Differential Expression Ratio Research Articles

Changes in the proteome of Apis mellifera acutely exposed to sublethal dosage of glyphosate and imidacloprid

Uncontrolled use of pesticides has caused a dramatic reduction in the number of pollinators, including bees. Studies on the effects of pesticides on bees have reported effects on both metabolic and neurological levels under chronic exposure. In this study, variations in the differential expression of head and thorax–abdomen proteins in Africanized A. mellifera bees treated acutely with sublethal doses of glyphosate and imidacloprid were studied using a proteomic approach. A total of 92 proteins were detected, 49 of which were differentially expressed compared to those in the control group (47 downregulated and 2 upregulated). Protein interaction networks with differential protein expression ratios suggested that acute exposure of A. mellifera to sublethal doses of glyphosate could cause head damage, which is mainly associated with behavior and metabolism. Simultaneously, imidacloprid can cause damage associated with metabolism as well as, neuronal damage, cellular stress, and impairment of the detoxification system. Regarding the thorax–abdomen fractions, glyphosate could lead to cytoskeleton reorganization and a reduction in defense mechanisms, whereas imidacloprid could affect the coordination and impairment of the oxidative stress response.

Analysis of susceptibility genes and myocardial infarction risk correlation of ischemic cardiomyopathy based on bioinformatics.

BackgroundThe present study was to investigated differential expressed genes (GEGs) in ischemic cardiomyopathy (ICM), and to construct regulation networks, and to study the correlation between myocardial infarction risk.MethodsData sets were downloaded from the Gene Expression Omnibus (GEO) to screen out messenger RNA (mRNA) and long non-coding RNA (lncRNA) differentially expressed between ICM samples and normal samples. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Differentially expressed mRNA and lncRNA were analyzed, and bioinformatics methods were used to predict and analyze microRNA (miRNA), and a competing endogenous RNA (Hub gene) regulatory network was constructed. Using the Limma software package in R language, DEGs of ICM were screened with non-heart failure donors as the control group under the conditions that the differential expression ratio was not less than 2 times, and the corrected P value was <0.05. The ClusterProfiler software package was used for GO enrichment analysis and KEGG enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) 11.0 online database was used to screen key genes for protein-protein interaction (PPI) network analysis.ResultsThe GO function analysis and KEGG pathway analysis showed that the DEGs were significantly enriched in metabolic pathways, oxidative phosphorylation, extracellular matrix receptor interactions, and other pathways, and were closely related to fibrosis, collagen catabolic process, and inflammatory response function, and a Hub gene regulatory network related to ICM lncRNA was constructed. Bioinformatics methods were used to effectively analyze the DEGs of ICM, and the Hub gene regulatory network of ICM was successfully constructed.ConclusionsThis study identified a certain risk correlation between ICM susceptibility genes and myocardial infarction.

Fibrinogen isoforms as potential blood-based biomarkers of Alzheimer’s disease using a proteomics approach

Objective: Alzheimer’s disease (AD), the commonest form of dementia which is characterized by progressive decline in cognitive function, can only be definitively diagnosed after death. Although biomarkers may aid diagnosis, currently available AD biomarkers, which are predominantly based on cerebrospinal fluid and neuroimaging facilities, are either invasive or costly. Blood-based biomarkers for AD diagnosis are highly sought after due to its practicality at the clinic. This study was undertaken to determine the differential protein expression in plasma amongst Malaysian AD, mild cognitive impairment (MCI) and non-AD individuals. Methods: A proteomic approach which utilized two-dimensional differential in gel electrophoresis (2 D DIGE) was performed for blood samples from 15 AD, 14 MCI and 15 non-AD individuals. Results: Mass spectrometry (MS)-based protein identification via MALDI ToF/ToF showed that fibrinogen-β-chain (spot 64) and fibrinogen-γ-chain (spot 91) with differential expression ratio >1.5 were significantly upregulated (p < 0.05) in AD patients when compared to non-AD individuals. Further data analysis using Pearson correlation found that the upregulated fibrinogen-γ-chain was weakly but significantly (p < 0.05) and inversely correlated with cognitive decline. Conclusion: Fibrinogen isoforms may play important roles in the vascular pathology of AD as well as neuroinflammation. As such, fibrinogen appears to be a promising blood-based biomarker for AD. Further validation of the present findings in larger population is now warranted.

