scholarly journals Declining RNA integrity in control autopsy brain tissue is robustly and asymmetrically associated with selective neuronal mRNA signal loss

2021 ◽  
Author(s):  
Eleanor S. Johnson ◽  
Kendra E. Stenzel ◽  
Sangderk Lee ◽  
Eric M. Blalock
Keyword(s):  
Gene Expression ◽  
Brain Tissue ◽  
Transcriptional Profiling ◽  
Bioinformatic Analysis ◽  
Rna Degradation ◽  
Signal Loss ◽  
Human Brain Tissue ◽  
Floor Effect ◽  
Rna Integrity ◽  
Expression Pathways

AbstractRNA integrity numbers (RINs) are a standardized method for semi-quantification of RNA degradation, and are used in quality control prior to transcriptional profiling analysis. Recent work has demonstrated that RINs are associated with downstream transcriptional profiling, and correction procedures are typically employed in bioinformatic analysis pipelines to attempt to control for RIN’s influence on gene expression. However, relatively little work has been done to determine whether RIN’s influence is random, or is specifically targeted to a subset of mRNAs. We tested the hypothesis that RIN would be associated with a robust transcriptional profile seen across multiple studies.To test this, we downloaded subsets of raw transcriptional data from six published studies. We only included control, non-pathological post-mortem human brain tissue (n = 383 samples) in which independent subjects’ RIN values were also reported. A robust set of mRNAs consistently and significantly correlated with RIN across multiple studies, appearing to be selectively degraded as RIN declines. Many of the affected gene expression pathways are related to neurons (e.g., vesicle, mRNA transport, synapse, and mitochondria), suggesting that neuronal synaptic mRNA may be particularly vulnerable to degradation. Subsequent analysis of the relationship between RIN and vulnerable mRNA expression revealed most of the decay occurred over a relatively narrow RIN range of 7.2-8.6, with RIN values > 8.6 showing a ceiling effect, and those < 7.2 showing a floor effect on gene expression. Our data suggests that the RIN effect is pathway selective and non-linear, which may be an important consideration for current bioinformatic RIN correcting procedures, particularly in datasets in which declining RIN is confounded with a pathology under study (e.g., in Alzheimer’s disease).

scholarly journals Postmortem interval effect on RNA and gene expression in human brain tissue

2010 ◽  
Vol 12 (4) ◽  
pp. 311-318 ◽  
Author(s):  
Alex C. Birdsill ◽  
Douglas G. Walker ◽  
LihFen Lue ◽  
Lucia I. Sue ◽  
Thomas G. Beach
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Brain Tissue ◽  
Postmortem Interval ◽  
Human Brain Tissue ◽  
Interval Effect

scholarly journals Pathogenic LRRK2 Mutations Do Not Alter Gene Expression in Cell Model Systems or Human Brain Tissue

PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e22489 ◽  
Author(s):  
Michael J. Devine ◽  
Alice Kaganovich ◽  
Mina Ryten ◽  
Adamantios Mamais ◽  
Daniah Trabzuni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Brain Tissue ◽  
Cell Model ◽  
Model Systems ◽  
Human Brain Tissue

scholarly journals Limited predictability of postmortem human brain tissue quality by RNA integrity numbers

2016 ◽  
Vol 138 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Kai-C. Sonntag ◽  
George Tejada ◽  
Sivan Subburaju ◽  
Sabina Berretta ◽  
Francine M. Benes ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Tissue ◽  
Human Brain Tissue ◽  
Tissue Quality ◽  
Postmortem Human Brain ◽  
Rna Integrity

Effect of Sample Preservation Method on Gene Expression and RNA Integrity in Acute Myelogenous Leukemia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 3018-3018 ◽  
Author(s):  
Jonathan Ben-Ezra ◽  
Amy C. Ladd ◽  
Catherine I. Dumur ◽  
Kellie J. Archer ◽  
Alden Chesney ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myelogenous Leukemia ◽  
Mononuclear Cells ◽  
Rna Degradation ◽  
Myelogenous Leukemia ◽  
Synthesis Product ◽  
Data Set ◽  
Rna Integrity ◽  
Preservation Method ◽  
Acute Myelogenous

