Abstract

Molecular characterization of unsequenced plant species with complex genomes is now possible by genotyping-by-sequencing (GBS) using recent next generation sequencing technologies. This study represents the first use of GBS application to sample genome-wide variants of crested wheatgrass [Agropyron cristatum (L.) Gaertn.] and assess the genetic diversity present in 192 genotypes from 12 tetraploid lines. Bioinformatic analysis identified 45,507 single nucleotide polymorphism (SNP) markers in this outcrossing grass species. The model-based Bayesian analysis revealed four major clusters of the samples assayed. The diversity analysis revealed 15.8% of SNP variation residing among the 12 lines, and 12.1% SNP variation present among four genetic clusters identified by the Bayesian analysis. The principal coordinates analysis and dendrogram were able to distinguish four lines of Asian origin from Canadian cultivars and breeding lines. These results serve as a valuable resource for understanding genetic variability, and will aid in the genetic improvement of this outcrossing polyploid grass species for forage production. These findings illustrate the potential of GBS application in the characterization of non-model polyploid plants with complex genomes.

Highlights

  • Genotyping-by-sequencing (GBS) is a powerful genomic approach for identification of genetic variation on a genome-wide scale for genetic diversity analysis of non-model plants [1,2,3]

  • A GBS-based pipeline, called Haplotag, was developed by Tinker et al [9], which can generate tag-level haplotype and single nucleotide polymorphism (SNP) data for polyploid organisms. This approach has been successfully applied in the study of diploid and polyploid genomes in oat (Avena sativa) [10,11,12] and genetic diversity analysis of northern wheatgrass

  • Our analysis showed high within-line genetic variation (Table 2) of assayed CWG lines, which is in agreement with studies on highly outcrossing species [37]

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Summary

Introduction

Genotyping-by-sequencing (GBS) is a powerful genomic approach for identification of genetic variation on a genome-wide scale for genetic diversity analysis of non-model plants [1,2,3]. The GBS application, despite being a powerful approach, has certain limitations, including many missing data points, uneven genome coverage, complex bioinformatics, and issues related to polyploidy [5,6,7,8] To overcome these limitations, a GBS-based pipeline, called Haplotag, was developed by Tinker et al [9], which can generate tag-level haplotype and single nucleotide polymorphism (SNP) data for polyploid organisms. A GBS-based pipeline, called Haplotag, was developed by Tinker et al [9], which can generate tag-level haplotype and single nucleotide polymorphism (SNP) data for polyploid organisms This approach has been successfully applied in the study of diploid and polyploid genomes in oat (Avena sativa) [10,11,12] and genetic diversity analysis of northern wheatgrass

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