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The quality of rice (Oryza sativa L) is determined by a combination of appearance, flavor, aroma, texture, storage characteristics, and nutritional composition. Rice quality directly influences acceptance by consumers and commercial value. The genetic mechanism underlying rice quality is highly complex, and is influenced by genotype, environment, and chemical factors such as starch type, protein content, and amino acid composition. Minor variations in these chemical components may lead to substantial differences in rice quality. Among these components, starch is the most crucial and influential factor in determining rice quality. In this study, quantitative trait loci (QTLs) associated with eight physicochemical properties related to the rapid viscosity analysis (RVA) profile were identified using a high-density sequence map constructed using recombinant inbred lines (RILs). Fifty-nine QTLs were identified across three environments, among which qGT6.4 was a novel locus co-located across all three environments. By integrating RNA-seq data, we identified the differentially expressed candidate gene OsCRLK2 within the qGT6.4 interval. osclrk2 mutants exhibited decreased gelatinization temperature (GT), apparent amylose content (AAC) and viscosity, and increased chalkiness. Furthermore, osclrk2 mutants exhibited downregulated expression of the majority of starch biosynthesis-related genes compared to wild type (WT) plants. In summary, OsCRLK2, which encodes a receptor-like protein kinase, appears to consistently influence rice quality across different environments. This discovery provides a new genetic resource for use in the molecular breeding of rice cultivars with improved quality.
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Introduction: Accurate white blood cells segmentation from cytopathological images is crucial for evaluating leukemia. However, segmentation is difficult in clinical practice. Given the very large numbers of cytopathological images to be processed, diagnosis becomes cumbersome and time consuming, and diagnostic accuracy is also closely related to experts' experience, fatigue and mood and so on. Besides, fully automatic white blood cells segmentation is challenging for several reasons. There exists cell deformation, blurred cell boundaries, and cell color differences, cells overlapping or adhesion. Methods: The proposed method improves the feature representation capability of the network while reducing parameters and computational redundancy by utilizing the feature reuse of Ghost module to reconstruct a lightweight backbone network. Additionally, a dual-stream feature fusion network (DFFN) based on the feature pyramid network is designed to enhance detailed information acquisition. Furthermore, a dual-domain attention module (DDAM) is developed to extract global features from both frequency and spatial domains simultaneously, resulting in better cell segmentation performance. Results: Experimental results on ALL-IDB and BCCD datasets demonstrate that our method outperforms existing instance segmentation networks such as Mask R-CNN, PointRend, MS R-CNN, SOLOv2, and YOLACT with an average precision (AP) of 87.41%, while significantly reducing parameters and computational cost. Discussion: Our method is significantly better than the current state-of-the-art single-stage methods in terms of both the number of parameters and FLOPs, and our method has the best performance among all compared methods. However, the performance of our method is still lower than the two-stage instance segmentation algorithms. in future work, how to design a more lightweight network model while ensuring a good accuracy will become an important problem.
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Origin and evolution of tetraploid Elymus fibrosus (Schrenk) Tzvelev were characterized using low-copy nuclear gene Rpb2 (the second largest subunit of RNA polymerase II), and chloroplast region trnL-trnF (spacer between the tRNA Leu (UAA) gene and the tRNA-Phe (GAA) gene). Ten accessions of E. fibrosus along with 19 Elymus species with StH genomic constitution and diploid species in the tribe Triticeae were analyzed. Chloroplast trnL-trnF sequence data suggested that Pseudoroegneria (St genome) was the maternal donor of E. fibrosus. Rpb2 data confirmed the presence of StH genomes in E. fibrosus, and suggested that St and H genomes in E. fibrosus each is more likely originated from single gene pool. Single origin of E. fibrosus might be one of the reasons causing genetic diversity in E. fibrosus lower than those in E. caninus and E. trachycaulus, which have similar ecological preferences and breeding systems with E. fibrosus, and each was originated from multiple sources. Convergent evolution of St and H copy Rpb2 sequences in some accessions of E. fibrosus might have occurred during the evolutionary history of this allotetraploid.