Abstract Cryopreservation of patient bone marrow specimens allows for future purification of tumor cells for research or diagnostic purposes. It has not been determined whether this practice causes significant changes in gene expression. In order to evaluate this, we performed microarray analysis (Affymetrix U133A and U133A 2.0 gene chips) on mononuclear cells from 5 acute myelogenous leukemia (AML) patient samples (&gt;70% blast count) that had been either a) cryopreserved, b) snap frozen, or c) resuspended in TRIzol and stored at −80°C. Samples remained frozen for a period of 1–4 weeks. While gene expression changes between groups were minor, there were some differences. Thirteen probe sets between TRIzol and cryopreserved samples, and 60 probe sets between TRIzol and snap frozen samples, varied significantly (&gt;2-fold difference and p&lt;0.01; t-test). While both non-TRIzol samples lost transcripts associated with mature, contaminating granulocytes, the snap frozen samples also lost transcripts associated with cell growth and metabolism. To determine whether the observed changes were enough to cause a misclassification of AML subtypes, we performed an unsupervised cluster analysis on the 15 original samples plus 15 new AML samples (13 unique cases), all of varying subtypes. RNA from all of these samples was undegraded. All samples passed strict quality control parameters, not limited to but including tumor content, % rRNA, cDNA and cRNA synthesis product size, and GAPDH 3′-5′ ratios. Differentially preserved samples originating from the same patient segregated together during the clustering process regardless of preservation method. Three main clusters emerged; cluster #1 (FAB-M0 and -M1, n=3), cluster #2 (FAB-M3, n=5), and cluster #3 (FAB-M2, -M4 and -M5b, n=22). In cluster #3, there were three sub-groupings. One group contained only M4 and M5b subtypes, another contained only the M2 subtype, and the third contained both M2 and M4 subtypes. RNA isolated from snap frozen samples was sometimes moderately to severely degraded. When we examined three snap frozen samples, not part of the above data set, exhibiting moderate RNA degradation, they all clustered incorrectly according to the above established groups. Given these results, we conclude that cryopreservation is an acceptable method of cell preservation for gene expression analysis, but snap frozen samples should be closely evaluated for RNA degradation before using in microarray analyses.

scholarly journals Exploration of the sputum methylome and omics deconvolution by quadratic programming in molecular profiling of asthma and COPD: the road to sputum omics 2.0

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Espen E. Groth ◽  
Melanie Weber ◽  
Thomas Bahmer ◽  
Frauke Pedersen ◽  
Anne Kirsten ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quadratic Programming ◽  
In Silico ◽  
Rna Degradation ◽  
Published Data ◽  
Whole Genome ◽  
Cellular Composition ◽  
Mixed Cell ◽  
Rna Integrity ◽  
Cell Counts

Abstract Background To date, most studies involving high-throughput analyses of sputum in asthma and COPD have focused on identifying transcriptomic signatures of disease. No whole-genome methylation analysis of sputum cells has been performed yet. In this context, the highly variable cellular composition of sputum has potential to confound the molecular analyses. Methods Whole-genome transcription (Agilent Human 4 × 44 k array) and methylation (Illumina 450 k BeadChip) analyses were performed on sputum samples of 9 asthmatics, 10 healthy and 10 COPD subjects. RNA integrity was checked by capillary electrophoresis and used to correct in silico for bias conferred by RNA degradation during biobank sample storage. Estimates of cell type-specific molecular profiles were derived via regression by quadratic programming based on sputum differential cell counts. All analyses were conducted using the open-source R/Bioconductor software framework. Results A linear regression step was found to perform well in removing RNA degradation-related bias among the main principal components of the gene expression data, increasing the number of genes detectable as differentially expressed in asthma and COPD sputa (compared to controls). We observed a strong influence of the cellular composition on the results of mixed-cell sputum analyses. Exemplarily, upregulated genes derived from mixed-cell data in asthma were dominated by genes predominantly expressed in eosinophils after deconvolution. The deconvolution, however, allowed to perform differential expression and methylation analyses on the level of individual cell types and, though we only analyzed a limited number of biological replicates, was found to provide good estimates compared to previously published data about gene expression in lung eosinophils in asthma. Analysis of the sputum methylome indicated presence of differential methylation in genomic regions of interest, e.g. mapping to a number of human leukocyte antigen (HLA) genes related to both major histocompatibility complex (MHC) class I and II molecules in asthma and COPD macrophages. Furthermore, we found the SMAD3 (SMAD family member 3) gene, among others, to lie within differentially methylated regions which has been previously reported in the context of asthma. Conclusions In this methodology-oriented study, we show that methylation profiling can be easily integrated into sputum analysis workflows and exhibits a strong potential to contribute to the profiling and understanding of pulmonary inflammation. Wherever RNA degradation is of concern, in silico correction can be effective in improving both sensitivity and specificity of downstream analyses. We suggest that deconvolution methods should be integrated in sputum omics analysis workflows whenever possible in order to facilitate the unbiased discovery and interpretation of molecular patterns of inflammation.

scholarly journals Transcriptional profiling of Multiple System Atrophy cerebellar tissue highlights differences between the parkinsonian and cerebellar sub-types of the disease

2020 ◽  
Author(s):  
Ignazio S. Piras ◽  
Christiane Bleul ◽  
Isabelle Schrauwen ◽  
Joshua Talboom ◽  
Lorida Llaci ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple System Atrophy ◽  
Brain Tissue ◽  
Transcriptional Profiling ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Profiling ◽  
Specific Gene Expression ◽  
Rna Expression Profiling ◽  
Endothelial Genes

