Journal articles: 'Transcriptome profiling'

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Reznikov, Leah R., David K. Meyerholz, Mahmoud Abou Alaiwa, Shin-Ping Kuan, Yan-Shin J. Liao, Nicholas L. Bormann, Thomas B. Bair, Margaret Price, David A. Stoltz, and Michael J. Welsh. "The vagal ganglia transcriptome identifies candidate therapeutics for airway hyperreactivity." American Journal of Physiology-Lung Cellular and Molecular Physiology 315, no. 2 (August 1, 2018): L133—L148. http://dx.doi.org/10.1152/ajplung.00557.2017.

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Mainstay therapeutics are ineffective in some people with asthma, suggesting a need for additional agents. In the current study, we used vagal ganglia transcriptome profiling and connectivity mapping to identify compounds beneficial for alleviating airway hyperreactivity (AHR). As a comparison, we also used previously published transcriptome data from sensitized mouse lungs and human asthmatic endobronchial biopsies. All transcriptomes revealed agents beneficial for mitigating AHR; however, only the vagal ganglia transcriptome identified agents used clinically to treat asthma (flunisolide, isoetarine). We also tested one compound identified by vagal ganglia transcriptome profiling that had not previously been linked to asthma and found that it had bronchodilator effects in both mouse and pig airways. These data suggest that transcriptome profiling of the vagal ganglia might be a novel strategy to identify potential asthma therapeutics.

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Kain,, Steven R. "Reshaping Whole Transcriptome Profiling." Genetic Engineering & Biotechnology News 31, no. 4 (February 15, 2011): 26–27. http://dx.doi.org/10.1089/gen.31.04.12.

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Crunkhorn, Sarah. "Profiling the malaria transcriptome." Nature Reviews Drug Discovery 18, no. 10 (September 2019): 748. http://dx.doi.org/10.1038/d41573-019-00151-3.

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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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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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Courtney, Eliza, Shan Kornfeld, Karolina Janitz, and Michal Janitz. "Transcriptome profiling in neurodegenerative disease." Journal of Neuroscience Methods 193, no. 2 (November 2010): 189–202. http://dx.doi.org/10.1016/j.jneumeth.2010.08.018.

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Belder, Nevin, Berna Savaş, Arzu Ensari, Mehmet Ayhan Kuzu, and Hilal Özdağ. "Transcriptome profiling of colorectal cancer." Current Opinion in Biotechnology 24 (July 2013): S38. http://dx.doi.org/10.1016/j.copbio.2013.05.075.

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Montjean, Debbie, Pierre De La Grange, David Gentien, Audrey Rapinat, Stéphanie Belloc, Paul Cohen-Bacrie, Yves Menezo, and Moncef Benkhalifa. "Sperm transcriptome profiling in oligozoospermia." Journal of Assisted Reproduction and Genetics 29, no. 1 (October 12, 2011): 3–10. http://dx.doi.org/10.1007/s10815-011-9644-3.

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Rioux, Geneviève, Zainab Ridha, Mélissa Simard, Florence Turgeon, Sylvain L. Guérin, and Roxane Pouliot. "Transcriptome Profiling Analyses in Psoriasis: A Dynamic Contribution of Keratinocytes to the Pathogenesis." Genes 11, no. 10 (September 30, 2020): 1155. http://dx.doi.org/10.3390/genes11101155.

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Psoriasis is an immune-mediated inflammatory skin disease with a complex etiology involving environmental and genetic factors. A better insight into related genomic alteration helps design precise therapies leading to better treatment outcome. Gene expression in psoriasis can provide relevant information about the altered expression of mRNA transcripts, thus giving new insights into the disease onset. Techniques for transcriptome analyses, such as microarray and RNA sequencing (RNA-seq), are relevant tools for the discovery of new biomarkers as well as new therapeutic targets. This review summarizes the findings related to the contribution of keratinocytes in the pathogenesis of psoriasis by an in-depth review of studies that have examined psoriatic transcriptomes in the past years. It also provides valuable information on reconstructed 3D psoriatic skin models using cells isolated from psoriatic patients for transcriptomic studies.

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Packer, Jonathan S., Qin Zhu, Chau Huynh, Priya Sivaramakrishnan, Elicia Preston, Hannah Dueck, Derek Stefanik, et al. "A lineage-resolved molecular atlas of C. elegans embryogenesis at single-cell resolution." Science 365, no. 6459 (September 5, 2019): eaax1971. http://dx.doi.org/10.1126/science.aax1971.

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Caenorhabditis elegans is an animal with few cells but a wide diversity of cell types. In this study, we characterize the molecular basis for their specification by profiling the transcriptomes of 86,024 single embryonic cells. We identify 502 terminal and preterminal cell types, mapping most single-cell transcriptomes to their exact position in C. elegans’ invariant lineage. Using these annotations, we find that (i) the correlation between a cell’s lineage and its transcriptome increases from middle to late gastrulation, then falls substantially as cells in the nervous system and pharynx adopt their terminal fates; (ii) multilineage priming contributes to the differentiation of sister cells at dozens of lineage branches; and (iii) most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state.

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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.

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Gobert, Geoffrey N. "Applications for profiling the schistosome transcriptome." Trends in Parasitology 26, no. 9 (September 2010): 434–39. http://dx.doi.org/10.1016/j.pt.2010.04.009.

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Haerizadeh, Farzad, Mohan B. Singh, and Prem L. Bhalla. "Transcriptome profiling of soybean root tips." Functional Plant Biology 38, no. 6 (2011): 451. http://dx.doi.org/10.1071/fp10230.

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Soybean (Glycine max L.), a major legume crop, is important to human nutrition and is a source of animal feed. Similar to many legumes, a key feature of the soybean is its symbiotic association with soil bacteria that fix atmospheric nitrogen. However, knowledge of the gene expression of its root system, particularly the root meristematic region, is limited. Here, we have addressed this by investigating the gene expression profile of the soybean root tip, using soybean Affymetrix chips containing 37 500 probe sets (Affymetrix Inc.) and have compared this expression profile with that of the nonmeristematic tissue. We identified a total of 5012 upregulated and 4136 downregulated genes in the soybean root tip. Among the upregulated genes, 559 showed strong preferential expression in the root tip, indicating that they are likely to be associated with root apical meristem specificity and root tip function. Genes involved in membrane transport, defence signalling and metabolism were upregulated in the soybean root tip. Further, our data provide a resource of novel target genes for further studies involving root development and biology, and will possibly have a positive impact on future crop breeding.

