scholarly journals RNA-Sequencing Profiling Analysis of Pericyte-Derived Extracellular Vesicle-Mimetic Nanovesicles-Regulated Genes in Primary Cultured Fibroblasts From Normal and Peyronie’s Disease Penile Tunica Albuginea

2020 ◽  
Author(s):  
Guo Nan Yin ◽  
Shuguang Piao ◽  
Zhiyong Liu ◽  
Lei Wang ◽  
Jiyeon Ock ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Target Genes ◽  
Tunica Albuginea ◽  
Global Gene Expression ◽  
Extracellular Vesicle ◽  
Sequencing Data ◽  
Rt Pcr ◽  
Cultured Fibroblasts ◽  
Primary Fibroblasts

Abstract BackgroundPeyronie’s disease (PD) is a severe fibrotic disease of the tunica albuginea that causes penis curvature and leads to penile pain, deformity, and erectile dysfunction. The role of pericytes in the pathogenesis of fibrosis has recently been determined. Extracellular vesicle (EV)-mimetic nanovesicles (NVs) have attracted attention regarding intercellular communication between cells in the field of fibrosis. However, the global gene expression of pericyte-derived EV-mimetic NVs (PC-NVs) in regulating fibrosis remains unknown. Here, we used RNA-sequencing technology to investigate the potential target genes regulated by PC-NVs in primary fibroblasts derived from human PD plaque. MethodsHuman primary fibroblasts derived from normal and PD patients was cultured and treated with cavernosum pericytes isolated extracellular vesicle (EV)-mimetic nanovesicles (NVs). A global gene expression RNA-sequencing assay was performed on normal fibroblasts, PD fibroblasts, and PD fibroblasts treated with PC-NVs. Reverse transcription polymerase chain reaction (RT-PCR) was used for sequencing data validation. ResultsA total of 4135 genes showed significantly differential expression in the normal fibroblasts, PD fibroblasts, and PD fibroblasts treated with PC-NVs. However, only 91 contra-regulated genes were detected among the three libraries. Furthermore, 20 contra-regulated genes were selected and 11 showed consistent changes in the RNA-sequencing assay, which were validated by RT-PCR. ConclusionThe gene expression profiling results suggested that these validated genes may be good targets for understanding potential mechanisms and conducting molecular studies into PD.

scholarly journals RNA-sequencing profiling analysis of pericyte-derived extracellular vesicle–mimetic nanovesicles-regulated genes in primary cultured fibroblasts from normal and Peyronie’s disease penile tunica albuginea

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guo Nan Yin ◽  
Shuguang Piao ◽  
Zhiyong Liu ◽  
Lei Wang ◽  
Jiyeon Ock ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Tunica Albuginea ◽  
Global Gene Expression ◽  
Extracellular Vesicle ◽  
Peyronie’S Disease ◽  
Rt Pcr ◽  
Cultured Fibroblasts ◽  
Primary Fibroblasts ◽  
Peyronie's Disease

Abstract Background Peyronie’s disease (PD) is a severe fibrotic disease of the tunica albuginea that causes penis curvature and leads to penile pain, deformity, and erectile dysfunction. The role of pericytes in the pathogenesis of fibrosis has recently been determined. Extracellular vesicle (EV)–mimetic nanovesicles (NVs) have attracted attention regarding intercellular communication between cells in the field of fibrosis. However, the global gene expression of pericyte-derived EV–mimetic NVs (PC–NVs) in regulating fibrosis remains unknown. Here, we used RNA-sequencing technology to investigate the potential target genes regulated by PC–NVs in primary fibroblasts derived from human PD plaque. Methods Human primary fibroblasts derived from normal and PD patients was cultured and treated with cavernosum pericytes isolated extracellular vesicle (EV)–mimetic nanovesicles (NVs). A global gene expression RNA-sequencing assay was performed on normal fibroblasts, PD fibroblasts, and PD fibroblasts treated with PC–NVs. Reverse transcription polymerase chain reaction (RT-PCR) was used for sequencing data validation. Results A total of 4135 genes showed significantly differential expression in the normal fibroblasts, PD fibroblasts, and PD fibroblasts treated with PC–NVs. However, only 91 contra-regulated genes were detected among the three libraries. Furthermore, 20 contra-regulated genes were selected and 11 showed consistent changes in the RNA-sequencing assay, which were validated by RT-PCR. Conclusion The gene expression profiling results suggested that these validated genes may be good targets for understanding potential mechanisms and conducting molecular studies into PD.

