Displaying publications 1 - 20 of 89 in total

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  1. Fulltext Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research
    Awuah WA, Roy S, Tan JK, Adebusoye FT, Qiang Z, Ferreira T, et al.
    J Cell Mol Med, 2024 Apr;28(7):e18159.
    PMID: 38494861 DOI: 10.1111/jcmm.18159
    Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.
    Matched MeSH terms: Sequence Analysis, RNA
  2. The molecular landscape of neurological disorders: insights from single-cell RNA sequencing in neurology and neurosurgery
    Awuah WA, Ahluwalia A, Ghosh S, Roy S, Tan JK, Adebusoye FT, et al.
    Eur J Med Res, 2023 Nov 16;28(1):529.
    PMID: 37974227 DOI: 10.1186/s40001-023-01504-w
    Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology in neurological and neurosurgical research, revolutionising our comprehension of complex neurological disorders. In brain tumours, scRNA-seq has provided valuable insights into cancer heterogeneity, the tumour microenvironment, treatment resistance, and invasion patterns. It has also elucidated the brain tri-lineage cancer hierarchy and addressed limitations of current models. Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. In epilepsy, scRNA-seq has explored the cellular and molecular heterogeneity underlying the condition, uncovering unique glial subpopulations and dysregulation of the immune system. ScRNA-seq has characterised distinct cellular constituents and responses to spinal cord injury in spinal cord diseases, as well as provided molecular signatures of various cell types and identified interactions involved in vascular remodelling. Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. This review highlights the potential of scRNA-seq in guiding precision medicine approaches, identifying clinical biomarkers, and facilitating therapeutic discovery. However, challenges related to data analysis, standardisation, sample acquisition, scalability, and cost-effectiveness need to be addressed. Despite these challenges, scRNA-seq has the potential to transform clinical practice in neurological and neurosurgical research by providing personalised insights and improving patient outcomes.
    Matched MeSH terms: Sequence Analysis, RNA
  3. CircPrime: a web-based platform for design of specific circular RNA primers
    Sharko F, Rbbani G, Siriyappagouder P, Raeymaekers JAM, Galindo-Villegas J, Nedoluzhko A, et al.
    BMC Bioinformatics, 2023 May 19;24(1):205.
    PMID: 37208611 DOI: 10.1186/s12859-023-05331-y
    BACKGROUND: Circular RNAs (circRNAs) are covalently closed-loop RNAs with critical regulatory roles in cells. Tens of thousands of circRNAs have been unveiled due to the recent advances in high throughput RNA sequencing technologies and bioinformatic tools development. At the same time, polymerase chain reaction (PCR) cross-validation for circRNAs predicted by bioinformatic tools remains an essential part of any circRNA study before publication.

    RESULTS: Here, we present the CircPrime web-based platform, providing a user-friendly solution for DNA primer design and thermocycling conditions for circRNA identification with routine PCR methods.

    CONCLUSIONS: User-friendly CircPrime web platform ( http://circprime.elgene.net/ ) works with outputs of the most popular bioinformatic predictors of circRNAs to design specific circular RNA primers. CircPrime works with circRNA coordinates and any reference genome from the National Center for Biotechnology Information database).

