Individual Transcript Levels Research Articles

Neuron-Glia-Ratio-Like Approach Evidenced for Limited Variability and In-Aggregate Circadian Shifts in Cortical Cell-Specific Transcriptomes.

Regardless of shifts in levels of individual transcripts, it remains elusive whether natural variability in cell-specific transcriptomes within the cerebral cortex is limited in aggregate. It is also unclear whether cortical cell-specific transcriptomes might change dynamically in absence of cell number changes. Total variation in neuron- and glia-specific in-aggregate transcriptomes could be identified in a model-free way via glia-neuron ratio approach, by univariate median-to-median ratios comparing integral levels of cell-specific transcripts within a tissue sample. When deleterious, regenerative or developmental events affecting cortical cell numbers were subtle, median-to-median ratios demonstrated within-group variability not exceeding <20-25% in most cases. These levels of total variability might be explained in part by limited (~5-10%) circadian and stress-induced shifts in cell-specific cortical transcriptomes. Relevant in-aggregate transcriptomic alterations were identified after shifts in cell numbers induced by well-validated deleterious events including ischemia, traumatic injury, microglia's activation/depletion or specific mutations. Cortical median-to-median ratios also follow naturally occurring changes in the numbers of excitatory, inhibitory neurons and glial cells during perinatal brain development. These findings characterize cortical cell-specific transcriptomes as subjects to circadian shifts and lifetime events, urging the importance of reporting full details on an origin of any transcriptomic sample collected in vivo.

ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data.

Exitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for the detection and annotation of exitrons in long-read RNA-seq data. Here, we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the individual transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. In addition, ScanExitronLR optionally reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data. ScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index. Supplementary data are available at Bioinformatics online.

Allelic Gene Polymorphisms Suspected to Diversify the Individual Early Metabolic Response Upon Influenza H3N2 and SARS-CoV-2 Infections

Allelic Gene Polymorphisms Suspected to Diversify the Individual Early Metabolic Response Upon Influenza H3N2 and SARS-CoV-2 Infections

Transcriptomic score: A biomarker index of Alzheimer’s risk and resilience

AbstractBackgroundOne definition of resilience is the absence of disease despite high levels of risk. And in most cases, risk itself is best quantified by a multivariate profile rather than a single risk factor. Thus, multivariate risk profiles may be most appropriate for defining risk and resilience. RNA expression may serve as a risk biomarker, but no method has been proposed to build a whole‐transcriptome risk index of Alzheimer’s disease (AD) that could identify resilient individuals at the highest transcriptomic risk. Here, we derived a novel method for transcriptome‐wide gene expression data called “transcriptomic risk score” (TRS). We also employed the algorithm to build a “transcriptomic resilience score” (TReS) that offsets that risk.MethodAnalogous to a polygenic risk score, TRS is a weighted rank‐sum statistic that represents a subject’s relative expression level across the transcriptome, where the standardized beta coefficients are used as weights. We leveraged the TRS approach on peripheral blood gene expression profiles of 364 normal controls and 188 AD cases from ADNI and AddNeuroMed batch 1. Using TRSas a means of risk quantification, we then identified resilient normal controls as those with the highest percentiles of risk. High‐risk AD cases with matched TRSs range were retained for comparison. Expression levels of individual transcripts not included in the best‐fit TRS were contrasted between the high‐risk normal controls and high‐risk AD cases using mixed‐effect linear models. A TReS was derived using the residual transcriptomic variation that buffers against the transcriptomic risk. The association between TReS and case status was evaluated using a logistic regression model.ResultThe derived TReS differentiated resilient subjects (high‐risk normal controls) and high‐risk AD cases in independent replication samples (216 normal controls and 223 AD cases), with significant differentiation seen at all evaluated p‐value bins and a maximum of 3% variance accounted for at a p‐value threshold of 0.1.ConclusionThis analysis indicated that TRS and TReS analysis of blood has the potential of facilitating the understanding of phenotypic variability and improving clinically useful biomarker profiles for AD.

