Journal articles: 'HUMAN TRANSCRIPTOME'

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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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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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Hu, S., Y. Li, J. Wang, Y. Xie, K. Tjon, L. Wolinsky, R. R. O. Loo, J. A. Loo, and D. T. Wong. "Human Saliva Proteome and Transcriptome." Journal of Dental Research 85, no. 12 (December 2006): 1129–33. http://dx.doi.org/10.1177/154405910608501212.

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This paper tests the hypothesis that salivary proteins and their counterpart mRNAs co-exist in human whole saliva. Global profiling of human saliva proteomes and transcriptomes by mass spectrometry (MS) and expression microarray technologies, respectively, revealed many similarities between saliva proteins and mRNAs. Of the function-known proteins identified in saliva, from 61 to 70% were also found present as mRNA transcripts. For genes not detected at both protein and mRNA levels, we made further efforts to determine if the counterpart is present. Of 19 selected genes detected only at the protein level, the mRNAs of 13 (68%) genes were found in saliva by RT-PCR. In contrast, of many mRNAs detected only by microarrays, their protein products were found in saliva, as reported previously by other investigators. The saliva transcriptome may provide preliminary insights into the boundary of the saliva proteome.

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An, Xiuli, Vincent P. Schulz, Jie Li, Kunlu Wu, Jing Liu, Fumin Xue, Jingping Hu, Narla Mohandas, and Patrick G. Gallagher. "Global transcriptome analyses of human and murine terminal erythroid differentiation." Blood 123, no. 22 (May 29, 2014): 3466–77. http://dx.doi.org/10.1182/blood-2014-01-548305.

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Key Points Transcriptome analyses of human and murine reveal significant stage and species-specific differences across stages of terminal erythroid differentiation. These transcriptomes provide a significant resource for understanding mechanisms of normal and perturbed erythropoiesis.

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Strausberg, R. L., and G. J. Riggins. "Navigating the human transcriptome." Proceedings of the National Academy of Sciences 98, no. 21 (October 9, 2001): 11837–38. http://dx.doi.org/10.1073/pnas.221463598.

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Rusk, Nicole. "The human transient transcriptome." Nature Methods 13, no. 8 (July 28, 2016): 612. http://dx.doi.org/10.1038/nmeth.3952.

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Đerke, Filip, and Niko Njirić. "Human transcriptome - molecular neurobiology." Gyrus 3, no. 3 (September 2015): 148–51. http://dx.doi.org/10.17486/gyr.3.1031.

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Goh, Sung-Ho, Matthew Josleyn, Y. Terry Lee, Robert L. Danner, Robert B. Gherman, Maggie C. Cam, and Jeffery L. Miller. "The human reticulocyte transcriptome." Physiological Genomics 30, no. 2 (July 2007): 172–78. http://dx.doi.org/10.1152/physiolgenomics.00247.2006.

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RNA from circulating blood reticulocytes was utilized to provide a robust description of genes transcribed at the final stages of erythroblast maturation. After depletion of leukocytes and platelets, Affymetrix HG-U133 arrays were hybridized with probe generated from the reticulocyte total RNA (blood obtained from 14 umbilical cords and 14 healthy adult humans). Among the cord and adult reticulocyte profiles, 698 probe sets (488 named genes) were detected in each of the 28 samples. Among the highly expressed genes, promoter analyses revealed a subset of transcription factor binding motifs encoded at higher than expected frequencies including the hypoxia-related arylhydrocarbon receptor repressor family. Over 100 probe sets demonstrated differential expression between the cord and adult reticulocyte samples. For verification, the array expression patterns for 21 genes were confirmed by real-time PCR (correlation coefficient 0.98). Only four transcripts (MAP17, FLJ32009 , ARRB2, and FLJ27365 ) were identified as being upregulated in the adult blood transcriptome. Further analysis revealed that the lipid-regulating protein MAP17 was present in the membrane fraction of adult erythrocytes, but not detected in cord blood erythrocytes. Combined with other clinical and experimental data, these reticulocyte transcriptome profiles should be useful to better understand the molecular bases of terminal erythroid differentiation, hemoglobin switching, iron metabolism and malarial pathogenesis.

