Standard RNA-seq Research Articles

Analyzing RNA-Seq data from Chlamydia with super broad transcriptomic activation: challenges, solutions, and implications for other systems

BackgroundRNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression.ResultsStandard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends. By incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection.ConclusionsThis study highlights the limitations of standard RNA-Seq analysis tools in scenarios with extensive transcriptomic activation, such as in Chlamydia spp. during early infection. Our revised normalization methods, incorporating host reads or total sequencing depth, provide a more accurate representation of gene expression dynamics. These approaches may inform similar adjustments in other systems with unbalanced gene expression dynamics, enhancing the accuracy of transcriptomic analysis.

Improved characterization of single-cell RNA-seq libraries with paired-end avidity sequencing.

Prevailing poly(dT)-primed 3' single-cell RNA-seq protocols generate barcoded cDNA fragments containing the reverse transcriptase priming site, which is expected to be the poly(A) tail or a genomic adenine homopolymer. Direct sequencing across this priming site was historically difficult because of DNA sequencing errors induced by the homopolymeric primer at the 'barcode' end. Here, we evaluate the capability of "avidity base chemistry" DNA sequencing from Element Biosciences to sequence through this homopolymer accurately, and the impact of the additional cDNA sequence on read alignment and precise quantification of polyadenylation site usage. We find that the Element Aviti instrument sequences through the thymine homopolymer into the subsequent cDNA sequence without detectable loss of accuracy. The resulting paired-end alignments enable direct and independent assignment of reads to polyadenylation sites, which bypasses complexities and limitations of conventional approaches but does not consistently improve read mapping rates compared to single-end alignment. We also characterize low-level artifacts and arrive at an adjusted adapter trimming and alignment workflow that significantly improves the alignment of sequence data from Element and Illumina, particularly in the context of extended read lengths. Our analyses confirm that Element avidity sequencing is an effective alternative to Illumina sequencing for standard single-cell RNA-seq, particularly for polyadenylation site analyses but do not rule out the potential for similar performance from other emerging platforms.

Transposase-Assisted RNA/DNA Hybrid Co-Tagmentation for Target Meta-Virome of Foodborne Viruses.

Foodborne diseases are major public health problems globally. Metagenomics has emerged as a widely used tool for pathogen screening. In this study, we conducted an updated Tn5 transposase-assisted RNA/DNA hybrid co-tagmentation (TRACE) library construction approach. To address the detection of prevalent known foodborne viruses and the discovery of unknown pathogens, we employed both specific primers and oligo-T primers during reverse transcription. The method was validated using clinical samples confirmed by RT-qPCR and compared with standard RNA-seq library construction methods. The mapping-based approach enabled the retrieval of nearly complete genomes (>95%) for the majority of virus genome segments (86 out of 88, 97.73%), with a mean coverage depth of 21,494.53× (ranging from 77.94× to 55,688.58×). Co-infection phenomena involving prevalent genotypes of Norovirus with Astrovirus and Human betaherpesvirus 6B were observed in two samples. The updated TRACE-seq exhibited superior performance in viral reads percentages compared to standard RNA-seq library preparation methods. This updated method has expanded its target pathogens beyond solely Norovirus to include other prevalent foodborne viruses. The feasibility and potential effectiveness of this approach were then evaluated as an alternative method for surveilling foodborne viruses, thus paving the way for further exploration into whole-genome sequencing of viruses.

Immunosuppression with cyclosporine versus tacrolimus shows distinctive nephrotoxicity profiles within renal compartments.

