Journal articles on the topic 'Transcriptomic analysi'
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1
Ochsner, Scott A., Christopher M. Watkins, Apollo McOwiti, Xueping Xu, Yolanda F. Darlington, Michael D. Dehart, Austin J. Cooney, David L. Steffen, Lauren B. Becnel, and Neil J. McKenna. "Transcriptomine, a web resource for nuclear receptor signaling transcriptomes." Physiological Genomics 44, no. 17 (September 1, 2012): 853–63. http://dx.doi.org/10.1152/physiolgenomics.00033.2012.
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The nuclear receptor (NR) superfamily of ligand-regulated transcription factors directs ligand- and tissue-specific transcriptomes in myriad developmental, metabolic, immunological, and reproductive processes. The NR signaling field has generated a wealth of genome-wide expression data points, but due to deficits in their accessibility, annotation, and integration, the full potential of these studies has not yet been realized. We searched public gene expression databases and MEDLINE for global transcriptomic datasets relevant to NRs, their ligands, and coregulators. We carried out extensive, deep reannotation of the datasets using controlled vocabularies for RNA Source and regulating molecule and resolved disparate gene identifiers to official gene symbols to facilitate comparison of fold changes and their significance across multiple datasets. We assembled these data points into a database, Transcriptomine ( http://www.nursa.org/transcriptomine ), that allows for multiple, menu-driven querying strategies of this transcriptomic “superdataset,” including single and multiple genes, Gene Ontology terms, disease terms, and uploaded custom gene lists. Experimental variables such as regulating molecule, RNA Source, as well as fold-change and P value cutoff values can be modified, and full data records can be either browsed or downloaded for downstream analysis. We demonstrate the utility of Transcriptomine as a hypothesis generation and validation tool using in silico and experimental use cases. Our resource empowers users to instantly and routinely mine the collective biology of millions of previously disparate transcriptomic data points. By incorporating future transcriptome-wide datasets in the NR signaling field, we anticipate Transcriptomine developing into a powerful resource for the NR- and other signal transduction research communities.
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Callaway, Edward M., Hong-Wei Dong, Joseph R. Ecker, Michael J. Hawrylycz, Z. Josh Huang, Ed S. Lein, John Ngai, et al. "A multimodal cell census and atlas of the mammalian primary motor cortex." Nature 598, no. 7879 (October 6, 2021): 86–102. http://dx.doi.org/10.1038/s41586-021-03950-0.
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AbstractHere we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input–output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.
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Nesterenko, Maksim, and Aleksei Miroliubov. "From head to rootlet: comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea: Rhizocephala)." F1000Research 11 (May 27, 2022): 583. http://dx.doi.org/10.12688/f1000research.110492.1.
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Background: Rhizocephalan barnacles stand out in the diverse world of metazoan parasites. The body of a rhizocephalan female is modified beyond revealing any recognizable morphological features, consisting of the interna, the system of rootlets, and the externa, a sac-like reproductive body. Moreover, rhizocephalans have an outstanding ability to control their hosts, literally turning them into “zombies”. Despite all these amazing traits, there is no genomic and transcriptomic data about any Rhizocephala. Methods: We collected transcriptomes from four body parts of an adult female rhizocephalan Peltogaster reticulata: externa and main, growing, and thoracic parts of the interna. We used all prepared data for the de novo assembly of the reference transcriptome. Next, a set of encoded proteins was determined, the expression levels of protein-coding genes in different parts of the parasite body were calculated and lists of enriched bioprocesses were identified. We also in silico identified and analyzed sets of potential excretory / secretory proteins. Finally, we applied phylostratigraphy and evolutionary transcriptomics approaches to our data. Results: The assembled reference transcriptome included transcripts of 12,620 protein-coding genes and was the first for both P. reticulata and Rhizocephala. Based on the results obtained, the spatial heterogeneity of protein-coding genes expression in different regions of P. reticulata adult female body was established. The results of both transcriptomic analysis and histological studies indicated the presence of germ-like cells in the lumen of the interna. The potential molecular basis of the interaction between the nervous system of the host and the parasite's interna was also determined. Given the prolonged expression of development-associated genes, we suggest that rhizocephalans “got stuck in the metamorphosis”, even in their reproductive stage. Conclusions: The results of the first comparative transcriptomic analysis for Rhizocephala not only clarified but also expanded the existing ideas about the biology of this amazing parasites.
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Nesterenko, Maksim, and Aleksei Miroliubov. "From head to rootlet: comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea: Rhizocephala)." F1000Research 11 (January 9, 2023): 583. http://dx.doi.org/10.12688/f1000research.110492.2.
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Background: Rhizocephalan barnacles stand out in the diverse world of metazoan parasites. The body of a rhizocephalan female is modified beyond revealing any recognizable morphological features, consisting of the interna, a system of rootlets, and the externa, a sac-like reproductive body. Moreover, rhizocephalans have an outstanding ability to control their hosts, literally turning them into “zombies”. Despite all these amazing traits, there are no genomic or transcriptomic data about any Rhizocephala. Methods: We collected transcriptomes from four body parts of an adult female rhizocephalan Peltogaster reticulata: the externa, and the main, growing, and thoracic parts of the interna. We used all prepared data for the de novo assembly of the reference transcriptome. Next, a set of encoded proteins was determined, the expression levels of protein-coding genes in different parts of the parasite’s body were calculated and lists of enriched bioprocesses were identified. We also in silico identified and analyzed sets of potential excretory / secretory proteins. Finally, we applied phylostratigraphy and evolutionary transcriptomics approaches to our data. Results: The assembled reference transcriptome included transcripts of 12,620 protein-coding genes and was the first for any rhizocephalan. Based on the results obtained, the spatial heterogeneity of protein-coding gene expression in different regions of the adult female body of P. reticulata was established. The results of both transcriptomic analysis and histological studies indicated the presence of germ-like cells in the lumen of the interna. The potential molecular basis of the interaction between the nervous system of the host and the parasite's interna was also determined. Given the prolonged expression of development-associated genes, we suggest that rhizocephalans “got stuck in their metamorphosis”, even at the reproductive stage. Conclusions: The results of the first comparative transcriptomic analysis for Rhizocephala not only clarified but also expanded the existing ideas about the biology of these extraordinary parasites.
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Chen, Wanze, Orane Guillaume-Gentil, Pernille Yde Rainer, Christoph G. Gäbelein, Wouter Saelens, Vincent Gardeux, Amanda Klaeger, et al. "Live-seq enables temporal transcriptomic recording of single cells." Nature 608, no. 7924 (August 17, 2022): 733–40. http://dx.doi.org/10.1038/s41586-022-05046-9.
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AbstractSingle-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity1. However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy2,3, thus allowing to couple a cell’s ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell’s trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.
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Gui, Yu, Xiujing He, Jing Yu, and Jing Jing. "Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy." Journal of Clinical Medicine 12, no. 4 (February 6, 2023): 1279. http://dx.doi.org/10.3390/jcm12041279.
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The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.
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Cheon, Seongmin, Sung-Gwon Lee, Hyun-Hee Hong, Hyun-Gwan Lee, Kwang Young Kim, and Chungoo Park. "A guide to phylotranscriptomic analysis for phycologists." Algae 36, no. 4 (December 15, 2021): 333–40. http://dx.doi.org/10.4490/algae.2021.36.12.7.
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Phylotranscriptomics is the study of phylogenetic relationships among taxa based on their DNA sequences derived from transcriptomes. Because of the relatively low cost of transcriptome sequencing compared with genome sequencing and the fact that phylotranscriptomics is almost as reliable as phylogenomics, the phylotranscriptomic analysis has recently emerged as the preferred method for studying evolutionary biology. However, it is challenging to perform transcriptomic and phylogenetic analyses together without programming expertise. This study presents a protocol for phylotranscriptomic analysis to aid marine biologists unfamiliar with UNIX command-line interface and bioinformatics tools. Here, we used transcriptomes to reconstruct a molecular phylogeny of dinoflagellate protists, a diverse and globally abundant group of marine plankton organisms whose large and complex genomic sequences have impeded conventional phylogenic analysis based on genomic data. We hope that our proposed protocol may serve as practical and helpful information for the training and education of novice phycologists.
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Chaudhuri, Roy R., Lu Yu, Alpa Kanji, Timothy T. Perkins, Paul P. Gardner, Jyoti Choudhary, Duncan J. Maskell, and Andrew J. Grant. "Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome." Microbiology 157, no. 10 (October 1, 2011): 2922–32. http://dx.doi.org/10.1099/mic.0.050278-0.
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C ampylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community.
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Ortiz, Randy, Priyanka Gera, Christopher Rivera, and Juan C. Santos. "Pincho: A Modular Approach to High Quality De Novo Transcriptomics." Genes 12, no. 7 (June 22, 2021): 953. http://dx.doi.org/10.3390/genes12070953.
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Transcriptomic reconstructions without reference (i.e., de novo) are common for data samples derived from non-model biological systems. These assemblies involve massive parallel short read sequence reconstructions from experiments, but they usually employ ad-hoc bioinformatic workflows that exhibit limited standardization and customization. The increasing number of transcriptome assembly software continues to provide little room for standardization which is exacerbated by the lack of studies on modularity that compare the effects of assembler synergy. We developed a customizable management workflow for de novo transcriptomics that includes modular units for short read cleaning, assembly, validation, annotation, and expression analysis by connecting twenty-five individual bioinformatic tools. With our software tool, we were able to compare the assessment scores based on 129 distinct single-, bi- and tri-assembler combinations with diverse k-mer size selections. Our results demonstrate a drastic increase in the quality of transcriptome assemblies with bi- and tri- assembler combinations. We aim for our software to improve de novo transcriptome reconstructions for the ever-growing landscape of RNA-seq data derived from non-model systems. We offer guidance to ensure the most complete transcriptomic reconstructions via the inclusion of modular multi-assembly software controlled from a single master console.
