Resolving microsatellite genotype ambiguity in populations of allopolyploid and diploidized autopolyploid organisms using negative correlations between allelic variables

Abstract

11A major limitation in the analysis of genetic marker data from polyploid organisms is 12 non-Mendelian segregation, particularly when a single marker yields allelic signals from 13 multiple, independently segregating loci (isoloci). However, with markers such as mi-14 crosatellites that detect more than two alleles, it is sometimes possible to deduce which 15 alleles belong to which isoloci. Here we describe a novel mathematical property of codom-16 inant marker data when it is recoded as binary (presence/absence) allelic variables: under 17 random mating in an infinite population, two allelic variables will be negatively correlated 18 if they belong to the same locus, but uncorrelated if they belong to different loci. We

Ecological distributions, phenological isolation, and genetic structure in sympatric and parapatric populations of theLarrea tridentatapolyploid complex

“…Similarly, the frequency of double reduction (the probability of gametes getting both alleles from sister chromatids) can also influence allele frequencies in polyploids, altering demographic and coalescent expectations (Arnold et al, 2012). Though imperative for accurately modeling the population genetics of polyploids, recently developed computational approaches for the analysis of highly variable genetic markers in polyploids (POLYSAT, Clark and Jasieniuk, 2011; Clark and Schreier, 2015) are optimized for smaller microsatellite data sets and are unable to accommodate AFLP data sets as large as the one we generated here (see below). For these reasons, recent genetic studies of autopolyploid populations have generally used dominant markers and analytical methods that assume diploid inheritance (Guo et al, 2005; Falush et al, 2007; Kloda et al, 2008; Ma et al, 2010; Rebernig et al, 2010a, 2010b; but see Servick et al, 2015).…”

Secondary origin, hybridization and sexual reproduction in a diploid- tetraploid contact zone of the facultative apomictic orchidZygopetalum mackayi

“…For genotyping, PCR products were separated on 6% denaturing polyacrylamide gels for 3 hours at 250 volts and visualized by silver staining (Creste et al 2001). For each locus, polymorphism information content (PIC) (Botstein et al 1980) was calculated using the polysat (Clark & Schreier 2017) for R 3.4.0 (R Development Core Team 2017).…”

“…Genetic diversity within and among populations were estimated from three distinct indices as they accommodate the type of data used (allelic diversity): Shannon index (Shannon 2001), Simpson index (Simpson 1949) and Nei index (Nei 1978). Parameter values were estimated using the poppr and181 polysat packages (Kamvar et al 2014;Clark & Schreier 2017) for R 3.4.0 (R Development Core Team 2017).…”

“…The genetic relatedness among cytotypes was estimated based on Bruvo distances, using the package polysat (Clark & Schreier 2017) for R 3.4.0 (R Development Core Team 2017). Bruvo distances allow the comparison of individuals with different ploidy levels (Bruvo et al 2004).…”

Genetic profile analysis of aquaculture Russian sturgeon (Acipenser gueldenstaedtii) – implications for restocking measures

“…For genotyping we used the GeneScan-500 LIZ Size Standard (Applied Biosystems) with ABI Prism 310 Genetic Analyzer (Applied Biosystems), followed by the analysis with GeneMapper ID v3.1 (Applied Biosystems). We generated a matrix of pairwise distances between individuals by using cmdscale (http://stat.ethz.ch/R-manual/R-patched/library/stats/html/cmdscale.html) and the Polysat 1.4-1 R package (Clark & Drauch Schreier 2015), with two options provided by the package: Bruvo`s distance (Bruvo et al 2004) which takes mutational distance between alleles into account and Lynch`s distance (Lynch 1990) which is a simple band-sharing measure (Clark 2015). With the same Polysat 1.4-1 R package we performed a PCoA (Principal Coordinate Analysis) on the matrix, with the first two principal coordinates plotted and each strain represented by a different symbol.…”