Calcineurin inhibitors (CNIs) are the backbone for immunosuppression after solid organ transplantation. Although successful in preventing kidney transplant rejection, their nephrotoxic side effects contribute to allograft injury. Renal parenchymal lesions occur for cyclosporine A (CsA) as well as for the currently favored tacrolimus (Tac). We aimed to study whether chronic CsA and Tac exposures, before reaching irreversible nephrotoxic damage, affect renal compartments differentially and whether related pathogenic mechanisms can be identified. CsA and Tac were administered chronically in wild type Wistar rats using osmotic minipumps over 4 weeks. Functional parameters were controlled. Electron microscopy, confocal, and 3D-structured illumination microscopy were used for histopathology. Clinical translatability was tested in human renal biopsies. Standard biochemical, RNA-seq, and proteomic technologies were applied to identify implicated molecular pathways. Both drugs caused significant albeit differential damage in vasculature and nephron. The glomerular filtration barrier was more affected by Tac than by CsA, showing prominent deteriorations in endothelium and podocytes along with impaired VEGF/VEGFR2 signaling and podocyte-specific gene expression. By contrast, proximal tubule epithelia were more severely affected by CsA than by Tac, revealing lysosomal dysfunction, enhanced apoptosis, impaired proteostasis and oxidative stress. Lesion characteristics were confirmed in human renal biopsies. We conclude that pathogenetic alterations in the renal compartments are specific for either treatment. Considering translation to the clinical setting, CNI choice should reflect individual risk factors for renal vasculature and tubular epithelia. As a step in this direction, we share protein signatures identified from multiomics with potential pathognomonic relevance.

Purification of Circular RNAs Using Poly(A) Tailing Followed by RNase R Digestion.

Thousands of eukaryotic protein-coding genes can be alternatively spliced to yield linear mRNAs and circular RNAs (circRNAs). Some circRNAs accumulate to higher levels than their cognate linear mRNAs, but the vast majority are expressed at low levels. Hence, for most circRNAs, only a handful of sequencing reads, if any, that span the backsplicing junction are observed in standard RNA-seq libraries. It thus has become common to use the 3'-5' exonuclease ribonuclease R (RNase R) to selectively degrade linear RNAs when aiming to prove transcript circularity or biochemically enrich circRNAs. However, RNase R fails to degrade linear RNAs with structured 3' ends or internal G-quadruplex structures. To overcome these shortcomings, we describe an improved protocol for circRNA purification from total RNA that employs a poly(A) tailing step prior to RNase R digestion, which is performed in a Li+ containing buffer (rather than K+) to destabilize G-quadruplexes. This biochemical method enables higher enrichment (two- to threefold) of circRNAs to be obtained compared to standard RNase R protocols due to more efficient removal of linear RNAs. By then performing quantitative RT-PCR (RT-qPCR) or generating RNA-seq libraries, the expression of individual circRNAs can be examined or the entire set of expressed circRNAs defined using established annotation algorithms. We describe step-by-step methods for annotating circRNAs using the CIRI2 and CIRCexplorer2 algorithms. In total, this overall approach can be used to enrich for circRNAs from any total RNA sample, thereby enabling one to quickly identify and validate circRNAs of interest for functional studies.

Broad variation in response of individual introns to splicing inhibitors in a humanized yeast strain.

Intron branchpoint (BP) recognition by the U2 snRNP is a critical step of splicing, vulnerable to recurrent cancer mutations and bacterial natural product inhibitors. The BP binds a conserved pocket in the SF3B1 (human) or Hsh155 (yeast) U2 snRNP protein. Amino acids that line this pocket affect the binding of splicing inhibitors like Pladienolide-B (Plad-B), such that organisms differ in their sensitivity. To study the mechanism of splicing inhibitor action in a simplified system, we modified the naturally Plad-B resistant yeast Saccharomyces cerevisiae by changing 14 amino acids in the Hsh155 BP pocket to those from human. This humanized yeast grows normally, and splicing is largely unaffected by the mutation. Splicing is inhibited within minutes after the addition of Plad-B, and different introns appear inhibited to different extents. Intron-specific inhibition differences are also observed during cotranscriptional splicing in Plad-B using single-molecule intron tracking to minimize gene-specific transcription and decay rates that cloud estimates of inhibition by standard RNA-seq. Comparison of Plad-B intron sensitivities to those of the structurally distinct inhibitor Thailanstatin-A reveals intron-specific differences in sensitivity to different compounds. This work exposes a complex relationship between the binding of different members of this class of inhibitors to the spliceosome and intron-specific rates of BP recognition and catalysis. Introns with variant BP sequences seem particularly sensitive, echoing observations from mammalian cells, where monitoring individual introns is complicated by multi-intron gene architecture and alternative splicing. The compact yeast system may hasten the characterization of splicing inhibitors, accelerating improvements in selectivity and therapeutic efficacy.

