Evaluation of DNA yield from various sources for use in single nucleotide polymorphism panels
Dates
Publication Date
2023-07-28
Start Date
2014-01-01
End Date
2021-12-30
Citation
Walter, W.D. and Pearce, D. 2023. Evaluation of DNA yield from various sources for use in single nucleotide polymorphism panels: U.S. Geological Survey data release, https://doi.org/10.5066/P96VPBSO.
Summary
Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, micro-satellites have been the primary method, however, there currently is a shift from micro-satellites to single nucleotide polymorphisms (SNPs). With the DNA requirements being different, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in various panels. We found four sample categories that met the DNA requirements for use in all [...]
Summary
Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, micro-satellites have been the primary method, however, there currently is a shift from micro-satellites to single nucleotide polymorphisms (SNPs). With the DNA requirements being different, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in various panels. We found four sample categories that met the DNA requirements for use in all three panels, three sample categories that only met the DNA requirements for two panels, and one sample category that did not meet any of the three panels requirements. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates, tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction could influence DNA yield.
