High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations

Abstract

Populations of cells can be perturbed by various chemical and genetic treatments and the impact on the cells gene expression (transcription, i.e. mRNA levels) and morphology (in an image-based assay) can be measured in high dimensions. The patterns observed in this profile data can be used for more than a dozen applications in drug discovery and basic biology research, but both types of profiles are rarely available for large-scale experiments. We provide a collection of four datasets with both gene expression and morphological profile data useful for developing and testing multi-modal methodologies. Roughly a thousand features are measured for each of the two data types, across more than 28,000 thousand chemical and genetic perturbations. We define biological problems that can be investigated using the shared and complementary information in these two data modalities, provide baseline analysis and evaluation metrics for multi-omic applications, and make the data resource publicly available (http://broad.io/rosetta).

Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

“…A recent patch-seq study in the adult mouse motor cortex supports a lack of discrete boundaries in the adult mouse primary motor cortex, providing evidence of a continuum of correlated transcriptomic and morphoelectrical clusters present within families of cells (Scala et al, 2020). Consistent with these observations, recent comprehensive work has shown that while gene expression can be correlated to a cell's electrophysiology and morphology, each additional parameter adds slightly more nuanced variation (Nandi et al, 2020;Haghighi et al, 2021). As tools emerge to interrogate individual cell connectivity and merge them with neuronal subtypes defined in other contexts, heterogeneity has been identified within "subclasses" (Campagnola et al, 2021).…”

Morphology and gene expression profiling provide complementary information for mapping cell state

“…For both, screening additional cell types 44,47,48 and timepoints might increase the ability to detect and characterize perturbations in cell state. If experiments capture both profiling types, the profiles can be integrated and increase their power and resolution 28,29,49,50 .…”

“…Conversely, l-Ergothioneine induced many more transcriptional changes than morphological changes, which influenced genes associated with RNA splicing (GO:0008380) (Figure 4F). This type of analysis opens the door to exploring relationships between particular mRNA levels and specific morphologies when perturbing cells 29,30 .…”

“…Integrating gene expression and morphology profiles with chemical structures revealed that each data type provides complementary information for predicting a drug's mechanism of action 29,30 , for predicting the effects of perturbations 31 , and for identifying nuisance compounds that can lead to false hits 32 . As well, to some degree, gene expression and morphology datasets contain sufficient information to predict changes in each other 29,30 . However, the field lacks a systematic study evaluating both assays' information content in terms of distinct versus overlapping signals, diversity of cell states, and performance in valuable tasks such as predicting compound mechanisms.…”

Cell Painting predicts impact of lung cancer variants

“…This suggests the possibility to model their correspondences using computational approaches to translate one data type from the other or to understand their causal relationships. Our dataset has been simultaneously used in a study to identify which gene expression variations correspond with which morphology variations, and vice versa 26 . While this has been explored at the bulk level, our results and previous work based on scRNAseq 18 indicate that this type of analysis could be extended to understand multi-omics connections at the single-cell level.…”