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Tissue-Specific Differential Expression of Novel Genes and Long Intergenic Noncoding RNAs in Humans With Extreme Response to Evoked Endotoxemia.
Ferguson JF, Xue C, Gao Y, Tian T, Shi J, Zhang X, Wang Y, Li YD, Wei Z, Li M, Zhang H, Reilly MP
(2018) Circ Genom Precis Med 11: e001907
MeSH Terms: Adipose Tissue, Animals, Endotoxemia, Female, Gene Expression Regulation, Genome-Wide Association Study, Humans, Immunity, Innate, Inflammation, Male, Mice, Monocytes, RNA, Long Noncoding, RNA, Messenger, Sequence Analysis, RNA
Show Abstract · Added April 2, 2019
BACKGROUND - Cytokine responses to activation of innate immunity differ between individuals, yet the genomic and tissue-specific transcriptomic determinants of inflammatory responsiveness are not well understood. We hypothesized that tissue-specific mRNA and long intergenic noncoding RNA (lincRNA) induction differs between individuals with divergent evoked inflammatory responses.
METHODS - In the GENE Study (Genetics of Evoked Response to Niacin and Endotoxemia), we performed an inpatient endotoxin challenge (1 ng/kg lipopolysaccharide [LPS]) in healthy humans. We selected individuals in the top (high responders) and bottom (low responders) extremes of inflammatory responses and applied RNA sequencing to CD14 monocytes (N=15) and adipose tissue (N=25) before and after LPS administration.
RESULTS - Although only a small number of genes were differentially expressed at baseline, there were clear differences in the magnitude of the transcriptional response post-LPS between high and low responders, with a far greater number of genes differentially expressed by endotoxemia in high responders. Furthermore, tissue responses differed during inflammation, and we found a number of tissue-specific differentially expressed lincRNAs post-LPS, which we validated. Relative to nondifferentially expressed lincRNAs, differentially expressed lincRNAs were equally likely to be nonconserved as conserved between human and mouse, indicating that conservation is not a predictor of lincRNAs associated with human inflammatory pathophysiology. Differentially expressed genes also were enriched for signals with inflammatory and cardiometabolic disease in published genome-wide association studies. CTB-41I6.2 ( AC002091.1), a nonconserved human-specific lincRNA, is one of the top lincRNAs regulated by endotoxemia in monocytes, but not in adipose tissue. Knockdown experiments in THP-1 monocytes suggest that this lincRNA enhances LPS-induced interleukin 6 ( IL6) expression in monocytes, and we now refer to this as monocyte LPS-induced lincRNA regulator of IL6 ( MOLRIL6).
CONCLUSIONS - We highlight mRNAs and lincRNAs that represent novel candidates for modulation of innate immune and metabolic responses in humans.
CLINICAL TRIAL REGISTRATION - URL: https://www.clinicaltrials.gov . Unique identifier: NCT00953667.
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15 MeSH Terms
Pulmonary Vascular Platform Models the Effects of Flow and Pressure on Endothelial Dysfunction in Associated Pulmonary Arterial Hypertension.
D'Amico RW, Faley S, Shim HN, Prosser JR, Agrawal V, Bellan LM, West JD
(2018) Int J Mol Sci 19:
MeSH Terms: Animals, Bone Morphogenetic Protein Receptors, Type II, Cell Line, Disease Models, Animal, Endothelial Cells, Hypertension, Pulmonary, Mice, Sequence Analysis, RNA
Show Abstract · Added April 2, 2019
Endothelial dysfunction is a known consequence of bone morphogenetic protein type II receptor () mutations seen in pulmonary arterial hypertension (PAH). However, standard 2D cell culture models fail to mimic the mechanical environment seen in the pulmonary vasculature. Hydrogels have emerged as promising platforms for 3D disease modeling due to their tunable physical and biochemical properties. In order to recreate the mechanical stimuli seen in the pulmonary vasculature, we have created a novel 3D hydrogel-based pulmonary vasculature model ("artificial arteriole") that reproduces the pulsatile flow rates and pressures seen in the human lung. Using this platform, we studied both and WT endothelial cells to better understand how the addition of oscillatory flow and physiological pressure influenced gene expression, cell morphology, and cell permeability. The addition of oscillatory flow and pressure resulted in several gene expression changes in both WT and cells. However, for many pathways with relevance to PAH etiology, cells responded differently when compared to the WT cells. cells were also found not to elongate in the direction of flow, and instead remained stagnant in morphology despite mechanical stimuli. The increased permeability of the layer was successfully reproduced in our artificial arteriole, with the addition of flow and pressure not leading to significant changes in permeability. Our artificial arteriole is the first to model many mechanical properties seen in the lung. Its tunability enables several new opportunities to study the endothelium in pulmonary vascular disease with increased control over environmental parameters.
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Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients.
