Overrepresented Gene Ontology Terms Research Articles

Dog Domestication Strongly Relied on Translation Regulation According to Differential Gene Expression Analysis.

Domestication of dogs from their shared ancestors with wolves occurred more than 15,000 years ago and affected many characteristics of the species. We analyzed the blood RNA sequence data of 12 dogs and 11 wolves from Europe and Asia to shed more light on the domestication history of dogs. We implemented a differential gene expression analysis, a weighted gene correlation network analysis, gene ontology and genetic pathway analyses. We found that both the sample origin (Europe or Asia) and the species had a significant effect on the blood gene expression profiles of the animals. We identified 1567 differentially expressed genes between wolves and dogs and found several significantly overrepresented gene ontology terms, such as RNA polymerase II transcription regulatory region sequence-specific DNA binding or translation. We identified 11 significant gene co-expression networks, hosting a total of 4402 genes, related to DNA replication, metabolism of RNA or metabolism of proteins, for example. Our findings suggest that gene expression regulation played a cardinal role in dog domestication. We recommend further diversifying the analyzed dog and wolf populations in the future by including individuals from different dog breeds and geographical origins, in order to enhance the specificity of detecting significant, true positive genes related to domestication as well as to reduce the false positive rate.

Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis

BackgroundIntramuscular fat (IMF) content and its fatty acid (FA) composition are typically controlled by several genes, each with a small effect. In the current study, to pinpoint candidate genes and putative regulators involved in FA composition, we performed a multivariate integrative analysis between intramuscular FA and transcriptome profiles of porcine longissimus dorsi (LD) muscle. We also carried out a combination of network, regulatory impact factor (RIF), in silico prediction of putative target genes, and functional analyses to better support the biological relevance of our findings.ResultsFor this purpose, we used LD RNA-Seq and intramuscular FA composition profiles of 129 Iberian × Duroc backcrossed pigs. We identified 378 correlated variables (13 FA and 365 genes), including six FA (C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, C18:0, and C16:1n-7) that were among the most interconnected variables in the predicted network. The detected FA-correlated genes include genes involved in lipid and/or carbohydrate metabolism or in regulation of IMF deposition (e.g., ADIPOQ, CHUK, CYCS, CYP4B1, DLD, ELOVL6, FBP1, G0S2, GCLC, HMGCR, IDH3A, LEP, LGALS12, LPIN1, PLIN1, PNPLA8, PPP1R1B, SDR16C5, SFRP5, SOD3, SNW1, and TFRC), meat quality (GALNT15, GOT1, MDH1, NEU3, PDHA1, SDHD, and UNC93A), and transport (e.g., EXOC7 and SLC44A2). Functional analysis highlighted 54 over-represented gene ontology terms, including well-known biological processes and pathways that regulate lipid and carbohydrate metabolism. RIF analysis suggested a pivotal role for six transcription factors (CARHSP1, LBX1, MAFA, PAX7, SIX5, and TADA2A) as putative regulators of gene expression and intramuscular FA composition. Based on in silico prediction, we identified putative target genes for these six regulators. Among these, TADA2A and CARHSP1 had extreme RIF scores and present novel regulators in pigs. In addition, the expression of TADA2A correlated (either positively or negatively) with C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, and that of CARHSP1 correlated (positively) with the C16:1n-7 lipokine. We also found that these two transcription factors share target genes that are involved in lipid metabolism (e.g., GOT1, PLIN1, and TFRC).ConclusionsThis integrative analysis of muscle transcriptome and intramuscular FA profile revealed valuable information about key candidate genes and potential regulators for FA and lipid metabolism in pigs, among which some transcription factors are proposed to control gene expression and modulate FA composition differences.

