“All of that collectively fits,” says Alan Packer, a senior scientist at the Simons Foundation Autism Research Initiative. “It’s a reassuring sign that they’re on the right track.”
Meanwhile, a second research group has developed a machine-learning algorithm called ExPecto that pinpoints how specific noncoding mutations can disrupt the way genes turn on and off throughout the body. The algorithm assigns a disease impact score to every single nucleotide in the human genome. “It can predict the impact of any variant anywhere, even if it has never been seen in the human population before,” says Olga Troyanskaya, deputy director for genomics at the Simons Foundation’s Flatiron Institute and one of ExPecto’s creators.
Using this method, Troyanskaya and her collaborators at the Flatiron Institute and Princeton University computed the impact of more than 140 million mutations in different bodily tissues. In a study published in the July 16, 2018, Nature Genetics, the researchers identified mutations potentially responsible for increasing the risk of several immune-related diseases, including chronic hepatitis B virus infection and Crohn’s disease. Study co-author Chandra Theesfeld of Princeton University then experimentally verified the results, finding that ExPecto’s predicted mutations were more promising potential contributors to the diseases than those proposed by previous studies.
Troyanskaya and colleagues next examined the impact of noncoding mutations in the Simons Simplex Collection. In a paper in the May 27, 2019, Nature Genetics, the team found that noncoding mutations in children with autism had significantly higher impact scores than those of their siblings. The researchers then inserted more than 50 of the highest-scoring mutations into cultured cells, where they found that the mutations did indeed affect the levels of different autism-associated proteins that appeared within the cells.
While these studies provide only initial glimpses of the role of noncoding DNA in human disorders, they are enough to provide avenues for further research and even some surprises. For instance, in the Science study, the promoter regions that took the hardest hit in individuals with autism were not regions close to the gene, but ones about 1,000 base pairs away. “It’s an interesting twist, and a slight mystery,” Sanders says. The explanation, he says, may be that these promoter regions act like enhancers — noncoding regions that increase the expression of a gene.
And while many of the noncoding mutations that cause disease probably do so by increasing or decreasing the transcription of a gene, the 2019 Nature Genetics study suggests that a second mechanism is also often at play, at least in autism: Some of the mutations, instead of affecting transcription levels, affect how messenger RNA gets processed after it has transcribed a gene. “Perhaps the scope of these latter kinds of mutations has been underestimated,” Packer says.
Ultimately, the 2019 Nature Genetics paper suggests, mutations in the noncoding genome may explain just as many cases of autism as mutations in genes do.
“These noncoding mutations are not just some esoteric thing that some kids might have,” Troyanskaya says. “They are quite likely just as important a player in autism as the coding mutations are.”
Jian Zhou, a Flatiron research fellow in Troyanskaya’s group, anticipates that ExPecto will be particularly useful for studying the evolutionary consequences of mutations. The researchers found, for instance, that mutations were less likely to affect genes expressed throughout the human body than genes specialized for one specific tissue type. “We don’t have a full explanation yet,” he says, but one possibility is that a mutation in a body-wide gene might have a higher likelihood of being fatal or otherwise preventing an individual from passing on their genetic information. “Evolution has already done the experiments for us,” Zhou says.
These three studies are just the first steps in the attempt to unlock the vast amounts of information hidden away in the noncoding portions of the genome. Troyanskaya hopes that eventually these approaches will improve how genetic data are used for diagnosing and treating diseases and disorders. “Right now, 98 percent of the genome is usually being thrown away,” she says. “Our work allows you to think about what we can do with the 98 percent.”