TASSEL-GBS: A High Capacity Genotyping by Sequencing Analysis Pipeline
By Jeff Glaubitz, T. Casstevens, Fei Lu, J. Harriman, Robert Elshire, Qi Sun, Edward Buckler. PLoS ONE, 2014
1,494 citations recorded by the source corpus.
Genotyping by sequencing (GBS) is a next generation sequencing based method that takes advantage of reduced representation to enable high throughput genotyping of large numbers of individuals at a large number of SNP markers. The relatively straightforward, robust, and cost-effective GBS protocol is currently being applied in numerous species by a large number of researchers. Herein we describe a bioinformatics pipeline, tassel-gbs, designed for the efficient processing of raw GBS sequence data into SNP genotypes. The tassel-gbs pipeline successfully fulfills the following key design criteria: (1) Ability to run on the modest computing resources that are typically available to small breeding or ecological research programs, including desktop or laptop machines with only 8–16 GB of RAM, (2) Scalability from small to extremely large studies, where hundreds of thousands or even millions of SNPs can be scored in up to 100,000 individuals (e.g., for large breeding programs or genetic surveys), and (3) Applicability in an accelerated breeding context, requiring rapid turnover from tissue collection to genotypes. Although a reference genome is required, the pipeline can also be run with an unfinished “pseudo-reference” consisting of numerous contigs. We describe the tassel-gbs pipeline in detail and benchmark it based upon a large scale, species wide analysis in maize (Zea mays), where the average error rate was reduced to 0.0042 through application of population genetic-based SNP filters. Overall, the GBS assay and the tassel-gbs pipeline provide robust tools for studying genomic diversity.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/af744d09fdf2f09158db755bdb39473a216e76a5
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Citations in the corpus
- Genetic mapping of quantitative trait loci in crops (2017, neutral): “To analyze GBS data, the TASSEL GBS pipeline is available for large quantities of data from a large number of samples with a reference genome [80], while the UNEAK pipeline is designed for specieswithout a reference genome [81].”
- High-Throughput SNP Genotyping to Accelerate Crop Improvement (2014, positive): “Likewise, the TASSEL-GBS pipeline was developed primarily for species with a reference genome available, and has been optimized for dealing with large data sets (Glaubitz et al. 2014).”
- Genomics to systems biology in animal and veterinary sciences: Progress, lessons and opportunities☆ (2014, neutral): “sequencing”; (Glaubitz et al., 2014)).”
- LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms (2015, neutral): “We then used the 12X grape reference genome (Jaillon et al. 2007; Adam-Blondon et al. 2011) and the Tassel / BWA version 4 pipeline to generate a genotype matrix (Li and Durbin 2009; Glaubitz et al. 2014).”
- Novel Methods to Optimize Genotypic Imputation for Low‐Coverage, Next‐Generation Sequence Data in Crop Plants (2014, neutral): “We compare results from three distinct maize datasets genotyped using maize GBS build v. 2.7 (Glaubitz et al., 2014): (i) 429 replicate samples representing 287 related temperate inbred Ex-PVP and Iowa breeding lines (temperate inbreds; Romay et al., 2013), (ii) 467 replicate samples from a panel…”
- Genome‐wide Association for Plant Height and Flowering Time across 15 Tropical Maize Populations under Managed Drought Stress and Well‐Watered Conditions in Sub‐Saharan Africa (2016, neutral): “Nitrogen crop science, vol. 56, september–october 2016 www.crops.org 2367 pipeline (Glaubitz et al. 2014).”