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Eng, Chee-Huat Linus, Sheel Shah, Julian Thomassie, and Long Cai. "Profiling the transcriptome with RNA SPOTs." Nature Methods 14, no. 12 (November 13, 2017): 1153–55. http://dx.doi.org/10.1038/nmeth.4500.

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Asmann, Yan W., Michael B. Wallace, and E. Aubrey Thompson. "Transcriptome Profiling Using Next-Generation Sequencing." Gastroenterology 135, no. 5 (November 2008): 1466–68. http://dx.doi.org/10.1053/j.gastro.2008.09.042.

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Tombácz, Dóra, István Prazsák, Gábor Torma, Zsolt Csabai, Zsolt Balázs, Norbert Moldován, Béla Dénes, Michael Snyder, and Zsolt Boldogkői. "Time-Course Transcriptome Profiling of a Poxvirus Using Long-Read Full-Length Assay." Pathogens 10, no. 8 (July 21, 2021): 919. http://dx.doi.org/10.3390/pathogens10080919.

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Viral transcriptomes that are determined using first- and second-generation sequencing techniques are incomplete. Due to the short read length, these methods are inefficient or fail to distinguish between transcript isoforms, polycistronic RNAs, and transcriptional overlaps and readthroughs. Additionally, these approaches are insensitive for the identification of splice and transcriptional start sites (TSSs) and, in most cases, transcriptional end sites (TESs), especially in transcript isoforms with varying transcript ends, and in multi-spliced transcripts. Long-read sequencing is able to read full-length nucleic acids and can therefore be used to assemble complete transcriptome atlases. Although vaccinia virus (VACV) does not produce spliced RNAs, its transcriptome has a high diversity of TSSs and TESs, and a high degree of polycistronism that leads to enormous complexity. We applied single-molecule, real-time, and nanopore-based sequencing methods to investigate the time-lapse transcriptome patterns of VACV gene expression.

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Pradeep, Chaithra, Dharam Nandan, Arya A. Das, and Dinesh Velayutham. "Comparative Transcriptome Profiling of Disruptive Technology, Single- Molecule Direct RNA Sequencing." Current Bioinformatics 15, no. 2 (March 10, 2020): 165–72. http://dx.doi.org/10.2174/1574893614666191017154427.

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Background: The standard approach for transcriptomic profiling involves high throughput short-read sequencing technology, mainly dominated by Illumina. However, the short reads have limitations in transcriptome assembly and in obtaining full-length transcripts due to the complex nature of transcriptomes with variable length and multiple alternative spliced isoforms. Recent advances in long read sequencing by the Oxford Nanopore Technologies (ONT) offered both cDNA as well as direct RNA sequencing and has brought a paradigm change in the sequencing technology to greatly improve the assembly and expression estimates. ONT enables molecules to be sequenced without fragmentation resulting in ultra-long read length enabling the entire genes and transcripts to be fully characterized. The direct RNA sequencing method, in addition, circumvents the reverse transcription and amplification steps. Objective: In this study, RNA sequencing methods were assessed by comparing data from Illumina (ILM), ONT cDNA (OCD) and ONT direct RNA (ODR). Methods: The sensitivity & specificity of the isoform detection was determined from the data generated by Illumina, ONT cDNA and ONT direct RNA sequencing technologies using Saccharomyces cerevisiae as model. Comparative studies were conducted with two pipelines to detect the isoforms, novel genes and variable gene length. Results: Mapping metrics and qualitative profiles for different pipelines are presented to understand these disruptive technologies. The variability in sequencing technology and the analysis pipeline were studied.

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Levy, Eric, Pamela Milani, Fabio Navarro, Gabor Bartha, Charles Abbott, Jose Jacob, Rena McClory, et al. "75 Comprehensive profiling of the tumor-immune microenvironment using an augmented transcriptome." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (November 2021): A83. http://dx.doi.org/10.1136/jitc-2021-sitc2021.075.

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BackgroundComprehensive profiling of both the tumor and tumor microenvironment (TME) can help further our understanding of tumor progression and response to treatment. Many immune features can be extracted from transcriptomic data, including characterization of the immune infiltrate and profiling the diversity of immune receptors. To address this, we have developed multiple TME profiling features as part of the ImmunoID NeXT Platform®, an augmented, immuno-oncology-optimized exome/transcriptome platform designed to provide comprehensive information regarding the tumor and TME from a single FFPE tumor sample. These features including quantification of immune cell infiltration and profiling of the T-cell receptor (TCR) and B-cell receptor (BCR).MethodsTo develop our immune infiltrate quantification method, we profiled the transcriptomes of eight purified immune cell types using ImmunoID NeXT™ to develop platform-specific gene sets, and compared our transcriptome quantification to immune cell quantification with IHC. For TCR and BCR methods, we analyzed the reproducibility of clone results, and compared top clones to standalone TCR and BCR sequencing approaches. In addition, we characterized the immune content of over 800 tumor samples across 14 cancer types. Finally, we analyzed the immune features in a cohort of melanoma patients who underwent PD-1 blockade.ResultsWe observe significant concordances between cell fractions by IHC and ImmunoID NeXT’s transcriptome-based scores in tumor FFPE samples for B cells, CD8+ T cells, and macrophages (R2>0.82, R2>0.75, and R2>0.52, respectively). For TCR and BCR methods, abundances of clones shared between subsequent curls of a tumor FFPE sample have very high concordances (R2>0.89, R2>0.92, and R2>0.76 for TRB, IgG, and IgA, respectively). Compared to the standalone approaches, we identify 100% of the top 500 TRB clones and 95% of the top 500 IgG clones, with highly concordant abundances (R2>0.94 and R2>0.82 for TRB and IgG, respectively) in a PBMC sample. We identify biologically-relevant immune signatures across tumor types by characterizing the immune features across over 800 tumor samples. Finally, in a melanoma cohort, TRB clonality and CD8+ T cell scores are significantly different in responders to checkpoint inhibition.ConclusionsRNA sequencing can be used as a scalable approach to profile the immune composition in tumors. Such analysis can add to our understanding of the tumor-immune interaction, including studies of response to immunotherapy. We show that immune infiltrate quantification and TCR and BCR profiling – all part of the ImmunoID NeXT Platform – are able to accurately and effectively evaluate the composition and diversity of tumor-infiltrating immune cells.

