Analysing time course microarray data using Bioconductor: a case study using yeast2 Affymetrix arrays

Time-series gene expression patterns and their characteristics of Beauveria bassiana in the process of infecting pest insects

Beauveria bassiana has been widely used as an important biological control fungus for agricultural and forest pests, and clarifying the interaction mechanism between B. bassiana and its host will help to better exert the efficacy of the mycoinsecticide. Here, we proposed a novel pattern analysis (PA) method for analyzing time-series data and applied it to a transcriptomic data set of B. bassiana infecting Galleria mellonella. We screened out 14 patterns including 868 genes, which had some characteristics that were not inferior to differentially expressed genes (DEGs). Compared with the previous analysis of this data set, we had three novel discoveries during B. bassiana infection, including overall downregulation of gene expression, the more critical first 24 h, and enrichment of regulatory functions of downregulated genes. Our new PA method promises to be an important complement to DEGs analysis for time-series transcriptomic data, and our findings enrich our knowledge of molecular mechanisms of fungal-host interactions.

A Lung Transcriptomic Analysis for Exploring Host Response in COVID-19

Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) rose without precedent for Wuhan, China, in December 2019. It is a kind of exceptionally pathogenic human coronavirus (HCoV) which causes zoonotic sicknesses and represents a significant risk to general wellbeing. Recognizing the hidden biology and pathogenesis of this novel coronavirus is extremely critical to comprehend as well as boosting the treatment of this deadly pandemic. The point of this study is to recognize key genes which show significant expression in the SARS-CoV-2 infected lungs as compared to healthy ones. Our analysis uncovered 149 gene-signatures that show substantial up-regulation in COVID-19 lungs. Out of these, top ten dysregulated genes STAP1, CASP5, FDCSP, CARD17, ST20, AKR1B10, CLC, KCNJ2-AS1, RNASE2 and FLG are found to be significant based on various crucial statistical factors and may end up being acceptable helpful drug targets.

Exposure to the lampricide TFM elicits an environmental stress response in yeast

The pesticide 3-trifluoromethyl-4-nitrophenol (TFM) is used to control sea lamprey populations in the Great Lakes and Lake Champlain. Little is known about the effects of this pesticide on gene expression in eukaryotic species. This study used microarray analysis to determine the effects of short term, high dose TFM exposure on gene expression in Saccharomyces cerevisiae. Yeast grown in standard glucose-containing media showed significant variation in gene expression in pathways related to cytoplasmic translation with the majority of these genes being downregulated. These findings were supported by the analysis of a similar but glucose-free experiment revealing that these cytoplasmic translation genes, mostly ribosomal subunit expressing genes, were similarly downregulated. The repression of the ribosomal subunit genes suggests that TFM exposure, regardless of glucose availability, evokes features of the environmental stress response in yeast.

Knockout of the Hmt1p Arginine Methyltransferase in Saccharomyces cerevisiae Leads to the Dysregulation of Phosphate-associated Genes and Processes

Hmt1p is the predominant arginine methyltransferase in Saccharomyces cerevisiae Its substrate proteins are involved in transcription, transcriptional regulation, nucleocytoplasmic transport and RNA splicing. Hmt1p-catalyzed methylation can also modulate protein-protein interactions. Hmt1p is conserved from unicellular eukaryotes through to mammals where its ortholog, PRMT1, is lethal upon knockout. In yeast, however, the effect of knockout on the transcriptome and proteome has not been described. Transcriptome analysis revealed downregulation of phosphate-responsive genes in hmt1Δ, including acid phosphatases PHO5, PHO11, and PHO12, phosphate transporters PHO84 and PHO89 and the vacuolar transporter chaperone VTC3 Analysis of the hmt1Δ proteome revealed decreased abundance of phosphate-associated proteins including phosphate transporter Pho84p, vacuolar alkaline phosphatase Pho8p, acid phosphatase Pho3p and subunits of the vacuolar transporter chaperone complex Vtc1p, Vtc3p and Vtc4p. Consistent with this, phosphate homeostasis was dysregulated in hmt1Δ cells, showing decreased extracellular phosphatase levels and decreased total P_i in phosphate-depleted medium. In vitro, we showed that transcription factor Pho4p can be methylated at Arg-241, which could explain phosphate dysregulation in hmt1Δ if interplay exists with phosphorylation at Ser-242 or Ser-243, or if Arg-241 methylation affects the capacity of Pho4p to homodimerize or interact with Pho2p. However, the Arg-241 methylation site was not validated in vivo and the localization of a Pho4p-GFP fusion in hmt1Δ was not different from wild type. To our knowledge, this is the first study to reveal an association between Hmt1p and phosphate homeostasis and one which suggests a regulatory link between S-adenosyl methionine and intracellular phosphate.

Exposure to the lampricide 3-trifluoromethyl-4-nitrophenol results in increased expression of carbohydrate transporters in Saccharomyces cerevisiae

The lampricide 3-trifluoromethyl-4-nitrophenol (TFM) is used to control sea lamprey (Petromyzon marinus) populations in freshwater lakes. Although TFM can have sublethal and lethal effects, little is known about gene expression changes with TFM exposure. Microarray analysis was used to determine differential gene expression over 4 h of exposure in Saccharomyces cerevisiae. Among the most significantly up-regulated genes were regulators of carbohydrate transport, including HXT1, HXT3, HXT4, IMA5, MIG2, and YKR075C. Environ Toxicol Chem 2016;35:1727-1732. © 2015 SETAC.

