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Published January 8, 2018 | Submitted + Published + Supplemental Material
Journal Article Open

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.

Additional Information

© 2018 Published by The Company of Biologists Ltd. Received July 5, 2017; Accepted November 23, 2017; Published 8 January 2018. Competing interests: The authors declare competing financial interests in the form of patents (N.A.P. and S.E.F.), pending patent applications (N.A.P. and H.M.T.C.) and a pending startup company (N.A.P. and H.M.T.C.). Author contributions: Methodology: V.T., H.M.T.C., S.E.F., N.A.P.; Software: V.T.; Validation: V.T.; Investigation: V.T., H.M.T.C.; Writing - original draft: V.T., N.A.P.; Writing - review & editing: V.T., H.M.T.C., S.E.F., N.A.P.; Visualization: V.T., S.E.F., N.A.P.; Supervision: S.E.F., N.A.P.; Project administration: N.A.P.; Funding acquisition: S.E.F., N.A.P. This work was funded by the National Institutes of Health (R01EB006192 and R01HD075605), by the Defense Advanced Research Projects Agency (HR0011-17-2-0008), by the National Science Foundation Molecular Programming Project (NSF-CCF-1317694), by the Gordon and Betty Moore Foundation (GBMF2809), by the Beckman Institute at Caltech (Programmable Molecular Technology Center, PMTC), by the Translational Imaging Center at the University of Southern California, by the Rosen Center for Bioengineering at Caltech, by the John Simon Guggenheim Memorial Foundation, by a Herchel Smith Postdoctoral Research Fellowship from the University of Cambridge, by a Professorial Fellowship at Balliol College (University of Oxford), and by the Eastman Visiting Professorship at the University of Oxford. Deposited in PMC for release after 12 months.

Attached Files

Published - dev156869.full.pdf

Submitted - 214619.full.pdf

Supplemental Material - DEV156869supp.pdf

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Additional details

Created:
August 19, 2023
Modified:
October 20, 2023