Compositional Features and Codon Usage Pattern of Genes Associated with Parkinson's Disease.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Codon usage bias (CUB) reflects genome organization and gene expression.
• Parkinson's disease (PD) genetics is complex, with limited research on CUB in associated genes.

Purpose of the Study:

• To investigate codon usage patterns and compositional features of PD-associated genes using bioinformatics.
• To identify over-represented and under-represented codons and understand factors influencing CUB in PD.

Main Methods:

• Bioinformatic analysis of protein-coding sequences from PD-associated genes.
• Calculation of improved effective number of codons (Nc) and Nc prime.
• Analysis of GC content, Relative Synonymous Codon Usage (RSCU), Correspondence Analysis (COA), and Neutrality Plot.

Main Results:

• Low CUB indicated by average Nc (42.74) and Nc prime (44.26).
• GC content near 50%, with GC1 highest and GC2 lowest.
• GTG (Val) was the sole universally over-represented codon; other over-represented codons ended in A/T, and under-represented codons ended in G/C.
• Specific codons were absent in certain PD genes (e.g., SNCA1-8).
• COA showed distinct codon usage patterns among PD genes.
• Neutrality plot suggested mutation pressure influences CUB.

Conclusions:

• PD-associated genes exhibit low codon usage bias.
• Specific codon usage patterns and absences are notable in these genes.
• Mutation pressure is a significant factor shaping codon usage bias in Parkinson's disease genetics.