Genomic Selection in Preliminary Yield Trials in a Winter Wheat Breeding Program

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved phenotypes. The use of predicted phenotypes to make selections is an active area of research. Here, we evaluate GP for predicting grain yield and compare genomic and phenotypic selection by tracking lines advanced. We examined four independent nurseries of F3:6 and F3:7 lines trialed at 6 to 10 locations each year. Yield was analyzed using mixed models that accounted for experimental design and spatial variations. Genotype-by-sequencing provided nearly 27,000 high-quality SNPs. Average genomic predictive ability, estimated for each year by randomly masking lines as missing in steps of 10% from 10 to 90%, and using the remaining lines from the same year as well as lines from other years in a training set, ranged from 0.23 to 0.55. The predictive ability estimated for a new year using the other years ranged from 0.17 to 0.28. Further, we tracked lines advanced based on phenotype from each of the four F3:6 nurseries. Lines with both above average genomic estimated breeding value (GEBV) and phenotypic value (BLUP) were retained for more years compared to lines with either above average GEBV or BLUP alone. The number of lines selected for advancement was substantially greater when predictions were made with 50% of the lines from the testing year added to the training set. Hence, evaluation of only 50% of the lines yearly seems possible. This study provides insights to assess and integrate genomic selection in breeding programs of autogamous crops

Evaluation and Association Mapping of Resistance to Tan Spot and Stagonospora Nodorum Blotch in Adapted Winter Wheat Germplasm

Tan spot and Stagonospora nodorum blotch (SNB), often occurring together, are two economically significant diseases of wheat in the Northern Great Plains of the United States. They are caused by the fungi Pyrenophora tritici-repentis and Parastagonospora nodorum, respectively, both of which produce multiple necrotrophic effectors (NE) to cause disease. In this work, 120 hard red winter wheat (HRWW) cultivars or elite lines, mostly from the United States, were evaluated in the greenhouse for their reactions to the two diseases as well as NE produced by the two pathogens. One P. nodorum isolate (Sn4) and four Pyrenophora tritici-repentis isolates (Pti2, 331-9, DW5, and AR CrossB10) were used separately in the disease evaluations. NE sensitivity evaluation included ToxA, Ptr ToxB, SnTox1, and SnTox3. The numbers of lines that were rated highly resistant to individual isolates ranged from 11 (9%) to 30 (25%) but only six lines (5%) were highly resistant to all isolates, indicating limited sources of resistance to both diseases in the U.S. adapted HRWW germplasm. Sensitivity to ToxA was identified in 83 (69%) of the lines and significantly correlated with disease caused by Sn4 and Pti2, whereas sensitivity to other NE was present at much lower frequency and had no significant association with disease. As expected, association mapping located ToxA and SnTox3 sensitivity to chromosome arm 5BL and 5BS, respectively. A total of 24 potential quantitative trait loci was identified with −log (P value) \u3e 3.0 on 12 chromosomes, some of which are novel. This work provides valuable information and tools for HRWW production and breeding in the Northern Great Plains

Association mapping for important biotic & abiotic related traits in structured wheat population

This study was carried out in two successive seasons; 2009/2010 and 2010/2011 using two F3:6 nurseries. The first nursery contained 276 lines and two local checks genotyped using 1925 polymorphic DArT markers, while the second nursery consisted of 278 lines plus the same local checks and genotyped using 2236 polymorphic DArT markers. The nurseries were phenotyped in six to nine environments in Nebraska. The purpose of the study was to i) determine the breadth of the genetic base of the F3:6 nurseries that we currently use in our selection process ii) apply association-mapping approaches to identify DArT markers associated with important traits in F3:6 wheat populations iii) applying genomic selection methods in our breeding program. The results showed that the F3:6 populations had sufficient genetic diversity that would make the selection effective in improving the population productivity and adaptability to Nebraska environmental condition. As for the second objective we applied different statistical methods to identify markers that have significant correlation with the yield, grain volume weight, disease resistance, plant height and maturity. We have been successful in identifying potential QTL s for these traits. Some of the QTLs have been published, others are novel QTLs. The comparison of the prediction accuracy for phenotypic selection with that from genomic selection indicated that GS were 94, 64, 84, 85 and 79% as accurate as Ps for grain yield, grain volume weight, plant height, anthesis date and leaf rust, respectively. We concluded that, when factors such as heritability, relative costs of genotyping versus field evaluation, and the number of cycles of selection per year are taken into account, the efficiency of GS becomes favorable in comparison with phenotypic selection

Data from: Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations

Though epistasis has long been postulated to play a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed LASSO. The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than one fold in some cases as measured by cross validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices

Genomic Selection in Preliminary Yield Trials in a Winter Wheat Breeding Program

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved phenotypes. The use of predicted phenotypes to make selections is an active area of research. Here, we evaluate GP for predicting grain yield and compare genomic and phenotypic selection by tracking lines advanced. We examined four independent nurseries of F3:6 and F3:7 lines trialed at 6 to 10 locations each year. Yield was analyzed using mixed models that accounted for experimental design and spatial variations. Genotype-by-sequencing provided nearly 27,000 high-quality SNPs. Average genomic predictive ability, estimated for each year by randomly masking lines as missing in steps of 10% from 10 to 90%, and using the remaining lines from the same year as well as lines from other years in a training set, ranged from 0.23 to 0.55. The predictive ability estimated for a new year using the other years ranged from 0.17 to 0.28. Further, we tracked lines advanced based on phenotype from each of the four F3:6 nurseries. Lines with both above average genomic estimated breeding value (GEBV) and phenotypic value (BLUP) were retained for more years compared to lines with either above average GEBV or BLUP alone. The number of lines selected for advancement was substantially greater when predictions were made with 50% of the lines from the testing year added to the training set. Hence, evaluation of only 50% of the lines yearly seems possible. This study provides insights to assess and integrate genomic selection in breeding programs of autogamous crops

Multi-detector CT assessment of traumatic renal lesions

Background: Urinary tract injuries occur in 3–10% of abdominal trauma, kidneys being the most commonly injured. Contrast-enhanced CT is the imaging technique of choice for renal trauma, since it can quickly and accurately demonstrate not only renal injuries, and also associated damage to other organs. CT can help detect active hemorrhage and urine leakage and is the most accurate screening test for high-grade injuries and is of great help in guiding transcatheter embolization and delineating preexisting disease entities. Aim of the work: To demonstrate different traumatic lesions of the kidneys using multi-detector CT, and its use in staging and management of lesions. Methods: Study was carried out on 41 patients with abdominal trauma and suspected renal injury. All patients were subjected to contrast-enhanced multiphasic renal CT study in correlation with surgical and conventional angiography data when available. Results: All patients were classified after the American Association for the Surgery of Trauma grading system. Grade I injury was diagnosed in 2.4% of patients, grade II in 7.3%, grade III in 29.3%, grade IV in 53.7% and grade V in 7.3%. 80.5% of patients were managed conservatively, 12.2% of patients underwent total nephrectomy and 7.3% of patients died before management. Conclusion: Multiphasic CT well demonstrated various traumatic renal lesions with proper diagnosis and staging of renal trauma and guiding management

phenotype

Phenotype data for 280 lines in the Nebraska Wheat Breeding Program measured in 2010 at nine testing sites

DartGenot

Genotype data for DArT markers regarding 280 lines in the Nebraska Wheat Breeding Program