PseudoChecker: an integrated online platform for gene inactivation inference

Area of Science:

• Comparative genomics
• Evolutionary biology
• Bioinformatics

Background:

• High-throughput genome sequencing generates vast amounts of data, necessitating advanced computational tools for analysis.
• Pseudogenization, the inactivation of genes through mutations, is an understudied yet significant source of evolutionary novelty.
• Existing methods for pseudogenization inference are limited, lacking automation and comprehensive evaluation metrics.

Purpose of the Study:

• To introduce PseudoChecker, the first integrated, automated online platform for inferring gene inactivation (pseudogenization).
• To provide a user-friendly, comparative genomics-based approach for identifying disruptive mutations and evaluating gene coding status.
• To develop a novel metric, PseudoIndex, for empirical assessment of gene pseudogenization.

Main Methods:

• Development of an automated comparative genomics pipeline for pseudogenization inference.
• Integration of a graphical user interface (GUI) for enhanced usability and accessibility.
• Implementation of the PseudoIndex metric for quantitative evaluation of gene inactivation.
• Validation using known pseudogenes and functional genes across mammalian lineages.

Main Results:

• PseudoChecker achieved high accuracy, correctly inferring 97% of gene loss events and 95% of functional genes in a validation set.
• The platform demonstrated full automation and a simplified workflow compared to existing methods.
• The PseudoIndex effectively provided an empirical measure for assessing gene coding status.

Conclusions:

• PseudoChecker is a reliable and accurate tool for pseudogenization inference, significantly advancing comparative genomics.
• The platform's automated nature and user-friendly interface facilitate the study of evolutionary genomic events.
• PseudoChecker is freely accessible online, promoting broader research in evolutionary biology and genomics.