Genetic control of global gene expression levels in the intestinal mucosa: a human twin study

2009 ◽  
Vol 38 (1) ◽  
pp. 73-79 ◽  
Author(s):  
Robert Häsler ◽  
Alexander Begun ◽  
Sandra Freitag-Wolf ◽  
Martin Kerick ◽  
Nancy Mah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mrna Expression ◽  
Genetic Control ◽  
Intestinal Mucosa ◽  
Expression Profiles ◽  
Global Gene Expression ◽  
Model Organisms ◽  
Expression Levels ◽  
Molecular Phylogenetic ◽  
Health And Disease

Phenotypic variation between individuals, such as different mRNA expression levels, is influenced by genetic and nongenetic factors. Although several studies have addressed the interplay between genotypes and expression profiles in various model organisms in the recent years, the detailed and relative contributions of genetic and nongenetic factors in regulating plasticity of gene expression in barrier organs (e.g., skin, gut), which are exposed to continuous environmental challenge, are still poorly understood. Here we systematically monitored the level of genetic control over genomewide mRNA expression profiles in the healthy intestinal mucosa of 10 monozygotic and 10 dizygotic human twin pairs with microarray analyses. Our results, which are supported by real-time PCR and analysis of molecular phylogenetic conservation, indicate that genes associated with energy metabolism and cell and tissue regeneration pathways are under strong genetic control. Conversely, genes associated with immune response seem to be mainly controlled by exogenous factors. Further insights into the relative extent of genetic and nongenetic determinants of transcriptomal profiles and their influence on physiological and pathophysiological mechanisms are crucial to understanding the key role played by gene-environment interactions in health and disease.

Gene expression profiles and tumor locations in colorectal cancer (left vs. right vs. rectum).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 3527-3527 ◽  
Author(s):  
Martin K. H. Maus ◽  
Diana L. Hanna ◽  
Craig Stephens ◽  
Peter Philipp Grimminger ◽  
Melinda Epstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Tumor Biology ◽  
Tumor Location ◽  
Genetic Profile ◽  
Mrna Levels ◽  
Mutation Status ◽  
Expression Levels ◽  
Genetic Profiles

3527 Background: Recent data suggests that CRC from different locations show distinct genetic profiles. Right-sided tumors have a worse prognosis and may have less benefit from targeted therapies. We investigated the tumor locations and genetic profiles (KRAS and BRAF mutation status and ERCC1, TS, EGFR and VEGFR2 mRNA expression) in 580 CRC tumors. Methods: FFPE tumor specimen from 580 patients with advanced CRC adenocarcinoma were microdissected and DNA and RNA were extracted. Specifically designed primers and probes were used to detect 7 different base substitutions in codon 12 and 13 of KRAS, V600E mutations in BRAF and the mRNA expression levels of ERCC1, TS, EGFR and VEGFR2 by RT-PCR. These values were analyzed according to tumor location (left vs. right vs. rectum). Results: BRAF mutations were significantly more common in the right colon (15%), followed by rectum (3.8%) and left colon (2.5%). KRAS mutations occurred at similar frequencies throughout the colon. Gene expression of ERCC1 was significantly higher in right-sided than left-sided colon tumors in KRAS wild-type colon cancers. The highest expression levels for all genes were seen in rectum. These differences reached significant levels for ERCC1 (rectum vs. right and rectum vs. left, p<0.001), TS (rectum vs. left, p<0.036) and VEGFR2 (rectum vs. right and rectum vs. left, p<0.001). Conclusions: Tumor location in CRC is associated with specific mutation and expression profiles. Differences in chemosensitivity may be explained by mutation status and mRNA levels in right vs. left CRC. Rectum cancers showed a distinct genetic profile when compared to colon which indicates different tumor biology and may be related to differences in the microflora.

scholarly journals Comparability of reference-based and reference-free transcriptome analysis approaches at the gene expression level