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Macrander, Jason, Jyothirmayi Panda, Daniel Janies, Marymegan Daly, and Adam M. Reitzel. "Venomix: a simple bioinformatic pipeline for identifying and characterizing toxin gene candidates from transcriptomic data." PeerJ 6 (July 31, 2018): e5361. http://dx.doi.org/10.7717/peerj.5361.
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The advent of next-generation sequencing has resulted in transcriptome-based approaches to investigate functionally significant biological components in a variety of non-model organism. This has resulted in the area of “venomics”: a rapidly growing field using combined transcriptomic and proteomic datasets to characterize toxin diversity in a variety of venomous taxa. Ultimately, the transcriptomic portion of these analyses follows very similar pathways after transcriptome assembly often including candidate toxin identification using BLAST, expression level screening, protein sequence alignment, gene tree reconstruction, and characterization of potential toxin function. Here we describe the Python package Venomix, which streamlines these processes using common bioinformatic tools along with ToxProt, a publicly available annotated database comprised of characterized venom proteins. In this study, we use the Venomix pipeline to characterize candidate venom diversity in four phylogenetically distinct organisms, a cone snail (Conidae; Conus sponsalis), a snake (Viperidae; Echis coloratus), an ant (Formicidae; Tetramorium bicarinatum), and a scorpion (Scorpionidae; Urodacus yaschenkoi). Data on these organisms were sampled from public databases, with each original analysis using different approaches for transcriptome assembly, toxin identification, or gene expression quantification. Venomix recovered numerically more candidate toxin transcripts for three of the four transcriptomes than the original analyses and identified new toxin candidates. In summary, we show that the Venomix package is a useful tool to identify and characterize the diversity of toxin-like transcripts derived from transcriptomic datasets. Venomix is available at: https://bitbucket.org/JasonMacrander/Venomix/.
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Udaondo, Zulema, Kanchana Sittikankaew, Tanaporn Uengwetwanit, Thidathip Wongsurawat, Chutima Sonthirod, Piroon Jenjaroenpun, Wirulda Pootakham, Nitsara Karoonuthaisiri, and Intawat Nookaew. "Comparative Analysis of PacBio and Oxford Nanopore Sequencing Technologies for Transcriptomic Landscape Identification of Penaeus monodon." Life 11, no. 8 (August 23, 2021): 862. http://dx.doi.org/10.3390/life11080862.
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With the advantages that long-read sequencing platforms such as Pacific Biosciences (Menlo Park, CA, USA) (PacBio) and Oxford Nanopore Technologies (Oxford, UK) (ONT) can offer, various research fields such as genomics and transcriptomics can exploit their benefits. Selecting an appropriate sequencing platform is undoubtedly crucial for the success of the research outcome, thus there is a need to compare these long-read sequencing platforms and evaluate them for specific research questions. This study aims to compare the performance of PacBio and ONT platforms for transcriptomic analysis by utilizing transcriptome data from three different tissues (hepatopancreas, intestine, and gonads) of the juvenile black tiger shrimp, Penaeus monodon. We compared three important features: (i) main characteristics of the sequencing libraries and their alignment with the reference genome, (ii) transcript assembly features and isoform identification, and (iii) correlation of the quantification of gene expression levels for both platforms. Our analyses suggest that read-length bias and differences in sequencing throughput are highly influential factors when using long reads in transcriptome studies. These comparisons can provide a guideline when designing a transcriptome study utilizing these two long-read sequencing technologies.
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Herrera-Uribe, Juber, Kristen A. Byrne, Haibo Liu, Sage Becker, Crystal L. Loving, and Christopher K. Tuggle. "The transcriptional landscape of porcine peripheral blood immune cells." Journal of Immunology 204, no. 1_Supplement (May 1, 2020): 92.18. http://dx.doi.org/10.4049/jimmunol.204.supp.92.18.
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Abstract Blood consists of different immune cells with essential functions given by distinct molecular signatures including transcriptomic profiles. The porcine immune system shares many similarities with that in human; however, the porcine immune cell transcriptome has not been as comprehensively studied. To identify distinct transcriptomic profiles of major porcine peripheral blood immune cells, we employed magnetic separation and fluorescence activated cell sorting methods to isolate 9 different cell types from blood PBMCs from two healthy pigs, representing monocytes, neutrophils, NK cells and specific populations of T and B cells. We obtained deep individual cell type transcriptomes using RNA-seq, detecting up to 10,974 genes. Principal component analysis revealed appropriate clustering of replicate samples and the separation of T, B, NK and myeloid cell groups. Pairwise comparisons revealed significant expression of a large number of genes specific for monocytes, neutrophils and NK cells only, while enrichment analysis identified highly differentially expressed genes for all cell types. Gene Ontology term analysis showed high enrichment of biological processes related to the nature of each cell type (i.e., B cell antigen presentation enriched in B cell transcriptome). The gene enrichment and specific genes of porcine immune cells is being further validated in silico to human datasets using gene set enrichment analysis (GSEA), and in vitro using qRT-PCR analysis. Taken together, the gene expression profiles reported here is the first comprehensive transcriptomic study of circulating porcine immune cell types and provides a valuable resource to elucidate molecular markers for porcine immune cell identity and function.
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Gross, Joshua B., Dennis A. Sun, Brian M. Carlson, Sivan Brodo-Abo, and Meredith E. Protas. "Developmental Transcriptomic Analysis of the Cave-Dwelling Crustacean, Asellus aquaticus." Genes 11, no. 1 (December 29, 2019): 42. http://dx.doi.org/10.3390/genes11010042.
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Cave animals are a fascinating group of species often demonstrating characteristics including reduced eyes and pigmentation, metabolic efficiency, and enhanced sensory systems. Asellus aquaticus, an isopod crustacean, is an emerging model for cave biology. Cave and surface forms of this species differ in many characteristics, including eye size, pigmentation, and antennal length. Existing resources for this species include a linkage map, mapped regions responsible for eye and pigmentation traits, sequenced adult transcriptomes, and comparative embryological descriptions of the surface and cave forms. Our ultimate goal is to identify genes and mutations responsible for the differences between the cave and surface forms. To advance this goal, we decided to use a transcriptomic approach. Because many of these changes first appear during embryonic development, we sequenced embryonic transcriptomes of cave, surface, and hybrid individuals at the stage when eyes and pigment become evident in the surface form. We generated a cave, a surface, a hybrid, and an integrated transcriptome to identify differentially expressed genes in the cave and surface forms. Additionally, we identified genes with allele-specific expression in hybrid individuals. These embryonic transcriptomes are an important resource to assist in our ultimate goal of determining the genetic underpinnings of the divergence between the cave and surface forms.
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Ungar, B., M. Yavzori, E. Fudim, O. Picard, U. Kopylov, R. Eliakim, D. Shouval, et al. "P032 Host transcriptome signatures in human fecal-washes predict histological remission in IBD patients." Journal of Crohn's and Colitis 16, Supplement_1 (January 1, 2022): i152—i153. http://dx.doi.org/10.1093/ecco-jcc/jjab232.161.
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Abstract Background Colonoscopy is the gold standard for evaluation of inflammation in inflammatory bowel diseases (IBD), yet entails cumbersome preparations and risks of injury. Existing non-invasive prognostic tools are limited in their diagnostic power. Moreover, transcriptomics of colonic biopsies have been inconclusive in their association with clinical features. Our aim was to assess the utility of host transcriptomics of fecal wash samples of IBD patients compared to controls. Methods In this prospective cohort study, we obtained biopsies and fecal-wash samples from IBD patients and controls undergoing lower endoscopy. We performed RNAseq of biopsies and matching fecal-washes, and associated them with endoscopic and histological inflammation status. We also performed fecal mass-spectrometry proteomics on a subset of samples. We inferred cell compositions using computational deconvolution and used classification algorithms to identify informative genes. Results We analyzed biopsies and fecal washes from 39 patients (19 IBD, 20 controls). Host fecal-transcriptome carried information that was distinct from biopsy RNAseq and fecal proteomics. Transcriptomics of fecal washes, yet not of biopsies, from patients with histological inflammation were significantly correlated to one another (p=5.3*10–12). Fecal-transcriptome was significantly more powerful in identifying histological inflammation compared to transcriptome of intestinal biopsies (150 genes with area-under-the-curve >0.9 in fecal samples versus 10 genes in biopsy RNAseq). Fecal samples were enriched in inflammatory monocytes, regulatory T cells, natural killer-cells and innate lymphoid cells. Figure 1 - Fecal-wash host transcriptome predicts histological inflammation. A) Study layout, B) Clustergram of fecal-wash host cell mRNA signatures, demonstrating that patients with histological inflammation (red) are clustered when measuring fecal wash transcriptome yet not biopsy transcriptomes. C-D) Principle Component Analysis demonstrating improved separation of inflamed patients based on fecal host transcriptomes. E, F) Expression of host genes in fecal washes has higher statistical power (Area under the Curve, AUC) in classifying histological inflammation compared to biopsies. D shows NFKBIA as an example, E shows the AUC of the 5% best classifying genes, F shows the overall AUC based on biopsies or washes. Gray areas have AUC>0.9. G) UMAP of cells obtained from scRNAseq of mouse small intestine fecal washes. Conclusion Fecal wash host transcriptome is a powerful biomarker reflecting histological inflammation. Furthermore, it opens the way to identifying important correlates and therapeutic targets that may be obscure using biopsy transctriptomics.
