External RNA Research Articles

Genomic progression for local invasion of cutaneous squamous cell carcinoma from the superficial to the deep portion.

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer. While many treatments exist, our understanding of its genomic progression, especially from the epidermis to the deep dermis, remains limited. This study aims to identify genetic mutations associated with the progression of cSCC into the deep dermis, providing insights into its aggressive behavior and high-risk features. We performed high-depth whole-exome sequencing on 12 cSCC tissues, along with paired normal tissues from six patients, using microdissection techniques. The mutational analysis focused on identifying alterations enriched during cSCC progression. Gene Ontology enrichment analysis, immunohistochemical assays, and external single-cell RNA data were utilized for validation. A total of 8863 non-synonymous somatic mutations were identified in 4092 genes across the superficial and deep portions of cSCCs. Analysis of deep portion mutations revealed a significant correlation with gene ontology biological processes, particularly cell junction organization, and cell-cell adhesion. Clonal mutations in these processes were more prevalent in the deep portions, indicating their impact on the cSCC mutation landscape. Genetic evolution analysis identified 29 causal genes associated with dermal invasion in cSCC. We highlight somatic mutations in cSCC, revealing heterogeneity between superficial and deep regions. Altered genes in cell junction organization and cell-cell adhesion emerged as pivotal in dermal invasion. We identified 29 causal genes primarily in deep tumor regions. Our findings emphasize analyzing multiple tumor regions to capture varied mutational landscapes. These insights advance our understanding of cSCC progression, emphasizing genetic and cellular changes during tumor evolution.

318 Profiling Long RNA Transcriptome From Circulating Extracellular Vesicles in Subarachnoid Hemorrhage for Biomarker Discovery

INTRODUCTION: Aneurysmal subarachnoid hemorrhage (aSAH) is associated with a high mortality rate and permanent neurological deficits following acute brain injury. Previous studies have aimed at investigating CNS specific biomarkers that can predict the outcomes following aSAH. Liquid biopsy represents a promising minimally invasive approach for biomarker discovery using biofluids (plasma, CSF). METHODS: CSF was collected from patients (n = 10) during in-hospital stay at multiple time points via the external ventricular drain and EV RNA was sequenced using Oxford Nanopore Technologies. RESULTS: We detected different biotypes in EV RNA with minimal rRNA contamination (protein coding; 58.4%, pseudogene; 23.1%, LncRNA; 10%, rRNA; 1.7%). This is the first study reporting presence of long (>500 bp) RNA transcripts in CSF derived EVs. Approximately, 80% of the sequenced reads were up to 500 bp long and 20% reads 500-10,000 bp long. Principal Component Analysis demonstrated distinct clustering of samples based on location (anterior vs. posterior circulation) and type of aneurysm (saccular, dissecting, bilobed). A set of protein coding genes (S100A9, EEF1A1, SCARNA1, DMTN) were found to be differentially enriched in patients who developed cerebral vasospasm (n = 6). Furthermore, for each patient there was a unique population of biomarkers upregulated in acute (HBB, COX2) vs. chronic (SEPTIN7, PDK4) immune response following aSAH. Preliminary findings reveal potential candidate biomarkers providing insight into the pathogenesis and prognosis. CONCLUSIONS: There is an unmet need for inclusion of diagnostic and predictive biomarkers in clinical management of aSAH to decrease the overall mortality. In this study, we overcame challenges of analyzing low input RNA using a sensitive and optimized sequencing platform. Validation and testing in a larger study population offers new opportunities for biomarker discovery.

A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning-expressed responses.

RNA-Sequencing is widely used to investigate changes in gene expression at the transcription level in plants. Most plant RNA-Seq analysis pipelines base the normalization approaches on the assumption that total transcript levels do not vary between samples. However, this assumption has not been demonstrated. In fact, many common experimental treatments and genetic alterations affect transcription efficiency or RNA stability, resulting in unequal transcript abundance. The addition of synthetic RNA controls is a simple correction that controls for variation in total mRNA levels. However, adding spike-ins appropriately is challenging with complex plant tissue, and carefully considering how they are added is essential to their successful use. We demonstrate that adding external RNA spike-ins as a normalization control produces differences in RNA-Seq analysis compared to traditional normalization methods, even between two times of day in untreated plants. We illustrate the use of RNA spike-ins with 3' RNA-Seq and present a normalization pipeline that accounts for differences in total transcriptional levels. We evaluate the effect of normalization methods on identifying differentially expressed genes in the context of identifying the effect of the time of day on gene expression and response to chilling stress in sorghum.

