Spatially precise in situ transcriptomics in intact biological systems

Biological tissues are composed of cells of diverse types and states that are spatially organized with nanoscale precision over extended length scales to perform coordinated functions. Understanding patterns of gene expression in tissues is needed to understand complex cellular behaviors in health and disease. Current methods for highly multiplexed RNA imaging are limited in their spatial resolution and lack precise subcellular landmarks, limiting the ability to localize transcripts to nanoscale and subcellular compartments. Here, I describe the development of targeted expansion sequencing (targeted ExSeq), a multiplexed RNA imaging method that enables efficient detection of a predefined set of transcripts in three-dimensional tissues with nanoscale resolution. Targeted ExSeq integrates expansion microscopy, an approach for volumetric super-resolution tissue imaging through the principle of physical magnification, with targeted in situ sequencing, an approach for imaging RNA transcripts of interest. Targeted ExSeq was used to spatially map layer-specific cell type organization in the primary visual cortex in the mouse brain, nanoscale RNA localization within dendrites and dendritic spines in the mouse hippocampus, and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. The approach for targeted RNA in situ sequencing was adapted to whole-mount RNA imaging of intact preimplantation mouse embryos. By integrating immunofluorescence and in situ sequencing with live-embryo mechanical measurements, a spatially-resolved multimodal map of preimplantation embryogenesis was generated to study self-organization in development, finding early lineage segregation events and progressive mechanical softening. Joint measurements demonstrated that early lineage segregation events have differential mechanical and morphological properties that align with distinct developmental programs.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Harvard-MIT Program in Health Sciences and Technology

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Sinha, Anubhav

Advisors dc:contributor.advisor

• Boyden, Edward S.
• Regev, Aviv

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/152792

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/152792