Comparison of the effectiveness of ISJ and SSR markers and detection of outlier loci in conservation genetics of Pulsatilla patens populations

Are the Organellar Genomes Useful for Fine Scale Population Structure Analysis of Endangered Plants?-A Case Study of Pulsatilla patens (L.) Mill

Pulsatilla patens is a rare and endangered species in Europe and its population resources have significantly decreased over the past decades. Previous genetic studies of this species made it possible to estimate the genetic diversity of the European population and to describe the structure of chloroplast and mitochondrial genomes. The main aim of these studies was to characterize the variability of chloroplast and mitochondrial genomes in more detail at the intra-population and inter-population levels. Our study presents new organelle genome reference sequences that allow the design of novel markers that can be the starting point for testing hypotheses, past and modern biogeography of rare and endangered species P. patens, and adaptive responses of this species to changing environments. The study included sixteen individuals from five populations located in Northeastern Poland. Comparative analysis of 16 P. patens plastomes from 5 populations enabled us to identify 160 point mutations, including 64 substitutions and 96 InDels. The most numerous detected SNPs and Indels (75%) were accumulated in three intergenic spacers: ndhD-ccsA, rps4-rps16, and trnL(UAG)-ndhF. The mitogenome dataset, which was more than twice as large as the plastome (331 kbp vs. 151 kbp), revealed eight times fewer SNPs (8 vs. 64) and six times fewer InDels (16 vs. 96). Both chloroplast and mitochondrial genome identified the same number of haplotypes-11 out of 16 individuals, but both organellar genomes slightly differ in haplotype clustering. Despite the much lower variation, mitogenomic data provide additional resolution in the haplotype detection of P. patens, enabling molecular identification of individuals, which were unrecognizable based on the plastome dataset.

Assessing genotyping errors in mammalian museum study skins using high-throughput genotyping-by-sequencing

The use of museum specimens held in natural history repositories for population and conservation genetic research is increasing in tandem with the use of massively parallel sequencing technologies. Short Tandem Repeats (STRs), or microsatellite loci, are commonly used genetic markers in wildlife and population genetic studies. However, they traditionally suffered from a host of issues including length homoplasy, high costs, low throughput, and difficulties in reproducibility across laboratories. Massively parallel sequencing technologies can address these problems, but the incorporation of museum specimen derived DNA suffers from significant fragmentation and exogenous DNA contamination. Combatting these issues requires extra measures of stringency in the lab and during data analysis, yet there have not been any high-throughput sequencing studies evaluating microsatellite allelic dropout from museum specimen extracted DNA. In this study, we evaluate genotyping errors derived from mammalian museum skin DNA extracts for previously characterized microsatellites across PCR replicates utilizing high-throughput sequencing. We found it useful to classify samples based on DNA concentration, which determined the rate by which genotypes were accurately recovered. Longer microsatellites performed worse in all museum specimens. Allelic dropout rates across loci were dependent on sample quantity, with high concentration museum specimens performing as well and recovering quality metrics nearly as high as the frozen tissue sample. Based on our results, we provide a set of best practices for quality assurance and incorporation of reliable genotypes from museum specimens.