Identification of Two bZIP Transcription Factors Interacting with the Promoter of Soybean Rubisco Activase Gene (GmRCAα)

Rubisco activase (RCA), a key photosynthetic protein, catalyses the activation of Rubisco and thus plays an important role in photosynthesis. Although the RCA gene has been characterized in a variety of species, the molecular mechanism regulating its transcription remains unclear. Our previous studies on RCA gene expression in soybean suggested that expression of this gene is regulated by trans-acting factors. In the present study, we verified activity of the GmRCAα promoter in both soybean and Arabidopsis and used a yeast one-hybrid (Y1H) system for screening a leaf cDNA expression library to identify transcription factors (TFs) interacting with the GmRCAα promoter. Four basic leucine zipper (bZIP) TFs, GmbZIP04g, GmbZIP07g, GmbZIP1 and GmbZIP71, were isolated, and GmbZIP04g and GmbZIP07g were confirmed as able to bind to a 21-nt G-box-containing sequence. Additionally, the expression patterns of GmbZIP04g, GmbZIp07g and GmRCAα were analysed in response to abiotic stresses and during a 24-h period. Our study will help to advance elucidation of the network regulating GmRCAα transcription

GmMYB181, a Soybean R2R3-MYB Protein, Increases Branch Number in Transgenic Arabidopsis

Soybean (Glycine max) is an important economic crop that provides abundant oil and high quality protein for human beings. As the process of reproductive growth directly determines the crop seed yield and quality, we initiated studies to identify genes that regulate soybean floral organ development. One R2R3-MYB transcription factor gene, designated as GmMYB181, was found to be enriched in flowers based on microarray analysis and was further functionally investigated in transgenic Arabidopsis. GmMYB181 protein contains two MYB domains, which localized to the nucleus and displayed transcriptional activation in yeast hybrid system. Real-time quantitative PCR (qRT-PCR) results suggested GmMYB181 exclusively expressed in flower tissue. In Arabidopsis, overexpression of GmMYB181 altered the morphology of floral organs, fruit size and plant architecture, including outward curly sepals, smaller siliques, increased lateral branches and reduced plant height, indicating that GmMYB181 is involved in the development of reproductive organs and plays an important role in controlling plant architecture. Further, microarray analysis revealed that overexpressing GmMYB181 in Arabidopsis affected the expression of 3450 genes in mature flowers, including those involved in floral organ, seed/fruit development, and responded to different hormone signals

Phytochrome control of plant growth and metabolism in Arabidopsis thaliana

Plants rely on light to supply photosynthetic energy and to provide information of the surrounding environment. Phytochromes are photoreceptors that sense external light quality and quantity, which in turn guide the strategy of plant growth. A large body of research has focused on Arabidopsis thaliana seedlings, where phytochrome control of responses such as hypocotyl elongation, hook opening and cotyledon greening, has been intensively explored. Mathematical models have also helped elucidate the molecular mechanism of phytochrome signalling. A smaller proportion of studies have investigated the role of phytochrome in controlling plant plasticity in adult plants. This work has shown that phytochrome depletion enhances leaf petiole elongation and slows growth, but there is a lack of information on how these marked changes alter metabolism. In this thesis, I use phytochrome multiple mutants of to explore how phytochromes interact with metabolism to affect plant growth. My analysis revealed that phytochrome loss results in dramatically reduced biomass production, especially in high order phyABDE mutant that lacks four out of five phytochromes. This is caused, at least partly, by impaired photosynthesis in phytochrome mutants, including reduced chlorophyll level and less CO2 uptake. Furthermore, cell wall synthesis and protein levels, major dry biomass constituents, are also repressed in phytochrome-depleted plants. Interestingly, these mutants accumulate more daytime sucrose and starch than wild type does, possibly due to their retarded growth in light. Further metabolic profiling reveals that these phytochrome mutants over-accumulate sugars, organic acids and amino acids. The sizable increase in raffinose and proline suggests a possible link to stress tolerance. Indeed, ABA and salt responses are significantly reduced in phytochrome mutants at both seedling and adult stages. These mutants are also more resistant to prolonged darkness, with less chlorophyll degradation in dark and higher survival rates. Collectively, this thesis shows that phytochromes have a novel role in plant resource management, controlling the allocation of resources for growth, switching the metabolism between growth and stress-coping states based on the availability of light from the environment. It brings new interest into phytochrome research in Arabidopsis, suggesting possible application of such knowledge to crop studies in the future