Ribosome Profiling of Plants.

Translation is a key step in control of gene expression, yet most analyses of global responses to a stimulus focus on transcription and the transcriptome. For RNA viruses in particular, which have no DNA-templated transcriptional control, control of viral and host translation is crucial. Here, we describe the method of ribosome profiling (ribo-seq) in plants, applied to virus infection. Ribo-seq is a deep sequencing technique that reveals the translatome by presenting a snapshot of the positions and relative amounts of translating ribosomes on all mRNAs in the cell. In contrast to RNA-seq, a crude cell extract is first digested with ribonuclease to degrade all mRNA not protected by a translating 80S ribosome. The resulting ribosome-protected fragments (RPFs) are deep sequenced. The number of reads mapping to a specific mRNA compared to the standard RNA-seq reads reveals the translational efficiency of that mRNA. Moreover, the precise positions of ribosome pause sites, previously unknown translatable open reading frames, and noncanonical translation events can be characterized quantitatively using ribo-seq. As this technique requires meticulous technique, here we present detailed step-by-step instructions for cell lysate preparation by flash freezing of samples, nuclease digestion of cell lysate, monosome collection by sucrose cushion ultracentrifugation, size-selective RNA extraction and rRNA depletion, library preparation for sequencing and finally quality control of sequenced data. These experimental methods apply to many plant systems, with minor nuclease digestion modifications depending on the plant tissue and species. This protocol should be valuable for studies of plant virus gene expression, and the global translational response to virus infection, or any other biotic or abiotic stress, by the host plant.

HIF-1 regulates common bidirectional gene expression changes during hypoxia and iron deficiency in human induced pluripotent stem cell derived cardiomyocytes

Abstract Background Heart failure regardless of cause is characterised by extensive transcriptional reprogramming and a switch to foetal developmental programmes via unknown mechanisms (1-3). An additional factor that adversely impacts heart failure patients is iron deficiency (ID)(4). ID is also associated with worse prognosis in acute coronary syndromes (5). However, the mechanisms by which ID interferes with clinical outcomes in heart disease remain incompletely understood. Purpose The purpose of this study was to investigate gene expression changes in human cardiomyocytes during hypoxia and ID, two important stressors in the context of ischaemia and heart failure. Methods In this study, we use human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) derived through a protocol that promotes left ventricle cardiomyocyte differentiation (6). Cells were harvested at different stages of differentiation (day 6 and day 32) and mature (day 32) hiPSC-CMs were treated with 30 μM deferoxamine to induce ID either under normoxic or hypoxic conditions with 1% O2. hiPSC contraction was assessed using musclemotion software and metabolism through use of a Seahorse extracellular flux analyser. RNA was isolated using standard isolation kits and RNA-seq (n=5) was performed. Data was analysed for gene expression by alignment with the human hg19 reference genome using the software STAR. A log2 fold change of 1 and P value of <0.0001 were considered significant. Results We show that both hypoxic and ID hiPSC-CMs demonstrate impaired contractility and reduced oxygen consumption, features of cardiomyocytes from failing hearts. Importantly, hiPSC-CMs exposed to hypoxia, ID or the combination of the two exhibit bidirectional gene expression changes with significant overlap (Figure 1). Focusing on the commonly affected gene set, it becomes evident that hypoxia & ID work via similar mechanisms involving activation of the HIF-1 pathway, that in turn orchestrates the metabolic switch to glycolysis and glutamine oxidation similar to foetal cells. Overall, hypoxia promotes a shift towards immature gene programmes, with 45% of dysregulated genes in hypoxia mimicking expression patterns of less mature cells. Interestingly changes in long non-coding RNA (lncRNA) profiles in hypoxia and ID mimic gene expression changes in these conditions (figure 2). Although restoring oxygen levels in hypoxic hiPSC-CMs rescues the hypoxic transcriptional signature, hiPSC-CMs previously exposed to hypoxia can use glycolytic pathways more efficiently upon further exposures to hypoxia. Conclusion These results shed light into the mechanisms ID impacts heart disease patients and are suggestive that HIF-1 is a key player in orchestrating the gene switch in ID and hypoxia.

