Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats

Gileta, Alexander F.; Gao, Jianjun; Chitre, Apurva S.; Bimschleger, Hannah; Pierre, Celine L. St.; Gopalakrishnan, Shyam; Palmer, Abraham A.

doi:10.1534/g3.120.401325

Cited by 23 publications

(45 citation statements)

References 72 publications

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“…To obtain genotypes, we used ddGBS, a genotyping method that reduces the complexity of the genome by only sequencing regions proximal to restriction enzyme cut sites [6,74]. We have recently described the technical aspects of this protocol in detail [75]. The ddGBS protocol used in this paper is a synthesis of the GBS approach described in Graboski et al [76] and used more recently by Parker et al [14] and Gonzales et al [33], and an analogous approach known as double digest restriction associated DNA sequencing (ddRADseq) [77].…”

Section: Methodsmentioning

confidence: 99%

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Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Gileta

Fitzpatrick

Chitre

et al. 2018

Preprint

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30Sprague Dawley (SD) rats are one of the most commonly used outbred rat strains. Despite 31 this, the genetic characteristics of SD are poorly understood. We collected behavioral data from 32 4,625 SD rats acquired predominantly from two commercial vendors, Charles River Laboratories 33 and Harlan Sprague Dawley Inc. Using double-digest genotyping-by-sequencing (ddGBS), we 34 obtained dense, high-quality genotypes at 234,887 SNPs across 4,061 rats. This genetic data 35 allowed us to characterize the variation present in Charles River vs. Harlan SD rats. We found that 36 the two populations are highly diverged (FST > 0.4). We also used these data to perform a genome-37 wide association study (GWAS) of Pavlovian conditioned approach (PavCA), which assesses the 38 propensity for rats to attribute motivational value to discrete, reward-associated cues. Due to the 39 genetic divergence between rats from Charles River and Harlan, we performed two separate 40 GWAS by fitting a linear mixed model that accounted for within vendor population structure and 41 using meta-analysis to jointly analyze the two studies. We identified 18 independent loci that were 42 significantly associated with one or more metrics used to describe PavCA; we also identified 3 43 loci that were body weight, which was only measured in a subset of the rats. The genetic 44 characterization of SD rats is a valuable resource for the rat community that can be used to inform 45 future study design. 46 AuthorSummary 47 Outbred Sprague Dawley rats are among the most commonly used rats for neuroscience, 48 physiology and pharmacological research. SD rats are sold by several commercial vendors, 49 including Charles River Laboratories and Harlan Sprague Dawley Inc. (now Envigo). Despite their 50wide spread use, little is known about the genetic diversity of SD. We genotyped more than 4,000 51 2 SD rats, which we used to characterize genetic differences between SD rats from Charles River 52 Laboratories and Harlan. Our analysis revealed that the two SD colonies are highly divergent. We 53 also performed a genome-wide association study (GWAS) for Pavlovian conditioned approach 54 (PavCA), which assesses the propensity for rats to attribute motivational value to discrete, reward-55 associated cues. Our results demonstrate that, despite sharing an identical name, SD rats are 56 obtained from different vendors are genetically very different. We conclude that results obtained 57 using SD rats should not be presented without also carefully noting the vendor. 58 Introduction 59Rats are among the most commonly used organisms for experimental psychology and 60 biomedical research. Whereas research using mice makes extensive use of inbred strains, in rats, 61 it is more common to use commercially available outbred populations. Among the commercially 62 available outbred rat populations, the Sprague Dawley strain (SD) is one of the most widely used. 63SD rats are distributed by several vendors. Each vendor has multiple breeding locations, and each 64 breeding locatio...

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Section: Methodsmentioning

confidence: 99%

“…We have recently described the bioinformatic steps that we use for ddGBS in detail [75]. We follow an analogous approach in this paper, though we deviate at the imputation step due to our use of SD instead of HS rats.…”

Section: Methodsmentioning

confidence: 99%

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Gileta

Fitzpatrick

Chitre

et al. 2018

Preprint

Self Cite

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“…Several recent studies found that standard NGS software is preferable to RAD-specific software in RADseq data analyses (Gileta et al, 2020;Shafer et al, 2017;Warmuth & Ellegren, 2019;Wickland et al, 2017). Warmuth and Ellegren (2019) showed that incorporating genotype uncertainty using ANGSD can improve demographic inference from RADseq data when compared to both a RADseq specific genotype calling pipeline, STACKS (Catchen et al, 2013;Rochette et al, 2019), and a widely used NGS genotype calling pipeline, GATK.…”