How tool combinations in different pipeline versions affect the outcome in RNA-seq analysis.

Data analysis tools are continuously changed and improved over time. In order to test how these changes influence the comparability between analyses, the output of different workflow options of the nf-core/rnaseq pipeline were compared. Five different pipeline settings (STAR+Salmon, STAR+RSEM, STAR+featureCounts, HISAT2+featureCounts, pseudoaligner Salmon) were run on three datasets (human, Arabidopsis, zebrafish) containing spike-ins of the External RNA Control Consortium (ERCC). Fold change ratios and differential expression of genes and spike-ins were used for comparative analyses of the different tools and versions settings of the pipeline. An overlap of 85% for differential gene classification between pipelines could be shown. Genes interpreted with a bias were mostly those present at lower concentration. Also, the number of isoforms and exons per gene were determinants. Previous pipeline versions using featureCounts showed a higher sensitivity to detect one-isoform genes like ERCC. To ensure data comparability in long-term analysis series it would be recommendable to either stay with the pipeline version the series was initialized with or to run both versions during a transition time in order to ensure that the target genes are addressed the same way.

Triosephosphate isomerase 1 may be a risk predictor in laryngeal squamous cell carcinoma: a multi-centered study integrating bulk RNA, single-cell RNA, and protein immunohistochemistry

BackgroundAlthough great progress has been made in anti-cancer therapy, the prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains unsatisfied. Quantities of studies demonstrate that glycolytic reprograming is essential for the progression of cancers, where triosephosphate isomerase 1 (TPI1) serves as a catalytic enzyme. However, the clinicopathological significance and potential biological functions of TPI1 underlying LSCC remains obscure.MethodsWe collected in-house 82 LSCC tissue specimens and 56 non-tumor tissue specimens. Tissue microarrays (TMA) and immunohistochemical (IHC) experiments were performed. External LSCC microarrays and bulk RNA sequencing data were integrated to evaluate the expression of TPI1. We used a log-rank test and the CIBERSORT algorithm to assess the prognostic value of TPI1 and its association with the LSCC microenvironment. Malignant laryngeal epithelial cells and immune-stromal cells were identified using inferCNV and CellTypist. We conducted a comprehensive analysis to elucidate the molecular functions of TPI1 in LSCC tissue and single cells using Pearson correlation analysis, high dimensional weighted gene co-expression analysis, gene set enrichment analysis, and clustered regularly interspaced short palindromic repeats (CRISPR) screen. We explored intercellular communication patterns between LSCC single cells and immune-stromal cells and predicted several therapeutic agents targeting TPI1.ResultsBased on the in-house TMA and IHC analysis, TPI1 protein was found to have a strong positive expression in the nucleus of LSCC cells but only weakly positive activity in the cytoplasm of normal laryngeal cells (p < 0.0001). Further confirmation of elevated TPI1 mRNA expression was obtained from external datasets, comparing 251 LSCC tissue samples to 136 non-LSCC tissue samples (standardized mean difference = 1.06). The upregulated TPI1 mRNA demonstrated a high discriminative ability between LSCC and non-LSCC tissue (area under the curve = 0.91; sensitivity = 0.87; specificity = 0.79), suggesting its potential as a predictive marker for poor prognosis (p = 0.037). Lower infiltration abundance was found for plasma cells, naïve B cells, monocytes, and neutrophils in TPI-high expression LSCC tissue. Glycolysis and cell cycle were significantly enriched pathways for both LSCC tissue and single cells, where heat shock protein family B member 1, TPI1, and enolase 1 occupied a central position. Four outgoing communication patterns and two incoming communication patterns were identified from the intercellular communication networks. TPI1 was predicted as an oncogene in LSCC, with CRISPR scores less than -1 across 71.43% of the LSCC cell lines. TPI1 was positively correlated with the half maximal inhibitory concentration of gemcitabine and cladribine.ConclusionsTPI1 is dramatically overexpressed in LSCC than in normal tissue, and the high expression of TPI1 may promote LSCC deterioration through its metabolic and non-metabolic functions. This study contributes to advancing our knowledge of LSCC pathogenesis and may have implications for the development of targeted therapies in the future.

