Method of the Year 2020: spatially resolved transcriptomics

Spatially resolved transcriptomics methods are changing the way we understand complex tissues.

Nature Methods has crowned spatially resolved transcriptomics Method of the Year 2020.

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.

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.

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.

Prime editors enable different types of small mutations to be introduced into genomes.

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

Single-objective light sheet fluorescence microscopes are driving innovation in volumetric imaging.

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

Method development pushes the limit of completeness of genome sequences.

Behavioral analysis has come a long way from tedious manual annotation, and further strides in automation are expected.

Computational approaches help us explore complexities of the T cell receptor repertoire.

Researchers are putting new spins on familiar dyes and showing their versatility for labeling living systems.