Veterinary Science Collected Works - Research Publications
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ItemCombining NDVI and Bacterial Blight Score to Predict Grain Yield in Field Pea.(Frontiers Media SA, 2022)Field pea is the most commonly grown temperate pulse crop, with close to 15 million tons produced globally in 2020. Varieties improved through breeding are important to ensure ongoing improvements in yield and disease resistance. Genomic selection (GS) is a modern breeding approach that could substantially improve the rate of genetic gain for grain yield, and its deployment depends on the prediction accuracy (PA) that can be achieved. In our study, four yield trials representing breeding lines' advancement stages of the breeding program (S0, S1, S2, and S3) were assessed with grain yield, aerial high-throughput phenotyping (normalized difference vegetation index, NDVI), and bacterial blight disease scores (BBSC). Low-to-moderate broad-sense heritability (0.31-0.71) and narrow-sense heritability (0.13-0.71) were observed, as the estimated additive and non-additive genetic components for the three traits varied with the different models fitted. The genetic correlations among the three traits were high, particularly in the S0-S2 stages. NDVI and BBSC were combined to investigate the PA for grain yield by univariate and multivariate GS models, and multivariate models showed higher PA than univariate models in both cross-validation and forward prediction methods. A 6-50% improvement in PA was achieved when multivariate models were deployed. The highest PA was indicated in the forward prediction scenario when the training population consisted of early generation breeding stages with the multivariate models. Both NDVI and BBSC are commonly used traits that could be measured in the early growth stage; however, our study suggested that NDVI is a more useful trait to predict grain yield with high accuracy in the field pea breeding program, especially in diseased trials, through its incorporation into multivariate models.
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ItemStrategies of preserving genetic diversity while maximizing genetic response from implementing genomic selection in pulse breeding programs.(Springer Science and Business Media LLC, 2022-06)Genomic selection maximizes genetic gain by recycling parents to germplasm pool earlier and preserves genetic diversity by restricting the number of fixed alleles and the relationship in pulse breeding programs. Using a stochastic computer simulation, we investigated the benefit of optimization strategies in the context of genomic selection (GS) for pulse breeding programs. We simulated GS for moderately complex to highly complex traits such as disease resistance, grain weight and grain yield in multiple environments with a high level of genotype-by-environment interaction for grain yield. GS led to higher genetic gain per unit of time and higher genetic diversity loss than phenotypic selection by shortening the breeding cycle time. The genetic gain obtained from selecting the segregating parents early in the breeding cycle (at F1 or F2 stages) was substantially higher than selecting at later stages even though prediction accuracy was moderate. Increasing the number of F1 intercross (F1i) families and keeping the total number of progeny of F1i families constant, we observed a decrease in genetic gain and increase in genetic diversity, whereas increasing the number of progeny per F1i family while keeping a constant number of F1i families increased the rate of genetic gain and had higher genetic diversity loss per unit of time. Adding 50 F2 family phenotypes to the training population increased the accuracy of genomic breeding values (GEBVs) and genetic gain per year and decreased the rate of genetic diversity loss. Genetic diversity could be preserved by applying a strategy that restricted both the percentage of alleles fixed and the average relationship of the group of selected parents to preserve long-term genetic improvement in the pulse breeding program.
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ItemPulse Root Ideotype for Water Stress in Temperate Cropping System(MDPI, 2021-04)Pulses are a key component of crop production systems in Southern Australia due to their rotational benefits and potential profit margins. However, cultivation in temperate cropping systems such as that of Southern Australia is limited by low soil water availability and subsoil constraints. This limitation of soil water is compounded by the irregular rainfall, resulting in the absence of plant available water at depth. An increase in the productivity of key pulses and expansion into environments and soil types traditionally considered marginal for their growth will require improved use of the limited soil water and adaptation to sub soil constrains. Roots serve as the interface between soil constraints and the whole plant. Changes in root system architecture (RSA) can be utilised as an adaptive strategy in achieving yield potential under limited rainfall, heterogenous distribution of resources and other soil-based constraints. The existing literature has identified a "'Steep, Deep and Cheap" root ideotype as a preferred RSA. However, this idiotype is not efficient in a temperate system where plant available water is limited at depth. In addition, this root ideotype and other root architectural studies have focused on cereal crops, which have different structures and growth patterns to pulses due to their monocotyledonous nature and determinant growth habit. The paucity of pulse-specific root architectural studies warrants further investigations into pulse RSA, which should be combined with an examination of the existing variability of known genetic traits so as to develop strategies to alleviate production constraints through either tolerance or avoidance mechanisms. This review proposes a new model of root system architecture of "Wide, Shallow and Fine" roots based on pulse roots in temperate cropping systems. The proposed ideotype has, in addition to other root traits, a root density concentrated in the upper soil layers to capture in-season rainfall before it is lost due to evaporation. The review highlights the potential to achieve this in key pulse crops including chickpea, lentil, faba bean, field pea and lupin. Where possible, comparisons to determinate crops such as cereals have also been made. The review identifies the key root traits that have shown a degree of adaptation via tolerance or avoidance to water stress and documents the current known variability that exists in and amongst pulse crops setting priorities for future research.
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ItemTranscriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL(BMC, 2015-05-12)BACKGROUND: Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL. RESULTS: We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy. CONCLUSIONS: The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat.
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ItemGenome-wide association analysis of stripe rust resistance in modern Chinese wheat(BMC, 2020-10-27)BACKGROUND: Stripe rust (yellow rust) is a significant disease for bread wheat (Triticum aestivum L.) worldwide. A genome-wide association study was conducted on 240 Chinese wheat cultivars and elite lines genotyped with the wheat 90 K single nucleotide polymorphism (SNP) arrays to decipher the genetic architecture of stripe rust resistance in Chinese germplasm. RESULTS: Stripe rust resistance was evaluated at the adult plant stage in Pixian and Xindu in Sichuan province in the 2015-2016 cropping season, and in Wuhan in Hubei province in the 2013-2014, 2016-2017 and 2018-2019 cropping seasons. Twelve stable loci for stripe rust resistance were identified by GWAS using TASSEL and GAPIT software. These loci were distributed on chromosomes 1B, 1D, 2A, 2B, 3A, 3B, 4B (3), 4D, 6D, and 7B and explained 3.6 to 10.3% of the phenotypic variation. Six of the loci corresponded with previously reported genes/QTLs, including Sr2/Yr30/Lr27, while the other six (QYr.hbaas-1BS, QYr.hbaas-2BL, QYr.hbaas-3AL, QYr.hbaas-4BL.3, QYr.hbaas-4DL, and QYr.hbaas-6DS) are probably novel. The results suggest high genetic diversity for stripe rust resistance in this population. The resistance alleles of QYr.hbaas-2AS, QYr.hbaas-3BS, QYr.hbaas-4DL, and QYr.hbaas-7BL were rare in the present panel, indicating their potential use in breeding for stripe rust resistance in China. Eleven penta-primer amplification refractory mutation system (PARMS) markers were developed from SNPs significantly associated with seven mapped QTLs. Twenty-seven genes were predicted for mapped QTLs. Six of them were considered as candidates for their high relative expression levels post-inoculation. CONCLUSION: The resistant germplasm, mapped QTLs, and PARMS markers developed in this study are resources for enhancing stripe rust resistance in wheat breeding.