Unmodificated stepless regulation of CRISPR/Cas12a multi-performance.

As CRISPR technology is promoted to more fine-divided molecular biology applications, its inherent performance finds it increasingly difficult to cope with diverse needs in these different fields, and how to more accurately control the performance has become a key issue to develop CRISPR technology to a new stage. Herein, we propose a CRISPR/Cas12a regulation strategy based on the powerful programmability of nucleic acid nanotechnology. Unlike previous difficult and rigid regulation of core components Cas nuclease and crRNA, only a simple switch of different external RNA accessories is required to change the reaction kinetics or thermodynamics, thereby finely and almost steplessly regulating multi-performance of CRISPR/Cas12a including activity, speed, specificity, compatibility, programmability and sensitivity. In particular, the significantly improved specificity is expected to mark advance the accuracy of molecular detection and the safety of gene editing. In addition, this strategy was applied to regulate the delayed activation of Cas12a, overcoming the compatibility problem of the one-pot assay without any physical separation or external stimulation, and demonstrating great potential for fine-grained control of CRISPR. This simple but powerful CRISPR regulation strategy without any component modification has pioneering flexibility and versatility, and will unlock the potential for deeper applications of CRISPR technology in many finely divided fields.

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model.

Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

The Inhibition and Variability of Two Different RT-qPCR Assays Used for Quantifying SARS-CoV-2 RNA in Wastewater

Faecal shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its subsequent detection in wastewater turned the spotlight onto wastewater-based epidemiology (WBE) for monitoring the coronavirus-disease 2019 (COVID-19) pandemic. WBE for SARS-CoV-2 has been deployed in 70 countries, providing insights into disease prevalence, forecasting and the spatiotemporal tracking and emergence of SARS-CoV-2 variants. Wastewater, however, is a complex sample matrix containing numerous reverse transcription quantitative PCR (RT-qPCR) inhibitors whose concentration and diversity are influenced by factors including population size, surrounding industry and agriculture and climate. Such differences in the RT-qPCR inhibitor profile are likely to impact the quality of data produced by WBE and potentially produce erroneous results.To help determine the possible impact of RT-qPCR assay on data quality, two assays employed by different laboratories within the UK’s SARS-CoV-2 wastewater monitoring programme were assessed in the Cefas laboratory in Weymouth, UK. The assays were based on Fast Virus (FV) and qScript (qS) chemistries using the same primers and probes, but at different concentrations and under different cycling conditions. Bovine serum albumin and MgSO4 were also added to the FV assay reaction mixture. Two-hundred and eighty-six samples were analysed, and an external control RNA (EC RNA)-based method was used to measure RT-qPCR inhibition. Compared with qS, FV showed a 40.5% reduction in mean inhibition and a 57.0% reduction in inter-sample inhibition variability. A 4.1-fold increase in SARS-CoV-2 quantification was seen for FV relative to qS; partially due (1.5-fold) to differences in reverse transcription efficiency and the use of a dsDNA standard. Analytical variability was reduced by 51.2% using FV while qS increased the number of SARS-CoV-2 negative samples by 2.6-fold. This study indicates the importance of thorough method optimisation for RT-qPCR-based WBE which should be performed using a selection of samples which are representative of the physiochemical properties of wastewater. Furthermore, RT-qPCR inhibition, analytical variability and reverse transcription efficiency should be key considerations during assay optimisation. A standardised framework for the optimisation and validation of WBE procedures should be formed including concessions for emergency response situations that would allow flexibility in the process to address the difficult balance between the urgency of providing data and the availability of resources.

Exogenous spike-in mouse RNAs for accurate differential gene expression analysis in barley using RT-qPCR.

Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) followed by the 2-ΔΔCt method is the most common way to measure transcript levels for relative gene expression assays. The quality of an RT-qPCR assay is dependent upon the identification and validation of reference genes to normalize gene expression data. The so-called housekeeping genes are commonly used as internal reference genes because they are assumed to be ubiquitously expressed at stable levels. Commonly, researchers do not validate their reference genes but rely on historical reference genes or previously validated genes from an unrelated experiment. Using previously validated reference genes to assess gene expression changes occurring during malting resulted in extensive variability. Therefore, a new method was tested and validated to circumvent the use of internal reference genes. Total mouse RNA was chosen as the external reference RNA and a suite of primer sets to putatively stable mouse genes was created to identify stably expressed genes for use as an external reference gene. cDNA was created by co-amplifying total mouse RNA, as an RNA spike-in, and barley RNA. When using the external reference genes to normalize malting gene expression data, standard deviations were significantly reduced and significant differences in transcript abundance were observed, whereas when using the internal reference genes, standard deviations were larger with no significant differences seen. Furthermore, external reference genes were more accurate at assessing expression levels in malting and developing grains, whereas the internal reference genes overestimated abundance in developing grains and underestimated abundance in malting grains.