Kahles A, Lehmann KV, Toussaint NC, Hüser M, Stark SG, Sachsenberg T, Stegle O, Kohlbacher O, Sander C, Cancer Genome Atlas Research Network, Rätsch G
(2018) Cancer Cell 34: 211-224.e6
MeSH Terms: Alternative Splicing, Humans, Neoplasms, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sequence Analysis, RNA, Whole Exome Sequencing
Show Abstract · Added October 30, 2019
Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions ("neojunctions") in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders ("putative neoantigens").
Copyright © 2018 Elsevier Inc. All rights reserved.
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Transcriptional profiling of the ductus arteriosus: Comparison of rodent microarrays and human RNA sequencing.
Yarboro MT, Durbin MD, Herington JL, Shelton EL, Zhang T, Ebby CG, Stoller JZ, Clyman RI, Reese J
(2018) Semin Perinatol 42: 212-220
MeSH Terms: Animals, Animals, Newborn, Ductus Arteriosus, Embryo, Mammalian, Gene Expression Profiling, Gene Expression Regulation, Developmental, Genetic Association Studies, Humans, Microarray Analysis, Models, Animal, Rodentia, Sequence Analysis, RNA, Species Specificity, Vascular Patency
Show Abstract · Added November 26, 2018
DA closure is crucial for the transition from fetal to neonatal life. This closure is supported by changes to the DA's signaling and structural properties that distinguish it from neighboring vessels. Examining transcriptional differences between these vessels is key to identifying genes or pathways responsible for DA closure. Several microarray studies have explored the DA transcriptome in animal models but varied experimental designs have led to conflicting results. Thorough transcriptomic analysis of the human DA has yet to be performed. A clear picture of the DA transcriptome is key to guiding future research endeavors, both to allow more targeted treatments in the clinical setting, and to understand the basic biology of DA function. In this review, we use a cross-species cross-platform analysis to consider all available published rodent microarray data and novel human RNAseq data in order to provide high priority candidate genes for consideration in future DA studies.
Copyright © 2018 Elsevier Inc. All rights reserved.
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Single-Cell Transcriptomic Profiling of Pluripotent Stem Cell-Derived SCGB3A2+ Airway Epithelium.
McCauley KB, Alysandratos KD, Jacob A, Hawkins F, Caballero IS, Vedaie M, Yang W, Slovik KJ, Morley M, Carraro G, Kook S, Guttentag SH, Stripp BR, Morrisey EE, Kotton DN
(2018) Stem Cell Reports 10: 1579-1595
MeSH Terms: Animals, Cell Differentiation, Cell Line, Cell Lineage, Cell Plasticity, Epithelium, Gene Expression Profiling, Genes, Reporter, Humans, Induced Pluripotent Stem Cells, Kinetics, Lung, Mice, Secretoglobins, Sequence Analysis, RNA, Single-Cell Analysis, Solubility, Spheroids, Cellular, Time Factors, Transcriptome, Wnt Signaling Pathway
Show Abstract · Added April 1, 2019
Lung epithelial lineages have been difficult to maintain in pure form in vitro, and lineage-specific reporters have proven invaluable for monitoring their emergence from cultured pluripotent stem cells (PSCs). However, reporter constructs for tracking proximal airway lineages generated from PSCs have not been previously available, limiting the characterization of these cells. Here, we engineer mouse and human PSC lines carrying airway secretory lineage reporters that facilitate the tracking, purification, and profiling of this lung subtype. Through bulk and single-cell-based global transcriptomic profiling, we find PSC-derived airway secretory cells are susceptible to phenotypic plasticity exemplified by the tendency to co-express both a proximal airway secretory program as well as an alveolar type 2 cell program, which can be minimized by inhibiting endogenous Wnt signaling. Our results provide global profiles of engineered lung cell fates, a guide for improving their directed differentiation, and a human model of the developing airway.
Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
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21 MeSH Terms
A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples.
Chen H, Li C, Peng X, Zhou Z, Weinstein JN, Cancer Genome Atlas Research Network, Liang H
(2018) Cell 173: 386-399.e12
MeSH Terms: Aneuploidy, B7-H1 Antigen, Chromatin, Databases, Genetic, Enhancer Elements, Genetic, Gene Expression Regulation, Neoplastic, Humans, Immunotherapy, Neoplasms, Sequence Analysis, RNA, Survival Rate
Show Abstract · Added October 30, 2019
The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on "chromatin-state" to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Tuning Hsf1 levels drives distinct fungal morphogenetic programs with depletion impairing Hsp90 function and overexpression expanding the target space.
