How-to use microsatellites for population genetics, Part I: Study Design, DNA extraction, Microsatellite Marker Design/Outsourcing

So… you want to use microsatellite markers to assess the genetic variation and population structure of your focal study organism? Well if you are anything like me two years ago.. then you have no idea where to start. Otherwise- congratulations if you are already an expert- in which case you probably don’t need to read on 🙂

“See No Weevil, Hear No Weevil, Speak No Weevil”                                                                          Illustration by Jacki Whisenant, contracted by Julie Hopper. Copyright 2017.

Two years ago, I was just like you (and these weevils above), and felt a bit overwhelmed and lost in undertaking the large task of designing microsatellite markers and genotyping these markers for the two weevils species (Neochetina bruchi and N. eichhorniae) that I have discussed in previous posts. 

Very briefly to recap on my work:  these two weevil species are used all over the world for the biological control of the invasive water hyacinth, including the Sacramento-San Joaquin River Delta, California. They have had variable success, with notable reduction of biomass and cover of water hyacinth in warmer climates compared to more temperate climates such as the Delta. Although temperature plays a large role in their success, I am also investigating the role of genetic variation and particularly whether there is lower genetic diversity and heterozygosity in the Delta compared to the native origin of these weevils (Uruguay and Argentina).

In Part I- (this blog), I will detail the how-to’s of sampling design and strategy, and the development of (or outsourcing) microsatellite markers.

In Part II- (next blog) I will discuss how to make your final microsatellite marker selections, and the workflow of multiplex PCR and genotyping.

In Part III- (come back in a month!) I will detail how to analyze the data with various R-packages and other computer programs, and how to format the data files correctly for these programs.

On this note, please research your study system thoroughly, as every organism is different and may require different sampling strategies and methods than I detail here for two diploid beetle species (Insecta). Additionally.. my overview below on Part I- is very brief and I definitely skip small steps to be succinct. Also my suggestions are not the only way to do things and below this blog, I post links to several other great resources. Lastly- This work is currently in prep for publication and I will post an update again after publication.

Part I: 


Figure from: Grunwald et al. 2017, Phytopathology
Figure from: Grunwald, N.J., Everhart, S.E., Knaus, B.J., Kamvar, Z.N. 2017. Best Practices for Population Genetic Analyses. Phytopathology 107, 1000-1010.

Sampling Design and Strategy:

First before you start sampling or ordering primers- make sure that you have a solid study question with a testable hypothesis, and a good study framework.

Next: all of the power in your genetic analyses (aka, accuracy and ability to detect differentiation among populations, etc.) depend on: 1) your sample quality (aka DNA quality), the number of samples (replicates) per treatment or location, 2) the number of high quality microsatellite markers (e.g.quality relating to two important characteristics: markers are polymorphic -having 2 or more alleles per locus-with more being better, and the markers lack true null alleles), 3) the robustness of your PCR  – whether the PCR conditions are truly suitable for your markers, and whether they can result in reproducible data, 4) the assumptions of the data and 5) the choice of statistical tests and whether the tests are truly suitable for the data.

I will cover the latter (regarding statistical tests) in a future blog, but for today I would like to focus on the ideal # of samples and the # of polymorphic markers. There has been debate about how many samples and how many markers are necessary for robust studies, and if you study an endangered species -sometimes you just have to work with what you got!

In a perfect world– you will want to make up for what you lack in samples with microsatellite markers (loci) and vice versa. So if you have a lower end of replicates, then you will want a higher number of microsatellite markers (# of loci, and more important is to have polymorphic loci with 2 or more alleles/locus) to test for each individual (replicate), and again vice-versa. There are a couple great papers that discuss sampling strategies and study design that you should definitely check out, particularly the one noted in the figure above (Grunwald et al. 2017), as well as Hale et al. 2012 which states that 25-30 individuals per population should be sufficient to accurately estimate allele frequencies given population (with some caveats). Caveats being that obviously, 25-30 individuals per population would likely NOT be enough if you only have four microsatellite markers, particularly if these markers are not polymorphic or very variable (variability referencing to the # of alleles per locus- the more the better!).. so keep this in mind. In general, with that many samples- 10-15 polymorphic markers should be fine (although the more the better), but again this depends on your study question and study system. Also, more samples might be necessary if you are interested in population differentiation (population genetic structure). In fact, in a landscape genetics study, Landguth et al. 2012 demonstrated that increasing the number of loci (and particularly having more variable loci) is more likely to increase the power of population genetic inferences compared to increasing the number of individuals.