The Dynamic Regulation of mRNA Translation and Ribosome Biogenesis During Germ Cell Development and Reproductive Aging.

The regulation of mRNA translation, both globally and at the level of individual transcripts, plays a central role in the development and function of germ cells across species. Genetic studies using flies, worms, zebrafish and mice have highlighted the importance of specific RNA binding proteins in driving various aspects of germ cell formation and function. Many of these mRNA binding proteins, including Pumilio, Nanos, Vasa and Dazl have been conserved through evolution, specifically mark germ cells, and carry out similar functions across species. These proteins typically influence mRNA translation by binding to specific elements within the 3′ untranslated region (UTR) of target messages. Emerging evidence indicates that the global regulation of mRNA translation also plays an important role in germ cell development. For example, ribosome biogenesis is often regulated in a stage specific manner during gametogenesis. Moreover, oocytes need to produce and store a sufficient number of ribosomes to support the development of the early embryo until the initiation of zygotic transcription. Accumulating evidence indicates that disruption of mRNA translation regulatory mechanisms likely contributes to infertility and reproductive aging in humans. These findings highlight the importance of gaining further insights into the mechanisms that control mRNA translation within germ cells. Future work in this area will likely have important impacts beyond germ cell biology.

Network preservation reveals shared and unique biological processes associated with chronic alcohol abuse in NAc and PFC.

Chronic alcohol abuse has been linked to the disruption of executive function and allostatic conditioning of reward response dysregulation in the mesocorticolimbic pathway (MCL). Here, we analyzed genome-wide mRNA and miRNA expression from matched cases with alcohol dependence (AD) and controls (n = 35) via gene network analysis to identify unique and shared biological processes dysregulated in the prefrontal cortex (PFC) and nucleus accumbens (NAc). We further investigated potential mRNA/miRNA interactions at the network and individual gene expression levels to identify the neurobiological mechanisms underlying AD in the brain. By using genotyped and imputed SNP data, we identified expression quantitative trait loci (eQTL) uncovering potential genetic regulatory elements for gene networks associated with AD. At a Bonferroni corrected p≤0.05, we identified significant mRNA (NAc = 6; PFC = 3) and miRNA (NAc = 3; PFC = 2) AD modules. The gene-set enrichment analyses revealed modules preserved between PFC and NAc to be enriched for immune response processes, whereas genes involved in cellular morphogenesis/localization and cilia-based cell projection were enriched in NAc modules only. At a Bonferroni corrected p≤0.05, we identified significant mRNA/miRNA network module correlations (NAc = 6; PFC = 4), which at an individual transcript level implicated miR-449a/b as potential regulators for cellular morphogenesis/localization in NAc. Finally, we identified eQTLs (NAc: mRNA = 37, miRNA = 9; PFC: mRNA = 17, miRNA = 16) which potentially mediate alcohol's effect in a brain region-specific manner. Our study highlights the neurotoxic effects of chronic alcohol abuse as well as brain region specific molecular changes that may impact the development of alcohol addiction.

P.324RNAscope multiplex in situ hybridisation reveals unique patterns of dystrophin isoform expression in the developing mammalian foetus