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Mercer, Tim R., Shane Neph, Marcel E. Dinger, Joanna Crawford, Martin A. Smith, Anne-Marie J. Shearwood, Eric Haugen, et al. "The Human Mitochondrial Transcriptome." Cell 146, no. 4 (August 2011): 645–58. http://dx.doi.org/10.1016/j.cell.2011.06.051.

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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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Lam, Chi Keung, Lei Tian, Nadjet Belbachir, Alexa Wnorowski, Rajani Shrestha, Ning Ma, Tomoya Kitani, June-Wha Rhee, and Joseph C. Wu. "Identifying the Transcriptome Signatures of Calcium Channel Blockers in Human Induced Pluripotent Stem Cell–Derived Cardiomyocytes." Circulation Research 125, no. 2 (July 5, 2019): 212–22. http://dx.doi.org/10.1161/circresaha.118.314202.

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Rationale: Calcium channel blockers (CCBs) are an important class of drugs in managing cardiovascular diseases. Patients usually rely on these medications for the remainder of their lives after diagnosis. Although the acute pharmacological actions of CCBs in the hearts are well-defined, little is known about the drug-specific effects on human cardiomyocyte transcriptomes and physiological alterations after long-term exposure. Objective: This study aimed to simulate chronic CCB treatment and to examine both the functional and transcriptomic changes in human cardiomyocytes. Methods and Results: We differentiated cardiomyocytes and generated engineered heart tissues from 3 human induced pluripotent stem cell lines and exposed them to 4 different CCBs—nifedipine, amlodipine, diltiazem, and verapamil—at their physiological serum concentrations for 2 weeks. Without inducing cell death and damage to myofilament structure, CCBs elicited line-specific inhibition on calcium kinetics and contractility. While all 4 CCBs exerted similar inhibition on calcium kinetics, verapamil applied the strongest inhibition on cardiomyocyte contractile function. By profiling cardiomyocyte transcriptome after CCB treatment, we identified little overlap in their transcriptome signatures. Verapamil is the only inhibitor that reduced the expression of contraction-related genes, such as MYH (myosin heavy chain) and troponin I, consistent with its depressive effects on contractile function. The reduction of these contraction-related genes may also explain the responsiveness of patients with hypertrophic cardiomyopathy to verapamil in managing left ventricular outflow tract obstruction. Conclusions: This is the first study to identify the transcriptome signatures of different CCBs in human cardiomyocytes. The distinct gene expression patterns suggest that although the 4 inhibitors act on the same target, they may have distinct effects on normal cardiac cell physiology.

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Ouwendijk, Werner J. D., Alexander Choe, Maria A. Nagel, Don Gilden, Albert D. M. E. Osterhaus, Randall J. Cohrs, and Georges M. G. M. Verjans. "Restricted Varicella-Zoster Virus Transcription in Human Trigeminal Ganglia Obtained Soon after Death." Journal of Virology 86, no. 18 (June 27, 2012): 10203–6. http://dx.doi.org/10.1128/jvi.01331-12.

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We analyzed the varicella-zoster virus (VZV) transcriptome in 43 latently infected human trigeminal ganglia (TG) with postmortem intervals (PMIs) ranging from 3.7 to 24 h. Multiplex reverse transcriptase PCR (RT-PCR) revealed no VZV transcripts with a PMI of <9 h. Real-time PCR indicated a significant increase (P= 0.02) in VZV ORF63 transcript levels but not the virus DNA burden with longer PMI. Overall, both the breadth of the VZV transcriptome and the VZV ORF63 transcript levels in human cadaver TG increased with longer PMI.

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Kocabas, A. M., J. Crosby, P. J. Ross, H. H. Otu, Z. Beyhan, H. Can, W. L. Tam, et al. "The transcriptome of human oocytes." Proceedings of the National Academy of Sciences 103, no. 38 (September 12, 2006): 14027–32. http://dx.doi.org/10.1073/pnas.0603227103.