You can also test your samples with genotype accumulation curves to see if you have captured the majority of genetic variation (I used the poppr package in R for this and will discuss more on poppr and its primer in Part III of this blog series).

With that said.. If I would have known 1 year ago what I know now…. I would have asked for folks around the world to collect more weevils for me, and I would have extracted more DNA!  Just remember.. not all of your DNA extractions are going to end up working out..due to various human error and/or preservation issues. Thus its always good to add at least 10-20 more samples than you think you need!

Sampling locations of Neochetina bruchi and N. eichhorniae individuals that I used for the focal population genetics study (Hopper et al. In Prep). Thanks to all those who sent me weevils!

Designing or Outsourcing Microsatellite Marker Design: 

  • Marker Outsource Options: I want to first be upfront in that I actually ended up outsourcing this component of my study as I was going through a tough time and taking care of my dad who had metastatic cancer via at-home hospice care in Columbus, Ohio for two months. Needless to say- I was working remotely then, which made the decision to outsource this part of the lab work an easy decision. I researched a lot of outsource options and in the end I went with the cheaper and most recommended option by several colleagues- the Savannah River Ecology Lab at the University of Georgia. In the end I have mixed opinions on their work and please email me if you would like more info and I will detail the ups and downs.
  • Brief Workflow for designing microsatellite markers: 
    1. First! Check the literature to make sure microsatellite markers have not already been developed for your species or a sister species (the latter of which will sometimes work). Using previously developed markers is obviously the easiest and cheapest route!
    2. If the markers have not already been developed: Obtain high quality and high molecular weight DNA Extractions. I love doing 5% Chelex DNA extractions, but the resulting DNA can be full of PCR inhibitors- so I always use the second half of the DNAeasy kit to purify and clean up my DNA samples. You can also buy replacement spin columns for these kits way cheaper from Epoch Life Science. Then quantify them on a nano-drop or a similar DNA quantification instrument and additionally run them on a gel to make sure that you have ≥100 uL of ≥50 ng/uL of >10kb DNA per sample.
    3. Send to a sequencing facility (Illumina with paired ends >150bp preferred)
    4. Clean up sequences/fix Errors and Run a program called “Pal_finder”, or use a similar program. Pal_finder can analyze 454 or paired-end Illumina sequences ( ~150bp from each end).  This program sends possible primers to Primer3 for primer design and searches for how often each primer and primer pair occur.

    5. Filter the resulting data set by only including: a) sequences for which primers can be designed (e.g. enough flanking sequence) and b) primer pairs that occurred 1-3 times. Then, sort by motif length (di, tri, tetra, etc.) to quickly find tri or tetra nucleotide repeats and look to see if the motif was found in both directions of the sequence (which can be bad as they typically end up being smaller PCR products, but this depends on your goals). Finally, order a bunch of the primers that look promising-say 48 primer pairs to start, and test them out on a subset of 24 individuals, with an equal distribution of these individuals across all your study locations, or select individuals that you think will have a lot of variation. See Initial PCR testing in the next Blog. 

To be continued…


Grunwald, N.J., Everhart, S.E., Knaus, B.J., Kamvar, Z.N. 2017. Best Practices for Population Genetic Analyses. Phytopathology 107, 1000-1010.

Hale, M.L., Burg, T.M., Steeves, T.E. 2012. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PloS one 7, e45170.

Landguth, E.L., Fedy, B.C., Oyler-McCance, S.J., Garey, A.L., Emel, S.L., Mumma, M., Wagner, H.H., Fortin, M.-J., Cushman, S.A. 2012. Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern. Molecular ecology resources 12, 276-284.

Helpful Resources on Getting Started for Part I

Lecture on Intro to Microsatellites

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