Literature DB >> 26000847

Designing Cell-Type-Specific Genome-wide Experiments.

Ava Handley1, Tamás Schauer2, Andreas G Ladurner3, Carla E Margulies4.   

Abstract

Multicellular organisms depend on cell-type-specific division of labor for survival. Specific cell types have their unique developmental program and respond differently to environmental challenges, yet are orchestrated by the same genetic blueprint. A key challenge in biology is thus to understand how genes are expressed in the right place, at the right time, and to the right level. Further, this exquisite control of gene expression is perturbed in many diseases. As a consequence, coordinated physiological responses to the environment are compromised. Recently, innovative tools have been developed that are able to capture genome-wide gene expression using cell-type-specific approaches. These novel techniques allow us to understand gene regulation in vivo with unprecedented resolution and give us mechanistic insights into how multicellular organisms adapt to changing environments. In this article, we discuss the considerations needed when designing your own cell-type-specific experiment from the isolation of your starting material through selecting the appropriate controls and validating the data.
Copyright © 2015 Elsevier Inc. All rights reserved.

Mesh:

Year:  2015        PMID: 26000847     DOI: 10.1016/j.molcel.2015.04.024

Source DB:  PubMed          Journal:  Mol Cell        ISSN: 1097-2765            Impact factor:   17.970


  12 in total

Review 1.  Cell-selective proteomics for biological discovery.

Authors:  Shannon E Stone; Weslee S Glenn; Graham D Hamblin; David A Tirrell
Journal:  Curr Opin Chem Biol       Date:  2017-01-12       Impact factor: 8.822

2.  cTag-PAPERCLIP Reveals Alternative Polyadenylation Promotes Cell-Type Specific Protein Diversity and Shifts Araf Isoforms with Microglia Activation.

Authors:  Hun-Way Hwang; Yuhki Saito; Christopher Y Park; Nathalie E Blachère; Yoko Tajima; John J Fak; Ilana Zucker-Scharff; Robert B Darnell
Journal:  Neuron       Date:  2017-09-13       Impact factor: 17.173

3.  A Multiplexed System for Quantitative Comparisons of Chromatin Landscapes.

Authors:  Peter van Galen; Aaron D Viny; Oren Ram; Russell J H Ryan; Matthew J Cotton; Laura Donohue; Cem Sievers; Yotam Drier; Brian B Liau; Shawn M Gillespie; Kaitlin M Carroll; Michael B Cross; Ross L Levine; Bradley E Bernstein
Journal:  Mol Cell       Date:  2015-12-10       Impact factor: 17.970

4.  Single-cell RNA Sequencing Analysis Reveals New Immune Disorder Complexities in Hypersplenism.

Authors:  Hai-Chao Zhao; Chang-Zhou Chen; Huang-Qin Song; Xiao-Xiao Wang; Lei Zhang; Hao-Liang Zhao; Jie-Feng He
Journal:  Front Immunol       Date:  2022-07-05       Impact factor: 8.786

5.  INTACT vs. FANS for Cell-Type-Specific Nuclei Sorting: A Comprehensive Qualitative and Quantitative Comparison.

Authors:  Monika Chanu Chongtham; Tamer Butto; Kanak Mungikar; Susanne Gerber; Jennifer Winter
Journal:  Int J Mol Sci       Date:  2021-05-19       Impact factor: 5.923

6.  Analysis of C. elegans muscle transcriptome using trans-splicing-based RNA tagging (SRT).

Authors:  Xiaopeng Ma; Ge Zhan; Monica C Sleumer; Siyu Chen; Weihong Liu; Michael Q Zhang; Xiao Liu
Journal:  Nucleic Acids Res       Date:  2016-08-23       Impact factor: 16.971

7.  Cross-Laboratory Analysis of Brain Cell Type Transcriptomes with Applications to Interpretation of Bulk Tissue Data.

Authors:  B Ogan Mancarci; Lilah Toker; Shreejoy J Tripathy; Brenna Li; Brad Rocco; Etienne Sibille; Paul Pavlidis
Journal:  eNeuro       Date:  2017-11-30

8.  EC-tagging allows cell type-specific RNA analysis.

Authors:  Naoki Hida; Mohamed Y Aboukilila; Dana A Burow; Rakesh Paul; Marc M Greenberg; Michael Fazio; Samantha Beasley; Robert C Spitale; Michael D Cleary
Journal:  Nucleic Acids Res       Date:  2017-09-06       Impact factor: 16.971

9.  Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing data.

Authors:  Jiaxin Fan; Xuran Wang; Rui Xiao; Mingyao Li
Journal:  PLoS Genet       Date:  2021-03-04       Impact factor: 5.917

10.  Progress in mimicking brain microenvironments to understand and treat neurological disorders.

Authors:  Mai T Ngo; Brendan A C Harley
Journal:  APL Bioeng       Date:  2021-04-08
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.