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Highlight: Skyline Drivers

Two graphs, one from 2011 and one from 2014, show the increased “skyline” in genetic variation associated with schizophrenia, due to enhanced detection techniques.

The “skyline”—Manhattan plot graph of genetic variation associated with schizophrenia—has risen dramatically over the past few years, thanks to the enhanced ability to detect subtle effects of common gene variants that comes with larger sample sizes. Bars that rise above the red line indicate chromosomal sites that confer risk.

Source: Psychiatric Genomics Consortium

The skyline-like pattern created by graphing the genes implicated in schizophrenia grew dramatically over the past few years, with the advent of more statistically powerful studies.17,18 Now the challenge is to discover which of these genetic changes alter brain circuitry. To find out how a gene works in the brain, scientists selectively silence that gene in a living neuron. A new genetic engineering technique called CRISPR (Clustered Regularly InterSpaced Palindromic Repeats), adapted for neuroscience by Feng Zhang, Ph.D., and colleagues at the Massachusetts Institute of Technology, offers a way to readily and precisely edit DNA—to fix “typos” in the genomes of living cells by adding or deleting genes using the Cas9 complex. A DNA snipping enzyme borrowed from bacterial antiviral defenses, teamed with a “programmable” RNA guidance system, becomes an exquisitely specific missile that can precisely target any site in the genome. A suspect gene variant—such as one of the more than 100 linked to schizophrenia that are driving the skyline in the graph above—could potentially be inserted into stem cells and grown into neurons—via “disease-in-a-dish” technology (see Highlight)—to study the cellular machinery of the disease process. The CRISPR technology could someday evolve into a therapeutic tool for treating such genetically influenced mental illnesses.19

“We’ve come to view the Cas9 complex as the ultimate guided missile that we can use to target precise sites in the genome.”

Feng Zhang, Ph.D., Massachusetts Institute of Technology

Highlight from Strategic Objective 1