Volume 17 Issue 1, January 2020

Moving athletically, from Turkey to California to Wisconsin and from engineering to the biostatistics of Hi-C.

Armed with a rapidly maturing toolbox for single-cell analysis, scientists are threading together multiple layers of omic data to assemble rich portraits of cellular identity and function.

Advances in single-cell genomics technologies have enabled investigation of the gene regulation programs of multicellular organisms at unprecedented resolution and scale. Development of single-cell multimodal omics tools is another major step toward understanding the inner workings of biological systems.

Single-cell omics approaches provide high-resolution data on cellular phenotypes, developmental dynamics and communication networks in diverse tissues and conditions. Emerging technologies now measure different modalities of individual cells, such as genomes, epigenomes, transcriptomes and proteomes, in addition to spatial profiling. Combined with analytical approaches, these data open new avenues for accurate reconstruction of gene-regulatory and signaling networks driving cellular identity and function. Here we summarize computational methods for analysis and integration of single-cell omics data across different modalities and discuss their applications, challenges and future directions.

The field of single-cell RNA sequencing (scRNA-seq) has been paired with genomics, epigenomics, spatial omics, proteomics and imaging to achieve multimodal measurements of individual cellular phenotypes and genotypes. In its purest form, single-cell multimodal omics involves the simultaneous detection of multiple traits in the same cell. More broadly, multimodal omics also encompasses comparative pairing and computational integration of measurements made across multiple distinct cells to reconstruct phenotypes. Here I highlight some of the biological insights gained from multimodal studies and discuss the challenges and opportunities in this emerging field.

Combining a voltage sensor with random-access microscopy allows imaging of neuronal activity in behaving mice.

An optical gating strategy allows day-long light-sheet imaging of the developing heart in zebrafish embryos.

Direct library preparation (DLP) for amplification-free single-cell whole-genome sequencing has been upgraded to a high-throughput, scalable platform for identification of clonal populations and their genomic features, integrating them with single-cell morphology.

A protein co-regulation database facilitates proteome-wide functional annotations.

A method using CRISPR–Cas technology, nanopore sequencing and bioinformatics enables quantification of short tandem repeats with high accuracy.

Change is a constant in the burgeoning field of metabolomics. That includes data analysis tools and repositories.

FreeHi-C takes Hi-C sequencing data as input and simulates reads with random mutations and indels from the interacting fragment pairs. FreeHi-C-simulated replicates are used for benchmarking Hi-C analysis methods and enable data augmentation for differential chromatin interaction analysis.

A deep learning-based software tool, DIA-NN, enables deep proteome analysis from data generated using fast chromatographic approaches and data-independent acquisition mass spectrometry.

VarID is a computational method that quantifies the dynamics of transcriptional variability with the goal of identifying the role of highly variable genes, such as weakly expressed transcription factors, in cell differentiation or state transitions.

Micropatterning of cryo-EM grids enables controlled adhesion of mammalian cells for cryo-ET-based structural studies. This approach leads to reproducible cellular morphology and improves focused ion beam thinning of cells for in-cell structural analyses.

mEosEM survives 1% OsO₄ treatment and Epon embedding for improved super-resolution correlative light and electron microscopy.

SIMFLUX combines elements of MINFLUX with structured illumination to double localization precision and improve resolution in localization microscopy. The approach was demonstrated on DNA origami and on cellular microtubules.

A miniaturized NMR-on-a-chip needle can be implanted into rodent brains and can measure blood flow and oxygenation changes in vivo in a small volume at an unprecedentedly high temporal resolution of a few milliseconds.

An alternative to focused ion beam scanning electron microscopy (FIB-SEM), gas cluster ion beam scanning electron microscopy (GCIB-SEM) is compatible with large tissue samples while achieving similar isotropic resolution.

European XFEL allows investigation of the picosecond time range in the photocycle of photoactive yellow protein.

An approach combining cryo-electron microscopy and mass spectrometry analysis of protein complexes enriched directly from cells enables structure determination of unknown complexes at atomic resolution.

DuMPLING (dynamic μ-fluidic microscopy phenotyping of a library before in situ genotyping) enables screening of dynamic phenotypes in strain libraries and was used here to study genes that coordinate replication and cell division in Escherichia coli.

Single-cell isolation following time-lapse imaging (SIFT) enables high-throughput screening of complex and dynamic phenotypes from pooled bacterial libraries. SIFT was used to generate ultraprecise synthetic gene oscillators.

Probabilistic cell typing by in situ sequencing (pciSeq), leverages previous single-cell RNA sequencing classification and multiplexed in situ RNA detection to spatially map cell types accurately in the mouse hippocampus and isocortex.

Simultaneous two-photon microscopic and one-photon mesoscopic imaging of calcium signals enables correlation of local cellular and brain-wide network activity.