An open index of research

A status.lu publication

Biology & Genetics

Spatially resolved, highly multiplexed RNA profiling in single cells

Kok Hao Chen, Alistair N. Boettiger, Jeffrey R. Moffitt, Siyuan Wang, Xiaowei Zhuang

Published 24 April 2015 · Science · Journal article

Summary

This paper introduces MERFISH, a single-molecule imaging method that uses error-robust barcoding combined with sequential rounds of hybridization and imaging to identify many RNA species in single cells in situ. The error-correcting binary codes allow detection and misidentification correction across thousands of transcripts. The authors imaged up to ~1,000 genes in individual human cells, mapping spatial expression and revealing gene co-variation and subcellular RNA localization.

Key findings

  • Developed MERFISH using combinatorial, error-robust barcoding read out over multiple imaging rounds.
  • Simultaneously profiled hundreds to ~1,000 RNA species in single cells while preserving spatial context.
  • Revealed correlated gene expression groups and spatial/subcellular RNA distribution patterns.

Subjects & keywords

Cite this paper

APA

Kok Hao Chen, Alistair N. Boettiger, Jeffrey R. Moffitt, Siyuan Wang, & Xiaowei Zhuang (2015). Spatially resolved, highly multiplexed RNA profiling in single cells. Science. https://doi.org/10.1126/science.aaa6090

BibTeX
@article{chen2015spatially,
  author    = {Kok Hao Chen and Alistair N. Boettiger and Jeffrey R. Moffitt and Siyuan Wang and Xiaowei Zhuang},
  title     = {Spatially resolved, highly multiplexed RNA profiling in single cells},
  journal   = {Science},
  year      = {2015},
  doi       = {10.1126/science.aaa6090},
  url       = {https://doi.org/10.1126/science.aaa6090}
}

Related in Biology & Genetics

Accurate structure prediction of biomolecular interactions with AlphaFold 3

Josh Abramson, Jonas Adler and John M. Jumper

This paper introduced AlphaFold 3, a unified deep learning model that predicts the joint structure of complexes containing proteins, nucleic acids, small-molecule ligands, ions, and modified residues. It replaces much of the prior architecture with a diffusion-based module that directly generates atomic coordinates. The model achieved substantially improved accuracy over specialized tools across many interaction types, including protein-ligand and protein-nucleic acid complexes.

Nature Open access

De novo design of protein structure and function with RFdiffusion

Joseph L. Watson, David Juergens and David Baker

This paper introduced RFdiffusion, a generative diffusion model built on the RoseTTAFold network for de novo protein design. It enables a range of design tasks, including unconditional generation, symmetric oligomer design, functional motif scaffolding, and binder design. Many designs were experimentally validated, with solved structures closely matching the intended models.

Nature Open access

A draft human pangenome reference

Wen-Wei Liao, Mobin Asri and Jana Ebler

The Human Pangenome Reference Consortium presents a first draft human pangenome built from 47 phased, diploid genome assemblies of genetically diverse individuals. The assemblies cover more than 99% of the expected sequence per genome at over 99% base-level and structural accuracy, and are combined into a graph-based reference. Relative to GRCh38, the pangenome adds about 119 million base pairs of euchromatic polymorphic sequence and 1,115 gene duplications, improving representation of variation at structurally complex loci.

Nature Open access