Veterinary and Agricultural Sciences Collected Works - Research Publications

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    Improved Wheat Growth and Yield by Delayed Leaf Senescence Using Developmentally Regulated Expression of a Cytokinin Biosynthesis Gene
    Joshi, S ; Choukimath, A ; Isenegger, D ; Panozzo, J ; Spangenberg, G ; Kant, S (FRONTIERS MEDIA SA, 2019-10-18)
    Delaying leaf senescence in plants, especially under water stress conditions, can help to maintain the remobilization of stored nutrients in source-sink relationships, thus leading to improved crop yields. Leaf senescence can be delayed by plant hormones such as cytokinin. Here, the Isopentenyl transferase (IPT) gene, encoding a cytokinin biosynthesis enzyme, driven by a modified AtMYB32xs promoter was transformed into wheat. Transgenic wheat plants exhibited delayed leaf senescence, retaining chlorophyll for longer under controlled environment conditions. Selected independent transgenic events and their corresponding nulls were grown under field conditions for two consecutive years under well-watered and water stress treatments using automated rainout shelters. Three independent transgenic events had improved canopy green cover, lower canopy temperatures, and higher leaf water potential than their respective non-transgenic nulls, with no abnormality in morphology and phenology. Increased grain yield was observed in transgenic events under both water treatments, with the yield increase more pronounced under water stress (26-42%). These results have shown that delayed leaf senescence using the chimeric transgene AtMYB32xs-p::IPT can be a useful strategy to achieve grain yield gains in wheat and potentially other crops for sustainable food production.
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    Genomic Prediction and Genetic Correlation of Agronomic, Blackleg Disease, and Seed Quality Traits in Canola (Brassica napus L.)
    Fikere, M ; Barbulescu, DM ; Malmberg, MM ; Maharjan, P ; Salisbury, PA ; Kant, S ; Panozzo, J ; Norton, S ; Spangenberg, GC ; Cogan, NOI ; Daetwyler, HD (MDPI, 2020-06-01)
    Genomic selection accelerates genetic progress in crop breeding through the prediction of future phenotypes of selection candidates based on only their genomic information. Here we report genetic correlations and genomic prediction accuracies in 22 agronomic, disease, and seed quality traits measured across multiple years (2015-2017) in replicated trials under rain-fed and irrigated conditions in Victoria, Australia. Two hundred and two spring canola lines were genotyped for 62,082 Single Nucleotide Polymorphisms (SNPs) using transcriptomic genotype-by-sequencing (GBSt). Traits were evaluated in single trait and bivariate genomic best linear unbiased prediction (GBLUP) models and cross-validation. GBLUP were also expanded to include genotype-by-environment G × E interactions. Genomic heritability varied from 0.31to 0.66. Genetic correlations were highly positive within traits across locations and years. Oil content was positively correlated with most agronomic traits. Strong, not previously documented, negative correlations were observed between average internal infection (a measure of blackleg disease) and arachidic and stearic acids. The genetic correlations between fatty acid traits followed the expected patterns based on oil biosynthesis pathways. Genomic prediction accuracy ranged from 0.29 for emergence count to 0.69 for seed yield. The incorporation of G × E translates into improved prediction accuracy by up to 6%. The genomic prediction accuracies achieved indicate that genomic selection is ready for application in canola breeding.