Large-scale Gene Expression Analysis Research Articles

Areal specializations in the morpho-electric and transcriptomic properties of primate layer 5 extratelencephalic projection neurons

Large-scale analysis of single-cell gene expression has revealed transcriptomically defined cell subclasses present throughout the primate neocortex with gene expression profiles that differ depending upon neocortical region. Here, we test whether the interareal differences in gene expression translate to regional specializations in the physiology and morphology of infragranular glutamatergic neurons by performing Patch-seq experiments in brain slices from the temporal cortex (TCx) and motor cortex (MCx) of the macaque. We confirm that transcriptomically defined extratelencephalically projecting neurons of layer 5 (L5 ET neurons) include retrogradely labeled corticospinal neurons in the MCx and find multiple physiological properties and ion channel genes that distinguish L5 ET from non-ET neurons in both areas. Additionally, while infragranular ET and non-ET neurons retain distinct neuronal properties across multiple regions, there are regional morpho-electric and gene expression specializations in the L5 ET subclass, providing mechanistic insights into the specialized functional architecture of the primate neocortex.

The SPARC-related modular calcium binding 1 (Smoc1) regulated by androgen is required for mouse gubernaculum development and testicular descent.

Testicular descent occurs in two consecutive stages: the transabdominal stage and the inguinoscrotal stage. Androgens play a crucial role in the second stage by influencing the development of the gubernaculum, a structure that pulls the testis into the scrotum. However, the mechanisms of androgen actions underlying many of the processes associated with gubernaculum development have not been fully elucidated. To identify the androgen-regulated genes, we conducted large-scale gene expression analyses on the gubernaculum harvested from luteinizing hormone/choriogonadotropin receptor knockout (Lhcgr KO) mice, an animal model of inguinoscrotal testis maldescent resulting from androgen deficiency. We found that the expression of secreted protein acidic and rich in cysteine (SPARC)-related modular calcium binding 1 (Smoc1) was the most severely suppressed at both the transcript and protein levels, while its expression was the most dramatically induced by testosterone administration in the gubernacula of Lhcgr KO mice. The upregulation of Smoc1 expression by testosterone was curtailed by the addition of an androgen receptor antagonist, flutamide. In addition, in vitro studies demonstrated that SMOC1 modestly but significantly promoted the proliferation of gubernacular cells. In the cultures of myogenic differentiation medium, both testosterone and SMOC1 enhanced the expression of myogenic regulatory factors such as paired box 7 (Pax7) and myogenic factor 5 (Myf5). After short-interfering RNA-mediated knocking down of Smoc1, the expression of Pax7 and Myf5 diminished, and testosterone alone did not recover, but additional SMOC1 did. These observations indicate that SMOC1 is pivotal in mediating androgen action to regulate gubernaculum development during inguinoscrotal testicular descent.

Identification of follicle-stimulating hormone-responsive genes in Sertoli cells during early postnatal mouse testis development.

In the mouse testis, Sertoli cells rapidly divide during a narrow window of time pre-pubertally and differentiate thereafter. The number of Sertoli cells determines the testis size and germ cell-carrying capacity. Follicle-stimulating hormone (FSH) binds its cognate FSH-receptors expressed on Sertoli cells and acts as a mitogen to regulate their proliferation. Fshb-/- mutant adult male mice have reduced Sertoli cell number and testis size and reduced sperm number and motility. However, FSH-responsive genes in early postnatal mouse Sertoli cells are unknown. To identify FSH-responsive genes in early postnatal mouse Sertoli cells. A fluorescence-activated cell sorting method was developed to rapidly purify Sertoli cells from control and Fshb-/- mice carrying a Sox9 GfpKI allele. These pure Sertoli cells were used for large-scale gene expression analyses. We show that mouse Sertoli cells rarely divide beyond postnatal day 7. Our in vivo BrdU labeling studies indicate loss of FSH results in a 30% reduction in Sertoli cell proliferation in mice at 5 days of age. Flowsorted GFP+ Sertoli cells with maximal Fshr expression were 97%-98% pure and mostly devoid of Leydig and germ cells as assessed by Taqman qPCR quantification of gene expression and immunolabeling of the corresponding cell-specific markers. Large-scale gene expression analysis identified several differentially regulated genes in flow-sorted GFP+ Sertoli cells obtained from testis of control and Fshb-/- mice at 5 days of age. The top 25 networks identified by pathway analysis include those related to the cell cycle, cell survival and most importantly, carbohydrate and lipid metabolism and molecular transport. Several of the FSH-responsive genes identified in this study could serve as useful markers for Sertoli cell proliferation in normal physiology, toxicant-induced Sertoli cell/testis injury, and other pathological conditions. Our studies reveal that FSH-regulates macromolecular metabolism and molecular transport networks of genes in early postnatal Sertoli cells most likely in preparation for establishment of functional associations with germ cells to successfully coordinate spermatogenesis.

