Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for...

Area of Science:

• Molecular Ecology
• Population Genetics
• Genomics

Background:

• Restriction site-associated DNA sequencing (RADseq) is a powerful tool for studying genetic variation in nonmodel organisms.
• Genotyping errors in RADseq data can significantly impact population genetic analyses.
• Limited attention has been given to estimating and reporting genotyping error rates for RADseq.

Purpose of the Study:

• To quantify genotyping error in RADseq data without a reference genome.
• To optimize de novo assembly parameters in Stacks for error reduction and locus recovery.
• To estimate error rates at the locus, allele, and single-nucleotide polymorphism levels.

Main Methods:

• Utilized individual sample replicates to assess genotyping error.
• Employed the Stacks software package for de novo assembly parameter optimization.
• Applied double-digest RAD sequencing to a nonmodel plant species (Berberis alpina).

Main Results:

• Developed a method to quantify RADseq genotyping error without a reference genome.
• Optimized Stacks parameters to minimize errors and maximize informative loci.
• Quantified error rates for loci, alleles, and single-nucleotide polymorphisms using empirical data.

Conclusions:

• Accurate estimation and reporting of genotyping error are essential for reliable population genetic inferences from RADseq data.
• The developed methods improve the accuracy and reliability of RADseq-based studies in nonmodel organisms.
• This work provides a framework for assessing and mitigating genotyping errors in RADseq analyses.