Proteogenomics Reveal the Overexpression of HLA-I in Cancer.

An accurate quantification of HLA class I gene expression is important in understanding the interplay with the tumor microenvironment of antitumor cytotoxic T cell activities. Because HLA-I sequences are highly variable, standard RNAseq and mass spectrometry-based quantification workflows using common genome and protein sequence references do not provide HLA-I allele specific quantifications. Here, we used personalized HLA-I nucleotide and protein reference sequences based on the subjects' HLA-I genotypes and surveyed tumor and adjacent normal samples from patients across nine cancer types. Mass spectrometry using data dependent acquisition data was validated to be sufficient to estimate HLA-A protein expression at the allele level. We found that HLA-I proteins were present in significantly higher levels in tumors compared to adjacent normal tissues from 41 to 63% of head and neck squamous cell carcinoma, uterine corpus endometrial carcinoma, and clear cell renal cell carcinoma patients, and this was driven by increased levels of HLA-I gene transcripts. Most immune cell types are universally enriched in HLA-I high tumors, while endothelial and neuronal cells showed divergent relationships with HLA-I. Pathway analysis revealed that tumor senescence and autophagy activity influence the level of HLA-I proteins in glioblastoma. Genes correlated to HLA-I protein expression are mostly the ones directly involved in HLA-I function in immune response and cell death, while glycosylation genes are exclusively co-expressed with HLA-I at the protein level.

PD-L1 Expression by RNA-Sequencing in Non-Small Cell Lung Cancer: Concordance with Immunohistochemistry and Associations with Pembrolizumab Treatment Outcomes.

Programmed cell death ligand (PD-L1) expression by immunohistochemistry (IHC) lacks sensitivity for pembrolizumab immunotherapy selection in non-small cell lung cancer (NSCLC), particularly for tumors with low expression. We retrospectively evaluated transcriptomic PD-L1 by mRNA next-generation sequencing (RNA-seq). In an unselected NSCLC patient cohort (n = 3168) tested during standard care (2017-2021), PD-L1 IHC and RNA-seq demonstrated moderate concordance, with 80% agreement overall. Most discordant cases were either low or negative for PD-L1 expression by IHC but high by RNA-seq. RNA-seq accurately discriminated PD-L1 IHC high from low tumors by receiver operator curve (ROC) analysis but could not distinguish PD-L1 IHC low from negative tumors. In a separate pembrolizumab monotherapy cohort (n = 102), NSCLC tumors classified as PD-L1 high versus not high by RNA-seq had significantly improved response, progression-free survival, and overall survival as an individual measure and in combination with IHC high or low status. PD-L1 IHC status (high or low) trended toward but had no significant associations with improved outcomes. Conventional PD-L1 IHC testing has inherent limitations, making it an imperfect reference standard for evaluating novel testing technologies. RNA-seq offers an objective PD-L1 measure that could represent a complementary method to IHC to improve NSCLC patient selection for immunotherapy.

Feasibility of mass cytometry proteomic characterisation of circulating tumour cells in head and neck squamous cell carcinoma for deep phenotyping