Circulating cell-free DNA methylation mirrors alterations in cerebral patterns in epilepsy

BackgroundDNA methylation profiling of circulating cell-free DNA (cfDNA) has rapidly become a promising strategy for biomarker identification and development. The cell-type-specific nature of DNA methylation patterns and the direct relationship between cfDNA and apoptosis can potentially be used non-invasively to predict local alterations. In addition, direct detection of altered DNA methylation patterns performs well as a biomarker. In a previous study, we demonstrated marked DNA methylation alterations in brain tissue from patients with mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE–HS).ResultsWe performed DNA methylation profiling in cfDNA isolated from the serum of MTLE patients and healthy controls using BeadChip arrays followed by systematic bioinformatic analysis including deconvolution analysis and integration with DNase accessibility data sets. Differential cfDNA methylation analysis showed an overrepresentation of gene ontology terms and transcription factors related to central nervous system function and regulation. Deconvolution analysis of the DNA methylation data sets ruled out the possibility that the observed differences were due to changes in the proportional contribution of cortical neurons in cfDNA. Moreover, we found no overrepresentation of neuron- or glia-specific patterns in the described cfDNA methylation patterns. However, the MTLE–HS cfDNA methylation patterns featured a significant overrepresentation of the epileptic DNA methylation alterations previously observed in the hippocampus.ConclusionsOur results support the use of cfDNA methylation profiling as a rational approach to seeking non-invasive and reproducible epilepsy biomarkers.

Reconstruction and Exploratory Analysis of mTORC1 Signaling Pathway and Its Applications to Various Diseases Using Network-Based Approach.

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

Coexpression of Gene Transcripts with Monoamine Oxidase A Quantified by Human In Vivo Positron Emission Tomography.

The monoamine oxidase A (MAO-A) is integral to monoamine metabolism and is thus relevant to the pathophysiology of various neuropsychiatric disorders; however, associated gene-enzyme relations are not well understood. This study aimed to unveil genes coexpressed with MAO-A. Therefore, 18 179 mRNA expression maps (based on the Allen Human Brain Atlas) were correlated with the cerebral distribution volume (VT) of MAO-A assessed in 36 healthy subjects (mean age ± standard deviation: 32.9 ± 8.8 years, 18 female) using [11C]harmine positron emission tomography scans. Coexpression analysis was based on Spearman's ρ, over-representation tests on Fisher's exact test with false discovery rate (FDR) correction. The analysis revealed 35 genes in cortex (including B-cell translocation gene family, member 3, implicated in neuroinflammation) and 247 genes in subcortex (including kallikrein-related peptidase 10, implicated in Alzheimer's disease). Significantly over-represented Gene Ontology terms included "neuron development", "neuron differentiation", and "cell-cell signaling" as well as "axon" and "neuron projection". In vivo MAO-A enzyme distribution and MAOA expression did not correlate in cortical areas (ρ = 0.08) while correlation was found in subcortical areas (ρ = 0.52), suggesting influences of region-specific post-transcriptional and -translational modifications. The herein reported information could contribute to guide future genetic studies, deepen the understanding of associated pathomechanisms and assist in the pursuit of novel therapeutic targets.

DNA methylation profile of liver of mice conceived by invitro fertilization.

Offspring generated by invitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