The solute carrier family 7 member 11 (SLC7A11) is regulated by LH/androgen and required for cystine/glutathione homeostasis in mouse Sertoli cells

Luteinizing hormone (LH) stimulates testosterone production from Leydig cells. Both LH and testosterone play important roles in spermatogenesis and male fertility. To identify LH - and testosterone - responsive transporter genes that play key roles in spermatogenesis, we performed large-scale gene expression analyses on testes obtained from adult control and Lhb knockout mice. We found a significant reduction in cystine/glutamate transporter encoding Slc7a11 mRNA in testes of Lhb null mice. We observed that Slc7a11/SLC7A11 expression was initiated pre-pubertally and developmentally regulated in mouse testis. Immunolocalization studies confirmed that SLC7A11 was mostly expressed in Sertoli cells in testes of control and germ cell-deficient mice. Western blot analyses indicated that SLC7A11 was significantly reduced in testes of mutant mice lacking either LH or androgen receptor selectively in Sertoli cells. Genetic and pharmacological rescue of Lhb knockout mice restored the testicular expression of Slc7a11 comparable to that observed in controls. Additionally, Slc7a11 mRNA was significantly suppressed upon Sertoli cell/testicular damage induced in mice by cadmium treatment. Knockdown of Slc7a11 in vitro in TM4 Sertoli cells or treatment of mice with sulfasalazine, a SLC7A11 inhibitor caused a significant reduction in intracellular cysteine and glutathione levels but glutamate content remained unchanged as determined by metabolomic analysis. Knockdown of Slc7a11 resulted in compensatory upregulation of other glutamate transporters belonging to the Slc1a family presumably to maintain intracellular glutamate levels. Collectively, our studies identified that SLC7A11 is an LH/testosterone-regulated transporter that is required for cysteine/glutathione but not glutamate homeostasis in mouse Sertoli cells.

Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

BackgroundA comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle.ResultsOur transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits.ConclusionsWe generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits.

Gene expression profiling of trout muscle during flesh quality recovery following spawning

BackgroundSexual maturation causes loss of fish muscle mass and deterioration of fillet quality attributes that prevent market success. We recently showed that fillet yield and flesh quality recover in female trout after spawning. To gain insight into the molecular mechanisms regulating flesh quality recovery, we used an Agilent-based microarray platform to conduct a large-scale time course analysis of gene expression in female trout white muscle from spawning to 33 weeks post-spawning.ResultsIn sharp contrast to the situation at spawning, muscle transcriptome of female trout at 33 weeks after spawning was highly similar to that of female trout of the same cohort that did not spawn, which is consistent with the post-spawning flesh quality recovery. Large-scale time course analysis of gene expression in trout muscle during flesh quality recovery following spawning led to the identification of approximately 3340 unique differentially expressed genes that segregated into four major clusters with distinct temporal expression profiles and functional categories. The first cluster contained approximately 1350 genes with high expression at spawning and downregulation after spawning and was enriched with genes linked to mitochondrial ATP synthesis, fatty acid catabolism and proteolysis. A second cluster of approximately 540 genes with transient upregulation 2 to 8 weeks after spawning was enriched with genes involved in transcription, RNA processing, translation, ribosome biogenesis and protein folding. A third cluster containing approximately 300 genes upregulated 4 to 13 weeks after spawning was enriched with genes encoding ribosomal subunits or regulating protein folding. Finally, a fourth cluster that contained approximately 940 genes with upregulation 8 to 24 weeks after spawning, was dominated by genes encoding myofibrillar proteins and extracellular matrix components and genes involved in glycolysis.ConclusionOverall, our study indicates that white muscle tissue restoration and flesh quality recovery after spawning are associated with transcriptional changes promoting anaerobic ATP production, muscle fibre hypertrophic growth and extracellular matrix remodelling. The generation of the first database of genes associated with post-spawning muscle recovery may provide insights into the molecular and cellular mechanisms controlling muscle yield and fillet quality in fish and provide a useful list of potential genetic markers for these traits.