Mechanism of transcriptional regulation of Meox1 by transforming growth factor β (1) and its effect on cell migration of adult human dermal fibroblasts

Objective: To explore the transcriptional regulation mechanism of transforming growth factor β(1) (TGF-β(1)) on Meox1 and its effect on cell migration of adult human dermal fibroblasts (HDF-a). Methods: (1) HDF-a cells were cultured in RPMI 1640 complete medium (hereinafter referred to as routinely cultured). The cells were divided into TGF-β(1) stimulation group and blank control group. The cells in TGF-β(1) stimulation group were stimulated with 10 μL TGF-β(1) in the mass concentration of 1 mg/μL, while the cells in blank control group were stimulated with the equal volume of phosphate buffer solution. After 72 hours in culture, partial cells in both groups were collected for transcriptome sequencing. The genes with differential expression ratio greater than or equal to 2 and P 0.05); the enrichment of Smad4 protein on the promoter of Meox1 in the cells of empty plasmid group was similar to that of Smad4 OE group (t=0.60, P>0.05). (5) Twenty-four hours after scratching, the scratch healing width of cells in siRNA-Meox1 group was narrower than that of negative interference group, while that of Meox1 OE group was wider than that of empty plasmid group. After 24 hours in culture, the number of migration cells in negative interference group was significantly higher than that in siRNA-Meox1 group (t=9.12, P<0.01), and that in empty plasmid group was significantly lower than that in Meox1 OE group (t=8.99, P<0.01). (6) The expression of Meox1 protein in the scar tissue was significantly higher than that in normal skin of patients with hypertrophic scars. Conclusions: TGF-β(1) transcriptionally regulates Meox1 expression via Smad2/3 in HDF-a cells, thus promoting cell migration.

CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data

BackgroundThe Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information.ResultsWe implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer.ConclusionsCAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.

Differential expression of microRNAs in serum of severe burn patients and analysis of the signaling pathway at early stage

Objective: To explore differential expression of microRNAs in serum of patients with severe burn and analysis of the signaling pathway at early stage. Methods: In this study, we included three healthy adult volunteers and three patients with severe burn, conforming to the inclusion criteria and hospitalized in Tongren Hospital of Wuhan University & Wuhan Third Hospital in July 2015. Venous whole blood of 6 mL of each burn patient and healthy volunteer was collected at 24 to 48 h post injury of burn patients. The whole blood was divided into burn group and healthy control group. Whole blood of 2 mL of each one was used to determine white blood cell count and neutrophile granulocyte content. Serum was separated from the other whole blood of 4 mL of each one. Half of serum was used to determine content of blood glucose, total protein, and albumin; another half of serum was used to extract total RNA with Trizol method. The differentially expressed microRNA, with differential expression ratio larger than or equal to 1.500 between 2 groups, were screened by microRNA chip technique. Then cluster analysis and functional enrichment analysis of Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway were performed on the differentially expressed microRNAs. Data were processed with t test. Results: (1) Content of white blood cell count, neutrophile granulocyte of whole blood, and blood glucose of serum of patients in burn group was obviously higher than that in healthy control group (with t values from 4.27 to 7.83, P<0.05 or P<0.01). Content of total protein and albumin of serum of patients in burn group was significantly lower than that in healthy control group (with t values respectively -12.80 and -12.36, P values below 0.01). (2)Compared with those in serum of healthy control group, differential expression ratios of 48 microRNAs in serum of burn group were larger than 1.500, with 22 up-regulated microRNAs and 26 down-regulated microRNAs. MicroRNA expression profile in serum of burn group was different from that of healthy control group. (3)Functional enrichment analysis of KEGG signaling pathway showed that compared with those in serum of healthy control group, microRNAs of differential expression in serum of burn group took part in tumor transcription misregulation signaling pathway, tumor proteoglycan signaling pathway, long-term potentiation signaling pathway, tumor associated microRNAs signaling pathway, citrate cycle signaling pathway, tumor necrosis factor signaling pathway, focal adhesion signaling pathway, endocytosis signaling pathway, insulin secretion signaling pathway, and estrogen signaling pathway. Conclusions: MicroRNA expression profile in serum of patients with severe burn is different from that in serum of healthy adults. MicroRNAs of differential expression may take part in important pathophysiological process of energy metabolism, inflammatory response, and regulation of blood glucose at early stage of severe burn.

