scholarly journals Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression level with cell volume

2021 ◽  
Author(s):  
Jie Lin
Keyword(s):  
Gene Expression ◽  
Cell Volume ◽  
Direct Consequence ◽  
Rna Polymerases ◽  
Gene Expression Level ◽  
Expression Level ◽  
Expression Levels ◽  
Genes Expression ◽  
Biophysical Mechanism ◽  
Cycle Regulation

Many experiments have shown that most genes’ expression levels are typically proportional to cell volumes in growing cells. However, a finite number of genes often exhibit nonlinear scaling of expression levels with cell volume. Their corresponding mRNA and protein concentrations are therefore not constant as the cell volume increases. While these genes with changing concentrations often have important biological functions such as cell cycle regulation, the biophysical mechanism underlying the nonlinear scaling between the gene expression level and the cell volume is still unclear. In this manuscript, we show that the nonlinear scaling is, in fact, a direct consequence of heterogeneous recruitment abilities of promoters to RNA polymerases. Those genes with weaker (stronger) recruitment abilities compared with the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Our model makes predictions in agreement with experimental observations, including a correlation between the expression levels and nonlinear scaling degrees with cell volume among genes.

scholarly journals Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Qirun Wang ◽  
Jie Lin
Keyword(s):  
Gene Expression ◽  
Cell Volume ◽  
Direct Consequence ◽  
Rna Polymerases ◽  
Mrna Levels ◽  
Expression Levels ◽  
Promoter Sequences ◽  
Biophysical Mechanism ◽  
Expression Model ◽  
Cycle Regulation

AbstractWhile most genes’ expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae’s mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.

scholarly journals Lipid Productivity and Biosynthesis Genes Response of Indigenous Chlorella sp. T4 Strain under Different Nitrogen and Phosphorus Load

2021 ◽  
Author(s):  
S’fiso Thuthukani Gumbi ◽  
Ajit Kumar ◽  
Ademola Olufolahan Olaniran
Keyword(s):  
Gene Expression ◽  
Fatty Acid ◽  
Physiological Response ◽  
Biomass Yield ◽  
Biodiesel Production ◽  
Gene Expression Level ◽  
Expression Level ◽  
Nitrogen And Phosphorus ◽  
Expression Levels ◽  
Lipid Yield

Abstract Microalgae can synthesize and accumulate high neutral lipids upon exposure to abiotic stress such as nutrient starvation or limitation. In this study, indigenous microalgae Chlorella sp. T4 was cultivated in nitrogen and phosphorus under both limiting and replete conditions. Growth, lipid yield, fatty acid profiles and biosynthetic gene expression levels were determined to ascertain cell’s response under these conditions. An impaired cell growth was observed under nitrogen limiting condition, evident by the lowest biomass yield (0.58±0.03 g L−1) as revealed by low quantum efficiency of photosystem II (Fv/Fm) value and chlorophyll a content. An increase in lipid content yield was observed under nitrogen and phosphorus limiting conditions as compared to the control. Nutrient limiting conditions produced fatty acid methyl ester that is suitable for biodiesel production compared to the control (BG-11). Gene expression analysis using real time q-PCR for photosynthesis (rbcL) and lipid biosynthesis (accD, KAS-1, ω-6 FAD, ω-3 FAD) genes revealed different expression levels under both limiting and replete conditions. Under nutrient limiting conditions, increase in the expression of accD, KAS-1, ω-6 FAD and ω-3 FAD genes was observed, whereas a decrease in rbcL gene expression level was noted. A significant correlation could be drawn between the expression levels of the biosynthetic genes and growth rate, biomass yield, physiological response, lipid yield and fatty acid composition. These results provide an insight into the physiological response and gene expression level under different nutrient levels, which could be harnessed for future genetic engineering of Chlorella sp. T4 for improved lipid production.

Chromatin Signature and Transcription Factor Binding Provide a Predictive Basis for Understanding Plant Gene Expression

2019 ◽  
Vol 60 (7) ◽  
pp. 1471-1486 ◽  
Author(s):  
Zefeng Wu ◽  
Jing Tang ◽  
Junjie Zhuo ◽  
Yuhan Tian ◽  
Feiyang Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Histone Modifications ◽  
Gene Expression Level ◽  
Expression Level ◽  
Good Prediction ◽  
Chromatin Modifications ◽  
Chromatin Signature ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Chromatin accessibility and post-transcriptional histone modifications play important roles in gene expression regulation. However, little is known about the joint effect of multiple chromatin modifications on the gene expression level in plants, despite that the regulatory roles of individual histone marks such as H3K4me3 in gene expression have been well-documented. By using machine-learning methods, we systematically performed gene expression level prediction based on multiple chromatin modifications data in Arabidopsis and rice. We found that as few as four histone modifications were sufficient to yield good prediction performance, and H3K4me3 and H3K36me3 being the top two predictors with known functions related to transcriptional initiation and elongation, respectively. We demonstrated that the predictive powers differed between protein-coding and non-coding genes as well as between CpG-enriched and CpG-depleted genes. We also showed that the predictive model trained in one tissue or species could be applied to another tissue or species, suggesting shared underlying mechanisms. More interestingly, the gene expression levels of conserved orthologs are easier to predict than the species-specific genes. In addition, chromatin state of distal enhancers was moderately correlated to gene expression but was dispensable if given the chromatin features of the proximal regions of genes. We further extended the analysis to transcription factor (TF) binding data. Strikingly, the combinatorial effects of only a few TFs were roughly fit to gene expression levels in Arabidopsis. Overall, by using quantitative modeling, we provide a comprehensive and unbiased perspective on the epigenetic and TF-mediated regulation of gene expression in plants.