Experimental Study on Mechanical Properties of Briquette Coal Samples with Different Moisture Content

Coal seam water injection is an important technical method to prevent and control coal and gas outburst and other disasters. Water can soften coal and change its mechanical properties. In order to study the mechanical properties of coal samples with different moisture content, briquette coal samples with five moistures content (4%, 6%, 8%, 10%, and 12%) were selected to carry out triaxial compression tests under different confining pressures (0.1, 0.2, 0.4, 0.8, and 1.2 MPa). Then, the mechanical response mechanism of the water-bearing briquette coal was analyzed. The results show that the slope of the linear elastic stage of the stress-strain curve gradually decreases with the increase of moisture content. Water-bearing coal exhibits strain strengthening characteristics under high confining pressure, which transforms the water-bearing coal from brittle to ductile state. The peak stress under different moisture content conditions shows a linear relationship with the confining pressure. The internal friction angle decreases linearly with the increase of moisture content. The cohesion varies parabolically with the increase of moisture content and reaches the maximum value when the moisture content is 8%. The coal body with moisture content between 7% and 9% has a high bonding force, which is beneficial to the consolidation of the coal body. Therefore, ensuring a reasonable moisture content of coal through coal seam injection can provide a basis for preventing coal and gas outburst

Soybean MADS-box gene GmAGL1 promotes flowering via the photoperiod pathway

Abstract Background The MADS-box transcription factors are an ancient family of genes that regulate numerous physiological and biochemical processes in plants and facilitate the development of floral organs. However, the functions of most of these transcription factors in soybean remain unknown. Results In this work, a MADS-box gene, GmAGL1, was overexpressed in soybean. Phenotypic analysis showed that GmAGL1 overexpression not only resulted in early maturation but also promoted flowering and affected petal development. Furthermore, the GmAGL1 was much more effective at promoting flowering under long-day conditions than under short-day conditions. Transcriptome sequencing analysis showed that before flowering, the photoperiod pathway photoreceptor CRY2 and several circadian rhythm genes, such as SPA1, were significantly down-regulated, while some other flowering-promoting circadian genes, such as GI and LHY, and downstream genes related to flower development, such as FT, LEAFY, SEP1, SEP3, FUL, and AP1, were up-regulated compared with the control. Other genes related to the flowering pathway were not noticeably affected. Conclusions The findings reported herein indicate that GmAGL1 may promote flowering mainly through the photoperiod pathway. Interestingly, while overexpression of GmAGL1 promoted plant maturity, no reduction in seed production or oil and protein contents was observed

MU R-CNN: A Two-Dimensional Code Instance Segmentation Network Based on Deep Learning

In the context of Industry 4.0, the most popular way to identify and track objects is to add tags, and currently most companies still use cheap quick response (QR) tags, which can be positioned by computer vision (CV) technology. In CV, instance segmentation (IS) can detect the position of tags while also segmenting each instance. Currently, the mask region-based convolutional neural network (Mask R-CNN) method is used to realize IS, but the completeness of the instance mask cannot be guaranteed. Furthermore, due to the rich texture of QR tags, low-quality images can lower intersection-over-union (IoU) significantly, disabling it from accurately measuring the completeness of the instance mask. In order to optimize the IoU of the instance mask, a QR tag IS method named the mask UNet region-based convolutional neural network (MU R-CNN) is proposed. We utilize the UNet branch to reduce the impact of low image quality on IoU through texture segmentation. The UNet branch does not depend on the features of the Mask R-CNN branch so its training process can be carried out independently. The pre-trained optimal UNet model can ensure that the loss of MU R-CNN is accurate from the beginning of the end-to-end training. Experimental results show that the proposed MU R-CNN is applicable to both high- and low-quality images, and thus more suitable for Industry 4.0