The maximal C(3) self-complementary trinucleotide circular code X in genes of bacteria, eukaryotes, plasmids and...

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology
• Computational Biology

Background:

• A set X of 20 trinucleotides was previously identified in prokaryotic and eukaryotic genes, exhibiting a preferential reading frame.
• This set X possesses mathematical properties, being a maximal C(3) self-complementary trinucleotide circular code.
• Recent advancements allow for analysis of trinucleotide data in plasmids and viruses, alongside expanded prokaryotic gene data.

Purpose of the Study:

• To re-evaluate and strengthen the identification of the circular code X in various gene kingdoms using a new statistical approach.
• To investigate the occurrence probability of complementary/permutation (CP) trinucleotide sets within gene kingdoms.
• To explore the presence and characteristics of variant trinucleotide codes in different gene taxonomic groups.

Main Methods:

• Quantified the preferential frame identification approach with a new definition analyzing CP trinucleotide set occurrence probability.
• Studied the circular code X across multiple gene taxonomic groups within kingdoms to enhance statistical significance.
• Developed a probabilistic model based on independent trinucleotide occurrence to explain observed frequencies and asymmetries.

Main Results:

• The circular code X was confirmed and strengthened in prokaryotic and eukaryotic genes, and newly identified in plasmid genes.
• A subset of X (18 or 16 trinucleotides) was found in viral genes.
• A probabilistic model successfully explained trinucleotide code frequencies and asymmetries across all studied gene kingdoms.
• Variant X codes were identified in approximately 30% of studied gene taxonomic groups in bacteria, eukaryotes, and plasmids, with some exhibiting self-complementary or C(3) self-complementary circular properties.

Conclusions:

• The study validates and expands the understanding of the trinucleotide circular code X across diverse gene kingdoms, including prokaryotes, eukaryotes, plasmids, and viruses.
• A probabilistic model provides a mechanistic explanation for the observed trinucleotide code properties.
• The identification of variant X codes reveals genetic diversity and suggests potential functional implications in various organisms.