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confidence: 99%

“…This approach outperformed the RADseq specific software STACKS and TASSEL-GBS (Glaubitz et al, 2014). Finally, Gileta et al, (2020) showed that by mapping to a reference genome, genotype calling can be greatly improved with haplotype imputation from genotype likelihoods using ANGSD and Beagle (Browning & Yu, 2009) in combination. However, these three novel pipelines for RADseq data all assume that a reference genome is available, which is frequently not the case.…”

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A reference‐free approach to analyse RADseq data using standard next generation sequencing toolkits

Heller

Nursyifa

Garcia‐Erill

et al. 2021

Molecular Ecology Resources

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Genotyping‐by‐sequencing methods such as RADseq are popular for generating genomic and population‐scale data sets from a diverse range of organisms. These often lack a usable reference genome, restricting users to RADseq specific software for processing. However, these come with limitations compared to generic next generation sequencing (NGS) toolkits. Here, we describe and test a simple pipeline for reference‐free RADseq data processing that blends de novo elements from STACKS with the full suite of state‐of‐the art NGS tools. Specifically, we use the de novo RADseq assembly employed by STACKS to create a catalogue of RAD loci that serves as a reference for read mapping, variant calling and site filters. Using RADseq data from 28 zebra sequenced to ~8x depth‐of‐coverage we evaluate our approach by comparing the site frequency spectra (SFS) to those from alternative pipelines. Most pipelines yielded similar SFS at 8x depth, but only a genotype likelihood based pipeline performed similarly at low sequencing depth (2–4x). We compared the RADseq SFS with medium‐depth (~13x) shotgun sequencing of eight overlapping samples, revealing that the RADseq SFS was persistently slightly skewed towards rare and invariant alleles. Using simulations and human data we confirm that this is expected when there is allelic dropout (AD) in the RADseq data. AD in the RADseq data caused a heterozygosity deficit of ~16%, which dropped to ~5% after filtering AD. Hence, AD was the most important source of bias in our RADseq data.

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“…Unfortunately, genome wide DNA variants have never been thoroughly uncovered in the NIH-HS rats. A recent study reported an adapted genotyping by sequencing (GBS) approach that was used to discover and genotype genome variants in this outbred strain [9,20]. No doubt, GBS is powerful, but this genome sampling sequencing approach may not reveal a comprehensive picture of DNA variants [21].…”

Section: Introductionmentioning

confidence: 99%

Novel roles of DNA variation in maintenance of AT rich genome and conserved function in rats

Zinski

Wang

Michal

et al. 2021

Preprint

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Whether or not DNA variation changes genome-wide nucleotide compositions remains largely unknown. By examining 4,604,291 DNA variants between two rat strains, we observed that sequencing depth is strongly correlated with genome content as 21.41, 38.36, 44.26 and 6512.70 average reads per locus were collected for Y, X, autosomes and mitochondrial (MT) genomes; respectively (P<0.0001). The mutation rates corresponding to these four genome subsets were 0.055, 0.401, 1.733 and 4.475 variants per kb (P<0.0001), confirming the links between recombination frequencies and DNA variability. Although SNPs (single nucleotide polymorphisms) tend to reduce AT content, more CG deletions than CG insertions (INDELs) implies the GC content would not increase. Therefore, the SNP-INDEL interplay may play a key role in maintenance of the AT-rich genomes in rat during evolution. Formation of CpG sites appear to be hindered because genome-wide G INDELs (1.38%) with C as the 5’-nucleotide and CG INDELs (1.19%) are rare. However, the relatively high C—>G/G—>C rate in 5’UTRs (untranslated regions) and G/C INDELs in the 5’UTR and/or exonic regions highlight their importance for execution of gene function. Our study provides evidence that DNA variation does not jeopardize genome stability and functional conservation during evolution.

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Adapting Genotyping-by-Sequencing and Variant Calling for Heterogeneous Stock Rats

Cited by 23 publications

References 72 publications

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies

A reference‐free approach to analyse RADseq data using standard next generation sequencing toolkits

Novel roles of DNA variation in maintenance of AT rich genome and conserved function in rats

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