Quantitative proteomic landscapes of primary and recurrent glioblastoma reveal a protumorigeneic role for FBXO2-dependent glioma-microenvironment interactions.

Recent efforts have described the evolution of glioblastoma from initial diagnosis to post-treatment recurrence on a genomic and transcriptomic level. However, the evolution of the proteomic landscape is largely unknown. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to characterize the quantitative proteomes of two independent cohorts of paired newly diagnosed and recurrent glioblastomas. Recurrence-associated proteins were validated using immunohistochemistry and further studied in human glioma cell lines, orthotopic xenograft models, and human organotypic brain slice cultures. External spatial transcriptomic, single-cell, and bulk RNA sequencing data were analyzed to gain mechanistic insights. Although overall proteomic changes were heterogeneous across patients, we identified BCAS1, INF2, and FBXO2 as consistently upregulated proteins at recurrence and validated these using immunohistochemistry. Knockout of FBXO2 in human glioma cells conferred a strong survival benefit in orthotopic xenograft mouse models and reduced invasive growth in organotypic brain slice cultures. In glioblastoma patient samples, FBXO2 expression was enriched in the tumor infiltration zone and FBXO2-positive cancer cells were associated with synaptic signaling processes. These findings demonstrate a potential role of FBXO2-dependent glioma-microenvironment interactions to promote tumor growth. Furthermore, the published datasets provide a valuable resource for further studies.

Staphylococcus aureus utilizes environmental RNA as a building material in specific polysaccharide-dependent biofilms

Biofilms are surface-bound microbial communities that are typically embedded in a matrix of self-produced extracellular polymeric substances and can cause chronic infections. Extracellular DNA is known to play a crucial role in biofilm development in diverse bacteria; however, the existence and function of RNA are poorly understood. Here, we show that RNA contributes to the structural integrity of biofilms formed by the human pathogen Staphylococcus aureus. RNase A dispersed both fresh and mature biofilms, indicating the importance of RNA at various stages. RNA-sequencing analysis demonstrated that the primary source of RNA in the biofilm matrix was the Brain Heart Infusion medium (>99.32%). RNA purified from the medium promoted biofilm formation. Microscopic and molecular interaction analyses demonstrated that polysaccharides were critical for capturing and stabilizing external RNA in biofilms, which contributes to biofilm organization. These findings provide a basis for exploring the role of externally derived substances in bacterial biofilm organization.

BioEssays 2/2022

BioEssaysVolume 44, Issue 2 2270003 COVER PICTUREFree Access BioEssays 2/2022 First published: 21 January 2022 https://doi.org/10.1002/bies.202270003AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Graphical Abstract In article 2100239, Anthony Monaco presents a revised model for organismal life incorporating coevolution, horizontal transfer, and inheritance of internal and external RNA and DNA pools. The author uses the Price Equation to model dynamic changes in both internal and external RNA pools from fluctuating environmental conditions and to relate this to phenotypic trait values and evolutionary change across generations. Volume44, Issue2February 20222270003 RelatedInformation

The selfish environment meets the selfish gene: Coevolution and inheritance of RNA and DNA pools: A model for organismal life incorporating coevolution, horizontal transfer, and inheritance of internal and external RNA and DNA pools.: A model for organismal life incorporating coevolution, horizontal transfer, and inheritance of internal and external RNA and DNA pools.

Throughout evolution, there has been interaction and exchange between RNA pools in the environment, and DNA and RNA pools of eukaryotic organisms. Metagenomic and metatranscriptomic sequencing of invertebrate hosts and their microbiota has revealed a rich evolutionary history of RNA virus shuttling between species. Horizontal transfer adapted the RNA pool for successful future interactions which lead to zoonotic transmission and detrimental RNA viral pandemics like SARS-CoV2. In eukaryotes, noncoding RNA (ncRNA) is an established mechanism derived from prokaryotes to defend against viral attack through innate immunity and regulation of host-derived mRNA. Transgenerational inheritance of ncRNA is evidence for feedforward adaptive immunity and epigenetically encoded environmental change across generations, which may explain the ''missing heritability'' of common disease. Causal graph theory and the Price Equation can model epigenetic inheritance involving dynamic internal and external RNA pools. Experimental designs should include metatranscriptomic analyses to understand how ncRNA responds to rapidly changing environmental conditions, within and between organisms, and across generations.