At 2.4Mb in length, the dystrophin gene is the largest in the genome. The gene has 79 exons and contains multiple internal promoters, resulting in a variety of N-terminally truncated proteins of otherwise near-identical sequence: the major isoforms being dp260, dp140, and dp71. These isoforms are believed to play unique cellular roles, and consequently have tissue-specific expression patterns (260 in the retina, 140 in the brain and 71 in many tissues). Dp427 is the only isoform expressed in skeletal muscle -where the resultant dystrophin protein plays a key role in muscle membrane integrity and signalling- but even this isoform is also expressed in specific regions of the brain. The shared sequence identity at both mRNA and protein level makes study of these unique isoforms challenging and limits the utility of immunohistochemistry approaches. RNAscope is a novel in-situ hybridisation technique that offers high (individual transcript-level) resolution and sensitivity, and the ability to multiplex, resolving multiple transcript species at sub-cellular levels. We here use this technique on whole mount canine 30 day old foetuses with probes designed to the same transcript, targeting 5′, central and 3′ sequences of the long dp427 mRNA, each either present or absent in a given isoform: dp71 will bind the 3′ probe alone, dp140 the 3′ and the central, and dp427 will bind all three. We can thus detect and distinguish multiple dystrophin mRNA isoforms at subcellular histological levels to gain unique insights into their expression and distribution in the developing mammal. Our data reveals the potential of this novel technology: dp427 is found prominently expressed in developing skeletal and smooth muscle, but is also present at high levels in specific hindbrain regions, while expression of dp140 appears restricted to the developing cortical plate and deeper midbrain. Dp71 is more widespread, particularly prominent in myotendinous junctions, cartilage and epithelial layers.

Systemic response to rupture of intracranial aneurysms involves expression of specific gene isoforms

BackgroundRupture of an intracranial aneurysm (IA) causes a systemic response that involves an immune/inflammatory reaction. Our previous study revealed a downregulation of genes related to T lymphocytes and an upregulation of genes related to monocytes and neutrophils after IA rupture. It remains unknown whether that resulted from alterations in transcription or cell count. We sought to characterize the systemic response to IA rupture through analysis of transcript expression profiles in peripheral blood cells. We also investigated effects of IA rupture on the composition of mononuclear cells in peripheral blood.MethodsWe included 19 patients in the acute phase of IA rupture (RAA, first 72 h), 20 patients in the chronic phase (RAC, 3–15 months), and 20 controls. Using deep transcriptome sequencing, we analyzed the expression of protein-coding and noncoding RNAs. Expression levels, transcript biotypes, alternative splicing and other features of the regulated transcripts were studied. A functional analysis was performed to determine overrepresented ontological groups among gene expression profiles. Flow cytometry was used to analyze alterations in the level of mononuclear leukocyte subpopulations.ResultsComparing RAA and controls, we identified 491 differentially expressed transcripts (303 were downregulated, and 188 were upregulated in RAA). The results indicate that the molecular changes in response to IA rupture occur at the level of individual transcripts. Functional analysis revealed that the most impacted biological processes are related to regulation of lymphocyte activation and toll-like receptor signaling pathway. Differences between RAC and controls were less prominent. Analysis of leukocyte subsets revealed a significantly decreased number of CD4+ lymphocytes and increase of classical and intermediate monocytes in RAA patients compared to controls.ConclusionsIA rupture in the acute phase strongly influences the transcription profiles of peripheral blood cells as well as the composition of mononuclear cells. A specific pattern of gene expression alteration was found, suggesting a depression of lymphocyte response and enhancement of monocyte activity.

P106 INFLAMMATORY BOWEL DISEASE CHARACTERIZATION OF SHARED AND UNIQUE ALTERATIONS IN IMMUNE CELLS, MOLECULAR PATHWAYS, AND TRANSCRIPTS