scholarly journals Global Gene Expression and Mutation Signatures Are Preserved in PDX Models of Pediatric AML and Aid Discovery of Targeted Therapy for Cases with CBFA2T3/GLIS2 Rearrangement

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3766-3766
Author(s):  
Mark Wunderlich ◽  
Jing Chen ◽  
Eric O'Brien ◽  
Nicole Manning ◽  
Christina Sexton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Targeted Therapies ◽  
Global Gene Expression ◽  
Specific Gene ◽  
Sequencing Data ◽  
Patient Sample ◽  
Nsg Mice ◽  
Pediatric Aml ◽  
Pdx Models

Therapies for pediatric acute myeloid leukemia (AML) remain unsatisfactory and generally do not incorporate molecularly-targeted agents aside from FLT3 inhibitors outside of the relapse setting. Patient-derived xenograft (PDX) models of AML are increasingly accessible for the preclinical evaluation of targeted therapies, though the degree to which these systems recapitulate the disease state as found in patients has not been well defined for AML. Gene expression profiling of patient blasts has been successfully used to discriminate distinct subtypes of AML, to uncover sub-type specific vulnerabilities, and to predict response to therapy and outcomes. We sought to systematically examine PDX models of pediatric AML for their ability to replicate global gene expression patterns and preserve mutational signatures found in patients. In addition, we conducted in-depth bioinformatic analyses of samples with cryptic CBA2T3-GLIS2 fusion generated by the inv(16)(p13.3q24.3) for identification of potential novel targeted therapies. We performed detailed analyses of RNA sequencing data from a diverse series of 24 pediatric AML PDX models established from samples obtained from patients with relapse and refractory disease. Initially we compared our PDX data against 49 selected relapse and refractory patient sample data files found in the NCI TARGET dataset of pediatric AML. When applying unsupervised hierarchical clustering to the PDX samples, we found that clustering was associated with MLL status. Clustering of the combined sets of samples by MLL status showed integration of samples according to mutation profile, regardless of data source (PDX or patient). The expression levels of all detectable transcripts were highly conserved between PDX and patient MLL-r samples. Separate analysis of each dataset yielded MLL specific gene lists that included a subset of overlapping genes which may point to a unique relapse and refractory pediatric MLL-r signature. This list contains several interesting new targets for further study. A subset of 12 PDX models were compared directly to the matched patient sample from which they were established. This analysis revealed strong similarity, with each PDX most closely related to its matched patient sample, suggesting retention of sample-specific gene expression in immune deficient mice. We set up our PDX models in NSG mice with transgenic expression of human myelo-supportive cytokines SCF, GM-CSF, and IL-3 in order to promote the most efficient and robust engraftment of precious patient material. In order to detect any skewing effects due to the host mouse strain, we compared NSGS PDX RNA sequencing data to 10 matched NSG PDX models. This comparison revealed consistent differences in only 9 transcripts, which were almost entirely related to increased JAK/STAT signaling and macrophage activation pathways in NSGS mice relative to NSG mice. Interestingly, during this analysis we observed a distinct PCA-driven clustering of a pair of PDX samples with previously clinically unidentified driver mutations. Reanalysis of the RNA sequencing data revealed evidence of a cryptic GLIS2 rearrangement (found in ~1% of pediatric AML cases) as the driver mutation, which was subsequently confirmed by RT-PCR in both samples. The unique CBFA2T3/GLIS2 RNA signature was mined to guide the composition of a focused 75-molecule in vitro drug screen against ex vivo PDX samples with an emphasis on the SHH, WNT, and BCL2 pathways. This screen identified the Wnt-C59 PORCN inhibitor as having specific activity against CBFA2T3/GLIS2+ AMLs. Further testing of C-59 in combinatorial studies revealed enhanced effects with the addition of the BCL2 inhibitor, venetoclax. In vivo experiments are currently underway to determine the pre-clinical efficacy of this novel combination. In summary, we found highly significant fidelity of gene expression in PDX models of relapse and refractory pediatric AML. Analysis of this dataset has led to several insights, including potential targeted therapies, highlighting how this system could be a valuable tool for discovery of novel targeted therapies, especially for very rare, distinct subtypes of disease. Disclosures Perentesis: Kurome Therapeutics: Consultancy.

