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Rockburst is a complex dynamic disaster in coal mining and affected by many factors. To accurately predict the rockburst hazard among complex influencing factors, a prediction model of rockburst hazard based on the Gaussian process for binary classification (GPC) was proposed after the identification of the intrinsic relationship between multiple factors of coal mines and rockburst. Through computerized machine learning and integrated intelligent analysis, the non-linear mapping of rockburst hazard and its influencing factors was established. The multi-factor pattern recognition model was constructed using artificial intelligence. The prediction criteria of the rockburst hazard probability and the hazard probability value of the prediction area unit were determined by applying neural network and fuzzy inference methods. In addition, the rockburst hazardous zone was classified, and the corresponding technical scheme for the prevention was put forward. The validity and feasibility of the regional prediction of rockburst hazard based on GPC were verified in the engineering practice. This method is highly targeted and can improve the accuracy and precision of rockburst prediction, thus contributing to the safe and efficient production of coal mines.

As one of the most serious shock dynamic disasters in coal mining, rock burst only occurs under the certain geodynamic environment. Geodynamic is the necessary requirement for the occurrence of rock burst, and the disturbance of mining engineering is the sufficient requirement. In terms of the fault structure, the method of geodynamic zoning is used to classify fault structure forms of rock burst in mines, and a model of geological structure is established to reveal the connection between fault structure and mine engineering. Besides, the influence of fault structure on rock burst is analyzed, and the controlling mechanism of the fault structure on the tectonic evolution of the mine area and the occurrence of rock burst is revealed. This research provides a treatment plan for the prediction and prevention of rock burst and guides the safe production in the coal mining engineering.

Diverse pathogen effectors convergently target conserved components in plant immunity guarded by intracellular nucleotide-binding domain leucine-rich repeat receptors (NLRs) and activate effector-triggered immunity (ETI), often causing cell death. Little is known of the differences underlying ETI in different plants triggered by the same effector. In this study, we demonstrated that effector RipAW triggers ETI on Nicotiana benthamiana and Nicotiana tabacum. Both the first 107 amino acids (N1-107) and RipAW E3-ligase activity are required but not sufficient for triggering ETI on N. benthamiana. However, on N. tabacum, the N1-107 fragment is essential and sufficient for inducing cell death. The first 60 amino acids of the protein are not essential for RipAW-triggered cell death on either N. benthamiana or N. tabacum. Furthermore, simultaneous mutation of both R75 and R78 disrupts RipAW-triggered ETI on N. tabacum, but not on N. benthamiana. In addition, N. tabacum recognizes more RipAW orthologs than N. benthamiana. These data showcase the commonalities and specificities of RipAW-activated ETI in two evolutionally related species, suggesting Nicotiana species have acquired different abilities to perceive RipAW and activate plant defences during plant–pathogen co-evolution., This work was funded by the Nature Science Basic Research Plan of Shaanxi Province (2020JM-160), the Special Research project from Shaanxi province (F2020221001), the Program of Introducing Talents of Innovative Discipline to Universities (Project 111) from the State administration of Foreign Experts Affairs (B18042) and the External Science and Technology Cooperation Program of Ningxia Academy of Agriculture and Forestry Sciences (DW-X-2018012), the Start-up Funds of Northwest A&F University (Z111021601), the Fundamental Research Fund for the Central Universities of China (Z109021706), the Key Research and Development plan of Ningxia Province (2021BEF02033), and the National Natural Science Foundation of China for C.Z. (31901573).

