scholarly journals Gene Expression Profile and Co-Expression Network of Pearl Gentian Grouper under Cold Stress by Integrating Illumina and PacBio Sequences

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1745
Author(s):  
Ben-Ben Miao ◽  
Su-Fang Niu ◽  
Ren-Xie Wu ◽  
Zhen-Bang Liang ◽  
Bao-Gui Tang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cold Stress ◽  
Differential Expression Analysis ◽  
Endocrine System ◽  
Control Group ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Cold Tolerant ◽  
Stress Signals ◽  
Membrane Changes

Pearl gentian grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) is a fish of high commercial value in the aquaculture industry in Asia. However, this hybrid fish is not cold-tolerant, and its molecular regulation mechanism underlying cold stress remains largely elusive. This study thus investigated the liver transcriptomic responses of pearl gentian grouper by comparing the gene expression of cold stress groups (20, 15, 12, and 12 °C for 6 h) with that of control group (25 °C) using PacBio SMRT-Seq and Illumina RNA-Seq technologies. In SMRT-Seq analysis, a total of 11,033 full-length transcripts were generated and used as reference sequences for further RNA-Seq analysis. In RNA-Seq analysis, 3271 differentially expressed genes (DEGs), two low-temperature specific modules (tan and blue modules), and two significantly expressed gene sets (profiles 0 and 19) were screened by differential expression analysis, weighted gene co-expression networks analysis (WGCNA), and short time-series expression miner (STEM), respectively. The intersection of the above analyses further revealed some key genes, such as PCK, ALDOB, FBP, G6pC, CPT1A, PPARα, SOCS3, PPP1CC, CYP2J, HMGCR, CDKN1B, and GADD45Bc. These genes were significantly enriched in carbohydrate metabolism, lipid metabolism, signal transduction, and endocrine system pathways. All these pathways were linked to biological functions relevant to cold adaptation, such as energy metabolism, stress-induced cell membrane changes, and transduction of stress signals. Taken together, our study explores an overall and complex regulation network of the functional genes in the liver of pearl gentian grouper, which could benefit the species in preventing damage caused by cold stress.

scholarly journals Integrative Analysis of Axolotl Gene Expression Data From Regenerative and Wound Healing Limb Tissues

2019 ◽  
Author(s):  
Mustafa Sibai ◽  
Cüneyd Parlayan ◽  
Pelin Tuğlu ◽  
Gürkan Öztürk ◽  
Turan Demircan
Keyword(s):  
Gene Expression ◽  
Wound Healing ◽  
Differential Expression Analysis ◽  
Limb Regeneration ◽  
Ambystoma Mexicanum ◽  
Integrative Analysis ◽  
Control Group ◽  
Rna Seq ◽  
Amputation Injury ◽  
Study Designs

ABSTRACTAxolotl (Ambystoma mexicanum) is a urodele amphibian endowed with remarkable regenerative capacities manifested in scarless wound healing and full restoration of amputated limbs. Several regenerative cues of the axolotl limb were successfully unraveled due to the advent of high-throughput technologies and their employment in tackling research questions on several OMICS levels. The field of regenerative biology and medicine has therefore utilized the axolotl as a major and powerful experimental model. Studies which have previously unraveled differentially expressed (DE) genes en masse in different phases of the axolotl limb regeneration have primarily used microarrays and RNA-Seq technologies. However, as different labs are conducting such experiments, sufficient consistency may be lacking due to statistical limitations arising from limited number of sample replicates as well as possible differences in study designs. This study, therefore, aims to bridge such gaps by performing an integrative analysis of publicly available microarray and RNA-Seq data from axolotl limb samples having comparable study designs. Three biological groups were conceived for the analysis; homeostatic tissues (control group), from amputation/injury timepoint up to around 50 hours post amputation (wound healing group), and from 50 hours to 28 days post amputation/injury (regenerative group). Integrative analysis was separately carried out on the selected microarray and RNA-Seq data from axolotl limb samples using the “merging” method. Differential expression analysis was separately implemented on the processed data from both technologies using the R/Bioconductor “limma” package. A total of 1254 genes (adjusted P < 0.01) were found DE in regenerative samples compared to the control, out of which 351 showed magnitudes of Log Fold Changes (LogFC) > 1 and were identified as the top DE genes from data of both technologies. Downstream analyses illustrated consistent correlations of the logFCs of DE genes distributed among the biological comparisons, within and between both technologies. Gene ontology annotations demonstrated concordance with the literature on the biological process involved in the axolotl limb regeneration. qPCR analysis validated the observed gene expression level differences between regenerative and control samples for a set of five genes. Future studies may benefit from the utilized concept and approach for enhanced statistical power and robust discovery of biomarkers of regeneration.

