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Background: RNA sequencing is a vital technique for analyzing RNA behavior in cells, but it often suffers from various biases that distort the data. Traditional methods to address these biases are typically empirical and handle them individually, limiting their effectiveness. Our study introduces the Gaussian Self-Benchmarking (GSB) framework, a novel approach that leverages the natural distribution patterns of guanine (G) and cytosine (C) content in RNA to mitigate multiple biases simultaneously. This method is grounded in a theoretical model, organizing k-mers based on their GC content and applying a Gaussian model for alignment to ensure empirical sequencing data closely match their theoretical distribution., Results: The GSB framework demonstrated superior performance in mitigating sequencing biases compared to existing methods. Testing with synthetic RNA constructs and real human samples showed that the GSB approach not only addresses individual biases more effectively but also manages co-existing biases jointly. The framework's reliance on accurately pre-determined parameters like mean and standard deviation of GC content distribution allows for a more precise representation of RNA samples. This results in improved accuracy and reliability of RNA sequencing data, enhancing our understanding of RNA behavior in health and disease., Conclusions: The GSB framework presents a significant advancement in RNA sequencing analysis by providing a well-validated, multi-bias mitigation strategy. It functions independently from previously identified dataset flaws and sets a new standard for unbiased RNA sequencing results. This development enhances the reliability of RNA studies, broadening the potential for scientific breakthroughs in medicine and biology, particularly in genetic disease research and the development of targeted treatments., (© 2024. The Author(s).)

A pterygium is a common conjunctival degeneration and inflammatory condition. It grows onto the corneal surface or limbus, causing blurred vision and cosmetic issues. Ultraviolet is a well-known risk factor for the development of a pterygium, although its pathogenesis remains unclear, with only limited understanding of its hereditary basis. In this study, we collected RNA-seq from both pterygial tissues and conjunctival tissues (as controls) from six patients (a total of twelve biological samples) and retrieved publicly available data, including eight pterygium samples and eight controls. We investigated the intrinsic gene regulatory mechanisms closely linked to the inflammatory reactions of pterygiums and compared Asian (Korea) and the European (Germany) pterygiums using multiple analysis approaches from different perspectives. The increased expression of antioxidant genes in response to oxidative stress and DNA damage implies an association between these factors and pterygium development. Also, our comparative analysis revealed both similarities and differences between Asian and European pterygiums. The decrease in gene expressions involved in the three primary inflammatory signaling pathways-JAK/STAT, MAPK, and NF-kappa B signaling-suggests a connection between pathway dysfunction and pterygium development. We also observed relatively higher activity of autophagy and antioxidants in the Asian group, while the European group exhibited more pronounced stress responses against oxidative stress. These differences could potentially be necessitated by energy-associated pathways, specifically oxidative phosphorylation.

RNA sequencing (RNA-seq) analysis of virus-infected host cells enables researchers to study a wide range of phenomena involving host-virus interactions. This includes genomic analysis of the viral population itself, as well as analysis of the transcriptional dynamics of the virus and host during infection. In this chapter, we provide a guide for researchers interested in performing RNA-seq data analysis of virus-infected host cells or cell lines. We outline several bioinformatic protocols for quantifying viral abundance, assembling viral genomes from mixed samples, and performing differential expression analysis, among other common workflows. These workflows can be used as starting points for researchers aiming to analyze RNA-seq datasets of mixed samples containing both host and viral RNA, such as virus-infected cell lines or clinical samples., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Obesity is becoming an epidemic of widespread concern, but the underlying causes remain elusive. In this study, whole transcriptome RNA sequencing revealed differential profiles of noncoding (nc) RNAs and mRNAs in visceral adipose tissue from obese (BMI > 32.5 kg/m 2 ) and lean (BMI < 20 kg/m 2 ) individuals, with 1920 differentially expressed genes, 1466 long noncoding (lnc) RNAs, 122 micro (mi) RNAs, and 52 circular (circ) RNAs identified. Gene Set Enrichment Analysis, Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis revealed that these ncRNAs were involved in inflammation-related pathways that included cytokine-cytokine receptor interaction, the tumor necrosis factor and nuclear factor kappa B signaling pathways. The results indicated a critical role of inflammation in the pathogenesis of obesity. The network interaction of lncRNA, circRNA, and miRNA revealed a competing endogenous (ce) RNA network that was associated with inflammation. The ceRNA network included circORC5/miR-197-5p/TNFRSF10D and circNTRK2/miR-760/LAT, which were dysregulated in obese patients. In conclusion, this whole transcriptome study provided a pool of data that will be useful for identifying biomarkers of obesity and identified an obesity-associated ceRNA network that is regulated by circORC5 and circNTRK2., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

For a global epidemic like Type 2 diabetes mellitus (T2DM), while impaired gene regulation is identified as a primary cause of aberrant cellular physiology; in the past few years, non-coding RNAs (ncRNAs) have emerged as important regulators of cellular metabolism. However, there are no reports of comprehensive in-depth cross-talk between these regulatory elements and the potential consequences in the skeletal muscle during diabetes. Here, using RNA sequencing, we identified 465 mRNAs and 12 long non-coding RNAs (lncRNAs), to be differentially regulated in the skeletal muscle of diabetic mice and pathway enrichment analysis of these altered transcripts revealed pathways of insulin, FOXO and AMP-activated protein kinase (AMPK) signaling to be majorly over-represented. Construction of networks showed that these pathways significantly interact with each other that might underlie aberrant skeletal muscle metabolism during diabetes. Gene-gene interaction network depicted strong interactions among several differentially expressed genes (DEGs) namely, Prkab2, Irs1, Pfkfb3, Socs2 etc. Seven altered lncRNAs depicted multiple interactions with the altered transcripts, suggesting possible regulatory roles of these lncRNAs. Inverse patterns of expression were observed between several of the deregulated microRNAs (miRNAs) and the differentially expressed transcripts in the tissues. Towards validation, overexpression of miR-381-3p and miR-539-5p in skeletal muscle C2C12 cells significantly decreased the transcript levels of their targets, Nfkbia, Pik3r1 and Pi3kr1, Cdkn2d, respectively. Collectively, the findings provide a comprehensive understanding of the interactions and cross-talk between the ncRNome and transcriptome in the skeletal muscle during diabetes and put forth potential therapeutic options for improving insulin sensitivity., (© 2021 The Author(s).)

The pathogenic mechanisms underlying severe SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection remain largely unelucidated. High-throughput sequencing technologies that capture genome and transcriptome information are key approaches to gain detailed mechanistic insights from infected cells. These techniques readily detect both pathogen- and host-derived sequences, providing a means of studying host-pathogen interactions. Recent studies have reported the presence of host-virus chimeric (HVC) RNA in transcriptome sequencing (RNA-seq) data from SARS-CoV-2-infected cells and interpreted these findings as evidence of viral integration in the human genome as a potential pathogenic mechanism. Since SARS-CoV-2 is a positive-sense RNA virus that replicates in the cytoplasm, it does not have a nuclear phase in its life cycle. Thus, it is biologically unlikely to be in a location where splicing events could result in genome integration. Therefore, we investigated the biological authenticity of HVC events. In contrast to true biological events like mRNA splicing and genome rearrangement events, which generate reproducible chimeric sequencing fragments across different biological isolates, we found that HVC events across >100 RNA-seq libraries from patients with coronavirus disease 2019 (COVID-19) and infected cell lines were highly irreproducible. RNA-seq library preparation is inherently error prone due to random template switching during reverse transcription of RNA to cDNA. By counting chimeric events observed when constructing an RNA-seq library from human RNA and spiked-in RNA from an unrelated species, such as the fruit fly, we estimated that ∼1% of RNA-seq reads are artifactually chimeric. In SARS-CoV-2 RNA-seq, we found that the frequency of HVC events was, in fact, not greater than this background "noise." Finally, we developed a novel experimental approach to enrich SARS-CoV-2 sequences from bulk RNA of infected cells. This method enriched viral sequences but did not enrich HVC events, suggesting that the majority of HVC events are, in all likelihood, artifacts of library construction. In conclusion, our findings indicate that HVC events observed in RNA-sequencing libraries from SARS-CoV-2-infected cells are extremely rare and are likely artifacts arising from random template switching of reverse transcriptase and/or sequence alignment errors. Therefore, the observed HVC events do not support SARS-CoV-2 fusion to cellular genes and/or integration into human genomes. IMPORTANCE The pathogenic mechanisms underlying SARS-CoV-2, the virus responsible for COVID-19, are not fully understood. In particular, relatively little is known about the reasons some individuals develop life-threatening or persistent COVID-19. Recent studies identified host-virus chimeric (HVC) reads in RNA-sequencing data from SARS-CoV-2-infected cells and suggested that HVC events support potential "human genome invasion" and "integration" by SARS-CoV-2. This suggestion has fueled concerns about the long-term effects of current mRNA vaccines that incorporate elements of the viral genome. SARS-CoV-2 is a positive-sense, single-stranded RNA virus that does not encode a reverse transcriptase and does not include a nuclear phase in its life cycle, so some doubts have rightfully been expressed regarding the authenticity of HVCs and the role played by endogenous retrotransposons in this phenomenon. Thus, it is important to independently authenticate these HVC events. Here, we provide several lines of evidence suggesting that the observed HVC events are likely artifactual.

