Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

Detecting Activated Cell Populations Using Single-Cell RNA-Seq.

Neuron | Oct 11, 2017

Single-cell RNA sequencing offers a promising opportunity for probing cell types mediating specific behavioral functions and the underlying molecular programs. However, this has been hampered by a long-standing issue in transcriptional profiling of dissociated cells, specifically the transcriptional perturbations that are artificially induced during conventional whole-cell dissociation procedures. Here, we develop Act-seq, which minimizes artificially induced transcriptional perturbations and allows for faithful detection of both baseline transcriptional profiles and acute transcriptional changes elicited by behavior/experience-driven activity. Using Act-seq, we provide the first detailed molecular taxonomy of distinct cell types in the amygdala. We further show that Act-seq robustly detects seizure-induced acute gene expression changes in multiple cell types, revealing cell-type-specific activation profiles. Furthermore, we find that acute stress preferentially activates neuronal subpopulations that express the neuropeptide gene Cck. Act-seq opens the way for linking physiological stimuli with acute transcriptional dynamics in specific cell types in diverse complex tissues.

Pubmed ID: 29024657 RIS Download

Mesh terms: Amygdala | Animals | Male | Mice | Mice, Inbred C57BL | Organ Culture Techniques | Sequence Analysis, RNA | Single-Cell Analysis

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


ImageJ

It is an open source image processing Java program designed for scientific multidimensional images. This open platform for scientific image analysis is used in life sciences. Image J has been transformed to ImageJ2 application. This new application improves ImageJ data engine to be sufficient to analyze modern datasets and makes the addition of new functionality possible and provides a framework for interoperability between a plethora of external image visualization and analysis programs. ImageJ2 strengthens ImageJ’s utility by: 1) generalizing the ImageJ data model; 2) introducing a robust architecture instrumental in building bridges across a range of other image processing tools; 3) remaining open source and cross-platform with permissive licensing, enabling continued widespread adoption and extension; 4) building on the huge collection of existing ImageJ plugins while enabling the creation of new plugins with more powerful features; and 5) leveraging a correspondingly large and diverse community to foster a collaborative and interdisciplinary project that facilitates the collective advancement of science.

tool

View all literature mentions

SEURAT

A software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data.

tool

View all literature mentions

Database for Annotation Visualization and Integrated Discovery

A database which provides a comprehensive set of functional annotation tools for investigators to understand biological meaning behind large list of genes. For any given gene list, DAVID tools are able to perform a variety of actions such as identifying enriched biological themes (particularly GO terms), discovering enriched functional-related gene groups, clustering redundant annotation terms, and visualizing genes on BioCarta and KEGG pathway maps.

tool

View all literature mentions