Shi, C.-M. | bioRxiv Science

bioRxiv2019

Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski’s scorpion (Scorpiones: Buthidae) in arid Asian inland

Reliable delimitation of venomous scorpions is not only consequential to toxicological studies but also instructive to conservation and exploration of these important medical resources. In the present study, we delimited species boundary for the the Przewalski’s scorpion from arid northwest China through a combined approach employing phylogenetic analysis, ecological niche modeling and morphological comparison. Our results indicate that the the Przewalski’s scorpion represent an independent taxonomic unit and should be recognized as full species rank, Mesobuthus przewalsii stat. n.. This species and the Chinese scorpion M. martensii represent the eastern members of the M. caucasicus species group which manifests a trans-Central Asia distribution across the Tianshan Mountains range. We also discussed the likely geographic barrier and climatic boundary that demarcate distributional range of the the Przewalski’s scorpion.Competing Interest StatementThe authors have declared no competing interest.View Full Text

zoology↗

bioRxiv2018

AIM-SNPtag: a computationally efficient approach for developing ancestry-informative SNP panels

Inferring an individuals ancestry or group membership using a small set of highly informative genetic markers is very useful in forensic and medical genetics. However, given the huge amount of SNP data available from a diverse of populations, it is challenging to develop informative panels by exhaustively searching for all possible SNP combination. In this study, we formulate it as an algorithm problem of selecting an optimal set of SNPs that maximizes the inference accuracy while minimizes the set size. Built on this conception, we develop a computational approach that is capable of constructing ancestry informative panels from multi-population genome-wide SNP data efficiently. We evaluate the performance of the method by comparing the panel size and membership inference accuracy of the constructed SNP panels to panels selected through empirical procedures in former studies. For the membership inference of population groups including Asian, European, African, East Asian and Southeast Asian, a 36-SNP panel developed by our approach has an overall accuracy of 99.07%, and a 21-SNP subset of the panel has an overall accuracy of 95.36%. In comparison, the existing panel requires 74 SNPs to achieve an accuracy of 94.14% on the same set of population groups. We further apply the method to four subpopulations within Europe (Finnish, British, Spain and Italia); a 175-SNP panel can discriminate individuals of those European subpopulations with an accuracy of 99.36%, of which a 68-SNP subset can achieve an accuracy of 95.07%. We expect our method to be a useful tool for constructing ancestry informative markers in forensic genetics.

bioinformatics↗