A recessive high-density pod mutant resource of Brassica napus

Exploring silique number in Brassica napus L.: Genetic and molecular advances for improving yield

Silique number is a crucial yield-related trait for the genetic enhancement of rapeseed (Brassica napus L.). The intricate molecular process governing the regulation of silique number involves various factors. Despite advancements in understanding the mechanisms regulating silique number in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), the molecular processes involved in controlling silique number in rapeseed remain largely unexplored. In this review, we identify candidate genes and review the roles of genes and environmental factors in regulating rapeseed silique number. We use genetic regulatory networks for silique number in Arabidopsis and grain number in rice to uncover possible regulatory pathways and molecular mechanisms involved in regulating genes associated with rapeseed silique number. A better understanding of the genetic network regulating silique number in rapeseed will provide a theoretical basis for the genetic improvement of this trait and genetic resources for the molecular breeding of high-yielding rapeseed.

Point clouds segmentation of rapeseed siliques based on sparse-dense point clouds mapping

In this study, we propose a high-throughput and low-cost automatic detection method based on deep learning to replace the inefficient manual counting of rapeseed siliques. First, a video is captured with a smartphone around the rapeseed plants in the silique stage. Feature point detection and matching based on SIFT operators are applied to the extracted video frames, and sparse point clouds are recovered using epipolar geometry and triangulation principles. The depth map is obtained by calculating the disparity of the matched images, and the dense point cloud is fused. The plant model of the whole rapeseed plant in the silique stage is reconstructed based on the structure-from-motion (SfM) algorithm, and the background is removed by using the passthrough filter. The downsampled 3D point cloud data is processed by the DGCNN network, and the point cloud is divided into two categories: sparse rapeseed canopy siliques and rapeseed stems. The sparse canopy siliques are then segmented from the original whole rapeseed siliques point cloud using the sparse-dense point cloud mapping method, which can effectively save running time and improve efficiency. Finally, Euclidean clustering segmentation is performed on the rapeseed canopy siliques, and the RANSAC algorithm is used to perform line segmentation on the connected siliques after clustering, obtaining the three-dimensional spatial position of each silique and counting the number of siliques. The proposed method was applied to identify 1457 siliques from 12 rapeseed plants, and the experimental results showed a recognition accuracy greater than 97.80%. The proposed method achieved good results in rapeseed silique recognition and provided a useful example for the application of deep learning networks in dense 3D point cloud segmentation.

Transcriptomic Profiling of Shoot Apical Meristem Aberrations in the Multi-Main-Stem Mutant (ms) of Brassica napus L

Rapeseed (Brassica napus L.) is a globally important oilseed crop with various uses, including the consumption of its succulent stems as a seasonal vegetable, but its uniaxial branching habit limits the stem yield. Therefore, developing a multi-stem rapeseed variety has become increasingly crucial. In this study, a natural mutant of the wild type (ZY511, Zhongyou511) with stable inheritance of the multi-stem trait (ms) was obtained, and it showed abnormal shoot apical meristem (SAM) development and an increased main stem number compared to the WT. Histological and scanning electron microscopy analyses revealed multiple SAMs in the ms mutant, whereas only a single SAM was found in the WT. Transcriptome analyses showed significant alterations in the expression of genes involved in cytokinin (CK) biosynthesis and metabolism pathways in the ms mutant. These findings provide insight into the mechanism of multi-main-stem formation in Brassica napus L. and lay a theoretical foundation for breeding multi-main-stem rapeseed vegetable varieties.

Genetic analysis and QTL mapping for silique density in rapeseed (Brassica napus L.)

KEY MESSAGE

Genetic models, QTLs and candidate gene for silique density on main inflorescence of rapeseed were identified. Silique density is one of the critical factors to determine seed yield and plant architecture in rapeseed (Brassica napus L.); however, the genetic control of this trait is largely unknown. In this study, the genetic model for silique density on main inflorescence (SDMI) of rapeseed was estimated according to the phenotypic data of P₁ (an inbreed line with high SDMI), P₂ (an inbreed line with low SDMI), F₁, F₂, BC₁P₁ and BC₁P₂ populations, revealing that SDMI is probably controlled by multi-minor genes with or without major gene. The QTLs for SDMI and its component characters including silique number on main inflorescence (SNMI) and main inflorescence length (MIL) were consequently mapped from a DH population derived from P₁ and P₂ by using a genetic linkage map constructed by restriction site-associated DNA sequencing (RAD seq) technology. A total of eight, 14 and three QTLs were identified for SDMI, SNMI and MIL under three environments, respectively, with an overlap among SDMI and SNMI in 55.7-75.4 cm on linkage group C06 which corresponding to 11.6-27.3 Mb on chromosome C06. Genomic resequencing was further conducted between a high- and a low-SDMI pool constructed from the DH population, and QTL-seq analysis identified a 0.15 Mb interval (25.98-26.13 Mb) from the C06-QTL region aforementioned. Transcriptome sequencing and qRT-PCR identified one possible candidate gene (BnARGOS) from the 0.15 Mb interval. This study will provide novel insights into the genetic basis of SD in rapeseed.

Uncovering Trait Associations Resulting in Maximal Seed Yield in Winter and Spring Oilseed Rape

Seed yield is a complex trait for many crop species including oilseed rape (OSR) (Brassica napus), the second most important oilseed crop worldwide. Studies have focused on the contribution of distinct factors in seed yield such as environmental cues, agronomical practices, growth conditions, or specific phenotypic traits at the whole plant level, such as number of pods in a plant. However, how female reproductive traits contribute to whole plant level traits, and hence to seed yield, has been largely ignored. Here, we describe the combined contribution of 33 phenotypic traits within a B. napus diversity set population and their trade-offs at the whole plant and organ level, along with their interaction with plant level traits. Our results revealed that both Winter OSR (WOSR) and Spring OSR (SOSR); the two more economically important OSR groups in terms of oil production; share a common dominant reproductive strategy for seed yield. In this strategy, the main inflorescence is the principal source of seed yield, producing a good number of ovules, a large number of long pods with a concomitantly high number of seeds per pod. Moreover, we observed that WOSR opted for additional reproductive strategies than SOSR, presenting more plasticity to maximise seed yield. Overall, we conclude that OSR adopts a key strategy to ensure maximal seed yield and propose an ideal ideotype highlighting crucial phenotypic traits that could be potential targets for breeding.