scholarly journals Cholesterol Transporters ABCA1 and ABCG1 Gene Expression in Peripheral Blood Mononuclear Cells in Patients with Metabolic Syndrome

Cholesterol ◽  
2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Zahra Tavoosi ◽  
Hemen Moradi-Sardareh ◽  
Massoud Saidijam ◽  
Reza Yadegarazari ◽  
Shiva Borzuei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Syndrome ◽  
Mononuclear Cells ◽  
Fasting Blood Glucose ◽  
Control Group ◽  
Regulation Mechanism ◽  
Healthy Individuals ◽  
Peripheral Blood Mononuclear ◽  
Significant Difference ◽  
Abca1 Expression

ABCA1 and ABCG1 genes encode the cholesterol transporter proteins that play a key role in cholesterol and phospholipids homeostasis. This study was aimed at evaluating and comparing ABCA1 and ABCG1 genes expression in metabolic syndrome patients and healthy individuals. This case-control study was performed on 36 patients with metabolic syndrome and the same number of healthy individuals in Hamadan (west of Iran) during 2013-2014. Total RNA was extracted from mononuclear cells and purified using RNeasy Mini Kit column. The expression of ABCA1 and ABCG1 genes was performed by qRT-PCR. Lipid profile and fasting blood glucose were measured using colorimetric procedures. ABCG1 expression in metabolic syndrome patients was significantly lower (about 75%) compared to that of control group, while for ABCA1 expression, there was no significant difference between the two studied groups. Comparison of other parameters such as HDL-C, FBS, BMI, waist circumference, and systolic and diastolic blood pressure between metabolic syndrome patients and healthy individuals showed significant differences (P<0.05). Decrease in ABCG1 expression in metabolic syndrome patients compared to healthy individuals suggests that hyperglycemia, related metabolites, and hyperlipidemia over the transporter capacity resulted in decreased expression of ABCG1. Absence of a significant change in ABCA1 gene expression between two groups can indicate a different regulation mechanism for ABCA1 expression.

scholarly journals Comparative RNA-Seq Analyses of Solenopsis japonica (Hymenoptera: Formicidae) Reveal Gene in Response to Cold Stress

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1610
Author(s):  
Mohammad Vatanparast ◽  
Youngjin Park
Keyword(s):  
Gene Expression ◽  
Cold Stress ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Predatory Behavior ◽  
P Value ◽  
Molecular Response ◽  
Rna Seq ◽  
Protein Database ◽  
Brood Chamber