Laser Capture Microdissection-Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research.

A major goal of methodologies related to large scale gene expression analyses is to initiate comprehensive information on transcript signatures in single cells within the tissue's anatomy. Until now, this could be achieved in a stepwise experimental approach: (1) identify the majority of transcripts in a single cell (single cell transcriptome); (2) provide information on transcripts on multiple cell subtypes in a complex sample (cell heterogeneity); and (3) give information on each cell's spatial location within the tissue (zonation transcriptomics). Such genetic information will allow construction of functionally relevant gene expression maps of single cells of a given anatomically defined tissue compartment and thus pave the way for subsequent analyses, including their epigenetic modifications. Until today these aims have not been achieved in the area of cardiovascular disease research though steps toward these goals become apparent: laser capture microdissection (LCM)-based mRNA expression microarrays of atherosclerotic plaques were applied to gain information on local gene expression changes during disease progression, providing limited spatial resolution. Moreover, while LCM-derived tissue RNA extracts have been shown to be highly sensitive and covers a range of 10-16,000 genes per array/small amount of RNA, its original promise to isolate single cells from a tissue section turned out not to be practicable because of the inherent contamination of the cell's RNA of interest with RNA from neighboring cells. Many shortcomings of LCM-based analyses have been overcome using single-cell RNA sequencing (scRNA-seq) technologies though scRNA-seq also has several limitations including low numbers of transcripts/cell and the complete loss of spatial information. Here, we describe a protocol toward combining advantages of both techniques while avoiding their flaws.

Large-scale analysis of longitudinal skin gene expression in systemic sclerosis reveals relationships of immune cell and fibroblast activity with skin thickness and a trend towards normalisation over time

ObjectivesDetermine relationships between skin gene expression and systemic sclerosis (SSc) clinical disease features, and changes in skin gene expression over time.MethodsA total of 339 forearm skin biopsies were obtained from...

Application of RNA Interference Technology to Acroporid Juvenile Corals

Numerous genes involved in calcification, algal endosymbiosis, and the stress response have been identified in corals by large-scale gene expression analysis, but functional analysis of those genes is lacking. There are few experimental examples of gene expression manipulation in corals, such as gene knockdown by RNA interference (RNAi). The purpose of this study is to establish an RNAi method for coral juveniles. As a first trial, the genes encoding green fluorescent protein (GFP, an endogenous fluorophore expressed by corals) and thioredoxin (TRX, a stress response gene) were selected for knockdown. Synthesized double-stranded RNAs (dsRNAs) corresponding to GFP and TRX were transformed into planula larvae by lipofection method to attempt RNAi. Real-time PCR analysis to verify knockdown showed that GFP and TRX expression levels tended to decrease with each dsRNA treatment (not significant). In addition, stress exposure experiments following RNAi treatment revealed that planulae with TRX knockdown exhibited increased mortality at elevated temperatures. In GFP-knockdown corals, decreased GFP fluorescence was observed. However, the effect of GFP-knockdown was confirmed only in the coral at the initial stages of larval metamorphosis into polyps, but not in planulae and 1 month-old budding polyps. This study showed that lipofection RNAi can be applied to coral planulae and polyps after settlement, and that this method provides a useful tool to modify expression of genes involved in stress tolerance and fluorescence emission of the corals.

HGF/MET Axis Induces Tumor Secretion of Tenascin-C and Promotes Stromal Rewiring in Pancreatic Cancer.