Veri AO, Miao Z, Shapiro RS, Tebbji F, O'Meara TR, Kim SH, Colazo J, Tan K, Vyas VK, Whiteway M, Robbins N, Wong KH, Cowen LE
(2018) PLoS Genet 14: e1007270
MeSH Terms: Blotting, Western, Candida albicans, Chromatin Immunoprecipitation, Genes, Fungal, HSP90 Heat-Shock Proteins, Heat Shock Transcription Factors, Morphogenesis, Oligonucleotide Array Sequence Analysis, Reverse Transcriptase Polymerase Chain Reaction, Sequence Analysis, RNA, Temperature, Virulence
Show Abstract · Added November 7, 2019
The capacity to respond to temperature fluctuations is critical for microorganisms to survive within mammalian hosts, and temperature modulates virulence traits of diverse pathogens. One key temperature-dependent virulence trait of the fungal pathogen Candida albicans is its ability to transition from yeast to filamentous growth, which is induced by environmental cues at host physiological temperature. A key regulator of temperature-dependent morphogenesis is the molecular chaperone Hsp90, which has complex functional relationships with the transcription factor Hsf1. Although Hsf1 controls global transcriptional remodeling in response to heat shock, its impact on morphogenesis remains unknown. Here, we establish an intriguing paradigm whereby overexpression or depletion of C. albicans HSF1 induces morphogenesis in the absence of external cues. HSF1 depletion compromises Hsp90 function, thereby driving filamentation. HSF1 overexpression does not impact Hsp90 function, but rather induces a dose-dependent expansion of Hsf1 direct targets that drives overexpression of positive regulators of filamentation, including Brg1 and Ume6, thereby bypassing the requirement for elevated temperature during morphogenesis. This work provides new insight into Hsf1-mediated environmentally contingent transcriptional control, implicates Hsf1 in regulation of a key virulence trait, and highlights fascinating biology whereby either overexpression or depletion of a single cellular regulator induces a profound developmental transition.
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Unsupervised Trajectory Analysis of Single-Cell RNA-Seq and Imaging Data Reveals Alternative Tuft Cell Origins in the Gut.
Herring CA, Banerjee A, McKinley ET, Simmons AJ, Ping J, Roland JT, Franklin JL, Liu Q, Gerdes MJ, Coffey RJ, Lau KS
(2018) Cell Syst 6: 37-51.e9
MeSH Terms: Algorithms, Animals, Basic Helix-Loop-Helix Transcription Factors, Cell Differentiation, Cell Lineage, Humans, Image Cytometry, Intestinal Mucosa, Intestine, Small, K562 Cells, Mice, Mice, Inbred C57BL, RNA, Sequence Analysis, RNA, Single-Cell Analysis
Show Abstract · Added April 3, 2018
Modern single-cell technologies allow multiplexed sampling of cellular states within a tissue. However, computational tools that can infer developmental cell-state transitions reproducibly from such single-cell data are lacking. Here, we introduce p-Creode, an unsupervised algorithm that produces multi-branching graphs from single-cell data, compares graphs with differing topologies, and infers a statistically robust hierarchy of cell-state transitions that define developmental trajectories. We have applied p-Creode to mass cytometry, multiplex immunofluorescence, and single-cell RNA-seq data. As a test case, we validate cell-state-transition trajectories predicted by p-Creode for intestinal tuft cells, a rare, chemosensory cell type. We clarify that tuft cells are specified outside of the Atoh1-dependent secretory lineage in the small intestine. However, p-Creode also predicts, and we confirm, that tuft cells arise from an alternative, Atoh1-driven developmental program in the colon. These studies introduce p-Creode as a reliable method for analyzing large datasets that depict branching transition trajectories.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
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Landscape of X chromosome inactivation across human tissues.
Tukiainen T, Villani AC, Yen A, Rivas MA, Marshall JL, Satija R, Aguirre M, Gauthier L, Fleharty M, Kirby A, Cummings BB, Castel SE, Karczewski KJ, Aguet F, Byrnes A, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Lappalainen T, Regev A, Ardlie KG, Hacohen N, MacArthur DG
(2017) Nature 550: 244-248
MeSH Terms: Chromosomes, Human, X, Female, Genes, X-Linked, Genome, Human, Genomics, Humans, Male, Organ Specificity, Phenotype, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome, X Chromosome Inactivation
Show Abstract · Added October 27, 2017
X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals. The extent to which XCI is shared between cells and tissues remains poorly characterized, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression and phenotypic traits. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.
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13 MeSH Terms
The impact of rare variation on gene expression across tissues.
Li X, Kim Y, Tsang EK, Davis JR, Damani FN, Chiang C, Hess GT, Zappala Z, Strober BJ, Scott AJ, Li A, Ganna A, Bassik MC, Merker JD, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Hall IM, Battle A, Montgomery SB
(2017) Nature 550: 239-243
MeSH Terms: Bayes Theorem, Female, Gene Expression Profiling, Genetic Variation, Genome, Human, Genomics, Genotype, Humans, Male, Models, Genetic, Organ Specificity, Sequence Analysis, RNA
Show Abstract · Added October 27, 2017
Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.
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12 MeSH Terms