The molecular basis of the mechanism and the potential biomarkers of endometrial cancer (EC) remain to be studied. In the present study, we hypothesized that the comprehensive characterization of transcriptional changes in EC could help achieve this aim. By taking advantage of RNA-seq data from The Cancer Genome Atlas, we determined the profile of differently expressed genes (DEGs) between EC tumor tissues and normal samples. On this basis, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analyses. The interacting partners for each of the DEGs were explored and a protein-protein interaction network was constructed. Consequently, 10 hub genes were identified and their association with mortality in EC patients was investigated. The genes, AURKA, CENPA, and KIF2C, were found to be potential biomarkers for EC with a significant prognostic effect. Our work provided a basis for EC studies in both biological and clinical settings., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Sophisticated cross-talk between bone marrow mesenchymal stromal cells (BM MSCs) and haematopoietic/leukaemic stem cells in patients with myelodysplastic syndromes (MDS) and myeloid leukaemia have been emphasized in previous reports. However, mesenchymal elements in patients with chronic myelomonocytic leukaemia (CMML) were poorly investigated. By utilizing a parallel RNA-sequencing method, we investigated the transcriptional profile and functional defects of primary BM MSCs from patients with CMML for the first time. Within a 24-patient cohort, transcriptional and functional analysis reveals a prominent enrichment of WNT/β-catenin signalling and multiple biology processes. Deregulated expression of WNT/β-catnin factors CTNNB1, CMYC, LEF1, and FRZB is associated with impaired proliferation, senescence phenotype, and abnormal secretion in CMML MSCs. The impaired ability to support healthy CD34 + haematopoietic stem and progenitor cells (HSPCs) correlates with activation of WNT/β-catenin signalling in CMML MSCs. Furthermore, we observed an association between WNT/β-catenin factors and treatment response to hypomethylating agents (HMAs) in a cohort of patients with MDS/myeloproliferative neoplasms (MPNs). Taken together, our study provides evidence for transcriptional and functional abnormalities in CMML MSCs, and suggests potential prognostic value of evaluating WNT/β-catenin signalling in patients with CMML., (© 2021 British Society for Haematology and John Wiley & Sons Ltd.)

Objective: Dendrobium nobile is a genuine Chinese medicine. Dendrobium nobile Lindl. alkaloids (DNLA) protects against CCl 4 -induced acute liver injury. This study used RNA-Seq to explore the mechanisms., Methods: Mice were pretreated with DNLA (10 and 20 mg/kg, po) for 7 days, and subsequently intoxicated with CCl 4 (20 μL/kg, ip for 24 h). Liver RNA was extracted and subjected to RNA-Seq. The bioinformatics, including PCA, GO, KEGG, two-dimensional clustering, Ingenuity Pathways Analysis (IPA), and Illumina BaseSpace Correlation Engine (BSCE) were used to analyze the data. qPCR was performed on selected genes to verify RNA-Seq results., Results: DNLA protection against CCl 4 hepatotoxicity was confirmed by histopathology. PCA revealed the distinct gene expression patterns between the different treatment groups. GO showed that CCl 4 induced the activation, adhesion and proliferation of immune cells. KEGG showed CCl 4 induced oxidative stress, diseases and compromised adaptive responses. CCl 4 induced differentially expressed genes (DEGs) were identified by DESeq2 with Padj < 0.05 and 2D-clustered with other groups. DNLA reverted CCl 4 -induced DEGs in a dose-dependent manner. qPCR analysis of S100 g, Sprr1, CCL3/7, Saa2/3, IL1rn, Cox7a2 and Rad15 confirmed RNA-Seq results. IPA showed that CCl 4 treatment altered some signaling and metabolic pathways, which were ameliorated or returned to normal following DNLA treatment. The CCl 4 -activated mitochondrial oxidative phosphorylation was illustrated as an example. IPA Upstream Regulator Analysis further revealed the activated or inhibited molecules and chemicals that are responsible for CCl 4 -induced DEGs, and DNLA attenuated these changes. BSCE analysis verified that CCl 4 -induced DEGs were highly correlated with the GEO database of CCl 4 hepatotoxicity in rodents, and DNLA dose-dependently attenuated such correlation., Conclusion: RNA-Seq revealed CCl 4 -induced DEGs, disruption of canonical pathways, activation or inhibition of upstream regulators, which are highly correlated with database for CCl 4 hepatotoxicity. All these changes were attenuated or returned to normal by DNLA, demonstrating the mechanisms for DNLA to protect against CCl 4 hepatotoxicity., (Copyright © 2021 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.)

Human adipose-derived stromal/stem cells (ASC) have immunomodulatory properties and the potential to differentiate into several cell lines, important for application in regenerative medicine. However, the contamination with dermal fibroblasts (FIB) can impair the beneficial effects of ASC in cell therapy. It is then essential to develop new strategies that contribute to the distinction between these two cell types. In this study, we performed functional assays, high-throughput RNA sequencing (RNA-Seq) and quantitative PCR (qPCR) to find new markers that can distinguish ASC and FIB. We showed that ASC have adipogenic and osteogenic differentiation capacity and alkaline phosphatase activity, not observed in FIB. Gene expression variation analysis identified more than 2000 differentially expressed genes (DEG) between these two cell types. We validated 16 genes present in the list of DEG, including the alkaline phosphatase gene (ALPL). In conclusion, we showed that ASC and FIB have distinct biological properties as demonstrated by alkaline phosphatase activity and differentiation capacity, besides having different gene expression profiles. SIGNIFICANCE OF THE STUDY: Although many differences between stromal stem cells derived from human adipose tissue (ASC) and human dermal fibroblasts (FIB) are described, it is still difficult to find specific markers to differentiate them. This problem can interfere with the therapeutic use of ASC. This work aimed to find new markers to differentiate these two cell populations. Our findings suggest that these cells can be distinguished by biological and molecular characteristics, such as adipogenic and osteogenic differentiation, alkaline phosphatase activity and differential gene expression profiles. The DEG were related to the regulation of the cell cycle, development process, structural organization of the cell and synthesis of the extracellular matrix. This study helps to find new cellular markers to distinguish the two populations and to better understand the properties of these cells, which can improve cell therapy., (© 2021 John Wiley & Sons Ltd.)