Solenopsis japonica, as a fire ant species, shows some predatory behavior towards earthworms and woodlice, and preys on the larvae of other ant species by tunneling into a neighboring colony’s brood chamber. This study focused on the molecular response process and gene expression profiles of S. japonica to low (9 °C)-temperature stress in comparison with normal temperature (25 °C) conditions. A total of 89,657 unigenes (the clustered non-redundant transcripts that are filtered from the longest assembled contigs) were obtained, of which 32,782 were annotated in the NR (nonredundant protein) database with gene ontology (GO) terms, gene descriptions, and metabolic pathways. The results were 81 GO subgroups and 18 EggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups) keywords. Differentially expressed genes (DEGs) with log2fold change (FC) > 1 and log2FC < −1 with p-value ≤ 0.05 were screened for cold stress temperature. We found 215 unigenes up-regulated and 115 unigenes down-regulated. Comparing transcriptome profiles for differential gene expression resulted in various DE proteins and genes, including fatty acid synthases and lipid metabolism, which have previously been reported to be involved in cold resistance. We verified the RNA-seq data by qPCR on 20 up- and down-regulated DEGs. These findings facilitate the basis for the future understanding of the adaptation mechanisms of S. japonica and the molecular mechanisms underlying the response to low temperatures.

Abstract 545: Differential mRNA Expression is Influenced by Apolipoprotein A-I in Order to Promote Foam Cell Regression

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
Elisa C Maruko ◽  
Hao Xu ◽  
Sushma Kaul ◽  
Brian J Capaldo ◽  
Nathalie Pamir ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Analysis ◽  
Immune Cell ◽  
Foam Cell ◽  
Differential Expression Analysis ◽  
Ldl Receptor ◽  
Gene Set Enrichment Analysis ◽  
Control Group ◽  
Apolipoprotein A

Atherosclerosis is a disease of both lipids and inflammatory immune cells. More specifically, elevated plasma levels of low-density lipoproteins (LDL) leads to migration of circulating monocytes into the artery wall. Lipid loaded monocyte cells subsequently proliferate in the arterial walls becoming macrophage foam cells; a hallmark of atherosclerotic lesions. A proposed mechanism of the protective effects of high-density lipoprotein (HDL) is apolipoprotein A-I (apo A-I) acting as a mediator of cholesterol efflux and subsequent foam cell regression. To better understand the biological changes stimulated by apo A-I treatment, differential expression analysis of microarray data was performed on spleen cells from apo A-I treated mice. LDL receptor null (LDLr -/- ) and LDL receptor and apo A-I null (LDLr -/- , apoA-I -/- ) mice were fed a western diet consisting of 0.2% cholesterol and 42% of calories as fat for 12 weeks. After 6 weeks of diet, a subset of mice for each genotype was subcutaneously injected with 200 micrograms of apo A-I 3 times a week for the remaining 6 weeks. The control group mice were subcutaneously injected with 200 micrograms of saline or BSA. Spleen cell RNA was isolated, purified, and analyzed for differential expression analysis using Illumina BeadArray Microarray Technology Analysis. Individual gene expression analysis for LDLr -/- , apoA-I -/- apo A-I treated mice showed 281 significantly differentially expressed genes compared to BSA treated mice. LDLr -/- A-I treated mice had 1502. Of the significant genes, 189 intersected across both genotypes. LDLr -/- , apoA-I -/- A-I mice showed 73 up-regulated and 116 down-regulated genes. Similarly, LDLr -/- A-I mice had 71 up-regulated and 118 down-regulated. One-directional Gene Set Enrichment Analysis (GSEA) of LDLr -/- , apoA-I -/- A-I mice revealed 49 significant pathways while a total of 63 were found for LDLr -/- . Of these pathways, 21 were up-regulated and 13 were down-regulated in both genotypes. Eight of the top 10 most significant up-regulated pathways in both genotypes were immune cell related. Their functions involve receptor, adhesion, and chemokine signaling. Overall, preliminary analysis suggests A-I treatment induces similar gene expression changes across different genotypes.

scholarly journals Identifying inaccuracies in gene expression estimates from unstranded RNA-seq data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail Pomaznoy ◽  
Ashu Sethi ◽  
Jason Greenbaum ◽  
Bjoern Peters
Keyword(s):  
Gene Expression ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
Library Preparation ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Machine Learning Model ◽  
Specific Manner ◽  
Library Preparation Protocol