Inflammatory Bowel Disease (IBD), characterized by chronic inflammation of the intestine, is propelled by alterations in the immune profile and inflammatory mediators within affected tissue. However, as IBD pathobiology is heterogeneous in nature, a more comprehensive understanding of common and distinct variations within individuals is required for more precise diagnostic methods and tailored therapeutic regimens. Using publicly available IBD transcriptomes from American and European patient cohorts, we aimed to elucidate alterations, both similar and distinct, in the immune profile, molecular pathways, and transcripts in affected tissue. Whole transcriptomes from healthy controls, active or non-active IBD cohorts were utilized (~500 patient endoscopic biopsies, NCBI GEO). Immune profiles were assessed by the core LM22 signature (CIBERSORT) (p<0.05). Pathway analysis was performed using Ingenuity Pathway Analysis (IPA, Qiagen) (p<0.05). In healthy human colon, immune cell profiling revealed a consistent abundance of B cells (plasma), T cells (CD4 memory resting), mast cells (resting) and macrophages (M2). In active-IBD involved tissue, we observed substantial alterations in the immune landscape including increased neutrophils, T CD4 memory activated cells, active dendritic cells, M0/M1 macrophages, and B naïve cells, as well as noticeably reduced T CD8 cells, Tregs, B memory cells, dendritic resting cells, and M2 macrophages (Fig 1). This immune signature was similarly observed across IBD cohorts with the exception of eosinophils, T CD4 resting cells, and Tγδ cells. In uninvolved tissue from active-IBD, the immune cell composition was similar to healthy control with the exception of elevated T CD4 memory activated cells and reduced Tregs (Fig 1). Next, relative to healthy control, IPA of differentially expressed transcripts from IBD cohorts revealed similarly altered pathways linked to bacterial signaling (TLR, LPS/IL-1, fMLP), inflammation (Th1/2 responses, chemokine and cytokine), inflammasome activation, and activated cell signaling (NFkB, ERK/MAPK, p38, iNOS, PI3K). However, pathways that differed among IBD cohorts included select signaling linked to inflammation (IL17A, OX40), growth (TGFb, PTEN, p53), and metabolic (PPARa, leptin) functions. At the individual transcript level, we found several novel transcripts consistently altered in IBD affected tissues among cohorts including KYNU, LPCAT1, CLDN8 as well as those differentially altered including MASPIN, FGFR2, AGRP, INSR. We determined the global immune cell landscape and molecular pathways that were similarly and differentially altered, highlighting the complex, heterogeneic nature of IBD pathobiology. Further utilization of this approach may provide clues for development of precise diagnostic and personalized therapeutic intervention for IBD patients. Figure 1. Alterations in the immune cell landscape in healthy control, active-IBD-involved, and active-IBD-noninvolved tissue samples. Graphs represent changes in relative abundances of subsets of B cells, T cells, dendritic cells, macrophages, mast cells, and neutrophils (GSE38713, *,#p<0.05, *compared to healthy control, #compared to active-IBD-involved) (CIBERSORT, cibersort.stanford.edu).

P106 INFLAMMATORY BOWEL DISEASE CHARACTERIZATION OF SHARED AND UNIQUE ALTERATIONS IN IMMUNE CELLS, MOLECULAR PATHWAYS, AND TRANSCRIPTS

Inflammatory Bowel Disease (IBD), characterized by chronic inflammation of the intestine, is propelled by alterations in the immune profile and inflammatory mediators within affected tissue. However, as IBD pathobiology is heterogeneous in nature, a more comprehensive understanding of common and distinct variations within individuals is required for more precise diagnostic methods and tailored therapeutic regimens. Using publicly available IBD transcriptomes from American and European patient cohorts, we aimed to elucidate alterations, both similar and distinct, in the immune profile, molecular pathways, and transcripts in affected tissue. Whole transcriptomes from healthy controls, active or non-active IBD cohorts were utilized (∼500 patient endoscopic biopsies, NCBI GEO). Immune profiles were assessed by the core LM22 signature (CIBERSORT) (p<0.05). Pathway analysis was performed using Ingenuity Pathway Analysis (IPA, Qiagen) (p<0.05). In healthy human colon, immune cell profiling revealed a consistent abundance of B cells (plasma), T cells (CD4 memory resting), mast cells (resting) and macrophages (M2). In active-IBD involved tissue, we observed substantial alterations in the immune landscape including increased neutrophils, T CD4 memory activated cells, active dendritic cells, M0/M1 macrophages, and B naïve cells, as well as noticeably reduced T CD8 cells, Tregs, B memory cells, dendritic resting cells, and M2 macrophages (Fig 1). This immune signature was similarly observed across IBD cohorts with the exception of eosinophils, T CD4 resting cells, and Tγδ cells. In uninvolved tissue from active-IBD, the immune cell composition was similar to healthy control with the exception of elevated T CD4 memory activated cells and reduced Tregs (Fig 1). Next, relative to healthy control, IPA of differentially expressed transcripts from IBD cohorts revealed similarly altered pathways linked to bacterial signaling (TLR, LPS/IL-1, fMLP), inflammation (Th1/2 responses, chemokine and cytokine), inflammasome activation, and activated cell signaling (NFkB, ERK/MAPK, p38, iNOS, PI3K). However, pathways that differed among IBD cohorts included select signaling linked to inflammation (IL17A, OX40), growth (TGFb, PTEN, p53), and metabolic (PPARa, leptin) functions. At the individual transcript level, we found several novel transcripts consistently altered in IBD affected tissues among cohorts including KYNU, LPCAT1, CLDN8 as well as those differentially altered including MASPIN, FGFR2, AGRP, INSR. We determined the global immune cell landscape and molecular pathways that were similarly and differentially altered, highlighting the complex, heterogeneic nature of IBD pathobiology. Further utilization of this approach may provide clues for development of precise diagnostic and personalized therapeutic intervention for IBD patients.