scholarly journals Transcriptome RNA Sequencing Data Set of Gene Expression in Moraxella catarrhalis On- and Off-Phase Variants of the Type III DNA Methyltransferase ModM3

2020 ◽  
Vol 9 (14) ◽  
Author(s):  
Luke V. Blakeway ◽  
Aimee Tan ◽  
Ian R. Peak ◽  
John M. Atack ◽  
Kate L. Seib
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Moraxella Catarrhalis ◽  
Dna Methyltransferase ◽  
Global Gene Expression ◽  
Chronic Obstructive ◽  
Sequencing Data ◽  
Data Set ◽  
Obstructive Pulmonary Disease ◽  
Content Type

Moraxella catarrhalis is a leading bacterial cause of otitis media and exacerbations of chronic obstructive pulmonary disease. Here, we announce a transcriptome RNA sequencing data set detailing global gene expression in two M. catarrhalis CCRI-195ME variants with expression of the DNA methyltransferase ModM3 phase varied either on or off.

Artificial intelligence-powered spatial analysis of tumor infiltrating lymphocytes (TIL) to reflect target gene expressions of novel immuno-oncology agents.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14534-e14534
Author(s):  
Chan-Young Ock ◽  
Seunghwan Shin ◽  
Wonkyung Jung ◽  
Sangheon Ahn ◽  
Haejoon Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Artificial Intelligence ◽  
Spatial Analysis ◽  
Rna Sequencing ◽  
Target Gene ◽  
Target Genes ◽  
Checkpoint Inhibitors ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Gene Expressions

e14534 Background: Novel immuno-oncology (IO) agents are promising but showing their efficacy in early phase clinical trials has been challenging due to limited enrichment strategies using practical biomarker platforms. We hypothesize that an artificial intelligence (AI)-powered spatial analysis of TIL using practically feasible H&E slides, can reflect a specific target gene expression derived from RNA sequencing. This enhances its potential application in early development of novel IO agents. Methods: An AI-powered spatial TIL analyzer, namely Lunit SCOPE IO, was developed with data from 2.8 x 109 micrometer2 H&E-stained tissue regions and 5.9 x 106 TILs from 3,166 whole slide images of multiple cancer types, annotated by board-certified pathologists. Inflamed Score and Immune-Excluded Score was defined as the proportion of all tumor-containing 1 mm2-size tiles within a WSI classified as being of inflamed immune phenotype (high TIL density within cancer epithelium) and immune-excluded phenotype (low TIL density within cancer epithelium, but high TIL density within stroma), respectively. We used RNA sequencing data and H&E images from The Cancer Genome Atlas database, excluding those of mesenchymal origin (n = 7,467). Spearman's rank correlation between each gene expression and IS or IES, respectively, was calculated. Correlation coefficient > 0.2 and false discovery rate (FDR) < 1% was considered as a significant correlation. Results: In a total of 20,304 genes, 871 (4.3%) and 1,155 (5.7%) genes were significantly correlated with Inflamed Score (IS) and Immune-Excluded Score (IES), respectively. The IS was highly related to genes reflecting immune cytolytic activity and targets of approved immune checkpoint inhibitors (Table). Interestingly, it was also significantly correlated with target genes of novel IO such as TIGIT, LAG3, TIM3, IDO, Adenosine receptor A2A, OX40, ICOS, M-CSF, IL2, IL7, and IL12. Moreover, the IES was exclusively correlated with the target genes of CEACAM, TGFB, and IL1. Conclusions: Expression levels of novel I-O target genes are correlated with three scores derived from AI-powered TIL analysis using H&E slides, which can be easily applied to clinical research.[Table: see text]

scholarly journals Receptor-driven invasion profiles in diffuse intrinsic pontine glioma (DIPG)

2021 ◽  
Author(s):  
Anju Karki ◽  
Noah E Berlow ◽  
Jin-Ah Kim ◽  
Esther Hulleman ◽  
Qianqian Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Factor ◽  
Protein Expression ◽  
Cell Viability ◽  
Rna Sequencing ◽  
Cell Invasion ◽  
Growth Factor Receptor ◽  
Diffuse Intrinsic Pontine Glioma ◽  
Sequencing Data ◽  
Pontine Glioma