    Matched MeSH terms: Sequence Analysis, RNA/methods
  4. scGGAN: single-cell RNA-seq imputation by graph-based generative adversarial network
    Huang Z, Wang J, Lu X, Mohd Zain A, Yu G
    Brief Bioinform, 2023 Mar 19;24(2).
    PMID: 36733262 DOI: 10.1093/bib/bbad040
    Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
    Matched MeSH terms: Sequence Analysis, RNA/methods
  5. Fulltext Single-cell RNA sequencing analysis of human Alzheimer's disease brain samples reveals neuronal and glial specific cells differential expression
    Soreq L, Bird H, Mohamed W, Hardy J
    PLoS One, 2023;18(2):e0277630.
    PMID: 36827281 DOI: 10.1371/journal.pone.0277630
    Alzheimer's disease is the most common neurological disease worldwide. Unfortunately, there are currently no effective treatment methods nor early detection methods. Furthermore, the disease underlying molecular mechanisms are poorly understood. Global bulk gene expression profiling suggested that the disease is governed by diverse transcriptional regulatory networks. Thus, to identify distinct transcriptional networks impacted into distinct neuronal populations in Alzheimer, we surveyed gene expression differences in over 25,000 single-nuclei collected from the brains of two Alzheimer's in disease patients in Braak stage I and II and age- and gender-matched controls hippocampal brain samples. APOE status was not measured for this study samples (as well as CERAD and THAL scores). Our bioinformatic analysis identified discrete glial, immune, neuronal and vascular cell populations spanning Alzheimer's disease and controls. Astrocytes and microglia displayed the greatest transcriptomic impacts, with the induction of both shared and distinct gene programs.
    Matched MeSH terms: Sequence Analysis, RNA
  6. Fulltext On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data
    Ng GYL, Tan SC, Ong CS
    PLoS One, 2023;18(10):e0292961.
    PMID: 37856458 DOI: 10.1371/journal.pone.0292961
    Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell types. Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. Generally speaking, feature selection methods are categorized into filter-, wrapper-, and embedded-based approaches. From the existing literature, methods from filter- and embedded-based approaches are widely applied in scRNA-seq gene selection tasks. The wrapper-based method that gives promising results in other fields has yet been extensively utilized for selecting gene features from scRNA-seq data; in addition, most of the existing wrapper methods used in this field are clustering instead of classification-based. With a large number of annotated data available today, this study applied a classification-based approach as an alternative to the clustering-based wrapper method. In our work, a quantum-inspired differential evolution (QDE) wrapped with a classification method was introduced to select a subset of genes from twelve well-known scRNA-seq transcriptomic datasets to identify cell types. In particular, the QDE was combined with different machine-learning (ML) classifiers namely logistic regression, decision tree, support vector machine (SVM) with linear and radial basis function kernels, as well as extreme learning machine. The linear SVM wrapped with QDE, namely QDE-SVM, was chosen by referring to the feature selection results from the experiment. QDE-SVM showed a superior cell type classification performance among QDE wrapping with other ML classifiers as well as the recent wrapper methods (i.e., FSCAM, SSD-LAHC, MA-HS, and BSF). QDE-SVM achieved an average accuracy of 0.9559, while the other wrapper methods achieved average accuracies in the range of 0.8292 to 0.8872.
    Matched MeSH terms: Sequence Analysis, RNA/methods
  7. Fulltext clrDV: a differential variability test for RNA-Seq data based on the skew-normal distribution
    Li H, Khang TF
    PeerJ, 2023;11:e16126.
    PMID: 37790621 DOI: 10.7717/peerj.16126
    BACKGROUND: Pathological conditions may result in certain genes having expression variance that differs markedly from that of the control. Finding such genes from gene expression data can provide invaluable candidates for therapeutic intervention. Under the dominant paradigm for modeling RNA-Seq gene counts using the negative binomial model, tests of differential variability are challenging to develop, owing to dependence of the variance on the mean.

    METHODS: Here, we describe clrDV, a statistical method for detecting genes that show differential variability between two populations. We present the skew-normal distribution for modeling gene-wise null distribution of centered log-ratio transformation of compositional RNA-seq data.

    RESULTS: Simulation results show that clrDV has false discovery rate and probability of Type II error that are on par with or superior to existing methodologies. In addition, its run time is faster than its closest competitors, and remains relatively constant for increasing sample size per group. Analysis of a large neurodegenerative disease RNA-Seq dataset using clrDV successfully recovers multiple gene candidates that have been reported to be associated with Alzheimer's disease.