Simple SummaryIt has been previously shown that activation of the MET receptor by its ligand, the hepatocyte growth factor (HGF), modulates the tumor-stroma cross-talk in models of pancreatic cancer. We now wish to cast light on the molecular mechanisms by which this ligand/receptor pair sustains the interaction between cancer cells and the tumor microenviroment. To this end, we compared data obtained by large-scale analysis of gene expression in pancreatic cancer cells grown in the presence of HGF versus cells grown in the presence of HGF and treated with specific inhibitors of HGF/MET signaling. By clustering differentially expressed genes according to functional groups, we identified candidate genes involved in the process. Among these, tenascin C was selected due to its activity in sustaining the malignant phenotype. Our results highlight a new role for tenascin C, which could represent the operative arm through which MET promotes activation of the stromal compartment in pancreatic cancer.Pancreatic ductal adenocarcinoma is an aggressive tumor characterized by the presence of an abundant stromal compartment contributing significantly to the malignant phenotype. Pancreatic stellate cells are peculiar fibroblasts present in the stroma and represent the predominant source of extracellular matrix proteins, pro-inflammatory cytokines, and growth factors, including hepatocyte growth factor (HGF). Exploiting a co-culture system of human pancreatic stellate cells and cancer cells, we demonstrated that fibroblast activation was reduced upon HGF/MET axis inhibition. To unveil the signaling pathways sustaining stroma modulation orchestrated by MET activation in the tumor, we analyzed the gene expression profile in pancreatic cancer cells stimulated with HGF and treated with HGF/MET inhibitors. Transcriptome analysis showed that, among all the genes modulated by HGF, a subset of 125 genes was restored to the basal level following treatment with the inhibitors. By examining these genes via ingenuity pathway analysis, tenascin C emerged as a promising candidate linking MET signaling and tumor microenvironment. MET-dependent tenascin C modulation in pancreatic cancer cells was validated at RNA and protein levels both in vitro and in vivo. In conclusion, this work identifies tenascin C as a gene modulated by MET activation, suggesting a role in MET-mediated tumor-stroma interplay occurring during pancreatic tumor progression.

Dynamic and Temporal Transcriptomic Analysis Reveals Ferroptosis-Mediated Antileukemia Activity of S-Dimethylarsino-Glutathione: Insights into Novel Therapeutic Strategy

Dynamic and Temporal Transcriptomic Analysis Reveals Ferroptosis-Mediated Antileukemia Activity of S-Dimethylarsino-Glutathione: Insights into Novel Therapeutic Strategy

A large-scale genome-wide gene expression analysis in peripheral blood identifies very few differentially expressed genes related to antidepressant treatment and response in patients with major depressive disorder

A better understanding of the biological factors underlying antidepressant treatment in patients with major depressive disorder (MDD) is needed. We perform gene expression analyses and explore sources of variability in peripheral blood related to antidepressant treatment and treatment response in patients suffering from recurrent MDD at baseline and after 8 weeks of treatment. The study includes 281 patients, which were randomized to 8 weeks of treatment with vortioxetine (N = 184) or placebo (N = 97). To our knowledge, this is the largest dataset including both gene expression in blood and placebo-controlled treatment response measured by a clinical scale in a randomized clinical trial. We identified three novel genes whose RNA expression levels at baseline and week 8 are significantly (FDR < 0.05) associated with treatment response after 8 weeks of treatment. Among these genes were SOCS3 (FDR = 0.0039) and PROK2 (FDR = 0.0028), which have previously both been linked to depression. Downregulation of these genes was associated with poorer treatment response. We did not identify any genes that were differentially expressed between placebo and vortioxetine groups at week 8 or between baseline and week 8 of treatment. Nor did we replicate any genes identified in previous peripheral blood gene expression studies examining treatment response. Analysis of genome-wide expression variability showed that type of treatment and treatment response explains very little of the variance, a median of <0.0001% and 0.05% in gene expression across all genes, respectively. Given the relatively large size of the study, the limited findings suggest that peripheral blood gene expression might not be the best approach to explore the biological factors underlying antidepressant treatment.

The knowledge of chromosomal sex is important for large-scale analysis of gene expression

The aim of the study was to determine the sex of the fetus in gene expression data lacking this information using expression of the Y-linked genes, and to elucidate the difference between sex-chromosomal-linked gene expression between placental samples with XX and XY genotypes during pregnacy. We have detected 27 differentially expressed sex-chromosomes-linked genes. We have shown that, in most cases, the expression of genes from X-chromosomes in pregnancy carrying baby girls is higher than in pregnancy carrying baby boys, but there are exceptions to this pattern, which must be taken into account in large-scale studies of gene expression. The nature of the difference in gene expression during pregnancy carrying baby girls and boys (positive or ne gative difference) persists during pregnancy, but the magnitude of the difference may remain unchanged or decrease from the first to the third trimester. Taking sex dimorphism into account when analyzing large-scale gene expression data between trimesters of pregnancy increases the number of differentially expressed genes, which improves the informative value of the study and is important for elucidating the pathogenesis of pregnancy complications associated with placental dysfunction.