Abstract 2204: A proteomic landscape of diffuse-type gastric cancer

Abstract Gastric cancer is a heterogeneous disease characterized by poor clinical outcomes and limited targeted treatment options. Among them, diffuse-type gastric cancer (DGC) is the subtype with worst prognosis. Here we describe the first proteomic landscape of DGC. We carried out proteome profiling and targeted exome DNA sequencing of 84 DGC samples. We analyzed the 1,008 (168 x 6) raw files together for uniformed quality control and protein identification with 1% global protein false discovery rate (FDR), which resulted in the identification of 11,340 gene products (GPs). A SAM (significance analysis of microarray) analysis identified 1,641 proteins as differentially expressed between T (tumor) and N (nearby) with statistical significance (FDR q value&amp;lt;0.01 by SAM and differential expression ratio&amp;gt;0.5/ &amp;lt; -0.5), including 1,211 up-regulated and 430 down-regulated GPs. Gene Ontology annotation indicated that tumor proteomes were significantly enriched in cell cycle, DNA replication, checkpoint, E2F, WNT, p53 signaling, epithelial mesenchymal transition (EMT), and inflammation/cytokine-receptor interaction pathways, and the proteomes of the nearby tissues are enriched in metabolism pathways, such as fatty acid metabolism, oxidative phosphorylation, and amino acid metabolism. Notably, many gastric makers (ANXA10, VSIG1, CLDN18, CTSE, TFF2, MUC5AC and MUC6) and signature proteins for stomach functions, including digestion, absorption, secretion, and stomach acid generation (PGC, GIF, GAST, and ATP4A), were lost in tumors. Based on proteome profiling alone, DGC can be subtyped into 3 major classes (PX1-3) that exhibit distinct proteome features and correlate with distinct clinical outcomes (Gehan-Breslow-Wilcoxon P = 0.024). PX1 exhibits proteome stability and the best overall survival; PX2 exhibits dysregulation in DNA replication and cell cycle, and is most sensitive to chemotherapy; PX3 features hyper-activated immune response and is not responsive to chemotherapy. We identified seven-marker proteins that can stratify DGC patients into these three subtypes, opening a door for proteome subtyping in clinical application and intervention. Furthermore, we nominated drug target candidates taking into consideration both the altered DGC proteome and association data with patients’ overall survival. This study revealed the altered signaling pathways in DGC and demonstrated the advantage of proteomic approach in molecular subtyping of cancer. Citation Format: Sai Ge, Xia Xia, Chen Ding, Bei Zhen, Quan Zhou, Jinwen Feng, Jiajia Yuan, Rui Chen, Yumei Li, Zhongqi Ge, Jiafu Ji, Lianhai Zhang, Jiayuan Wang, Zhongwu Li, Yumei Lai, Ying Hu, Yanyan Li, Yilin Li, Jing Gao, Lin Chen, Jianming Xu, Chunchao Zhang, Sung Yun Jung, Mingwei Liu, Lei Song, Wanlin Liu, Gaigai Guo, Tongqing Gong, Yin Huang, Yang Qiu, Tieliu Shi, Weimin Zhu, Yi Wang, Fuchu He, Lin Shen, Jun Qin, CNHPP. A proteomic landscape of diffuse-type gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2204. doi:10.1158/1538-7445.AM2017-2204

Early Assessment of Colorectal Cancer by Quantifying Circulating Tumor Cells in Peripheral Blood: ECT2 in Diagnosis of Colorectal Cancer.