Roles for ribosomal RNA (rRNA) in gene regulation remain largely unexplored. With hundreds of rDNA units positioned across multiple loci, it is not possible to genetically modify rRNA in mammalian cells, hindering understanding of ribosome function. It remains elusive whether expansion segments (ESs), tentacle-like rRNA extensions that vary in sequence and size across eukaryotic evolution, may have functional roles in translation control. Here, we develop variable expansion segment-ligand chimeric ribosome immunoprecipitation RNA sequencing (VELCRO-IP RNA-seq), a versatile methodology to generate species-adapted ESs and to map specific mRNA regions across the transcriptome that preferentially associate with ESs. Application of VELCRO-IP RNA-seq to a mammalian ES, ES9S, identified a large array of transcripts that are selectively recruited to ribosomes via an ES. We further characterize a set of 5' UTRs that facilitate cap-independent translation through ES9S-mediated ribosome binding. Thus, we present a technology for studying the enigmatic ESs of the ribosome, revealing their function in gene-specific translation., Competing Interests: Declaration of interests K.L., G.W.B., and M.B. are inventors on patents and submitted provisional patent applications related to the Hoxa9 P4 stem-loop and RNA therapeutics and to their various uses., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Main Conclusion: A hypothetical model of drought tolerance mechanism of Larix kaempferi was established through SMRT-seq and Illumina HiSeq. Larix kaempferi is an important economic and ecological species and a major afforestation species in north-eastern China. To date, no information has been reliably derived regarding full-length cDNA sequencing information on L. kaempferi. By single-molecule long-read isoform sequencing (SMRT-seq), here we report a total of 26,153,342 subreads (21.24 Gb) and 330,371 circular consensus sequence (CCS) reads after the modification of site mismatch, and 35,414 unigenes were successfully collected. To gain deeper insights into the molecular mechanisms of L. kaempferi response to drought stress, we combined Illumina HiSeq with SMRT-seq to decode full-length transcripts. In this study, we report 27 differentially expressed genes (DEGs) involved in the perception and transmission of drought stress signals in L. kaempferi. A large number of DEGs responding to drought stress were detected in L. kaempferi, especially DEGs involved in the reactive oxygen species (ROS) scavenging, lignin biosynthesis, and sugar metabolism, and DEGs encoding drought stress proteins. We detected 73 transcription factors (TFs) under drought stress, including AP2/ERF, bZIP, TCP, and MYB. This study provides basic full sequence resources for L. kaempferi research and will help us to better understand the functions of drought-resistance genes in L. kaempferi.

Advances in next generation sequencing (NGS) technologies resulted in a broad array of large-scale gene expression studies and an unprecedented volume of whole messenger RNA (mRNA) sequencing data, or the transcriptome (also known as RNA sequencing, or RNA-seq). These include the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA), among others. Here we cover some of the commonly used datasets, provide an overview on how to begin the analysis pipeline, and how to explore and interpret the data provided by these publicly available resources.

Background: Our current understanding of atopic dermatitis (AD) and psoriasis pathophysiology is largely derived from skin biopsy studies that cause scarring and may be impractical in large-scale clinical trials. Although tape strips show promise as a minimally invasive technique in these common diseases, a comprehensive molecular profiling characterizing and differentiating the 2 diseases in tape strips is unavailable., Objective: Our aim was to construct a global transcriptome of tape strips from lesional and nonlesional skin of adults with moderate-to-severe AD and psoriasis., Methods: A total of 20 tape strips were obtained from lesional and nonlesional skin of patients with AD and psoriasis and skin from controls (n = 20 each); the strips were subjected to RNA sequencing (RNA-seq), with quantitative RT-PCR validation of immune and barrier biomarkers., Results: We detected RNA-seq profiles in 96 of 100 of samples (96%), with 4123 and 5390 genes differentially expressed in AD and psoriasis lesions versus in controls, respectively (fold change ≥ 2; false discovery rate [FDR] < 0.05). Nonlesional tape-stripped skin from patients with AD was more similar to lesional skin than to nonlesional skin of patients with psoriasis, which showed larger differentiation from lesions. AD and psoriasis tissues shared increases in levels of dendritic cell and T-cell markers (CD3, ITGAX/CD11c, and CD83), but AD tissues showed preferential T H 2 skewing (IL-13, CCL17/TARC, and CCL18), whereas psoriasis was characterized by higher levels of expression of T H 17-related (IL-17A/F and IL-36A/IL-36G), T H 1-related (IFN-γ and CXCL9/CXCL10), and innate immunity-related (nitric oxide synthase 2/inducible nitric oxide synthase and IL-17C) products (FDR < 0.05). Terminal differentiation (FLG2 and LCE5A), tight junction (CLDN8), and lipid biosynthesis and metabolism (FA2H and ALOXE3) products were significantly downregulated in both AD and psoriasis (FDR < 0.05). Nitric oxide synthase 2/inducible nitric oxide synthase expression (determined by quantitative PCR) differentiated AD and psoriasis with 100% accuracy., Conclusion: RNA-seq tape strip profiling detected distinct immune and barrier signatures in lesional and nonlesional AD and psoriasis skin, suggesting their utility as a minimally invasive alternative to biopsies for detecting disease biomarkers., (Copyright © 2020 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

RNA sequencing profiles and characterizes cell and tissue samples, giving important insights into molecular mechanisms. Such data is imperative for cardiomyocytes derived from induced pluripotent stem cells (iPSC-CMs) and used in related translational and basic research. Here we provide reliable protocols to extract differentially expressed genes in iPSC-CMs with RNA sequencing., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)

Analysis of circular RNA (circRNA) expression from RNA-Seq data can be performed with different algorithms and analysis pipelines, tools allowing the extraction of heterogeneous information on the expression of this novel class of RNAs. Computational pipelines were developed to facilitate the analysis of circRNA expression by leveraging different public tools in easy-to-use pipelines. This chapter describes the complete workflow for a computationally reproducible analysis of circRNA expression starting for a public RNA-Seq experiment. The main steps of circRNA prediction, annotation, classification, sequence reconstruction, quantification, and differential expression are illustrated.

Sequence-based markers have added a new dimension in the efficiency of identifying alien introgressions in wheat. Expressed sequence tag-sequence tagged sites (EST-STS) markers have proved useful in tracing alien chromatin. In this study, we report the development of Thinopyrum bessarabicum- and Secale anatolicum -specific EST-STS markers and their application in tracing respective alien chromatin introgressions in wheat. The parental lines, Chinese Spring (CS), ISR991.1 (CS/ Th. bessarabicum amphidiploid), and ISR1049.2 (CS/ Secale anatolicum amphidiploid), were used as core experimental materials. Using comparative analysis of RNA-Seq data, 10 903 and 10 660 candidate sequences specific to Th. bessarabicum and S. anatolicum , respectively, were assembled and identified. To validate the genome specificity of these candidate sequences, 68 and 64 EST-STS markers were developed from randomly selected candidate sequences of Th. bessarabicum and S. anatolicum , respectively, and tested on sets of alien addition lines. Fifty-five and 53 markers for Th. bessarabicum and S. anatolicum chromatin, respectively, were assigned to chromosomal location(s), covering all seven chromosomes. Approximately 83% of S. anatolicum -specific markers were transferable to S. cereale . The genome-specific candidate sequences identified and the EST-STS markers developed will be valuable resources for exploitation of Th. bessarabicum and Secale species diversity in wheat and triticale breeding.

The liver has an excellent capacity for regeneration when faced with external injury and the damage differs from that of other organs in the body. Our aim was to identify the role of circular RNA (circRNA) during the DNA synthesis phase (36 h) of mice liver regeneration. High-throughput RNA sequencing was conducted to explore circRNA and messenger RNA (mRNA) expression in three pairs of mice liver tissue at 0 and 36 h after 2/3 partial hepatectomy. One hundred differentially expressed circRNAs were detected, including 66 upregulated and 34 downregulated circRNAs. We also explored 2483 differentially expressed mRNAs, including 1422 upregulated and 1061 downregulated mRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes indicated that cell cycle regulation, material metabolism, and multiple classical pathways were involved in the DNA synthesis process. A competing endogenous RNA (ceRNA) network containing 5 circRNAs, 28 target genes, and 533 microRNAs (miRNAs) was constructed, and we selected the top 5 miRNAs to map it. Potential key circRNAs were validated with the quantitative real-time PCR technique and their regeneration curves, including consecutive time points, were produced. Finally, a cell counting kit-8 assay on key circRNAs of ceRNA network was performed to further confirm their roles in the DNA synthesis phase of liver regeneration. This study provides a circRNA expression profile for liver regeneration and contributes valuable information for future research.

