DOI: 10.5061/dryad.fqz612jss
title: Alignment-free methods for polyploid genomes: quick and reliable genetic distance estimation

description: Polyploid genomes pose several inherent challenges to population genetic
 analyses. While alignment-based methods are fundamentally limited in their
 applicability to polyploids, alignment-free methods bypass most of these
 limits. We investigated the use of Mash, a k-mer analysis tool that uses
 the MinHash method to reduce complexity in large genomic datasets, for
 basic population genetic analyses of polyploid sequences. We measured the
 degree to which Mash correctly estimated pairwise genetic distance in
 simulated haploid and polyploid short-read sequences with various levels
 of missing data. Mash-based estimates of genetic distance were comparable
 to alignment-based estimates, and were less impacted by missing data. We
 also used Mash to analyze publicly available short-read data for three
 polyploid and one diploid species, then compared Mash results to published
 results. For both simulated and real data, Mash accurately estimated
 pairwise genetic differences for polyploids as well as diploids as much as
 476 times faster than alignment-based methods, though we found that Mash
 genetic distance estimates could be biased by per-sample read depth. Mash
 may be a particularly useful addition to the toolkit of polyploid
 geneticists for rapid confirmation of alignment-based results and for
 basic population genetics in reference-free systems or those with only
 poor quality sequence data available.
description: Simulated reads for haploid and polyploid samples for genetic
 distance estimation.  We simulated phylogenetic trees
 using toytree (Eaton,
 2020) in Python 3.7 for 50 individuals using a tree height of
 1e6, then simulated SNP loci following these trees by generating sequences
 in ipcoal (McKenzie
 & Eaton, 2020). For haploid data, we simulated 1000 loci
 with 100bp each for 50 individuals, diverging with an effective population
 size of 1e5, and a recombination rate of 1e-9. We simulated polyploid data
 in an allotetraploid scenario, wherein an ancestrally diverged lineage
 hybridizes, then diversifies into population groups. To accomplish this,
 we built a phylogenetic tree with a single deep node (700000 generations),
 and two symmetrical trees with shallower nodes (Figure 1), which represent
 the mean locus tree after polyploidization. We simulated 1000 loci for
 each of 30 individuals using the parameters listed above, then combined
 loci from symmetrical branches to create homeologous loci. This simulation
 method does not account for incomplete lineage sorting, wherein individual
 locus trees do not match the true population genetic history, but
 effectively simulates the problem of similar homeologous loci that can
 confound alignment-based methods. To simulate missing data, we used custom
 scripts in R to randomly remove sequence data for 5-75% of reads. We
 compared Mash and alignment-based analyses for each level of missing
 data.
description: Files are in fasta format. Associated processing scripts can be
 found at: <b id="docs-internal-guid-dc90dcc8-7fff-3c1b-e64c-eb45264854f3">https://github.com/avanwallendael/mash_sim.</b>