Identifying adaptive variation in spatially structured populations using low-coverage whole-genome sequencing data.

Accounting for genotype uncertainty and structured migration in low-coverage sequencing data reduces false negatives in detecting adaptive variation in populations.

• Why it matters: Identifying adaptive genetic variation is crucial for conservation efforts, but current methods often ignore genotype uncertainty and evolutionary processes, leading to biased results.
• What they did: Researchers developed a model that incorporates genotype uncertainty from low-coverage sequencing and describes how local adaptation, migration, mutation, and drift interact, tested with simulations and applied to 3.7 million SNPs in North American rosy-finches.
• The result: The approach significantly decreases false negatives and improves detection of adaptive variation, enabling more accurate insights into evolutionary processes in structured populations.