ADOPS--Automatic Detection Of Positively Selected Sites.

Area of Science:

• Evolutionary biology
• Molecular evolution
• Bioinformatics

Background:

• Maximum-likelihood methods are standard for detecting adaptive amino acid sites but require extensive data preparation and analysis.
• Existing methods necessitate multiple software applications for sequence alignment, phylogenetic inference, and model execution.
• Significant manual effort is involved in preparing input files and interpreting output from these analyses.

Purpose of the Study:

• To develop an automated and flexible software tool for detecting positively selected sites.
• To streamline the process of identifying amino acid sites responsible for adaptive evolution.
• To provide a user-friendly solution for analyzing unaligned nucleotide sequence data.

Main Methods:

• Development of the ADOPS (Automatic Detection Of Positively Selected Sites) software pipeline.
• Integration of sequence alignment, phylogenetic tree inference, and maximum-likelihood model execution.
• Application of the software to a dataset of 54 Coffea putative S-RNase sequences.

Main Results:

• Demonstration of ADOPS as an effective tool for automatic detection of positively selected sites.
• Successful identification of adaptive amino acid sites in Coffea S-RNase sequences under various conditions.
• Validation of the software's utility in a real-world evolutionary biology study.

Conclusions:

• ADOPS significantly simplifies and automates the detection of positively selected sites.
• The software reduces the manual effort and complexity associated with traditional methods.
• ADOPS is a valuable, freely available resource for evolutionary and molecular biology research.