Abstract Background Diffuse intrinsic pontine glioma (DIPG) is a devastating pediatric cancer with unmet clinical need. DIPG is invasive in nature, where tumor cells interweave into the fiber nerve tracts of the pons making the tumor unresectable. Accordingly, novel approaches in combating the disease is of utmost importance and receptor-driven cell invasion in the context of DIPG is under-researched area. Here we investigated the impact on cell invasion mediated by PLEXINB1, PLEXINB2, platelet growth factor receptor (PDGFR)α, PDGFRβ, epithelial growth factor receptor (EGFR), activin receptor 1 (ACVR1), chemokine receptor 4 (CXCR4) and NOTCH1. Methods We used previously published RNA-sequencing data to measure gene expression of selected receptors in DIPG tumor tissue versus matched normal tissue controls (n=18). We assessed protein expression of the corresponding genes using DIPG cell culture models. Then, we performed cell viability and cell invasion assays of DIPG cells stimulated with chemoattractants/ligands. Results RNA-sequencing data showed increased gene expression of receptor genes such as PLEXINB2, PDGFRα, EGFR, ACVR1, CXCR4 and NOTCH1 in DIPG tumors compared to the control tissues. Representative DIPG cell lines demonstrated correspondingly increased protein expression levels of these genes. Cell viability assays showed minimal effects of growth factors/chemokines on tumor cell growth in most instances. Recombinant SEMA4C, SEM4D, PDGF-AA, PDGF-BB, ACVA, CXCL12 and DLL4 ligand stimulation altered invasion in DIPG cells. Conclusions We show that no single growth factor-ligand pair universally induces DIPG cell invasion. However, our results reveal a potential to create a composite of cytokines or anti-cytokines to modulate DIPG cell invasion.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

scholarly journals FgHtf1 Regulates Global Gene Expression towards Aerial Mycelium and Conidiophore Formation in the Cereal Fungal Pathogen Fusarium graminearum

2020 ◽  
Vol 86 (9) ◽  
Author(s):  
Gaili Fan ◽  
Huawei Zheng ◽  
Kai Zhang ◽  
Veena Devi Ganeshan ◽  
Stephen Obol Opiyo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Family ◽  
Fusarium Graminearum ◽  
Target Genes ◽  
Homeobox Gene ◽  
Global Gene Expression ◽  
Binding Motifs ◽  
Content Type ◽  
Aerial Growth

ABSTRACT The homeobox gene family of transcription factors (HTF) controls many developmental pathways and physiological processes in eukaryotes. We previously showed that a conserved HTF in the plant-pathogenic fungus Fusarium graminearum, Htf1 (FgHtf1), regulates conidium morphology in that organism. This study investigated the mechanism of FgHtf1-mediated regulation and identified putative FgHtf1 target genes by a chromatin immunoprecipitation assay combined with parallel DNA sequencing (ChIP-seq) and RNA sequencing. A total of 186 potential binding peaks, including 142 genes directly regulated by FgHtf1, were identified. Subsequent motif prediction analysis identified two DNA-binding motifs, TAAT and CTTGT. Among the FgHtf1 target genes were FgHTF1 itself and several important conidiation-related genes (e.g., FgCON7), the chitin synthase pathway genes, and the aurofusarin biosynthetic pathway genes. In addition, FgHtf1 may regulate the cAMP-protein kinase A (PKA)-Msn2/4 and Ca2+-calcineurin-Crz1 pathways. Taken together, these results suggest that, in addition to autoregulation, FgHtf1 also controls global gene expression and promotes a shift to aerial growth and conidiation in F. graminearum by activation of FgCON7 or other conidiation-related genes. IMPORTANCE The homeobox gene family of transcription factors is known to be involved in the development and conidiation of filamentous fungi. However, the regulatory mechanisms and downstream targets of homeobox genes remain unclear. FgHtf1 is a homeobox transcription factor that is required for phialide development and conidiogenesis in the plant pathogen F. graminearum. In this study, we identified FgHtf1-controlled target genes and binding motifs. We found that, besides autoregulation, FgHtf1 also controls global gene expression and promotes conidiation in F. graminearum by activation of genes necessary for aerial growth, FgCON7, and other conidiation-related genes.