    Matched MeSH terms: Sequence Analysis, RNA/methods
  8. In Silico Identification and Characterization of circRNAs During Host-Pathogen Interactions
    Ealam Selvan M, Lim KS, Teo CH, Lim YY
    J Vis Exp, 2022 Oct 21.
    PMID: 36342167 DOI: 10.3791/64565
    Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via back-splicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wet-lab techniques. To solve this issue, a step-by-step protocol of in silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions.
    Matched MeSH terms: Sequence Analysis, RNA
  9. Fulltext Single-cell RNA sequencing analysis of shrimp immune cells identifies macrophage-like phagocytes
    Yang P, Chen Y, Huang Z, Xia H, Cheng L, Wu H, et al.
    Elife, 2022 Oct 06;11.
    PMID: 36200862 DOI: 10.7554/eLife.80127
    Despite the importance of innate immunity in invertebrates, the diversity and function of innate immune cells in invertebrates are largely unknown. Using single-cell RNA-seq, we identified prohemocytes, monocytic hemocytes, and granulocytes as the three major cell-types in the white shrimp hemolymph. Our results identified a novel macrophage-like subset called monocytic hemocytes 2 (MH2) defined by the expression of certain marker genes, including Nlrp3 and Casp1. This subtype of shrimp hemocytes is phagocytic and expresses markers that indicate some conservation with mammalian macrophages. Combined, our work resolves the heterogenicity of hemocytes in a very economically important aquatic species and identifies a novel innate immune cell subset that is likely a critical player in the immune responses of shrimp to threatening infectious diseases affecting this industry.
    Matched MeSH terms: Sequence Analysis, RNA
  10. Intracellular and exosomal microRNAome profiling of human vascular smooth muscle cells during replicative senescence
    Nguyen DDN, Zain SM, Kamarulzaman MH, Low TY, Chilian WM, Pan Y, et al.
    Am J Physiol Heart Circ Physiol, 2021 10 01;321(4):H770-H783.
    PMID: 34506226 DOI: 10.1152/ajpheart.00058.2021
    Vascular aging is highly associated with cardiovascular morbidity and mortality. Although the senescence of vascular smooth muscle cells (VSMCs) has been well established as a major contributor to vascular aging, intracellular and exosomal microRNA (miRNA) signaling pathways in senescent VSMCs have not been fully elucidated. This study aimed to identify the differential expression of intracellular and exosomal miRNA in human VSMCs (hVSMCs) during replicative senescence. To achieve this aim, intracellular and exosomal miRNAs were isolated from hVSMCs and subsequently subjected to whole genome small RNA next-generation sequencing, bioinformatics analyses, and qPCR validation. Three significant findings were obtained. First, senescent hVSMC-derived exosomes tended to cluster together during replicative senescence and the molecular weight of the exosomal protein tumor susceptibility gene 101 (TSG-101) increased relative to the intracellular TSG-101, suggesting potential posttranslational modifications of exosomal TSG-101. Second, there was a significant decrease in both intracellular and exosomal hsa-miR-155-5p expression [n = 3, false discovery rate (FDR) < 0.05], potentially being a cell type-specific biomarker of hVSMCs during replicative senescence. Importantly, hsa-miR-155-5p was found to associate with cell-cycle arrest and elevated oxidative stress. Lastly, miRNAs from the intracellular pool, that is, hsa-miR-664a-3p, hsa-miR-664a-5p, hsa-miR-664b-3p, hsa-miR-4485-3p, hsa-miR-10527-5p, and hsa-miR-12136, and that from the exosomal pool, that is, hsa-miR-7704, were upregulated in hVSMCs during replicative senescence (n = 3, FDR < 0.05). Interestingly, these novel upregulated miRNAs were not functionally well annotated in hVSMCs to date. In conclusion, hVSMC-specific miRNA expression profiles during replicative senescence potentially provide valuable insights into the signaling pathways leading to vascular aging.NEW & NOTEWORTHY This is the first study on intracellular and exosomal miRNA profiling on human vascular smooth muscle cells during replicative senescence. Specific dysregulated sets of miRNAs were identified from human vascular smooth muscle cells. Hsa-miR-155-5p was significantly downregulated in both intracellular and exosomal hVSMCs, suggesting its crucial role in cellular senescence. Hsa-miR-155-5p might be the mediator in linking cellular senescence to vascular aging and atherosclerosis.
    Matched MeSH terms: Sequence Analysis, RNA
  11. Fulltext Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology
    Sathasivam HP, Kist R, Sloan P, Thomson P, Nugent M, Alexander J, et al.
    Br J Cancer, 2021 Aug;125(3):413-421.
    PMID: 33972745 DOI: 10.1038/s41416-021-01411-z
    BACKGROUND: This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.