Abstract 2293: Outstanding chromosomal expression patterning in human cancers

Abstract Cancer transcriptome is an effect of abnormal genetic and/or epigenetic regulation. In the past, transcriptome was studied at the level of individual transcripts for their differential expression. Spatial gene expression patterns along chromosomes were not yet characterized for cancer. We hypothesized that gene expression patterning is not randomly distributed along the chromosomes in cancer versus normal tissues. We analyzed cancer transcriptome from the National Cancer Institute Genomic Data Commons, and identified genomic regions with significant shifts in expression from normal tissues to tumors. We used a novel highly efficient method in the Ckmeans.1d.dp package for clustering genes by chromosomal location and expression level. We identified two chromosomal zones of note that exhibit similar expression patterns across several cancer types. In breast, lung, liver, and esophageal cancers, a zone near 6p22.2 contains genes that are similarly highly upregulated in tumor tissues compared to matched normal tissues. This zone contains a group of histone cluster 1 genes, among which are 14 known cancer genes. In colorectal, lung, liver, and esophageal cancers, a zone on 14q32.33 exhibits either heavy up- or downregulation, dependent on the specific cancer. This zone is rich in immunoglobulin heavy variable genes. Table 1 lists genomic zones of note specific to six cancer types. Our study provides an atlas of outstanding chromosomal expression patterning that can be used as markers for cancer in general and also for specific cancer types. Table 1. Outstanding genomic zones specific to six human cancer types.Cancer type Chr:start-end (Mb) Cytogenetic band # Matched tumor/normal pairsBreastchr2:88-92p11.2112Colorectalchr7:141-146q3541Esophagealchr11:7-12p15.48Kidneychr12:85-91q21.3323Liverchr8:15-22p2250Lungchr8:121-126q24.1357 Citation Format: Spencer Barnes, Mingzhou Song. Outstanding chromosomal expression patterning in human cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2293.

Molecular Signatures of Psychosocial Stress and Cognition Are Modulated by Chronic Lithium Treatment.

Chronic psychosocial stress is an important environmental risk factor of psychiatric diseases such as schizophrenia. Social defeat in rodents has been shown to be associated with maladaptive cellular and behavioral consequences including cognitive impairments. Although gene expression changes upon psychosocial stress have been described, a comprehensive transcriptome profiling study at the global level in precisely defined hippocampal subregions which are associated with learning has been lacking. In this study, we exposed adult C57Bl/6N mice for 3 weeks to "resident-intruder" paradigm and combined laser capture microdissection with microarray analyses to identify transcriptomic signatures of chronic psychosocial stress in dentate gyrus and CA3 subregion of the dorsal hippocampus. At the individual transcript level, we detected subregion specific stress responses whereas gene set enrichment analyses (GSEA) identified several common pathways upregulated upon chronic psychosocial stress related to proteasomal function and energy supply. Behavioral profiling revealed stress-associated impairments most prominent in fear memory formation which was prevented by chronic lithium treatment. Thus, we again microdissected the CA3 region and performed global transcriptome analysis to search for molecular signatures altered by lithium treatment in stressed animals. By combining GSEA with unsupervised clustering, we detected pathways that are regulated by stress and lithium in the CA3 region of the hippocampus including proteasomal components, oxidative phosphorylation, and anti-oxidative mechanisms. Our study thus provides insight into hidden molecular phenotypes of chronic psychosocial stress and lithium treatment and proves a beneficial role for lithium treatment as an agent attenuating negative effects of psychosocial stress on cognition.

