Hello, it's my first work with microsatellite and the last one, I hope. I have 6 markers for some populations of Microtus gregalis from Transbaikal region. In some of them for big proportion of samples there are strange peaks patterns I can't explain. Unfortunately, I haven't time to sequence all the strange patterns, so maybe anyone has any reasonable explanation to them. Until it I decided just to remove these samples.
A,B,C pictures are for one microsatellite locus. As I understand these samples are heterozygous, but the place of the second peak is unclear. D,E for the second misat locus, and samples here have more than two peaks, which can be understood as the real locus sizes. Which explanation could be for these pictures?
Looks like part of your issue is stuttering (also known as leading peaks) from 'slippage' of the Taq polymerase. These two resources may help you better interpret what you're seeing:
Article Development and Use of Single Sequence Repeats (SSRs) Marker...
https://openwetware.org/wiki/Luckau_Protocols:Scoring
Welcome to microsatellite genotyping. Your experience is typical. One question I had regarding your specific situation is whether or not you are multiplexing your markers on the electrophoresis run? D and E look to me to be characteristic of pull-up of similarly sized alleles from an adjacent locus that has a different dye. In other words, if you have extremely high fluorescence of one of your other loci in the same area, even if they are a different dye, there my be bleed-through that is confounding the genotype of your blue locus. You can check this by turning on your other dye colors to see if some other dye peak is sitting there in the same spot where you're seeing multiple alleles for your blue locus.
With regard to A, B and C, my advice is to be consistent about calling the last peak in the series. So, for instance, on A, I would call the tallest peak as allele #1, and the last peak as allele #2. It looks to me like you have stuttering + large allele dropout. It makes it challenging, but there's not much you can do about it other than either call it missing data, OR call the genotypes using a consistent method.
If you get anyone on here telling you how to "fix" this by adjusting PCR conditions, I'd encourage you to NOT waste your time on that. In my experience it is unlikely to fix anything. Some loci are just tough to score and no amount of optimization will fix that.
Good answers, are these peaks better than the bands observed in gel electrophoresis?
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