Circulating tumor cells (CTCs) in peripheral blood is an indication of poor prognosis for patients with different cancer types. However, most of the available technologies for detecting CTCs show low sensitivity and specificity. Therefore, we attempted to find an alternative marker for CTCs of colorectal cancer. We have directly extracted RNA from CTCs contained in 1.5 mL peripheral blood from 90 colorectal cancer patients and 151 healthy donors, and screened these samples for candidate marker genes by nested real-time quantitative polymerase chain reaction (PCR). From genes selected from a public database of microarray analyses, we successfully identified epithelial cell transforming sequence 2 oncogene (ECT2) as a gene that exhibits high differential expression ratios (p < 0.01). ECT2 displays good sensitivity and specificity, with an area under the curve (AUC) value of 0.821. This marker gene also has a high detection rate in patients with serum carcinoembryonic antigen (CEA) concentrations below the diagnostic threshold of 5 ng/mL. The expression of ECT2 can therefore serve as an alternative measurement that can compensate for the inadequacy of the current CEA test in the diagnosis and monitoring of colorectal cancer patients.

Systematic large-scale meta-analysis identifies a panel of two mRNAs as blood biomarkers for colorectal cancer detection.

Colorectal cancer (CRC) is the third most common cancer in the world. A significant survival rate is achieved if it is detected at an early stage. A whole blood screening test, without any attempt to isolate blood fractions, could be an important tool to improve early detection of colorectal cancer. We searched for candidate markers with a novel approach based on the Transcriptome Mapper (TRAM), aimed at identifying specific RNAs with the highest differential expression ratio between colorectal cancer tissue and normal blood samples. This tool permits a large-scale systematic meta-analysis of all available data obtained by microarray experiments. The targeting of RNA took into consideration that tumour phenotypic variation is associated with changes in the mRNA levels of genes regulating or affecting this variation.A real time quantitative reverse transcription polymerase chain reaction (qRT- PCR) was applied to the validation of candidate markers in the blood of 67 patients and 67 healthy controls. The expression of genes: TSPAN8, LGALS4, COL1A2 and CEACAM6 resulted as being statistically different.In particular ROC curves attested for TSPAN8 an AUC of 0.751 with a sensitivity of 83.6% and a specificity of 58.2% at a cut off of 10.85, while the panel of the two best genes showed an AUC of 0.861 and a sensitivity of 92.5% with a specificity of 67.2%.Our preliminary study on a total of 134 subjects showed promising results for a blood screening test to be validated in a larger cohort with the staging stratification and in patients with other gastrointestinal diseases.

Promising Role of Moderate Soil Drying and Subsequent Recovery Through Moderate Wetting at Grain-Filling Stage for Rice Yield Enhancement