Transcriptomic responses to prion disease in rats.

BackgroundPrions diseases are fatal neurodegenerative diseases of mammals. While the molecular responses to prion infection have been extensively characterized in the laboratory mouse, little is known in other rodents. To explore these responses and make comparisons, we generated a prion disease in the laboratory rat by successive passage beginning with mouse RML prions.ResultsWe describe the accumulation of rat prions, associated pathology and the transcriptional impact throughout the disease course. Comparative transcriptional profiling between laboratory mice and rats suggests that similar molecular and cellular processes are unfolding in response to prion infection. At the level of individual transcripts, however, variability exists between mice and rats and many genes deregulated by prion infection in mice are not affected in rats.ConclusionOur findings detail the molecular responses to prion disease in the rat and highlight the usefulness of comparative approaches to understanding neurodegeneration and prion diseases in particular.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1884-7) contains supplementary material, which is available to authorized users.

AtRTD - a comprehensive reference transcript dataset resource foraccurate quantification of transcript-specific expression in Arabidopsis thaliana.

Summary RNA‐sequencing (RNA‐seq) allows global gene expression analysis at the individual transcript level. Accurate quantification of transcript variants generated by alternative splicing (AS) remains a challenge. We have developed a comprehensive, nonredundant Arabidopsis reference transcript dataset (AtRTD) containing over 74 000 transcripts for use with algorithms to quantify AS transcript isoforms in RNA‐seq.The AtRTD was formed by merging transcripts from TAIR10 and novel transcripts identified in an AS discovery project. We have estimated transcript abundance in RNA‐seq data using the transcriptome‐based alignment‐free programmes Sailfish and Salmon and have validated quantification of splicing ratios from RNA‐seq by high resolution reverse transcription polymerase chain reaction (HR RT‐PCR).Good correlations between splicing ratios from RNA‐seq and HR RT‐PCR were obtained demonstrating the accuracy of abundances calculated for individual transcripts in RNA‐seq.The AtRTD is a resource that will have immediate utility in analysing Arabidopsis RNA‐seq data to quantify differential transcript abundance and expression.

Expression of cell cycle-regulated genes and prostate cancer prognosis in a population-based cohort.

Prostate cancer (PCa) is clinically and biologically heterogeneous, making it difficult to predict at detection whether it will take an indolent or aggressive disease course. Cell cycle-regulated genes may be more highly expressed in actively dividing cells, with transcript levels reflecting tumor growth rate. Here, we evaluated expression of cell cycle genes in relation to PCa outcomes in a population-based cohort. Gene expression data were generated from tumor tissues obtained at radical prostatectomy for 383 population-based patients (12.3-years average follow-up). The overall mean and individual transcript levels of 30 selected cell cycle genes was compared between patients with no evidence of recurrence (73%) and those who recurred (27%) or died (7%) from PCa. The multivariate adjusted hazard ratio (HR) for a change from the 25th to 75th percentile of mean gene expression level (range 8.02-10.05) was 1.25 (95%CI 0.96-1.63; P = 0.10) for PCa recurrence risk, and did not vary substantially by Gleason score, TMPRSS2-ERG fusion status, or family history of PCa. For lethal PCa, the HR for a change (25th to 75th percentile) in mean gene expression level was 2.04 (95%CI 1.26-3.31; P = 0.004), adjusted for clinicopathological variables. The ROC curve for mean gene expression level alone (AUC = 0.740) did not perform as well as clinicopathological variables alone (AUC = 0.803) for predicting lethal PCa, and the addition of mean gene expression to clinicopathological variables did not substantially improve prediction (AUC = 0.827; P = 0.18). Higher TK1 expression was strongly associated with both recurrent (P = 6.7 × 10(-5)) and lethal (P = 6.4 × 10(-6)) PCa. Mean expression level for 30 selected cell cycle-regulated genes was unrelated to recurrence risk, but was associated with a twofold increase in risk of lethal PCa. However, gene expression had less discriminatory accuracy than clinical variables alone for predicting lethal events. Transcript levels for several genes in the panel were significantly overexpressed in lethal versus non-recurrent PCa.