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Saito, Hirohisa, Toshiharu Nakajima, and Kenji Matsumoto. "Human Mast Cell Transcriptome Project." International Archives of Allergy and Immunology 125, no. 1 (2001): 1–8. http://dx.doi.org/10.1159/000053790.

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Gatherer, D., S. Seirafian, C. Cunningham, M. Holton, D. J. Dargan, K. Baluchova, R. D. Hector, et al. "High-resolution human cytomegalovirus transcriptome." Proceedings of the National Academy of Sciences 108, no. 49 (November 22, 2011): 19755–60. http://dx.doi.org/10.1073/pnas.1115861108.

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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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Zhang, Wen. "Advancements of transcriptome imputation and related transcriptome-wide association studies." Current Research in Biochemistry and Molecular Biology 1, no. 1 (September 2, 2019): 14–16. http://dx.doi.org/10.33702/crbmb.2019.1.1.4.

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Despite the progresses of genome-wide association studies (GWASs) in revealing genetic mechanisms of human complex traits, the basis through which most identified risk variants function are highly unknown and need further investigations as well as discoveries. Recent advancements of transcriptome predictions put the transcriptome-wide association studies (TWASs) forward into a new era. TWAS through imputed transcriptomes could discover more gene-trait associations and relevant joint-tissue TWAS via eQTL analysis provide insights into furthering elucidations about gene-level association studies in difficult-to-acquire tissues. This mini-review goes over the recent advancements of gene expression imputations as well as the gene-trait association studies, which highlight the importance of genetically regulated expression (GReX) in this area.

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Chehimi, Samar N., Richard C. Crist, and Benjamin C. Reiner. "Unraveling Psychiatric Disorders through Neural Single-Cell Transcriptomics Approaches." Genes 14, no. 3 (March 22, 2023): 771. http://dx.doi.org/10.3390/genes14030771.

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The development of single-cell and single-nucleus transcriptome technologies is enabling the unraveling of the molecular and cellular heterogeneity of psychiatric disorders. The complexity of the brain and the relationships between different brain regions can be better understood through the classification of individual cell populations based on their molecular markers and transcriptomic features. Analysis of these unique cell types can explain their involvement in the pathology of psychiatric disorders. Recent studies in both human and animal models have emphasized the importance of transcriptome analysis of neuronal cells in psychiatric disorders but also revealed critical roles for non-neuronal cells, such as oligodendrocytes and microglia. In this review, we update current findings on the brain transcriptome and explore molecular studies addressing transcriptomic alterations identified in human and animal models in depression and stress, neurodegenerative disorders (Parkinson’s and Alzheimer’s disease), schizophrenia, opioid use disorder, and alcohol and psychostimulant abuse. We also comment on potential future directions in single-cell and single-nucleus studies.

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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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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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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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Carrow, James K., Lauren M. Cross, Robert W. Reese, Manish K. Jaiswal, Carl A. Gregory, Roland Kaunas, Irtisha Singh, and Akhilesh K. Gaharwar. "Widespread changes in transcriptome profile of human mesenchymal stem cells induced by two-dimensional nanosilicates." Proceedings of the National Academy of Sciences 115, no. 17 (April 11, 2018): E3905—E3913. http://dx.doi.org/10.1073/pnas.1716164115.

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Two-dimensional nanomaterials, an ultrathin class of materials such as graphene, nanoclays, transition metal dichalcogenides (TMDs), and transition metal oxides (TMOs), have emerged as a new generation of materials due to their unique properties relative to macroscale counterparts. However, little is known about the transcriptome dynamics following exposure to these nanomaterials. Here, we investigate the interactions of 2D nanosilicates, a layered clay, with human mesenchymal stem cells (hMSCs) at the whole-transcriptome level by high-throughput sequencing (RNA-seq). Analysis of cell–nanosilicate interactions by monitoring changes in transcriptome profile uncovered key biophysical and biochemical cellular pathways triggered by nanosilicates. A widespread alteration of genes was observed due to nanosilicate exposure as more than 4,000 genes were differentially expressed. The change in mRNA expression levels revealed clathrin-mediated endocytosis of nanosilicates. Nanosilicate attachment to the cell membrane and subsequent cellular internalization activated stress-responsive pathways such as mitogen-activated protein kinase (MAPK), which subsequently directed hMSC differentiation toward osteogenic and chondrogenic lineages. This study provides transcriptomic insight on the role of surface-mediated cellular signaling triggered by nanomaterials and enables development of nanomaterials-based therapeutics for regenerative medicine. This approach in understanding nanomaterial–cell interactions illustrates how change in transcriptomic profile can predict downstream effects following nanomaterial treatment.

