DOI: 10.5061/dryad.cm08m
title: Data from: Paralogs are revealed by proportion of heterozygotes and deviations in read ratios in genotyping by sequencing data from natural populations

description: Whole genome duplications have occurred in the recent ancestors of many
 plants, fish, and amphibians, resulting in a pervasiveness of paralogous
 loci and the potential for both disomic and tetrasomic inheritance in the
 same genome. Paralogs can be difficult to reliably genotype and are often
 excluded from genotyping-by-sequencing (GBS) analyses; however, removal
 requires paralogs to be identified which is difficult without a reference
 genome. We present a method for identifying paralogs in natural
 populations by combining two properties of duplicated loci: 1) the
 expected frequency of heterozygotes exceeds that for singleton loci, and
 2) within heterozygotes, observed read ratios for each allele in GBS data
 will deviate from the 1:1 expected for singleton (diploid) loci. These
 deviations are often not apparent within individuals, particularly when
 sequence coverage is low; but, we postulated that summing allele reads for
 each locus over all heterozygous individuals in a population would provide
 sufficient power to detect deviations at those loci. We identified
 paralogous loci in three species: Chinook salmon (Oncorhynchus
 tshawytscha) which retains regions with ongoing residual tetrasomy on
 eight chromosome arms following a recent whole genome duplication,
 mountain barberry (Berberis alpina) which has a large proportion of
 paralogs that arose through an unknown mechanism, and dusky parrotfish
 (Scarus niger) which has largely re-diploidized following an ancient whole
 genome duplication. Importantly, this approach only requires the genotype
 and allele-specific read counts for each individual, information which is
 readily obtained from most GBS analysis pipelines.
description: HDplot R
 codeCode to run HDplot in R
 with generic format as input. Example input file is
 HDplot_R_genericInputHDplot.RHDplot_R_genericInputExample input file for HDplot R package. Each row is a locus entry, there are five columns of data associated with each locus. Column locus_ID contains the locus name. Sequence reads for each allele are given in columns depth_a and depth_b. Sequence reads for each allele are summed over heterozygous individuals for each locus. The num_hets column indicates the number of heterozygous individuals for each locus while the num_samples column contains the total number of individuals in the data set.HDplot_pythonPython code to run HDplot. This can take input directly from the Stacks program in the form of the .vcf output from Stacks. The file HDplot_python_exampleInput.vcf is included as an example of the required format. The file vcf_to_depth.py is necessary to run HDplot_python and must be included in the same directory.vcf_to_depthPython package called by HDplot_python.py that extracts sequence read counts from the .vcf format input.HDplot_python_exampleInputExample .vcf format input for the HDplot_python.py program.HDplot_simulationR code to simulate data for HDplot. This code also runs HDplot internally and produces plots showing expected distributions based on simulation parameters. Simulation parameters include the number of singleton, duplicate, and diverged duplicate loci, the total population size, the sampled population size, average read depth per locus, statistical distribution of reads per locus to sample from and distribution of reads per allele to sample from.Chinook_sequenceReadsChinook salmon dataset processed with HDplot in this manuscript. File is in the .vcf format output by the Stacks genotyping program.Barberry_sequenceReadsMountain Barberry dataset processed with HDplot in this manuscript. File is in the .vcf format output by the Stacks genotyping program.Parrotfish_sequenceReadsDusky Parrotfish dataset processed with HDplot in this manuscript. File is in the .vcf format output by the Stacks genotyping program.