A group from the University of California (UC), Berkeley, has developed a new technique, based on CRISPR genome editing, that links targeted, genome-wide genetic changes with a deep-sequencing readout that quantitatively measures the expression phenotype induced by each edit. The team developed the method, called CiBER-seq, to rapidly determine all the DNA sequences in the genome that regulate the expression of a specific gene.

The work is published in Science in the paper titled, “CiBER-seq dissects genetic networks by quantitative CRISPRi profiling of expression phenotypes.”

While the technique will mostly benefit basic researchers who are interested in tracking the genetic network that impacts a gene they’re interested in, it will also help researchers quickly find the regulatory sequences that control disease genes and possibly find new targets for drugs.

“A disease where you might want to use this approach is cancer, where we know certain genes that those cancer cells express, and need to express, in order to survive and grow,” said Nicholas Ingolia, PhD, UC Berkeley associate professor of molecular and cell biology. “What this tool would let you do is ask the question: What are the upstream genes, what are the regulators that are controlling those genes that we know about?”

Those controllers may be easier to target therapeutically in order to shut down the cancer cells.

The new technique simplifies something that has been difficult to do until now: backtrack along genetic pathways in a cell to find these ultimate controllers.

“We have a lot of good ways of working forward,” Ingolia said. “This is a nice way of working backward, figuring out what is upstream of something. I think it has a lot of potential uses in disease research.”

“I sometimes use the analogy that when we walk into a dark room and flip a light switch, we can see what light gets switched on. That light is like a gene, and we can tell, when we flip the switch, what genes it turns on. We are already very good at that,” he added. “What this lets us do is work backward. If we have a light we care about, we want to find out what are the switches that control it. This gives us a way to do that.”

Guided by a piece of guide RNA complementary to the DNA in the gene, the Cas9 protein binds to the gene and cuts or, as with CRISPR interference (CRISPRi), inhibits it. This new technique, which Ingolia calls CRISPRi with barcoded expression reporter sequencing, or CiBER-seq, solves that problem, allowing these experiments to be done simultaneously by pooling tens of thousands of CRISPR experiments.

The technique employs deep sequencing to directly measure the increased or decreased activity of genes in the pool.

“In one pooled CiBER-seq experiment, in one day, we can find all the upstream regulators for several different target genes, whereas, if you were to use a fluorescence-based technique, each of those targets would take you multiple days of measurement time,” Ingolia said.

CRISPRing each gene in an organism in parallel is straightforward, thanks to companies that sell ready-made, single guide RNAs to use with the Cas9 protein. Researchers can order sgRNAs for every gene in the genome, and for each gene, a dozen different sgRNAs—most genes are strings of thousands of nucleotides, while sgRNAs are about 20 nucleotides long.

The team’s key innovation was to link each sgRNA with a barcode connected to a promoter that will only transcribe the barcode if the gene of interest is also switched on. Each barcode reports on the effect of one sgRNA, individually targeting one gene out of a complex pool of thousands of sgRNAs. Deep sequencing tells you the relative abundances of every barcode in the sample allowing you to quickly assess which of the 6,000 genes in yeast has an effect on the promoter and, thus, expression of the gene of interest.

“This is really the heart of what we were able to do differently: the idea that you have a big library of different guide RNAs, each of which is going to perturb a different gene, but it has the same query promoter on it—the response you are studying. That query promoter transcribes the random barcode that we link to each guide,” he said. “If there is a response you care about, you poke each different gene in the genome and see how the response changes.”

“By looking more directly at a gene expression response, we can pick up on a lot of subtlety to the physiology itself, what is going on inside the cell,” he said.

The method was able to recapitulate known regulatory pathways linking protein synthesis with nutrient availability in budding yeast cells. Unexpectedly, the authors found that the cellular logic also appears to consider protein production machinery in this decision. By uncovering additional facets of this deeply conserved pathway, the findings demonstrate the utility of comprehensive and quantitative CiBER-seq profiling in mapping the gene networks underlying cellular decisions.

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