Notes

Look at Prognostic Factors, such as Duodenal P-Glycoprotein Expression, within Doggy Long-term Enteropathy.
BZR transcription factors play essential roles in plant growth and environmental stimuli, and they are also the positive regulators of Brassinosteroid (BR) signal transduction in diverse plants. In addition, BZR TFs, as crucial regulators of BR synthesis, may have multiple stress-resistance functions and their related regulatory mechanisms have been well illustrated in model plants. Here, we carried out a genome-wide identification of BZR members in Chinese pear (Pyrus bretschneideri) and identified 13 members. By comparative analysis in five Rosaceae genomes, BZR members in the pear genome may have undergone large-scale duplication events during evolution. Purifying selection played an important role in almost all of the orthologous and paralogous gene pairs. According to the expression analysis of the PbBZRs during fruit development, three PbBZRs were selected for detailed analysis. Transcriptional activation assays presented that PbBZR1 repressed the promoters of P. bretschneideri lignin biosynthetic genes, such as PbCES9, PbCOMT3, and PbHCT6. Our study traces the evolution of BZR gene family members in Rosaceae genomes and illustrates that the rates of gene loss and gain are far from equilibrium in different species. At the same time, our results suggest that PbBZR1 may be involved in the negative regulation of lignin biosynthesis.Farmers require accurate yield estimates, since they are key to predicting the volume of stock needed at supermarkets and to organizing harvesting operations. In many cases, the yield is visually estimated by the crop producer, but this approach is not accurate or time efficient. This study presents a rapid sensing and yield estimation scheme using off-the-shelf aerial imagery and deep learning. A Region-Convolutional Neural Network was trained to detect and count the number of apple fruit on individual trees located on the orthomosaic built from images taken by the unmanned aerial vehicle (UAV). The results obtained with the proposed approach were compared with apple counts made in situ by an agrotechnician, and an R2 value of 0.86 was acquired (MAE 10.35 and RMSE 13.56). As only parts of the tree fruits were visible in the top-view images, linear regression was used to estimate the number of total apples on each tree. An R2 value of 0.80 (MAE 128.56 and RMSE 130.56) was obtained. With the number of fruits detected and tree coordinates two shapefile using Python script in Google Colab were generated. With the previous information two yield maps were displayed one with information per tree and another with information per tree row. We are confident that these results will help to maximize the crop producers' outputs via optimized orchard management.Most plants are exquisitely sensitive to their environment and adapt by reprogramming post-embryonic development. The systematic understanding of molecular mechanisms regulating developmental reprogramming has been underexplored because abiotic and biotic stimuli that lead to reprogramming of post-embryonic development vary and the outcomes are highly species-specific. In this review, we discuss the diversity and similarities of developmental reprogramming processes by summarizing recent key findings in reprogrammed development plant regeneration, nodule organogenesis in symbiosis, and haustorial formation in parasitism. We highlight the potentially shared molecular mechanisms across the different developmental programs, especially a core network module mediated by the AUXIN RESPONSIVE FACTOR (ARF) and the LATERAL ORGAN BOUNDARIES DOMAIN (LBD) family of transcription factors. This allows us to propose a new holistic concept that will provide insights into the nature of plant development, catalyzing the fusion of subdisciplines in plant developmental biology.Fusarium head blight (FHB) is a devastating disease in cereals around the world. Because it is quantitatively inherited and technically difficult to reproduce, breeding to increase resistance in wheat germplasm is difficult and slow. Genomic selection (GS) is a form of marker-assisted selection (MAS) that simultaneously estimates all locus, haplotype, or marker effects across the entire genome to calculate genomic estimated breeding values (GEBVs). Since its inception, there have been many studies that demonstrate the utility of GS approaches to breeding for disease resistance in crops. In this study, the Uniform Northern (NUS) and Uniform Southern (SUS) soft red winter wheat scab nurseries (a total 452 lines) were evaluated as possible training populations (TP) to predict FHB traits in breeding lines of the UK (University of Kentucky) wheat breeding program. DON was best predicted by the SUS; Fusarium damaged kernels (FDK), FHB rating, and two indices, DSK index and DK index were best predicted by NUS. GDC-0077 The highest prediction accuracies were obtained when the NUS and SUS were combined, reaching up to 0.5 for almost all traits except FHB rating. Highest prediction accuracies were obtained with bigger TP sizes (300-400) and there were not significant effects of TP optimization method for all traits, although at small TP size, the PEVmean algorithm worked better than other methods. To select for lines with tolerance to DON accumulation, a primary breeding target for many breeders, we compared selection based on DON BLUES with selection based on DON GEBVs, DSK GEBVs, and DK GEBVs. At selection intensities (SI) of 30-40%, DSK index showed the best performance with a 4-6% increase over direct selection for DON. Our results confirm the usefulness of regional nurseries as a source of lines to predict GEBVs for local breeding programs, and shows that an index that includes DON, together with FDK and FHB rating could be an excellent choice to identify lines with low DON content and an overall improved FHB resistance.Among the biotic constraints to wheat (Triticum aestivum L.) production, fusarium head blight (FHB), caused by Fusarium graminearum, leaf rust (LR), caused by Puccinia triticina, and stripe rust (SR) caused by Puccinia striiformis are problematic fungal diseases worldwide. Each can significantly reduce grain yield while FHB causes additional food and feed safety concerns due to mycotoxin contamination of grain. Genetic resistance is the most effective and sustainable approach for managing wheat diseases. In the past 20 years, over 500 quantitative trait loci (QTLs) conferring small to moderate effects for the different FHB resistance types have been reported in wheat. Similarly, 79 Lr-genes and more than 200 QTLs and 82 Yr-genes and 140 QTLs have been reported for seedling and adult plant LR and SR resistance, respectively. Most QTLs conferring rust resistance are race-specific generally conforming to a classical gene-for-gene interaction while resistance to FHB exhibits complex polygenic inheritance with several genetic loci contributing to one resistance type.
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