The study was conducted at the grain-filling stage to elucidate the physiological and molecular mechanisms of the root to enhance yield under alternate wetting and drying (AWD) compared with conventional irrigation. Measurements of root dry weight (RDW), seed setting rate, total kernel weight, and grain yield were determined along with 2D electrophoresis to detect altered protein expression in response to moderate soil drying (MD) and the subsequent recovery phase as moderate wetting (MW) under AWD compared with continuous wetting under CI. We found significant enhancement in RDW as well as 14.30 % increase in inferior spikelets, seed setting and 10.32 g m−2 increase in final yield. Among the total 55 differentially expressed proteins, 26 proteins were differentially expressed under both MD treatment and MW treatment, whereas 14 proteins under MD and 15 proteins under MW showed distinct expression. Differentially expressed proteins were involved in redox homeostasis, signaling, defense, energy, photoassimilate remobilization and included 14-3-3 proteins, cysteine-rich receptor-like protein kinase, monodehydroascorbate reductase, ascorbate peroxidase, glutathione S-transferases, translationally controlled tumor protein, remorin C-terminal domain containing protein, protein disulfide isomerase, DnaK family protein, cysteine synthase, aminotransferase, phosphoglycerate mutase, pyruvate phosphate dikinase, ATP synthase, and abscisic acid stress ripening (ASR1). The differential expression ratio of the signaling, redox, and defense group proteins was almost the same under MD and MW. ABA signaling, amino acid synthesis, and N remobilization were upregulated under MD, and the enzymes involved in carbohydrate, energy, and transportation metabolism were upregulated under MW. In conclusion, at the rice grain-filling stage, AWD is a potential technique to trigger signaling and the enzymatic protein network for systematic senescence initiation, root enlargement for maximum nutrient uptake, and maximize photoassimilate remobilization for yield enhancement.

A novel differential diagnostic model for multiple primary lung cancer: Differentially-expressed gene analysis of multiple primary lung cancer and intrapulmonary metastasis.

The incidence of synchronous multiple primary lung cancer (MPLC) is increasing. However, present diagnostic methods are unable to satisfy the individualized treatment requirements of patients with MPLC. The present study aimed to establish a quantitative mathematical model and analyze its diagnostic value for distinguishing between MPLC and cases of the histologically similar disease, intrapulmonary metastasis (IPM). The sum value of the differential expression ratios of four proteins, namely p53, p16, p27 and c-erbB2, was evaluated by immunohistochemically-staining specimens of primary cancers, second separate cancers, metastatic lymph nodes and metastatic cancers. The sum value of the differential expression ratio of the four proteins from the primary tumor and the lymph-node metastasis or metastatic cancer was <90 in the 11 patients with a single metastatic cancer and in the 30 patients with lymph-node metastasis, but was >90 in the 14 patients with different histological types of MPLC. Therefore, a quantitative differentially-expressed gene mathematical model was established as follows: Sum of the differential expression ratios = p16T1 − T + p27T1 − T2 + C-erbB2T1 − T2 + p53T1 − T2, where T1 is the primary cancer and T2 is the lymph node metastasis, metastatic cancer or the second separate cancer. The quantitative differentially-expressed gene mathematical model is considered to be a useful tool for distinguishing between MPLC and IPM.

Functional study of miR-27a in human hepatic stellate cells by proteomic analysis: comprehensive view and a role in myogenic tans-differentiation.

We previous reported that miR-27a regulates lipid metabolism and cell proliferation during hepatic stellate cells (HSCs) activation. To further explore the biological function and underlying mechanisms of miR-27a in HSCs, global protein expression affected by overexpression of miR-27a in HSCs was analyzed by a cleavable isotope-coded affinity tags (cICAT) based comparative proteomic approach. In the present study, 1267 non-redundant proteins were identified with unique accession numbers (score ≥1.3, i.e. confidence ≥95%), among which 1171 were quantified and 149 proteins (12.72%) were differentially expressed with a differential expression ratio of 1.5. We found that up-regulated proteins by miR-27a mainly participate in cell proliferation and myogenesis, while down-regulated proteins were the key enzymes involved in de novo lipid synthesis. The expression of a group of six miR-27a regulated proteins was validated and the function of one miR-27a regulated protein was further validated. The results not only delineated the underlying mechanism of miR-27a in modulating fat metabolism and cell proliferation, but also revealed a novel role of miR-27a in promoting myogenic tans-differentiation during HSCs activation. This study also exemplified proteomics strategy as a powerful tool for the functional study of miRNA.

Editors' pick: transcriptomes of 1000 genomes.

