Doblin: inferring dominant clonal lineages from high-resolution DNA barcoding time series.

Area of Science:

• Evolutionary biology
• Microbial ecology
• Bioinformatics

Background:

• Cellular lineage dynamics are shaped by evolutionary forces like mutation, drift, and selection.
• Polyclonal populations exhibit clonal competition, influenced by ecological interactions.
• High-resolution lineage tracking with DNA barcoding and sequencing enables precise clonal dynamics quantification.

Purpose of the Study:

• Introduce Doblin, an R software suite for identifying dominant barcode lineages.
• Benchmark Doblin's accuracy in recovering clone identity and relative fitness.
• Apply Doblin to analyze clonal dynamics in bacterial evolution and microbial colonization.

Main Methods:

• Developed Doblin, an R suite utilizing high-resolution lineage tracking data.
• Benchmarked Doblin with simulated lineage data to assess accuracy.
• Applied Doblin to analyze laboratory evolution of Escherichia coli and gut microbial communities.

Main Results:

• Doblin accurately identifies clone identity and relative fitness from lineage tracking data.
• The software successfully analyzed clonal dynamics in antibiotic-treated E. coli.
• Doblin was effective in analyzing microbial community colonization experiments.

Conclusions:

• Doblin is a versatile tool for analyzing lineage time-series data across various experimental setups.
• The R suite aids in understanding clonal dynamics in evolutionary and ecological contexts.
• Doblin provides a robust method for identifying dominant lineages in complex biological systems.