Background Variant calling and refinement from whole genome/exome sequencing data is a fundamental task for genomics studies. Due to the limited accuracy of NGS sequencing and variant callers, IGV-based manual review is required for further false positive variant filtering, which costs massive labor and time, and results in high inter- and intra-lab variability. Results To overcome the limitation of manual review, we developed a novel approach for Variant Filter by Automated Scoring based on Tagged-signature (VariFAST), and also provided a pipeline integrating GATK Best Practices with VariFAST, which can be easily used for high quality variants detection from raw data. Using the bam and vcf files, VariFAST calculates a v-score by sum of weighted metrics causing false positive variations, and marks tags in the manner of keeping high consistency with manual review, for each variant. We validated the performance of VariFAST for germline variant filtering using the benchmark sequencing data from GIAB, and also for somatic variant filtering using sequencing data of both malignant carcinoma and benign adenomas as well. VariFAST also includes a predictive model trained by XGBOOST algorithm for germline variants refinement, which reveals better MCC and AUC than the state-of-the-art VQSR, especially outcompete in INDEL variant filtering. Conclusion VariFAST can assist researchers efficiently and conveniently to filter the false positive variants, including both germline and somatic ones, in NGS data analysis. The VariFAST source code and the pipeline integrating with GATK Best Practices are available at https://github.com/bioxsjtu/VariFAST.

Simple Summary Phospholipase D is the most important kind of phospholipase in plants, which can specifically catalyze the hydrolysis of phosphodiester bonds at the end of phospholipid molecules to produce phospholipid acid and a free group. Phospholipase D is not only involved in maintaining the structural stability of plant cell membrane and the dynamic balance of lipid composition but also involved in a variety of physiological processes, such as plant growth and development and stress response, including stomatal closure, root elongation, cell senescence, high salt stress, cold stress, and drought stress. It plays a critical role in plant growth and development, as well as in hormone and stress responses. In this study, the basic information on phospholipase D gene family was comprehensively introduced, and the physical and chemical properties, systematic evolution, gene structure, conservative motif, chromosome location, gene replication, cis-acting element prediction, GO annotation, interspecific collinearity, and quantitative analysis of potato phospholipase D gene family were analyzed to gain a better understanding of potato phospholipase D gene family. Through the analysis of potato phospholipase D gene family, our results lay the foundation for further understanding of the function of phospholipase gene family in higher plants. Abstract Phospholipase D (PLD) is the most important phospholipid hydrolase in plants, which can hydrolyze phospholipids into phosphatidic acid (PA) and choline. When plants encounter low temperature, drought and high salt stress, phospholipase D and its products play an important role in regulating plant growth and development and coping with stress. In this study, 16 members of StPLD gene family were identified in potato genome, which were distributed in α, β, δ, and ζ subfamilies, and their expression patterns under salt, high temperature, drought, and ABA stress were detected by qRT-PCR method. Gene expression analysis showed that the expression of StPLD genes in potato was upregulated and downregulated to varying degrees under the four stresses, indicating that the PLD gene family is involved in the interaction of potato plant hormones and abiotic stress signals. Chromosome distribution showed that StPLD gene was unevenly distributed on 8 chromosomes, and only one pair of tandem repeat genes was found. All StPLD promoters contain hormone and stress-related cis-regulatory elements to respond to different stresses. Structural analysis showed that StPLD genes in the same subgroup had a similar exon–intron structure. Our study provides a valuable reference for further research of the function and structure of PLD gene.

Background Next-generation sequencing technology is developing rapidly and target capture sequencing has become an important technique. Several different platforms for library preparation and target capture with different bait types respectively are commercially available. Here we compare the performance of the four platforms with different bait types to find out their advantages and limitations. The purpose of this study is to help investigators and clinicians select the appropriate platform for their particular application and lay the foundation for the development of a better target capture platform for next-generation sequencing. Results We formulate capture efficiency as a novel parameter that can be used to better evaluations of specificity and coverage depth among the different capture platforms. Target coverage, capture efficiency, GC bias, AT Dropout, sensitivity in single nucleotide polymorphisms, small insertions and deletions detection, and the feature of each platform were compared for low input samples. In general, all platforms perform well and small differences among them are revealed. In our results, RNA baits have stronger binding power than DNA baits, and with ultra deep sequencing, double stranded RNA baits perform better than single stranded RNA baits in all aspects. DNA baits got better performance in the region with high GC content and RNA baits got lower AT dropout suggesting that the binding power is different between DNA and RNA baits to genome regions with different characteristics. Conclusions The platforms with double stranded RNA baits have the most balanced capture performance. Our results show the key differences in performance among the four updated platforms with four different bait types. The better performance of double stranded RNA bait with ultra deep sequencing suggests that it may improve the sensitivity of ultra low frequent mutation detection. In addition, we further propose that the mixed baits of double stranded RNA and single stranded DNA may improve target capture performance.