Gene fusions involving the three neurotrophic tyrosine receptor kinase genes NTRK1, NTRK2, or NTRK3 were identified as oncogenic drivers in many cancer types. Two small molecule inhibitors have been tested in clinical trials recently and require the detection of a NTRK fusion gene prior to therapeutic application. Fluorescence in situ hybridization (FISH) and targeted next-generation sequencing (tNGS) assays are commonly used for diagnostic profiling of gene fusions. In the presented study we applied an external quality assessment (EQA) scheme in order to investigate the suitability of FISH and RNA-/DNA-based tNGS for detection of NTRK fusions in a multinational and multicentric ring trial. In total 27 participants registered for this study. Nine institutions took part in the FISH-based and 18 in the NGS-based round robin test, the latter additionally subdivided into low-input and high-input NGS methods (regarding nucleic acid input). Regardless of the testing method applied, all participants received tumor sections of 10 formalin-fixed and paraffin-embedded (FFPE) tissue blocks for in situ hybridization or RNA/DNA extraction, and the results were submitted via an online questionnaire. For FISH testing, eight of nine (88.8%) participants, and for NGS-based testing 15 of 18 (83.3%) participants accomplished the round robin test successfully. The overall high success rate demonstrates that FISH- and tNGS-based NTRK testing can be well established in a routine diagnostic setting. Complementing this dataset, we provide an updated in silico analysis on the coverage of more than 150 NTRK fusion variants by several commercially available RNA-based tNGS panels., (© 2020 Wiley Periodicals, Inc.)

Prediction of gene function and gene regulatory networks is one of the most active topics in bioinformatics. The accumulation of publicly available gene expression data for hundreds of plant species, together with advances in bioinformatical methods and affordable computing, sets ingenuity as one of the major bottlenecks in understanding gene function and regulation. Here, we show how a credit card-sized computer retailing for <50 USD can be used to rapidly predict gene function and infer regulatory networks from RNA sequencing data. To achieve this, we constructed a bioinformatical pipeline that downloads and allows quality-control of RNA sequencing data; and generates a gene co-expression network that can reveal enzymes and transcription factors participating and controlling a given biosynthetic pathway. We exemplify this by first identifying genes and transcription factors involved in the biosynthesis of secondary cell wall in the plant Artemisia annua, the main natural source of the anti-malarial drug artemisinin. Networks were then used to dissect the artemisinin biosynthesis pathway, which suggest potential transcription factors regulating artemisinin biosynthesis. We provide the source code of our pipeline (https://github.com/mutwil/LSTrAP-Lite) and envision that the ubiquity of affordable computing, availability of biological data and increased bioinformatical training of biologists will transform the field of bioinformatics. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony., Competing Interests: Declaration of competing interest No conflicts of interest to declare., (Copyright © 2019 Elsevier B.V. All rights reserved.)

As the diploid progenitor of common wheat, Aegilops tauschii is considered to be a valuable resistance source to various biotic and abiotic stresses. However, little has been reported concerning the molecular mechanism of drought tolerance in Ae. tauschii . In this work, the drought tolerance of 155 Ae. tauschii accessions was firstly screened on the basis of their coleoptile lengths under simulated drought stress. Subsequently, two accessions (XJ002 and XJ098) with contrasting coleoptile lengths were selected and intensively analyzed on rate of water loss (RWL) as well as physiological characters, confirming the difference in drought tolerance at the seedling stage. Further, RNA-seq was utilized for global transcriptome profiling of the two accessions seedling leaves under drought stress conditions. A total of 6969 differentially expressed genes (DEGs) associated with drought tolerance were identified, and their functional annotations demonstrated that the stress response was mediated by pathways involving alpha-linolenic acid metabolism, starch and sucrose metabolism, peroxisome, mitogen-activated protein kinase (MAPK) signaling, carbon fixation in photosynthetic organisms, and glycerophospholipid metabolism. In addition, DEGs with obvious differences between the two accessions were intensively analyzed, indicating that the expression level of DEGs was basically in alignment with the physiological changes of Ae. tauschii under drought stress. The results not only shed fundamental light on the regulatory process of drought tolerance in Ae. tauschii , but also provide a new gene resource for improving the drought tolerance of common wheat., Competing Interests: The authors declare no conflict of interest.

Background: In gene expression studies, RNA sample pooling is sometimes considered because of budget constraints or lack of sufficient input material. Using microarray technology, RNA sample pooling strategies have been reported to optimize both the cost of data generation as well as the statistical power for differential gene expression (DGE) analysis. For RNA sequencing, with its different quantitative output in terms of counts and tunable dynamic range, the adequacy and empirical validation of RNA sample pooling strategies have not yet been evaluated. In this study, we comprehensively assessed the utility of pooling strategies in RNA-seq experiments using empirical and simulated RNA-seq datasets., Result: The data generating model in pooled experiments is defined mathematically to evaluate the mean and variability of gene expression estimates. The model is further used to examine the trade-off between the statistical power of testing for DGE and the data generating costs. Empirical assessment of pooling strategies is done through analysis of RNA-seq datasets under various pooling and non-pooling experimental settings. Simulation study is also used to rank experimental scenarios with respect to the rate of false and true discoveries in DGE analysis. The results demonstrate that pooling strategies in RNA-seq studies can be both cost-effective and powerful when the number of pools, pool size and sequencing depth are optimally defined., Conclusion: For high within-group gene expression variability, small RNA sample pools are effective to reduce the variability and compensate for the loss of the number of replicates. Unlike the typical cost-saving strategies, such as reducing sequencing depth or number of RNA samples (replicates), an adequate pooling strategy is effective in maintaining the power of testing DGE for genes with low to medium abundance levels, along with a substantial reduction of the total cost of the experiment. In general, pooling RNA samples or pooling RNA samples in conjunction with moderate reduction of the sequencing depth can be good options to optimize the cost and maintain the power.

The papillary thyroid carcinoma (PTC) usually shows an excellent prognosis. But some patients suffer recurrence after treatment. Recent progress in RNA sequencing (RNA-Seq) allows us to explore whole-transcriptomic gene expression profiles to develop RNA-seq based predictive model for stratifying the risk of recurrence of PTC. RNA-seq and clinical data from The Cancer Genome Atlas thyroid carcinoma cohort were divided chronologically into a training cohort (before 2011, n = 240) and a validation cohort (after 2011, n = 239). A risk score model was developed in training cohort using univariate Cox analysis followed by stepwise multivariate Cox analysis, and assessed in the validation cohort. Univariate and multivariate analyses identified five independent predictive genes (TOP2A, RP11-180M15.7, RP11-635N19.1, PROSER3, and TMEM139) significantly (p < 0.05) associated with recurrence-free survival of PTC. The proposed risk score model defined by these five genes was able to divide patients into high-risk and low-risk groups with significantly different recurrence risk in both training cohort [hazard ratio (HR) 6.62, 95% confidence interval (CI) 3.16-13.86] and validation cohort [HR 3.40, 95% CI1.29-8.94). Furthermore, the model is independent of clinicopathologic factors and demonstrated better predictive performance than other clinical covariates in PTC patients with no distant metastasis. Our results indicate that TOP2A, RP11-180M15.7, RP11-635N19.1, PROSER3, and TMEM139 are potential independent predictive genes for the recurrence of PTC and the proposed RNA sequencing-based model has significant predictive value and may improve recurrence risk stratification for early-stage PTC patients.

