Chromosome-scale de novo genome assembly and annotation of three representative Casuarina species: C. equisetifolia, C. glauca, and C. cunninghamiana.

Australian pine (Casuarina spp.) is extensively planted in tropical and subtropical regions for wood production, shelterbelts, environmental protection, and ecological restoration due to their superior biological characteristics, such as rapid growth, wind and salt tolerance, and nitrogen fixation. To analyze the genomic diversity of Casuarina, we sequenced the genomes and constructed de novo genome assemblies of the three most widely planted Casuarina species: C. equisetifolia, C. glauca, and C. cunninghamiana. We generated chromosome-scale genome sequences using both Pacific Biosciences (PacBio) Sequel sequencing and chromosome conformation capture technology (Hi-C). The total genome sizes for C. equisetifolia, C. glauca, and C. cunninghamiana are 268 942 579 bp, 296 631 783 bp, and 293 483 606 bp, respectively, of which 25.91, 27.15, and 27.74% were annotated as repetitive sequences. We annotated 23 162, 24 673, and 24 674 protein-coding genes in C. equisetifolia, C. glauca, and C. cunninghamiana, respectively. We then collected branchlets from male and female individuals for whole-genome bisulfite sequencing (BS-seq) to explore the epigenetic regulation of sex determination in these three species. Transcriptome sequencing (RNA-seq) revealed differential expression of phytohormone-related genes between male and female plants. In summary, we generated three chromosome-level genome assemblies and comprehensive DNA methylation and transcriptome datasets from both male and female material for three Casuarina species, providing a basis for the comprehensive investigation of genomic diversity and functional gene discovery of Casuarina in the future.

De novo genome assembly of the stress tolerant forest species Casuarina equisetifolia provides insight into secondary growth.

Casuarina equisetifolia (C. equisetifolia), a conifer-like angiosperm with resistance to typhoon and stress tolerance, is mainly cultivated in the coastal areas of Australasia. C. equisetifolia, making it a valuable model to study secondary growth associated genes and stress-tolerance traits. However, the genome sequence is unavailable and therefore wood-associated growth rate and stress resistance at the molecular level is largely unexplored. We therefore constructed a high-quality draft genome sequence of C. equisetifolia by a combination of Illumina second-generation sequencing reads and Pacific Biosciences single-molecule real-time (SMRT) long reads to advance the investigation of this species. Here, we report the genome assembly, which contains approximately 300 megabases (Mb) and scaffold size of N50 is 1.06 Mb. Additionally, gene annotation, assisted by a combination of prediction and RNA-seq data, generated 29 827 annotated protein-coding genes and 1983 non-coding genes, respectively. Furthermore, we found that the total number of repetitive sequences account for one-third of the genome assembly. Here we also construct the genome-wide map of DNA modification, such as two novel forms N6 -adenine (6mA) and N4-methylcytosine (4mC) at the level of single-nucleotide resolution using single-molecule real-time (SMRT) sequencing. Interestingly, we found that 17% of 6mA modification genes and 15% of 4mC modification genes also included alternative splicing events. Finally, we investigated cellulose, hemicellulose, and lignin-related genes, which were associated with secondary growth and contained different DNA modifications. The high-quality genome sequence and annotation of C. equisetifolia in this study provide a valuable resource to strengthen our understanding of the diverse traits of trees.

Structural characteristics in network control of molecular multiplex networks.

Numerous real-world systems can be naturally modeled as multilayer networks, providing an efficient tool to characterize these complex systems. Although recent progress in understanding the controlling of synthetic multiplex networks, how to control real multilayer systems remains poorly understood. Here, we explore the controllability and energy requirement of molecular multiplex networks coupled by transcriptional regulatory network (TRN) and protein-protein interaction (PPI) network from the perspective of network structural characteristics. Our findings reveal that the driver nodes tend to avoid essential or pathogen-related genes. However, imposing external inputs on these essential or pathogen-related genes can remarkably reduce the energy cost, implying their crucial role in network control. Moreover, we find that the minimal driver nodes, as well as the energy required, are associated with disassortative coupling between TRN and PPI networks. Our results provide a comprehensive understanding of the roles of genes in biology and network control across several species.

UV-fluorescence imaging for real-time non-destructive monitoring of pork freshness.

This study aimed to develop a cost-effective fluorescence imaging system to rapidly monitor pork freshness indicators during chilled storage. The system acquired fluorescence images of pork and the color features were extracted from these images to establish partial least squares regression (PLSR) models to predict total volatile basic nitrogen (TVB-N), total viable count (TVC), pH for pork. For TVB-N, TVC and pH values, Rp were 0.92, 0.88 and 0.74, residual predictive deviation (RPD) were 2.24, 2.03, and 1.19, respectively. For TVB-N and TVC indicators showed that the predictive ability of this model was largely comparable to that of fluorescence hyperspectral imaging. However, combining fluorescence and color imaging improved the model's predictive ability. For TVB-N, TVC and pH, Rp were 0.94, 0.93 and 0.85, RPD were 2.62, 2.59, and 1.95, respectively. Therefore, this study developed a system with great potential for detecting the value of most pork quality indicators in real-time.

[Carbon balance in an interplanting Pinus massoniana stand in subtropical eroded red soil region, China.] / 亚热带红壤侵蚀区马尾松不同套种模式生态系统碳平衡.