Transcriptomic data from the rat liver after five days of exposure to legacy or emerging brominated flame retardants.

Large-scale gene expression analysis of legacy* and emerging** brominated flame retardants were conducted in the male Harlan Sprague Dawley rat [1]. Each animal was dosed for 5 days with the chemical at concentrations of 0.1 – 1000 μmol/kg body weight per day. Following the last dose, a specimen of the left liver was removed for RNA extraction. The amplified RNA (aRNA) was fragmented and then hybridized to Affymetrix Rat Genome 230 2.0 Arrays. Each GeneChip® array was scanned using an Affymetrix GeneChip® Scanner 3000 7 G to generate raw expression level data (.CEL files). Statistical contrasts were used to find pairwise gene expression differences between the control group and each dose group using the R/maanova package [2]. The transcriptomic data can be used to provide insights into the degree of toxicity, toxic mechanisms, disease pathways activated by exposure, and for benchmark dose analysis. The gene expression data for each of the nine flame retardants discussed here accompanies the research article entitled, “Comparative Toxicity and Liver Transcriptomics of Legacy and Emerging Brominated Flame Retardants following 5-Day Exposure in the Rat” [1].* polybrominated diphenyl ether 47 (PBDE 47), decabromodiphenyl ether (decaBDE), hexabromocyclododecane (HBCD); ** 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (TBB); bis(2-ethylhexyl) tetrabromophthalate (TBPH); tetrabromobisphenol A-bis(2,3-dibromopropyl ether (TBBPA-DBPE); 1,2-bis(tribromophenoxy)ethane (BTBPE); decabromodiphenylethane (DBDPE); hexachlorocyclopentadienyl-dibromocyclooctane (HCDBCO).

Robust gene expression programs underlie recurrent cell states and phenotype switching in melanoma.

Melanoma cells can switch between a melanocytic and a mesenchymal-like state. Scattered evidence indicates that additional intermediate state(s) may exist. Here, to search for such states and decipher their underlying gene regulatory network (GRN), we studied 10 melanoma cultures using single-cell RNA sequencing (RNA-seq) as well as 26 additional cultures using bulk RNA-seq. Although each culture exhibited a unique transcriptome, we identified shared GRNs that underlie the extreme melanocytic and mesenchymal states and the intermediate state. This intermediate state is corroborated by a distinct chromatin landscape and is governed by the transcription factors SOX6, NFATC2, EGR3, ELF1 and ETV4. Single-cell migration assays confirmed the intermediate migratory phenotype of this state. Using time-series sampling of single cells after knockdown of SOX10, we unravelled the sequential and recurrent arrangement of GRNs during phenotype switching. Taken together, these analyses indicate that an intermediate state exists and is driven by a distinct and stable 'mixed' GRN rather than being a symbiotic heterogeneous mix of cells.

Older molecular brain age in severe mental illness.

Psychiatric disorders are associated with accelerated aging and enhanced risk for neurodegenerative disorders. Brain aging is associated with molecular, cellular and structural changes that are robust on the group-level, yet show substantial inter-individual variability. Here we assessed deviations in gene expression from normal age-dependent trajectories, and tested their validity as predictors of risk for major mental illnesses and neurodegenerative disorders. We performed large-scale gene expression and genotype analyses in postmortem samples of two frontal cortical brain regions from 214 control subjects aged 20–90 years. Individual estimates of “molecular age” were derived from age-dependent genes, identified by robust regression analysis. Deviation from chronological age was defined as “delta age”. Genetic variants associated with deviations from normal gene expression patterns were identified by expression quantitative trait loci (cis-eQTL) of age-dependent genes or genome-wide association study (GWAS) on delta age, combined into distinct polygenic risk scores (PRScis-eQTL and PRSGWAS), and tested for predicting brain disorders or pathology in independent postmortem expression datasets and clinical cohorts. In these validation datasets, molecular ages, defined by 68 and 76 age-related genes for two brain regions respectively, were positively correlated with chronological ages (r=0.88/0.91), elevated in bipolar disorder (BP) and schizophrenia (SCZ), and unchanged in major depressive disorder (MDD). Exploratory analyses in independent clinical datasets show that PRSs were associated with SCZ and MDD diagnostics, and with cognition in SCZ and pathology in Alzheimer’s disease (AD). These results suggest that older molecular brain aging is a common feature of severe mental illnesses and neurodegeneration.