2021 ◽  
Vol 22 (S11) ◽  
Author(s):  
Sung-Gwon Lee ◽  
Dokyun Na ◽  
Chungoo Park
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Expression Profiles ◽  
Gene Families ◽  
Cell Types ◽  
Model Organisms ◽  
Expression Levels ◽  
Large Gene ◽  
Gene Expression Quantification ◽  
Gene Expression Levels

Abstract Background Lately, high-throughput RNA sequencing has been extensively used to elucidate the transcriptome landscape and dynamics of cell types of different species. In particular, for most non-model organisms lacking complete reference genomes with high-quality annotation of genetic information, reference-free (RF) de novo transcriptome analyses, rather than reference-based (RB) approaches, are widely used, and RF analyses have substantially contributed toward understanding the mechanisms regulating key biological processes and functions. To date, numerous bioinformatics studies have been conducted for assessing the workflow, production rate, and completeness of transcriptome assemblies within and between RF and RB datasets. However, the degree of consistency and variability of results obtained by analyzing gene expression levels through these two different approaches have not been adequately documented. Results In the present study, we evaluated the differences in expression profiles obtained with RF and RB approaches and revealed that the former tends to be satisfactorily replaced by the latter with respect to transcriptome repertoires, as well as from a gene expression quantification perspective. In addition, we urge cautious interpretation of these findings. Several genes that are lowly expressed, have long coding sequences, or belong to large gene families must be validated carefully, whenever gene expression levels are calculated using the RF method. Conclusions Our empirical results indicate important contributions toward addressing transcriptome-related biological questions in non-model organisms.

scholarly journals Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bing He ◽  
Ping Chen ◽  
Sonia Zambrano ◽  
Dina Dabaghie ◽  
Yizhou Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Kidney ◽  
Cell Types ◽  
Model Organisms ◽  
Mural Cell ◽  
Glomerular Cell ◽  
Individual Gene ◽  
The Individual

AbstractMolecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

scholarly journals Granulosa cells from human primordial and primary follicles show differential global gene expression profiles

2018 ◽  
Vol 33 (4) ◽  
pp. 666-679 ◽  
Author(s):  
E H Ernst ◽  
S Franks ◽  
K Hardy ◽  
P Villesen ◽  
K Lykke-Hartmann
Keyword(s):  
Gene Expression ◽  
Granulosa Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression

scholarly journals Dynamical consequences of regional heterogeneity in the brain’s transcriptional landscape

2020 ◽  
Author(s):  
Gustavo Deco ◽  
Kevin Aquino ◽  
Aurina Arnatkevičiūtė ◽  
Stuart Oldham ◽  
Kristina Sabaroedin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Brain Regions ◽  
Biophysical Model ◽  
Neuronal Dynamics ◽  
Regional Heterogeneity ◽  
Magnetic Resonance Imaging Mri

AbstractBrain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles and MRI-derived estimates of myeloarchitecture. We further show that regional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional activity timescales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptional data to constrain models of large-scale brain function.

scholarly journals Expression of mRNAs for Pro-and Anti-Apoptotic Factors in Granulosa Cells and Follicular Fluid of Women Undergoing in Vitro Fertilization. A Pilot Study

2021 ◽  
Author(s):  
Jozsef Bodis ◽  
Endre Sulyok ◽  
Akos Varnagy ◽  
Viktória Prémusz ◽  
Krisztina Godony ◽  
...  
Keyword(s):  
Gene Expression ◽  
In Vitro Fertilization ◽  
Mrna Expression ◽  
Granulosa Cells ◽  
Follicular Fluid ◽  
Vitro Fertilization ◽  
Expression Levels ◽  
The Impact ◽  
Apoptotic Factors