BackgroundCirculating tumour cells (CTCs) are a potential cancer biomarker, but current methods of CTC analysis at single-cell resolution are limited. Here, we describe high-dimensional single-cell mass cytometry proteomic analysis of CTCs in HNSCC.MethodsParsortix microfluidic-enriched CTCs from 14 treatment-naïve HNSCC patients were analysed by mass cytometry analysis using 41 antibodies. Immune cell lineage, epithelial-mesenchymal transition (EMT), stemness, proliferation and immune checkpoint expression was assessed alongside phosphorylation status of multiple signalling proteins. Patient-matched tumour gene expression and CTC EMT profiles were compared. Standard bulk CTC RNAseq was performed as a baseline comparator to assess mass cytometry data.ResultsCTCs were detected in 13/14 patients with CTC counts of 2–24 CTCs/ml blood. Unsupervised clustering separated CTCs into epithelial, early EMT and advanced EMT groups that differed in signalling pathway activation state. Patient-specific CTC cluster patterns separated into immune checkpoint low and high groups. Patient tumour and CTC EMT profiles differed. Mass cytometry outperformed bulk RNAseq to detect CTCs and characterise cell phenotype.DiscussionWe demonstrate mass cytometry allows high-plex proteomic characterisation of CTCs at single-cell resolution and identify common CTC sub-groups with potential for novel biomarker development and immune checkpoint inhibitor treatment stratification.

3' RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism.

Introduction: The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Methods and results: Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. Conclusions: These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

Abstract 2107: Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens

Abstract Purpose: HTG EdgeSeq is a Next Generation Sequencing (NGS) based RNA Sequencing (RNA Seq) platform using a quantitative nuclease protection chemistry that enables extraction-free quantitation of mRNA/miRNAs with significantly reduces FFPE sample requirements compared to standard RNA-Seq, which makes it a feasible option for potential clinical applications. A customized gene panel was designed and developed for detection gene signatures. Procedure: The customized gene panel consists of 1327 genes, including 900 genes in signaling pathways in oncology & immuno-oncology, which including Nature Kill (NK) cells, neutrophils, Plasmacytoid dendritic cells (pDCs), DCs, monocytes, Tregs, B cells, tumor associated macrophages (TAMs), TGFβ, EMT, interferon-γ signature, IL-17, β-catenin etc. and 15 house-keeping genes. The validation included in silico probe design, feasibility testing, data comparison with The Cancer Genome Atlas (TCGA) and precision studies in six cancer indications including: Non-Small-Cell Lung Cancer (NSCLC), Head and Neck Squamous Cell Carcinoma (HNSCC), Hepatocellular Carcinoma (HCC), Colorectal Cancer (CRC), gastric cancer (OC), ovarian cancer (GC). Data Summary: After the In-silico probe design for all genes the custom probe pool for quality control test in biological samples was performed by evaluating directional and expected expression of 1327 selected genes in 59 FFPE samples from six indications. All probes performed as expected according to specification; gene expression signatures data were consistent with the different cancer indication tested. Expected differential expression of the selected genes was based on RNA-Seq data as reported in TCGA. In addition, principal component analysis (PCA) performed on the entire data et, showed a distinct clustering of samples by indication, demonstrating that the custom panel was able to reliably identify each indication. For the validation, precision studies including inter-well, inter-day, inter-processor, inter-sequencer and site-to-site comparisons were performed using FFPE tissue lysate pools prepared from each of the 6 indications. Predefined acceptance criteria are ≥ 90% of all Lin`s Concordance Correlation Coefficients (LCCC) comparisons to be greater than 0.90. The results showed that the predefined acceptance criteria were met, which are 95.9% of LCCC > 0.90 for inter-well repeatability, and 100% of LCCC >0.90 for inter-day, inter-processor, inter-sequencer and inter-site comparisons. Conclusions: The designed panel met all the predefined quality and analytical acceptance criteria, also, the reported results is corrected with TCGA RNA-Seq data, and the precision studies confirmed its performance. Customized gene panel can be possibly utilized for potential predictive and prognostic biomarkers identification to inform new cancer therapies development. Citation Format: Vittorio D'Urso, Dorothee Foernzler, Dennis O’Rourke, Danyi Wang, Jorge F Sanchez-Garcia, Heidi Giese, Thomas Clarke IV, XiaoZhe (Janet) Wang, Andreas Machl, Ti Cai, Juergen Scheuenpflug, Zheng Feng. Development a customized panel with clinical application potential for transcriptome analyses in selected cancer types using FFPE specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2107.

