Dataset Information

Next-Generation Sequencing identified piRNA profiles in healthy and Alzheimer’s-affected human brain

ABSTRACT: To investigate the presence of piRNAs and their potential functions in human brain and neurodegenerations, we performed the genomic profiling in Healthy Brain (HB) sample as well as Alzheimer-affected brain (AD) sample by adopting Next-Gen small RNA sequencing technology. Using deep sequencing of small RNAs, we identified an extensive catalogue of 564 and 451 mature piRNAs in HB and AD respectively. The piRNAs from each sample exhibited varied length distribution between 26-32 nts and are originated from different genomic locations. We found 149 piRNAs to be differentially expressed in Alzheimer’s disease which comprises of 146 up-regulated and 3 down-regulated piRNAs. Ours is the first study that reported the presence of piRNAs in healthy as well as Alzheimer’s disease-affected human brain. The extensive catalogue of human piRNAs detected in this study provides a useful resource for decrypting the involvement of piRNAs in neurological functions as well as neurodegenerations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE85075 | GEO | 2017/01/28

SECONDARY ACCESSION(S): PRJNA336186

REPOSITORIES: GEO

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Project description:Alzheimer’s disease (AD), the most common age-related neurodegenerative disease, is closely associated with and manifested by neuroinflammation, yet the alteration of immune landscape in AD is largely unknown, preventing a deeper mechanistic understanding of neuroinflammation in AD. Two thirds of AD patients are females, and women have a higher risk of developing AD. Women with AD have more extensive brain histological changes than men with AD, more severe cognitive symptoms, and more severe neurodegeneration, suggesting that the disease affects female and male brains differentially. Despite evident AD sex variance, mechanisms and pathways are still poorly understood. Thus, a focus on sex differences in AD is essential to move the field towards effective interventions and to develop sex-specific therapies. To understand the cellular heterogeneity and disease-associated cellular changes in human AD brain, we performed unbiased massively parallel single nucleus RNA sequencing with postmortem frozen human brain tissues of middle temporal gyrus, a brain cortical region strongly affected by AD. From 12 individuals with and without AD, we isolated brain nuclei by sucrose gradient ultracentrifugation, generated single nucleus libraries with 10x Chromium platform (10x Genomics), and sequenced on NovaSeq6000 S4 sequencer (Illumina). We integrated snRNA-seq data of human brains from these 12 individuals of both Alzheimer’s Disease (AD, Braak Stage V/VI, n = 6) and age-matched healthy controls (HC, Braak Stage I/II, n = 6) by single nucleus analysis using Seurat. After quality control filtering, we profiled and analyzed 64,845 single nucleus transcriptomes, clustered all the cells jointly across the 12 donors that include 6 females and 6 males, and identified and annotated the major cell types of the human brain by interrogating the expression patterns of known gene markers, including neurons, excitatory neurons, inhibitory neurons, astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, endothelial cells, and pericytes.

Project description:Purpose: The aim of this study is to identify known and novel small RNAs (Piwi-interacting RNAs and microRNAs) in normal ovary and epithelial ovarian malignancies by adopting high-throughput RNA sequencing (RNA-Seq) and unveil their possible functions in neoplastic pathways of the two most frequently observed and highly lethal subtypes of epithelial ovarian cancers, endometrioid ovarian cancer (ENOCa) and serous ovarian cancer (SOCa). The study has been performed in normal ovarian tissues as well as malignant tissues of these cancer subtypes. Methods: 1 µg of total RNA was used as the starting material for library preparation as prescribed by Illumina Truseq small RNA library protocol. Small RNA sequencing was carried out by Genotypic Technology, Bangalore, India on Illumina Next-Seq 500 platform. Library preparation was done by performing 3' and 5' adapter ligation followed by reverse transcription of cDNA and amplification of the library. The construct of the library was fractionated to select 16-40 nucleotide insert of small RNAs using PAGE. The quality check of the library was done in Agilent Technologies 2100 Bioanalyzer using a DNA-specific chip, such as High Sensitivity DNA. The sequence reads that passed through Quality Check by FastQC and aligned to the human genome (hg19) were further analysed using in-house pipelines and set of known and novel piRNAs and miRNAs were identified. The sets of known piRNAs and miRNAs identified were assessed for their involvement in neoplastic processes of ovarian cancer subtypes by performing target analysis and GO enrichment studies. Results: Using an in-house prediction pipeline, we mapped about 10-15 million sequence reads per sample to the human genome (hg19) and detected 256, 234 and 219 annotated piRNAs in ENOCa, SOCa, and normal ovary respectively; whereas the average number of known miRNAs present in each sample was estimated to be 480. The annotated piRNAs obtained from each sample exhibited varied length distribution between 26-32 nts. Conclusions: For the first time, our study reported the presence of piRNAs in ENOCa, SOCa and normal ovarian tissue from the next-gen sequencing of small RNAs of 16-40 nts length. The extensive catalogue of human EOCa small RNAs (both piRNAs and miRNAs) detected in this study provides a useful resource to dissect complex neoplastic events that are possibly mediated by these ncRNAs, especially by piRNAs. Moreover, these piRNAs could be used as probable small RNA biomarkers for the EOCa.

Project description:Winter2017 - Brain Energy Metabolism with PPP This model is described in the article: Mathematical analysis of the influence of brain metabolism on the BOLD signal in Alzheimer's disease Felix Winter1,2, Catrin Bludszuweit-Philipp1 and Olaf Wolkenhauer2,3 Journal of Cerebral Blood Flow & Metabolism Abstract: Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a standard clinical tool for the detection of brain activation. In Alzheimer’s disease (AD), task-related and resting state fMRI have been used to detect brain dysfunction. It has been shown that the shape of the BOLD response is affected in early AD. To correctly interpret these changes, the mechanisms responsible for the observed behaviour need to be known. The parameters of the canonical hemodynamic response function (HRF) commonly used in the analysis of fMRI data have no direct biological interpretation and cannot be used to answer this question. We here present a model that allows relating AD-specific changes in the BOLD shape to changes in the underlying energy metabolism. According to our findings, the classic view that differences in the BOLD shape are only attributed to changes in strength and duration of the stimulus does not hold. Instead, peak height, peak timing and full width at half maximum are sensitive to changes in the reaction rate of several metabolic reactions. Our systems-theoretic approach allows the use of patient-specific clinical data to predict dementia- driven changes in the HRF, which can be used to improve the results of fMRI analyses in AD patients. This model is hosted on BioModels Database and identified by: BIOMD0000000627. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Next-Generation Sequencing identified piRNA profiles in healthy and Alzheimer’s-affected human brain

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