Homo- and Hetero-Dimers of CAD Enzymes Regulate Lignification and Abiotic Stress Response in Moso Bamboo

Lignin biosynthesis enzymes form complexes for metabolic channelling during lignification and these enzymes also play an essential role in biotic and abiotic stress response. Cinnamyl alcohol dehydrogenase (CAD) is a vital enzyme that catalyses the reduction of aldehydes to alcohols, which is the final step in the lignin biosynthesis pathway. In the present study, we identified 49 CAD enzymes in five Bambusoideae species and analysed their phylogenetic relationships and conserved domains. Expression analysis of Moso bamboo PheCAD genes in several developmental tissues and stages revealed that among the PheCAD genes, PheCAD2 has the highest expression level and is expressed in many tissues and PheCAD1, PheCAD6, PheCAD8 and PheCAD12 were also expressed in most of the tissues studied. Co-expression analysis identified that the PheCAD2 positively correlates with most lignin biosynthesis enzymes, indicating that PheCAD2 might be the key enzyme involved in lignin biosynthesis. Further, more than 35% of the co-expressed genes with PheCADs were involved in biotic or abiotic stress responses. Abiotic stress transcriptomic data (SA, ABA, drought, and salt) analysis identified that PheCAD2, PheCAD3 and PheCAD5 genes were highly upregulated, confirming their involvement in abiotic stress response. Through yeast two-hybrid analysis, we found that PheCAD1, PheCAD2 and PheCAD8 form homo-dimers. Interestingly, BiFC and pull-down experiments identified that these enzymes form both homo- and hetero- dimers. These data suggest that PheCAD genes are involved in abiotic stress response and PheCAD2 might be a key lignin biosynthesis pathway enzyme. Moreover, this is the first report to show that three PheCAD enzymes form complexes and that the formation of PheCAD homo- and hetero- dimers might be tissue specific

Homo- and Hetero-Dimers of CAD Enzymes Regulate Lignification and Abiotic Stress Response in Moso Bamboo

Lignin biosynthesis enzymes form complexes for metabolic channelling during lignification and these enzymes also play an essential role in biotic and abiotic stress response. Cinnamyl alcohol dehydrogenase (CAD) is a vital enzyme that catalyses the reduction of aldehydes to alcohols, which is the final step in the lignin biosynthesis pathway. In the present study, we identified 49 CAD enzymes in five Bambusoideae species and analysed their phylogenetic relationships and conserved domains. Expression analysis of Moso bamboo PheCAD genes in several developmental tissues and stages revealed that among the PheCAD genes, PheCAD2 has the highest expression level and is expressed in many tissues and PheCAD1, PheCAD6, PheCAD8 and PheCAD12 were also expressed in most of the tissues studied. Co-expression analysis identified that the PheCAD2 positively correlates with most lignin biosynthesis enzymes, indicating that PheCAD2 might be the key enzyme involved in lignin biosynthesis. Further, more than 35% of the co-expressed genes with PheCADs were involved in biotic or abiotic stress responses. Abiotic stress transcriptomic data (SA, ABA, drought, and salt) analysis identified that PheCAD2, PheCAD3 and PheCAD5 genes were highly upregulated, confirming their involvement in abiotic stress response. Through yeast two-hybrid analysis, we found that PheCAD1, PheCAD2 and PheCAD8 form homo-dimers. Interestingly, BiFC and pull-down experiments identified that these enzymes form both homo- and hetero- dimers. These data suggest that PheCAD genes are involved in abiotic stress response and PheCAD2 might be a key lignin biosynthesis pathway enzyme. Moreover, this is the first report to show that three PheCAD enzymes form complexes and that the formation of PheCAD homo- and hetero- dimers might be tissue specific

