TwinCons: Conservation score for uncovering deep sequence similarity and divergence

Area of Science:

• Bioinformatics
• Computational Biology
• Molecular Evolution

Background:

• Detecting deep evolutionary relationships in biological sequences is challenging.
• Identifying conserved and variable regions is crucial for understanding protein and nucleic acid function.
• Signature positions, conserved within groups but different between them, offer unique insights.

Purpose of the Study:

• To develop a novel computational tool, TwinCons, for analyzing sequence alignments.
• To identify conserved, variable, and signature positions and segments within alignments.
• To enable combined sequence and structural analysis for deeper evolutionary insights.

Main Methods:

• TwinCons utilizes composite alignments with pre-defined groups as input.
• It mathematically calculates the 'cost' of transforming one group to another at each alignment position.
• The program outputs scores representing conserved, variable, and signature positions, enabling visualization.

Main Results:

• TwinCons successfully detected conserved segments between proteins in translation and transcription systems.
• It identified conserved residues and distributed signatures across ribosomal RNA (rRNA) structure.
• The tool revealed deep co-evolution between bacterial and archaeal ribosomal proteins (rProteins) and rRNA.

Conclusions:

• TwinCons provides a unified score for conserved, variable, and signature positions, facilitating structural mapping.
• The program's ability to analyze both nucleic acid and protein alignments enables integrated analyses.
• TwinCons uncovered deep co-evolutionary signals between rRNA and rProteins at the base of the tree of life.