GENES MEDIATING CELL GROWTH IN ALDOSTERONE-PRODUCING ADENOMAS

Objective: Aldosterone-producing adenomas (APA) are a major cause of primary aldosteronism. Somatic mutations explain the excess aldosterone production in the majority of patients with APA with mutations in KCNJ5 encoding a potassium channel the most prevalent in most reported populations. Mechanisms driving cell proliferation are largely undefined. Design and method: Quantitative transcriptome analysis using RNA-seq was used to identify differentially expressed genes between macro-APAs (n = 9, diameter &gt;= 30 mm) and micro-APAs (n = 12, diameter &lt;= 10 mm). Validation of RNA-seq data by TaqMan real-time PCR was performed for 14 genes in a broader cohort of APAs (NMD, no mutation detected, n = 28; KCNJ5-mutated, n = 43). Results: Hierarchical cluster analysis of the 500 genes with largest coefficient of variation indicated sample clustering based on genotype (KCNJ5 or NMD) and APA diameter. Differential expression of 155 and 348 genes was found between micro- and macro-APAs with KCNJ5 mutations and NMD, respectively. Among the top 5 overrepresented Gene Ontology terms (biological process), cell death was exclusively enriched in NMD micro- vs NMD macro-APAs. The expression levels of 10 genes were validated with a potential function related to cell growth. Expression of BEX1 (a reported tumour suppressor) was 2.8-fold down regulated in macro-APAs relative to micro-APAs (P &lt; 0.001), and a linear negative correlation of BEX1 expression with APA diameter was observed in NMD APAs (r = -0.501, P = 0.007). Genes involved in beta-catenin signalling, SFRP2, DKK1 and TSPAN12 were 5.9-fold (P &lt; 0.001), 1.8-fold (P = 0.007) and 8.3-fold (P &lt; 0.0001) down regulated, respectively, in macro-APAs compared with micro-APAs. BAI1 and CCL21 were also down regulated in macro-APAs relative to micro-APAs (3.3-fold, P = 0.026; 2.6-fold, P = 0.145, respectively). Additionally, the expression of TMPRSS3 (r = 0.727, P &lt; 0.001), BMP4 (r = 0.389, P = 0.041) and FBXL21 (r = 0.761, P &lt; 0.001) showed a linear positive correlation with adenoma diameter in NMD subgroup. Conclusions: APA display distinct transcriptome profiles according to adenoma diameter which may help identify genes involved in APA tumour cell growth.

Transcriptome Analyses of Myometrium from Fibroid Patients Reveals Phenotypic Differences Compared to Non-Diseased Myometrium.

Uterine fibroid tissues are often compared to their matched myometrium in an effort to understand their pathophysiology, but it is not clear whether the myometria of uterine fibroid patients represent truly non-disease control tissues. We analyzed the transcriptomes of myometrial samples from non-fibroid patients (M) and compared them with fibroid (F) and matched myometrial (MF) samples to determine whether there is a phenotypic difference between fibroid and non-fibroid myometria. Multidimensional scaling plots revealed that M samples clustered separately from both MF and F samples. A total of 1169 differentially expressed genes (DEGs) (false discovery rate < 0.05) were observed in the MF comparison with M. Overrepresented Gene Ontology terms showed a high concordance of upregulated gene sets in MF compared to M, particularly extracellular matrix and structure organization. Gene set enrichment analyses showed that the leading-edge genes from the TGFβ signaling and inflammatory response gene sets were significantly enriched in MF. Overall comparison of the three tissues by three-dimensional principal component analyses showed that M, MF, and F samples clustered separately from each other and that a total of 732 DEGs from F vs. M were not found in the F vs. MF, which are likely understudied in the pathogenesis of uterine fibroids and could be key genes for future investigation. These results suggest that the transcriptome of fibroid-associated myometrium is different from that of non-diseased myometrium and that fibroid studies should consider using both matched myometrium and non-diseased myometrium as controls.

RNAseq Reveals Differential Gene Expression Contributing to Phytophthora nicotianae Adaptation to Partial Resistance in Tobacco

Phytophthora nicotianae is a devastating oomycete plant pathogen with a wide host range. On tobacco, it causes black shank, a disease that can result in severe economic losses. Deployment of host resistance is one of the most effective means of controlling tobacco black shank, but adaptation to complete and partial resistance by P. nicotianae can limit the long-term effectiveness of the resistance. The molecular basis of adaptation to partial resistance is largely unknown. RNAseq was performed on two isolates of P. nicotianae (adapted to either the susceptible tobacco genotype Hicks or the partially resistant genotype K 326 Wz/Wz) to identify differentially expressed genes (DEGs) during their pathogenic interactions with K 326 Wz/Wz and Hicks. Approximately 69% of the up-regulated DEGs were associated with pathogenicity in the K 326 Wz/Wz-adapted isolate when sampled following infection of its adapted host K 326 Wz/Wz. Thirty-one percent of the up-regulated DEGs were associated with pathogenicity in the Hicks-adapted isolate on K 326 Wz/Wz. A broad spectrum of over-represented gene ontology (GO) terms were assigned to down-regulated genes in the Hicks-adapted isolate. In the host, a series of GO terms involved in nuclear biosynthesis processes were assigned to the down-regulated genes in K 326 Wz/Wz inoculated with K 326 Wz/Wz-adapted isolate. This study enhances our understanding of the molecular mechanisms of P. nicotianae adaptation to partial resistance in tobacco by elucidating how the pathogen recruits pathogenicity-associated genes that impact host biological activities.