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Ferraro, Nicole M., Benjamin J. Strober, Jonah Einson, Nathan S. Abell, Francois Aguet, Alvaro N. Barbeira, Margot Brandt, et al. "Transcriptomic signatures across human tissues identify functional rare genetic variation." Science 369, no. 6509 (September 10, 2020): eaaz5900. http://dx.doi.org/10.1126/science.aaz5900.

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Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.

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Miles, Lindsay S., Nadia A. Ayoub, Jessica E. Garb, Robert A. Haney, and Brian C. Verrelli. "Ovarian Transcriptomic Analyses in the Urban Human Health Pest, the Western Black Widow Spider." Genes 11, no. 1 (January 12, 2020): 87. http://dx.doi.org/10.3390/genes11010087.

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Due to their abundance and ability to invade diverse environments, many arthropods have become pests of economic and health concern, especially in urban areas. Transcriptomic analyses of arthropod ovaries have provided insight into life history variation and fecundity, yet there are few studies in spiders despite their diversity within arthropods. Here, we generated a de novo ovarian transcriptome from 10 individuals of the western black widow spider (Latrodectus hesperus), a human health pest of high abundance in urban areas, to conduct comparative ovarian transcriptomic analyses. Biological processes enriched for metabolism—specifically purine, and thiamine metabolic pathways linked to oocyte development—were significantly abundant in L. hesperus. Functional and pathway annotations revealed overlap among diverse arachnid ovarian transcriptomes for highly-conserved genes and those linked to fecundity, such as oocyte maturation in vitellogenin and vitelline membrane outer layer proteins, hormones, and hormone receptors required for ovary development, and regulation of fertility-related genes. Comparative studies across arachnids are greatly needed to understand the evolutionary similarities of the spider ovary, and here, the identification of ovarian proteins in L. hesperus provides potential for understanding how increased fecundity is linked to the success of this urban pest.

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Vij, Shubha, Lai ZhenYang, Wong Pui Mun, Chak Li-Ling, Wang Yue, Chan Woon-Khiong, and Ariff Bongso. "The Human Embryonic Stem Cells Transcriptome: How Much Do We Know?" Open Biotechnology Journal 2, no. 1 (February 29, 2008): 56–62. http://dx.doi.org/10.2174/1874070700802010056.

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The establishment of human embryonic stem cell (hESC) lines in 1998 served to set the pace for understanding the molecular biology behind the two hallmark features of stem cells: self renewal and pluripotency. The excitement was generated in the hope that understanding the molecular biology of hESCs would provide a good model for studying early human development, disease and drug discovery and also hold the promise for providing a cure for degenerative human diseases. In spite of the large number of studies, the molecular basis of pluripotency has remained a matter of intrigue ever since the embryonic stem cells (ESCs) were first identified. A considerable percentage of these studies have been transcriptome-based. Interestingly, significant differences are seen not only between mouse and human ESC transcriptomes but also amongst the hESC studies. Nevertheless, a key set of pluripotency genes seem to be common, reinforcing the utility of transcriptome-based approaches in identifying the molecular basis of pluripotency in hESCs.

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Tang, Shizhen, Aron S. Buchman, Philip L. De Jager, David A. Bennett, Michael P. Epstein, and Jingjing Yang. "Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia." PLOS Genetics 17, no. 4 (April 2, 2021): e1009482. http://dx.doi.org/10.1371/journal.pgen.1009482.

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Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL’s estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer’s dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use.

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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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Pertea, Mihaela. "The Human Transcriptome: An Unfinished Story." Genes 3, no. 3 (June 29, 2012): 344–60. http://dx.doi.org/10.3390/genes3030344.

