Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches.

A major challenge in the application of the CRISPR-Cas13d system is to accurately predict its guide-dependent on-target and off-target effect. Here, we perform CRISPR-Cas13d proliferation screens and design a deep learning model, named DeepCas13, to predict the on-target activity from guide sequences and secondary structures. DeepCas13 outperforms existing methods to predict the efficiency of guides targeting both protein-coding and non-coding RNAs. Guides targeting non-essential genes display off-target viability effects, which are closely related to their on-target efficiencies. Choosing proper negative control guides during normalization mitigates the associated false positives in proliferation screens. We apply DeepCas13 to the guides targeting lncRNAs, and identify lncRNAs that affect cell viability and proliferation in multiple cell lines. The higher prediction accuracy of DeepCas13 over existing methods is extensively confirmed via a secondary CRISPR-Cas13d screen and quantitative RT-PCR experiments. DeepCas13 is freely accessible via http://deepcas13.weililab.org .

HiCAR is a robust and sensitive method to analyze open-chromatin-associated genome organization.

The long-range interactions of cis-regulatory elements (cREs) play a central role in gene regulation. cREs can be characterized as accessible chromatin sequences. However, it remains technically challenging to comprehensively identify their spatial interactions. Here, we report a new method HiCAR (Hi-C on accessible regulatory DNA), which utilizes Tn5 transposase and chromatin proximity ligation, for the analysis of open-chromatin-anchored interactions with low-input cells. By applying HiCAR in human embryonic stem cells and lymphoblastoid cells, we demonstrate that HiCAR identifies high-resolution chromatin contacts with an efficiency comparable with that of in situ Hi-C over all distance ranges. Interestingly, we found that the "poised" gene promoters exhibit silencer-like function to repress the expression of distal genes via promoter-promoter interactions. Lastly, we applied HiCAR to 30,000 primary human muscle stem cells and demonstrated that HiCAR is capable of analyzing chromatin accessibility and looping using low-input primary cells and clinical samples.