Contrasting gene expression patterns induced by levodopa and pramipexole treatments in the rat model of Parkinson's disease

Whether the treatment of Parkinson's disease has to be initiated with levodopa or a D2 agonist like pramipexole remains debatable. Levodopa is more potent against symptoms than D2 agonists, but D2 agonists are less prone to induce motor complications and may have neuroprotective effects. Although regulation of plastic changes in striatal circuits may be the key to their different therapeutic potential, the gene expression patterns induced by de novo treatments with levodopa or D2 agonists are currently unknown. By studying the whole striatal transcriptome in a rodent model of early stage Parkinson's disease, we have identified the gene expression patterns underlying therapeutically comparable chronic treatments with levodopa or pramipexole. Despite the overall relatively small size of mRNA expression changes at the level of individual transcripts, our data show a robust and complete segregation of the transcript expression patterns induced by both treatments. Moreover, transcripts related to oxidative metabolism and mitochondrial function were enriched in levodopa-treated compared to vehicle-treated and pramipexole-treated animals, whereas transcripts related to olfactory transduction pathways were enriched in both treatment groups compared to vehicle-treated animals. Thus, our data reveal the plasticity of genetic striatal networks possibly contributing to the therapeutic effects of the most common initial treatments for Parkinson's disease, suggesting a role for oxidative stress in the long term complications induced by levodopa and identifying previously overlooked signaling cascades as potentially new therapeutic targets.

FECUND EU-Project: Optimisation of early reproductive success in dairy cattle through the definition of new trait and improved reproductive biotechnology

at germinal vesicle (GV) and MII stage, we employed Bovine oligonucleotide microarrays (Missouri Consortium, http://www.ag.arizona.edu/microarray/BOM.html). Following normalization of the microarray data, analysis revealed changes in the level of 61 transcripts (≥1.4 fold) between the two groups, corresponding to 50 up-regulated and 11 down-regulated transcripts in MF oocytes compared to SF oocytes. The gene expression data were classified according to gene ontology, themajority of these genes was associated with regulation of transcription, translation, cell cycle, and mitochondrial activity. Subsets of 15 differentially expressed genes were validated by quantitative real-time RT-PCR. Before maturation, significant differences (p<0.01) were revealed at the level of TAF1A, MTRF1L and ATP5C1 between MF and SF oocytes, the differences in other genes (NGDN, PRPF18 and ATP5F1) were on borderline of statistical difference. After maturation, real time RT-PCR quantification revealed different regulation of individual transcripts. The level of transcripts remained stable forATP5F1andBRD7 inMFandSFoocytes; in the case of TAF1A, the level of transcript remained stable only in SF oocytes. In all other investigated genes the quantification revealed a substantial drop in the level of individual transcripts in MF and SF oocytes after maturation. These results suggest that developmental competency may be quantitative trait, which is dependent on small changes in the RNA transcription profiles of many genes.