Abstract RNA-seq methods are widely utilized for transcriptomic profiling of biological samples. However, there are known caveats of this technology which can skew the gene expression estimates. Specifically, if the library preparation protocol does not retain RNA strand information then some genes can be erroneously quantitated. Although strand-specific protocols have been established, a significant portion of RNA-seq data is generated in non-strand-specific manner. We used a comprehensive stranded RNA-seq dataset of 15 blood cell types to identify genes for which expression would be erroneously estimated if strand information was not available. We found that about 10% of all genes and 2.5% of protein coding genes have a two-fold or higher difference in estimated expression when strand information of the reads was ignored. We used parameters of read alignments of these genes to construct a machine learning model that can identify which genes in an unstranded dataset might have incorrect expression estimates and which ones do not. We also show that differential expression analysis of genes with biased expression estimates in unstranded read data can be recovered by limiting the reads considered to those which span exonic boundaries. The resulting approach is implemented as a package available at https://github.com/mikpom/uslcount.

scholarly journals recount-brain: a curated repository of human brain RNA-seq datasets metadata

2019 ◽  
Author(s):  
Ashkaun Razmara ◽  
Shannon E. Ellis ◽  
Dustin J. Sokolowski ◽  
Sean Davis ◽  
Michael D. Wilson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Gene Expression Data ◽  
Differential Expression Analysis ◽  
Controlled Vocabulary ◽  
The Cancer Genome Atlas ◽  
Tissue Type ◽  
Expression Data ◽  
Rna Seq ◽  
Human Brain Tissue

AbstractThe usability of publicly-available gene expression data is often limited by the availability of high-quality, standardized biological phenotype and experimental condition information (“metadata”). We released the recount2 project, which involved re-processing ∼70,000 samples in the Sequencing Read Archive (SRA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) projects. While samples from the latter two projects are well-characterized with extensive metadata, the ∼50,000 RNA-seq samples from SRA in recount2 are inconsistently annotated with metadata. Tissue type, sex, and library type can be estimated from the RNA sequencing (RNA-seq) data itself. However, more detailed and harder to predict metadata, like age and diagnosis, must ideally be provided by labs that deposit the data.To facilitate more analyses within human brain tissue data, we have complemented phenotype predictions by manually constructing a uniformly-curated database of public RNA-seq samples present in SRA and recount2. We describe the reproducible curation process for constructing recount-brain that involves systematic review of the primary manuscript, which can serve as a guide to annotate other studies and tissues. We further expanded recount-brain by merging it with GTEx and TCGA brain samples as well as linking to controlled vocabulary terms for tissue, Brodmann area and disease. Furthermore, we illustrate how to integrate the sample metadata in recount-brain with the gene expression data in recount2 to perform differential expression analysis. We then provide three analysis examples involving modeling postmortem interval, glioblastoma, and meta-analyses across GTEx and TCGA. Overall, recount-brain facilitates expression analyses and improves their reproducibility as individual researchers do not have to manually curate the sample metadata. recount-brain is available via the add_metadata() function from the recount Bioconductor package at bioconductor.org/packages/recount.

scholarly journals ABioTrans: A Biostatistical tool for Transcriptomics Analysis

2019 ◽  
Author(s):  
Zou Yutong ◽  
Bui Thuy Tien ◽  
Kumar Selvarajoo
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Gene Expression Omnibus ◽  
Rna Seq ◽  
Distribution Fitting ◽  
Web Browser ◽  
Genome Wide ◽  
Data Files ◽  
R Packages

