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In Ray Bradbury's classic short story "A Sound of Thunder," there is a lesson no doubt heavy on the minds of today's gene-hacking scientists: a man travels back in time to hunt dinosaurs, only to find that by mistakenly stepping on a butterfly he subtly alters the entire future. With our newly acquired ability to permanently alter the genetics of entire species, it's hard not to wonder whether Bradbury's writings were fiction or foreshadowing.

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The good news is that a group of scientists at MIT and Harvard think they may have come up with a way to keep genetically engineered mutants from messing around too much with the course of evolution.

Using a gene-editing technique called Crispr, scientists can make these mutants by creating what's known as a gene drive to circumvent the traditional rules of genetic inheritance. Gene drives overcome the 50-50 odds a parent has of passing on its genes to offspring, instead "driving" a desired gene edit to reoccur in nearly 100 percent of offspring. This kind of engineering could be useful in the wild for solving major global issues, like Zika virus: by engineering a mosquito that passes on a fatal defect to its offspring and releasing it to breed with wild populations, researchers believe they could vastly reduce the spread of Zika. The very big catch is that we have no sense of the size of such engineering's butterfly effects—it could theoretically cause a global mosquito extinction, which is probably a bad idea.

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That's where the new gene drive technique comes in. The MIT and Harvard scientists say they can eradicate concerns about the rampant spread of a genetic mutation in the wild by limiting how many generations of offspring wind up receiving the genetically engineered traits.

Previously, an organism altered with a gene drive would pass on all of its traits to its offspring, and its offspring would pass on all of those traits as well, indefinitely. But in what researchers are calling a "daisy chain gene drive," the ability to pass on those traits grows weaker with every generation, meaning scientists can, at least to some extent, control how many generations receive the gene-driven traits.

It works like this: the genetic components that make the gene drive work are split up and spread out across the genome, so that over time, some of those elements are not passed on to offspring, resulting in the gene-drive eventually ceasing to work. Because natural selection tends to eliminate lab-altered genes, the idea is that over time the offspring that maintained the gene-edited traits will die out, even if those populations grew more quickly to start.

The research is still nascent—it is mostly based on modeling, with only two-element daisy drive systems having been successfully demonstrated. Currently, MIT's Sculpting Evolution lab is working on testing it out using nematode worms in the lab.

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But the idea here is big. Gene drives could be used to prevent diseases like malaria and Zika, by creating mosquito populations that self-destruct over time. They could promote sustainable agriculture by killing the need for toxic pesticides by reversing pesticide resistance in insects and herbicide resistance in weeds. They could help conserve endangered species of plants and animals by killing off the invasive species threatening them. And the daisy-drive could render concerns about the unknown domino effects of such science a footnote, making it extraordinarily improbable that scientists might accidentally alter an entire species. Assuming it all goes right.

"We hope that daisy drives will simplify decision-making concerning the possible alteration of wild organisms in order to address some of the world’s most critical disease and ecologic threats," the scientists wrote in a post on Medium.  "Our goal is to promote responsible use and to give local communities the autonomy to decide how to solve their own ecological problems."

If it works, the daisy-chain gene drive could substantially reduce the risk of tinkering with genetics, and open the future up to a vast array of lab-engineered possibility.