Differential gene expression analysis reveals pathways important in early post-traumatic osteoarthritis in an equine model

BackgroundPost-traumatic osteoarthritis (PTOA) is a common and significant problem in equine athletes. It is a disease of the entire joint, with the synovium thought to be a key player in disease onset and progression due to its role in inflammation. The development of effective tools for early diagnosis and treatment of PTOA remains an elusive goal. Altered gene expression represents the earliest discernable disease-related change, and can provide valuable information about disease pathogenesis and identify potential therapeutic targets. However, there is limited work examining global gene expression changes in early disease. In this study, we quantified gene expression changes in the synovium of osteoarthritis-affected joints using an equine metacarpophalangeal joint (MCPJ) chip model of early PTOA. Synovial samples were collected arthroscopically from the MCPJ of 11 adult horses before (preOA) and after (OA) surgical induction of osteoarthritis and from sham-operated joints. After sequencing synovial RNA, Salmon was used to quasi-map reads and quantify transcript abundances. Differential expression analysis with the limma-trend method used a fold-change cutoff of log2(1.1). Functional annotation was performed with PANTHER at FDR < 0.05. Pathway and network analyses were performed in Reactome and STRING, respectively.ResultsRNA was sequenced from 28 samples (6 preOA, 11 OA, 11 sham). “Sham” and “preOA” were not different and were grouped. Three hundred ninety-seven genes were upregulated and 365 downregulated in OA synovium compared to unaffected. Gene ontology (GO) terms related to extracellular matrix (ECM) organization, angiogenesis, and cell signaling were overrepresented. There were 17 enriched pathways, involved in ECM turnover, protein metabolism, and growth factor signaling. Network analysis revealed clusters of differentially expressed genes involved in ECM organization, endothelial regulation, and cellular metabolism.ConclusionsEnriched pathways and overrepresented GO terms reflected a state of high metabolic activity and tissue turnover in OA-affected tissue, suggesting that the synovium may retain the capacity to support healing and homeostasis in early disease. Limitations of this study include small sample size and capture of one point post-injury. Differentially expressed genes within key pathways may represent potential diagnostic markers or therapeutic targets for PTOA. Mechanistic validation of these findings is an important next step.

Determining the effects of trastuzumab, cetuximab and afatinib by phosphoprotein, gene expression and phenotypic analysis in gastric cancer cell lines

BackgroundGastric cancer is the fifth most frequently diagnosed cancer and the third leading cause of cancer death worldwide. The molecular mechanisms of action for anti-HER-family drugs in gastric cancer cells are incompletely understood. We compared the molecular effects of trastuzumab and the other HER-family targeting drugs cetuximab and afatinib on phosphoprotein and gene expression level to gain insights into the regulated pathways. Moreover, we intended to identify genes involved in phenotypic effects of anti-HER therapies.MethodsA time-resolved analysis of downstream intracellular kinases following EGF, cetuximab, trastuzumab and afatinib treatment was performed by Luminex analysis in the gastric cancer cell lines Hs746T, MKN1, MKN7 and NCI-N87. The changes in gene expression after treatment of the gastric cancer cell lines with EGF, cetuximab, trastuzumab or afatinib for 4 or 24 h were analyzed by RNA sequencing. Significantly enriched pathways and gene ontology terms were identified by functional enrichment analysis. Furthermore, effects of trastuzumab and afatinib on cell motility and apoptosis were analyzed by time-lapse microscopy and western blot for cleaved caspase 3.ResultsThe Luminex analysis of kinase activity revealed no effects of trastuzumab, while alterations of AKT1, MAPK3, MEK1 and p70S6K1 activations were observed under cetuximab and afatinib treatment. On gene expression level, cetuximab mainly affected the signaling pathways, whereas afatinib had an effect on both signaling and cell cycle pathways. In contrast, trastuzumab had little effects on gene expression. Afatinib reduced average speed in MKN1 and MKN7 cells and induced apoptosis in NCI-N87 cells. Following treatment with afatinib, a list of 14 genes that might be involved in the decrease of cell motility and a list of 44 genes that might have a potential role in induction of apoptosis was suggested. The importance of one of these genes (HBEGF) as regulator of motility was confirmed by knockdown experiments.ConclusionsTaken together, we described the different molecular effects of trastuzumab, cetuximab and afatinib on kinase activity and gene expression. The phenotypic changes following afatinib treatment were reflected by altered biological functions indicated by overrepresentation of gene ontology terms. The importance of identified genes for cell motility was validated in case of HBEGF.

