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Biology subjects

Dhariwal, R.

Publications and source records attributed to Dhariwal, R..

2 recordsLinked to original sources

Development and validation of KASP markers for a novel powdery mildew resistance gene in wheat using BSR-Seq analysis

Wheat powdery mildew occurs as a devastating infection caused by the pathogenic fungi Blumeeria graminis f. sp. tritici (Bgt). The management of disease becomes much more effective when host resistance methods are employed. The WL711-2U/2B line served as the introgressed line to identify genes linked with powdery mildew resistance. This allowed us to look into the potential resistance components in response to powdery mildew infection. The resistance status of the line towards powdery mildew developed from a single dominant gene named PmAT. Bulked segregant RNA-Seq (BSR-Seq) together with previous QTL-Seq SNP markers helped identify strong candidate regions in chromosome arm 2B extending from 531114848 bp to 530235618 bp. The LOD score from this region reached 72.4 with a PVE% of 64.7, thus proving its main role in resistance. The physical position was subsequently locked up, which was different from the previously identified genes on the same chromosome arm in its position, suggesting that it is most likely a new Pm gene. The QTL interval contained five potential genes that we identified during this research. The five candidate genes directs the protein production, which performs functions linked to the pentatricopeptide repeat family as well as B-box-type zinc finger domain, P-loop-containing nucleoside triphosphate hydrolase, and plant peroxidase. HighlightThe identification of a new wheat powdery mildew resistance gene (PmAT) using a combination of BSR-Seq and QTL-Seq analysis, which located five candidate genes specifically on chromosome 2B.

genetics↗

Deep Learning Genome-wide Linkage Association Study for Wheat Fusarium Head Blight Resistance Genes Discovery

BackgroundFusarium head blight (FHB) is one of the most devastating diseases of wheat worldwide and artificial intelligence can assist with understanding resistance to the disease. Considering different sample populations, marker types, reference maps, and statistical methods, we developed a Deep Learning Genome-wide Linkage Association Study (dpGLAS) of FHB resistance in wheat. ResultsThe dpGLAS was first applied to two bi-parental population datasets in which the cultivar AC Barrie was a common parent for FHB resistance. Eight candidate gene markers were discovered in the one AC Barrie population and 10 in the other associated with FHB resistance. Eight of these markers were also supported by the conventional QTL mapping. Most of these candidate marker genes were found associated with the Reactive Oxygen Species (ROS) and Abscisic acid (ABA) axes. These ROS and ABA pathways were further supported by RNA-seq transcriptome data of FHB resistant cv. AAC Tenacious, a parent of the third bi-parental population. In this dataset, the ROS-centered Panther protein families were significantly enriched in those genes that had most different response to FHB when compared the resistance Tenacious and the susceptible Roblin. ConclusionsThis study developed the framework of dpGLAS and identified candidate genes for FHB resistance in the Canadian spring wheat cultivars AC Barrie and AAC Tenacious.

bioinformatics↗