    METHODS: Patients with oral epithelial dysplasia at one hospital were selected as the 'training set' (n = 56) whilst those at another hospital were selected for the 'test set' (n = 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.

    RESULTS: A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65, p = 0.0003].

    CONCLUSIONS: This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.

    Matched MeSH terms: Sequence Analysis, RNA
  12. Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy
    Chong ZX, Ho WY, Yeap SK, Wang ML, Chien Y, Verusingam ND, et al.
    J Chin Med Assoc, 2021 Jun 01;84(6):563-576.
    PMID: 33883467 DOI: 10.1097/JCMA.0000000000000535
    Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.
    Matched MeSH terms: Sequence Analysis, RNA*
  13. Fulltext Molecular characterization of the viral structural protein genes in the first outbreak of dengue virus type 2 in Hunan Province, inland China in 2018
    Guan J, He Z, Qin M, Deng X, Chen J, Duan S, et al.
    BMC Infect Dis, 2021 Feb 10;21(1):166.
    PMID: 33568111 DOI: 10.1186/s12879-021-05823-3
    BACKGROUND: An unexpected dengue outbreak occurred in Hunan Province in 2018. This was the first dengue outbreak in this area of inland China, and 172 cases were reported.

    METHODS: To verify the causative agent of this outbreak and characterise the viral genes, the genes encoding the structural proteins C/prM/E of viruses isolated from local residents were sequenced followed by mutation and phylogenetic analysis. Recombination, selection pressure, potential secondary structure and three-dimensional structure analyses were also performed.

    RESULTS: Phylogenetic analysis revealed that all epidemic strains were of the cosmopolitan DENV-2 genotype and were most closely related to the Zhejiang strain (MH010629, 2017) and then the Malaysia strain (KJ806803, 2013). Compared with the sequence of DENV-2SS, 151 base substitutions were found in the sequences of 89 isolates; these substitutions resulted in 20 non-synonymous mutations, of which 17 mutations existed in all samples (two in the capsid protein, six in the prM/M proteins, and nine in the envelope proteins). Moreover, amino acid substitutions at the 602nd (E322:Q → H) and 670th (E390: N → S) amino acids may have enhanced the virulence of the epidemic strains. One new DNA binding site and five new protein binding sites were observed. Two polynucleotide binding sites and seven protein binding sites were lost in the epidemic strains compared with DENV-2SS. Meanwhile, five changes were found in helical regions. Minor changes were observed in helical transmembrane and disordered regions. The 429th amino acid of the E protein switched from a histamine (positively charged) to an asparagine (neutral) in all 89 isolated strains. No recombination events or positive selection pressure sites were observed. To our knowledge, this study is the first to analyse the genetic characteristics of epidemic strains in the first dengue outbreak in Hunan Province in inland China.

    CONCLUSIONS: The causative agent is likely to come from Zhejiang Province, a neighbouring province where dengue fever broke out in 2017. This study may help clarify the intrinsic geographical relatedness of DENV-2 and contribute to further research on pathogenicity and vaccine development.