AbstractHere we report a bio-statistical/informatics tool, ABioTrans, developed in R for gene expression analysis. The tool allows the user to directly read RNA-Seq data files deposited in the Gene Expression Omnibus or GEO database. Operated using any web browser application, ABioTrans provides easy options for multiple statistical distribution fitting, Pearson and Spearman rank correlations, PCA, k-means and hierarchical clustering, differential expression analysis, Shannon entropy and noise (square of coefficient of variation) analyses, as well as Gene ontology classifications.Availability and implementationABioTrans is available at https://github.com/buithuytien/ABioTransOperating system(s): Platform independent (web browser)Programming language: R (R studio)Other requirements: Bioconductor genome wide annotation databases, R-packages (shiny, LSD, fitdistrplus, actuar, entropy, moments, RUVSeq, edgeR, DESeq2, NOISeq, AnnotationDbi, ComplexHeatmap, circlize, clusterProfiler, reshape2, DT, plotly, shinycssloaders, dplyr, ggplot2). These packages will automatically be installed when the ABioTrans.R is executed in R studio.No restriction of usage for non-academic.

scholarly journals The Methylation Patterns and Transcriptional Responses to Chilling Stress at the Seedling Stage in Rice

2019 ◽  
Vol 20 (20) ◽  
pp. 5089 ◽  
Author(s):  
Hui Guo ◽  
Tingkai Wu ◽  
Shuxing Li ◽  
Qiang He ◽  
Zhanlie Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Low Temperature ◽  
Cold Stress ◽  
Cold Tolerance ◽  
Temperature Stress ◽  
Chilling Stress ◽  
Low Temperature Stress ◽  
Expression Level ◽  
Altered Expression ◽  
Cold Tolerant

Chilling stress is considered the major abiotic stress affecting the growth, development, and yield of rice. To understand the transcriptomic responses and methylation regulation of rice in response to chilling stress, we analyzed a cold-tolerant variety of rice (Oryza sativa L. cv. P427). The physiological properties, transcriptome, and methylation of cold-tolerant P427 seedlings under low-temperature stress (2–3 °C) were investigated. We found that P427 exhibited enhanced tolerance to low temperature, likely via increasing antioxidant enzyme activity and promoting the accumulation of abscisic acid (ABA). The Methylated DNA Immunoprecipitation Sequencing (MeDIP-seq) data showed that the number of methylation-altered genes was highest in P427 (5496) and slightly lower in Nipponbare (Nip) and 9311 (4528 and 3341, respectively), and only 2.7% (292) of methylation genes were detected as common differentially methylated genes (DMGs) related to cold tolerance in the three varieties. Transcriptome analyses revealed that 1654 genes had specifically altered expression in P427 under cold stress. These genes mainly belonged to transcription factor families, such as Myeloblastosis (MYB), APETALA2/ethylene-responsive element binding proteins (AP2-EREBP), NAM-ATAF-CUC (NAC) and WRKY. Fifty-one genes showed simultaneous methylation and expression level changes. Quantitative RT-PCR (qRT-PCR) results showed that genes involved in the ICE (inducer of CBF expression)-CBF (C-repeat binding factor)—COR (cold-regulated) pathway were highly expressed under cold stress, including the WRKY genes. The homologous gene Os03g0610900 of the open stomatal 1 (OST1) in rice was obtained by evolutionary tree analysis. Methylation in Os03g0610900 gene promoter region decreased, and the expression level of Os03g0610900 increased, suggesting that cold stress may lead to demethylation and increased gene expression of Os03g0610900. The ICE-CBF-COR pathway plays a vital role in the cold tolerance of the rice cultivar P427. Overall, this study demonstrates the differences in methylation and gene expression levels of P427 in response to low-temperature stress, providing a foundation for further investigations of the relationship between environmental stress, DNA methylation, and gene expression in rice.

scholarly journals intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data

BMC Genomics ◽  
2020 ◽  
Vol 21 (S11) ◽  
Author(s):  
Yingying Cao ◽  
Simo Kitanovski ◽  
Daniel Hoffmann
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
High Throughput Sequencing ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
R Package ◽  
Integrative Approach ◽  
Integrated Analysis ◽  
Data Sets ◽  
Rna Seq

Abstract Background RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy. Results Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization. Conclusion intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.

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