icHET: interactive visualization of cytoplasmic heteroplasmy

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Heteroplasmy, the coexistence of different organelle genome types, is well-studied in animals.
• A significant gap exists in genome-wide heteroplasmy analysis tools for non-animal systems.
• Current methods lack comprehensive visualization and exploration capabilities.

Purpose of the Study:

• To introduce icHET, a novel computational workflow for analyzing and visualizing genome-wide heteroplasmy.
• To provide a tool for exploring heteroplasmy across diverse taxonomic groups.
• To facilitate the discovery of heteroplasmy patterns in multiple genomic samples.

Main Methods:

• Developed icHET, a computational workflow utilizing short-read sequencing data.
• Designed an interactive visualization component for heteroplasmy exploration.
• The workflow requires organellar (mitochondrial or plastid) and nuclear reference genomes.

Main Results:

• icHET enables genome-wide heteroplasmy analysis for any organism with appropriate reference genomes.
• The workflow produces interactive visualizations for enhanced data exploration.
• Facilitates the discovery of heteroplasmy across multiple samples.

Conclusions:

• icHET addresses the need for accessible genome-wide heteroplasmy analysis tools beyond animal systems.
• The interactive visualization aids in understanding complex heteroplasmy patterns.
• This workflow supports broader research into organelle genome dynamics.