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Transcriptome alterations of an in vitro-selected, moderately-resistant, two-row malting barley in response to 3ADON, 15ADON and NIV chemotypes of Fusarium graminearium

ABSTRACT: Fusarium head blight caused by Fusarium graminearum is a devastating disease of malting barley. Mycotoxins associated with contaminated grain can be transferred from malt to beer and pose a health risk to consumers. In western Canada, F. graminearum has undergone an adaptive shift from 15ADON constituency to dominance by virulent 3ADON-producers, likewise NIV-producers have established in regions of southern United States. Lack of adapted resistance sources with adequate malting quality has promoted the use of alternative breeding methodologies such as in vitro selection. We studied the low-deoxynivalenol characteristic of in vitro selected, two-row malting barley variety ‘Norman’ by RNAseq in contrast to its parental line ‘CDC Kendall’, when infected by 15ADON-, 3ADON- and NIV-producing isolates of F. graminearum. The current study documents higher mycotoxin accumulation by 3ADON isolates, thereby representing increased threat to barley production. At 72-96 hours post infection, significant alterations in transcription patterns were observed in both varieties with pronounced upregulation of the phenylpropanoid pathway and detoxification gene categories (UGT, GST, CyP450 and ABC) particularly in 3ADON treatment. Defense response was multi-tiered, where differential expression in ‘Norman’ associated with antimicrobial peptides (thionin 2.1, defensing, non-specific lipid-transfer protein) and stress-related proteins such as late embryogenesis abundant proteins, heat-shock, desiccation-related and a peroxidase (HvPrx5). Several gene targets identified in ‘Norman’ would be useful in application of breeding varieties with reduced deoxynivalenol content.

ORGANISM(S): Hordeum vulgare

PROVIDER: GSE174081 | GEO | 2021/05/08

REPOSITORIES: GEO

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Project description:Fusarium head blight (FHB) incited by Fusarium graminearum Schwabe is a devastating disease of barley and other cereal crops worldwide. Fusarium head blight is associated with trichothecene mycotoxins such as deoxynivalenol (DON), where contaminated grains are unfit for malting or animal feed industries. While genetically resistant cultivars offer the best economic and environmentally responsible means to mitigate disease, parent lines with adequate resistance are limited in barley. Resistancebreeding based upon quantitative genetic gains has been slow to date, due to intensive labour requirements of disease nurseries. The development of high throughput genome-wide molecular markers, allow application in genomic prediction models. A diverse genomic panel consisting of 400 two-row spring barley lines was assembled to focus on Canadian barley breeding programs. The panel was evaluated for FHB and DON content in three environments and over two years. Moreover, it was genotyped using an Illumina Infinium HTS iSelect custom beadchip array of single nucleotide polymorphic molecular markers (50K SNP), where over 23K molecular markers were polymorphic. Genomic prediction has been successfully demonstrated for reducing FHB and DON content in cereals using various statistically-based models of different underlying assumptions. Herein, we have studied an alternative method basedon machine learning and compare it with a statistical approach. Two encoding techniques were utilized (categorical or Hardy-Weinberg frequencies), followed by selecting essential genomic markers for phenotype prediction. Subsequently, we applied a transformer-based deep learning algorithm to predict FHB and DON. Apart from the transformer method, we also implemented a Residual Fully Connected Neural Network (RFCNN). Pearson correlation coefficients were calculated to compare true vs. predicted outputs. Under most model scenarios, the use of all markers vs. selected markers marginally improved prediction performance except for RFCNN method for FHB (27.6%). Hardy-Weinberg encoding generally improved correlation for FHB (6.9%) and DON (9.6%) for transformer. This study suggests the potential of the transformer based method for genomic prediction of complex traits such as FHB or DON, having performed better or equally compared with existing machine learning and statistical method. To genomic prediction in barley for Fusarium head blight and deoxynivalenol content using a custom Illumina Infinium array (BarleySNP50-JHI) (www.illumina.com). Sample types included leaves from 400 barley genotypes mostly of Canadian origin. This series includes 400 genotypes assayed on an Illumina infinium HTS platform 50K BeadChip.

Dataset Information

Transcriptome alterations of an in vitro-selected, moderately-resistant, two-row malting barley in response to 3ADON, 15ADON and NIV chemotypes of Fusarium graminearium

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