Flexible analysis of RNA-seq data using mixed effects models

Most methods for estimating differential expression from RNA-seq are based on statistics that compare normalized read counts between treatment classes. Unfortunately, reads are in general too short to be mapped unambiguously to features of interest, such as genes, isoforms or haplotype-specific isoforms. There are methods for estimating expression levels that account for this source of ambiguity. However, the uncertainty is not generally accounted for in downstream analysis of gene expression experiments. Moreover, at the individual transcript level, it can sometimes be too large to allow useful comparisons between treatment groups. In this article we make two proposals that improve the power, specificity and versatility of expression analysis using RNA-seq data. First, we present a Bayesian method for model selection that accounts for read mapping ambiguities using random effects. This polytomous model selection approach can be used to identify many interesting patterns of gene expression and is not confined to detecting differential expression between two groups. For illustration, we use our method to detect imprinting, different types of regulatory divergence in cis and in trans and differential isoform usage, but many other applications are possible. Second, we present a novel collapsing algorithm for grouping transcripts into inferential units that exploits the posterior correlation between transcript expression levels. The aggregate expression levels of these units can be estimated with useful levels of uncertainty. Our algorithm can improve the precision of expression estimates when uncertainty is large with only a small reduction in biological resolution. We have implemented our software in the mmdiff and mmcollapse multithreaded C++ programs as part of the open-source MMSEQ package, available on https://github.com/eturro/mmseq.

The ethylene response factor (ERF) genes from Tamarix hispida respond to salt, drought and ABA treatment

The ethylene response factor (ERF) genes are a subfamily of transcription factors containing a single AP2/ERF domain, which play crucial roles in plant development and response to biotic and abiotic stresses. In the present study, 16 ERF genes (named ThERF1–ThERF16) were isolated from Tamarix hispida, and their expression in response to salt, drought and ABA treatment was investigated using real-time RT-PCR. The results showed that all 16 ERFs are expressed in root, stem and leaf tissues, but the individual transcript levels vary strongly in roots, stem or leaves. Among these ThERFs, ThERF1 is the most abundant in roots, stems and leaves, indicating that it may play a more important physiological role than the other ThERF genes. The 16 ThERF genes are all highly differentially expressed in leaves, stems or roots under salt and drought stress, demonstrating that they are involved in the salt and drought stress responses. Under ABA treatment, expression of the ThERF genes was mainly down-regulated in roots, but induced in leaves or stems, suggesting that they are also involved in the ABA stress response. These results strongly suggest that ThERFs are abiotic stress response genes that may play important roles in the stress tolerance of T. hispida.

Childhood maltreatment is associated with distinct genomic and epigenetic profiles in posttraumatic stress disorder

Childhood maltreatment is likely to influence fundamental biological processes and engrave long-lasting epigenetic marks, leading to adverse health outcomes in adulthood. We aimed to elucidate the impact of different early environment on disease-related genome-wide gene expression and DNA methylation in peripheral blood cells in patients with posttraumatic stress disorder (PTSD). Compared with the same trauma-exposed controls (n = 108), gene-expression profiles of PTSD patients with similar clinical symptoms and matched adult trauma exposure but different childhood adverse events (n = 32 and 29) were almost completely nonoverlapping (98%). These differences on the level of individual transcripts were paralleled by the enrichment of several distinct biological networks between the groups. Moreover, these gene-expression changes were accompanied and likely mediated by changes in DNA methylation in the same loci to a much larger proportion in the childhood abuse (69%) vs. the non-child abuse-only group (34%). This study is unique in providing genome-wide evidence of distinct biological modifications in PTSD in the presence or absence of exposure to childhood abuse. The findings that nonoverlapping biological pathways seem to be affected in the two PTSD groups and that changes in DNA methylation appear to have a much greater impact in the childhood-abuse group might reflect differences in the pathophysiology of PTSD, in dependence of exposure to childhood maltreatment. These results contribute to a better understanding of the extent of influence of differences in trauma exposure on pathophysiological processes in stress-related psychiatric disorders and may have implications for personalized medicine.