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Dovrou, Aikaterini, Ekaterini Bei, Stelios Sfakianakis, Kostas Marias, Nickolas Papanikolaou, and Michalis Zervakis. "Synergies of Radiomics and Transcriptomics in Lung Cancer Diagnosis: A Pilot Study." Diagnostics 13, no. 4 (February 15, 2023): 738. http://dx.doi.org/10.3390/diagnostics13040738.
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Radiotranscriptomics is an emerging field that aims to investigate the relationships between the radiomic features extracted from medical images and gene expression profiles that contribute in the diagnosis, treatment planning, and prognosis of cancer. This study proposes a methodological framework for the investigation of these associations with application on non-small-cell lung cancer (NSCLC). Six publicly available NSCLC datasets with transcriptomics data were used to derive and validate a transcriptomic signature for its ability to differentiate between cancer and non-malignant lung tissue. A publicly available dataset of 24 NSCLC-diagnosed patients, with both transcriptomic and imaging data, was used for the joint radiotranscriptomic analysis. For each patient, 749 Computed Tomography (CT) radiomic features were extracted and the corresponding transcriptomics data were provided through DNA microarrays. The radiomic features were clustered using the iterative K-means algorithm resulting in 77 homogeneous clusters, represented by meta-radiomic features. The most significant differentially expressed genes (DEGs) were selected by performing Significance Analysis of Microarrays (SAM) and 2-fold change. The interactions among the CT imaging features and the selected DEGs were investigated using SAM and a Spearman rank correlation test with a False Discovery Rate (FDR) of 5%, leading to the extraction of 73 DEGs significantly correlated with radiomic features. These genes were used to produce predictive models of the meta-radiomics features, defined as p-metaomics features, by performing Lasso regression. Of the 77 meta-radiomic features, 51 can be modeled in terms of the transcriptomic signature. These significant radiotranscriptomics relationships form a reliable basis to biologically justify the radiomics features extracted from anatomic imaging modalities. Thus, the biological value of these radiomic features was justified via enrichment analysis on their transcriptomics-based regression models, revealing closely associated biological processes and pathways. Overall, the proposed methodological framework provides joint radiotranscriptomics markers and models to support the connection and complementarities between the transcriptome and the phenotype in cancer, as demonstrated in the case of NSCLC.
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Krüger, Manuela, Oushadee A. J. Abeyawardana, Claudia Krüger, Miloslav Juříček, and Helena Štorchová. "Differentially Expressed Genes Shared by Two Distinct Cytoplasmic Male Sterility (CMS) Types of Silene vulgaris Suggest the Importance of Oxidative Stress in Pollen Abortion." Cells 9, no. 12 (December 16, 2020): 2700. http://dx.doi.org/10.3390/cells9122700.
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Cytoplasmic male sterility (CMS), encoded by the interacting mitochondrial and nuclear genes, causes pollen abortion or non-viability. CMS is widely used in agriculture and extensively studied in crops. Much less is known about CMS in wild species. We performed a comparative transcriptomic analysis of male sterile and fertile individuals of Silene vulgaris, a model plant for the study of gynodioecy, to reveal the genes responsible for pollen abortion in this species. We used RNA-seq datasets previously employed for the analysis of mitochondrial and plastid transcriptomes of female and hermaphrodite flower buds, making it possible to compare the transcriptomes derived from three genomes in the same RNA specimen. We assembled de novo transcriptomes for two haplotypes of S. vulgaris and identified differentially expressed genes between the females and hermaphrodites, associated with stress response or pollen development. The gene for alternative oxidase was downregulated in females. The genetic pathways controlling CMS in S. vulgaris are similar to those in crops. The high number of the differentially expressed nuclear genes contrasts with the uniformity of organellar transcriptomes across genders, which suggests these pathways are evolutionarily conserved and that selective mechanisms may shield organellar transcription against changes in the cytoplasmic transcriptome.
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Wang, Changli, Lijun Chen, Yaobin Chen, Wenwen Jia, Xunhui Cai, Yufeng Liu, Fenghu Ji, et al. "Abnormal global alternative RNA splicing in COVID-19 patients." PLOS Genetics 18, no. 4 (April 14, 2022): e1010137. http://dx.doi.org/10.1371/journal.pgen.1010137.
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Viral infections can alter host transcriptomes by manipulating host splicing machinery. Despite intensive transcriptomic studies on SARS-CoV-2, a systematic analysis of alternative splicing (AS) in severe COVID-19 patients remains largely elusive. Here we integrated proteomic and transcriptomic sequencing data to study AS changes in COVID-19 patients. We discovered that RNA splicing is among the major down-regulated proteomic signatures in COVID-19 patients. The transcriptome analysis showed that SARS-CoV-2 infection induces widespread dysregulation of transcript usage and expression, affecting blood coagulation, neutrophil activation, and cytokine production. Notably, CD74 and LRRFIP1 had increased skipping of an exon in COVID-19 patients that disrupts a functional domain, which correlated with reduced antiviral immunity. Furthermore, the dysregulation of transcripts was strongly correlated with clinical severity of COVID-19, and splice-variants may contribute to unexpected therapeutic activity. In summary, our data highlight that a better understanding of the AS landscape may aid in COVID-19 diagnosis and therapy.
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Mattei, Daniele, Andranik Ivanov, Marc van Oostrum, Stanislav Pantelyushin, Juliet Richetto, Flavia Mueller, Michal Beffinger, et al. "Enzymatic Dissociation Induces Transcriptional and Proteotype Bias in Brain Cell Populations." International Journal of Molecular Sciences 21, no. 21 (October 26, 2020): 7944. http://dx.doi.org/10.3390/ijms21217944.
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Different cell isolation techniques exist for transcriptomic and proteotype profiling of brain cells. Here, we provide a systematic investigation of the influence of different cell isolation protocols on transcriptional and proteotype profiles in mouse brain tissue by taking into account single-cell transcriptomics of brain cells, proteotypes of microglia and astrocytes, and flow cytometric analysis of microglia. We show that standard enzymatic digestion of brain tissue at 37 °C induces profound and consistent alterations in the transcriptome and proteotype of neuronal and glial cells, as compared to an optimized mechanical dissociation protocol at 4 °C. These findings emphasize the risk of introducing technical biases and biological artifacts when implementing enzymatic digestion-based isolation methods for brain cell analyses.
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Barral-Arca, Ruth, Alberto Gómez-Carballa, Miriam Cebey-López, Xabier Bello, Federico Martinón-Torres, and Antonio Salas. "A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus." International Journal of Molecular Sciences 21, no. 5 (March 6, 2020): 1831. http://dx.doi.org/10.3390/ijms21051831.
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Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infection worldwide. The absence of a commercial vaccine and the limited success of current therapeutic strategies against RSV make further research necessary. We used a multi-cohort analysis approach to investigate host transcriptomic biomarkers and shed further light on the molecular mechanism underlying RSV-host interactions. We meta-analyzed seven transcriptome microarray studies from the public Gene Expression Omnibus (GEO) repository containing a total of 922 samples, including RSV, healthy controls, coronaviruses, enteroviruses, influenzas, rhinoviruses, and coinfections, from both adult and pediatric patients. We identified > 1500 genes differentially expressed when comparing the transcriptomes of RSV-infected patients against healthy controls. Functional enrichment analysis showed several pathways significantly altered, including immunologic response mediated by RSV infection, pattern recognition receptors, cell cycle, and olfactory signaling. In addition, we identified a minimal 17-transcript host signature specific for RSV infection by comparing transcriptomic profiles against other respiratory viruses. These multi-genic signatures might help to investigate future drug targets against RSV infection.
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Ashwin, Helen, Karin Seifert, Sarah Forrester, Najmeeyah Brown, Sandy MacDonald, Sally James, Dimitris Lagos, et al. "Tissue and host species-specific transcriptional changes in models of experimental visceral leishmaniasis." Wellcome Open Research 3 (October 29, 2018): 135. http://dx.doi.org/10.12688/wellcomeopenres.14867.1.
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Background: Human visceral leishmaniasis, caused by infection with Leishmania donovani or L. infantum, is a potentially fatal disease affecting 50,000-90,000 people yearly in 75 disease endemic countries, with more than 20,000 deaths reported. Experimental models of infection play a major role in understanding parasite biology, host-pathogen interaction, disease pathogenesis, and parasite transmission. In addition, they have an essential role in the identification and pre-clinical evaluation of new drugs and vaccines. However, our understanding of these models remains fragmentary. Although the immune response to Leishmania donovani infection in mice has been extensively characterized, transcriptomic analysis capturing the tissue-specific evolution of disease has yet to be reported. Methods: We provide an analysis of the transcriptome of spleen, liver and peripheral blood of BALB/c mice infected with L. donovani. Where possible, we compare our data in murine experimental visceral leishmaniasis with transcriptomic data in the public domain obtained from the study of L. donovani-infected hamsters and patients with human visceral leishmaniasis. Digitised whole slide images showing the histopathology in spleen and liver are made available via a dedicated website, www.leishpathnet.org. Results: Our analysis confirms marked tissue-specific alterations in the transcriptome of infected mice over time and identifies previously unrecognized parallels and differences between murine, hamster and human responses to infection. We show commonality of interferon-regulated genes whilst confirming a greater activation of type 2 immune pathways in infected hamsters compared to mice. Cytokine genes and genes encoding immune checkpoints were markedly tissue specific and dynamic in their expression, and pathways focused on non-immune cells reflected tissue specific immunopathology. Our data also addresses the value of measuring peripheral blood transcriptomics as a potential window into underlying systemic disease. Conclusions: Our transcriptomic data, coupled with histopathologic analysis of the tissue response, provide an additional resource to underpin future mechanistic studies and to guide clinical research.
