Researchers in Europe have developed a new system to identify genes involved in rare and childhood diseases. This methodology, called Full Spectrum of Intolerance to Loss-of-function (FUSIL), could be used to pinpoint the genetic origin of several rare diseases though the use of mouse and informatics models. By identifying which genes are necessary for survival, scientists hope to be able to identify which genetic mutations of those genes lead to rare genetic disease.
Identifying the genetic source of a rare disease is one of the most difficult challenges faced by geneticists. The current diagnostic rate for rare diseases using sequencing programs is under 40%, meaning the majority of patients with a rare disease are not diagnosed on a genetic level, leading to a range of issues for the patient and family, not limited to psycho-social and healthcare costs. The low prevalence of rare diseases within the population makes it statistically difficult to fully understand their genetic causes, so additional disease-associated gene discovery methods are needed to complement current sequencing approaches.
The FUSIL resource is intended to help researchers identify mutations by categorizing which genes are essential for supporting life.
Gene essentiality, or the requirement of a gene for an organism’s survival, is known to correlate with intolerance to variation and has been directly assessed in a number of species using high-throughput cellular and animal models with disease.
In order to create FUSIL, researchers at the European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL–EBI), compared knockout mice viability and phenotyping data from the International Mouse Phenotyping Consortium (IMPC) to human cell lines provided by the Broad Institute’s Project Achilles. They then created categories to indicate, on a spectrum, how crucial a gene is to producing viable life. Readers can freely access the study databases used for EMBL-EBI’s Biostudies and the International Mouse Phenotyping Consortium.
The researchers then used FUSIL to identify new mutations likely responsible for rare childhood diseases by comparing their data with unsolved cases of genetic disorders identified by the 100,000 Genomes Project and the Deciphering Developmental Disorders (DDD) datasets.
“Loss of gene function is often referred to as a binary concept; lethal or viable,” says Violeta Muñoz-Fuentes, at EMBL-EBI. “In this study we show that gene essentiality is more of a spectrum ranging from cellular lethal, developmental lethal, sub-viable, viable with a visible phenotype, and viable without a visible phenotype.”
To clarify, cellular lethal would mean the gene would be essential for cell viability; developmental lethal would mean the gene would be essential for organism development; viable would mean the organism would be fully develop; and sub-viable would indicate that organism survival is less than expected.
The purpose for this classification was to demonstrate that genes in these five, mutually exclusive categories each have differing biological properties, particularly in diseases of Mandilianinheritance.
The scientists defined these categories for 3,819 genes, and then created an open access database to be used to benefit other researchers and provide insight for clinical applications.
“When you sequence a person’s genome it’s not always one mutation that stands out as altering a gene’s function,” said Terry Meehan, coordinator of Mouse Informatics at EMBL-EBI. “We currently don’t have a handle on which genes are important for development and which have a minor impact.”
“This study combines multiple sources of data from large scale projects to identify new candidate genes that, when mutated, are likely to have a causal relationship with rare human disorders,” said Pilar Cacheiro, research fellow at Queen Mary University of London. “Nearly 6% of the population are affected by these diseases during their lives.”
Researchers at EMBL–EBI are hoping that further advances in whole genome sequencing (WGS) using bioinformatics to isolate challenging genetic data will change the way scientists research and diagnose rare genetic diseases. The majority of rare disease patients remain undiagnosed due to a lack of detection or because a previously unknown gene is disrupted, but hopefully though FUSIL scientists will be able to identify a genetic component to specific rare disease phenotypes though this modeling approach.
Additionally, the first step in finding a treatment for a disease is finding a cause, so to be able to use this database to identify a missing genetic component for certain conditions is an important step. By providing clinicians and researchers with an open access resource to identify high-quality candidates of rare disease mutations, these scientists hope FUSIL will speed up the process for finding a cure for countless research teams.
“Of particular interest [in] healthcare, we [have] demonstrated that the set of genes that are essential for organism development is particularly associated with known human developmental disorders,” says Damian Smedley, Reader in Computational Genomics at Queen Mary University of London. “This provides [potential treatment] candidates for [the] undiscovered causative genes for these conditions.”