GOMCL: a toolkit to cluster, evaluate, and extract non-redundant associations of Gene Ontology-based functions

BackgroundFunctional enrichment of genes and pathways based on Gene Ontology (GO) has been widely used to describe the results of various -omics analyses. GO terms statistically overrepresented within a set of a large number of genes are typically used to describe the main functional attributes of the gene set. However, these lists of overrepresented GO terms are often too large and contains redundant overlapping GO terms hindering informative functional interpretations.ResultsWe developed GOMCL to reduce redundancy and summarize lists of GO terms effectively and informatively. This lightweight python toolkit efficiently identifies clusters within a list of GO terms using the Markov Clustering (MCL) algorithm, based on the overlap of gene members between GO terms. GOMCL facilitates biological interpretation of a large number of GO terms by condensing them into GO clusters representing non-overlapping functional themes. It enables visualizing GO clusters as a heatmap, networks based on either overlap of members or hierarchy among GO terms, and tables with depth and cluster information for each GO term. Each GO cluster generated by GOMCL can be evaluated and further divided into non-overlapping sub-clusters using the GOMCL-sub module. The outputs from both GOMCL and GOMCL-sub can be imported to Cytoscape for additional visualization effects.ConclusionsGOMCL is a convenient toolkit to cluster, evaluate, and extract non-redundant associations of Gene Ontology-based functions. GOMCL helps researchers to reduce time spent on manual curation of large lists of GO terms, minimize biases introduced by redundant GO terms in data interpretation, and batch processing of multiple GO enrichment datasets. A user guide, a test dataset, and the source code of GOMCL are available at https://github.com/Guannan-Wang/GOMCL and www.lsugenomics.org.

Experimental challenge with bovine respiratory syncytial virus in dairy calves: bronchial lymph node transcriptome response

Bovine Respiratory Disease (BRD) is the leading cause of mortality in calves. The objective of this study was to examine the response of the host’s bronchial lymph node transcriptome to Bovine Respiratory Syncytial Virus (BRSV) in a controlled viral challenge. Holstein-Friesian calves were either inoculated with virus (103.5 TCID50/ml × 15 ml) (n = 12) or mock challenged with phosphate buffered saline (n = 6). Clinical signs were scored daily and blood was collected for haematology counts, until euthanasia at day 7 post-challenge. RNA was extracted and sequenced (75 bp paired-end) from bronchial lymph nodes. Sequence reads were aligned to the UMD3.1 bovine reference genome and differential gene expression analysis was performed using EdgeR. There was a clear separation between BRSV challenged and control calves based on gene expression changes, despite an observed mild clinical manifestation of the disease. Therefore, measuring host gene expression levels may be beneficial for the diagnosis of subclinical BRD. There were 934 differentially expressed genes (DEG) (p < 0.05, FDR <0.1, fold change >2) between the BRSV challenged and control calves. Over-represented gene ontology terms, pathways and molecular functions, among the DEG, were associated with immune responses. The top enriched pathways included interferon signaling, granzyme B signaling and pathogen pattern recognition receptors, which are responsible for the cytotoxic responses necessary to eliminate the virus.

