Identifying disease-causing mechanisms and fundamental biology of neuromuscular disorder genes through genomic feature analysis
IntroductionNeuromuscular disorders (NMDs) encompass a broad group of conditions that primarily affect the peripheral nervous system. They are often caused by genetic alterations that impair skeletal muscle function and result in debilitating symptoms. Obtaining an accurate molecular diagnosis remains a challenge, potentially because variants in genes that have yet to be identified as causal. We therefore used advanced computational methods to study the genetic architecture of NMDs and to identify key features that distinguish NMD genes from other genes in the broader genome. MethodsCurated genes implicated in NMDs (n = 639; GeneTable of NMDs) were obtained and merged with a comprehensive set of genomic features for human autosomal protein-coding genes. Machine-learning-based feature selection and ranking were performed using Boruta, along with complementary analytical approaches. These analyses were used to identify the most important genic features (n = 134, subcategories: gene complexity, genetic variation, expression patterns, and other general gene traits) for discriminating NMD genes from other genes in the genome ResultsNMD genes exhibit enriched expression in disease-relevant tissues, including skeletal muscle and heart. Additionally, compared with other protein-coding genes, these genes exhibit increased transcriptomic complexity (e.g., longer transcripts and more unique isoforms), contain more short tandem repeats, and show greater variation in conservation across model organisms. ConclusionsThis study identified several key genomic features that may distinguish NMD genes from the rest of the genome. This may enhance the identification of novel causal genes and could ultimately facilitate earlier diagnosis and medical management for affected individuals.