A Practical Framework for GT-Seq Panel Optimization

Area of Science:

• Genomics
• Population Genetics
• Conservation Biology

Background:

• Genotyping-in-thousands by sequencing (GT-seq) panels are essential for ecological and evolutionary studies.
• Current optimization methods for GT-seq panels lack formalization, hindering reproducibility.

Purpose of the Study:

• To present a formalized, iterative workflow for optimizing GT-seq panels.
• To improve the performance and reliability of GT-seq panels across various populations and research contexts.

Main Methods:

• Developed an iterative optimization framework emphasizing systematic refinement and quality control.
• Applied the framework to develop and optimize a GT-seq panel for white-tailed deer.
• Utilized bioinformatic filtering and adjusted PCR conditions to select high-performing markers.

Main Results:

• Optimized a GT-seq panel from 646 loci to 508 high-performing markers.
• Increased the proportion of SNPs with >70% genotype rate from 25.5% to 87.8%.
• Enhanced the overall genotype rate from 39.4% to 84% through iterative refinement.

Conclusions:

• The presented iterative workflow provides a reproducible framework for GT-seq panel development.
• Prioritizing optimization is crucial for generating robust, high-throughput genotyping tools in non-model species.
• The workflow ensures consistent performance and maximizes data quality and utility for genetic studies.