RNA-seq provides an efficient and sensitive methodology to identify fusion transcripts in cancer tissues. Chimeric reads mapping across two different genes represent potential gene fusions. Various methodologies have been implemented in the detection of gene fusions by RNA-seq. Here we describe a general methodology used in processing and filtering of RNA-seq data, followed by filtering of multiple varieties of artifacts to nominate potentially relevant gene fusions. Functional relevance of gene fusions is assessed based on the predicted domain architecture of the putative fusion proteins.

The pancreas is a complex organ composed of an endocrine (pancreatic islets) and an exocrine portion. This mixed cell population has resulted in an implacable barrier to exploring the detailed mechanism and function of each cell type in previous investigative approaches. In recent years, single-cell RNA sequencing (scRNA-seq) technologies have provided in-depth analysis of cell heterogeneity in the pancreas and in pancreatic cancer. It is especially effective in cell-type-specific molecule identification and detection of interactions between cancer cells and the stromal microenvironment. To date, numerous reports have described the application of scRNA-seq in studies of pancreatic islets and pancreatic cancer. The aim of this paper is to review recent advances of pancreatic transcriptomics and pancreatic cancer using scRNA-seq strategies.

The reverse transcriptases (RTs) encoded by mobile group II introns and other non-LTR retroelements differ from retroviral RTs in being able to template-switch efficiently from the 5' end of one template to the 3' end of another with little or no complementarity between the donor and acceptor templates. Here, to establish a complete kinetic framework for the reaction and to identify conditions that more efficiently capture acceptor RNAs or DNAs, we used a t hermostable g roup II i ntron RT (TGIRT; GsI-IIC RT) that can template switch directly from synthetic RNA template/DNA primer duplexes having either a blunt end or a 3'-DNA overhang end. We found that the rate and amplitude of template switching are optimal from starter duplexes with a single nucleotide 3'-DNA overhang complementary to the 3' nucleotide of the acceptor RNA, suggesting a role for nontemplated nucleotide addition of a complementary nucleotide to the 3' end of cDNAs synthesized from natural templates. Longer 3'-DNA overhangs progressively decreased the template-switching rate, even when complementary to the 3' end of the acceptor template. The reliance on only a single bp with the 3' nucleotide of the acceptor together with discrimination against mismatches and the high processivity of group II intron RTs enable synthesis of full-length DNA copies of nucleic acids beginning directly at their 3' end. We discuss the possible biological functions of the template-switching activity of group II intron- and other non-LTR retroelement-encoded RTs, as well as the optimization of this activity for adapter addition in RNA- and DNA-Seq protocols., (© 2019 Lentzsch et al.)

Background: Formalin-fixed, paraffin-embedded (FFPE) tissues for RNA-seq have advantages over fresh frozen tissue including abundance and availability, connection to rich clinical data, and association with patient outcomes. However, FFPE-derived RNA is highly degraded and chemically modified, which impacts its utility as a faithful source for biological inquiry., Methods: True archival FFPE breast cancer cases (n = 58), stored at room temperature for 2-23 years, were utilized to identify key steps in tissue selection, RNA isolation, and library choice. Gene expression fidelity was evaluated by comparing FFPE data to public data obtained from fresh tissues, and by employing single-gene, gene set and transcription network-based regulon analyses., Results: We report a single 10 μm section of breast tissue yields sufficient RNA for RNA-seq, and a relationship between RNA quality and block age that was not linear. We find single-gene analysis is limiting with FFPE tissues, while targeted gene set approaches effectively distinguish ER+ from ER- breast cancers. Novel utilization of regulon analysis identified the transcription factor KDM4B to associate with ER+ disease, with KDM4B regulon activity and gene expression having prognostic significance in an independent cohort of ER+ cases., Conclusion: Our results, which outline a robust FFPE-RNA-seq pipeline for broad use, support utilizing FFPE tissues to address key questions in the breast cancer field, including the delineation between indolent and life-threatening disease, biological stratification and molecular mechanisms of treatment resistance.

A number of specialized clustering methods have been developed so far for the accurate analysis of single-cell RNA-sequencing (scRNA-seq) expression data, and several reports have been published documenting the performance measures of these clustering methods under different conditions. However, to date, there are no available studies regarding the systematic evaluation of the performance measures of the clustering methods taking into consideration the sample size and cell composition of a given scRNA-seq dataset. Herein, a comprehensive performance evaluation study of 11 selected scRNA-seq clustering methods was performed using synthetic datasets with known sample sizes and number of subpopulations, as well as varying levels of transcriptome complexity. The results indicate that the overall performance of the clustering methods under study are highly dependent on the sample size and complexity of the scRNA-seq dataset. In most of the cases, better clustering performances were obtained as the number of cells in a given expression dataset was increased. The findings of this study also highlight the importance of sample size for the successful detection of rare cell subpopulations with an appropriate clustering tool.

Small RNA sequencing has been widely adopted to study the diversity of extracellular RNAs (exRNAs) in biofluids; however, the analysis of exRNA samples can be challenging: they are vulnerable to contamination and artifacts from different isolation techniques, present in lower concentrations than cellular RNA, and occasionally of exogenous origin. To address these challenges, we present exceRpt, the exRNA-processing toolkit of the NIH Extracellular RNA Communication Consortium (ERCC). exceRpt is structured as a cascade of filters and quantifications prioritized based on one's confidence in a given set of annotated RNAs. It generates quality control reports and abundance estimates for RNA biotypes. It is also capable of characterizing mappings to exogenous genomes, which, in turn, can be used to generate phylogenetic trees. exceRpt has been used to uniformly process all ∼3,500 exRNA-seq datasets in the public exRNA Atlas and is available from genboree.org and github.gersteinlab.org/exceRpt., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2 -expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential. [Display omitted] • A comprehensive and dynamic molecular atlas of the spinal cord after acute injury • In situ depiction of cell-cell communication following spinal cord injury (SCI) • Spatial delineation of SCI-induced, WM-to-GM migrating Igfbp2 + -astrocytes • IGFBP2 treatment improves neuronal survival and functional outcomes of SCI in vivo Wang et al. conducted a comprehensive spatial transcriptomic analysis that provides a rich resource and a useful bioinformatic toolkit for disentangling the spatiotemporal re-organization of the injured spinal cord. They further spatially identified a subpopulation of injury-induced migrating astrocytes that secrete IGFBP2, which exhibits potent neuroprotection following SCI. [ABSTRACT FROM AUTHOR]

Introduction: The balanced fatty acid profile of olive oil not only enhances its stability but also contributes to its positive effects on health, making it a valuable dietary choice. Olive oil's high content of unsaturated fatty acids and low content of saturated fatty acids contribute to its beneficial effects on cardiovascular diseases and cancer. The quantities of these fatty acids in olive oil may fluctuate due to various factors, with genotype being a crucial determinant of the oil's quality. Methods: This study investigated the genetic basis of oil quality by comparing the transcriptome of two Iranian cultivars with contrasting oil profiles: Mari, known for its high oleic acid content, and Shengeh, characterized by high linoleic acid at Jaén index four. Results and discussion: Gas chromatography confirmed a significant difference in fatty acid composition between the two cultivars. Mari exhibited significantly higher oleic acid content (78.48%) compared to Shengeh (48.05%), while linoleic acid content was significantly lower in Mari (4.76%) than in Shengeh (26.69%). Using RNA sequencing at Jaén index four, we analyzed genes involved in fatty acid biosynthesis. Differential expression analysis identified 2775 genes showing statistically significant differences between the cultivars. Investigating these genes across nine fundamental pathways involved in oil quality led to the identification of 25 effective genes. Further analysis revealed 78 transcription factors and 95 transcription binding sites involved in oil quality, with BPC6 and RGA emerging as unique factors. This research provides a comprehensive understanding of the genetic and molecular mechanisms underlying oil quality in olive cultivars. The findings have practical implications for olive breeders and producers, potentially streamlining cultivar selection processes and contributing to the production of high-quality olive oil. [ABSTRACT FROM AUTHOR]