AbstractMultiple system atrophy (MSA) is a rare adult-onset neurodegenerative disease of unknown cause, with no effective therapeutic options, and no cure. Limited work to date has attempted to characterize the transcriptional changes associated with the disease, which presents as either predominating parkinsonian (MSA-P) or cerebellar (MSC-C) symptoms. We report here the results of RNA expression profiling of cerebellar white matter (CWM) tissue from two independent cohorts of MSA patients (n=66) and healthy controls (HC; n=66). RNA samples from bulk brain tissue and from oligodendrocytes obtained by laser capture microdissection (LCM) were sequenced. Differentially expressed genes (DEGs) were obtained and were examined before and after stratifying by MSA clinical sub-type.We detected the highest number of DEGs in the MSA-C group (n = 747) while only one gene was noted in MSA-P, highlighting the larger dysregulation of the transcriptome in the MSA-C CWM. Results from both bulk tissue and LCM analysis of MSA-C showed a downregulation of oligodendrocyte genes and an enrichment for myelination processes with a key role noted for the QKI gene. Additionally, we observed a significant upregulation of neuron-specific gene expression in MSA-C and an enrichment for synaptic processes. A third cluster of genes was associated with the upregulation of astrocyte and endothelial genes, two cell types with a key role in inflammation processes. Finally, network analysis in MSA-C showed enrichment for β-amyloid related functional classes, including the known Alzheimer’s disease (AD) genes, APP and PSEN1.This is the largest RNA profiling study ever conducted on post-mortem brain tissue from MSA patients. We were able to define specific gene expression signatures for MSA-C highlighting the different stages of the complex neurodegenerative cascade of the disease that included alterations in several cell-specific transcriptional programs. Finally, several results suggest a common transcriptional dysregulation between MSA and AD-related genes despite the clinical and neuropathological distinctions between the two diseases.

Allelic imbalance of tissue-type plasminogen activator (t-PA) gene expression in human brain tissue

2011 ◽  
Vol 105 (06) ◽  
pp. 945-953 ◽  
Author(s):  
Anna Tjärnlund-Wolf ◽  
Karin Hultman ◽  
Maurice Curtis ◽  
Richard Faull ◽  
Robert Medcalf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Brain ◽  
Brain Tissue ◽  
Stroke Recovery ◽  
Tissue Type ◽  
Human Brain Tissue ◽  
Mobility Shift ◽  
Intact Cells ◽  
Allelic Ratio

SummaryWe have identified a single-nucleotide polymorphism (SNP) in the t-PA enhancer (-7351C>T), which is associated with endothelial t-PA release in vivo. In vitro studies demonstrated that this SNP is functional at the level of transcription. In the brain, t-PA has been implicated in both physiologic and pathophysiologic processes. The aim of the present study was to examine the effect of the t-PA –7351C>T SNP on t-PA gene expression in human brain tissue. Allelic mRNA expression was measured in heterozygous post-mortem brain tissues using quantitative TaqMan genotyping assay. Protein-DNA interactions were assessed using electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP). Significantly higher levels of t-PA mRNA were generated from chromosomes that harboured the wild-type –7351C allele, as compared to those generated from the mutant T allele (for the hippocampus, C to T allelic ratio of ~1.3, p=0.010, n=12; and for the cortex, C to T allelic ratio of ~1.2, p=0.017, n=12). EMSA showed reduced neuronal and astrocytic nuclear protein binding affinity to the T allele, and identified Sp1 and Sp3 as the major transcription factors that bound to the –7351 site. ChIP analyses confirmed that Sp1 recognises this site in intact cells. In conclusion, the t-PA –7351C>T SNP affects t-PA gene expression in human brain tissue. This finding might have clinical implications for neurological conditions associated with enhanced t-PA levels, such as in the acute phase of cerebral ischaemia, and also for stroke recovery.

scholarly journals Preanalytical mRNA Stabilization of Whole Bone Marrow Samples

2007 ◽  
Vol 53 (4) ◽  
pp. 587-593 ◽  
Author(s):  
Claudia Langebrake ◽  
Kalle Günther ◽  
Jürgen Lauber ◽  
Dirk Reinhardt
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Gene Expression Pattern ◽  
Rna Isolation ◽  
Basic Research ◽  
Rna Degradation ◽  
Rna Integrity ◽  
Pairwise Correlation ◽  
Mrna Stabilization ◽  
Rna Stabilization