High-throughput transcriptional profiling of perturbations by Panax ginseng saponins and Panax notoginseng saponins using TCM-seq

Panax ginseng (PG) and Panax notoginseng (PN) are highly valuable Chinese medicines (CM). Although both CMs have similar active constituents, their clinical applications are clearly different. Over the past decade, RNA sequencing (RNA-seq) analysis has been employed to investigate the molecular mechanisms of extracts or monomers. However, owing to the limited number of samples in standard RNA-seq, few studies have systematically compared the effects of PG and PN spanning multiple conditions at the transcriptomic level. Here, we developed an approach that simultaneously profiles transcriptome changes for multiplexed samples using RNA-seq (TCM-seq), a high-throughput, low-cost workflow to molecularly evaluate CM perturbations. A species-mixing experiment was conducted to illustrate the accuracy of sample multiplexing in TCM-seq. Transcriptomes from repeated samples were used to verify the robustness of TCM-seq. We then focused on the primary active components, Panax notoginseng saponins (PNS) and Panax ginseng saponins (PGS) extracted from PN and PG, respectively. We also characterized the transcriptome changes of 10 cell lines, treated with four different doses of PNS and PGS, using TCM-seq to compare the differences in their perturbing effects on genes, functional pathways, gene modules, and molecular networks. The results of transcriptional data analysis showed that the transcriptional patterns of various cell lines were significantly distinct. PGS exhibited a stronger regulatory effect on genes involved in cardiovascular disease, whereas PNS resulted in a greater coagulation effect on vascular endothelial cells. This study proposes a paradigm to comprehensively explore the differences in mechanisms of action between CMs based on transcriptome readouts.

SLAM-seq reveals early transcriptomic response mechanisms upon glutamine deprivation in Chinese hamster ovary cells.

Mammalian cells frequently encounter subtle perturbations during recombinant protein production. Identifying the genetic factors that govern the cellular stress response can facilitate targeted genetic engineering to obtain production cell lines that demonstrate a higher stress tolerance. To simulate nutrient stress, Chinese hamster ovary (CHO) cells were transferred into a glutamine(Q)-free medium and transcriptional dynamics using thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) along with standard RNA-seq of stressed and unstressed cells were investigated. The SLAM-seq method allows differentiation between actively transcribed, nascent mRNA, and total (previously present) mRNA in the sample, adding an additional, time-resolved layer to classic RNA-sequencing. The cells tackle amino acid (AA) limitation by inducing the integrated stress response (ISR) signaling pathway, reflected in Atf4 overexpression in the early hours post Q deprivation, leading to subsequent activation of its targets, Asns, Atf3, Ddit3, Eif4ebp1, Gpt2, Herpud1, Slc7a1, Slc7a11, Slc38a2, Trib3, and Vegfa. The GCN2-eIF2α-ATF4 pathway is confirmed by a significant halt in transcription of translation-related genes at 24 h post Q deprivation. The downregulation of lipid synthesis indicates the inhibition of the mTOR pathway, further confirmed by overexpression of Sesn2. Furthermore, SLAM-seq detects short-lived transcription factors, such as Egr1, that would have been missed in standard experimental designs with RNA-seq. Our results describe the successful establishment of SLAM-seq in CHO cells and therefore facilitate its future use in other scenarios where dynamic transcriptome profiling in CHO cells is essential.

Genes associated with diagnosis and prognosis of Burkitt lymphoma.

Burkitt lymphoma (BL) is one of the most aggressive forms of non-Hodgkin's lymphomas that affect children and young adults. The expression of genes and other molecular markers during carcinogenesis can be the basis for diagnosis, prognosis and the design of new and effective drugs for the management of cancers. The aim of this study was to identify genes that can serve as prognostic and therapeutic targets for BL. We analysed RNA-seq data of BL transcriptome sequencing projects in Africa using standard RNA-seq analyses pipeline. We performed pathway enrichment analyses, protein-protein interaction networks, gene co-expression and survival analyses. Gene and pathway enrichment analyses showed that the differentially expressed genes are involved in tube development, signalling receptor binding, viral protein interaction, cell migration, external stimuli response, serine hydrolase activity and PI3K-Akt signalling pathway. Protein-protein interaction network analyses revealed the genes to be highly interconnected, whereas module analyses revealed 25 genes to possess the highest interaction score. Overall survival analyses delineated six genes (ADAMTSL4, SEMA5B, ADAMTS15, THBS2, SPON1 and THBS1) that can serve as biomarkers for prognosis for BL management.