    Matched MeSH terms: Sequence Analysis, RNA
  14. Fulltext Emergence of equine-like G3 strains as the dominant rotavirus among children under five with diarrhea in Sabah, Malaysia  during 2018-2019
    Amit LN, Mori D, John JL, Chin AZ, Mosiun AK, Jeffree MS, et al.
    PLoS One, 2021;16(7):e0254784.
    PMID: 34320003 DOI: 10.1371/journal.pone.0254784
    Rotavirus infection is a dilemma for developing countries, including Malaysia. Although commercial rotavirus vaccines are available, these are not included in Malaysia's national immunization program. A scarcity of data about rotavirus genotype distribution could be partially to blame for this policy decision, because there are no data for rotavirus genotype distribution in Malaysia over the past 20 years. From January 2018 to March 2019, we conducted a study to elucidate the rotavirus burden and genotype distribution in the Kota Kinabalu and Kunak districts of the state of Sabah. Stool specimens were collected from children under 5 years of age, and rotavirus antigen in these samples was detected using commercially available kit. Electropherotypes were determined by polyacrylamide gel electrophoresis of genomic RNA. G and P genotypes were determined by RT-PCR using type specific primers. The nucleotide sequence of the amplicons was determined by Sanger sequencing and phylogenetic analysis was performed by neighbor-joining method. Rotavirus was identified in 43 (15.1%) children with watery diarrhea. The male:female ratio (1.9:1) of the rotavirus-infected children clearly showed that it affected predominantly boys, and children 12-23 months of age. The genotypes identified were G3P[8] (74% n = 31), followed by G1P[8] (14% n = 6), G12P[6](7% n = 3), G8P[8](3% n = 1), and GxP[8] (3% n = 1). The predominant rotavirus circulating among the children was the equine-like G3P[8] (59.5% n = 25) with a short electropherotype. Eleven electropherotypes were identified among 34 strains, indicating substantial diversity among the circulating strains. The circulating genotypes were also phylogenetically diverse and related to strains from several different countries. The antigenic epitopes present on VP7 and VP4 of Sabahan G3 and equine-like G3 differed considerably from that of the RotaTeq vaccine strain. Our results also indicate that considerable genetic exchange is occurring in Sabahan strains. Sabah is home to a number of different ethnic groups, some of which culturally are in close contact with animals, which might contribute to the evolution of diverse rotavirus strains. Sabah is also a popular tourist destination, and a large number of tourists from different countries possibly contributes to the diversity of circulating rotavirus genotypes. Considering all these factors which are contributing rotavirus genotype diversity, continuous surveillance of rotavirus strains is of utmost importance to monitor the pre- and post-vaccination efficacy of rotavirus vaccines in Sabah.
    Matched MeSH terms: Sequence Analysis, RNA
  15. Fulltext Transcriptome analysis of chicken intraepithelial lymphocyte natural killer cells infected with very virulent infectious bursal disease virus
    Boo SY, Tan SW, Alitheen NB, Ho CL, Omar AR, Yeap SK
    Sci Rep, 2020 10 27;10(1):18348.
    PMID: 33110122 DOI: 10.1038/s41598-020-75340-x
    The infectious bursal disease (IBD) is an acute immunosuppressive viral disease that significantly affects the economics of the poultry industry. The IBD virus (IBDV) was known to infect B lymphocytes and activate macrophage and T lymphocytes, but there are limited studies on the impact of IBDV infection on chicken intraepithelial lymphocyte natural killer (IEL-NK) cells. This study employed an mRNA sequencing approach to investigate the early regulation of gene expression patterns in chicken IEL-NK cells after infection with very virulent IBDV strain UPM0081. A total of 12,141 genes were expressed in uninfected chicken IEL-NK cells, and most of the genes with high expression were involved in the metabolic pathway, whereas most of the low expressed genes were involved in the cytokine-cytokine receptor pathway. A total of 1,266 genes were differentially expressed (DE) at 3 day-post-infection (dpi), and these DE genes were involved in inflammation, antiviral response and interferon stimulation. The innate immune response was activated as several genes involved in inflammation, antiviral response and recruitment of NK cells to the infected area were up-regulated. This is the first study to examine the whole transcriptome profile of chicken NK cells towards IBDV infection and provides better insight into the early immune response of chicken NK cells.
