Mendelian diseases are diseases caused by a mutation in a single gene that arise spontaneously in the population. There are more than 4,500 known Mendelian diseases, and, according to the World Health Organization (WHO), the worldwide incidence of single gene disorders is approximately 10 for every 1,000 births. Unfortunately, the genetic mutation(s) underlying most of these diseases remains unknown.
There is hope, however. Recent advances in DNA sequencing and analysis are enabling Mendelian disease gene discovery at an unprecedented scale, and these new insights are ending diagnostic odysseys for many patients and their families. Moreover, disease gene discovery is helping to develop new therapeutic strategies. Nonetheless, more than two-thirds of the cases remain unsolved.
Mutated genes can be inherited in families, causing a variety of heritable disease phenotypes (physical traits that are genetically determined), depending on the gene and the mutation. Spontaneously arising gene mutations also occur in laboratory mouse populations, and these spontaneous mutant mice exhibit phenotypes similar to those in humans. Because of the physiological similarities between mice and humans, and because a high percentage of mouse genes are identical to human genes, mutant mice are important tools for geneticists and clinicians who seek to understand human disease pathways. Like humans, the actual genetic mutation remains unknown for many of these mutant mouse strains, and identifying it is the critical first step for understanding any Mendelian disease.
Taking advantage of new DNA sequencing technologies, a group at The Jackson Laboratory (JAX) led by Laura Reinholdt, Ph.D., set out to find the mutations responsible for the disease traits displayed in 172 spontaneous mutant mouse strains. To do so, they chose a technique often used in human clinical settings, known as exome sequencing. Exome sequencing focuses only on protein-coding genes, about 1.5% of the total genome sequence. Not surprisingly, it is a less expensive process and produces less data than whole genome sequencing, both important considerations, and it has been proven effective in finding disease mutations.
For their research, detailed in a paper in Genome Research, Reinholdt’s team developed an analytics pipeline optimized for mouse exome data and a powerful exome variation database. With the help of these tools, they found the likely disease-causing mutations in 91 of the mutant mouse strains, a tally of 53%, with 11% of the mutations discovered in novel genes, which hadn’t previously been associated with a disease phenotype. While this is a higher percentage of causative mutations than is observed in human clinical studies, it’s still somewhat low, given the extensive pedigrees and controlled breeding regimens used for the mice. So what could be causing Mendelian disease phenotypes in these strains if mutations can’t be found in the genes’ sequences? The researchers dug deeper to find out.
First they looked at strains that didn’t have a causative mutation identified, but had a strong candidate gene for the phenotype observed. They looked more closely at these specific genes and found that sequence variants were rare but something else was amiss. What they found was evidence for copy number variants (where instead of two copies of a gene there is only one or there are three or more) or structural mutations, where sequences are added to or deleted from each gene. Both are difficult to find using typical approaches for analyzing exome sequencing data. They also used whole genome sequencing with an analysis that detects structural anomalies with similar results—in many cases they were able to find a copy number variation or structural mutation that caused the phenotype.
So how does this relate to human disease? First, the thorough exploration of many mutations through the same process and pipeline shows that copy number variation and large-scale structural mutations may play a role in many of the human Mendelian diseases that have remained unsolved through exome sequencing alone. For clinical genomics clinics, it provides a likely “next step” for patient genome analyses when sequencing does not provide a causative mutation. Also, the researchers found relationships between mutated genes they found in mice and unresolved human diseases via a relatively straightforward data comparison. As more mouse disease mutations are found in mice in genes with human homologs—genes with similar function—the causative mutations for many rare human diseases will become far easier to find.