Geneticists looking inside the nuclear genome for mutations that contribute to disease have long relied on a principal known as constraint modeling, which allows researchers to assess the degree of selective pressure that leads to the purging of certain gene variants. But while constraint models have been highly effective for identifying disease-causing variants in the nuclear genome, they have not been useful for mutations in the mitochondrial genome, a source of frustration for geneticists and families living with genetic illnesses.
Decoding disease: Novel tool helps identify mutations in mitochondrial DNA