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Montague-Cardoso, Karli. "A brain-wide human microglial transcriptome." Nature Neuroscience 25, no. 2 (February 2022): 131. http://dx.doi.org/10.1038/s41593-022-01019-3.

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Wang, Yun, and Dimitris N. Tatakis. "Human gingiva transcriptome during wound healing." Journal of Clinical Periodontology 44, no. 4 (February 11, 2017): 394–402. http://dx.doi.org/10.1111/jcpe.12669.

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Kim, Jinsil, Keyan Zhao, Peng Jiang, Zhi-xiang Lu, Jinkai Wang, Jeffrey C. Murray, and Yi Xing. "Transcriptome landscape of the human placenta." BMC Genomics 13, no. 1 (2012): 115. http://dx.doi.org/10.1186/1471-2164-13-115.

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Cornforth, Daniel M., Justine L. Dees, Carolyn B. Ibberson, Holly K. Huse, Inger H. Mathiesen, Klaus Kirketerp-Møller, Randy D. Wolcott, Kendra P. Rumbaugh, Thomas Bjarnsholt, and Marvin Whiteley. "Pseudomonas aeruginosa transcriptome during human infection." Proceedings of the National Academy of Sciences 115, no. 22 (May 14, 2018): E5125—E5134. http://dx.doi.org/10.1073/pnas.1717525115.

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Laboratory experiments have uncovered many basic aspects of bacterial physiology and behavior. After the past century of mostly in vitro experiments, we now have detailed knowledge of bacterial behavior in standard laboratory conditions, but only a superficial understanding of bacterial functions and behaviors during human infection. It is well-known that the growth and behavior of bacteria are largely dictated by their environment, but how bacterial physiology differs in laboratory models compared with human infections is not known. To address this question, we compared the transcriptome of Pseudomonas aeruginosa during human infection to that of P. aeruginosa in a variety of laboratory conditions. Several pathways, including the bacterium’s primary quorum sensing system, had significantly lower expression in human infections than in many laboratory conditions. On the other hand, multiple genes known to confer antibiotic resistance had substantially higher expression in human infection than in laboratory conditions, potentially explaining why antibiotic resistance assays in the clinical laboratory frequently underestimate resistance in patients. Using a standard machine learning technique known as support vector machines, we identified a set of genes whose expression reliably distinguished in vitro conditions from human infections. Finally, we used these support vector machines with binary classification to force P. aeruginosa mouse infection transcriptomes to be classified as human or in vitro. Determining what differentiates our current models from clinical infections is important to better understand bacterial infections and will be necessary to create model systems that more accurately capture the biology of infection.

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Shi, L., Y. H. Lin, M. C. Sierant, F. Zhu, S. Cui, Y. Guan, M. A. Sartor, O. Tanabe, K. C. Lim, and J. D. Engel. "Developmental transcriptome analysis of human erythropoiesis." Human Molecular Genetics 23, no. 17 (April 29, 2014): 4528–42. http://dx.doi.org/10.1093/hmg/ddu167.

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Beyer, Marc, Michael R. Mallmann, Jia Xue, Andrea Staratschek-Jox, Daniela Vorholt, Wolfgang Krebs, Daniel Sommer, et al. "High-Resolution Transcriptome of Human Macrophages." PLoS ONE 7, no. 9 (September 21, 2012): e45466. http://dx.doi.org/10.1371/journal.pone.0045466.

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Bartel, Jörg, Jan Krumsiek, Katharina Schramm, Jerzy Adamski, Christian Gieger, Christian Herder, Maren Carstensen, et al. "The Human Blood Metabolome-Transcriptome Interface." PLOS Genetics 11, no. 6 (June 18, 2015): e1005274. http://dx.doi.org/10.1371/journal.pgen.1005274.

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FitzPatrick, D. R. "Transcriptome analysis of human autosomal trisomy." Human Molecular Genetics 11, no. 26 (December 15, 2002): 3249–56. http://dx.doi.org/10.1093/hmg/11.26.3249.

