A comparison of mainstream genotyping platforms for the evaluation and use of barley genetic resources

Benoit Darrier, Joanne Russell, Sara G. Milner, Pete E. Hedley, Paul D. Shaw, Malcolm Macaulay, Luke Ramsay, Claire Halpin, Martin Mascher, Delphine L. Fleury, Peter Langridge, Nils Stein, Robbie Waugh (Lead / Corresponding author)

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Abstract

We compared the performance of two commonly used genotyping platforms, genotyping-by-sequencing (GBS) and single nucleotide polymorphism-arrays (SNP), to investigate the extent and pattern of genetic variation within a collection of 1,000 diverse barley genotypes selected from the German Federal ex situ GenBank hosted at IPK Gatersleben. Each platform revealed equivalent numbers of robust bi-allelic SNPs (39,733 and 37,930 SNPs for the 50K SNP-array and GBS datasets respectively). A small overlap of 464 SNPs was common to both platforms, indicating that the methodologies we used selectively access informative polymorphism in different portions of the barley genome. Approximately half of the GBS dataset was comprised of SNPs with minor allele frequencies (MAFs) below 1%, illustrating the power of GBS to detect rare alleles in diverse germplasm collections. While desired for certain applications, the highly robust calling of alleles at the same SNPs across multiple populations is an advantage of the SNP-array, allowing direct comparisons of data from related or unrelated studies. Overall MAFs and diversity statistics (π) were higher for the SNP-array data, potentially reflecting the conscious removal of markers with a low MAF in the ascertainment population. A comparison of similarity matrices revealed a positive correlation between both approaches, supporting the validity of using either for entire GenBank characterization. To explore the potential of each dataset for focused genetic analyses we explored the outcomes of their use in genome-wide association scans for row type, growth habit and non-adhering hull, and discriminant analysis of principal components for the drivers of sub-population differentiation. Interpretation of the results from both types of analysis yielded broadly similar conclusions indicating that choice of platform used for such analyses should be determined by the research question being asked, group preferences and their capabilities to extract and interpret the different types of output data easily and quickly. Access to the requisite infrastructure for running, processing, analyzing, querying, storing, and displaying either datatype is an additional consideration. Our investigations reveal that for barley the cost per genotyping assay is less for SNP-arrays than GBS, which translates to a cost per informative datapoint being significantly lower for the SNP-array.

Original languageEnglish
Article number544
Pages (from-to)1-14
Number of pages14
JournalFrontiers in Plant Science
Volume10
DOIs
Publication statusPublished - 26 Apr 2019

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genetic resources
genotyping
single nucleotide polymorphism
barley
gene frequency
alleles
growth habit
germplasm conservation
infrastructure
hulls
discriminant analysis
statistics
genetic polymorphism
genetic variation
genome
genotype
extracts
assays

Keywords

  • Diversity
  • GBS
  • GWAS
  • Germplasm evaluation
  • SNP-array

Cite this

Darrier, Benoit ; Russell, Joanne ; Milner, Sara G. ; Hedley, Pete E. ; Shaw, Paul D. ; Macaulay, Malcolm ; Ramsay, Luke ; Halpin, Claire ; Mascher, Martin ; Fleury, Delphine L. ; Langridge, Peter ; Stein, Nils ; Waugh, Robbie. / A comparison of mainstream genotyping platforms for the evaluation and use of barley genetic resources. In: Frontiers in Plant Science. 2019 ; Vol. 10. pp. 1-14.
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note = "This research was supported by the UK BEIS (Department for Business, Energy & Industrial Strategy) via a Universities UK International Rutherford Fund Strategic Partner Grant No. RF2018-30 to CH and RW and the ERC project 669182 ‘SHUFFLE’ to RW. We acknowledge funding from ARC project No: DP170103975 to PL, RW, and BD, and the Leibniz Association to NS and MMas (Pakt f{\"u}r Forschung und Innovation: SAW2015-IPK-1 ‘BRIDGE’). SM was supported by a LeibnizDAAD fellowship from the German Academic Exchange service (DAAD). RW, JR, PH, PS, LR, and MMac were supported by the Scottish Government Rural and Environment Science and Analytical Services WP2 (RESAS).",
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Darrier, B, Russell, J, Milner, SG, Hedley, PE, Shaw, PD, Macaulay, M, Ramsay, L, Halpin, C, Mascher, M, Fleury, DL, Langridge, P, Stein, N & Waugh, R 2019, 'A comparison of mainstream genotyping platforms for the evaluation and use of barley genetic resources', Frontiers in Plant Science, vol. 10, 544, pp. 1-14. https://doi.org/10.3389/fpls.2019.00544