Introduction: The advent of RNA sequencing (RNA-Seq) has significantly advanced our understanding of the transcriptomic landscape, revealing intricate gene expression patterns across biological states and conditions. However, the complexity and volume of RNA-Seq data pose challenges in identifying differentially expressed genes (DEGs), critical for understanding the molecular basis of diseases like cancer. Methods: We introduce a novel Machine Learning-Enhanced Genomic Data Analysis Pipeline (ML-GAP) that incorporates autoencoders and innovative data augmentation strategies, notably the MixUp method, to overcome these challenges. By creating synthetic training examples through a linear combination of input pairs and their labels, MixUp significantly enhances the model's ability to generalize from the training data to unseen examples. Results: Our results demonstrate the ML-GAP's superiority in accuracy, efficiency, and insights, particularly crediting the MixUp method for its substantial contribution to the pipeline's effectiveness, advancing greatly genomic data analysis and setting a new standard in the field. Discussion: This, in turn, suggests that ML-GAP has the potential to perform more accurate detection of DEGs but also offers new avenues for therapeutic intervention and research. By integrating explainable artificial intelligence (XAI) techniques, ML-GAP ensures a transparent and interpretable analysis, highlighting the significance of identified genetic markers. [ABSTRACT FROM AUTHOR]

To thrive on melting alpine and polar snow, some Chlorophytes produce an abundance of astaxanthin, causing red blooms, often dominated by genus Sanguina. The red cells have not been cultured, but we recently grew a green biciliate conspecific with Sanguina aurantia from a sample of watermelon snow. This culture provided source material for Oxford Nanopore Technology and Illumina sequencing. Our assembly pipeline exemplifies the value of a hybrid long- and short-read approach for the complexities of working with a culture grown from a field sample. Using bioinformatic tools, we separated assembled contigs into 2 genomic pools based on a difference in GC content (57.5 and 55.1%). We present the data as 2 assemblies of S. aurantia variants but explore other possibilities. High-throughput chromatin conformation capture analysis (Hi-C sequencing) was used to scaffold the assemblies into a 96-Mb genome designated as "A" and a 102-Mb genome designated as "B." Both assemblies are highly contiguous: genome A consists of 38 scaffolds with an N50 of 5.4 Mb, while genome B has 50 scaffolds with an N50 of 6.4 Mb. RNA sequencing was used to improve gene annotation. [ABSTRACT FROM AUTHOR]

The search for genetic variants that act as causative factors in human diseases by disrupting the normal splicing process has primarily focused on single nucleotide variants (SNVs). It is worth noting that insertions or deletions (indels) have also been sporadically reported as causative disease variants through their potential impact on the splicing process. In this study, to perform identification of indels inducing exon extension/shrinkage events, we used individual‐specific genomes and RNA sequencing (RNA‐seq) data pertaining to the corresponding individuals and identified 12 exon extension/shrinkage events that were potentially induced by indels that disrupted authentic splice sites or created novel splice sites in 235 normal individuals. By evaluating the impact of these abnormal splicing events on the resulting transcripts, we found that five events led to the generation of premature termination codons (PTCs), including those occurring within genes associated with genetic disorders. Our analysis revealed that the potential functions of indels have been underexamined, and it is worth considering the possibility that indels may affect splice site usage, using RNA‐seq data to discover novel potentially disease‐associated mutations. [ABSTRACT FROM AUTHOR]

Background: Structural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM). Methods: This study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity. Results: OGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases—two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5′UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5′ and 3′ non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain. Conclusions: SVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs. [ABSTRACT FROM AUTHOR]

Plant height (PH) is a critical agronomic trait in Brassica napus, significantly impacting yield. Consequently, identifying genes associated with plant height is a pivotal objective in oilseed rape breeding. This study employed a combination of bulk segregant analysis sequencing (BSA-seq) and RNA sequencing (RNA-seq) for analysis. A novel quantitative trait locus (QTL), qPH_C02, was identified between 63,989,634 and 64,945,122 bp on chromosome C02, from which eight candidate genes were screened. The Gene Ontology (GO) analysis revealed enrichment in peroxisomes, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated enrichment in the oxidative phosphorylation (OP) pathway. It is hypothesized that the observed differences in plant height and silique length may be attributed to the regulation of peroxidase activity in the OP pathway, which in turn alters plant energy metabolism and controls nutrient uptake. Subsequently, we will further test this hypothesis. The results of this study will contribute to our understanding of the genetic basis for differences in plant height and provide a foundation for the selection and breeding of Brassica napus varieties with desired plant shapes. [ABSTRACT FROM AUTHOR]

Flooding stress caused by climate change is a serious threat to crop productivity. To enhance our understanding of flooding stress in soybean, we analyzed the transcriptome of the roots of soybean plants after waterlogging treatment for 10 days at the V2 growth stage. Through RNA sequencing analysis, 870 upregulated and 1129 downregulated differentially expressed genes (DEGs) were identified and characterized using Gene Ontology (GO) and MapMan software (version 3.6.0RC1). In the functional classification analysis, "alcohol biosynthetic process" was the most significantly enriched GO term in downregulated DEGs, and phytohormone-related genes such as ABA, cytokinin, and gibberellin were upregulated. Among the transcription factors (TFs) in DEGs, AP2/ERFs were the most abundant. Furthermore, our DEGs encompassed eight soybean orthologs from Arabidopsis and rice, such as 1-aminocyclopropane-1-carboxylate oxidase. Along with a co-functional network consisting of the TF and orthologs, the expression changes of those genes were tested in a waterlogging-resistant cultivar, PI567343. These findings contribute to the identification of candidate genes for waterlogging tolerance in soybean, which can enhance our understanding of waterlogging tolerance. [ABSTRACT FROM AUTHOR]

Background: The tumor microenvironment (TME) provides a region for intricate interactions within or between immune and non-immune cells. We aimed to reveal the tissue architecture and comprehensive landscape of cells within the TME of colorectal cancer (CRC). Methods: Fresh frozen invasive adenocarcinoma of the large intestine tissue from 10× Genomics Datasets was obtained from BioIVT Asterand. The integration of microarray-based spatial transcriptomics (ST) and RNA sequencing (RNA-seq) was applied to characterize gene expression and cell landscape within the TME of CRC tissue architecture. Multiple R packages and deconvolution algorithms including MCPcounter, XCELL, EPIC, and ESTIMATE methods were performed for further immune distribution analysis. Results: The subpopulations of immune and non-immune cells within the TME of the CRC tissue architecture were appropriately annotated. According to ST and RNA-seq analyses, a heterogeneous spatial atlas of gene distribution and cell landscape was comprehensively characterized. We distinguished between the cancer and stromal regions of CRC tissues. As expected, epithelial cells were located in the cancerous region, whereas fibroblasts were mainly located in the stroma. In addition, the fibroblasts were further subdivided into two subgroups (F1 and F2) according to the differentially expressed genes (DEGs), which were mainly enriched in pathways including hallmark-oxidative-phosphorylation, hallmark-e2f-targets and hallmark-unfolded-protein-response. Furthermore, the top 5 DEGs, SPP1, CXCL10, APOE, APOC1, and LYZ, were found to be closely related to immunoregulation of the TME, methylation, and survival of CRC patients. Conclusions: This study characterized the heterogeneous spatial landscape of various cell subtypes within the TME of the tissue architecture. The TME-related roles of fibroblast subsets addressed the potential crosstalk among diverse cells. [ABSTRACT FROM AUTHOR]