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Zhu, L. K., H. Ming, S. C. Liu, R. Iyyappan, E. D. Llano, M. Dvoran, Q. Chen, A. Susor, T. Zhou, and Z. L. Jiang. "47 High-resolution ribosome profiling reveals translational selectivity in the mammalian blastocyst." Reproduction, Fertility and Development 33, no. 2 (2021): 130. http://dx.doi.org/10.1071/rdv33n2ab47.

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Transcriptomic analyses of early mammalian embryos from multiple species have been comprehensively conducted in the last decade. However, mRNAs detected from overall transcriptomic profile of an embryo or a single cell do not necessarily represent their functional status, as there is a gap between the overall transcriptome and mRNAs that are actively translated. Ribosome profiling has been developed to infer the translational status of a specific mRNA species and thus analyse the genome-wide translatome. However, the broad application of ribosome profiling has been slowed by its complexity and the difficulty of adapting it to low-input samples such as embryos. In this study, we developed an ultra-low-input ribosome profiling protocol optimized for mammalian embryos and systematically analysed both polysome- and non-polysome-bound mRNA profiles of invitro-produced bovine blastocysts. Ten equal fractions were collected by means of sucrose density gradient and ultracentrifugation of lysates from 100 pooled blastocysts (n=2 pools), and subjected to RNA isolation and RNA sequencing. Our bioinformatics analyses of the mRNA profiles from each fraction along with the whole-transcriptome data revealed that compared with the overall transcriptome, there is a strong selection of mRNAs in the ribosome- and polysome-associated fractions, including transcriptional factors (e.g. POU5F1, ESRRB, AQP3, and APOA1) and genes involved in ribosome biogenesis, oxidative phosphorylation, and metabolic pathways, many of which are essential for the function of embryo implantation. We also identified novel epigenetic regulators selectively translated, including regulatory enzymes on histone modifications and RNA modifications (e.g. JMJD7, ALKBH4, ALKBH7, and METTL26). In addition, we confirmed the translation of the highly expressed, yet developmentally essential pathways in the blastocysts (e.g. Wnt and Notch signalling pathways). The selectively translated mRNAs were further validated by immunofluorescent staining at the protein level and cross-validated in both bovine and mouse blastocysts. Some of these genes show only modest expression in the overall transcriptome data. Their selective translation at the blastocyst stage is only being revealed by the ribosome fractions analyses, and their functions warrant future detailed investigations. In conclusion, this study reveals bona fide active translating mRNAs in the mammalian blastocyst. The low-input ribosome profiling protocol and the data presented here set an example and open future avenues for detailed ribosome fraction–based translatome analyses to reveal novel cellular/embryonic functional regulators beyond transcriptomic data.

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Zhu, L. K., H. Ming, S. C. Liu, R. Iyyappan, E. D. Llano, M. Dvoran, Q. Chen, A. Susor, T. Zhou, and Z. L. Jiang. "47 High-resolution ribosome profiling reveals translational selectivity in the mammalian blastocyst." Reproduction, Fertility and Development 33, no. 2 (2021): 130. http://dx.doi.org/10.1071/rdv33n2ab47.

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Transcriptomic analyses of early mammalian embryos from multiple species have been comprehensively conducted in the last decade. However, mRNAs detected from overall transcriptomic profile of an embryo or a single cell do not necessarily represent their functional status, as there is a gap between the overall transcriptome and mRNAs that are actively translated. Ribosome profiling has been developed to infer the translational status of a specific mRNA species and thus analyse the genome-wide translatome. However, the broad application of ribosome profiling has been slowed by its complexity and the difficulty of adapting it to low-input samples such as embryos. In this study, we developed an ultra-low-input ribosome profiling protocol optimized for mammalian embryos and systematically analysed both polysome- and non-polysome-bound mRNA profiles of invitro-produced bovine blastocysts. Ten equal fractions were collected by means of sucrose density gradient and ultracentrifugation of lysates from 100 pooled blastocysts (n=2 pools), and subjected to RNA isolation and RNA sequencing. Our bioinformatics analyses of the mRNA profiles from each fraction along with the whole-transcriptome data revealed that compared with the overall transcriptome, there is a strong selection of mRNAs in the ribosome- and polysome-associated fractions, including transcriptional factors (e.g. POU5F1, ESRRB, AQP3, and APOA1) and genes involved in ribosome biogenesis, oxidative phosphorylation, and metabolic pathways, many of which are essential for the function of embryo implantation. We also identified novel epigenetic regulators selectively translated, including regulatory enzymes on histone modifications and RNA modifications (e.g. JMJD7, ALKBH4, ALKBH7, and METTL26). In addition, we confirmed the translation of the highly expressed, yet developmentally essential pathways in the blastocysts (e.g. Wnt and Notch signalling pathways). The selectively translated mRNAs were further validated by immunofluorescent staining at the protein level and cross-validated in both bovine and mouse blastocysts. Some of these genes show only modest expression in the overall transcriptome data. Their selective translation at the blastocyst stage is only being revealed by the ribosome fractions analyses, and their functions warrant future detailed investigations. In conclusion, this study reveals bona fide active translating mRNAs in the mammalian blastocyst. The low-input ribosome profiling protocol and the data presented here set an example and open future avenues for detailed ribosome fraction–based translatome analyses to reveal novel cellular/embryonic functional regulators beyond transcriptomic data.