Next generation sequencing (NGS) technologies facilitate massive human DNA sequence variation data to be produced in a remarkable manner and speed. The functional effects of these variants can now also be analyzed by high-throughput RNA sequencing (RNA-seq) of the transcriptome. Prior to RNA-seq, analysis of human gene expression was performed by expression arrays with more limited coverage. In the recent issue of Nature, Lappalainen et al.[1] have, for the first time, used the full capacity of RNA-seq to create the largest existing catalog of potential causative functional variants in the genome and to characterize transcriptome variation in human populations in a subset of individuals from the 1000 Genomes Project. They reported a deep analysis of high-quality mRNA and miRNA sequences from lymphoblast cell lines from > 450 individuals belonging to five populations (CEPH-CEU Europeans, Finns, British, Toscani Italians, and Yoruba from Nigeria). The authors addressed several questions with their dataset. First, they investigated human transcriptome variation at the population level, which can manifest in overall expression levels or in splicing (in one gene). In a genome-wide perspective, Lappalainen et al. showed that population differences account for about 3% of the total variation, but they also identified 263–4.379 genes with differential expression and/or transcript ratios between population pairs. In the pairwise analysis, they observed something interesting: the African-European population pairs had a higher contribution of genes with differential splicing (75 to 85%) than the European populations had between each other (6 to 40%). Although this phenomenon has not been previously observed in humans, it is in agreement with phylogenetic differences between species being better captured by splicing rather than expression levels. Lappalainen et al. analyzed 644 autosomal miRNAs that could be quantified from > 50% of the individuals. Sixty of those miRNAs (9.3%) had significant cis-expression QTLs (eQTLs) for miRNA expression levels, indicating that genetic effects on miRNA expression are more widespread than had been known. The authors also provide evidence for the existence of feedback loops for mRNA and miRNA genes to have an effect on each other’s expression supporting the idea that miRNAs offer robustness in the expression programs. Altogether, Lappalainen et al. have produced the largest and most diverse catalogue of cis-regulatory variants in a single tissue to date. The authors used their data to analyze the functional properties of the newly found set of regulatory variants and transcriptome effects of protein-truncating loss-of-function variants. This collaborative effort further used the potential of RNA-seq to discover regulatory variants that affect not only expression levels but also splicing. Of the 7.825 genes with expression QTLs (eQTLs), 34% have a second, independent eQTL for any of their exons. The authors concluded that in the transcriptome there exists allelic heterogeneity for regulatory effects on a single gene and independence of exons within the same gene. As an ancillary benefit, the authors demonstrated that RNA-seq data is consistent even when produced in different laboratories, with more detailed analysis in a companion paper in Nature Biotechnology[2]. Namely, in the replicate analyses of RNA-seq data from seven laboratories, there was a smaller amount of variation among the laboratories than seen among the individuals. The study is a great example of integration of genomic sequencing and cellular phenotype data. Obviously, the amount of data produced in this study is enormous, and it can easily be expected that the data will also be used to support other pivotal work. Meanwhile, it will take some time to completely digest the magnitude of data and appreciate the impact it will have on functional genomics.

Expression of alternatively spliced variants of MAP2K4 gene in rheumatoid arthritis

Backgroundand objectivesMAP2K4 encodes a mitogen activated protein kinase kinase 4 (MKK4), important for optimal activation of JNK1-3 and p38 – the two members of the MAP kinase family previously implicated...