Background: Black spot disease in tree peony caused by the fungal necrotroph A. alternata, is a primary limiting factor in the production of the tree peony. The intricate molecular mechanisms underlying the tree peony resistance to A. alternata have not been thoroughly investigated. Results: The present study utilized high-throughput RNA sequencing (RNA-seq) technology to conduct global expression profiling, revealing an intricate network of genes implicated in the interaction between tree peony and A. alternata. RNA-Seq libraries were constructed from leaf samples and high-throughput sequenced using the BGISEQ-500 sequencing platform. Six distinct libraries were characterized. M1, M2 and M3 were derived from leaves that had undergone mock inoculation, while I1, I2 and I3 originated from leaves that had been inoculated with the pathogen. A range of 10.22–11.80 gigabases (Gb) of clean bases were generated, comprising 68,131,232 − 78,633,602 clean bases and 56,677 − 68,996 Unigenes. A grand total of 99,721 Unigenes were acquired, boasting a mean length of 1,266 base pairs. All these 99,721 Unigenes were annotated in various databases, including NR (Non-Redundant, 61.99%), NT (Nucleotide, 45.50%), SwissProt (46.32%), KEGG (Kyoto Encyclopedia of Genes and Genomes, 49.33%), KOG (clusters of euKaryotic Orthologous Groups, 50.18%), Pfam (Protein family, 47.16%), and GO (Gene Ontology, 34.86%). In total, 66,641 (66.83%) Unigenes had matches in at least one database. By conducting a comparative transcriptome analysis of the mock- and A. alternata-infected sample libraries, we found differentially expressed genes (DEGs) that are related to phytohormone signalling, pathogen recognition, active oxygen generation, and circadian rhythm regulation. Furthermore, multiple different kinds of transcription factors were identified. The expression levels of 10 selected genes were validated employing qRT-PCR (quantitative real-time PCR) to confirm RNA-Seq data. Conclusions: A multitude of transcriptome sequences have been generated, thus offering a valuable genetic repository for further scholarly exploration on the immune mechanisms underlying the tree peony infected by A. alternata. While the expression of most DEGs increased, a few DEGs showed decreased expression. [ABSTRACT FROM AUTHOR]

Objectives: Current data suggests that Bacille Calmette-Guerin (BCG) vaccination contributes to nonspecific enhancement of resistance to various infections. Thus, BCG vaccination induces both specific immunity against mycobacteria and non-specific "trained immunity" against various pathogens. To understand the fundamental mechanisms of "trained" immunity, studies of transcriptome changes occurring during BCG vaccination in innate immunity cells, as well as in their precursors, are necessary. Furthermore, this data possesses important significance for practical applications associated with the development of recombinant BCG strains aimed to enhance innate immunity against diverse infectious agents. Data description: We performed RNA sequencing of innate immune cells derived from murine bone marrow and spleen three days after subcutaneous BCG vaccination. Using fluorescence-activated cell sorting we obtained three cell populations for each mouse from both control and BCG vaccinated groups: bone marrow monocytes and neutrophils and splenic NK-cells. Then double-indexed cDNA libraries for Illumina sequencing from the collected samples were prepared, the resulting cDNA library mix was subjected to NovaSeq 6000 sequencing. This paper describes the collection of 24 RNA sequencing samples comprising 4 sets of immune cell populations obtained from subcutaneously BCG-vaccinated and control mice [ABSTRACT FROM AUTHOR]

Background: Cannabis sativa cultivars can be classified as marijuana or hemp, depending on its amount of the psychoactive cannabinoid Δ9‐tetrahydrocannabinolic acid (THCA). Hemp Cheungsam is a non-drug type Cannabis sativa that is characterized by low THCA content. However, the transcripts and expression profile of cannabinoid biosynthesis pathway genes of hemp Cheungsam have not been investigated. Methods: RNA-sequencing (RNA-seq) was performed on three different tissue types (flower, leaf, and stem) of hemp Cheungsam to understand their transcriptomes. The expression of cannabinoid biosynthesis pathway genes was further analyzed in each tissue type. Multiple sequence alignment and conserved domain analyses were used to investigate the homologs of cannbinoid biosynthesis genes. Results: We found that the cannabinoid biosynthesis pathway was mainly expressed in the flowers of hemp Cheungsam, similar to other Cannabis cultivars. However, expression of cannabidiolic acid (CBDA) synthase was much higher than THCA synthase and cannabichromenic acid (CBCA) synthase, suggesting that the transcription profile favors CBDA biosynthesis. Sequence analysis of cannabinoid biosynthesis pathway genes suggested the identity of orthologs in hemp Cheungsam. Conclusions: Cannabinoid biosynthesis in hemp Cheungsam mostly occurs in the flowers, compared to other plant organs. While CBDA synthase expression is high, THCA and CBCA synthase expression is considerably low, indicating lesser THCA biosynthesis and thus low THCA content. Sequence analysis of key genes (CBDA, THCA, and CBCA synthases) of the cannabinoid biosynthetic pathway indicates that orthologs are present in hemp Cheungsam. [ABSTRACT FROM AUTHOR]

Introduction: Influenza A virus (IAV) infection is a global respiratory disease, which annually leads to 3-5 million cases of severe illness, resulting in 290,000-650,000 deaths. Additionally, during the past century, four global IAV pandemics have claimed millions of human lives. The epithelial lining of the trachea plays a vital role during IAV infection, both as point of viral entry and replication as well as in the antiviral immune response. Tracheal tissue is generally inaccessible from human patients, which makes animal models crucial for the study of the tracheal host immune response. Method: In this study, pigs were inoculated with swine- or human-adapted H1N1 IAV to gain insight into how host adaptation of IAV shapes the innate immune response during infection. In-depth multi-omics analysis (global proteomics and RNA sequencing) of the host response in upper and lower tracheal tissue was conducted, and results were validated by microfluidic qPCR. Additionally, a subset of samples was selected for histopathological examination. Results: A classical innate antiviral immune response was induced in both upper and lower trachea after infection with either swine- or human-adapted IAV with upregulation of genes and higher abundance of proteins associated with viral infection and recognition, accompanied by a significant induction of interferon stimulated genes with corresponding higher proteins concentrations. Infection with the swine-adapted virus induced a much stronger immune response compared to infection with a human-adapted IAV strain in the lower trachea, which could be a consequence of a higher viral load and a higher degree of inflammation. Discussion: Central components of the JAK-STAT pathway, apoptosis, pyrimidine metabolism, and the cytoskeleton were significantly altered depending on infection with swine- or human-adapted virus and might be relevant mechanisms in relation to antiviral immunity against putative zoonotic IAV. Based on our findings, we hypothesize that during host adaptation, IAV evolve to modulate important host cell elements to favor viral infectivity and replication. [ABSTRACT FROM AUTHOR]

RNA sequencing (RNA-seq) has become a standard method for profiling gene expression, yet genomic DNA (gDNA) contamination carried over to the sequencing library poses a significant challenge to data integrity. Detecting and correcting this contamination is vital for accurate downstream analyses. Particularly, when RNA samples are scarce and invaluable, it becomes essential not only to identify but also to correct gDNA contamination to maximize the data's utility. However, existing tools capable of correcting gDNA contamination are limited and lack thorough evaluation. To fill the gap, we developed CleanUpRNAseq, which offers a comprehensive set of functionalities for identifying and correcting gDNA-contaminated RNA-seq data. Our package offers three correction methods for unstranded RNA-seq data and a dedicated approach for stranded data. Through rigorous validation on published RNA-seq datasets with known levels of gDNA contamination and real-world RNA-seq data, we demonstrate CleanUpRNAseq's efficacy in detecting and correcting detrimental levels of gDNA contamination across diverse library protocols. CleanUpRNAseq thus serves as a valuable tool for post-alignment quality assessment of RNA-seq data and should be integrated into routine workflows for RNA-seq data analysis. Its incorporation into OneStopRNAseq should significantly bolster the accuracy of gene expression quantification and differential expression analysis of RNA-seq data. [ABSTRACT FROM AUTHOR]