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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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Skvortsov, T. A., D. V. Ignatov, K. B. Majorov, A. S. Apt, and T. L. Azhikina. "Mycobacterium tuberculosis Transcriptome Profiling in Mice with Genetically Different Susceptibility to Tuberculosis." Acta Naturae 5, no. 2 (June 15, 2013): 62–69. http://dx.doi.org/10.32607/20758251-2013-5-2-62-69.

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Whole transcriptome profiling is now almost routinely used in various fields of biology, including microbiology. In vivo transcriptome studies usually provide relevant information about the biological processes in the organism and thus are indispensable for the formulation of hypotheses, testing, and correcting. In this study, we describe the results of genome-wide transcriptional profiling of the major human bacterial pathogen M. tuberculosis during its persistence in lungs. Two mouse strains differing in their susceptibility to tuberculosis were used for experimental infection with M. tuberculosis. Mycobacterial transcriptomes obtained from the infected tissues of the mice at two different time points were analyzed by deep sequencing and compared. It was hypothesized that the changes in the M. tuberculosis transcriptome may attest to the activation of the metabolism of lipids and amino acids, transition to anaerobic respiration, and increased expression of the factors modulating the immune response. A total of 209 genes were determined whose expression increased with disease progression in both host strains (commonly upregulated genes, CUG). Among them, the genes related to the functional categories of lipid metabolism, cell wall, and cell processes are of great interest. It was assumed that the products of these genes are involved in M. tuberculosis adaptation to the host immune system defense, thus being potential targets for drug development.

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Rossouw, Debra, Adri H. van den Dool, Dan Jacobson, and Florian F. Bauer. "Comparative Transcriptomic and Proteomic Profiling of Industrial Wine Yeast Strains." Applied and Environmental Microbiology 76, no. 12 (April 23, 2010): 3911–23. http://dx.doi.org/10.1128/aem.00586-10.

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ABSTRACT The geno- and phenotypic diversity of commercial Saccharomyces cerevisiae wine yeast strains provides an opportunity to apply the system-wide approaches that are reasonably well established for laboratory strains to generate insight into the functioning of complex cellular networks in industrial environments. We have previously analyzed the transcriptomes of five industrial wine yeast strains at three time points during alcoholic fermentation. Here, we extend the comparative approach to include an isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis of two of the previously analyzed wine yeast strains at the same three time points during fermentation in synthetic wine must. The data show that differences in the transcriptomes of the two strains at a given time point rather accurately reflect differences in the corresponding proteomes independently of the gene ontology (GO) category, providing strong support for the biological relevance of comparative transcriptomic data sets in yeast. In line with previous observations, the alignment proves to be less accurate when assessing intrastrain changes at different time points. In this case, differences between the transcriptome and proteome appear to be strongly dependent on the GO category of the corresponding genes. The data in particular suggest that metabolic enzymes and the corresponding genes appear to be strongly correlated over time and between strains, suggesting a strong transcriptional control of such enzymes. The data also allow the generation of hypotheses regarding the molecular origin of significant differences in phenotypic traits between the two strains.

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Wang, Jing, Zihao Ma, Steven A. Carr, Philipp Mertins, Hui Zhang, Zhen Zhang, Daniel W. Chan, et al. "Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction." Molecular & Cellular Proteomics 16, no. 1 (November 11, 2016): 121–34. http://dx.doi.org/10.1074/mcp.m116.060301.

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Peano, Clelia, Marco Severgnini, Ingrid Cifola, Gianluca De Bellis, and Cristina Battaglia. "Transcriptome amplification methods in gene expression profiling." Expert Review of Molecular Diagnostics 6, no. 3 (May 2006): 465–80. http://dx.doi.org/10.1586/14737159.6.3.465.

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Basu, Urmila, Josue Moura Romao, and Le Luo Guan. "Adipogenic Transcriptome Profiling Using High Throughput Technologies." Journal of Genomics 1 (2013): 22–28. http://dx.doi.org/10.7150/jgen.3781.

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Chang, Kai-Chih, Han-Yueh Kuo, Chuan Tang, Cheng-Wei Chang, Chia-Wei Lu, Chih-Chin Liu, Huei-Ru Lin, Kuan-Hsueh Chen, and Ming-Li Liou. "Transcriptome profiling in imipenem-selected Acinetobacter baumannii." BMC Genomics 15, no. 1 (2014): 815. http://dx.doi.org/10.1186/1471-2164-15-815.

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Vandepoele, Klaas, and Yves Van de Peer. "Exploring the Plant Transcriptome through Phylogenetic Profiling." Plant Physiology 137, no. 1 (January 2005): 31–42. http://dx.doi.org/10.1104/pp.104.054700.

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Singh, R. P., C. M. Shafeeque, S. K. Sharma, R. Singh, J. Mohan, K. V. H. Sastry, V. K. Saxena, and P. A. Azeez. "Chicken sperm transcriptome profiling by microarray analysis." Genome 59, no. 3 (March 2016): 185–96. http://dx.doi.org/10.1139/gen-2015-0106.

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It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21 639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

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Hamada, Hirotaka, Hiroaki Okae, Nobuo Yaegashi, and Takahiro Arima. "Transcriptome profiling of purified human trophoblast cells." Placenta 46 (October 2016): 108–9. http://dx.doi.org/10.1016/j.placenta.2016.08.026.

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Zhang, Pu, Marco Zucchelli, Sara Bruce, Fredwell Hambiliki, Anneli Stavreus-Evers, Lev Levkov, Heli Skottman, Erja Kerkelä, Juha Kere, and Outi Hovatta. "Transcriptome Profiling of Human Pre-Implantation Development." PLoS ONE 4, no. 11 (November 16, 2009): e7844. http://dx.doi.org/10.1371/journal.pone.0007844.

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CHEN, HSUAN-YU, SUNG-LIANG YU, KER-CHAU LI, and PAN-CHYR YANG. "Biomarkers and transcriptome profiling of lung cancer." Respirology 17, no. 4 (April 19, 2012): 620–26. http://dx.doi.org/10.1111/j.1440-1843.2012.02154.x.

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Zhu, Tong, and Xun Wang. "Large-Scale Profiling of the Arabidopsis Transcriptome." Plant Physiology 124, no. 4 (December 1, 2000): 1472–76. http://dx.doi.org/10.1104/pp.124.4.1472.

