Evaluation of Genomic Prediction for Pasmo Resistance in Flax.

Liqiang He,Gaofeng Jia,Sylvie Cloutier,Pingchuan Li,Khalid Rashid,Zhen Yao,Jin Xiao,Frank You,Xiue Wang

doi:10.3390/ijms20020359

Abstract

Pasmo (Septoria linicola) is a fungal disease causing major losses in seed yield and quality and stem fibre quality in flax. Pasmo resistance (PR) is quantitative and has low heritability. To improve PR breeding efficiency, the accuracy of genomic prediction (GP) was evaluated using a diverse worldwide core collection of 370 accessions. Four marker sets, including three defined by 500, 134 and 67 previously identified quantitative trait loci (QTL) and one of 52,347 PR-correlated genome-wide single nucleotide polymorphisms, were used to build ridge regression best linear unbiased prediction (RR-BLUP) models using pasmo severity (PS) data collected from field experiments performed during five consecutive years. With five-fold random cross-validation, GP accuracy as high as 0.92 was obtained from the models using the 500 QTL when the average PS was used as the training dataset. GP accuracy increased with training population size, reaching values >0.9 with training population size greater than 185. Linear regression of the observed PS with the number of positive-effect QTL in accessions provided an alternative GP approach with an accuracy of 0.86. The results demonstrate the GP models based on marker information from all identified QTL and the 5-year PS average is highly effective for PR prediction.

Highlights

Flax (Linum usitatissimum L.) is an important food and fibre crop cultivated and grown in cooler regions of the world, such as Canada [1]
The objective of this study was to evaluate the potential of quantitative trait loci (QTL) markers in genomic prediction (GP) and compare the GP efficiency affected by different markers, including genome-wide single nucleotide polymorphisms (SNPs) and QTL markers, to provide a realistic and highly accurate model for germplasm evaluation and parent selection in pasmo resistance breeding
Prediction accuracies of models obtained with SNP-134QTL and SNP-67QTL data sets were comparable (Table 3, Figure S1) and they explained a similar proportion of the phenotypic variation for pasmo severity (PS) (Table 2), confirming the redundancy or overlap between the two datasets

Summary

Introduction

Flax (Linum usitatissimum L.) is an important food and fibre crop cultivated and grown in cooler regions of the world, such as Canada [1]. Pasmo, elicited by the fungus Septoria linicola, is one of the most widespread diseases of flax, causing reductions in seed and oil yield, as well as fibre quality and durability [2]. Developing resistant cultivars is the most viable and effective option to control this disease that has become widespread in all flax production areas of North America and other parts of the world. Large variations in pasmo disease severity were observed in the flax core collection, which can be capitalized upon to develop resistant cultivars [3]. Field assessment of pasmo severity (PS) in germplasm and breeding lines is costly and, is heavily influenced by the environments due to strong genotype × environment (G × E) interactions [3,4]

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Discussion

Conclusion