Using single-worm RNA sequencing to study C. elegans responses to pathogen infection

BackgroundCaenorhabditis elegans is an excellent research model whose populations have been used in many studies to address various biological questions. Although worm-to-worm phenotypic variations in isogenic populations have been persistently observed, they are not well understood and are often ignored or averaged out in studies, masking the impacts of such variations on data collection and interpretation. Single-worm RNA sequencing that profiles the transcriptomes of individual animals has the power to examine differences between individuals in a worm population, but this approach has been understudied. The integrity of the starting RNA, the quality of the library and sequence data, as well as the transcriptome-profiling effectiveness of single-worm RNA-seq remain unclear. Therefore, more studies are needed to improve this technique and its application in research.ResultsIn this study, we aimed to develop a single-worm RNA-seq method that includes five steps: worm lysis and RNA extraction, cDNA synthesis, library preparation, sequencing, and sequence data analysis. We found that the mechanical lysis of worms using a Qiagen TissueLyser maintained RNA integrity and determined that the quality of our single-worm libraries was comparable to that of standard RNA-seq libraries based on assessments of a variety of parameters. Furthermore, analysis of pathogen infection-induced gene expression using single-worm RNA-seq identified a core set of genes and biological processes relating to the immune response and metabolism affected by infection. These results demonstrate the effectiveness of our single-worm RNA-seq method in transcriptome profiling and its usefulness in addressing biological questions.ConclusionsWe have developed a single-worm RNA-seq method to effectively profile gene expression in individual C. elegans and have applied this method to study C. elegans responses to pathogen infection. Key aspects of our single-worm RNA-seq libraries were comparable to those of standard RNA-seq libraries. The single-worm method captured the core set of, but not all, infection-affected genes and biological processes revealed by the standard method, indicating that there was gene regulation that is not shared by all individuals in a population. Our study suggests that combining single-worm and standard RNA-seq approaches will allow for detecting and distinguishing shared and individual-specific gene activities in isogenic populations.

Abstract LB130: High-throughput RNA sequencing directly from cell lysates enables reproducible phenotypic profiling for assessing novel compounds and treatments in cancer research

Abstract New oncology therapies are driven by multiple approaches, with a heavy emphasis on small-molecule therapeutics to target cancer cells and provide a therapeutic benefit to cancer patients. These small-molecule compounds can be used as a stand-alone treatment approach or may be combined with other compounds to bring enhanced effects. Compound therapeutic discovery relies heavily on high-throughput screening assays for measurement of phenotypic responses following compound treatment of oncology cell cultures which can range from very targeted assays to wide-ranging unbiased approaches. Standard whole transcriptome RNA-seq is a preferred method for unbiased measurement of phenotypic responses but is often overlooked due to limited scalability and high sample screening costs. To address these challenges, we have developed a high-throughput gene expression (HT-GEx) assay that combines a variety of strategies to enable a low-cost and high-throughput alternative to standard RNA-seq. First, a simplified workflow removes upstream RNA isolation steps and tags transcripts directly from cell lysate. This is achieved by incorporating both a sample barcode and a unique molecular index (UMI) during the reverse transcription reaction. Next, we leverage a 3’ end counting approach to enable a reduction in sequencing depth coverage (i.e. sample cost) without compromising gene detection sensitivity. With these key advances, a high-plex and high-throughput screening assay is achievable at a reduced cost by removing the need to purify RNA, tagging transcripts early in the workflow to allow pooling of samples and reducing sequencing depth. We have combined these high-throughput and cost-saving strategies and present results which confirm HT-GEx offers results on par with standard RNA-seq. Gene detection sensitivity based on number of genes detected per millions of reads is highly similar, with gene detection sensitivity saturated at approximately 2 million reads. Additionally, the number of genes detected between replicates for RNA samples and lysate samples demonstrate strong linear correlation, implying highly reproducible results. Thus, high-throughput gene expression is an ideal method for phenotypic screening in oncology cell lines following stand-alone or combined compound treatments. Citation Format: Andrea O'Hara, Michael Stephens, Ilaria DeVito, Laure Turner, Christopher Mozdzierz, Haythem Latif, Ginger Zhou. High-throughput RNA sequencing directly from cell lysates enables reproducible phenotypic profiling for assessing novel compounds and treatments in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB130.