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Wang, Lina, Rongling Wu, and Wenhao Bo. "Transcriptome profiling of PeCRY1 transgenic Populus tomentosa." Genes & Genomics 40, no. 4 (November 25, 2017): 349–59. http://dx.doi.org/10.1007/s13258-017-0631-7.

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Li, Yang, David Elashoff, Myungshin Oh, Uttam Sinha, Maie A. R. St John, Xiaofeng Zhou, Elliot Abemayor, and David T. Wong. "Serum Circulating Human mRNA Profiling and Its Utility for Oral Cancer Detection." Journal of Clinical Oncology 24, no. 11 (April 20, 2006): 1754–60. http://dx.doi.org/10.1200/jco.2005.03.7598.

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PurposeThe purpose of this study is to explore the presence of informative RNA biomarkers from human serum transcriptome, and evaluate the serum transcriptome diagnostics for disease detection. Oral squamous cell carcinoma (OSCC) was selected as the proof-of-concept disease.Patients and MethodsBlood samples were collected from patients (n = 32) with primary T1/T2 OSCC and matched healthy patients (n = 35). Circulating RNA was isolated from serum and linearly amplified using T7 polymerase. Microarrays were applied for profiling transcriptome in serum from 10 cancer patients and controls. The differential gene expression was analyzed by combining the present calls, t tests, and fold-change statistics. Quantitative polymerase chain reaction (PCR) was used to validate the selected candidate RNA markers identified by microarray. Receiver operating characteristic curve and classification models were exploited to evaluate the diagnostic power of these markers for OSCC.ResultsHuman serum circulating mRNAs were presented by reverse transcriptase PCR. Microarray identified 2,623 ± 868 probes assigned present calls in OSCC (n = 10) versus 1,792 ± 165 in healthy patients (n = 10), indicating a higher complexity of serum transciptome in OSCC patients (P = .002, Wilcoxon test). Three hundred thirty-five serum RNAs exhibited significantly differential expression level between the two groups (P < .05, t test; fold ≥ 2). Five cancer-related gene transcripts were consistently validated by quantitative PCR on serum from OSCC patients (n = 32) and controls (n = 35). The best combination of biomarkers yielded a receiver operating characteristic curve value of 88%, sensitivity (91%), and specificity (71%) in distinguishing OSCC.ConclusionThe utility of serum transcriptome diagnostics is successfully demonstrated for OSCC detection. This novel concept could be developed as an adjunctive tool for disease diagnosis.

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Puccetti, Antonio, Andrea Pelosi, Piera Filomena Fiore, Giuseppe Patuzzo, Claudio Lunardi, and Marzia Dolcino. "MicroRNA Expression Profiling in Behçet’s Disease." Journal of Immunology Research 2018 (2018): 1–18. http://dx.doi.org/10.1155/2018/2405150.

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Background. Behçet’s disease (BD) is a chronic inflammatory multisystem disease characterized by oral and genital ulcers, uveitis, and skin lesions. MicroRNAs (miRNAs) are key regulators of immune responses. Differential expression of miRNAs has been reported in several inflammatory autoimmune diseases; however, their role in BD is not fully elucidated. We aimed to identify miRNA expression signatures associated with BD and to investigate their potential implication in the disease pathogenesis. Methods. miRNA microarray analysis was performed in blood cells of BD patients and healthy controls. miRNA expression profiles were analyzed using Affymetrix arrays with a comprehensive coverage of miRNA sequences. Pathway analyses were performed, and the global miRNA profiling was combined with transcriptoma data in BD. Deregulation of selected miRNAs was validated by real-time PCR. Results. We identified specific miRNA signatures associated with BD patients with active disease. These miRNAs target pathways relevant in BD, such as TNF, IFN gamma, and VEGF-VEGFR signaling cascades. Network analysis revealed several miRNAs regulating highly connected genes within the BD transcriptoma. Conclusions. The combined analysis of deregulated miRNAs and BD transcriptome sheds light on some epigenetic aspects of BD identifying specific miRNAs, which may represent promising candidates as biomarkers and/or for the design of novel therapeutic strategies in BD.

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Bergamo, Alberta, Marco Gerdol, Alberto Pallavicini, Samuele Greco, Isabelle Schepens, Romain Hamelin, Florence Armand, Paul J. Dyson, and Gianni Sava. "Lysozyme-Induced Transcriptional Regulation of TNF-α Pathway Genes in Cells of the Monocyte Lineage." International Journal of Molecular Sciences 20, no. 21 (November 5, 2019): 5502. http://dx.doi.org/10.3390/ijms20215502.

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Lysozyme is one of the most important anti-bacterial effectors in the innate immune system of animals. Besides its direct antibacterial enzymatic activity, lysozyme displays other biological properties, pointing toward a significant anti-inflammatory effect, many aspects of which are still elusive. Here we investigate the perturbation of gene expression profiles induced by lysozyme in a monocyte cell line in vitro considering a perspective as broad as the whole transcriptome profiling. The results of the RNA-seq experiment show that lysozyme induces transcriptional modulation of the TNF-α/IL-1β pathway genes in U937 monocytes. The analysis of transcriptomic profiles with IPA® identified a simple but robust molecular network of genes, in which the regulation trends are fully consistent with the anti-inflammatory activity of lysozyme. This study provides the first evidence in support of the anti-inflammatory action of lysozyme on the basis of transcriptomic regulation data resulting from the broad perspective of a whole-transcriptome profiling. Such important effects can be achieved with the supplementation of relatively low concentrations of lysozyme, for a short time of exposure. These new insights allow the potential of lysozyme in pharmacological applications to be better exploited.

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Yang, Bo, Peixiu Yin, Ruicheng Yang, Bojie Xu, Jiyang Fu, Shuli Zhi, Menghong Dai, Chen Tan, Huanchun Chen, and Xiangru Wang. "Holistic insights into meningitic Escherichia coli infection of astrocytes based on whole transcriptome profiling." Epigenomics 12, no. 18 (September 2020): 1611–32. http://dx.doi.org/10.2217/epi-2019-0342.