Application of next generation sequencing for the elucidation of genes and pathways involved in the host response to bovine respiratory syncytial virus

High rates of calf mortality in the first 12 months of life, results in significant economic losses in Europe and the USA. Bovine respiratory disease (BRD) accounts for the largest proportion of calf mortality. There is a paucity of literature concerning the host response to BRD. In a controlled challenge study in artificially reared dairy calves [155 (S.D. 14) kg], the influence of the host response to bovine respiratory syncytial virus (BRSV) was examined. At AFBI Holstein-Friesian calves were either challenged with BRSV (n=12) or mock challenged with phosphate buffer saline (n=6). Calves were euthanised on day 7 post-challenge. Bronchial lymph nodes were collected and flash-frozen at −80 °C. RNA was extracted and sent to the University of Missouri’s DNA Core Facility for RNA-Seq library preparation and sequencing. Sequenced reads were adapter trimmed, quality assessed using FastQC and aligned to the bovine genome (UMD 3.1) using STAR. Differential gene expression analysis was performed using EdgeR, and pathway and gene ontology analyses were carried out using g:Profiler and Ingenuity Pathway Analysis (IPA). There was a clear separation between BRSV challenged and control calves based on log2 fold gene expression changes, despite an observed mild clinical manifestation of the disease. There were 934 differentially expressed genes (DEG) (P&lt;0.05, FDR&lt;0.1, fold change &gt;2) between the BRSV challenged and control calves. Over-represented pathways and gene ontology terms among the DEG were associated with immune responses and included: GO:0051607 defense response to virus, the KEGG pathway Influenza A and the IPA pathway Interferon Signaling.

Prolonged Bat Call Exposure Induces a Broad Transcriptional Response in the Male Fall Armyworm (Spodoptera frugiperda; Lepidoptera: Noctuidae) Brain.

Predation risk induces broad behavioral and physiological responses that have traditionally been considered acute and transitory. However, prolonged or frequent exposure to predators and the sensory cues of their presence they broadcast to the environment impact long-term prey physiology and demographics. Though several studies have assessed acute and chronic stress responses in varied taxa, these attempts have often involved a priori expectations of the molecular pathways involved in physiological responses, such as glucocorticoid pathways and neurohormone production in vertebrates. While relatively little is known about physiological and molecular predator-induced stress in insects, many dramatic insect defensive behaviors have evolved to combat selection by predators. For instance, several moth families, such as Noctuidae, include members equipped with tympanic organs that allow the perception of ultrasonic bat calls and facilitate predation avoidance by eliciting evasive aerial flight maneuvers. In this study, we exposed adult male fall armyworm (Spodoptera frugiperda) moths to recorded ultrasonic bat foraging and attack calls for a prolonged period and constructed a de novo transcriptome based on brain tissue from predator cue-exposed relative to control moths kept in silence. Differential expression analysis revealed that 290 transcripts were highly up- or down-regulated among treatment tissues, with many annotating to noteworthy proteins, including a heat shock protein and an antioxidant enzyme involved in cellular stress. Though nearly 50% of differentially expressed transcripts were unannotated, those that were are implied in a broad range of cellular functions within the insect brain, including neurotransmitter metabolism, ionotropic receptor expression, mitochondrial metabolism, heat shock protein activity, antioxidant enzyme activity, actin cytoskeleton dynamics, chromatin binding, methylation, axonal guidance, cilia development, and several signaling pathways. The five most significantly overrepresented Gene Ontology terms included chromatin binding, macromolecular complex binding, glutamate synthase activity, glutamate metabolic process, and glutamate biosynthetic process. As a first assessment of transcriptional responses to ecologically relevant auditory predator cues in the brain of moth prey, this study lays the foundation for examining the influence of these differentially expressed transcripts on insect behavior, physiology, and life history within the framework of predation risk, as observed in ultrasound-sensitive Lepidoptera and other ‘eared’ insects.

Transcriptional Remodeling in Primary Hippocampal Astrocytes from an Alzheimer's Disease Mouse Model.

