Whole-genome sequencing for generating SNP data is increasingly used in population genetic studies. However, obtaining genomes for massive numbers of samples is still not within the budgets of many researchers. It is thus imperative to select an appropriate reference genome and sequencing coverage to ensure the accuracy of the results for a specific research question, while balancing cost and feasibility. To evaluate the effect of the choice of the reference genome and sequencing coverage on downstream analyses, we used five confamilial reference genomes of variable relatedness and three levels of sequencing coverage (3.5x, 7.5x and 12x) in a population genomic study on two caddisfly species: Himalopsyche digitata and H. tibetana. Using these 30 datasets (five reference genomes × three coverages × two target species), we estimated population genetic indices (inbreeding coefficient, nucleotide diversity, pairwise and genome-wide FST) based on variants and population structure (PCA and admixture) based on genotype likelihood estimates. The results showed that both distantly related reference genomes and lower sequencing coverage lead to degradation of resolution. In addition, choosing a more closely related reference genome may significantly remedy the defects caused by low coverage. Therefore, we conclude that population genetic studies would benefit from closely related reference genomes, especially as the costs of obtaining a high-quality reference genome continue to decrease. However, to determine a cost-efficient strategy for a specific population genomic study, a trade-off between reference genome relatedness and sequencing depth can be considered.