scholarly journals LSTrAP-Crowd: Prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data

2020 ◽  
Author(s):  
Benedict Hew ◽  
Qiao Wen Tan ◽  
William Goh ◽  
Jonathan Wei Xiong Ng ◽  
Kenny Koh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Rna Sequencing ◽  
Gene Expression Data ◽  
Large Scale ◽  
Bacterial Resistance ◽  
Expression Data ◽  
Sequencing Data ◽  
Novel Proteins ◽  
Novel Antibiotics

AbstractBacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.

scholarly journals Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue

Circulation ◽  
2020 ◽  
Vol 142 (14) ◽  
pp. 1374-1388
Author(s):  
Yanming Li ◽  
Pingping Ren ◽  
Ashley Dawson ◽  
Hernan G. Vasquez ◽  
Waleed Ageedi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Aortic Wall ◽  
Genome Wide Association ◽  
Aortic Tissue ◽  
Sequencing Data ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Differential Gene

Background: Ascending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues. Methods: We performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies. Results: We identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene( ERG ) exerts an important role in maintaining normal aortic wall function. Conclusions: Our study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression.

130 A CATALOG OF REFERENCE GENES WITH HIGH, MEDIUM, AND LOW LEVELS OF EXPRESSION DURING BOVINE IN VIVO PRE-IMPLANTATION DEVELOPMENT

2017 ◽  
Vol 29 (1) ◽  
pp. 173
Author(s):  
Z. Jiang ◽  
J. Sun ◽  
S. Marjani ◽  
H. Dong ◽  
X. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Genes ◽  
Target Genes ◽  
Stable Expression ◽  
Bovine Embryo ◽  
Rna Seq ◽  
Rt Pcr ◽  
Data Set ◽  
Low Expression

Appropriate reference genes for accurate normalization in RT-PCR are essential for the study of gene expression. Ideal reference genes should not only have stable expression across stages of embryo development, but also be expressed at comparable levels to the target genes. Using RNA-seq data from in vivo-produced bovine oocytes and embryos from the 2-cell to blastocyst stage (Jiang et al., 2014 BMC Genomics 15, 756), we tried to establish a catalogue of all reference genes for RT-PCR analysis. One-way ANOVA generated 4055 genes that did not differ across stages. To reduce this list, we used the entire RNA-seq data set and first removed genes with a FPKM (fragments per kilobase of transcript per million mapped reads) of <1, and then rescaled each gene’s expression values within a range of 0 to 1. We subsequently calculated the expression variance for each gene across all stages. By assuming that the calculated variances follow a Gaussian distribution and that the majority of the genes do not have a stable expression level, a gene was classified as a reference if its variance significantly deviated (P < 0.05) from these assumptions. We identified 346 potential reference genes, all of which were among the candidates from the ANOVA analysis. We arbitrarily assigned genes in this list to high (FPKM ≥ 100), medium (10 < FPKM < 100), and low expression levels (FPKM ≤ 10), and 37, 154, and 155 genes, respectively, fell into these groups. Surprisingly, none of the commonly used reference genes, such as GAPDH, PPIA, ACTB, PRL15, GUSB, and H3F2A, were identified as being stably expressed across in vivo development. This is consistent with findings of prior RT-PCR studies (Robert et al. 2002 Biol. Reprod. 67, 1465–1472; Ross et al. 2010 Cell Reprogram. 12, 709–717). The following gene ontology terms were significantly enriched for the 346 genes: cell cycle, translation, transport, chromatin, cell division, and metabolic process, indicating that the early embryos maintained constant levels of genes involved in fundamental biological functions. Finally, we performed RT-PCR to validate the RNA-seq results using different bovine in vivo-derived oocytes and embryos (n = 3/stage). We successfully validated 10 selected genes, including those in the high (CS, PGD, and ACTR3), medium (CCT5, MRPL47, COG2, CRT9, and HELLS), and low expression groups (CDC23 and TTF1). In conclusion, we recommend the use of reference genes that are expressed at comparable levels to target genes. This study offers a useful resource to aid in the appropriate selection of reference genes, which will improve the accuracy of quantitative gene expression analyses across bovine embryo pre-implantation development.

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