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Method of the Year 2020: spatially resolved transcriptomics

Spatially resolved transcriptomics is our Method of the Year 2020, for its ability to provide valuable insights into the biology of cells and tissues while retaining information about spatial context.


News Feature


As single-cell omics continue to advance, the field of spatially resolved transcriptomics has emerged with a set of experimental and computational methods to map out the positions of cells and their gene expression profiles in space. Here we summarize current transcriptome-wide and sequencing-based methodologies and their applications in genomics research.

Comment | | Nature Methods

The recent advent of genome-scale imaging has enabled single-cell omics analysis in a spatially resolved manner in intact cells and tissues. These advances allow gene expression profiling of individual cells, and hence in situ identification and spatial mapping of cell types, in complex tissues. The high spatial resolution of these approaches further allows determination of the spatial organizations of the genome and transcriptome inside cells, both of which are key regulatory mechanisms for gene expression.

Comment | | Nature Methods

One major challenge in neuroscience is to gain a systematic understanding of the extraordinary diversity of brain cell types and how they contribute to brain function. Spatially resolved transcriptomics holds unmatched promise in unraveling the organization of brain cell types and their relationship with connectivity, circuit dynamics, behavior and disease. Here we discuss neuroscience applications of various spatially resolved transcriptomics methods, as well as technical challenges that need to be overcome to realize their full potentials.

Comment | | Nature Methods

Methods to Watch

Organoids generated by spatially organizing multiple cell types, called assembloids, will enable deeper insights into tissue function.

Method to Watch | | Nature Methods

Glycoproteomics is coming of age, thanks to advances in instrumentation, experimental methodologies and computational search algorithms.

Method to Watch | | Nature Methods