Characteristics and Cytological Analysis of Several Novel Allopolyploids and Aneuploids between Brassica oleracea and Raphanus sativus.

Polyploids are essential in plant evolution and species formation, providing a rich genetic reservoir and increasing species diversity. Complex polyploids with higher ploidy levels often have a dosage effect on the phenotype, which can be highly detrimental to gametes, making them rare. In this study, offspring plants resulting from an autoallotetraploid (RRRC) derived from the interspecific hybridization between allotetraploid Raphanobrassica (RRCC, 2n = 36) and diploid radish (RR, 2n = 18) were obtained. Fluorescence in situ hybridization (FISH) using C-genome-specific repeats as probes revealed two main genome configurations in these offspring plants: RRRCC (2n = 43, 44, 45) and RRRRCC (2n = 54, 55), showing more complex genome configurations and higher ploidy levels compared to the parental plants. These offspring plants exhibited extensive variation in phenotypic characteristics, including leaf type and flower type and color, as well as seed and pollen fertility. Analysis of chromosome behavior showed that homoeologous chromosome pairing events are widely observed at the diakinesis stage in the pollen mother cells (PMCs) of these allopolyploids, with a range of 58.73% to 78.33%. Moreover, the unreduced C subgenome at meiosis anaphase II in PMCs was observed, which provides compelling evidence for the formation of complex allopolyploid offspring. These complex allopolyploids serve as valuable genetic resources for further analysis and contribute to our understanding of the mechanisms underlying the formation of complex allopolyploids.

[Super-resolution reconstruction for lung four dimensional computed tomography images using multi-model Gaussian process regression].

Lung four dimensional computed tomography (4D-CT) can lead to accurate radiotherapy. However, for the safety of patients, the scan spacing of 4D-CT cannot be too small so that the inter-slice resolution of lung 4D-CT is low, and thus the coronal and sagittal images need to be interpolated to obtain high-resolution images. This paper presents a super-resolution reconstruction technique based on multi-model Gaussian process regression. We use the high-resolution transversal images and the corresponding low-resolution images as the training sets. The high-resolution pixels of the coronal and sagittal images can be predicted by constructing multiple Gaussian process regression models. The experimental results show that our method is superior to bicubic algorithm, projections onto convex sets, sparse coding, multi-phase similarity based method and Gaussian process regression method based on self-learning block in terms of the edge and detail recovery. The results demonstrate that the proposed method can effectively improve the quality of lung 4D-CT images, and potentially be applied to better image-guided radiation therapy of lung cancer.

Identification, Characterization, and Cytological Analysis of Several Unexpected Hybrids Derived from Reciprocal Crosses between Raphanobrassica and Its Diploid Parents.

Interspecific hybridization and accompanying backcross between crops and relatives have been recognized as a powerful method to broaden genetic diversity and transfer desirable adaptive traits. Crosses between radish (Raphanus sativus, RR, 2n = 18) and Brassica oleracea (CC, 2n = 18), which formed allotetraploid Raphanobrassica (RRCC, 2n = 36), initiated the construction of resynthetic allopolyploids. However, these progenies from the backcrosses between Raphanobrassica and the two diploid parents have not been well deciphered. Herein, thousands of backcrosses using both Raphanobrassica and the two diploid parents as pollen donors were employed. Several hybrids with expected (2n = 27) and unexpected chromosome numbers (2n = 26 and 2n = 36) were obtained. Fluorescence in situ hybridization (FISH) analysis with R-genome-specific sequences as probes demonstrated that the genome structures of the two expected hybrids were RRC and CCR, and the genome structures of the three unexpected hybrids were RRRC, CCCR, and RRC' (harbouring an incomplete C genome). The unexpected hybrids with extra R or C genomes showed similar phenotypic characteristics to their expected hybrids. FISH analysis with C-genome-specific sequences as probes demonstrated that the unexpected allotetraploid hybrids exhibited significantly more intergenomic chromosome pairings than the expected hybrids. The expected and unexpected hybrids provide not only novel germplasm resources for the breeding of radish and B. oleracea but also very important genetic material for genome dosage analysis.

Integrative Physiological and Transcriptome Analysis Reveals the Mechanism of Cd Tolerance in Sinapis alba.

Recently, pollution caused by the heavy metal Cd has seriously affected the environment and agricultural crops. While Sinapis alba is known for its edible and medicinal value, its tolerance to Cd and molecular response mechanism remain unknown. This study aimed to analyze the tolerance of S. alba to Cd and investigate its molecular response mechanism through transcriptomic and physiological indicators. To achieve this, S. alba seedlings were treated with different concentrations of CdCl2 (0.25 mmol/L, 0.5 mmol/L, and 1.0 mmol/L) for three days. Based on seedling performance, S. alba exhibited some tolerance to a low concentration of Cd stress (0.25 mmol/L CdCl2) and a strong Cd accumulation ability in its roots. The activities and contents of several antioxidant enzymes generally exhibited an increase under the treatment of 0.25 mmol/L CdCl2 but decreased under the treatment of higher CdCl2 concentrations. In particular, the proline (Pro) content was extremely elevated under the 0.25 and 0.5 mmol/L CdCl2 treatments but sharply declined under the 1.0 mmol/L CdCl2 treatment, suggesting that Pro is involved in the tolerance of S. alba to low concentration of Cd stress. In addition, RNA sequencing was utilized to analyze the gene expression profiles of S. alba exposed to Cd (under the treatment of 0.25 mmol/L CdCl2). The results indicate that roots were more susceptible to disturbance from Cd stress, as evidenced by the detection of 542 differentially expressed genes (DEGs) in roots compared to only 37 DEGs in leaves. GO and KEGG analyses found that the DEGs induced by Cd stress were primarily enriched in metabolic pathways, plant hormone signal transduction, and the biosynthesis of secondary metabolites. The key pathway hub genes were mainly associated with intracellular ion transport and cell wall synthesis. These findings suggest that S. alba is tolerant to a degree of Cd stress, but is also susceptible to the toxic effects of Cd. Furthermore, these results provide a theoretical basis for understanding Cd tolerance in S. alba.

Resolution enhancement for lung 4D-CT based on transversal structures by using multiple Gaussian process regression learning.

PURPOSE: Four-dimensional computed tomography (4D-CT) plays a useful role in many clinical situations. However, due to the hardware limitation of system, dense sampling along superior-inferior direction is often not practical. In this paper, we develop a novel multiple Gaussian process regression model to enhance the superior-inferior resolution for lung 4D-CT based on transversal structures. METHODS: The proposed strategy is based on the observation that high resolution transversal images can recover missing pixels in the superior-inferior direction. Based on this observation and motived by random forest algorithm, we employ multiple Gaussian process regression model learned from transversal images to improve superior-inferior resolution. Specifically, we first randomly sample 3 × 3 patches from original transversal images. The central pixel of these patches and the eight-neighbour pixels of their corresponding degraded versions form the label and input of training data, respectively. Multiple Gaussian process regression model is then built on the basis of multiple training subsets obtained by random sampling. Finally, the central pixel of the patch is estimated based on the proposed model, with the eight-neighbour pixels of each 3 × 3 patch from interpolated superior-inferior direction images as inputs. RESULTS: The performance of our method is extensively evaluated using simulated and publicly available datasets. Our experiments show the remarkable performance of the proposed method. CONCLUSIONS: In this paper, we propose a new approach to improve the 4D-CT resolution, which does not require any external data and hardware support, and can produce clear coronal/sagittal images for easy viewing.

Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction.

Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al's algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al's method, thus indicating the effectivity and competitiveness of the proposed algorithm.