Background Potato, the third most important crop worldwide, plays a critical role in human food security. Brown rot, one of the most destructive potato diseases caused by Ralstonia solanacearum, results in huge economic losses every year. A quick, stable, low cost and high throughout method is required to meet the demands of identification of germplasm resistance to bacterial wilt in potato breeding programs. Results Here we present a novel R. solanacearum hydroponic infection assay on potato plants grown in vitro. Through testing wilt symptom appearance and bacterial colonization in aerial part of plants, we found that the optimum conditions for in vitro potato infection were using an OD600 0.01 bacterial solution suspended with tap water for infection, broken potato roots and an open container. Infection using R. solanacearum strains with differential degree of aggressivity demonstrated that this infection system is equally efficient as soil-drench inoculation for assessment of R. solanacearum virulence on potato. A small-scale assessment of 32 potato germplasms identified three varieties highly resistant to the pathogen, which indicates this infection system is a useful method for high-throughout screening of potato germplasm for resistance. Furthermore, we demonstrate the utility of a strain carrying luminescence to easily quantify bacterial colonization and the detection of latent infections in hydroponic conditions, which can be efficiently used in potato breeding programs. Conclusions We have established a quick and efficient in vitro potato infection system, which may facilitate breeding for new potato cultivars with high resistance to R. solanacearum.

Alternative splicing (AS) is an important mechanism by which eukaryotes regulate transcription and protein diversity. The dynamic changes in AS that occur on a genome-wide scale during interactions between plant roots and pathogens remain unknown. Here, we used the interaction between Arabidopsis and Ralstonia solanacearum as a model to explore the AS changes that take place during the response of roots to infection by means of high-throughput RNA-sequencing. We showed that dynamic changes in AS occur much earlier than changes at the level of transcription during R.solanacearum infection. Comparing genes that are regulated at the transcriptional and AS levels indicated that there are few common genes between differentially spliced genes (DSGs) and differentially expressed genes (DEGs). The functional gene ontology (GO) analysis identified that the enriched GO terms for the DSGs were different from those of the DEGs. The DSGs were over-represented in GO terms associated with post-transcriptional and translational regulations, suggesting that AS may act on RNA stability and during post-translation, thus affecting the output of plant defense molecules. Meanwhile, changes in DSGs were infection stage-specific. Furthermore, the nucleotide binding domain and leucine-rich repeat proteins and receptor-like kinases, key regulators in plant immunity, were shown to undergo dynamic changes in AS in response to R. solanacearum. Taken together, AS, along with transcription, modulates plant root defense to R. solanacearum through transcriptome reprogramming.

