Search

The main type of saponins occurring in the root of Platycodon grandiflorus (Jacq.) A. DC. are oleanolic acid glycosides. The CYP716 gene family plays a major role in catalyzing the conversion of β-amyrin into oleanolic acid. However, studies on the CYP716 genes in P. grandiflorus are limited, and its evolutionary history remains poorly understood. In this study, 22 PgCYP716 genes were identified, distributed among seven subfamilies. Cis-acting elements of the PgCYP716 promoters were mainly involved in plant hormone regulation and responses to abiotic stresses. PgCYP716A264, PgCYP716A391, PgCYP716A291, and PgCYP716BWv3 genes were upregulated in the root and during saponin accumulation, as shown by RNA-seq analysis, suggesting that these four genes play an important role in saponin synthesis. The results of subcellular localization indicated that these four genes encoded membrane proteins. Furthermore, the catalytic activity of these four genes was proved in the yeast, which catalyzed the conversion of β-amyrin into oleanolic acid. We found that the content of β-amyrin, platycodin D, platycoside E, platycodin D3, and total saponins increased significantly when either of the four genes was over expressed in the transgenic hair root. In addition, the expression of PgSS, PgGPPS2, PgHMGS, and PgSE was also upregulated while these four genes were overexpressed. These data support that these four PgCYP716 enzymes oxidize β-amyrin to produce oleanolic acid, ultimately promoting saponin accumulation by activating the expression of upstream pathway genes. Our results enhanced the understanding of the functional variation among the PgCYP716 gene family involved in triterpenoid biosynthesis and provided a theoretical foundation for improving saponin content and enriching the saponin biosynthetic pathway in P. grandiflorus. [ABSTRACT FROM AUTHOR]

The dimensions of organs such as flowers, leaves, and seeds are governed by processes of cellular proliferation and expansion. In soybeans, the dimensions of these organs exhibit a strong correlation with crop yield, quality, and other phenotypic traits. Nevertheless, there exists a scarcity of research concerning the regulatory genes influencing flower size, particularly within the soybean species. In this study, 309 samples of 3 soybean types (123 cultivar, 90 landrace, and 96 wild) were re-sequenced. The microscopic phenotype of soybean flower organs was photographed using a three-eye microscope, and the phenotypic data were extracted by means of computer vision. Pearson correlation analysis was employed to assess the relationship between petal and seed phenotypes, revealing a strong correlation between the sizes of these two organs. Through GWASs, SNP loci significantly associated with flower organ size were identified. Subsequently, haplotype analysis was conducted to screen for upstream and downstream genes of these loci, thereby identifying potential candidate genes. In total, 77 significant SNPs associated with vexil petals, 562 significant SNPs associated with wing petals, and 34 significant SNPs associated with keel petals were found. Candidate genes were screened by candidate sites, and haplotype analysis was performed on the candidate genes. Finally, the present investigation yielded 25 and 10 genes of notable significance through haplotype analysis in the vexil and wing regions, respectively. Notably, Glyma.07G234200, previously documented for its high expression across various plant organs, including flowers, pods, leaves, roots, and seeds, was among these identified genes. The research contributes novel insights to soybean breeding endeavors, particularly in the exploration of genes governing organ development, the selection of field materials, and the enhancement of crop yield. It played a role in the process of material selection during the growth period and further accelerated the process of soybean breeding material selection. [ABSTRACT FROM AUTHOR]

Crop 3-dimensional (3D) reconstruction is one of the most fundamental techniques in crop phenomics, and is an important tool to accurately describe the holographic structure of crop morphology. 3D reconstruction models of crops are important for high-throughput crop phenotype acquisition, crop plant characteristics evaluation, and plant structure and phenotype correlation analysis. In order to promote and popularize the 3D reconstruction technology in crop phenotype research, the basic methods and application characteristics, the current advances of research and the prospects of 3D reconstruction in crops were review in this paper. Firstly, the existing methods of crop 3D reconstruction were summarized, the basic principles of each method were reviewed, the characteristics, advantages and disadvantages of each method were analyzed, the applicability of each method on the basis of the general process of crop 3D reconstruction methods were introduced, and the specific process and considerations for the implementation of each method were summarized. Secondly, the application of crop 3D reconstruction were divided into three parts: single crop reconstruction, field group reconstruction and root system, according to different target objects, and the applications of crop 3D reconstruction technology from these three perspectives were reviewed, the research advances of each method for different crop 3D reconstruction based on accuracy, speed and cost were explored, and the problems and challenges of crop 3D reconstruction in the context of different reconstruction objects were organized. Finally, the prospects of crop 3D reconstruction technology were analyzed.

Summary: Soybean is one of the most economically important crops worldwide and an important source of unsaturated fatty acids and protein for the human diet. Consumer demand for healthy fats and oils is increasing, and the global demand for vegetable oil is expected to double by 2050. Identification of key genes that regulate seed fatty acid content can facilitate molecular breeding of high‐quality soybean varieties with enhanced fatty acid profiles. Here, we analysed the genetic architecture underlying variations in soybean seed fatty acid content using 547 accessions, including mainly landraces and cultivars from northeastern China. Through fatty acid profiling, genome re‐sequencing, population genomics analyses, and GWAS, we identified a SEIPIN homologue at the FA9 locus as an important contributor to seed fatty acid content. Transgenic and multiomics analyses confirmed that FA9 was a key regulator of seed fatty acid content with pleiotropic effects on seed protein and seed size. We identified two major FA9 haplotypes in 1295 resequenced soybean accessions and assessed their phenotypic effects in a field planting of 424 accessions. Soybean accessions carrying FA9H2 had significantly higher total fatty acid contents and lower protein contents than those carrying FA9H1. FA9H2 was absent in wild soybeans but present in 13% of landraces and 26% of cultivars, suggesting that it may have been selected during soybean post‐domestication improvement. FA9 therefore represents a useful genetic resource for molecular breeding of high‐quality soybean varieties with specific seed storage profiles. [ABSTRACT FROM AUTHOR]

The study of plant phenotypes based on 3D models has become an important research direction for automatic plant phenotype acquisition. Building a labeled three-dimensional dataset of the whole growth period can help the development of 3D crop plant models in point cloud segmentation. Therefore, the demand for 3D whole plant growth period model datasets with organ-level markers is growing rapidly. In this study, five different soybean varieties were selected, and three-dimensional reconstruction was carried out for the whole growth period (13 stages) of soybean using multiple-view stereo technology (MVS). Leaves, main stems, and stems of the obtained three-dimensional model were manually labeled. Finally, two-point cloud semantic segmentation models, RandLA-Net and BAAF-Net, were used for training. In this paper, 102 soybean stereoscopic plant models were obtained. A dataset with original point clouds was constructed and the subsequent analysis confirmed that the number of plant point clouds was consistent with corresponding real plant development. At the same time, a 3D dataset named Soybean-MVS with labels for the whole soybean growth period was constructed. The test result of mAccs at 88.52% and 87.45% verified the availability of this dataset. In order to further promote the study of point cloud segmentation and phenotype acquisition of soybean plants, this paper proposed an annotated three-dimensional model dataset for the whole growth period of soybean for 3D plant organ segmentation. The release of the dataset can provide an important basis for proposing an updated, highly accurate, and efficient 3D crop model segmentation algorithm. In the future, this dataset will provide important and usable basic data support for the development of three-dimensional point cloud segmentation and phenotype automatic acquisition technology of soybeans. [ABSTRACT FROM AUTHOR]