Accounting for technical noise in Bayesian graphical models of single-cell RNA-sequencing data.

Single-cell RNA-sequencing (scRNAseq) data contain a high level of noise, especially in the form of zero-inflation, that is, the presence of an excessively large number of zeros. This is largely due to dropout events and amplification biases that occur in the preparation stage of single-cell experiments. Recent scRNAseq experiments have been augmented with unique molecular identifiers (UMI) and External RNA Control Consortium (ERCC) molecules which can be used to account for zero-inflation. However, most of the current methods on graphical models are developed under the assumption of the multivariate Gaussian distribution or its variants, and thus they are not able to adequately account for an excessively large number of zeros in scRNAseq data. In this article, we propose a single-cell latent graphical model (scLGM)-a Bayesian hierarchical model for estimating the conditional dependency network among genes using scRNAseq data. Taking advantage of UMI and ERCC data, scLGM explicitly models the two sources of zero-inflation. Our simulation study and real data analysis demonstrate that the proposed approach outperforms several existing methods.

External dsRNA Downregulates Anthocyanin Biosynthesis-Related Genes and Affects Anthocyanin Accumulation in Arabidopsis thaliana.

Exogenous application of double-stranded RNAs (dsRNAs) and small-interfering RNAs (siRNAs) to plant surfaces has emerged as a promising method for regulation of essential genes in plant pathogens and for plant disease protection. Yet, regulation of plant endogenous genes via external RNA treatments has not been sufficiently investigated. In this study, we targeted the genes of chalcone synthase (CHS), the key enzyme in the flavonoid/anthocyanin biosynthesis pathway, and two transcriptional factors, MYBL2 and ANAC032, negatively regulating anthocyanin biosynthesis in Arabidopsis. Direct foliar application of AtCHS-specific dsRNAs and siRNAs resulted in an efficient downregulation of the AtCHS gene and suppressed anthocyanin accumulation in A. thaliana under anthocyanin biosynthesis-modulating conditions. Targeting the AtMYBL2 and AtANAC032 genes by foliar dsRNA treatments markedly reduced their mRNA levels and led to a pronounced upregulation of the AtCHS gene. The content of anthocyanins was increased after treatment with AtMYBL2-dsRNA. Laser scanning microscopy showed a passage of Cy3-labeled AtCHS-dsRNA into the A. thaliana leaf vessels, leaf parenchyma cells, and stomata, indicating the dsRNA uptake and spreading into leaf tissues and plant individual cells. Together, these data show that exogenous dsRNAs were capable of downregulating Arabidopsis genes and induced relevant biochemical changes, which may have applications in plant biotechnology and gene functional studies.

Stably expressed genes in single-cell RNA sequencing.

In single-cell RNA-sequencing (scRNA-seq) experiments, RNA transcripts are extracted and measured from isolated cells to understand gene expression at the cellular level. Measurements from this technology are affected by many technical artifacts, including batch effects. In analogous bulk gene expression experiments, external references, e.g. synthetic gene spike-ins often from the External RNA Controls Consortium (ERCC), may be incorporated to the experimental protocol for use in adjusting measurements for technical artifacts. In scRNA-seq experiments, the use of external spike-ins is controversial due to dissimilarities with endogenous genes and uncertainty about sufficient precision of their introduction. Instead, endogenous genes with highly stable expression could be used as references within scRNA-seq to help normalize the data. First, however, a specific notion of stable expression at the single-cell level needs to be formulated; genes could be stable in absolute expression, in proportion to cell volume, or in proportion to total gene expression. Different types of stable genes will be useful for different normalizations and will need different methods for discovery. We compile gene sets whose products are associated with cellular structures and record these gene sets for future reuse and analysis. We find that genes whose final products are associated with the cytosolic ribosome have expressions that are highly stable with respect to the total RNA content. Notably, these genes appear to be stable in bulk measurements as well. Supplementary data are available through GitHub (johanngb/sc-stable).

