Scientists have gotten pretty good, over the past few decades, at splicing in beneficial genes to crops.
By using techniques like CRISPR gene editing, agricultural scientists can create GMO crops for all kinds of scenarios: sure, mostly enhanced yield or resistance to pesticides, but also the capability of surviving in drought or higher temperatures or poor soil. That process, though, takes time: according to the Morgridge Institute for Research, the process is extremely expensive and can take more than a decade.
That’s just not fast enough to cope with a rapidly changing planet, with diseases that can drift and take hold within days. So researchers at the John Innes Centre, a British plant science facility, came up with what they’re calling AgRenSeq. (The name is a combination of association genetics and R gene enrichment sequencing; if any of that makes sense to you, or if you want it to, you can read the full study here.)
It is, as Popular Science calls it, a sort of “goggle” for wild varieties of crops, with wheat being the tested crop. Essentially, it provides a large searchable database of similar wild crops, allowing scientists to quickly find the section of the genome they want to sequence, and then sequence only that section. So if you want to solve a problem of, say, a particular fungal disease in wheat, you could find a variety of wild wheat that seems immune from that disease. Then you’d search the database to figure out what part of the wheat genome usually deals with resistance to fungal disease, and then sequence your fungus-proof wild wheat—but just that part.
The researchers say it could dramatically reduce both the time and the cost of genetic engineering, from a decade or more to only months, and from millions of dollars to thousands. The process could, if it proves effective—this is just a proof of concept—make it much, much easier for scientists to cope with new diseases, new pests, and new problems.