Abstract Background: Gene expression profiling is a useful tool for cancer diagnosis and basic research. A major limitation is that, even during short-term storage of native specimens of peripheral blood or bone marrow (BM) and/or RNA isolation, significant changes of gene expression pattern can occur because of gene induction, repression, and RNA degradation. Methods: We investigated the effectiveness of a newly developed RNA stabilization and preparation system for BM specimens (PAXgene™ Bone Marrow RNA System) over time. We analyzed 256 RNA samples, processed from 64 BM specimens. Results: Although the overall RNA yield (normalized to 1 × 107 leukocytes) was not different, the RNA preparation using unstabilized reference samples had an ∼3 times higher failure rate. With the PAXgene system, we observed significantly higher RNA integrity compared with the reference RNA preparation system (P &lt;0.01). In the stabilized samples, we found very high pairwise correlation in gene expression (ΔΔCT 0.16–0.53) for the analyzed genes (GATA1, RUNX1, NCAM1, and SPI1) after 48-h storage compared with immediate preparation of RNA (2 h after BM collection). However, we found major differences in half of the analyzed genes using the reference RNA isolation procedure (ΔΔCT 1.07 and 1.32). Conclusions: The PAXgene system is able to stabilize RNA from clinical BM samples and is suitable to isolate high-quality and -quantity RNA.

scholarly journals Bioinformatic Analysis Reveals Phosphodiesterase 4D-Interacting Protein as a Key Frontal Cortex Dementia Switch Gene

2020 ◽  
Vol 21 (11) ◽  
pp. 3787
Author(s):  
Judith A. Potashkin ◽  
Virginie Bottero ◽  
Jose A. Santiago ◽  
James P. Quinn
Keyword(s):  
Gene Expression ◽  
Chemical Interaction ◽  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Molecular Pathways ◽  
Interacting Protein ◽  
Key Factor ◽  
Key Genes ◽  
Expression Pathways ◽  
Phosphodiesterase 4D

The mechanisms that initiate dementia are poorly understood and there are currently no treatments that can slow their progression. The identification of key genes and molecular pathways that may trigger dementia should help reveal potential therapeutic reagents. In this study, SWItch Miner software was used to identify phosphodiesterase 4D-interacting protein as a key factor that may lead to the development of Alzheimer’s disease, vascular dementia, and frontotemporal dementia. Inflammation, PI3K-AKT, and ubiquitin-mediated proteolysis were identified as the main pathways that are dysregulated in these dementias. All of these dementias are regulated by 12 shared transcription factors. Protein–chemical interaction network analysis of dementia switch genes revealed that valproic acid may be neuroprotective for these dementias. Collectively, we identified shared and unique dysregulated gene expression, pathways and regulatory factors among dementias. New key mechanisms that lead to the development of dementia were revealed and it is expected that these data will advance personalized medicine for patients.

scholarly journals Identification of Brain Expression Quantitative Trait Loci Associated with Schizophrenia and Affective Disorders in Normal Brain Tissue

2016 ◽  
Author(s):  
Oneil G. Bhalala ◽  
Artika P. Nath ◽  
Michael Inouye ◽  
Christopher R. Sibley ◽  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait Loci ◽  
Human Brain ◽  
Brain Tissue ◽  
Quantitative Trait ◽  
Affective Disorders ◽  
Tissue Expression ◽  
Human Brain Tissue ◽  
Brain Expression ◽  
Causal Genes

AbstractSchizophrenia and the affective disorders, here comprising bipolar disorder and major depressive disorder, are psychiatric illnesses that lead to significant morbidity and mortality worldwide. Whilst understanding of their pathobiology remains limited, large case-control studies have recently identified single nucleotide polymorphisms (SNPs) associated with these disorders. However, discerning the functional effects of these SNPs has been difficult as the associated causal genes are unknown. Here we evaluated whether schizophrenia and affective disorder associated-SNPs are correlated with gene expression within human brain tissue. Specifically, to identify expression quantitative trait loci (eQTLs), we leveraged disorder-associated SNPs identified from six Psychiatric Genomics Consortium and CONVERGE Consortium studies with gene expression levels in post-mortem, neurologically-normal tissue from two independent human brain tissue expression datasets (UK Brain Expression Consortium (UKBEC) and Genotype-Tissue Expression (GTEx)). We identified 6 188 and 16 720 cis-acting SNPs exceeding genome-wide significance (p<5x10−8) in the UKBEC and GTEx datasets, respectively. 1 288 cis-eQTLs were significant in a metaanalysis leveraging overlapping brain regions and were associated with expression of 15 genes, including three non-coding RNAs. One cis-eQTL, rs 16969968, results in a functionally disruptive missense mutation in CHRNA5, a schizophrenia-implicated gene. Meta-analysis identified 297 trans-eQTLs associated with 24 genes that were significant in a region-specific manner. Importantly, comparing across tissues, we find that blood eQTLs largely do not capture brain cis-eQTLs. This study identifies putatively causal genes whose expression in region-specific brain tissue may contribute to the risk of schizophrenia and affective disorders.

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