摘要:Next-generation sequencing (NGS) technology is being applied to an increasing number of non-model species and has been used as the primary approach for accurate genotyping in genetic and evolutionary studies. However, inferring genotypes from sequencing data is challenging, particularly for organisms with a high degree of heterozygosity. This is because genotype calls from sequencing data are often inaccurate due to low sequencing coverage, and if this is not accounted for, genotype uncertainty can lead to serious bias in downstream analyses, such as quantitative trait locus mapping and genome-wide association studies. Here, we used high-coverage reference data sets from Crassostrea gigas to simulate sequencing data with different coverage, and we evaluate the influence of genotype calling rate and accuracy as a function of coverage. Having initially identified the appropriate parameter settings for filtering to ensure genotype accuracy, we used two different single-nucleotide polymorphism (SNP) calling pipelines, single-sample and multi-sample. We found that a coverage of 15× was suitable for obtaining sufficient numbers of SNPs with high accuracy. Our work provides guidelines for the selection of sequence coverage when using NGS to investigate species with a high degree of heterozygosity and rapid decay of linkage disequilibrium.