MuWU: Mutant-seq library analysis and annotation.

Area of Science:

• Genomics
• Bioinformatics
• Plant Science

Background:

• Insertional mutagenesis is crucial for creating genome-wide loss-of-function mutations.
• Sequence-indexed mutant collections accelerate functional genomics and reverse genetics.
• Efficient computational analysis of Mutant-seq data is essential for generating these resources.

Purpose of the Study:

• To present MuWU, an automated workflow utility for processing Mutant-seq reads.
• To facilitate the identification of insertion sites for mutant collections like BonnMu in maize.
• To provide a fast, one-stop downstream processing pipeline for Mutant-seq data.

Main Methods:

• Developed MuWU as an automated, Snakemake-based workflow.
• Designed MuWU to process Mutant-seq reads for identifying tagged genes and insertion sites.
• Implemented functionality to differentiate germinal and somatic mutations and assign insertions to seed stocks.

Main Results:

• MuWU successfully automates complex bioinformatic tasks for Mutant-seq data.
• The workflow efficiently identifies insertion sites and links them to specific mutant lines.
• MuWU is adaptable for use with other species and transposable elements.

Conclusions:

• MuWU provides an efficient and reproducible solution for analyzing Mutant-seq data.
• This tool significantly aids in the characterization of insertional mutant collections for functional genomics.
• MuWU is freely available, promoting its use in diverse research settings.