Sporisorium scitamineum is a biotrophic fungus responsible for inducing sugarcane smut disease that results in significant reductions in sugarcane yield. Resistance mechanisms against sugarcane smut can be categorized into structural, biochemical, and physiological resistance. However, structural resistance has been relatively understudied. This study found that sugarcane variety ZZ9 displayed structural resistance compared to variety GT42 when subjected to different inoculation methods for assessing resistance to smut disease. Furthermore, the stomatal aperture and density of smut-susceptible varieties (ROC22 and GT42) were significantly higher than those of smut-resistant varieties (ZZ1, ZZ6, and ZZ9). Notably, S. scitamineum was found to be capable of entering sugarcane through the stomata on buds. According to the RNA sequencing of the buds of GT42 and ZZ9, seven Expansin protein-encoding genes were identified, of which six were significantly upregulated in GT42. The two genes c111037.graph_c0 and c113583.graph_c0, belonging to the α-Expansin and β-Expansin families, respectively, were functionally characterized, revealing their role in increasing the stomatal aperture. Therefore, these two sugarcane Expansin protein-coding genes contribute to the stomatal aperture, implying their potential roles in structural resistance to sugarcane smut. Our findings deepen the understanding of the role of the stomata in structural resistance to sugarcane smut and highlight their potential in sugarcane breeding for disease resistance. [ABSTRACT FROM AUTHOR]

Vibrio cholerae is an important foodborne pathogen. Cholix cytotoxin (Cholix), produced by V. cholerae, is a novel eukaryotic elongation factor 2 (eEF2) adenosine diphosphate ribosyltransferase that causes host cell death by inhibiting protein synthesis. However, the role of Cholix in the infectious diseases caused by V. cholerae remains unclear. Some bacterial cytotoxins are carried by host extracellular vesicles (EVs) and transferred to other cells. In this study, we investigated the effects of EV inhibitors and EV-regulating proteins on Cholix-induced hepatocyte death. We observed that Cholix-induced cell death was significantly enhanced in the presence of EV inhibitors (e.g., dimethyl amiloride, and desipramine) and Rab27a-knockdown cells, but it did not involve a sphingomyelin-dependent pathway. RNA sequencing analysis revealed that desipramine, imipramine, and EV inhibitors promoted the Cholix-activated c-Jun NH2-terminal kinase (JNK) pathway. Furthermore, JNK inhibition decreased desipramine-enhanced Cholix-induced poly (ADP-ribose) polymerase (PARP) cleavage. In addition, suppression of Apaf-1 by small interfering RNA further enhanced Cholix-induced PARP cleavage by desipramine. We identified a novel function of desipramine in which the stimulated JNK pathway promoted a mitochondria-independent cell death pathway by Cholix. [ABSTRACT FROM AUTHOR]

Microsatellite instability (MSI), a phenomenon caused by deoxyribonucleic acid (DNA) mismatch repair system deficiencies, is an important biomarker in cancer research and clinical diagnostics. MSI detection often involves next-generation sequencing data, with many studies focusing on DNA. Here, we introduce a novel approach by measuring microsatellite lengths directly from ribonucleic acid sequencing (RNA-seq) data and comparing its distribution to detect MSI. Our findings reveal distinct instability patterns between MSI-high (MSI-H) and microsatellite stable samples, indicating the efficacy of RNA–based MSI detection. Additionally, microsatellites in the 3′-untranslated regions showed the greatest predictive value for MSI detection. Notably, this efficacy extends to detecting MSI-H samples even in tumors not commonly associated with MSI. Our approach highlights the utility of RNA-seq data in MSI detection, facilitating more precise diagnostics through the integration of various biological data. [ABSTRACT FROM AUTHOR]

In this study, we introduce Robust estimation of Cell type proportions by Integrating single-reference-based DEconvolutions (ReCIDE), an innovative framework for robust estimation of cell type proportions by integrating single-reference-based deconvolutions. ReCIDE outperforms existing approaches in benchmark and real datasets, particularly excelling in estimating rare cell type proportions. Through exploratory analysis on public bulk data of triple-negative breast cancer (TNBC) patients using ReCIDE, we demonstrate a significant correlation between the prognosis of TNBC patients and the proportions of both T cell and perivascular-like cell subtypes. Built upon this discovery, we develop a prognostic assessment model for TNBC patients. Our contribution presents a novel framework for enhancing deconvolution accuracy, showcasing its effectiveness in medical research. [ABSTRACT FROM AUTHOR]

Tissue dissociation results in single-cell datasets with limited spatiotemporal context. The predictive power of single-cell RNA sequencing (scRNA-seq) can be improved by complementing with methods that 'anchor' cells in space and time. We assess how the information content produced by various spatial technologies can be used to integrate spatial information into scRNA-seq datasets. We reflect on the initial promises of scRNA-seq and whether complementary spatial data can bring us closer to truly observing plant biology at cellular resolution. Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the spatiotemporal context of cells. However, positional information is inherently lost during scRNA-seq, limiting its potential to characterize complex biological systems. In this review we highlight how current single-cell analysis pipelines cannot completely recover spatial information, which confounds biological interpretation. Various strategies exist to identify the location of RNA, from classical RNA in situ hybridization to spatial transcriptomics. Herein we discuss the possibility of utilizing this spatial information to supervise single-cell analyses. An integrative approach will maximize the potential of each technology, and lead to insights which go beyond the capability of each individual technology. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the surge in disinfectant use emphasised their pivotal role in infection control. While the majority of antimicrobial resistance research focuses on antibiotics, resistance to biocides, which are present in disinfectants and sanitisers, is escalating. Serratia sp. HRI is a highly resistant isolate, and through the study of this organism, the molecular mechanisms of resistance may be uncovered. Serratia sp. HRI was treated with the disinfectant benzalkonium chloride in preparation for RNA sequencing. Through mining of the RNA-Seq differential expression data, an uncharacterised Major Facilitator Superfamily (MFS) efflux pump gene was found to be up-regulated at least four-fold at four different time points of exposure. Real-time PCR revealed this uncharacterised MFS efflux gene was up-regulated after exposure to benzalkonium chloride and two additional disinfectants, didecyldimethylammonium chloride (DDAC) and VirukillTM. Additionally, expression of this gene was found to be higher at 20 min versus 90 min of exposure, indicating that the up-regulation of this gene is an initial response to biocide treatment that decreases over time. This suggests that MFS efflux pumps may be an initial survival mechanism for microorganisms, allowing time for longer-term resistance mechanisms. This work puts forward a novel biocide resistance gene that could have a major impact on biocide susceptibility and resistance. [ABSTRACT FROM AUTHOR]

Background: Individuals with Down syndrome (DS) have intellectual disability and develop Alzheimer's disease (AD) pathology during midlife, particularly in the hippocampal component of the medial temporal lobe memory circuit. However, molecular and cellular mechanisms underlying selective vulnerability of hippocampal CA1 neurons remains a major knowledge gap during DS/AD onset. This is compounded by evidence showing spatial (e.g., deep versus superficial) localization of pyramidal neurons (PNs) has profound effects on activity and innervation within the CA1 region. Objective: We investigated whether there is a spatial profiling difference in CA1 PNs in an aged female DS/AD mouse model. We posit dysfunction may be dependent on spatial localization and innervation patterns within discrete CA1 subfields. Methods: Laser capture microdissection was performed on trisomic CA1 PNs in an established mouse model of DS/AD compared to disomic controls, isolating the entire CA1 pyramidal neuron layer and sublayer microisolations of deep and superficial PNs from the distal CA1 (CA1a) region. Results: RNA sequencing and bioinformatic inquiry revealed dysregulation of CA1 PNs based on spatial location and innervation patterns. The entire CA1 region displayed the most differentially expressed genes (DEGs) in trisomic mice reflecting innate DS vulnerability, while trisomic CA1a deep PNs exhibited fewer but more physiologically relevant DEGs, as evidenced by bioinformatic inquiry. Conclusions: CA1a deep neurons displayed numerous DEGs linked to cognitive functions whereas CA1a superficial neurons, with approximately equal numbers of DEGs, were not linked to pathways of dysregulation, suggesting the spatial location of vulnerable CA1 PNs plays an important role in circuit dissolution. [ABSTRACT FROM AUTHOR]