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Sabates-Bellver, J., L. G. Van der Flier, M. de Palo, E. Cattaneo, C. Maake, H. Rehrauer, E. Laczko, et al. "Transcriptome Profile of Human Colorectal Adenomas." Molecular Cancer Research 5, no. 12 (December 1, 2007): 1263–75. http://dx.doi.org/10.1158/1541-7786.mcr-07-0267.

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Jan, Sabrina Z., Tinke L. Vormer, Aldo Jongejan, Michael D. Röling, Sherman J. Silber, Dirk G. de Rooij, Geert Hamer, Sjoerd Repping, and Ans M. M. van Pelt. "Unraveling transcriptome dynamics in human spermatogenesis." Development 144, no. 20 (September 21, 2017): 3659–73. http://dx.doi.org/10.1242/dev.152413.

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Oh, Jung-Hwa, Jin Ok Yang, Yoonsoo Hahn, Mi-Rang Kim, Sang-Soon Byun, Yeo-Jin Jeon, Jeong-Min Kim, et al. "Transcriptome analysis of human gastric cancer." Mammalian Genome 16, no. 12 (December 2005): 942–54. http://dx.doi.org/10.1007/s00335-005-0075-2.

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Sahakyan, Anna, and Kathrin Plath. "Transcriptome Encyclopedia of Early Human Development." Cell 165, no. 4 (May 2016): 777–79. http://dx.doi.org/10.1016/j.cell.2016.04.042.

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Majewska, Marta, Aleksandra Lipka, Lukasz Paukszto, Jan Pawel Jastrzebski, Kamil Myszczynski, Marek Gowkielewicz, Marcin Jozwik, and Mariusz Krzysztof Majewski. "Transcriptome profile of the human placenta." Functional & Integrative Genomics 17, no. 5 (March 1, 2017): 551–63. http://dx.doi.org/10.1007/s10142-017-0555-y.

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Rau, Christoph D., Chen Gao, and Yibin Wang. "Deconvolution of the Human Endothelial Transcriptome." Cell Systems 3, no. 3 (September 2016): 218–20. http://dx.doi.org/10.1016/j.cels.2016.09.006.

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van Ruissen, Fred, Bastiaan J. H. Jansen, Gys J. de Jongh, Patrick L. J. M. Zeeuwen, and Joost Schalkwijk. "A Partial Transcriptome of Human Epidermis." Genomics 79, no. 5 (May 2002): 671–78. http://dx.doi.org/10.1006/geno.2002.6756.

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Camberos, Victor, Jonathan Baio, Ana Mandujano, Aida F. Martinez, Leonard Bailey, Nahidh Hasaniya, and Mary Kearns-Jonker. "The Impact of Spaceflight and Microgravity on the Human Islet-1+ Cardiovascular Progenitor Cell Transcriptome." International Journal of Molecular Sciences 22, no. 7 (March 30, 2021): 3577. http://dx.doi.org/10.3390/ijms22073577.

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Understanding the transcriptomic impact of microgravity and the spaceflight environment is relevant for future missions in space and microgravity-based applications designed to benefit life on Earth. Here, we investigated the transcriptome of adult and neonatal cardiovascular progenitors following culture aboard the International Space Station for 30 days and compared it to the transcriptome of clonally identical cells cultured on Earth. Cardiovascular progenitors acquire a gene expression profile representative of an early-stage, dedifferentiated, stem-like state, regardless of age. Signaling pathways that support cell proliferation and survival were induced by spaceflight along with transcripts related to cell cycle re-entry, cardiovascular development, and oxidative stress. These findings contribute new insight into the multifaceted influence of reduced gravitational environments.

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Silvestro, Serena, Luigi Chiricosta, Agnese Gugliandolo, Jacopo Pizzicannella, Francesca Diomede, Placido Bramanti, Oriana Trubiani, and Emanuela Mazzon. "Extracellular Vesicles Derived from Human Gingival Mesenchymal Stem Cells: A Transcriptomic Analysis." Genes 11, no. 2 (January 21, 2020): 118. http://dx.doi.org/10.3390/genes11020118.