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Ashwin, Helen, Karin Seifert, Sarah Forrester, Najmeeyah Brown, Sandy MacDonald, Sally James, Dimitris Lagos, et al. "Tissue and host species-specific transcriptional changes in models of experimental visceral leishmaniasis." Wellcome Open Research 3 (January 2, 2019): 135. http://dx.doi.org/10.12688/wellcomeopenres.14867.2.
Full textAbstract:
Background: Human visceral leishmaniasis, caused by infection with Leishmania donovani or L. infantum, is a potentially fatal disease affecting 50,000-90,000 people yearly in 75 disease endemic countries, with more than 20,000 deaths reported. Experimental models of infection play a major role in understanding parasite biology, host-pathogen interaction, disease pathogenesis, and parasite transmission. In addition, they have an essential role in the identification and pre-clinical evaluation of new drugs and vaccines. However, our understanding of these models remains fragmentary. Although the immune response to Leishmania donovani infection in mice has been extensively characterized, transcriptomic analysis capturing the tissue-specific evolution of disease has yet to be reported. Methods: We provide an analysis of the transcriptome of spleen, liver and peripheral blood of BALB/c mice infected with L. donovani. Where possible, we compare our data in murine experimental visceral leishmaniasis with transcriptomic data in the public domain obtained from the study of L. donovani-infected hamsters and patients with human visceral leishmaniasis. Digitised whole slide images showing the histopathology in spleen and liver are made available via a dedicated website, www.leishpathnet.org. Results: Our analysis confirms marked tissue-specific alterations in the transcriptome of infected mice over time and identifies previously unrecognized parallels and differences between murine, hamster and human responses to infection. We show commonality of interferon-regulated genes whilst confirming a greater activation of type 2 immune pathways in infected hamsters compared to mice. Cytokine genes and genes encoding immune checkpoints were markedly tissue specific and dynamic in their expression, and pathways focused on non-immune cells reflected tissue specific immunopathology. Our data also addresses the value of measuring peripheral blood transcriptomics as a potential window into underlying systemic disease. Conclusions: Our transcriptomic data, coupled with histopathologic analysis of the tissue response, provide an additional resource to underpin future mechanistic studies and to guide clinical research.
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Ahn, Antonio, Euan J. Rodger, Jyoti Motwani, Gregory Gimenez, Peter A. Stockwell, Matthew Parry, Peter Hersey, Aniruddha Chatterjee, and Michael R. Eccles. "Transcriptional Reprogramming and Constitutive PD-L1 Expression in Melanoma Are Associated with Dedifferentiation and Activation of Interferon and Tumour Necrosis Factor Signalling Pathways." Cancers 13, no. 17 (August 24, 2021): 4250. http://dx.doi.org/10.3390/cancers13174250.
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Melanoma is the most aggressive type of skin cancer, with increasing incidence worldwide. Advances in targeted therapy and immunotherapy have improved the survival of melanoma patients experiencing recurrent disease, but unfortunately treatment resistance frequently reduces patient survival. Resistance to targeted therapy is associated with transcriptomic changes and has also been shown to be accompanied by increased expression of programmed death ligand 1 (PD-L1), a potent inhibitor of immune response. Intrinsic upregulation of PD-L1 is associated with genome-wide DNA hypomethylation and widespread alterations in gene expression in melanoma cell lines. However, an in-depth analysis of the transcriptomic landscape of melanoma cells with intrinsically upregulated PD-L1 expression is lacking. To determine the transcriptomic landscape of intrinsically upregulated PD-L1 expression in melanoma, we investigated transcriptomes in melanomas with constitutive versus inducible PD-L1 expression (referred to as PD-L1CON and PD-L1IND). RNA-Seq analysis was performed on seven PD-L1CON melanoma cell lines and ten melanoma cell lines with low inducible PD-L1IND expression. We observed that PD-L1CON melanoma cells had a reprogrammed transcriptome with a characteristic pattern of dedifferentiated gene expression, together with active interferon (IFN) and tumour necrosis factor (TNF) signalling pathways. Furthermore, we identified key transcription factors that were also differentially expressed in PD-L1CON versus PD-L1IND melanoma cell lines. Overall, our studies describe transcriptomic reprogramming of melanomas with PD-L1CON expression.
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Darden, Dijoia B., Gabriela L. Ghita, Zhongkai Wang, Julie A. Stortz, Maria-Cecilia Lopez, Michael C. Cox, Russell B. Hawkins, et al. "Chronic Critical Illness Elicits a Unique Circulating Leukocyte Transcriptome in Sepsis Survivors." Journal of Clinical Medicine 10, no. 15 (July 21, 2021): 3211. http://dx.doi.org/10.3390/jcm10153211.
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Surgical sepsis has evolved into two major subpopulations: patients who rapidly recover, and those who develop chronic critical illness (CCI). Our primary aim was to determine whether CCI sepsis survivors manifest unique blood leukocyte transcriptomes in late sepsis that differ from transcriptomes among sepsis survivors with rapid recovery. In a prospective cohort study of surgical ICU patients, genome-wide expression analysis was conducted on total leukocytes in human whole blood collected on days 1 and 14 from sepsis survivors who rapidly recovered or developed CCI, defined as ICU length of stay ≥ 14 days with persistent organ dysfunction. Both sepsis patients who developed CCI and those who rapidly recovered exhibited marked changes in genome-wide expression at day 1 which remained abnormal through day 14. Although summary changes in gene expression were similar between CCI patients and subjects who rapidly recovered, CCI patients exhibited differential expression of 185 unique genes compared with rapid recovery patients at day 14 (p < 0.001). The transcriptomic patterns in sepsis survivors reveal an ongoing immune dyscrasia at the level of the blood leukocyte transcriptome, consistent with persistent inflammation and immune suppression. Furthermore, the findings highlight important genes that could compose a prognostic transcriptomic metric or serve as therapeutic targets among sepsis patients that develop CCI.
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Londin, Eric R., Eleftheria Hatzimichael, Phillipe Loher, Leonard C. Edelstein, Chad Shaw, Kathleen Delgrosso, Paolo M. Fortina, Paul F. Bray, Steven E. McKenzie, and Isidore Rigoutsos. "Towards a Reference Human Platelet Transcriptome: Evaluation Of Inter-Individual Correlations and Its Relationship With a Platelet Proteome." Blood 122, no. 21 (November 15, 2013): 2297. http://dx.doi.org/10.1182/blood.v122.21.2297.2297.
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Abstract Next generation sequencing of RNA (RNA-seq) is an emerging technology that has so far been used successfully to profile the transcriptomes of several cell types and cell states. For the platelet transcriptome, RNA-seq descriptions exist for only a few subjects. Additionally, there have been no studies of the same individual’s transcriptome using two different technologies. As such, it has been unclear how well platelet transcriptomes correlate among different donors or across different RNA platforms, and what the transcriptomes’ relationship is with the platelet proteome. We generated RNA-seq profiles of the long RNA transcriptomes from the platelets of 10 healthy young males (5 white and 5 black). In addition to RNA-seq, we profiled the platelet messenger RNAs of the same 10 individuals using the Affymetrix GeneChip System. We observed that the abundance of platelet mRNA transcripts was highly correlated across the 10 individuals, a finding that was independent of race and of the employed technology. Additionally, our RNA-seq data showed that these high inter-individual correlations extend beyond mRNAs to several categories of non-coding RNAs. However, there was a notable exception: the category of pseudogenes exhibited a clear difference in expression by race. Comparison of our mRNA signatures with the only publicly available quantitative platelet proteome data showed that most (87.5%) identified platelet proteins had a detectable corresponding mRNA. Interestingly, there was also a high number of mRNAs that were present in the transcriptomes of all 10 individuals but had no representation in the proteome. Spearman correlation of the relative abundances for those platelet genes that were represented by both an mRNA and a protein, revealed an unexpectedly weak correlation between the transcriptome and the proteome. Further analysis of the overlapping and non-overlapping platelet mRNAs and proteins identified groups of genes with very distinct characteristics. Gene Ontology analysis of the respective gene identifiers revealed that the gene groups corresponded to distinct cellular processes, an interesting finding that provides novel insights for platelet biology. The very high inter-individual correlations of the transcriptome signatures across 10 different subjects representing two races together with the results of our analyses indicate that it is feasible to assemble a platelet mRNA-ome that can serve as a reference for future platelet transcriptomic studies of human health and disease. Disclosures: No relevant conflicts of interest to declare.