Chronic psychosocial stressors and salivary biomarkers in emerging adults

We investigated whole saliva as a source of biomarkers to distinguish individuals who have, and who have not, been chronically exposed to severe and threatening life difficulties. We evaluated RNA and DNA metrics, expression of 37 candidate genes, and cortisol release in response to the Trier Social Stress Test, as well as clinical characteristics, from 48 individuals stratified on chronic exposure to psychosocial stressors within the last year as measured by the Life Events and Difficulties Schedule. Candidate genes were selected based on their differential gene expression ratio in circulating monocytes from a published genome-wide analysis of adults experiencing different levels of exposure to a chronic stressor. In univariate analyses, we observed significantly decreased RNA integrity (RIN) score (P = 0.04), and reduced expression of glucocorticoid receptor-regulated genes (Ps < 0.05) in whole saliva RNA from individuals exposed to chronic stressors, as compared to those with no exposure. In those exposed, we observed significantly decreased BMI (P < 0.001), increased ever-smoking and increased lifetime alcohol abuse or dependence (P ≤ 0.03), and a reduction of cortisol release. In post hoc multivariate analyses including clinical and biospecimen-derived variables, we consistently observed significantly decreased expression of IL8 (Ps<0.05) in individuals exposed, with no significant association to RIN score. Alcohol use disorders, tobacco use, a reduced acute stress response and decreased salivary IL8 gene expression characterize emerging adults chronically exposed to severe and threatening psychosocial stressors.

Transcriptomic Analysis in Diabetic Nephropathy of Streptozotocin-Induced Diabetic Rats

Diabetic nephropathy (DN) is a major complication of diabetes and is caused by an imbalance in the expression of certain genes that activate or inhibit vital cellular functions of kidney. Despite several recent advances, the pathogenesis of DN remains far from clear, suggesting the need to carry out studies identifying molecular aspects, such as gene expression, that could play a key role in the development of DN. There are several techniques to analyze transcriptome in living organisms. In this study, the suppression subtractive hybridization (SSH) method was used to generate up- and down-regulated subtracted cDNA libraries in the kidney of streptozotocin (STZ)-induced diabetic rats. Northern-blot analysis was used to confirm differential expression ratios from the obtained SSH clones to identify genes related to DN. 400 unique SSH clones were randomly chosen from the two subtraction libraries (200 of each) and verified as differentially expressed. According to blast screening and functional annotation, 20.2% and 20.9% of genes were related to metabolism proteins, 9% and 3.6% to transporters and channels, 16% and 6.3% to transcription factors, 19% and 17.2% to hypothetical proteins, and finally 24.1 and 17.2% to unknown genes, from the down- and up-regulated libraries, respectively. The down- and up-regulated cDNA libraries differentially expressed in the kidney of STZ diabetic rats have been successfully constructed and some identified genes could be highly important in DN.

Relationships between differential gene expression and heterosis in cotton hybrids developed from the foundation parent CRI-12 and its pedigree-derived lines

CRI-12, an Upland cotton variety with high yield, elite fiber quality and disease resistance, is further characterized by its high heritability, combining ability and genetic stability. CRI-12 and its pedigree-derived lines were used to develop increased heterosis cotton hybrids, including CRI-28, CRI-29, XZM 2 and Jimian18. CRI-12 was chosen as the cotton foundation parent and analyzed by gene differential expressions between hybrids and their corresponding parents at seedling, squaring and flowering stages. The following approaches were considered the most viable candidates to elucidate the molecular basis of CRI-12: cDNA-amplified fragment length polymorphisms (cDNA-AFLPs), gene differential expression ratios, and vegetative growth heterosis and yield heterosis for correlation analysis. The results indicated that CRI-12 plays a predominant role in vegetative heterosis in CRI-28, CRI-29 and Jimian18 hybrids at the seedling and squaring stages; the percentage of dominant expression in single parents was greater than other patterns; downregulated expression in single parents was higher than upregulated expression in hybrids, and downregulated expression in hybrids was the lowest of the four patterns in the three growth stage cumulative totals. The gene differential expression ratio of hybrids and parents varied for the three growth stages, suggesting gene differential expression changes over time. Further analysis of differential gene expression ratios, vegetative growth and yield heterosis correlation revealed upregulated expression in hybrids were correlated with vegetative heterosis at the seedling and squaring stages, which play an important role in yield heterosis at the flowering stage. Downregulated expression in the maternal parent (CRI-12 and its pedigree-derived lines) suggested benefits in vegetative heterosis at the squaring stage, but a possible hybrid yield decrease at the flowering stage. These results provided evidence that CRI-12 and its pedigree-derived lines express genes integral for heterosis in CRI-28, CRI-29 and Jimian18.