scholarly journals Multiparametric MRI Features Predict the SYP Gene Expression in Low-Grade Glioma Patients: A Machine Learning-Based Radiomics Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Zheng Xiao ◽  
Shun Yao ◽  
Zong-ming Wang ◽  
Di-min Zhu ◽  
Ya-nan Bie ◽  
...  
Keyword(s):  
Neural Network ◽  
Gene Expression ◽  
Survival Rate ◽  
Convolutional Neural Network ◽  
Multiparametric Mri ◽  
Low Grade Glioma ◽  
Gene Expression Level ◽  
Expression Level ◽  
Low Grade ◽  
Expression Levels

PurposeSynaptophysin (SYP) gene expression levels correlate with the survival rate of glioma patients. This study aimed to explore the feasibility of applying a multiparametric magnetic resonance imaging (MRI) radiomics model composed of a convolutional neural network to predict the SYP gene expression in patients with glioma.MethodUsing the TCGA database, we examined 614 patients diagnosed with glioma. First, the relationship between the SYP gene expression level and outcome of survival rate was investigated using partial correlation analysis. Then, 7266 patches were extracted from each of the 108 low-grade glioma patients who had available multiparametric MRI scans, which included preoperative T1-weighted images (T1WI), T2-weighted images (T2WI), and contrast-enhanced T1WI images in the TCIA database. Finally, a radiomics features-based model was built using a convolutional neural network (ConvNet), which can perform autonomous learning classification using a ROC curve, accuracy, recall rate, sensitivity, and specificity as evaluation indicators.ResultsThe expression level of SYP decreased with the increase in the tumor grade. With regard to grade II, grade III, and general patients, those with higher SYP expression levels had better survival rates. However, the SYP expression level did not show any significant association with the outcome in Level IV patients.ConclusionOur multiparametric MRI radiomics model constructed using ConvNet showed good performance in predicting the SYP gene expression level and prognosis in low-grade glioma patients.

The investigation of CD36 scavenger receptor and MSR1 scavenger receptor gene expression level in patients with atherosclerosis

2010 ◽  
Vol 27 ◽  
pp. S66
Author(s):  
M. Piechota ◽  
A. Banaszewska ◽  
E. Guzniczak ◽  
G. Rosinski ◽  
T. Siminiak ◽  
...  
Keyword(s):  
Gene Expression ◽  
Receptor Gene ◽  
Scavenger Receptor ◽  
Gene Expression Level ◽  
Expression Level ◽  
Receptor Gene Expression

scholarly journals The BIRC Family Genes Expression in Patients with Triple Negative Breast Cancer

2021 ◽  
Vol 22 (4) ◽  
pp. 1820
Author(s):  
Anna Makuch-Kocka ◽  
Janusz Kocki ◽  
Anna Brzozowska ◽  
Jacek Bogucki ◽  
Przemysław Kołodziej ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Clinical Data ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Lymphatic Vessels ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Cancer Tissue ◽  
Expression Levels

The BIRC (baculoviral IAP repeat-containing; BIRC) family genes encode for Inhibitor of Apoptosis (IAP) proteins. The dysregulation of the expression levels of the genes in question in cancer tissue as compared to normal tissue suggests that the apoptosis process in cancer cells was disturbed, which may be associated with the development and chemoresistance of triple negative breast cancer (TNBC). In our study, we determined the expression level of eight genes from the BIRC family using the Real-Time PCR method in patients with TNBC and compared the obtained results with clinical data. Additionally, using bioinformatics tools (Ualcan and The Breast Cancer Gene-Expression Miner v4.5 (bc-GenExMiner v4.5)), we compared our data with the data in the Cancer Genome Atlas (TCGA) database. We observed diverse expression pattern among the studied genes in breast cancer tissue. Comparing the expression level of the studied genes with the clinical data, we found that in patients diagnosed with breast cancer under the age of 50, the expression levels of all studied genes were higher compared to patients diagnosed after the age of 50. We observed that in patients with invasion of neoplastic cells into lymphatic vessels and fat tissue, the expression levels of BIRC family genes were lower compared to patients in whom these features were not noted. Statistically significant differences in gene expression were also noted in patients classified into three groups depending on the basis of the Scarff-Bloom and Richardson (SBR) Grading System.

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