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Sun, Mingwei, Yilian Zhao, Xiaobin Shao, Jintao Ge, Xueyan Tang, Pengbo Zhu, Jiangying Wang, and Tongli Zhao. "EST–SSR Marker Development and Full-Length Transcriptome Sequence Analysis of Tiger Lily (Lilium lancifolium Thunb)." Applied Bionics and Biomechanics 2022 (January 28, 2022): 1–9. http://dx.doi.org/10.1155/2022/7641048.
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The fast advancement and deployment of sequencing technologies after the Human Genome Project have greatly increased our knowledge of the eukaryotic genome sequences. However, due to technological concerns, high-quality genomic data has been confined to a few key organisms. Moreover, our understanding of which portions of genomes make up genes and which transcript isoforms synthesize these genes is scarce. Therefore, the current study has been designed to explore the reliability of the tiger lily (Lilium lancifolium Thunb) transcriptome. The PacBio-SMRT was used for attaining the complete transcriptomic profile. We obtained a total of 815,624 CCS (Circular Consensus Sequence) reads with an average length of 1295 bp. The tiger lily transcriptome has been sequenced for the first time using third-generation long-read technology. Furthermore, unigenes (38,707), lncRNAs (6852), and TF members (768) were determined based on the transcriptome data, followed by evaluating SSRs (3319). It has also been revealed that 105 out of 128 primer pairs effectively amplified PCR products. Around 15,608 transcripts were allocated to 25 distinct KOG Clusters, and 10,706 unigenes were grouped into 52 functional categories in the annotated transcripts. Until now, no tiger lily lncRNAs have been discovered. Results of this study may serve as an extensive set of reference transcripts and help us learn more about the transcriptomes of tiger lilies and pave the path for further research.
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Parmar, Sourabh. "Transcriptomics Analysis using Galaxy and other Online Servers for Rheumatoid Arthritis." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 10, 2021): 459–66. http://dx.doi.org/10.22214/ijraset.2021.36331.
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Researchers use transcriptomics analyses for biological data mining, interpretation, and presentation. Galaxy-based tools are utilized to analyze various complex disease transcriptomic data to understand the pathogenesis of the disease, which are user-friendly. This work provides simple methods for differential expression analysis and analysis of these results in gene ontology and pathway enrichment tools like David, WebGestalt. This method is very effective in better analysis and understanding the transcriptomic data. Transcriptomics analysis has been made on rheumatoid arthritis sra data. Rheumatoid arthritis (RA) is a systemic autoimmune disease. T cells and autoantibodies mediate the pathogenesis. This article discusses the genes which are differentially expressed between the healthy (n=50) and diseased (n=51) and the functions of those genes in the pathogenesis of RA.
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Wei, Fu-Jin, Saneyoshi Ueno, Tokuko Ujino-Ihara, Maki Saito, Yoshihiko Tsumura, Yuumi Higuchi, Satoko Hirayama, Junji Iwai, Tetsuji Hakamata, and Yoshinari Moriguchi. "Construction of a reference transcriptome for the analysis of male sterility in sugi (Cryptomeria japonica D. Don) focusing on MALE STERILITY 1 (MS1)." PLOS ONE 16, no. 2 (February 25, 2021): e0247180. http://dx.doi.org/10.1371/journal.pone.0247180.
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Sugi (Cryptomeria japonica D. Don) is an important conifer used for afforestation in Japan. As the genome of this species is 11 Gbps, it is too large to assemble within a short timeframe. Transcriptomics is one approach that can address this deficiency. Here we designed a workflow consisting of three stages to de novo assemble transcriptome using Oases and Trinity. The three transcriptomic stage used were independent assembly, automatic and semi-manual integration, and refinement by filtering out potential contamination. We identified a set of 49,795 cDNA and an equal number of translated proteins. According to the benchmark set by BUSCO, 87.01% of cDNAs identified were complete genes, and 78.47% were complete and single-copy genes. Compared to other full-length cDNA resources collected by Sanger and PacBio sequencers, the extent of the coverage in our dataset was the highest, indicating that these data can be safely used for further studies. When two tissue-specific libraries were compared, there were significant expression differences between male strobili and leaf and bark sets. Moreover, subtle expression difference between male-fertile and sterile libraries were detected. Orthologous genes from other model plants and conifer species were identified. We demonstrated that our transcriptome assembly output (CJ3006NRE) can serve as a reference transcriptome for future functional genomics and evolutionary biology studies.
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Brenner, Eric, Gayatri R. Tiwari, Manav Kapoor, Yunlong Liu, Amy Brock, and R. Dayne Mayfield. "Single cell transcriptome profiling of the human alcohol-dependent brain." Human Molecular Genetics 29, no. 7 (March 6, 2020): 1144–53. http://dx.doi.org/10.1093/hmg/ddaa038.
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Abstract Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.
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Salazar, Juan Alfonso, Cristian Vergara-Pulgar, Claudia Jorquera, Patricio Zapata, David Ruiz, Pedro Martínez-Gómez, Rodrigo Infante, and Claudio Meneses. "De Novo Transcriptome Sequencing in Kiwifruit (Actinidia chinensis var. deliciosa (A Chev) Liang et Ferguson) and Development of Tissue-Specific Transcriptomic Resources." Agronomy 11, no. 5 (May 7, 2021): 919. http://dx.doi.org/10.3390/agronomy11050919.
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Kiwifruit (Actinidia chinensis var. deliciosa (A Chev) Liang et Ferguson) is a sub-tropical vine species from the Actinidiaceae family native to China. This species has an allohexaploid genome (from diploid and autotetraploid parents), contained in 174 chromosomes producing a climacteric and fleshy fruit called kiwifruit. Currently, only a small body of transcriptomic and proteomic data are available for A. chinensis var. deliciosa. In this low molecular knowledge context, the main goal of this study is to construct a tissue-specific de novo transcriptome assembly, generating differential expression analysis among these specific tissues, to obtain new useful transcriptomic information for a better knowledge of vegetative, floral and fruit growth in this species. In this study, we have analyzed different whole transcriptomes from shoot, leaf, flower bud, flower and fruit at four development stages (7, 50, 120 and 160 days after flowering; DAF) in kiwifruit obtained through RNA-seq sequencing. The first version of the developed A. chinensis var. deliciosa de novo transcriptome contained 142,025 contigs (x¯ = 1044 bp, N50 = 1133 bp). Annotation was performed with BLASTX against the TAIR10 protein database, and we found an annotation proportion of 35.6% (50,508), leaving 64.4% (91,517) of the contigs without annotation. These results represent a reference transcriptome for allohexaploid kiwifruit generating a database of A. chinensis var. deliciosa genes related to leaf, flower and fruit development. These results provided highly valuable information identifying over 20,000 exclusive genes including all tissue comparisons, which were associated with the proteins involved in different biological processes and molecular functions.
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Thompson, Ammon, Michael R. May, Brian R. Moore, and Artyom Kopp. "A hierarchical Bayesian mixture model for inferring the expression state of genes in transcriptomes." Proceedings of the National Academy of Sciences 117, no. 32 (July 24, 2020): 19339–46. http://dx.doi.org/10.1073/pnas.1919748117.
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Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets—where we demonstrate its ability to correctly infer true (known) expression states—and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-sequencing (RNA-seq) datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely available R package zigzag.
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Xi, Dandan, Xiaofeng Li, Changwei Zhang, Lu Gao, Yuying Zhu, Shiwei Wei, Ying Li, Mingmin Jiang, Hongfang Zhu, and Zhaohui Zhang. "The Combined Analysis of Transcriptome and Metabolome Provides Insights into Purple Leaves in Eruca vesicaria subsp. sativa." Agronomy 12, no. 9 (August 27, 2022): 2046. http://dx.doi.org/10.3390/agronomy12092046.
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Background: Arugula is an essential oil crop of cruciferous species worldwide and serves as a salad vegetable. Purple plant leaves provide nutrients benefiting human beings and are mainly attributed to high anthocyanins. In this study, we collected a purple arugula cultivar with purple leaves and a green arugula with green leaves. The genetic bases and mechanisms underlying purple leaf formation in arugula remain unclear. Therefore, we conducted integrative metabolomics and transcriptomics of two arugula cultivars with different leaf colors. Methods: To study the underlying mechanisms, transcriptomic and metabolomic analyses were carried out. Results: Metabolomic analysis revealed that 84 of 747 metabolites were significantly differentially expressed, comprising 30 depleted and 49 enriched metabolites. Further analysis showed that cyanidin is the main components responsible for the purple color. A total of 144,790 unigenes were obtained by transcriptomic analysis, with 13,204 unigenes differentially expressed, comprising 8120 downregulated and 5084 upregulated unigenes. Seven structural genes, PAL, C4H, 4CL, CHS, CCoAOMT, LDOX, and UFGT, were identified as candidate genes associated with anthocyanin accumulation through combined analysis of transcriptome and metabolome. Conclusions: Collectively, the differences in the expression levels of PAL, C4H, 4CL, CHS, CCoAOMT, LDOX, and UFGT might be responsible for purple leaf coloration, providing important data for the discovery of candidate genes and molecular bases controlling the purple leaves in arugula.
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Chebbo, Mohamad, Said Assou, Veronique Pantesco, Catherine Duez, Marie C. Alessi, Pascal Chanez, and Delphine Gras. "Platelets Purification Is a Crucial Step for Transcriptomic Analysis." International Journal of Molecular Sciences 23, no. 6 (March 13, 2022): 3100. http://dx.doi.org/10.3390/ijms23063100.