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Human gingival mesenchymal stem cells (hGMSCs) have outstanding characteristics of proliferation and are able to differentiate into osteogenic, chondrogenic, adipogenic, and neurogenic cell lineages. The extracellular vesicles (EVs) secreted by hGMSCs contain proteins, lipids, mRNA and microRNA have emerged as important mediators of cell-to-cell communication. In this study, we analyzed the transcriptome of hGMSCs-derived EVs using Next Generation Sequencing (NGS). The functional evaluation of the transcriptome highlighted 26 structural protein classes and the presence of “non-coding RNAs”. Our results showed that EVs contain several growth factors such as Transforming Growth Factor-β (TGF-β), Fibroblast Growth Factor (FGF), and Vascular Endothelial Growth Factors (VEGF) implicated in osteoblast differentiation and in angiogenetic process. Furthermore, the transcriptomic analysis showed the presence of glial cell-derived neurotrophic factor (GDNF) family ligands and neurotrophins involved in neuronal development. The NGS analysis also identified the presence of several interleukins among which some with anti-inflammatory action. Moreover, the transcriptome profile of EVs contained members of the Wnt family, involved in several biological processes, such as cellular proliferation and tissue regeneration. In conclusion, the huge amount of growth factors included in the hGMSCs-derived EVs could make them a big resource in regenerative medicine.

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Ham, Seokjin, and Seung-Jae V. Lee. "Advances in transcriptome analysis of human brain aging." Experimental & Molecular Medicine 52, no. 11 (November 2020): 1787–97. http://dx.doi.org/10.1038/s12276-020-00522-6.

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AbstractAging is associated with gradual deterioration of physiological and biochemical functions, including cognitive decline. Transcriptome profiling of brain samples from individuals of varying ages has identified the whole-transcriptome changes that underlie age-associated cognitive declines. In this review, we discuss transcriptome-based research on human brain aging performed by using microarray and RNA sequencing analyses. Overall, decreased synaptic function and increased immune function are prevalent in most regions of the aged brain. Age-associated gene expression changes are also cell dependent and region dependent and are affected by genotype. In addition, the transcriptome changes that occur during brain aging include different splicing events, intersample heterogeneity, and altered levels of various types of noncoding RNAs. Establishing transcriptome-based hallmarks of human brain aging will improve the understanding of cognitive aging and neurodegenerative diseases and eventually lead to interventions that delay or prevent brain aging.

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Salafutdinov, Ilnur I., Dilara Z. Gatina, Maria I. Markelova, Ekaterina E. Garanina, Sergey Yu Malanin, Ilnaz M. Gazizov, Andrei A. Izmailov, et al. "A Biosafety Study of Human Umbilical Cord Blood Mononuclear Cells Transduced with Adenoviral Vector Carrying Human Vascular Endothelial Growth Factor cDNA In Vitro." Biomedicines 11, no. 7 (July 18, 2023): 2020. http://dx.doi.org/10.3390/biomedicines11072020.

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The biosafety of gene therapy remains a crucial issue for both the direct and cell-mediated delivery of recombinant cDNA encoding biologically active molecules for the pathogenetic correction of congenital or acquired disorders. The diversity of vector systems and cell carriers for the delivery of therapeutic genes revealed the difficulty of developing and implementing a safe and effective drug containing artificial genetic material for the treatment of human diseases in practical medicine. Therefore, in this study we assessed changes in the transcriptome and secretome of umbilical cord blood mononuclear cells (UCB-MCs) genetically modified using adenoviral vector (Ad5) carrying cDNA encoding human vascular endothelial growth factor (VEGF165) or reporter green fluorescent protein (GFP). A preliminary analysis of UCB-MCs transduced with Ad5-VEGF165 and Ad5-GFP with MOI of 10 showed efficient transgene expression in gene-modified UCB-MCs at mRNA and protein levels. The whole transcriptome sequencing of native UCB-MCs, UCB-MC+Ad5-VEGF165, and UCB-MC+Ad5-GFP demonstrated individual sample variability rather than the effect of Ad5 or the expression of recombinant vegf165 on UCB-MC transcriptomes. A multiplex secretome analysis indicated that neither the transduction of UCB-MCs with Ad5-GFP nor with Ad5-VEGF165 affects the secretion of the studied cytokines, chemokines, and growth factors by gene-modified cells. Here, we show that UCB-MCs transduced with Ad5 carrying cDNA encoding human VEGF165 efficiently express transgenes and preserve transcriptome and secretome patterns. This data demonstrates the biosafety of using UCB-MCs as cell carriers of therapeutic genes.

