Multidimensional quantitative analysis of mRNA expression within intact vertebrate embryos

Abstract

For decades, in situ hybridization methods have been essential tools for studies of vertebrate development and disease, as they enable qualitative analyses of mRNA expression in an anatomical context. Quantitative mRNA analyses typically sacrifice the anatomy, relying on embryo microdissection, dissociation, cell sorting and/or homogenization. Here, we eliminate the trade-off between quantitation and anatomical context, using quantitative in situ hybridization chain reaction (qHCR) to perform accurate and precise relative quantitation of mRNA expression with subcellular resolution within whole-mount vertebrate embryos. Gene expression can be queried in two directions: read-out from anatomical space to expression space reveals co-expression relationships in selected regions of the specimen; conversely, read-in from multidimensional expression space to anatomical space reveals those anatomical locations in which selected gene co-expression relationships occur. As we demonstrate by examining gene circuits underlying somitogenesis, quantitative read-out and read-in analyses provide the strengths of flow cytometry expression analyses, but by preserving subcellular anatomical context, they enable bi-directional queries that open a new era for in situ hybridization.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2018
Source ID
10.1242/dev.156869

Entities

People

  • Harry Choi
  • Niles A. Pierce
  • Scott E. Fraser
  • Vikas Trivedi

Organizations

  • Balliol College
  • California Institute of Technology
  • Defense Advanced Research Projects Agency
  • Gordon and Betty Moore Foundation
  • John Simon Guggenheim Memorial Foundation
  • National Institutes of Health
  • National Science Foundation
  • University of Cambridge
  • University of Oxford
  • University of Southern California

Tags

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design

Technology Areas

  • Space