Histone Sprocket Arginine Residues Are Important for Gene Expression, DNA Repair, and Cell Viability in Saccharomyces cerevisiae

A critical feature of the intermolecular contacts that bind DNA to the histone octamer is the series of histone arginine residues that insert into the DNA minor groove at each superhelical location where the minor groove faces the histone octamer. One of these "sprocket" arginine residues, histone H4 R45, significantly affects chromatin structure in vivo and is lethal when mutated to alanine or cysteine in Saccharomyces cerevisiae (budding yeast). However, the roles of the remaining sprocket arginine residues (H3 R63, H3 R83, H2A R43, H2B R36, H2A R78, H3 R49) in chromatin structure and other cellular processes have not been well characterized. We have genetically characterized mutations in each of these histone residues when introduced either singly or in combination to yeast cells. We find that pairs of arginine residues that bind DNA adjacent to the DNA exit/entry sites in the nucleosome are lethal in yeast when mutated in combination and cause a defect in histone occupancy. Furthermore, mutations in individual residues compromise repair of UV-induced DNA lesions and affect gene expression and cryptic transcription. This study reveals simple rules for how the location and structural mode of DNA binding influence the biological function of each histone sprocket arginine residue.

Neuronal calcium signaling pathways are associated with the development of epilepsy

Epilepsy is the most common serious neurological disorder worldwide, however, the specific causative factors and mechanisms underlying epilepsy remain unclear. The current study aimed to study the potential genes or pathways associated with epilepsy, based on rat miRNA expression profiles. The microarray dataset GSE49850 was downloaded and analyzed with the TimeCourse R software package, which was used to generate comparisons between the control and electrically-stimulated groups. The target genes of differentially expressed miRNAs were queried in the miRWalk database and functional enrichment was conducted using the Database for Annotation, Visualization and Integrated Discovery software tools. The interaction network of the target genes was constructed based on the Biomolecular Interaction Network Database and clustered using ClusterONE. In total, 152 differentially expressed miRNAs were identified, with rno-miR-21-5p being the most significantly differentially expressed. A total of 526 target genes of the differentially expressed miRNAs were obtained. Functional analysis indicated that these genes were predominantly involved in responses to stimuli. The interaction network showed that the GRIN and STX gene family, which are involved in synaptic signal transmission, were significant. In conclusion, the present study identified that the development of epilepsy was closely associated with neuronal calcium signaling pathways.

Transcriptional response to cardiac injury in the zebrafish: systematic identification of genes with highly concordant activity across in vivo models

Background

Zebrafish is a clinically-relevant model of heart regeneration. Unlike mammals, it has a remarkable heart repair capacity after injury, and promises novel translational applications. Amputation and cryoinjury models are key research tools for understanding injury response and regeneration in vivo. An understanding of the transcriptional responses following injury is needed to identify key players of heart tissue repair, as well as potential targets for boosting this property in humans.

Results

We investigated amputation and cryoinjury in vivo models of heart damage in the zebrafish through unbiased, integrative analyses of independent molecular datasets. To detect genes with potential biological roles, we derived computational prediction models with microarray data from heart amputation experiments. We focused on a top-ranked set of genes highly activated in the early post-injury stage, whose activity was further verified in independent microarray datasets. Next, we performed independent validations of expression responses with qPCR in a cryoinjury model. Across in vivo models, the top candidates showed highly concordant responses at 1 and 3 days post-injury, which highlights the predictive power of our analysis strategies and the possible biological relevance of these genes. Top candidates are significantly involved in cell fate specification and differentiation, and include heart failure markers such as periostin, as well as potential new targets for heart regeneration. For example, ptgis and ca2 were overexpressed, while usp2a, a regulator of the p53 pathway, was down-regulated in our in vivo models. Interestingly, a high activity of ptgis and ca2 has been previously observed in failing hearts from rats and humans.

Conclusions

We identified genes with potential critical roles in the response to cardiac damage in the zebrafish. Their transcriptional activities are reproducible in different in vivo models of cardiac injury.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-852) contains supplementary material, which is available to authorized users.

Analysis of time-resolved gene expression measurements across individuals

Genetic and environmental determinants of altered cellular function, disease state, and drug response are increasingly studied using time-resolved transcriptomic profiles. While it is widely acknowledged that the rate of biological processes may vary between individuals, data analysis approaches that go beyond evaluating differential expression of single genes have so far not taken this variability into account. To this end, we introduce here a robust multi-gene data analysis approach and evaluate it in a biomarker discovery scenario across four publicly available datasets. In our evaluation, existing methods perform surprisingly poorly on time-resolved data; only the approach taking the variability into account yields reproducible and biologically plausible results. Our results indicate the need to capture gene expression between potentially heterogeneous individuals at multiple time points, and highlight the importance of robust data analysis in the presence of heterogeneous gene expression responses.

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components.

Interplay of microRNAs, transcription factors and target genes: linking dynamic expression changes to function

MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the post-transcriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-γ stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24-48 h) with respect to mRNAs (12-24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-γ stimulation. Linking expression profiles of transcriptional regulators and miRNAs with their annotated functions, we demonstrate the dynamic interplay of miRNAs and upstream regulators with biological functions. Finally, our data revealed network motifs in the form of feed-forward loops involving transcriptional regulators, mRNAs and miRNAs. Additional information obtained from integrating time-series mRNA and miRNA data may represent an important step towards understanding the regulatory principles of gene expression.