    Matched MeSH terms: Sequence Analysis, RNA/veterinary
  16. Fulltext Mapping a Circular RNA-microRNA-mRNA-Signaling Regulatory Axis That Modulates Stemness Properties of Cancer Stem Cell Populations in Colorectal Cancer Spheroid Cells
    Rengganaten V, Huang CJ, Tsai PH, Wang ML, Yang YP, Lan YT, et al.
    Int J Mol Sci, 2020 Oct 23;21(21).
    PMID: 33114016 DOI: 10.3390/ijms21217864
    Spheroidal cancer cell cultures have been used to enrich cancer stem cells (CSC), which are thought to contribute to important clinical features of tumors. This study aimed to map the regulatory networks driven by circular RNAs (circRNAs) in CSC-enriched colorectal cancer (CRC) spheroid cells. The spheroid cells established from two CRC cell lines acquired stemness properties in pluripotency gene expression and multi-lineage differentiation capacity. Genome-wide sequencing identified 1503 and 636 circRNAs specific to the CRC parental and spheroid cells, respectively. In the CRC spheroids, algorithmic analyses unveiled a core network of mRNAs involved in modulating stemness-associated signaling pathways, driven by a circRNA-microRNA (miRNA)-mRNA axis. The two major circRNAs, hsa_circ_0066631 and hsa_circ_0082096, in this network were significantly up-regulated in expression levels in the spheroid cells. The two circRNAs were predicted to target and were experimentally shown to down-regulate miR-140-3p, miR-224, miR-382, miR-548c-3p and miR-579, confirming circRNA sponging of the targeted miRNAs. Furthermore, the affected miRNAs were demonstrated to inhibit degradation of six mRNA targets, viz. ACVR1C/ALK7, FZD3, IL6ST/GP130, SKIL/SNON, SMAD2 and WNT5, in the CRC spheroid cells. These mRNAs encode proteins that are reported to variously regulate the GP130/Stat, Activin/Nodal, TGF-β/SMAD or Wnt/β-catenin signaling pathways in controlling various aspects of CSC stemness. Using the CRC spheroid cell model, the novel circRNA-miRNA-mRNA axis mapped in this work forms the foundation for the elucidation of the molecular mechanisms of the complex cellular and biochemical processes that determine CSC stemness properties of cancer cells, and possibly for designing therapeutic strategies for CRC treatment by targeting CSC.
    Matched MeSH terms: Sequence Analysis, RNA
  17. Fulltext Transcriptome dataset from bark and latex tissues of three Hevea brasiliensis clones
    Abu Bakar MF, Kamerkar U, Abdul Rahman SN, Muhd Sakaff MKL, Othman AS
    Data Brief, 2020 Oct;32:106188.
    PMID: 32904357 DOI: 10.1016/j.dib.2020.106188
    Hevea brasiliensis is exploited for its latex production, and it is the only viable source of natural rubber worldwide. The demand for natural rubber remains high due its high-quality properties, which synthetic rubber cannot compete with. In this paper, we present transcriptomic data and analysis of three H. brasiliensis clones using tissue from latex and bark tissues collected from 10-year-old plant. The combined, assembled transcripts were mapped onto an H. brasiliensis draft genome. Gene ontology analysis showed that the most abundant transcripts related to molecular functions, followed by biological processes and cellular components. Simple sequence repeats (SSR) and single nucleotide polymorphisms (SNP) were also identified, and these can be useful for selection of parental and new clones in a breeding program. Data generated by RNA sequencing were deposited in the NCBI public repository under accession number PRJNA629890.
    Matched MeSH terms: Sequence Analysis, RNA
  18. Identifying IGH disease clones for MRD monitoring in childhood B-cell acute lymphoblastic leukemia using RNA-Seq
    Li Z, Jiang N, Lim EH, Chin WHN, Lu Y, Chiew KH, et al.
    Leukemia, 2020 09;34(9):2418-2429.
    PMID: 32099036 DOI: 10.1038/s41375-020-0774-4
    Identifying patient-specific clonal IGH/TCR junctional sequences is critical for minimal residual disease (MRD) monitoring. Conventionally these junctional sequences are identified using laborious Sanger sequencing of excised heteroduplex bands. We found that the IGH is highly expressed in our diagnostic B-cell acute lymphoblastic leukemia (B-ALL) samples using RNA-Seq. Therefore, we used RNA-Seq to identify IGH disease clone sequences in 258 childhood B-ALL samples for MRD monitoring. The amount of background IGH rearrangements uncovered by RNA-Seq followed the Zipf's law with IGH disease clones easily identified as outliers. Four hundred and ninety-seven IGH disease clones (median 2, range 0-7 clones/patient) are identified in 