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Nature Studies Present Single-Cell Higher-Order Testing Approach, Cas12a Enzyme Optimization

A method for studying higher-order interactions among genes in single-cell data is reported in Nature Methods this week. The technique — called single-cell higher-order testing, or scHOT — is based on a statistical framework that captures nonlinear changes in variability and correlation structure by using sample ranking approaches to avoid having to discretize responses and risk obscuring biologically meaningful results, according to developers at the University of Cambridge and the University of Sydney. "This is especially important for continuous single-cell trajectories and for studying spatial structure within ostensibly homogeneous cell types," they write. In the paper, the researchers use scHOT to study coordinated changes in higher-order interactions during embryonic development of the mouse liver and show that it can identify subtle changes in gene-gene correlations across space using spatially resolved transcriptomics data from the mouse olfactory bulb.

Investigators from the Broad Institute and Massachusetts General Hospital report in Nature Biotechnology this week on optimizing the CRISPR enzyme Cas12a to enable its effective use for pooled genetic screening. While Cas12a enzymes hold promise as tools for multiplexed genetic perturbations because they can process multiple guide RNAs expressed as a single transcript and execute target DNA cleavage, their use is limited by low activity and the lack of a well-validated pooled screening toolkit. To address this, the researchers tested variants of Cas12a from Acidaminococcus to select a highly effective construct, then refined on-target design rules and developed a comprehensive set of off-target rules to predict and exclude promiscuous guides. They also developed alternative direct repeat sequences for use with multiplexed arrays that can substitute for the wild-type sequence. They demonstrate their optimized Cas12a toolkit in a genetic interaction screen of genes implicated in apoptosis and show that it performs as well as Cas9 in genome-wide dropout screens but at greatly reduced library size.