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Aim: To investigate the mRNAs and noncoding RNAs (ncRNAs) expression in astrocytes upon meningitic- Escherichia coli infection. Materials & methods: The transcription of mRNAs and ncRNAs were fully investigated and profiled by whole transcriptome sequencing and bioinformatic approaches. Whole transcriptome differences between the infected astrocytes and brain microvascular endothelial cells were further compared and characterized. Results: A total of 2045 mRNAs, 74 long noncoding RNAs, 27 miRNAs and 418 circular RNAs were differentially transcribed in astrocytes upon infection. Competing endogenous RNAs regulatory networks were constructed and preliminary validated. Transcriptomic differences between astrocyte and brain microvascular endothelial cells revealed the cell-specific responses against the infection. Conclusion: Our study comprehensively characterized the ncRNAs and mRNAs profiles in astrocytes upon meningitic- E. coli infection, which will facilitate future functional studies.

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Dong, Xiaomin, Yanan You, and Jia Qian Wu. "Building an RNA Sequencing Transcriptome of the Central Nervous System." Neuroscientist 22, no. 6 (July 7, 2016): 579–92. http://dx.doi.org/10.1177/1073858415610541.

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The composition and function of the central nervous system (CNS) is extremely complex. In addition to hundreds of subtypes of neurons, other cell types, including glia (astrocytes, oligodendrocytes, and microglia) and vascular cells (endothelial cells and pericytes) also play important roles in CNS function. Such heterogeneity makes the study of gene transcription in CNS challenging. Transcriptomic studies, namely the analyses of the expression levels and structures of all genes, are essential for interpreting the functional elements and understanding the molecular constituents of the CNS. Microarray has been a predominant method for large-scale gene expression profiling in the past. However, RNA-sequencing (RNA-Seq) technology developed in recent years has many advantages over microarrays, and has enabled building more quantitative, accurate, and comprehensive transcriptomes of the CNS and other systems. The discovery of novel genes, diverse alternative splicing events, and noncoding RNAs has remarkably expanded the complexity of gene expression profiles and will help us to understand intricate neural circuits. Here, we discuss the procedures and advantages of RNA-Seq technology in mammalian CNS transcriptome construction, and review the approaches of sample collection as well as recent progress in building RNA-Seq-based transcriptomes from tissue samples and specific cell types.

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Tian, Ruizheng, Yixiao Huang, Balachandar Balakrishnan, and Maohua Chen. "Gene Expression Profiling Indicated Diverse Functions and Characteristics of Core Genes in Pea Aphid." Insects 11, no. 3 (March 15, 2020): 186. http://dx.doi.org/10.3390/insects11030186.

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The pea aphid is a global insect pest, and variable phenotypes can be produced by pea aphids in the same genotype in response to changes in external environmental factors. However, detailed dynamic gene regulation networks and the core markers involved in different biological processes of pea aphids have not yet been reported. In this study, we obtained the published genomic and transcriptomic data, and performed transcriptome profiling of five pea aphid morphs (winged asexual female, wingless asexual female, wingless sexual female, winged male and wingless male) from each of three pea aphid genotypes, i.e., the transcriptomes from a total of 15 types of pea aphids were analyzed and the type-specific expression of genes in five different morphs was identified. The expression profiling was verified by quantitative real-time PCR (qPCR) analysis. Moreover, we determined the expression features and co-expression networks of highly variable genes. We also used the ARACNe method to obtain 263 core genes related to different biological pathways. Additionally, eight of the identified genes were aligned with transcription factor families, indicating that they act as transcription factors and regulate downstream genes. Furthermore, we found reliable markers using random forest methodology to distinguish different morphs of pea aphids. Our study provides a systematic and comprehensive approach for analyzing the core genes that may play important roles in a multitude of biological processes from the insect transcriptomes.

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Saygin, Didem, Tracy Tabib, Humberto E. T. Bittar, Eleanor Valenzi, John Sembrat, Stephen Y. Chan, Mauricio Rojas, and Robert Lafyatis. "Transcriptional profiling of lung cell populations in idiopathic pulmonary arterial hypertension." Pulmonary Circulation 10, no. 1 (January 2020): ??? http://dx.doi.org/10.1177/2045894020908782.

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Despite recent improvements in management of idiopathic pulmonary arterial hypertension, mortality remains high. Understanding the alterations in the transcriptome–phenotype of the key lung cells involved could provide insight into the drivers of pathogenesis. In this study, we examined differential gene expression of cell types implicated in idiopathic pulmonary arterial hypertension from lung explants of patients with idiopathic pulmonary arterial hypertension compared to control lungs. After tissue digestion, we analyzed all cells from three idiopathic pulmonary arterial hypertension and six control lungs using droplet-based single cell RNA-sequencing. After dimensional reduction by t-stochastic neighbor embedding, we compared the transcriptomes of endothelial cells, pericyte/smooth muscle cells, fibroblasts, and macrophage clusters, examining differential gene expression and pathways implicated by analysis of Gene Ontology Enrichment. We found that endothelial cells and pericyte/smooth muscle cells had the most differentially expressed gene profile compared to other cell types. Top differentially upregulated genes in endothelial cells included novel genes: ROBO4, APCDD1, NDST1, MMRN2, NOTCH4, and DOCK6, as well as previously reported genes: ENG, ORAI2, TFDP1, KDR, AMOTL2, PDGFB, FGFR1, EDN1, and NOTCH1. Several transcription factors were also found to be upregulated in idiopathic pulmonary arterial hypertension endothelial cells including SOX18, STRA13, LYL1, and ELK, which have known roles in regulating endothelial cell phenotype. In particular, SOX18 was implicated through bioinformatics analyses in regulating the idiopathic pulmonary arterial hypertension endothelial cell transcriptome. Furthermore, idiopathic pulmonary arterial hypertension endothelial cells upregulated expression of FAM60A and HDAC7, potentially affecting epigenetic changes in idiopathic pulmonary arterial hypertension endothelial cells. Pericyte/smooth muscle cells expressed genes implicated in regulation of cellular apoptosis and extracellular matrix organization, and several ligands for genes showing increased expression in endothelial cells. In conclusion, our study represents the first detailed look at the transcriptomic landscape across idiopathic pulmonary arterial hypertension lung cells and provides robust insight into alterations that occur in vivo in idiopathic pulmonary arterial hypertension lungs.

