Scaling-up RADseq methods for large datasets of non-invasive samples: Lessons for library construction and data...

Area of Science:

• Conservation genetics
• Wildlife population studies

Background:

• Genetic non-invasive sampling (gNIS) is vital for wildlife conservation, but DNA degradation and contamination pose challenges.
• Restriction-site-associated DNA sequencing (RADseq) generates vast genetic data, requiring shared loci with consistent coverage across individuals.

Purpose of the Study:

• To present a method for handling large-scale gNIS datasets from spotted hyenas using RADseq.
• To evaluate the impact of DNA quality, PCR duplicates, and SNP filters on genotype accuracy.
• To demonstrate a weighted re-pooling strategy for improved library preparation.

Main Methods:

• Generated 3RADseq data for over a thousand spotted hyenas from non-invasively collected samples.
• Screened samples for endogenous DNA, removed contaminated samples, and balanced sequencing pools.
• Assessed genotype accuracy using Mendelian errors in parent-offspring trios, considering DNA degradation, contamination, PCR duplicates, and SNP filters.

Main Results:

• Contaminated samples showed similar genotype error rates to non-contaminated samples when sequencing depth was balanced.
• PCR duplicates and SNP filtering strategies significantly impacted genotype accuracy.
• A weighted re-pooling strategy improved control over library preparation based on endogenous DNA content.

Conclusions:

• gNIS is a viable tool for large-scale genetic monitoring using SNPs.
• Optimized library preparation and data handling are crucial for accurate gNIS-based population genetics.
• The proposed methods enhance the reliability and cost-effectiveness of gNIS studies.