Abstract BackgroundThis observational clinical study evaluated the expression levels and predictive values of some apoptosis-related genes in granulosa cells (GCs) and follicular fluid (FF) of women undergoing in vitro fertilization (IVF).Methods GCs and FF were obtained at oocyte retrieval from 31 consecutive patients with heterogeneous infertility diagnosis (age: 34.3±5.8 years, body mass index: 24.02±3.12 kg/m2, duration of infertility: 4.2±2.1 years). mRNA expression of pro-apoptotic (BAX, CASP3, CASP8) and anti-apoptotic (BCL2, AMH, AMHR, FSHR, LHR, CYP19A1) factors was determined by quantitative RT-PCR using ROCHE LightCycler 480. Results No significant difference in GC or FF mRNA expression of pro- and anti-apoptotic factors could be demonstrated between IVF patients with (9 patients) or without (22 patients) clinical pregnancy. Each transcript investigated was detected in FF, but their levels were markedly reduced and independent of those in GCs. The number of retrieved oocytes was positively associated with GC AMHR (r=0.393, p=0.029), but the day of embryo transfer was negatively associated with GC LHR (r=-0.414, p=0.020) and GC FSHR transcripts (r=-0.535, p=0.002). When pregnancy positive group was analysed separately the impact of apoptosis- related gene expressions on some selected measures of IVF success could be observed. Strong positive relationship was found between gene expression levels of pro- and anti-apoptotic factors in GCs.ConclusionOur study provides only marginal evidences for the apoptosis dependence of IVF outcome and suggests that the apoptosis process induces adaptive increases of the anti-apoptotic gene expression to attenuate apoptosis and to protect cell survival.

scholarly journals Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Xiaofei Wang ◽  
Jie Qiao ◽  
Rongqi Wang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Risk Score ◽  
Expression Profiles ◽  
Univariate Analysis ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Expression Levels

Abstract The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

scholarly journals Early Response of CD8+ T Cells in COVID-19 Patients

2021 ◽  
Vol 11 (12) ◽  
pp. 1291
Author(s):  
Deni Ramljak ◽  
Martina Vukoja ◽  
Marina Curlin ◽  
Katarina Vukojevic ◽  
Maja Barbaric ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
T Cells ◽  
Mrna Expression ◽  
Cd8 T Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Effector Memory ◽  
Healthy Controls ◽  
Ifn Γ

Healthy and controlled immune response in COVID-19 is crucial for mild forms of the disease. Although CD8+ T cells play important role in this response, there is still a lack of studies showing the gene expression profiles in those cells at the beginning of the disease as potential predictors of more severe forms after the first week. We investigated a proportion of different subpopulations of CD8+ T cells and their gene expression patterns for cytotoxic proteins (perforin-1 (PRF1), granulysin (GNLY), granzyme B (GZMB), granzyme A (GZMA), granzyme K (GZMK)), cytokine interferon-γ (IFN-γ), and apoptotic protein Fas ligand (FASL) in CD8+ T cells from peripheral blood in first weeks of SARS-CoV-2 infection. Sixteen COVID-19 patients and nine healthy controls were included. The absolute counts of total lymphocytes (p = 0.007), CD3+ (p = 0.05), and CD8+ T cells (p = 0.01) in COVID-19 patients were significantly decreased compared to healthy controls. In COVID-19 patients in CD8+ T cell compartment, we observed lower frequency effector memory 1 (EM1) (p = 0.06) and effector memory 4 (EM4) (p < 0.001) CD8+ T cells. Higher mRNA expression of PRF1 (p = 0.05) and lower mRNA expression of FASL (p = 0.05) at the fifth day of the disease were found in COVID-19 patients compared to healthy controls. mRNA expression of PRF1 (p < 0.001) and IFN-γ (p < 0.001) was significantly downregulated in the first week of disease in COVID-19 patients who progressed to moderate and severe forms after the first week, compared to patients with mild symptoms during the entire disease course. GZMK (p < 0.01) and FASL (p < 0.01) mRNA expression was downregulated in all COVID-19 patients compared to healthy controls. Our results can lead to a better understanding of the inappropriate immune response of CD8+ T cells in SARS-CoV2 with the faster progression of the disease.

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