[Background]: Potato, the third most important crop worldwide, plays a critical role in human food security. Brown rot, one of the most destructive potato diseases caused by Ralstonia solanacearum, results in huge economic losses every year. A quick, stable, low cost and high throughout method is required to meet the demands of identification of germplasm resistance to bacterial wilt in potato breeding programs., [Results]: Here we present a novel R. solanacearum hydroponic infection assay on potato plants grown in vitro. Through testing wilt symptom appearance and bacterial colonization in aerial part of plants, we found that the optimum conditions for in vitro potato infection were using an OD600 0.01 bacterial solution suspended with tap water for infection, broken potato roots and an open container. Infection using R. solanacearum strains with differential degree of aggressivity demonstrated that this infection system is equally efficient as soil-drench inoculation for assessment of R. solanacearum virulence on potato. A small-scale assessment of 32 potato germplasms identified three varieties highly resistant to the pathogen, which indicates this infection system is a useful method for high-throughout screening of potato germplasm for resistance. Furthermore, we demonstrate the utility of a strain carrying luminescence to easily quantify bacterial colonization and the detection of latent infections in hydroponic conditions, which can be efficiently used in potato breeding programs., [Conclusions]: We have established a quick and efficient in vitro potato infection system, which may facilitate breeding for new potato cultivars with high resistance to R. solanacearum., This study was supported by the National Natural Science Foundation of China (No. 31601703), the Start-up Funds of Northwest A&F University (Z111021601), the Fundamental Research Fund for the Central Universities of China (Z109021706) and External Science and Technology Cooperation Program of Ningxia Academy of Agriculture and Forestry Sciences (DW-X-2018012). N.S.C. and M.V. work was funded by projects AGL2016-78002-R. (Spanish Ministry of Economy and Competitiveness) and financial support from the “Severo Ochoa Programme for Centres of Excellence in R&D” (SEV‐2015‐0533) and the CERCA Programme from the Catalan Government (Generalitat de Catalunya).

Background Lung cancer is one of the leading causes of cancer death worldwide, and genetic risk factors account for a large part of its carcinogenesis. The low economic requirements and high efficiency of next-generation sequencing (NGS) make it widely used in detecting genetic alterations in pathogenesis. Methods We performed targeted panel sequencing in 780 Han Chinese lung cancer patients using a commercial probe, and the correlations between dozens of susceptible sites were verified in 1113 healthy controls. This study used Fisher's exact test and Benjamini-Hochberg FDR correction to analyze the mutual exclusion between mutated genes, and Pearson's p was used to verify the correlations between mutations and lung cancer susceptibility. Results Our results determined the mutation spectrum and showed that each lung cancer patient carried at least one DNA mutation. The most frequently mutated gene was BRCA2 (mutation rate,10.6 %.). The co-occurrence and mutual exclusion analysis of DNA damage related genes showed that gene ATM was mutually exclusive from MSH6. We conducted a further case-control study in different subtypes of lung cancer and the results described 14 mutations associated with adenocarcinoma, 9 with squamous cell carcinoma, and 4 with small cell lung cancer. These variants were novel de-novo germline mutations in lung cancer. Particularly, rs3864017 in FANCD2 showed a protective effect of lung adenocarcinoma for carriers (OR = 0.146, 95 % CI = 0.052∼0.405, Padjusted = 3.37 × 10−4). Conclusions 18 candidate mutations might alter the risk of lung cancer in the Han Chinese population, including polymorphisms rs3864017(FANCD2), rs55740729(MSH6) and 16 rare variants. The underlying mechanisms of candidate genes in lung cancer remain unclear and we suggest more functional studies on exploring how these genes affect the risk of lung cancer.

Neuromedin U 2 receptor (NMU2R) plays important roles for the regulation of food intake and body weight. However, the molecular mechanism underlying the action of NMU2R has not been clearly defined. We have taken chemical genetic approach to examine the involvement of peptides in the regulation of NMU2R effects. A cell-based reporter gene assay has been developed and used for the screening of human NMU2R agonist. Three natural product compounds, EUK2010, EUK2011 and EUK2012, were identified that could activate the reporter gene expression in the cell-based functional assay. Although these compounds showed high EC50 at hundreds micro-molar range, in vitro pharmacological analysis suggested that they were specific agonists for the human NMU2R. The natural compounds could decrease food intake and lead to the reduction of body weight in different animal models. To understand the molecular basis of the NMU2R regulation of food intake and body weight, we examined the expression of a number of key genes in hypothalamus and adipose tissues after oral administration of EUK2010 in mice. Our results demonstrated that the expression levels of a number of neuropeptide genes were altered after the treatment of EUK2010. Interestingly, EUK2010 increased the expression of Leptin in white fat. These results suggested that these peptides may participate in the regulation of NMU2R effects in mice.