Genotyping-by-Sequencing and Its Exploitation for Forage and Cool-Season Grain Legume Breeding.

Paolo Annicchiarico,Yanling Wei,Luciano Pecetti,Nelson Nazzicari,Edward C Brummer

doi:10.3389/fpls.2017.00679

Abstract

Genotyping-by-Sequencing (GBS) may drastically reduce genotyping costs compared with single nucleotide polymorphism (SNP) array platforms. However, it may require optimization for specific crops to maximize the number of available markers. Exploiting GBS-generated markers may require optimization, too (e.g., to cope with missing data). This study aimed (i) to compare elements of GBS protocols on legume species that differ for genome size, ploidy, and breeding system, and (ii) to show successful applications and challenges of GBS data on legume species. Preliminary work on alfalfa and Medicago truncatula suggested the greater interest of ApeKI over PstI:MspI DNA digestion. We compared KAPA and NEB Taq polymerases in combination with primer extensions that were progressively more selective on restriction sites, and found greater number of polymorphic SNP loci in pea, white lupin and diploid alfalfa when adopting KAPA with a non-selective primer. This protocol displayed a slight advantage also for tetraploid alfalfa (where SNP calling requires higher read depth). KAPA offered the further advantage of more uniform amplification than NEB over fragment sizes and GC contents. The number of GBS-generated polymorphic markers exceeded 6,500 in two tetraploid alfalfa reference populations and a world collection of lupin genotypes, and 2,000 in different sets of pea or lupin recombinant inbred lines. The predictive ability of GBS-based genomic selection was influenced by the genotype missing data threshold and imputation, as well as by the genomic selection model, with the best model depending on traits and data sets. We devised a simple method for comparing phenotypic vs. genomic selection in terms of predicted yield gain per year for same evaluation costs, whose application to preliminary data for alfalfa and pea in a hypothetical selection scenario for each crop indicated a distinct advantage of genomic selection.

Highlights

Generation sequencing techniques provide many molecular markers at low cost by sequencing single nucleotide polymorphism (SNP) sites in a fraction of the genome
For the scenario of 1.25 M total reads per genotype, the combination of ApeKI and Kapa Biosystems (KAPA) provided a higher number of tags than the other GBS protocols in all sets of genotypes, for minimum read depths of 2 reads per tag or 6 (Figure 1A)
Results of diploid alfalfa for this read depth are likely to apply to tetraploid alfalfa under 2.5 M total reads per genotype, when considering the high consistency of results between diploid and tetraploid alfalfa verified under the 1.25 M total read scenario

Summary

Introduction

Generation sequencing techniques provide many molecular markers at low cost by sequencing single nucleotide polymorphism (SNP) sites in a fraction of the genome. GBS skips the shearing and size selection stage, combining the ligation of both adapters into one step. Another improvement of GBS is the modulation of length and nucleotide composition of barcode sequences. The current GBS cost per DNA sample (inclusive of sample preparation) is on the order of 25–30 € This represents a possible cost reduction of about 40–60% relative to SNP array-based genotyping, with greater reduction for relatively small experiments. At these costs, genomic selection (Heffner et al, 2009) can be applied even to crops of moderate or modest economic importance and/or with no sequenced genome. Relative to array-based genotyping, GBS presents challenges in coping with missing data and their imputation, and it may require optimization for different species

Objectives

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Results

Conclusion