addition of nucleotide modifications and random nucleotides increases the efficiency of small RNA capture. We further show, using unique molecular identifiers, that stochastic capture of low input RNA rather than PCR amplification influences the biased quantitation of intermediately and lowly expressed microRNAs. Our improved method allows the processing of tens to hundreds of samples simultaneously while retaining high efficiency quantitation of microRNAs in low input samples from tissues or bodily fluids.
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Project description:BACKGROUND: Small non-coding RNAs (sRNAs) play key roles in plant development, growth and responses to biotic and abiotic stresses. At least four classes of sRNAs have been well characterized in plants, including repeat-associated siRNAs (rasiRNAs), microRNAs (miRNAs), trans-acting siRNAs (tasiRNAs) and natural antisense transcript-derived siRNAs. Chinese fir (Cunninghamia lanceolata) is one of the most important coniferous evergreen tree species in China. No sRNA from Chinese fir has been described to date. RESULTS: To obtain sRNAs in Chinese fir, we sequenced a sRNA library generated from seeds, seedlings, leaves, stems and calli, using Illumina high throughput sequencing technology. A comprehensive set of sRNAs were acquired, including conserved and novel miRNAs, rasiRNAs and tasiRNAs. With BLASTN and MIREAP we identified a total of 115 conserved miRNAs comprising 40 miRNA families and one novel miRNA with precursor sequence. The expressions of 16 conserved and one novel miRNAs and one tasiRNA were detected by RT-PCR. Utilizing real time RT-PCR, we revealed that four conserved and one novel miRNAs displayed developmental stage-specific expression patterns in Chinese fir. In addition, 209 unigenes were predicted to be targets of 30 Chinese fir miRNA families, of which five target genes were experimentally verified by 5' RACE, including a squamosa promoter-binding protein gene, a pentatricopeptide (PPR) repeat-containing protein gene, a BolA-like family protein gene, AGO1 and a gene of unknown function. We also demonstrated that the DCL3-dependent rasiRNA biogenesis pathway, which had been considered absent in conifers, existed in Chinese fir. Furthermore, the miR390-TAS3-ARF regulatory pathway was elucidated. CONCLUSIONS: We unveiled a complex population of sRNAs in Chinese fir through high throughput sequencing. This provides an insight into the composition and function of sRNAs in Chinese fir and sheds new light on land plant sRNA evolution.
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Project description:The circulating microRNA (miRNA) profile has been widely used for identifying potential biomarkers against viral infections. However, data on circulating microRNA expression patterns in dengue patients are scanty. Considering the impact of severity caused by dengue infection, circulating miRNA profiles in plasma of dengue patients may prove to be valuable for developing early prognostic markers for the disease severity. Here, we described an in-depth analytical study of small RNA sequencing data obtained from the plasma of 39 dengue patients. Integrating bioinformatics and in vitro studies, we identified differentially expressed miRNAs (DEMs) (log2 fold change ?1.5, P?<?0.05) associated with dengue disease progression. In comparing miRNA expression pattern with the follow-up samples, nine miRNAs were found to exhibit an altered expression that could distinguish between severe dengue and the convalescent patients. To understand the abundance and specificity of the DEMs in the context of dengue infection and disease progression, eight top-hit DEMs were further validated in the dengue virus-infected cell lines as well as in the patient's plasma and peripheral blood mononuclear cells (PBMCs) using the quantitative reverse transcription-PCR (qRT-PCR) method. Importantly, receiver operating curve analysis further confirmed that the plasma expression pattern of hsa-miR-122-5p could differentiate between different stages of dengue infection (area under the concentration-time curve [AUC]?=?0.792), and dengue-negative patients with other febrile illnesses (AUC?=?0.984). The in silico analysis of DEM target genes suggested an enrichment of the pathways associated with metabolism and inflammation. Our study gives a global view of miRNA expression in the plasma from dengue patients and provides a precious resource of candidate miRNAs involved in dengue infection and disease progression.IMPORTANCE Dengue virus (DENV) infection usually causes dengue fever (DF) with flu-like illness affecting infants, young children, and adults. The DF occasionally evolves into a potentially lethal complication called dengue severe (DS) leading to a rapid fall in platelet count along with plasma leakage, fluid accumulation, respiratory distress, and severe bleeding. The diverse clinical spectrum of dengue disease, as well as its significant similarity to other febrile viral illnesses, makes early identification more challenging in this high-risk group. microRNAs (miRNAs) are small (?19 to 21?nucleotides [nt] in length), noncoding RNAs, extremely stable and easily detectable in the plasma; thus, they have potential as biomarkers for diagnosing and monitoring human diseases. This study provides a comprehensive analysis of miRNAs circulating in plasma of dengue virus-infected patients and identifies the miRNA signatures that have biomarker potential for dengue infection and disease progression.
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Project description:BACKGROUND: Plant small RNAs (sRNAs) associated with virulent virus infections have been reported by previous studies, while the involvement of sRNAs in latent virus infection remains largely uncharacterised. Apple trees show a high degree of resistance and tolerance to viral infections. We analysed two sRNA deep sequencing datasets, prepared from different RNA size fractions, to identify sRNAs involved in Apple stem grooving virus (ASGV) infection. RESULTS: sRNA analysis revealed virus-derived siRNAs (vsiRNAs) originating from two ASGV genetic variants. A vsiRNA profile for one of the ASGV variants was also generated showing an increase in siRNA production towards the 3' end of the virus genome. Virus-derived sRNAs longer than those previously analysed were also observed in the sequencing data. Additionally, tRNA-derived sRNAs were identified and characterised. These sRNAs covered a broad size-range and originated from both ends of the mature tRNAs as well as from their central regions. Several tRNA-derived sRNAs showed differential regulation due to ASGV infection. No changes in microRNA, natural-antisense transcript siRNA, phased-siRNA and repeat-associated siRNA levels were observed. CONCLUSIONS: This study is the first report on the apple sRNA-response to virus infection. The results revealed the vsiRNAs profile of an ASGV variant, as well as the alteration of the tRNA-derived sRNA profile in response to latent virus infection. It also highlights the importance of library preparation in the interpretation of high-throughput sequencing data.
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Project description:The surprising observation that virtually the entire human genome is transcribed means we know little about the function of many emerging classes of RNAs, except their astounding diversities. Traditional RNA function prediction methods rely on sequence or alignment information, which are limited in their abilities to classify the various collections of non-coding RNAs (ncRNAs). To address this, we developed Classification of RNAs by Analysis of Length (CoRAL), a machine learning-based approach for classification of RNA molecules. CoRAL uses biologically interpretable features including fragment length and cleavage specificity to distinguish between different ncRNA populations. We evaluated CoRAL using genome-wide small RNA sequencing data sets from four human tissue types and were able to classify six different types of RNAs with ∼80% cross-validation accuracy. Analysis by CoRAL revealed that microRNAs, small nucleolar and transposon-derived RNAs are highly discernible and consistent across all human tissue types assessed, whereas long intergenic ncRNAs, small cytoplasmic RNAs and small nuclear RNAs show less consistent patterns. The ability to reliably annotate loci across tissue types demonstrates the potential of CoRAL to characterize ncRNAs using small RNA sequencing data in less well-characterized organisms.
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