Increasing Alternative Promoter Repertories Is Positively Associated with Differential Expression and Disease Susceptibility

BackgroundAlternative Promoter (AP) usages have been shown to enable diversified transcriptional regulation of individual gene in a context-specific (e.g., pathway, cell lineage, tissue type, and development stage et. ac.) way. Aberrant uses of APs have been directly linked to mechanism of certain human diseases. However, whether or not there exists a general link between a gene's AP repertoire and its expression diversity is currently unknown. The general relation between a gene's AP repertoire and its disease susceptibility also remains largely unexplored.Methodology/Principal FindingsBased on the differential expression ratio inferred from all human microarray data in NCBI GEO and the list of disease genes curated in public repositories, we systemically analyzed the general relation of AP repertoire with expression diversity and disease susceptibility. We found that genes with APs are more likely to be differentially expressed and/or disease associated than those with Single Promoter (SP), and genes with more APs are more likely differentially expressed and disease susceptible than those with less APs. Further analysis showed that genes with increased number of APs tend to have increased length in all aspects of gene structure including 3′ UTR, be associated with increased duplicability, and have increased connectivity in protein-protein interaction network.ConclusionsOur genome-wide analysis provided evidences that increasing alternative promoter repertories is positively associated with differential expression and disease susceptibility.

Extent of differential allelic expression of candidate breast cancer genes is similar in blood and breast

IntroductionNormal gene expression variation is thought to play a central role in inter-individual variation and susceptibility to disease. Regulatory polymorphisms in cis-acting elements result in the unequal expression of alleles. Differential allelic expression (DAE) in heterozygote individuals could be used to develop a new approach to discover regulatory breast cancer susceptibility loci. As access to large numbers of fresh breast tissue to perform such studies is difficult, a suitable surrogate test tissue must be identified for future studies.MethodsWe measured differential allelic expression of 12 candidate genes possibly related to breast cancer susceptibility (BRCA1, BRCA2, C1qA, CCND3, EMSY, GPX1, GPX4, MLH3, MTHFR, NBS1, TP53 and TRXR2) in breast tissue (n = 40) and fresh blood (n = 170) of healthy individuals and EBV-transformed lymphoblastoid cells (n = 19). Differential allelic expression ratios were determined by Taqman assay. Ratio distributions were compared using t-test and Wilcoxon rank sum test, for mean ratios and variances respectively.ResultsWe show that differential allelic expression is common among these 12 candidate genes and is comparable between breast and blood (fresh and transformed lymphoblasts) in a significant proportion of them. We found that eight out of nine genes with DAE in breast and fresh blood were comparable, as were 10 out of 11 genes between breast and transformed lymphoblasts.ConclusionsOur findings support the use of differential allelic expression in blood as a surrogate for breast tissue in future studies on predisposition to breast cancer.

Methods for combining peptide intensities to estimate relative protein abundance

Labeling techniques are being used increasingly to estimate relative protein abundances in quantitative proteomic studies. These techniques require the accurate measurement of correspondingly labeled peptide peak intensities to produce high-quality estimates of differential expression ratios. In mass spectrometers with counting detectors, the measurement noise varies with intensity and consequently accuracy increases with the number of ions detected. Consequently, the relative variability of peptide intensity measurements varies with intensity. This effect must be accounted for when combining information from multiple peptides to estimate relative protein abundance. We examined a variety of algorithms that estimate protein differential expression ratios from multiple peptide intensity measurements. Algorithms that account for the variation of measurement error with intensity were found to provide the most accurate estimates of differential abundance. A simple Sum-of-Intensities algorithm provided the best estimates of true protein ratios of all algorithms tested.