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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
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Related Experiment Video

Updated: Nov 28, 2025

Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer&#39;s Disease
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scREAD: A Single-Cell RNA-Seq Database for Alzheimer's Disease.

Jing Jiang1, Cankun Wang1, Ren Qi1

  • 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.

Iscience
|November 26, 2020
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Summary

Researchers created scREAD, a database for Alzheimer's disease (AD) single-cell RNA sequencing data. This resource aids in understanding brain cell vulnerability in AD by analyzing gene expression and cell types.

Keywords:
BioinformaticsBiological DatabaseNeuroscience

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Area of Science:

  • Neuroscience
  • Genomics
  • Computational Biology

Background:

  • Alzheimer's disease (AD) is a leading cause of dementia, characterized by progressive neurodegeneration.
  • Single-cell RNA sequencing (scRNA-Seq) and single-nucleus RNA sequencing (snRNA-Seq) offer high resolution for studying cellular heterogeneity in the brain.
  • Understanding cell-type-specific vulnerabilities is crucial for elucidating AD pathogenesis.

Purpose of the Study:

  • To develop the first integrated database, scREAD, for managing and analyzing scRNA-Seq and snRNA-Seq data in Alzheimer's disease.
  • To provide a centralized resource for researchers studying AD at the single-cell level.
  • To facilitate the identification of cellular mechanisms underlying AD.

Main Methods:

  • Compiled and integrated 73 scRNA-Seq and snRNA-Seq datasets from human postmortem brain tissue and AD mouse models.
  • Developed analytical pipelines for control atlas construction and cell-type prediction.
  • Performed differential gene expression analysis and identified cell-type-specific regulons.

Main Results:

  • Established scREAD, a comprehensive database covering 10 brain regions and numerous AD datasets.
  • Generated detailed cell-type atlases and identified key differentially expressed genes.
  • Characterized cell-type-specific regulons implicated in Alzheimer's disease pathology.

Conclusions:

  • scREAD serves as a valuable, unprecedented resource for Alzheimer's disease research.
  • The database enables deeper insights into cell-type-specific molecular changes in AD.
  • Facilitates the discovery of novel therapeutic targets by pinpointing vulnerable cell populations.