RADseq underestimates diversity and introduces genealogical biases due to nonrandom haplotype sampling

Abstract

Reduced representation genome-sequencing approaches based on restriction digestion are enabling large-scale marker generation and facilitating genomic studies in a wide range of model and nonmodel systems. However, sampling chromosomes based on restriction digestion may introduce a bias in allele frequency estimation due to polymorphisms in restriction sites. To explore the effects of this nonrandom sampling and its sensitivity to different evolutionary parameters, we developed a coalescent-simulation framework to mimic the biased recovery of chromosomes in restriction-based short-read sequencing experiments (RADseq). We analysed simulated DNA sequence datasets and compared known values from simulations with those that would be estimated using a RADseq approach from the same samples. We compare these ‘true’ and ‘estimated’ values of commonly used summary statistics, \(\pi\), \(\theta_w\), Tajima's D and \(F_{ST}\). We show that loci with missing haplotypes have estimated summary statistic values that can deviate dramatically from true values and are also enriched for particular genealogical histories. These biases are sensitive to nonequilibrium demography, such as bottlenecks and population expansion. In silico digests with 102 completely sequenced Drosophila melanogaster genomes yielded results similar to our findings from coalescent simulations. Though the potential of RADseq for marker discovery and trait mapping in nonmodel systems remains undisputed, our results urge caution when applying this technique to make population genetic inferences.