Reef-building corals are keystone species that are threatened by anthropogenic stresses including climate change. To investigate corals’ responses to stress and other aspects of their biology, numerous genomic and transcriptomic studies have been performed, generating many hypotheses about the roles of particular genes and molecular pathways. However, it has not generally been possible to test these hypotheses rigorously because of the lack of genetic tools for corals or closely related cnidarians. CRISPR technology seems likely to alleviate this problem. Indeed, we show here that microinjection of single-guide RNA/Cas9 ribonucleoprotein complexes into fertilized eggs of the coralAcropora milleporacan produce a sufficiently high frequency of mutations to detect a clear phenotype in the injected generation. Based in part on experiments in a sea-anemone model system, we targeted the gene encoding Heat Shock Transcription Factor 1 (HSF1) and obtained larvae in which >90% of the gene copies were mutant. The mutant larvae survived well at 27 °C but died rapidly at 34 °C, a temperature that did not produce detectable mortality over the duration of the experiment in wild-type (WT) larvae or larvae injected with Cas9 alone. We conclude that HSF1 function (presumably its induction of genes in response to heat stress) plays an important protective role in corals. More broadly, we conclude that CRISPR mutagenesis in corals should allow wide-ranging and rigorous tests of gene function in both larval and adult corals.
The popularity of CRISPR-based gene editing has resulted in an abundance of tools to design CRISPR-Cas9 guides. This is also driven by the fact that designing highly specific and efficient guides is a crucial, but not trivial, task in using CRISPR for gene editing. Here, we thoroughly analyse the performance of 18 design tools. They are evaluated based on runtime performance, compute requirements, and guides generated. To achieve this, we implemented a method for auditing system resources while a given tool executes, and tested each tool on datasets of increasing size, derived from the mouse genome. We found that only five tools had a computational performance that would allow them to analyse an entire genome in a reasonable time, and without exhausting computing resources. There was wide variation in the guides identified, with some tools reporting every possible guide while others filtered for predicted efficiency. Some tools also failed to exclude guides that would target multiple positions in the genome. We also considered two collections with over a thousand guides each, for which experimental data is available. There is a lot of variation in performance between the datasets, but the relative order of the tools is partially conserved. Importantly, the most striking result is a lack of consensus between the tools. Our results show that CRISPR-Cas9 guide design tools need further work in order to achieve rapid whole-genome analysis and that improvements in guide design will likely require combining multiple approaches.
Background: CRISPR-based systems are playing an important role in modern genome engineering. A large number of computational methods have been developed to assist in the identification of suitable guides. However, there is only limited overlap between the guides that each tool identifies. This can motivate further development, but also raises the question of whether it is possible to combine existing tools to improve guide design. Results: We considered nine leading guide design tools, and their output when tested using two sets of guides for which experimental validation data is available. We found that consensus approaches were able to outperform individual tools. The best performance (with a precision of up to 0.912) was obtained when combining four of the tools and accepting all guides selected by at least three of them. Conclusions: These results can be used to improve CRISPR-based studies, but also to guide further tool development. However, they only provide a short-term solution as the time and computational resources required to run four tools may be impractical in certain applications.
The popularity of CRISPR-based gene editing has resulted in an abundance of tools to design CRISPR-Cas9 guides. This is also driven by the fact that designing highly specific and efficient guides is a crucial, but not trivial, task in using CRISPR for gene editing. Here, we thoroughly analyse the performance of 17 design tools. They are evaluated based on runtime performance, compute requirements, and guides generated. To achieve this, we implemented a method for auditing system resources while a given tool executes, and tested each tool on datasets of increasing size, derived from the mouse genome. We found that only five tools had a computational performance that would allow them to analyse an entire genome in a reasonable time, and without exhausting computing resources. There was wide variation in the guides identified, with some tools reporting every possible guide while others filtered for predicted efficiency. Some tools also failed to exclude guides that would target multiple positions in the genome. We also considered a collection of over a thousand guides for which experimental data is available. For the tools that attempt to filter based on efficiency, 65% to 85% of the guides they reported were experimentally found to be efficient, but with limited overlap in the sets produced by different tools. Our results show that CRISPR-Cas9 guide design tools need further work in order to achieve rapid whole-genome analysis and that improvements in guide design will likely require combining multiple approaches.
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