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Platelets are small anucleate cells derived from the fragmentation of megakaryocytes and are involved in different biological processes especially hemostasis, thrombosis, and immune response. Despite their lack of nucleus, platelets contain a reservoir of megakaryocyte-derived RNAs and all the machinery useful for mRNA translation. Interestingly, platelet transcriptome was analyzed in health and diseases and led to the identification of disease-specific molecular signatures. Platelet contamination by leukocytes and erythrocytes during platelet purification is a major problem in transcriptomic analysis and the presence of few contaminants in platelet preparation could strongly alter transcriptome results. Since contaminant impacts on platelet transcriptome remains theoretical, we aimed to determine whether low leukocyte and erythrocyte contamination could cause great or only minor changes in platelet transcriptome. Using microarray technique, we compared the transcriptome of platelets from the same donor, purified by common centrifugation method or using magnetic microbeads to eliminate contaminating cells. We found that platelet transcriptome was greatly altered by contaminants, as the relative amount of 8274 transcripts was different between compared samples. We observed an increase of transcripts related to leukocytes and erythrocytes in platelet purified without microbeads, while platelet specific transcripts were falsely reduced. In conclusion, serious precautions should be taken during platelet purification process for transcriptomic analysis, in order to avoid platelets contamination and result alteration.
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Sastry, Anand V., Alyssa Hu, David Heckmann, Saugat Poudel, Erol Kavvas, and Bernhard O. Palsson. "Independent component analysis recovers consistent regulatory signals from disparate datasets." PLOS Computational Biology 17, no. 2 (February 2, 2021): e1008647. http://dx.doi.org/10.1371/journal.pcbi.1008647.
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The availability of bacterial transcriptomes has dramatically increased in recent years. This data deluge could result in detailed inference of underlying regulatory networks, but the diversity of experimental platforms and protocols introduces critical biases that could hinder scalable analysis of existing data. Here, we show that the underlying structure of the E. coli transcriptome, as determined by Independent Component Analysis (ICA), is conserved across multiple independent datasets, including both RNA-seq and microarray datasets. We subsequently combined five transcriptomics datasets into a large compendium containing over 800 expression profiles and discovered that its underlying ICA-based structure was still comparable to that of the individual datasets. With this understanding, we expanded our analysis to over 3,000 E. coli expression profiles and predicted three high-impact regulons that respond to oxidative stress, anaerobiosis, and antibiotic treatment. ICA thus enables deep analysis of disparate data to uncover new insights that were not visible in the individual datasets.
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Li, Mengyao, Mohammad A. K. Azad, Philip E. Thompson, Kade D. Roberts, Tony Velkov, Yan Zhu, and Jian Li. "Transcriptomic Responses to Polymyxin B and Analogues in Human Kidney Tubular Cells." Antibiotics 12, no. 2 (February 20, 2023): 415. http://dx.doi.org/10.3390/antibiotics12020415.
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Polymyxins are last-line antibiotics for the treatment of Gram-negative ‘superbugs’. However, nephrotoxicity can occur in up to 60% of patients administered intravenous polymyxins. The mechanisms underpinning nephrotoxicity remain unclear. To understand polymyxin-induced nephrotoxicity, human renal proximal tubule cells were treated for 24 h with 0.1 mM polymyxin B or two new analogues, FADDI-251 or FADDI-287. Transcriptomic analysis was performed, and differentially expressed genes (DEGs) were identified using ANOVA (FDR < 0.2). Cell viability following treatment with polymyxin B, FADDI-251 or FADDI-287 was 66.0 ± 5.33%, 89.3 ± 3.96% and 90.4 ± 1.18%, respectively. Transcriptomics identified 430, 193 and 150 DEGs with polymyxin B, FADDI-251 and FADDI-287, respectively. Genes involved with metallothioneins and Toll-like receptor pathways were significantly perturbed by all polymyxins. Only polymyxin B induced perturbations in signal transduction, including FGFR2 and MAPK signaling. SIGNOR network analysis showed all treatments affected essential regulators in the immune system, autophagy, cell cycle, oxidative stress and apoptosis. All polymyxins caused significant perturbations of metal homeostasis and TLR signaling, while polymyxin B caused the most dramatic perturbations of the transcriptome. This study reveals the impact of polymyxin structure modifications on transcriptomic responses in human renal tubular cells and provides important information for designing safer new-generation polymyxins.
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Beisser, Daniela, Nadine Graupner, Christina Bock, Sabina Wodniok, Lars Grossmann, Matthijs Vos, Bernd Sures, Sven Rahmann, and Jens Boenigk. "Comprehensive transcriptome analysis provides new insights into nutritional strategies and phylogenetic relationships of chrysophytes." PeerJ 5 (January 10, 2017): e2832. http://dx.doi.org/10.7717/peerj.2832.
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BackgroundChrysophytes are protist model species in ecology and ecophysiology and important grazers of bacteria-sized microorganisms and primary producers. However, they have not yet been investigated in detail at the molecular level, and no genomic and only little transcriptomic information is available. Chrysophytes exhibit different trophic modes: while phototrophic chrysophytes perform only photosynthesis, mixotrophs can gain carbon from bacterial food as well as from photosynthesis, and heterotrophs solely feed on bacteria-sized microorganisms. Recent phylogenies and megasystematics demonstrate an immense complexity of eukaryotic diversity with numerous transitions between phototrophic and heterotrophic organisms. The question we aim to answer is how the diverse nutritional strategies, accompanied or brought about by a reduction of the plasmid and size reduction in heterotrophic strains, affect physiology and molecular processes.ResultsWe sequenced the mRNA of 18 chrysophyte strains on the Illumina HiSeq platform and analysed the transcriptomes to determine relations between the trophic mode (mixotrophic vs. heterotrophic) and gene expression. We observed an enrichment of genes for photosynthesis, porphyrin and chlorophyll metabolism for phototrophic and mixotrophic strains that can perform photosynthesis. Genes involved in nutrient absorption, environmental information processing and various transporters (e.g., monosaccharide, peptide, lipid transporters) were present or highly expressed only in heterotrophic strains that have to sense, digest and absorb bacterial food. We furthermore present a transcriptome-based alignment-free phylogeny construction approach using transcripts assembled from short reads to determine the evolutionary relationships between the strains and the possible influence of nutritional strategies on the reconstructed phylogeny. We discuss the resulting phylogenies in comparison to those from established approaches based on ribosomal RNA and orthologous genes. Finally, we make functionally annotated reference transcriptomes of each strain available to the community, significantly enhancing publicly available data on Chrysophyceae.ConclusionsOur study is the first comprehensive transcriptomic characterisation of a diverse set of Chrysophyceaen strains. In addition, we showcase the possibility of inferring phylogenies from assembled transcriptomes using an alignment-free approach. The raw and functionally annotated data we provide will prove beneficial for further examination of the diversity within this taxon. Our molecular characterisation of different trophic modes presents a first such example.
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Wang, Xinjun, Zhe Sun, Yanfu Zhang, Zhongli Xu, Hongyi Xin, Heng Huang, Richard H. Duerr, Kong Chen, Ying Ding, and Wei Chen. "BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data." Nucleic Acids Research 48, no. 11 (May 7, 2020): 5814–24. http://dx.doi.org/10.1093/nar/gkaa314.
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Abstract Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10× Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.
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Kakuk, Balázs, András Attila Kiss, Gábor Torma, Zsolt Csabai, István Prazsák, Máté Mizik, Klára Megyeri, Dóra Tombácz, and Zsolt Boldogkői. "Nanopore Assay Reveals Cell-Type-Dependent Gene Expression of Vesicular Stomatitis Indiana Virus and Differential Host Cell Response." Pathogens 10, no. 9 (September 15, 2021): 1196. http://dx.doi.org/10.3390/pathogens10091196.
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Vesicular stomatitis Indiana virus (VSIV) of genus Vesiculovirus, species IndianaVesiculovirus (formerly as Vesicular stomatitis virus, VSV) causes a disease in livestock that is very similar to the foot and mouth disease, thereby an outbreak may lead to significant economic loss. Long-read sequencing (LRS) -based approaches already reveal a hidden complexity of the transcriptomes in several viruses. This technique has been utilized for the sequencing of the VSIV genome, but our study is the first for the application of this technique for the profiling of the VSIV transcriptome. Since LRS is able to sequence full-length RNA molecules, it thereby provides more accurate annotation of the transcriptomes than the traditional short-read sequencing methods. The objectives of this study were to assemble the complete transcriptome of using nanopore sequencing, to ascertain cell-type specificity and dynamics of viral gene expression, and to evaluate host gene expression changes induced by the viral infection. We carried out a time-course analysis of VSIV gene expression in human glioblastoma and primate fibroblast cell lines using a nanopore-based LRS approach and applied both amplified and direct cDNA sequencing (as well as cap-selection) for a fraction of samples. Our investigations revealed that, although the VSIV genome is simple, it generates a relatively complex transcriptomic architecture. In this study, we also demonstrated that VSIV transcripts vary in structure and exhibit differential gene expression patterns in the two examined cell types.
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Vijayakumar, Periyasamy, Sanniyasi Bakyaraj, Arunasalam Singaravadivelan, Thangavelu Vasanthakumar, and Ramalingam Suresh. "Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology." Genome 62, no. 7 (July 2019): 489–501. http://dx.doi.org/10.1139/gen-2018-0144.