It is well known that alterations in astrocytes occur in Alzheimer's disease and reactive astrogliosis is one of the hallmarks of the disease. Recently, data has emerged that suggests that alterations in astrocytes may also occur early in the pathogenesis of the disease. The aim of present work was to characterize the transcriptional alterations occurring in cultured astrocytes from 3xTg-AD mouse pups compared to control non-transgenic mice. Furthermore, we also compared these changes to those reported by others in astrocytes from symptomatic AD mice. We conducted a whole-genome microarray study on primary cultured astrocytes from the hippocampus of 3xTg-AD and non-transgenic mouse newborn pups. We used cross-platform normalization and an unsupervised hierarchical clustering algorithm to compare our results with other datasets of cultured or freshly isolated astrocytes, including those isolated from plaque-stage APPswe/PS1dE9 AD mice. We found a set of 993 genes differentially expressed in 3xTg-AD as compared with non-Tg astrocytes. Over-represented gene ontology terms were related to calcium, cell-cell communication, mitochondria, transcription, nucleotide binding and phosphorylation. Of note, no genes related to inflammation were found in cultured 3xTg-AD astrocytes. Comparison with astrocytes isolated from plaque stage APPswe/PS1dE9 showed that 882 out of 993 genes were selectively changed in primary 3xTg-AD astrocytes while 50 genes were co-regulated and 61 were anti-regulated (regulated in the opposite direction in the datasets). Our data show that in cultured astrocytes from an AD mouse model, transcriptional changes occur and are different from those reported in models mimicking later stages of the disease.

Effects of developmental lead exposure on the hippocampal methylome: Influences of sex and timing and level of exposure

Developmental lead (Pb) exposure results in persistent cognitive/behavioral impairments as well as an elevated risk for developing a variety of diseases in later life. Environmental exposures during development can result in a variety of epigenetic changes, including alterations in DNA methylation, that can influence gene expression patterns and affect the function and development of the nervous system. The present promoter-based methylation microarray profiling study explored the extent to which developmental Pb exposure may modify the methylome of a brain region, hippocampus, known to be sensitive to the effects of Pb exposure. Male and female Long Evans rats were exposed to 0 ppm, 150 ppm, 375 ppm, or 750 ppm Pb through perinatal exposures (gestation through lactation), early postnatal exposures (birth through weaning), or long-term postnatal exposures (birth through postnatal day 55). Results showed a significant contribution of sex to the hippocampal methylome and effects of Pb exposure level, with non-linear dose response effects on methylation. Surprisingly, the developmental period of exposure contributed only a small amount of variance to the overall data and gene ontology (GO) analysis revealed the largest number of overrepresented GO terms in the groups with the lowest level of exposure. The highest number of significant differentially methylated regions was found in females exposed to Pb at the lowest exposure level. Our data reinforce the significant effect that low level Pb exposure may have on gene-specific DNA methylation patterns in brain and that this occurs in a sex-dependent manner.

A Microarray Study of Carpet-Shell Clam (Ruditapes decussatus) Shows Common and Organ-Specific Growth-Related Gene Expression Differences in Gills and Digestive Gland.

Growth rate is one of the most important traits from the point of view of individual fitness and commercial production in mollusks, but its molecular and physiological basis is poorly known. We have studied differential gene expression related to differences in growth rate in adult individuals of the commercial marine clam Ruditapes decussatus. Gene expression in the gills and the digestive gland was analyzed in 5 fast-growing and five slow-growing animals by means of an oligonucleotide microarray containing 14,003 probes. A total of 356 differentially expressed genes (DEG) were found. We tested the hypothesis that differential expression might be concentrated at the growth control gene core (GCGC), i.e., the set of genes that underlie the molecular mechanisms of genetic control of tissue and organ growth and body size, as demonstrated in model organisms. The GCGC includes the genes coding for enzymes of the insulin/insulin-like growth factor signaling pathway (IIS), enzymes of four additional signaling pathways (Raf/Ras/Mapk, Jnk, TOR, and Hippo), and transcription factors acting at the end of those pathways. Only two out of 97 GCGC genes present in the microarray showed differential expression, indicating a very little contribution of GCGC genes to growth-related differential gene expression. Forty eight DEGs were shared by both organs, with gene ontology (GO) annotations corresponding to transcription regulation, RNA splicing, sugar metabolism, protein catabolism, immunity, defense against pathogens, and fatty acid biosynthesis. GO term enrichment tests indicated that genes related to growth regulation, development and morphogenesis, extracellular matrix proteins, and proteolysis were overrepresented in the gills. In the digestive gland overrepresented GO terms referred to gene expression control through chromatin rearrangement, RAS-related small GTPases, glucolysis, and energy metabolism. These analyses suggest a relevant role of, among others, some genes related to the IIS, such as the ParaHox gene Xlox, CCAR and the CCN family of secreted proteins, in the regulation of growth in bivalves.