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Increasing grain yield potential in wheat has been a major target of most breeding programs. Genetic advance has been frequently hindered by negative correlations among yield components that have been often observed in segregant populations and germplasm collections. A tetraploid wheat collection was evaluated in seven environments and genotyped with a 90K SNP assay to identify major and stable quantitative trait loci (QTL) for grain yield per spike (GYS), kernel number per spike (KNS) and thousand-kernel weight (TKW), and to analyse the genetic relationships between the yield components at QTL level. The genome-wide association analysis detected eight, eleven and ten QTL for KNS, TKW and GYS, respectively, significant in at least three environments or two environments and the mean across environments. Most of the QTL for TKW and KNS were found located in different marker intervals, indicating that they are genetically controlled independently by each other. Out of eight KNS QTL, three were associated to significant increases of GYS, while the increased grain number of five additional QTL was completely or partially compensated by decreases in grain weight, thus producing no or reduced effects on GYS. Similarly, four consistent and five suggestive TKW QTL resulted in visible increase of GYS, while seven additional QTL were associated to reduced effects in grain number and no effects on GYS. Our results showed that QTL analysis for detecting TKW or KNS alleles useful for improving grain yield potential should consider the pleiotropic effects of the QTL or the association to other QTLs

Identification of Usefulness for Online Reviews Based on Grounded Theory and Multilayer Perceptron Neural Network

In the context of the continuous development of e-commerce platforms and consumer shopping patterns, online reviews of goods are increasing. At the same time, its commercial value is self-evident, and many merchants and consumers manipulate online reviews for profit purposes. Therefore, a method based on Grounded theory and Multi-Layer Perceptron (MLP) neural network is proposed to identify the usefulness of online reviews. Firstly, the Grounded theory is used to collect and analyze the product purchasing experiences of 35 consumers, and the characteristics of the usefulness of online reviews in each stage of purchase decision-making are extracted. Secondly, the MLP neural network classifier is used to identify the usefulness of online reviews. Finally, relevant comments are captured as the subject and compared with the traditional classifier algorithm to verify the effectiveness of the proposed method. The experimental results show that the feature extraction method considering consumers’ purchase decisions can improve the classification effect to a certain extent and provide some guidance and suggestions for enterprises in the practice of operating online stores

Fake online review recognition algorithm and optimisation research based on deep learning

With the rapid development of the e-commerce industry, online reviews of goods are a great help for consumers to make decisions. With the sharp increase in online order for goods and the explosion of product reviews, some merchants began to hire consumers to make fake purchases for profit, which led to the problem of identifying fake reviews. In this paper, we propose a method that uses feature engineering to eliminate the comments of false reviewers and combines convolutional neural network and recurrent neural network to classify and recognise reviews from the perspective of text. Traditional neural network models such as CNN, LSTM and BILSTM are compared with the hybrid model proposed by the text. The model is optimised by pre-training on the Baidu Baike commodity review database instead of the initial randomising word vector. The experimental results show that the combination of convolutional neural network and recurrent neural network can better extract the global and local features of false comments, and the model has a good effect. The updating of the pre-trained word vector makes the recognition effect of each model better

How does digital village construction influences carbon emission? The case of China.

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions. The study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications

How does digital village construction influences carbon emission? The case of China

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technology efficiency are important ways for digital village construction to reduce agricultural carbon emissions. The study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications

Knot optimization for biharmonic B-splines on manifold triangle meshes

Biharmonic B-splines, proposed by Feng and Warren, are an elegant generalization of univariate B-splines to planar and curved domains with fully irregular knot configuration. Despite the theoretic breakthrough, certain technical difficulties are imperative, including the necessity of Voronoi tessellation, the lack of analytical formulation of bases on general manifolds, expensive basis re-computation during knot refinement/removal, being applicable for simple domains only (e.g., such as euclidean planes, spherical and cylindrical domains, and tori). To ameliorate, this paper articulates a new biharmonic B-spline computing paradigm with a simple formulation. We prove that biharmonic B-splines have an equivalent representation, which is solely based on a linear combination of Green's functions of the bi-Laplacian operator. Consequently, without explicitly computing their bases, biharmonic B-splines can bypass the Voronoi partitioning and the discretization of bi-Laplacian, enable the computational utilities on any compact 2-manifold. The new representation also facilitates optimization-driven knot selection for constructing biharmonic B-splines on manifold triangle meshes. We develop algorithms for spline evaluation, data interpolation and hierarchical data decomposition. Our results demonstrate that biharmonic B-splines, as a new type of spline functions with theoretic and application appeal, afford progressive update of fully irregular knots, free of singularity, without the need of explicit parameterization, making it ideal for a host of graphics tasks on manifolds.MOE (Min. of Education, S’pore)Accepted versio

Heterogeneity analysis.

Heterogeneity analysis.</p

Conduction mechanism test.

Conduction mechanism test.</p