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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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Bono, Hidemasa, and Kiichi Hirota. "Meta-Analysis of Hypoxic Transcriptomes from Public Databases." Biomedicines 8, no. 1 (January 9, 2020): 10. http://dx.doi.org/10.3390/biomedicines8010010.

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Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

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Bray, Paul F., Paolo M. Fortina, Srikanth Nagalla, Kathleen Delgrosso, Adam Ertel, Isidore Rigoutsos, and Steven E. McKenzie. "High-Throughput Sequencing of the Human Platelet Transcriptome." Blood 116, no. 21 (November 19, 2010): 481. http://dx.doi.org/10.1182/blood.v116.21.481.481.

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Abstract Abstract 481 Most successful DNA-based genome wide association studies identify genomic regions, not genes themselves, and the findings are often devoid of context or mechanism. To identify the genetic basis of disease and disease traits, it is imperative to characterize the quantity and forms of the genes that are expressed in the tissue of interest. It is not feasible to use primary megakaryocytes to profile mRNA from large numbers of subjects, but platelet RNA is easy to obtain. Others and we have previously surveyed genome-wide platelet RNA expression using microarrays, an approach that has had a major impact on systems biology. However, microarrays have a number of limitations, including the use of probes only to known transcripts, a limited dynamic range for quantifying very low and high levels of transcripts, high background levels from cross-hybridization, and complicated normalization schemes to compare expression levels across experiments. Novel high-throughput sequencing approaches that overcome the limitations of microarrays have recently become available. RNA sequencing (RNAseq) has a remarkable ability to quantify mRNAs and provide information about transcript sequence variations, including single nucleotide changes and alternately spliced exons. The goal of these studies was to apply RNAseq to capture platelet transcriptome complexity. Total RNA was prepared using leukocyte-depleted platelets (LDP; less than 1 WBC per 5 million platelets) from 4 donors; 2 were studied twice each. Analysis of this material showed that compared to nucleated cells (HeLa, Meg-01), platelets had 50%-90% less ribosomal RNA, and high levels of messenger and small RNAs (Agilent 2100). The major reduction in platelet rRNA was confirmed by RNA gel analysis. The platelet whole transcriptomes were analyzed via the Applied Biosystems (AB) SOLiD 3Plus next generation sequencing protocols and platform. A typical sequence run generated ∼250 million reads of 50 bp each. We observed more than 30,000 independent platelet mRNA-coding transcripts from about 10,000 genes, demonstrating substantial numbers of variant isoforms. The increased sensitivity of RNAseq for low copy number is clear from these results, because prior platelet transcriptome studies using microarrays have identified only 1500–6000 expressed genes. As an example, the platelet-specific transcript, ITGA2B, showed very high copy number in platelets, but no expression in HeLa cells and modest expression in the megakaryocyte cell line, Meg-01. As is expected for RNA-Seq data, the density of mapped reads varies by exon and local sequence. We also provide examples of newly discovered SNPs that encode non-conservative amino acid changes (AKT2 1209A/T; PIK3CB 837C/G) and alter consensus exon/intron splice junction sites (P2YR12 nt 65 G/A). We have also identified a major difference in the ratio of two splice variants of the FcRg chain, 4:1 in one human platelet donor and 49:1 in another. In summary, we have demonstrated that RNAseq can accurately and sensitively determine the quantity and quality of variations in individual platelet transcriptomes. It appears that the the platelet transcriptome is approximately 10 times more complex than previously thought. The major relative reduction in platelet rRNA may be an advantage for characterizing functional platelet transcripts. RNAseq should permit better understanding of the molecular mechanisms regulating platelet physiology and identify novel genetic variants that contribute to disorders of thrombosis and hemostasis. Disclosures: No relevant conflicts of interest to declare.

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Journal articles on the topic 'HUMAN TRANSCRIPTOME'

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