While the effects of a singular gene and its protein output can be measured and quantified, many traits of organisms are part of far more complex regulatory pathways involving dozens of genes that turn on and off different systems. Mapping out how these pathways interact and what genes make them up has been a key part of genomic research for decades, though it has long been a slow and arduous process. But improvements in available technologies over the years have not only made it easier on the biological side of things, the creation of next gen sequencing and bioinformatics systems has also allowed for simpler generation of these regulatory maps in way less time.

The Quest For Tri-Functionality

The introduction of CRISPR has also opened up the possibility of conducting genome-wide deletion testing where each gene is knocked out individually and the phenotypic results monitored on a cellular level. New pathway understandings have definitively come about because of that, but it is still a step removed from full multi-functional testing. Since outright deletion may not properly represent the importance or use of a gene within a regulatory network and, instead, overexpression and downregulation might be better options. But until now separate CRISPR or other tool systems had to be used for each of those purposes, even if there are CRISPR variants that can do each thing, as using them together would interfere with each other’s processes.

This has led to the desire for a multi-functional CRISPR tool to be developed that would allow multiple forms of gene regulation to be used at once. There have already been successes in this area, such as a combination of a dead Cas9 complex with a cutting one, so that genes could be deleted and others could be transcriptionally upregulated. Dual activator and repressor systems have also been created, but a tri-directional CRISPR that could regulate both ways and also cut out sequences was the holy grail of tools.

Genomic Magic

Researchers at the University of Illinois had previously accomplished this, but had only tested the system in a very restricted manner. To create it, they combined the workings of a catalytically inactive Cas12a fused with an activator domain for upregulation (CRISPRa), a Cas9 lacking its nuclease domain for cut targeting fused with a repression domain for downregulation (CRISPRi), and lastly a normal catalytically working Cas9 (CRISPRd), thus resulting in their complex they termed CRISPR-AID. As just noted, however, they never tried to apply it to an entire genome at once until now.

For this new purpose, they have renamed their tool to being a more general multi-functional genome-wide CRISPR (MAGIC) system that can map genotypic changes into phenotypic results across an entire organism’s genome. They applied it to Saccharomyces cerevisiae, yeast, and had it map out an entire gain of function, reduction of function, and loss of function map in order to make, as they claim, the most comprehensive genome map of yeast ever made. Once this is done, the data can be retroactively used to determine how complex multi-gene traits work together and what changes can be made to have a desired impact on things like resistances and protein production.

A comparison afterward using two other searching techniques known as RNAi-Assisted Genome Evolution (RAGE) and CRISPR–Cas9- and homology directed-repair (HDR)-assisted genome-scale engineering (CHAnGE) showed that while those two tools failed to come up with any further gene variants for tolerance to the furfural molecule the researchers were looking for after two rounds of screening, MAGIC was able to continue showing potential variants through a third round and at a higher concentration of the molecule as well. It not only was able to find a greater number of natural existing gene variants, the tool was also able to engineer new variants itself that were shown to be effective.

An Upgrade To Eukaryotic Genomes

This combinatorial usage of overexpression, downregulation, and direct alteration has been proven to be useful for genome mapping and for the investigation of gene alterations that are desired. It is comprehensive in its coverage of an entire genome, even more so than the cDNA libraries used frequently for such mapping purposes. Since those only showcase genes as they are at one point in time and cannot account for genes expressed variantly and under differing conditions, along with them not covering RNA genes. Therefore, MAGIC and its use of CRISPR is a far better alternative, though it has yet to be tested on any higher eukaryotic organisms.

The research team are hopeful, however, that it can be accomplished. But it will require organisms that have a high transformation efficiency, a meaningful efficiency in editing of their genes, and can have high throughput screening applied for genome-wide mapping and alterations to be possible with MAGIC. Once there are organisms with more complex genomes that meet those criteria, then MAGIC and genomic screening can be applied to look into the million and billions of gene variations within a single genome. And then the real work can begin in regards to phenotypic trait expression.

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Photo CCs: Colorized cryo-SEM image of yeast from the Cell Image Library