Minimally Invasive Skin Transcriptome Extraction Using a Dermal Biomarker Patch.

IntroductionAdvances in the scientific understanding of the skin and characteristic genomic dermal signatures continue to develop rapidly. Nonetheless, skin diagnosis remains predicated on a subjective visual examination, frequently followed by biopsy and histology. These procedures often are not sufficiently sensitive, and in the case of many inflammatory diseases, biopsies are not justified, creating a situation where high-quality samples can be difficult to obtain. The wealth of molecular information available and the pace at which new data are acquired suggest that methods for minimally invasive biomarker collection could dramatically alter our understanding of skin disease and positively impact treatment paradigms.MethodsA chemical method was optimized to covalently modify custom dermal patches with single-stranded DNA that could bind to messenger RNA. These patches were applied to ex vivo skin samples and penetration evaluated by histological methods. Patches were then applied to both the skin of normal human subjects (lower arm) as well as lesional skin of psoriasis patients, and the transcriptome captured (N = 7; 33 unique samples). Standard RNA-Seq processing was performed to assess the gene detection rate and assessments made of the reproducibility of the extraction procedure as well as the overlap with matched punch biopsy samples from the same patient.ResultsWe have developed a dermal biomarker patch (DBP) designed to be minimally invasive and extract the dermal transcriptome. Using this platform, we have demonstrated successful molecular analysis from healthy human skin and psoriatic lesions, replicating the molecular information captured with punch biopsy.ConclusionThis DBP enables an unprecedented ability to monitor the molecular “fingerprint” of the skin over time or with various interventions, and generate previously inaccessible rich datasets. Furthermore, use of the DBP could be favored by patients relative to biopsy by limiting pain resulting from biopsy procedures. Given the large dynamic range observed in psoriatic skin, analysis of complex phenotypes is now possible, and the power of machine-learning methods can be brought to bear on dermatologic disease.

Making Invisible RNA Visible: Discriminative Sequencing Methods for RNA Molecules with Specific Terminal Formations.

Next generation sequencing of RNA molecules (RNA-seq) has become a common tool to characterize the expression profiles of RNAs and their regulations in normal physiological processes and diseases. Although increasingly accumulating RNA-seq data are widely available through publicly accessible sites, most of the data for short non-coding RNAs (sncRNAs) have been obtained for microRNA (miRNA) analyses by standard RNA-seq, which only capture the sncRNAs with 5′-phosphate (5′-P) and 3′-hydroxyl (3′-OH) ends. The sncRNAs with other terminal formations such as those with a 5′-hydroxyl end (5′-OH), a 3′-phosphate (3′-P) end, or a 2′,3′-cyclic phosphate end (2′,3′-cP) cannot be efficiently amplified and sequenced by standard RNA-seq. Due to the invisibility in standard RNA-seq data, these non-miRNA-sncRNAs have been a hidden component in the transcriptome. However, as the functional significances of these sncRNAs have become increasingly apparent, specific RNA-seq methods compatible with various terminal formations of sncRNAs have been developed and started shedding light on the previously unrecognized sncRNAs that lack 5′-P/3′-OH ends. In this review, we summarize the expanding world of sncRNAs with various terminal formations and the strategic approaches of specific RNA-seq methods to distinctively characterize their expression profiles.