Analysis Of Codon Usage Patterns In Genes Related To Amyotrophic Lateral Sclerosis (ALS)

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease marked by motor neuron degeneration and complex genetic underpinnings. Despite growing research into its molecular pathology, the role of codon usage bias (CUB) in ALS-related genes remains largely unexplored. In this study, we analyzed 607 ALS-associated genes and compared them with 138 human housekeeping genes to examine differences in codon usage. Using tools such as CAIcal and CodonW, we assessed nucleotide composition, GC content, RSCU values, ENC, neutrality plots, and parity plots. Statistical testing (Mann–Whitney U test) revealed 15 codons with significant usage differences between ALS and non-disease genes. These codons were further used as features in machine learning models (KNN, SVM, RF), where Random Forest achieved the highest classification accuracy (85.9%). Our results indicate that ALS genes are characterized by GC-rich codon preferences influenced by natural selection and functional constraints, likely related to translational efficiency and gene expression optimization. This codon-level distinction has implications for ALS biomarker discovery and the rational design of therapeutic gene constructs.