A 24,482-bp deletion is associated with increased seed weight in Brassica napus L

Fine mapping and candidate gene analysis of the major QTL qSW-A03 for seed weight in Brassica napus

Seed weight is a determining factor for improving rapeseed productivity. In the present study, a high-density genetic map was constructed via genome resequencing in an RIL population derived from a cross of two rapeseed varieties, ZS11 and DL704, with great differences in thousand-seed weight (TSW). A total of 1,306 bins involving 1,261,526 markers were used to construct the bin map. On the basis of the genetic map, QTL mapping for seed weight was performed. In total, 15 QTLs associated with TSW were detected. A major and stable QTL, qSW-A03, was mapped to a 2.8 cM interval on chromosome A03. Fine mapping delimited the qSW-A03 locus into a 59-kb region, and 11 genes within this region were predicted. By employing a combination of gene variation, gene expression difference and gene coexpression network analysis of seed weight, BnaDUF1666 was identified as a promising candidate gene. This study provides useful information for the genetic dissection of seed weight and promotes the molecular breeding of high-yield rapeseed.

RING-type E3 ligase BnaJUL1 ubiquitinates and degrades BnaTBCC1 to regulate drought tolerance in Brassica napus L

Drought stress poses a persistent threat to field crops and significantly limits global agricultural productivity. Plants employ ubiquitin-dependent degradation as a crucial post-translational regulatory mechanism to swiftly adapt to changing environmental conditions. JUL1 is a RING-type E3 ligase related to drought stress in Arabidopsis. In this study, we explored the function of BnaJUL1 (a homologous gene of JUL1 in Brassica napus) and discovered a novel gene BnaTBCC1 participating in drought tolerance. First, we utilised BnaJUL1-cri materials through the clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 system. Second, we confirmed that BnaJUL1 regulated drought tolerance through the drought tolerance assay and transcriptome analysis. Then, we identified a series of proteins interacting with BnaJUL1 through yeast library screening, including BnaTBCC1 (a tubulin binding cofactor C domain-containing protein); whose homologous gene TBCC1 knockdown mutants (tbcc1-1) exhibited ABA-sensitive germination in Arabidopsis, we then confirmed the involvement of BnaTBCC1 in drought tolerance in both Arabidopsis and Brassica. Finally, we established that BnaJUL1 could ubiquitinate and degrade BnaTBCC1 to regulate drought tolerance. Consequently, our study unveils BnaJUL1 as a novel regulator that ubiquitinates and degrades BnaTBCC1 to modulate drought tolerance and provided desirable germplasm for further breeding of drought tolerance in rapeseed.

Brassica napus Haploid and Double Haploid Production and Its Latest Applications

Rapeseed is one of the most important oil crops in the world. Increasing demand for oil and limited agronomic capabilities of present-day rapeseed result in the need for rapid development of new, superior cultivars. Double haploid (DH) technology is a fast and convenient approach in plant breeding as well as genetic research. Brassica napus is considered a model species for DH production based on microspore embryogenesis; however, the molecular mechanisms underlying microspore reprogramming are still vague. It is known that morphological changes are accompanied by gene and protein expression patterns, alongside carbohydrate and lipid metabolism. Novel, more efficient methods for DH rapeseed production have been reported. This review covers new findings and advances in Brassica napus DH production as well as the latest reports related to agronomically important traits in molecular studies employing the double haploid rapeseed lines.

A simple and efficient method to quantify the cell parameters of the seed coat, embryo and silique wall in rapeseed

BACKGROUND

Researchers interested in the seed size of rapeseed need to quantify the cell size and number of cells in the seed coat, embryo and silique wall. Scanning electron microscope-based methods have been demonstrated to be feasible but laborious and costly. After image preparation, the cell parameters are generally evaluated manually, which is time consuming and a major bottleneck for large-scale analysis. Recently, two machine learning-based algorithms, Trainable Weka Segmentation (TWS) and Cellpose, were released to overcome this long-standing problem. Moreover, the MorphoLibJ and LabelsToROIs plugins in Fiji provide user-friendly tools to deal with cell segmentation files. We attempted to verify the practicability and efficiency of these advanced tools for various types of cells in rapeseed.

RESULTS

We simplified the current image preparation procedure by skipping the fixation step and demonstrated the feasibility of the simplified procedure. We developed three methods to automatically process multicellular images of various tissues in rapeseed. The TWS-Fiji (TF) method combines cell detection with TWS and cell measurement with Fiji, enabling the accurate quantification of seed coat cells. The Cellpose-Fiji (CF) method, based on cell segmentation with Cellpose and quantification with Fiji, achieves good performance but exhibits systematic error. By removing border labels with MorphoLibJ and detecting regions of interest (ROIs) with LabelsToROIs, the Cellpose-MorphoLibJ-LabelsToROIs (CML) method achieves human-level performance on bright-field images of seed coat cells. Intriguingly, the CML method needs very little manual calibration, a property that makes it suitable for massive-scale image processing. Through a large-scale quantitative evaluation of seed coat cells, we demonstrated the robustness and high efficiency of the CML method at both the single-cell level and the sample level. Furthermore, we extended the application of the CML method to developing seed coat, embryo and silique wall cells and acquired highly precise and reliable results, indicating the versatility of this method for use in multiple scenarios.

CONCLUSIONS

The CML method is highly accurate and free of the need for manual correction. Hence, it can be applied for the low-cost, high-throughput quantification of diverse cell types in rapeseed with high efficiency. We envision that this method will facilitate the functional genomics and microphenomics studies of rapeseed and other crops.