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Jeon, Jongbum, Gir-Won Lee, Ki-Tae Kim, Sook-Young Park, Seongbeom Kim, Seomun Kwon, Aram Huh, et al. "Transcriptome Profiling of the Rice Blast Fungus Magnaporthe oryzae and Its Host Oryza sativa During Infection." Molecular Plant-Microbe Interactions® 33, no. 2 (February 2020): 141–44. http://dx.doi.org/10.1094/mpmi-07-19-0207-a.

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The rice blast (fungal pathogen: Magnaporthe oryzae and host: Oryza sativa) is one of the most important model pathosystems for understanding plant–microbe interactions. Although both genome sequences were published as the first cases of pathogen and host, only a few in planta transcriptome data during infection are available. Due to technical difficulties, previously reported fungal transcriptome data are not highly qualified to comprehensively profile the expression of fungal genes during infection. Here, we report the high-quality transcriptomes of M. oryzae and rice during infection using a sheath infection-based RNA sequencing approach. This comprehensive expression profiling of the fungal pathogen and its host will provide a better platform for understanding the plant–microbe interactions at the genomic level and serve as a valuable resource for the research community.

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Majewska, Marta, Aleksandra Lipka, Lukasz Paukszto, Jan Jastrzebski, Karol Szeszko, Marek Gowkielewicz, Ewa Lepiarczyk, Marcin Jozwik, and Mariusz Majewski. "Placenta Transcriptome Profiling in Intrauterine Growth Restriction (IUGR)." International Journal of Molecular Sciences 20, no. 6 (March 26, 2019): 1510. http://dx.doi.org/10.3390/ijms20061510.

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Intrauterine growth restriction (IUGR) is a serious pathological complication associated with compromised fetal development during pregnancy. The aim of the study was to broaden knowledge about the transcriptomic complexity of the human placenta by identifying genes potentially involved in IUGR pathophysiology. RNA-Seq data were used to profile protein-coding genes, detect alternative splicing events (AS), single nucleotide variant (SNV) calling, and RNA editing sites prediction in IUGR-affected placental transcriptome. The applied methodology enabled detection of 37,501 transcriptionally active regions and the selection of 28 differentially-expressed genes (DEGs), among them 10 were upregulated and 18 downregulated in IUGR-affected placentas. Functional enrichment annotation indicated that most of the DEGs were implicated in the processes of inflammation and immune disorders related to IUGR and preeclampsia. Additionally, we revealed that some genes (S100A13, GPR126, CTRP1, and TFPI) involved in the alternation of splicing events were mainly implicated in angiogenic-related processes. Significant SNVs were overlapped with 6533 transcripts and assigned to 2386 coding sequence (CDS), 1528 introns, 345 5’ untranslated region (UTR), 1260 3’UTR, 918 non-coding RNA (ncRNA), and 10 intergenic regions. Within CDS regions, 543 missense substitutions with functional effects were recognized. Two known mutations (rs4575, synonymous; rs3817, on the downstream region) were detected within the range of AS and DEG candidates: PA28β and PINLYP, respectively. Novel genes that are dysregulated in IUGR were detected in the current research. Investigating genes underlying the IUGR is crucial for identification of mechanisms regulating placental development during a complicated pregnancy.

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Nieuwenhuis, Sylvia, Joanna Widomska, Paul Blom, Peter-Bram A. C. ‘t Hoen, Baziel G. M. van Engelen, and Jeffrey C. Glennon. "Blood Transcriptome Profiling Links Immunity to Disease Severity in Myotonic Dystrophy Type 1 (DM1)." International Journal of Molecular Sciences 23, no. 6 (March 12, 2022): 3081. http://dx.doi.org/10.3390/ijms23063081.

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The blood transcriptome was examined in relation to disease severity in type I myotonic dystrophy (DM1) patients who participated in the Observational Prolonged Trial In DM1 to Improve QoL- Standards (OPTIMISTIC) study. This sought to (a) ascertain if transcriptome changes were associated with increasing disease severity, as measured by the muscle impairment rating scale (MIRS), and (b) establish if these changes in mRNA expression and associated biological pathways were also observed in the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) microarray dataset in blood (with equivalent MIRS/DMPK repeat length). The changes in gene expression were compared using a number of complementary pathways, gene ontology and upstream regulator analyses, which suggested that symptom severity in DM1 was linked to transcriptomic alterations in innate and adaptive immunity associated with muscle-wasting. Future studies should explore the role of immunity in DM1 in more detail to assess its relevance to DM1.

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Park, Chang Ha, Hyeon Ji Yeo, Ye Eun Park, Seung-A. Baek, Jae Kwang Kim, and Sang Un Park. "Transcriptome Analysis and Metabolic Profiling of Lycoris Radiata." Biology 8, no. 3 (August 29, 2019): 63. http://dx.doi.org/10.3390/biology8030063.