A comparison of mainstream genotyping platforms for the evaluation and use of barley genetic resources. / Darrier, Benoit; Russell, Joanne; Milner, Sara G.; Hedley, Pete E.; Shaw, Paul D.; Macaulay, Malcolm; Ramsay, Luke; Halpin, Claire; Mascher, Martin; Fleury, Delphine L.; Langridge, Peter; Stein, Nils; Waugh, Robbie (Lead / Corresponding author).

In: Frontiers in Plant Science, Vol. 10, 544, 26.04.2019, p. 1-14.

Research output: Contribution to journalArticle

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AU - Darrier, Benoit

AU - Russell, Joanne

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AU - Hedley, Pete E.

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AU - Macaulay, Malcolm

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AU - Mascher, Martin

AU - Fleury, Delphine L.

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AU - Stein, Nils

AU - Waugh, Robbie

N1 - This research was supported by the UK BEIS (Department for Business, Energy & Industrial Strategy) via a Universities UK International Rutherford Fund Strategic Partner Grant No. RF2018-30 to CH and RW and the ERC project 669182 ‘SHUFFLE’ to RW. We acknowledge funding from ARC project No: DP170103975 to PL, RW, and BD, and the Leibniz Association to NS and MMas (Pakt für Forschung und Innovation: SAW2015-IPK-1 ‘BRIDGE’). SM was supported by a LeibnizDAAD fellowship from the German Academic Exchange service (DAAD). RW, JR, PH, PS, LR, and MMac were supported by the Scottish Government Rural and Environment Science and Analytical Services WP2 (RESAS).

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N2 - We compared the performance of two commonly used genotyping platforms, genotyping-by-sequencing (GBS) and single nucleotide polymorphism-arrays (SNP), to investigate the extent and pattern of genetic variation within a collection of 1,000 diverse barley genotypes selected from the German Federal ex situ GenBank hosted at IPK Gatersleben. Each platform revealed equivalent numbers of robust bi-allelic SNPs (39,733 and 37,930 SNPs for the 50K SNP-array and GBS datasets respectively). A small overlap of 464 SNPs was common to both platforms, indicating that the methodologies we used selectively access informative polymorphism in different portions of the barley genome. Approximately half of the GBS dataset was comprised of SNPs with minor allele frequencies (MAFs) below 1%, illustrating the power of GBS to detect rare alleles in diverse germplasm collections. While desired for certain applications, the highly robust calling of alleles at the same SNPs across multiple populations is an advantage of the SNP-array, allowing direct comparisons of data from related or unrelated studies. Overall MAFs and diversity statistics (π) were higher for the SNP-array data, potentially reflecting the conscious removal of markers with a low MAF in the ascertainment population. A comparison of similarity matrices revealed a positive correlation between both approaches, supporting the validity of using either for entire GenBank characterization. To explore the potential of each dataset for focused genetic analyses we explored the outcomes of their use in genome-wide association scans for row type, growth habit and non-adhering hull, and discriminant analysis of principal components for the drivers of sub-population differentiation. Interpretation of the results from both types of analysis yielded broadly similar conclusions indicating that choice of platform used for such analyses should be determined by the research question being asked, group preferences and their capabilities to extract and interpret the different types of output data easily and quickly. Access to the requisite infrastructure for running, processing, analyzing, querying, storing, and displaying either datatype is an additional consideration. Our investigations reveal that for barley the cost per genotyping assay is less for SNP-arrays than GBS, which translates to a cost per informative datapoint being significantly lower for the SNP-array.

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