Transcriptional profiling of Toll-like receptor 2-deficient primary murine brain cells during Toxoplasma gondii infection.

BackgroundToxoplasma gondii is capable of persisting in the brain, although it is efficiently eliminated by cellular immune responses in most other sites. While Toll-like receptor 2 (TLR2) reportedly plays important roles in protective immunity against the parasite, the relationship between neurological disorders induced by T. gondii infection and TLR2 function in the brain remains controversial with many unknowns. In this study, primary cultured astrocytes, microglia, neurons, and peritoneal macrophages obtained from wild-type and TLR2-deficient mice were exposed to T. gondii tachyzoites. To characterize TLR2-dependent functional pathways activated in response to T. gondii infection, gene expression of different cell types was profiled by RNA sequencing.ResultsDuring T. gondii infection, a total of 611, 777, 385, and 1105 genes were upregulated in astrocytes, microglia, neurons, and macrophages, respectively, while 163, 1207, 158, and 1274 genes were downregulated, respectively, in a TLR2-dependent manner. Overrepresented Gene Ontology (GO) terms for TLR2-dependently upregulated genes were associated with immune and stress responses in astrocytes, immune responses and developmental processes in microglia, metabolic processes and immune responses in neurons, and metabolic processes and gene expression in macrophages. Overrepresented GO terms for downregulated genes included ion transport and behavior in astrocytes, cell cycle and cell division in microglia, metabolic processes in neurons, and response to stimulus, signaling and cell motility in macrophages.ConclusionsTo our knowledge, this is the first transcriptomic study of TLR2 function across different cell types during T. gondii infection. Results of RNA-sequencing demonstrated roles for TLR2 varied by cell type during T. gondii infection. Our findings facilitate understanding of the detailed relationship between TLR2 and T. gondii infection, and elucidate mechanisms underlying neurological changes during infection.

The Tolerome: A Database of Transcriptome-Level Contributions to Diverse Escherichia coli Resistance and Tolerance Phenotypes.

Tolerance and resistance are complex biological phenotypes that are desirable bioengineering goals for those seeking to design industrial strains or prevent the spread of antibiotic resistance. Over decades of research, a wealth of information has been generated to attempt to decode a molecular basis for tolerance, but to fully achieve the goal of engineering tolerance, researchers must be able to easily learn from a variety of data sources. To this end, we here describe a resource designed to enable scrutiny of diverse tolerance phenotypes. We have curated hundreds of gene expression studies exploring the response of Escherichia coli to chemical and environmental perturbations, from antibiotics to biofuels and solvents and more. Overall, our efforts give rise to a database encompassing more than 56 000 gene expression changes across 89 different stress conditions. This resource is designed for compatibility with the Resistome database, which includes more than 5000 strains with mutations conferring resistance or sensitivity but no transcriptomic data. Thus, the work here results in the first combined resource specialized to tolerance and resistance in E.coli that supports investigations across genomic, transcriptomic, and phenotypic levels. We leverage the database to identify promising bioengineering targets by searching globally across multiple stress conditions as well as by narrowing the focus to fewer conditions of interest, such as biofuel stress and antibiotic stress. We discuss some of the most frequently differentially expressed or coexpressed genes, and predict which transcription factors and sigma factors most likely contribute to gene expression profiles in a wide array of conditions. We also compare profiles from sensitive and resistant strains, gaining knowledge of how responses differ per overrepresented gene ontology terms. Finally, we search for genes that are frequently differentially expressed but not mutated, with the expectation that these may present interesting targets for future engineering efforts. The curated data presented here is publicly available, and should be advantageous to those studying a variety of bacterial tolerance phenotypes.