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Lycoris radiata belongs to the Amaryllidaceae family and is a bulbous plant native to South Korea, China, and Japan. Galantamine, a representative alkaloid of Amaryllidaceae plants, including L. radiata, exhibits selective and dominant acetylcholinesterase inhibition. In spite of the economic and officinal importance of L. radiata, the molecular biological and biochemical information on L. radiata is relatively deficient. Therefore, this study provides functional information of L. radiata, describe galantamine biosynthesis in the various organs, and provide transcriptomic and metabolic datasets to support elucidation of galantamine biosynthesis pathway in future studies. The results of studies conducted in duplicate revealed the presence of a total of 325,609 and 404,019 unigenes, acquired from 9,913,869,968 and 10,162,653,038 raw reads, respectively, after trimming the raw reads using CutAdapt, assembly using Trinity package, and clustering using CD-Hit-EST. All of the assembled unigenes were aligned to the public databases, including National Center for Biotechnology Information (NCBI) non-redundant protein (NR) and nucleotide (Nt) database, SWISS-PROT (UniProt) protein sequence data bank, The Arabidopsis Information Resource (TAIR), the Swiss-Prot protein database, Gene Ontology (GO), and Clusters of Orthologous Groups (COG) database to predict potential genes and provide their functional information. Based on our transcriptome data and published literatures, eight full-length cDNA clones encoding LrPAL2, LrPAL3, LrC4H2, LrC3H, LrTYDC2, LrNNR, LrN4OMT, and LrCYP96T genes, involved in galantamine biosynthesis, were identified in L. radiata. In order to investigate galantamine biosynthesis in different plant parts of L. radiata grown in a growth chamber, gene expression levels were measured through quantitative real-time polymerase chain reaction (qRT-PCR) analysis using these identified genes and galantamine levels were quantified by high-performance liquid chromatography (HPLC) analysis. The qRT-PCR data revealed high expression levels of LrNNR, LrN4OMT, and LrCYP96T in the bulbs, and, as expected, we observed higher amounts of galantamine in the bulbs than in the root and leaves. Additionally, a total of 40 hydrophilic metabolites were detected in the different organs using gas-chromatography coupled with time-of-flight mass spectrometry. In particular, a strong positive correlation between galantamine and sucrose, which provides energy for the secondary metabolite biosynthesis, was observed.

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Aristizabal Prada, Elke, Isabella Castellano, Eva Sušnik, Yuhong Yang, Lucie Meyer, Martina Tetti, Felix Beuschlein, Martin Reincke, and Tracy Williams. "Comparative Genomics and Transcriptome Profiling in Primary Aldosteronism." International Journal of Molecular Sciences 19, no. 4 (April 9, 2018): 1124. http://dx.doi.org/10.3390/ijms19041124.

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Menzies, Rebecca JZ, Yury V. Bukhman, Nancy F. Ng, Patricia A. Shaw, and Tak W. Mak. "GENOMIC AND TRANSCRIPTOME PROFILING OF EPITHELIAL OVARIAN CANCER." Clinical & Investigative Medicine 31, no. 4 (August 1, 2008): 17. http://dx.doi.org/10.25011/cim.v31i4.4817.

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Background: Epithelial ovarian cancer is the leading cause of death by gynecological malignancy. Due to inadequate screening modalities, a lack of characteristic presenting symptoms, limited treatments and a poor understanding of the molecular underpinnings of the disease, only 25% of ovarian cancers are diagnosed at an early stage. Current 5-year survival rates range from 80%, for disease diagnosed in Stage I to as low as 13% for Stage IV. Current screening for ovarian cancer involves measuring CA-125 levels. However, CA-125 testing has low sensitivity since it can be elevated in a variety of other gynecological diseases. Numerous studies have found molecular heterogeneity between the four histological subtypes of ovarian cancer (serous, endometrioid, clear cell and mucinous). However, treatments remain the same for all subtypes regardless of molecular heterogeneity. Thus, better treatment targets and biomarkers must be found for this disease. Methods:In our study 300 ovarian tumors will be genomically profiled using the Affymetrix Genome-Wide SNP Array 6.0 to identify loci and genes implicated in ovarian cancer. To date, 51 ovarian tumors have been analyzed using the SNP array. Results:Preliminary analysis of copy number variation in these tumors using Partek software has revealed a total of 978 loci. Known amplifications derived from the literature were seen at CCNE1 and ERBB2. Similarly, well known deletions ofp53 and RB1 in ovarian cancer were detected. Novel amplified loci at 18q11.2 and 4q33 were also detected. Novel deletions were detected at 7p13 and 8q22.2. Conclusion: Future work will include running the remaining 249 tumor samples on the SNP array and analyzing the complete dataset using Partek software. Future validation of identified genes in vitro and in vivo may provide insight and possible biomarkers that may be used clinically to benefit the ovarian cancer patient.

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Mortimer, Niall, Cristina Sánchez-Mora, Paula Rovira, Laura Vilar-Ribó, Vanesa Richarte, Montse Corrales, Christian Fadeuilhe, et al. "Transcriptome profiling in adult attention-deficit hyperactivity disorder." European Neuropsychopharmacology 41 (December 2020): 160–66. http://dx.doi.org/10.1016/j.euroneuro.2020.11.005.

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Khaledi, Ariane, Monika Schniederjans, Sarah Pohl, Roman Rainer, Ulrich Bodenhofer, Boyang Xia, Frank Klawonn, et al. "Transcriptome Profiling of Antimicrobial Resistance in Pseudomonas aeruginosa." Antimicrobial Agents and Chemotherapy 60, no. 8 (May 23, 2016): 4722–33. http://dx.doi.org/10.1128/aac.00075-16.

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ABSTRACTEmerging resistance to antimicrobials and the lack of new antibiotic drug candidates underscore the need for optimization of current diagnostics and therapies to diminish the evolution and spread of multidrug resistance. As the antibiotic resistance status of a bacterial pathogen is defined by its genome, resistance profiling by applying next-generation sequencing (NGS) technologies may in the future accomplish pathogen identification, prompt initiation of targeted individualized treatment, and the implementation of optimized infection control measures. In this study, qualitative RNA sequencing was used to identify key genetic determinants of antibiotic resistance in 135 clinicalPseudomonas aeruginosaisolates from diverse geographic and infection site origins. By applying transcriptome-wide association studies, adaptive variations associated with resistance to the antibiotic classes fluoroquinolones, aminoglycosides, and β-lactams were identified. Besides potential novel biomarkers with a direct correlation to resistance, global patterns of phenotype-associated gene expression and sequence variations were identified by predictive machine learning approaches. Our research serves to establish genotype-based molecular diagnostic tools for the identification of the current resistance profiles of bacterial pathogens and paves the way for faster diagnostics for more efficient, targeted treatment strategies to also mitigate the future potential for resistance evolution.

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Reeve, Jeff, and Philip F. Halloran. "Biopsy transcriptome expression profiling: proper validation is key." Lancet 389, no. 10069 (February 2017): 600–601. http://dx.doi.org/10.1016/s0140-6736(17)30282-9.

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Journal articles on the topic 'Transcriptome profiling'

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