Genotyping‐in‐Thousands by sequencing (GT‐seq): A cost effective SNP genotyping method based on custom amplicon sequencing

Abstract

Genotyping-in-Thousands by sequencing (GT-seq) is a method that uses next-generation sequencing of multiplexed PCR products to generate genotypes from relatively small panels (50-500) of targeted single-nucleotide polymorphisms (SNPs) for thousands of individuals in a single Illumina HiSeq lane. This method uses only unlabelled oligos and PCR master mix in two thermal cycling steps for amplification of targeted SNP loci. During this process, sequencing adapters and dual barcode sequence tags are incorporated into the amplicons enabling thousands of individuals to be pooled into a single sequencing library. Post sequencing, reads from individual samples are split into individual files using their unique combination of barcode sequences. Genotyping is performed with a simple perl script which counts amplicon-specific sequences for each allele, and allele ratios are used to determine the genotypes. We demonstrate this technique by genotyping 2068 individual steelhead trout (Oncorhynchus mykiss) samples with a set of 192 SNP markers in a single library sequenced in a single Illumina HiSeq lane. Genotype data were 99.9% concordant to previously collected TaqMan TM genotypes at the same 192 loci, but call rates were slightly lower with GT-seq (96.4%) relative to Taqman (99.0%). Of the 192 SNPs, 187 were genotyped in ≥90% of the individual samples and only 3 SNPs were genotyped in <70% of samples. This study demonstrates amplicon sequencing with GTseq greatly reduces the cost of genotyping hundreds of targeted SNPs relative to existing methods by utilizing a simple library preparation method and massive efficiency of scale.

Genetic Diversity, Population Structure, and Linkage Disequilibrium of a Core Collection of Ziziphus jujuba Assessed with Genome-wide SNPs Developed by Genotyping-by-sequencing and SSR Markers

“…The cost of next-generation sequencing platforms is much lower than that of the Sanger sequencing technique (Frank et al, 2013). Additionally, although the cost per polymorphic locus is similar for GBS and genotyping-in-thousands by sequencing (i.e., another next-generation sequencing approach) (Campbell et al, 2015), GBS can detect nearly 25-fold more polymorphic loci. This indicates that GBS is an efficient and cost-effective genotyping approach (Pértille et al, 2016).…”

Use of the melting curve assay as a means for high-throughput quantification of Illumina sequencing libraries

“…Differences between sequencing libraries for these parameters may hence influence accuracy of the MC assay-based quantification, and the method may not be suitable for a comparison of DNA quantities, if the DNA sequence contents are considerably different between the libraries. In general, libraries for multiplexed sequencing are, however, prepared in parallel from the identical targeted sequence(s) (Campbell, Harmon & Narum, 2015; Hosomichi et al, 2014; Shinozuka et al, 2015), and the DNA sequence contents of libraries should not be substantially different. For the scenario of different DNA sequence contents, NanoDrop- or TapeStation-based methods would be more suitable.…”

“…Although several library normalisation methods have been established, all of them incur a relatively high cost and/or require long processing times for a large number of samples (Table 1, Table S1) (Buehler et al, 2010; Campbell, Harmon & Narum, 2015; Harris et al, 2010; Hosomichi et al, 2014; Katsuoka et al, 2014; Kong et al, 2014; Rohland & Reich, 2012). Single libraries are commonly quantified with a well-established real-time PCR-based method (Buehler et al, 2010; Rohland & Reich, 2012) which, however, requires a relatively long processing time.…”

Advances in the Application of Genetics in Marine Turtle Biology and Conservation

“…Additionally, generating microsatellite data that is comparable across laboratories is problematic, which can impede large-scale stock structure and MSA syntheses. In contrast, SNPs typically have lower power per locus relative to microsatellites, but hundreds to thousands of SNP loci can now be rapidly and reliably quantified across large numbers of individuals (Campbell et al, 2015;Ali et al, 2016;Andrews et al, 2016). Additionally, SNPs in coding regions can be used to understand genotype and phenotype linkages and identify loci under selection if adequate genomic and budget resources are available (Hoban et al, 2016;Todd et al, 2016).…”