We measured the annual net biomass growth, carbon content of each component and soil heterotrophic respiration in four low-efficiency interplanting patterns, i.e., Pinus massoniana stands interplanting Myrica rubra, Sapindus mukurossi, Camellia oleifera and Gardenia jasminoides in Changting County, Fujian Province, with the aim to analyze the effects of interplanting patterns on carbon storage pattern and carbon balance of low-efficiency P. massoniana stand. The ranges of carbon content in different organs of M. rubra, S. mukurossi, C. oleifera, G. jasminoides and P. massoniana were 41.1%-50.1%, 42.2%-50.6%, 45.1%-48.9%, 44.7%-49.6% and 46.1%-51.9%, respectively. Carbon content of the same organ significantly differed among tree species. The pattern of P. massoniana interplanting M. rubra and S. mukurossi had the highest carbon stock and annual net carbon increase reserves, with values of 67.62-68.42 t·hm-2 and 9.21-9.45 t·hm-2·a-1, respectively. Followed by the lower pattern of C. oleifera, G. jasminoides, with values of 31.96-36.24 t·hm-2 and 4.09-4.16 t·hm-2·a-1, respectively. The P. massoniana pure forest was the lowest, with values of 17.01 t·hm-2 and 2.00 t·hm-2·a-1, respectively. Annual flux of soil heterotrophic respiration was following the order of P. massoniana interplanting M. rubra pattern (7.41 t·hm-2·a-1) > P. massoniana interplanting C. oleifera pattern (5.89 t·hm-2·a-1)> P. massoniana interplanting S. mukurossi pattern (5.86 t·hm-2·a-1) > P. massoniana interplanting G. jasminoides pattern (4.95 t·hm-2·a-1) > P. massoniana pure forest (2.45 t·hm-2·a-1). Annual net ecosystem carbon balance of P. massoniana interplanting M. rubra and S. mukurossi patterns were 2.04 and 3.27 t C·hm-2·a-1, showing a "carbon sink" pattern. The net carbon balance in the patterns of P. massoniana interplanting C. oleifera and G. jasminoides along with P. massoniana pure forest were -1.80, -0.80 and -0.45 t C·hm-2·a-1, which expressed a "carbon source" pattern. In the short-term, interplanting with M. rubra or S. mukurossi could improve the carbon income of the low-efficiency P. massoniana stand ecosystem.

Control energy of complex networks towards distinct mixture states.

Controlling complex networked systems is a real-world puzzle that remains largely unsolved. Despite recent progress in understanding the structural characteristics of network control energy, target state and system dynamics have not been explored. We examine how varying the final state mixture affects the control energy of canonical and conformity-incorporated dynamical systems. We find that the control energy required to drive a network to an identical final state is lower than that required to arrive a non-identical final state. We also demonstrate that it is easier to achieve full control in a conformity-based dynamical network. Finally we determine the optimal control strategy in terms of the network hierarchical structure. Our work offers a realistic understanding of the control energy within the final state mixture and sheds light on controlling complex systems.

Effect of correlations on controllability transition in network control.

The network control problem has recently attracted an increasing amount of attention, owing to concerns including the avoidance of cascading failures of power-grids and the management of ecological networks. It has been proven that numerical control can be achieved if the number of control inputs exceeds a certain transition point. In the present study, we investigate the effect of degree correlation on the numerical controllability in networks whose topological structures are reconstructed from both real and modeling systems, and we find that the transition point of the number of control inputs depends strongly on the degree correlation in both undirected and directed networks with moderately sparse links. More interestingly, the effect of the degree correlation on the transition point cannot be observed in dense networks for numerical controllability, which contrasts with the corresponding result for structural controllability. In particular, for directed random networks and scale-free networks, the influence of the degree correlation is determined by the types of correlations. Our approach provides an understanding of control problems in complex sparse networks.

Dependency links can hinder the evolution of cooperation in the prisoner's dilemma game on lattices and networks.

Networks with dependency links are more vulnerable when facing the attacks. Recent research also has demonstrated that the interdependent groups support the spreading of cooperation. We study the prisoner's dilemma games on spatial networks with dependency links, in which a fraction of individual pairs is selected to depend on each other. The dependency individuals can gain an extra payoff whose value is between the payoff of mutual cooperation and the value of temptation to defect. Thus, this mechanism reflects that the dependency relation is stronger than the relation of ordinary mutual cooperation, but it is not large enough to cause the defection of the dependency pair. We show that the dependence of individuals hinders, promotes and never affects the cooperation on regular ring networks, square lattice, random and scale-free networks, respectively. The results for the square lattice and regular ring networks are demonstrated by the pair approximation.

Robustness of controllability for networks based on edge-attack.

We study the controllability of networks in the process of cascading failures under two different attacking strategies, random and intentional attack, respectively. For the highest-load edge attack, it is found that the controllability of Erdos-Rényi network, that with moderate average degree, is less robust, whereas the Scale-free network with moderate power-law exponent shows strong robustness of controllability under the same attack strategy. The vulnerability of controllability under random and intentional attacks behave differently with the increasing of removal fraction, especially, we find that the robustness of control has important role in cascades for large removal fraction. The simulation results show that for Scale-free networks with various power-law exponents, the network has larger scale of cascades do not mean that there will be more increments of driver nodes. Meanwhile, the number of driver nodes in cascading failures is also related to the edges amount in strongly connected components.