nQuire: A Statistical Framework For Ploidy Estimation Using Next Generation Sequencing

Abstract

Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly -without measuring DNA content -from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats.We demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker's yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log-likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies.nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at github.com/clwgg/nQuire under the MIT license. Contact

Genotyping‐by‐sequencing and ecological niche modeling illuminate phylogeography, admixture, and Pleistocene range dynamics in quaking aspen (Populus tremuloides)

“…Given whole‐genome duplications and other polyploidization events (e.g., hybridization) are common in plants (e.g., Jiao et al, 2011; Wendel, Jackson, Meyers, & Wing, 2016), an adequate understanding of plant evolution, including the analysis and interpretation of population genetic data (e.g., Meirmans et al, 2018), requires information on ploidy variation. Recent years have witnessed a surge of interest in inferring ploidy directly from high‐throughput sequencing read data obtained from fresh plant material or herbarium specimens (e.g., Gompert & Mock, 2017; Viruel et al, 2019; Weiß et al, 2018). Using these techniques, our results show that it is feasible to establish the ploidy levels of P. tremuloides samples from GBS reads using GMM and ML approaches implemented in nQuire (Weiß et al, 2018), which are based on modeling SNP allele frequency histograms.…”

“…Recent years have witnessed a surge of interest in inferring ploidy directly from high‐throughput sequencing read data obtained from fresh plant material or herbarium specimens (e.g., Gompert & Mock, 2017; Viruel et al, 2019; Weiß et al, 2018). Using these techniques, our results show that it is feasible to establish the ploidy levels of P. tremuloides samples from GBS reads using GMM and ML approaches implemented in nQuire (Weiß et al, 2018), which are based on modeling SNP allele frequency histograms. Tetraploids were rare enough ( n = 2) to view them with low confidence, as they possibly reflect ploidy ambiguity, estimation errors, or sample contamination.…”

Differentiating diploid and triploid individuals using single nucleotide polymorphisms genotyped by amplicon sequencing

“…Methods have been developed that use data from next‐generation sequencing (NGS) instruments, but these methods were developed for data sets comprising thousands to hundreds of thousands of loci (Augusto Corrêa dos Santos, Goldman, & Riaño‐Pachón, ; Gompert & Mock, ; Weib, Pais, Cano, Kamoun, & Burbano, ). Amplicon sequencing techniques, such as Genotyping‐in‐Thousands by sequencing, or GT‐seq (Campbell, Harmon, & Narum, ), often genotype smaller numbers of loci (hundreds) with highly variable and skewed read depths.…”

“…This method has three main drawbacks: it requires identification of loci that are heterozygous prior to assessing ploidy, it expects polyploids to have higher heterozygosity than diploids (which may not be true for triploid fish depending on the position of the loci in relation to the centromere), and it does not allow correction for biased amplification or variable error rates. A second method is implemented in the software nquire (Weib et al, ). This method utilizes base frequencies at variables sites and then implements a Gaussian mixture model to determine the likelihood that a sample is diploid, triploid or tetraploid.…”

Performing Parentage Analysis for Polysomic Inheritances Based on Allelic Phenotypes

“…Fortunately, haplotype assembly (Aguiar and Istrail, 2013), phased sequencing (Yang et al, 2011;Manching et al, 2017) and haplotype inference (Neigenfind et al, 2008) can all help to maintain the efficiency of NGS data, and can segregate multi-allelic loci by combining the closely linked variants so as to increase the single-locus polymorphism. Additionally, polyploid genotype calling can directly call back the genotypes but can currently only be applied to the biallelic variants (Carley et al, 2017;Weiß et al, 2018).…”