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A better understanding of the biology of lactation, both in terms of gene expression and the identification of candidate genes for the production of milk and its components, is made possible by recent advances in RNA seq technology. The purpose of this study was to understand the synthesis of milk components and the molecular pathways involved, as well as to identify candidate genes for milk production traits within whole mammary transcriptomic datasets. We performed a meta-analysis of publically available RNA seq transcriptome datasets of mammary tissue/milk somatic cells. In total, 11 562 genes were commonly identified from all RNA seq based mammary gland transcriptomes. Functional annotation of commonly expressed genes revealed the molecular processes that contribute to the synthesis of fats, proteins, and lactose in mammary secretory cells and the molecular pathways responsible for milk synthesis. In addition, we identified several candidate genes responsible for milk production traits and constructed a gene regulatory network for RNA seq data. In conclusion, this study provides a basic understanding of the lactation biology of cows at the gene expression level.
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Cheng, Xuanjin, Junran Yan, Yongxing Liu, Jiahe Wang, and Stefan Taubert. "eVITTA: a web-based visualization and inference toolbox for transcriptome analysis." Nucleic Acids Research 49, W1 (May 21, 2021): W207—W215. http://dx.doi.org/10.1093/nar/gkab366.
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Abstract Transcriptome profiling is essential for gene regulation studies in development and disease. Current web-based tools enable functional characterization of transcriptome data, but most are restricted to applying gene-list-based methods to single datasets, inefficient in leveraging up-to-date and species-specific information, and limited in their visualization options. Additionally, there is no systematic way to explore data stored in the largest transcriptome repository, NCBI GEO. To fill these gaps, we have developed eVITTA (easy Visualization and Inference Toolbox for Transcriptome Analysis; https://tau.cmmt.ubc.ca/eVITTA/). eVITTA provides modules for analysis and exploration of studies published in NCBI GEO (easyGEO), detailed molecular- and systems-level functional profiling (easyGSEA), and customizable comparisons among experimental groups (easyVizR). We tested eVITTA on transcriptomes of SARS-CoV-2 infected human nasopharyngeal swab samples, and identified a downregulation of olfactory signal transducers, in line with the clinical presentation of anosmia in COVID-19 patients. We also analyzed transcriptomes of Caenorhabditis elegans worms with disrupted S-adenosylmethionine metabolism, confirming activation of innate immune responses and feedback induction of one-carbon cycle genes. Collectively, eVITTA streamlines complex computational workflows into an accessible interface, thus filling the gap of an end-to-end platform capable of capturing both broad and granular changes in human and model organism transcriptomes.
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Rychel, Kevin, Katherine Decker, Anand V. Sastry, Patrick V. Phaneuf, Saugat Poudel, and Bernhard O. Palsson. "iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning." Nucleic Acids Research 49, no. D1 (October 12, 2020): D112—D120. http://dx.doi.org/10.1093/nar/gkaa810.
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Abstract Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.
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Soula, Anaïs, Mélissa Valere, María-José López-González, Vicky Ury-Thiery, Alexis Groppi, Marc Landry, Macha Nikolski, and Alexandre Favereaux. "Small RNA-Seq reveals novel miRNAs shaping the transcriptomic identity of rat brain structures." Life Science Alliance 1, no. 5 (October 2018): e201800018. http://dx.doi.org/10.26508/lsa.201800018.
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In the central nervous system (CNS), miRNAs are involved in key functions, such as neurogenesis and synaptic plasticity. Moreover, they are essential to define specific transcriptomes in tissues and cells. However, few studies were performed to determine the miRNome of the different structures of the rat CNS, although a major model in neuroscience. Here, we determined by small RNA-Seq, the miRNome of the olfactory bulb, the hippocampus, the cortex, the striatum, and the spinal cord and showed the expression of 365 known miRNAs and 90 novel miRNAs. Differential expression analysis showed that several miRNAs were specifically enriched/depleted in these CNS structures. Transcriptome analysis by mRNA-Seq and correlation based on miRNA target predictions suggest that the specifically enriched/depleted miRNAs have a strong impact on the transcriptomic identity of the CNS structures. Altogether, these results suggest the critical role played by these enriched/depleted miRNAs, in particular the novel miRNAs, in the functional identities of CNS structures.
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Jeon, Hyeongseon, Juan Xie, Yeseul Jeon, Kyeong Joo Jung, Arkobrato Gupta, Won Chang, and Dongjun Chung. "Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives." Biomolecules 13, no. 2 (January 24, 2023): 221. http://dx.doi.org/10.3390/biom13020221.
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Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct characteristics. In order to guarantee biologically meaningful findings using transcriptomic experiments, it is important to consider various experimental factors in a systematic way through statistical power analysis. In this paper, we review and discuss the power analysis for three types of gene expression profiling technologies from a practical standpoint, including bulk RNA-seq, single-cell RNA-seq, and high-throughput spatial transcriptomics. Specifically, we describe the existing power analysis tools for each research objective for each of the bulk RNA-seq and scRNA-seq experiments, along with recommendations. On the other hand, since there are no power analysis tools for high-throughput spatial transcriptomics at this point, we instead investigate the factors that can influence power analysis.
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Armstrong, Eric J., and Jonathon H. Stillman. "Construction and Characterization of Two Novel Transcriptome Assemblies in the Congeneric Porcelain Crabs Petrolisthes cinctipes and P. manimaculis." Integrative and Comparative Biology 56, no. 6 (July 3, 2016): 1092–102. http://dx.doi.org/10.1093/icb/icw043.
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Crustaceans have commonly been used as non-model systems in basic biological research, especially physiological regulation. With the recent and rapid adoption of functional genomic tools, crustaceans are increasingly becoming model systems for ecological investigations of development and evolution and for mechanistic examinations of genotype–phenotype interactions and molecular pathways of response to environmental stressors. Comparative transcriptomic approaches, however, remain constrained by a lack of sequence data in closely related crustacean taxa. We identify challenges in the use of functional genomics tools in comparative analysis among decapod crustacean in light of recent advances. We present RNA-seq data from two congeneric species of porcelain crabs (Petrolisthes cinctipes and P. manimaculis) used to construct two de novo transcriptome assemblies with ∼194K and ∼278K contigs, respectively. We characterize and contrast these assemblies and compare them to a previously generated EST sequence library for P. cinctipes. We also discuss the potential use of these data as a case-study system in the broader context of crustacean comparative transcriptomics.
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Van Etten, Julia, Alexander Shumaker, Tali Mass, Hollie M. Putnam, and Debashish Bhattacharya. "Transcriptome analysis provides a blueprint of coral egg and sperm functions." PeerJ 8 (August 18, 2020): e9739. http://dx.doi.org/10.7717/peerj.9739.
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Background Reproductive biology and the evolutionary constraints acting on dispersal stages are poorly understood in many stony coral species. A key piece of missing information is egg and sperm gene expression. This is critical for broadcast spawning corals, such as our model, the Hawaiian species Montipora capitata, because eggs and sperm are exposed to environmental stressors during dispersal. Furthermore, parental effects such as transcriptome investment may provide a means for cross- or trans-generational plasticity and be apparent in egg and sperm transcriptome data. Methods Here, we analyzed M. capitata egg and sperm transcriptomic data to address three questions: (1) Which pathways and functions are actively transcribed in these gametes? (2) How does sperm and egg gene expression differ from adult tissues? (3) Does gene expression differ between these gametes? Results We show that egg and sperm display surprisingly similar levels of gene expression and overlapping functional enrichment patterns. These results may reflect similar environmental constraints faced by these motile gametes. We find significant differences in differential expression of egg vs. adult and sperm vs. adult RNA-seq data, in contrast to very few examples of differential expression when comparing egg vs. sperm transcriptomes. Lastly, using gene ontology and KEGG orthology data we show that both egg and sperm have markedly repressed transcription and translation machinery compared to the adult, suggesting a dependence on parental transcripts. We speculate that cell motility and calcium ion binding genes may be involved in gamete to gamete recognition in the water column and thus, fertilization.
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Zubcevic, Jasenka, Ashley Baker, and Christopher J. Martyniuk. "Transcriptional networks in rodent models support a role for gut-brain communication in neurogenic hypertension: a review of the evidence." Physiological Genomics 49, no. 7 (July 1, 2017): 327–38. http://dx.doi.org/10.1152/physiolgenomics.00010.2017.
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Hypertension (HTN) is the most prevalent condition observed in primary health care. Hypertension shows complex etiology, and neuroinflammation, overactive sympathetic drive, and the microbiome are each associated with the disease. To obtain mechanistic perspective into neurogenic HTN, we first constructed a framework for transcriptional regulators of the disease using the Comparative Toxicogenomics Database. This approach yielded a core group of 178 transcripts that are prevalent in studies of HTN, including leptin and neuropeptide Y. We then conducted a meta-analysis for transcriptome data generated in brain tissue from HTN studies. Eight expression studies were reanalyzed, in which transcriptomics was conducted in hypertensive animal models [spontaneously hypertensive rats (SHR) and high blood pressure (BPH/2J) Schlager mice] (140 microarrays). Most strikingly, a gut-brain connection was a dominant theme in both rodent models of HTN. The transcriptomic data in the rat CNS converged on processes that included gastrointestinal motility and appetite, among others. In the mouse model, pathways converged on gastrointestinal transit. Thus, our data provide a powerful review of current molecular evidence of the interplay between gut and brain in HTN. Analyses of meta-genome data also suggested that transcriptome networks related to natriuresis, thermoregulation, reproduction (lactation and pregnancy), and vasoconstriction were associated to HTN, supporting physiological observations in independent studies by others. Lastly, we present novel transcriptome networks that may contribute to a neurogenic origin of HTN. Using this framework, new therapeutic targets can be proposed and investigated in treatment strategies.