Improving the diagnostic yield of exome- sequencing by predicting gene\u2013phenotype associations using large-scale gene expression analysis

The diagnostic yield of exome and genome sequencing remains low (8–70%), due to incomplete knowledge on the genes that cause disease. To improve this, we use RNA-seq data from 31,499 samples to predict which genes cause specific disease phenotypes, and develop GeneNetwork Assisted Diagnostic Optimization (GADO). We show that this unbiased method, which does not rely upon specific knowledge on individual genes, is effective in both identifying previously unknown disease gene associations, and flagging genes that have previously been incorrectly implicated in disease. GADO can be run on www.genenetwork.nl by supplying HPO-terms and a list of genes that contain candidate variants. Finally, applying GADO to a cohort of 61 patients for whom exome-sequencing analysis had not resulted in a genetic diagnosis, yields likely causative genes for ten cases.

Large-scale gene expression analysis reveals robust gene signatures for prognosis prediction in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. High mortality in LUAD motivates us to stratify the patients into high- and low-risk groups, which is beneficial for the clinicians to design a personalized therapeutic regimen. To robustly predict the risk, we identified a set of robust prognostic gene signatures and critical pathways based on ten gene expression datasets by the meta-analysis-based Cox regression model, 25 of which were selected as predictors of multivariable Cox regression model by MMPC algorithm. Gene set enrichment analysis (GSEA) identified the Aurora-A pathway, the Aurora-B pathway, and the FOXM1 transcription factor network as prognostic pathways in LUAD. Moreover, the three prognostic pathways were also the biological processes of G2-M transition, suggesting that hyperactive G2-M transition in cell cycle was an indicator of poor prognosis in LUAD. The validation in the independent datasets suggested that overall survival differences were observed not only in all LUAD patients, but also in those with a specific TNM stage, gender, and age group. The comprehensive analysis demonstrated that prognostic signatures and the prognostic model by the large-scale gene expression analysis were more robust than models built by single data based gene signatures in LUAD overall survival prediction.

Pan-cancer genomic analysis links 3'UTR DNA methylation with increased gene expression in T cells.

BackgroundInvestigations into the function of non-promoter DNA methylation have yielded new insights into the epigenetic regulation of gene expression. However, integrated genome-wide non-promoter DNA methylation and gene expression analyses across a wide number of tumour types and corresponding normal tissues have not been performed.MethodsTo investigate the impact of non-promoter DNA methylation on cancer pathogenesis, we performed a large-scale analysis of gene expression and DNA methylation profiles, finding enrichment in the 3’UTR DNA methylation positively correlated with gene expression. Filtering for genes in which 3’UTR DNA methylation strongly correlated with gene expression yielded a list of genes enriched for functions involving T cell activation.FindingsThe important immune checkpoint gene Havcr2 showed a substantial increase in 3’UTR DNA methylation upon T cell activation and subsequent upregulation of gene expression in mice. Furthermore, this increase in Havcr2 gene expression was abrogated by treatment with decitabine.InterpretationThese findings indicate that the 3’UTR is a functionally relevant DNA methylation site. Additionally, we show a potential novel mechanism of HAVCR2 regulation in T cells, providing new insights for modulating immune checkpoint blockade.

Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes

MotivationMedulloblastoma (MB) is a brain cancer predominantly arising in children. Roughly 70% of patients are cured today, but survivors often suffer from severe sequelae. MB has been extensively studied by molecular profiling, but often in small and scattered cohorts. To improve cure rates and reduce treatment side effects, accurate integration of such data to increase analytical power will be important, if not essential.ResultsWe have integrated 23 transcription datasets, spanning 1350 MB and 291 normal brain samples. To remove batch effects, we combined the Removal of Unwanted Variation (RUV) method with a novel pipeline for determining empirical negative control genes and a panel of metrics to evaluate normalization performance. The documented approach enabled the removal of a majority of batch effects, producing a large-scale, integrative dataset of MB and cerebellar expression data. The proposed strategy will be broadly applicable for accurate integration of data and incorporation of normal reference samples for studies of various diseases. We hope that the integrated dataset will improve current research in the field of MB by allowing more large-scale gene expression analyses.Availability and implementationThe RUV-normalized expression data is available through the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) and can be accessed via the GSE series number GSE124814.Supplementary information Supplementary data are available at Bioinformatics online.