Sampling for Microsatellite-Based Population Genetic Studies: 25 to 30 Individuals per Population Is Enough to Accurately Estimate Allele Frequencies

<div><p>One of the most common questions asked before starting a new population genetic study using microsatellite allele frequencies is “how many individuals do I need to sample from each population?” This question has previously been answered by addressing how many individuals are needed to detect all of the alleles present in a population (i.e. rarefaction based analyses). However, we argue that obtaining accurate allele frequencies and accurate estimates of diversity are much more important than detecting all of the alleles, given that very rare alleles (i.e. new mutations) are not very informative for assessing genetic diversity within a population or genetic structure among populations. Here we present a comparison of allele frequencies, expected heterozygosities and genetic distances between real and simulated populations by randomly subsampling 5–100 individuals from four empirical microsatellite genotype datasets (<em>Formica lugubris</em>, <em>Sciurus vulgaris</em>, <em>Thalassarche melanophris</em>, and <em>Himantopus novaezelandia</em>) to create 100 replicate datasets at each sample size. Despite differences in taxon (two birds, one mammal, one insect), population size, number of loci and polymorphism across loci, the degree of differences between simulated and empirical dataset allele frequencies, expected heterozygosities and pairwise F_ST values were almost identical among the four datasets at each sample size. Variability in allele frequency and expected heterozygosity among replicates decreased with increasing sample size, but these decreases were minimal above sample sizes of 25 to 30. Therefore, there appears to be little benefit in sampling more than 25 to 30 individuals per population for population genetic studies based on microsatellite allele frequencies.</p> </div

Impact of sample size on the precision of sample allele frequencies.

<p>The range (lines) and mean ± one standard deviation (solid boxes) of allele frequencies of the 100 random replicates at each sample size for one common and one relatively rare allele in A) the ant dataset, B) the squirrel dataset, C) the albatross dataset and D) the kakī dataset. The alleles are: A) allele 159 at locus FE16 (grey boxes, real frequency  = 0.176) and allele 116 at locus FE17 (black boxes, real frequency  = 0.833); B) allele 196 at locus Scv8 (grey boxes, real frequency  = 0.126) and allele 162 at locus Scv23 (black boxes, real frequency  = 0.766); C) allele 187 at locus De35 (grey boxes, real frequency  = 0.147) and allele 165 at locus D5 (black boxes, real frequency  = 0.852); and D) allele 241 at locus Kakī_21 (grey boxes, real frequency  = 0.112) and allele 200 at locus Kakī_27 (black boxes, real frequency  = 0.745).</p

Impact of allele frequency and sample size on the accuracy of mean sample allele frequency.

<p>Mean difference from the real allele frequency for each sample size (of the 100 random replicates per size) for A) the ant dataset, B) the squirrel dataset, C) the albatross dataset and D) the kakī dataset. Black circles represent alleles with a real frequency ≥0.05 (data for the same allele at different sample sizes linked by a line), white circles represent alleles with a real frequency between 0.05 and 0.01, and grey circles represent alleles with a real frequency ≤0.01.</p

Impact of sample size on mean genetic distance between samples and the true population.

<p>Mean pairwise F_ST between the 100 random replicates and the empirical dataset for A) the ant dataset, B) the squirrel dataset, C) the albatross dataset and D) the kakī dataset at each sample size. Error bars are standard deviation.</p

Measuring change in sperm velocity for sperm incubated in their own seminal fluid vs rivals seminal fluid

Chinook salmon ejaculates were experimentally manipulated, separating sperm from seminal fluid and then recombining sperm with either seminal fluid from the same male or from a rival male. Ejaculates were collected from male chinook salmon taken at both stages of a two-stage social manipulation experiment. Social dominance was determined within each pair using video recordings of aggressive behavior. Sperm velocity was measured using Computer Assisted Sperm Analysis

Comparing sperm velocity and sperm concentration in males of different social status at each stage of the experiment

This file contains data used to compare ejaculate parameters between dominant and subdominant males at the same stage of the experiment. Sperm concentration and velocity measurements for male chinook salmon taken at both stages of a two-stage social manipulation experiment. Social dominance was determined within each pair using video recordings of aggressive behavior. Sperm concentration was measured using a haemocytometer. Sperm velocity was measured using Computer Assisted Sperm Analysis

Comparing fertilisation success for males of different social status and across seminal fluid treatments

Sperm competition trials were conducted, each trial using a single female and two male chinook salmon from a two-stage social manipulation experiment. Trials were also conducted using two seminal fluid treatments, (1) milt was unmanipulated, (2) seminal fluid was switched between the males in each trial. This data file contains sperm velocity measurements and paternity share data for each male. The paternity share of each male was determined using mircosatellite loci. Social dominance was determined within each pair using video recordings of aggressive behavior. Sperm concentration was measured using a haemocytometer. Sperm velocity was measured using Computer Assisted Sperm Analysis

NSW dataset and code for prioritization

Code and database for New South Wales prioritization. See ReadMe file for additional details, and see NZ dataset and code ReadMe (http://datadryad.org/resource/doi:10.5061/dryad.3qn55) for details on code design

Conservation Genomics Literature Search 2005-2015

This text file details the final list of publications fitting ISI Web of Science conservation genomics literature search detailed in Supplement 1 of the publication "Building strong relationships between conservation biology and primary industry leads to mutually-beneficial genomic advances". All final publications included in this literature search are detailed in the following text document by authors, year published, publication title, journal, and (if available) abstract

The preservation of gene order (synteny) surrounding the HOTAIRM1 (RF01976) locus across the Avian and other Vertebrate lineages.

<p>The preservation of gene order (synteny) surrounding the HOTAIRM1 (RF01976) locus across the Avian and other Vertebrate lineages.</p