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Haroon, Yu-Xin Li, Chen-Xu Ye, Jian Su, Ghulam Nabi, Xiao-Hong Su, and Lian-Xi Xing. "De Novo Transcriptome Assembly and Analysis of Longevity Genes Using Subterranean Termite (Reticulitermes chinensis) Castes." International Journal of Molecular Sciences 23, no. 21 (November 7, 2022): 13660. http://dx.doi.org/10.3390/ijms232113660.
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The longevity phenomenon is entirely controlled by the insulin signaling pathway (IIS-pathway). Both vertebrates and invertebrates have IIS-pathways that are comparable to one another, though no one has previously described de novo transcriptome assembly of IIS-pathway-associated genes in termites. In this research, we analyzed the transcriptomes of both reproductive (primary kings “PK” and queens “PQ”, secondary worker reproductive kings “SWRK” and queens “SWRQ”) and non-reproductive (male “WM” and female “WF” workers) castes of the subterranean termite Reticulitermes chinensis. The goal was to identify the genes responsible for longevity in the reproductive and non-reproductive castes. Through transcriptome analysis, we annotated 103,589,264 sequence reads and 184,436 (7G) unigenes were assembled, GC performance was measured at 43.02%, and 64,046 sequences were reported as CDs sequences. Of which 35 IIS-pathway-associated genes were identified, among 35 genes, we focused on the phosphoinositide-dependent kinase-1 (Pdk1), protein kinase B2 (akt2-a), tuberous sclerosis-2 (Tsc2), mammalian target of rapamycin (mTOR), eukaryotic translation initiation factor 4E (EIF4E) and ribosomal protein S6 (RPS6) genes. Previously these genes (Pdk1, akt2-a, mTOR, EIF4E, and RPS6) were investigated in various organisms, that regulate physiological effects, growth factors, protein translation, cell survival, proliferation, protein synthesis, cell metabolism and survival, autophagy, fecundity rate, egg size, and follicle number, although the critical reason for longevity is still unclear in the termite castes. However, based on transcriptome profiling, the IIS-pathway-associated genes could prolong the reproductive caste lifespan and health span. Therefore, the transcriptomic shreds of evidence related to IIS-pathway genes provide new insights into the maintenance and relationships between biomolecular homeostasis and remarkable longevity. Finally, we propose a strategy for future research to decrypt the hidden costs associated with termite aging in reproductive and non-reproductive castes.
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Koglin, Sven, Daronja Trense, Michael Wink, Hedwig Sauer-Gürth, and Dieter Thomas Tietze. "Characterization of a de novo assembled transcriptome of the Common Blackbird (Turdus merula)." PeerJ 5 (December 13, 2017): e4045. http://dx.doi.org/10.7717/peerj.4045.
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Background In recent years, next generation high throughput sequencing technologies have proven to be useful tools for investigations concerning the genomics or transcriptomics also of non-model species. Consequently, ornithologists have adopted these technologies and the respective bioinformatics tools to survey the genomes and transcriptomes of a few avian non-model species. The Common Blackbird is one of the most common bird species living in European cities, which has successfully colonized urban areas and for which no reference genome or transcriptome is publicly available. However, to target questions like genome wide gene expression analysis, a reference genome or transcriptome is needed. Methods Therefore, in this study two Common Blackbirds were sacrificed, their mRNA was isolated and analyzed by RNA-Seq to de novo assemble a transcriptome and characterize it. Illumina reads (125 bp paired-end) and a Velvet/Oases pipeline led to 162,158 transcripts. For the annotation (using Blast+), an unfiltered protein database was used. SNPs were identified using SAMtools and BCFtools. Furthermore, mRNA from three single tissues (brain, heart and liver) of the same two Common Blackbirds were sequenced by Illumina (75 bp single-end reads). The draft transcriptome and the three single tissues were compared by their BLAST hits with the package VennDiagram in R. Results Following the annotation against protein databases, we found evidence for 15,580 genes in the transcriptome (all well characterized hits after annotation). On 18% of the assembled transcripts, 144,742 SNPs were identified which are, consequently, 0.09% of all nucleotides in the assembled transcriptome. In the transcriptome and in the single tissues (brain, heart and liver), 10,182 shared genes were found. Discussion Using a next-generation technology and bioinformatics tools, we made a first step towards the genomic investigation of the Common Blackbird. The de novo assembled transcriptome is usable for downstream analyses such as differential gene expression analysis and SNP identification. This study shows the importance of the approach to sequence single tissues to understand functions of tissues, proteins and the phenotype.
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Liu, Dandan, Zhengxi Li, and Maolin Hou. "Comparison of Transcriptome Responses between Sogatella furcifera Females That Acquired Southern Rice Black-Streaked Dwarf Virus and Not." Insects 13, no. 2 (February 9, 2022): 182. http://dx.doi.org/10.3390/insects13020182.
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The southern rice black-streaked dwarf virus (SRBSDV) is transmitted horizontally by Sogatella furcifera in a persistent, propagative manner. Exposure of S. furcifera females to SRBSDV-infected rice plants may trigger transcriptomic changes in the insects, the transcriptomes of females that acquired SRBSDV and those that failed to, as well as females fed on healthy rice plants as control, were sequenced and compared. Nine transcriptomic libraries were constructed, from which a total of 53,084 genes were assembled. Among the genes, 1043 and 2932 were differentially expressed genes (DEGs) in S. furcifera females that acquired SRBSDV and that failed to, in comparison with the control, respectively. Functional enrichment analysis showed that DEGs identified in S. furcifera females exposed to SRBSDV are primarily involved in diverse signaling pathways related to primary metabolism and innate immunity. The DEGs in the S. furcifera females that failed to acquire the virus significantly outnumbered that in the insects that acquired the virus, and the virus exposure activated the humoral and cellular immune responses of the vectors, especially the apoptosis. The key gene in apoptosis encoding caspase 1 was upregulated by SRBSDV exposure, especially in S. furcifera females that failed to acquire the virus. Analysis of caspase 1 activity validated that SRBSDV exposure induced caspase 1 accumulation. Surprisingly, the expression of six female-specific genes was also upregulated by SRBSDV exposure, which was confirmed by RT-qPCR analysis. This study provides evidence to explain the differential virus acquisition at the transcriptome level.
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Gyoneva, Stefka, Raghavendra Hosur, David Gosselin, Baohong Zhang, Zhengyu Ouyang, Anne C. Cotleur, Michael Peterson, et al. "Cx3cr1-deficient microglia exhibit a premature aging transcriptome." Life Science Alliance 2, no. 6 (December 2019): e201900453. http://dx.doi.org/10.26508/lsa.201900453.
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CX3CR1, one of the highest expressed genes in microglia in mice and humans, is implicated in numerous microglial functions. However, the molecular mechanisms underlying Cx3cr1 signaling are not well understood. Here, we analyzed transcriptomes of Cx3cr1-deficient microglia under varying conditions by RNA-sequencing (RNA-seq). In 2-mo-old mice, Cx3cr1 deletion resulted in the down-regulation of a subset of immune-related genes, without substantial epigenetic changes in markers of active chromatin. Surprisingly, Cx3cr1-deficient microglia from young mice exhibited a transcriptome consistent with that of aged Cx3cr1-sufficient animals, suggesting a premature aging transcriptomic signature. Immunohistochemical analysis of microglia in young and aged mice revealed that loss of Cx3cr1 modulates microglial morphology in a comparable fashion. Our results suggest that CX3CR1 may regulate microglial function in part by modulating the expression levels of a subset of inflammatory genes during chronological aging, making Cx3cr1-deficient mice useful for studying aged microglia.
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Morcillo, Rafael, Juan Vílchez, Song Zhang, Richa Kaushal, Danxia He, Hailing Zi, Renyi Liu, Karsten Niehaus, Avtar Handa, and Huiming Zhang. "Plant Transcriptome Reprograming and Bacterial Extracellular Metabolites Underlying Tomato Drought Resistance Triggered by a Beneficial Soil Bacteria." Metabolites 11, no. 6 (June 9, 2021): 369. http://dx.doi.org/10.3390/metabo11060369.
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Water deficit is one of the major constraints to crop production and food security worldwide. Some plant growth-promoting rhizobacteria (PGPR) strains are capable of increasing plant drought resistance. Knowledge about the mechanisms underlying bacteria-induced plant drought resistance is important for PGPR applications in agriculture. In this study, we show the drought stress-mitigating effects on tomato plants by the Bacillus megaterium strain TG1-E1, followed by the profiling of plant transcriptomic responses to TG1-E1 and the profiling of bacterial extracellular metabolites. Comparison between the transcriptomes of drought-stressed plants with and without TG1-E1 inoculation revealed bacteria-induced transcriptome reprograming, with highlights on differentially expressed genes belonging to the functional categories including transcription factors, signal transduction, and cell wall biogenesis and organization. Mass spectrometry-based analysis identified over 40 bacterial extracellular metabolites, including several important regulators or osmoprotectant precursors for increasing plant drought resistance. These results demonstrate the importance of plant transcriptional regulation and bacterial metabolites in PGPR-induced plant drought resistance.