Miniaturization and optimization of 384-well compatible RNA sequencing library preparation.

Preparation of high-quality sequencing libraries is a costly and time-consuming component of metagenomic next generation sequencing (mNGS). While the overall cost of sequencing has dropped significantly over recent years, the reagents needed to prepare sequencing samples are likely to become the dominant expense in the process. Furthermore, libraries prepared by hand are subject to human variability and needless waste due to limitations of manual pipetting volumes. Reduction of reaction volumes, combined with sub-microliter automated dispensing of reagents without consumable pipette tips, has the potential to provide significant advantages. Here, we describe the integration of several instruments, including the Labcyte Echo 525 acoustic liquid handler and the iSeq and NovaSeq Illumina sequencing platforms, to miniaturize and automate mNGS library preparation, significantly reducing the cost and the time required to prepare samples. Through the use of External RNA Controls Consortium (ERCC) spike-in RNAs, we demonstrated the fidelity of the miniaturized preparation to be equivalent to full volume reactions. Furthermore, detection of viral and microbial species from cell culture and patient samples was also maintained in the miniaturized libraries. For 384-well mNGS library preparations, we achieved cost savings of over 80% in materials and reagents alone, and reduced preparation time by 90% compared to manual approaches, without compromising quality or representation within the library.

Up-regulation of RIP1 and IPS-1 in chronic HBV infected patients.

IPS-1 and RIP1 are the main downstream molecules of RIG1 and MDA5, as intracytoplasmic receptors, which are the main receptors involved in recognition of internal and external viral double-stranded RNA. In this project, mRNA levels of IPS-1 and RIP1 were investigated in the peripheral blood immune cells of chronic hepatitis B (CHB) patients. IPS-1 and RIP1 mRNA levels were measured in 60 CHB patients and 120 healthy subjects, using RT-qPCR technique. A significant increase in expression levels of IPS-1 and RIP1 was found in patients when compared to healthy individuals. There was no correlation between IPS-1 and RIP1expression levels with the serum levels of hepatitis B e-Antigen (HBeAg) and liver enzymes in patients. Based on the results, it seems that IPS-1 and RIP1 can participate in the induction of low chronic inflammation, which is a main cause of liver cirrhosis and hepatocellular carcinoma.

Analysis of Technical and Biological Variability in Single-Cell RNA Sequencing.

Profiling the transcriptomes of individual cells with single-cell RNA sequencing (scRNA-seq) has been widely applied to provide a detailed molecular characterization of cellular heterogeneity within a population of cells. Despite recent technological advances of scRNA-seq, technical variability of gene expression in scRNA-seq is still much higher than that in bulk RNA-seq. Accounting for technical variability is therefore a prerequisite for correctly analyzing single-cell data. This chapter describes a computational pipeline for detecting highly variable genes exhibiting higher cell-to-cell variability than expected by technical noise. The basic pipeline using the scater and scran R/Bioconductor packages includes deconvolution-based normalization, fitting the mean-variance trend, testing for nonzero biological variability, and visualization with highly variable genes. An outline of the underlying theory of detecting highly variable genes is also presented. We illustrate how the pipeline works by using two case studies, one from mouse embryonic stem cells with external RNA spike-ins, and the other from mouse dentate gyrus cells without spike-ins.

RNA Quality Control Using External Standard RNA.

In this paper, we propose a new evaluation method using external standard RNA for quality control of the extracted RNA. RNA Integrity Number and UV absorption are generally used as a basis for RNA quality control; however, these methods do not always reflect the quality of mRNA. While standard RNA is supposedly designed on the basis of mRNA, it has the potential to be used to evaluate the quality of the mRNA. In this study, we took into consideration the three essential factors, viz., yield of mRNA, inhibition to DNA polymerase, and degradation of mRNA for determining the RNA quality using standard RNA. It would be possible to know yield of mRNA and inhibition of the enzyme reaction by adding standard RNA before RNA extraction and looking at standard RNA loss. Degradation was evaluated by comparing the differences in the 3’ and 5’ regions of the RNA. In our study, it was demonstrated that in the crude extract of Saccharomyces cerevisiae, degradation was comparatively higher at the 3’ end of RNA than at the 5’ end. Hence, the degree of RNA degradation can be evaluated by comparing the ratio of degradation from the 3’ and 5’ end.