90.3% of patients. High hyperdiploid patients have the most IGH disease clones (median 3) while DUX4 subtype has the least (median 1) due to the rearrangements involving the IGH locus. In all, 90.8% of IGH disease clones found by Sanger sequencing are also identified by RNA-Seq. In addition, RNA-Seq identified 43% more IGH disease clones. In 69 patients lacking sensitive IGH targets, targeted NGS IGH MRD showed high correlation (R = 0.93; P = 1.3 × 10-14), better relapse prediction than conventional RQ-PCR MRD using non-IGH targets. In conclusion, RNA-Seq can identify patient-specific clonal IGH junctional sequences for MRD monitoring, adding to its usefulness for molecular diagnosis in childhood B-ALL.
    Matched MeSH terms: Sequence Analysis, RNA/methods*
  19. Isolation of SARS-CoV-2-related coronavirus from Malayan pangolins
    Xiao K, Zhai J, Feng Y, Zhou N, Zhang X, Zou JJ, et al.
    Nature, 2020 07;583(7815):286-289.
    PMID: 32380510 DOI: 10.1038/s41586-020-2313-x
    The current outbreak of coronavirus disease-2019 (COVID-19) poses unprecedented challenges to global health1. The new coronavirus responsible for this outbreak-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-shares high sequence identity to SARS-CoV and a bat coronavirus, RaTG132. Although bats may be the reservoir host for a variety of coronaviruses3,4, it remains unknown whether SARS-CoV-2 has additional host species. Here we show that a coronavirus, which we name pangolin-CoV, isolated from a Malayan pangolin has 100%, 98.6%, 97.8% and 90.7% amino acid identity with SARS-CoV-2 in the E, M, N and S proteins, respectively. In particular, the receptor-binding domain of the S protein of pangolin-CoV is almost identical to that of SARS-CoV-2, with one difference in a noncritical amino acid. Our comparative genomic analysis suggests that SARS-CoV-2 may have originated in the recombination of a virus similar to pangolin-CoV with one similar to RaTG13. Pangolin-CoV was detected in 17 out of the 25 Malayan pangolins that we analysed. Infected pangolins showed clinical signs and histological changes, and circulating antibodies against pangolin-CoV reacted with the S protein of SARS-CoV-2. The isolation of a coronavirus from pangolins that is closely related to SARS-CoV-2 suggests that these animals have the potential to act as an intermediate host of SARS-CoV-2. This newly identified coronavirus from pangolins-the most-trafficked mammal in the illegal wildlife trade-could represent a future threat to public health if wildlife trade is not effectively controlled.
    Matched MeSH terms: Sequence Analysis, RNA
  20. Transcriptome-wide identification and characterization of the Rab GTPase family in mango
    Lawson T, Lycett GW, Mayes S, Ho WK, Chin CF
    Mol Biol Rep, 2020 Jun;47(6):4183-4197.
    PMID: 32444976 DOI: 10.1007/s11033-020-05519-y
    The Rab GTPase family plays a vital role in several plant physiological processes including fruit ripening. Fruit softening during ripening involves trafficking of cell wall polymers and enzymes between cellular compartments. Mango, an economically important fruit crop, is known for its delicious taste, exotic flavour and nutritional value. So far, there is a paucity of information on the mango Rab GTPase family. In this study, 23 genes encoding Rab proteins were identified in mango by a comprehensive in silico approach. Sequence alignment and similarity tree analysis with the model plant Arabidopsis as a reference enabled the bona fide assignment of the deduced mango proteins to classify into eight subfamilies. Expression analysis by RNA-Sequencing (RNA-Seq) showed that the Rab genes were differentially expressed in ripe and unripe mangoes suggesting the involvement of vesicle trafficking during ripening. Interaction analysis showed that the proteins involved in vesicle trafficking and cell wall softening were interconnected providing further evidence of the involvement of the Rab GTPases in fruit softening. Correlation analyses showed a significant relationship between the expression level of the RabA3 and RabA4 genes and fruit firmness at the unripe stage of the mango varieties suggesting that the differences in gene expression level might be associated with the contrasting firmness of these varieties. This study will not only provide new insights into the complexity of the ripening-regulated molecular mechanism but also facilitate the identification of potential Rab GTPases to address excessive fruit softening.
    Matched MeSH terms: Sequence Analysis, RNA/methods
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