Comparing SNPs and Microsatellites for Population Structure Inference
Author Information
Author(s): Liu Nianjun, Chen Liang, Wang Shuang, Oh Cheongeun, Zhao Hongyu
Primary Institution: Yale University
Hypothesis
How do single-nucleotide polymorphisms (SNPs) compare to microsatellites in inferring population structure?
Conclusion
Microsatellites are generally more informative than SNPs for population structure inference, but SNPs can be effective when a large number are available.
Supporting Evidence
- Microsatellites are on average four to twelve times more informative than SNPs for population comparisons.
- SNPs constitute the majority among the most informative markers despite being less informative on average.
- The study used STRUCTURE 2.0 to analyze population structure with high informativeness markers.
Takeaway
This study looked at two types of genetic markers to see which one helps scientists understand population groups better. It found that one type, called microsatellites, usually works better, but SNPs can also be useful if there are a lot of them.
Methodology
The study used the COGA dataset to compare the informativeness of 328 microsatellites and 15,840 SNPs in 236 unrelated individuals for population structure inference.
Potential Biases
Self-reported ethnicity was used for population classification, which may introduce bias.
Limitations
The study only included two subpopulations and had an unbalanced number of individuals in those populations.
Participant Demographics
Participants included 18 Black non-Hispanic, 206 White non-Hispanic, and 12 White Hispanic individuals.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website