Island ecosystems,serving as natural laboratories,facilitate geographical isolation,ecological specialization,and species divergence.The Sichuan Basin,surrounded by mountain ranges,represents a typical continental isl...Island ecosystems,serving as natural laboratories,facilitate geographical isolation,ecological specialization,and species divergence.The Sichuan Basin,surrounded by mountain ranges,represents a typical continental island due to its marked environmental spatial heterogeneity.This heterogeneity may contribute to geographical isolation and habitat heterogeneity,resulting in genetic divergence within populations.Therefore,we used the White-browed Laughingthrush(Garrulax sannio)as a model specimen to investigate the genetic divergence in the Sichuan Basin and its surrounding mountain ranges,given its presence in various habitats within and beyond this basin.Employing a RAD-seq dataset of 140 G.sannio individuals from 17 distinct ecological zones in the Sichuan Basin and its surrounding mountain ranges,we conducted PCA,population structure analysis,phylogenetic tree construction,and gene flow analysis to comprehensively analyze G.sannio groups.Additionally,in conjunction with geographical and ecological data,we performed isolation by distance,isolation by environment,PCA,and latent factor mixed model analysis to identify factors influencing the genetic divergence among these G.sannio groups.In summary,the 17 G.sannio groups were categorized into high-elevation,medium-elevation,and lowelevation groups.Genetic divergence in G.sannio may be attributed to both geographical distance and key ecological factors,particularly elevation and key climatic variables.Notably,the high-elevation group exhibited a greater number of SNPs and selected genes associated with the key ecological factors compared to the lowelevation group.The ADCY9 gene and several associated key pathways were identified as crucial elements driving ecological adaptation(elevation and key climatic variables)in the high-elevation group.Furthermore,climate changes during the glacial cycles may have facilitated gene flow among these groups residing in the Sichuan Basin and its surrounding mountain ranges.Our findings provide evidence of genetic divergence in G.sannio influenced by the geographical distance and key ecological factors between the Sichuan Basin and its surrounding mountain ranges.These results lay the groundwork for future research on the molecular systematics of continental islands.展开更多
As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their cu...As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their customer resources,it is crucial for banks to accurately predict customers with a tendency to churn.Aiming at the typical binary classification problem like customer churn,this paper establishes an early-warning model for credit card customer churn.That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm(GSA)and an Improved Beetle Antennae Search(IBAS)is proposed to optimize the parameters of the CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.展开更多
In higher plants, WRKY gene family plays a significant role in transcriptional regulation. They are widely involved in biotic stress, abiotic stress, growth, development and metabolism regulation. In this study WRKY6 ...In higher plants, WRKY gene family plays a significant role in transcriptional regulation. They are widely involved in biotic stress, abiotic stress, growth, development and metabolism regulation. In this study WRKY6 from tobacco is cloned by homology cloning. 1647 nucleotide sequences were obtained. The deduced protein sequences show that this protein belongs to the second group of WRKY family, only have one WRKY structure, and the zinc-finger structure is C-X4-C-X23-H-X1-H. Phylogeny results show NtWRKY6 is much closer to NtWRKY1 generated 97% amino acids similarity. RT-PCR analysis has revealed that expression levels of NtWRKY6 has increased rapidly at 3 h under NaCI and PEG treatment. The results suggest that NtWRKY6 is an early responder and may be involved in NaCl and PEG abiotic stress in tobacco.展开更多
基金supported by the National Science Foundation of China(31372171)Leshan Normal University research grants(205210094,ZZ201805,CGZZ202002,205220114,DGZZ202006).
文摘Island ecosystems,serving as natural laboratories,facilitate geographical isolation,ecological specialization,and species divergence.The Sichuan Basin,surrounded by mountain ranges,represents a typical continental island due to its marked environmental spatial heterogeneity.This heterogeneity may contribute to geographical isolation and habitat heterogeneity,resulting in genetic divergence within populations.Therefore,we used the White-browed Laughingthrush(Garrulax sannio)as a model specimen to investigate the genetic divergence in the Sichuan Basin and its surrounding mountain ranges,given its presence in various habitats within and beyond this basin.Employing a RAD-seq dataset of 140 G.sannio individuals from 17 distinct ecological zones in the Sichuan Basin and its surrounding mountain ranges,we conducted PCA,population structure analysis,phylogenetic tree construction,and gene flow analysis to comprehensively analyze G.sannio groups.Additionally,in conjunction with geographical and ecological data,we performed isolation by distance,isolation by environment,PCA,and latent factor mixed model analysis to identify factors influencing the genetic divergence among these G.sannio groups.In summary,the 17 G.sannio groups were categorized into high-elevation,medium-elevation,and lowelevation groups.Genetic divergence in G.sannio may be attributed to both geographical distance and key ecological factors,particularly elevation and key climatic variables.Notably,the high-elevation group exhibited a greater number of SNPs and selected genes associated with the key ecological factors compared to the lowelevation group.The ADCY9 gene and several associated key pathways were identified as crucial elements driving ecological adaptation(elevation and key climatic variables)in the high-elevation group.Furthermore,climate changes during the glacial cycles may have facilitated gene flow among these groups residing in the Sichuan Basin and its surrounding mountain ranges.Our findings provide evidence of genetic divergence in G.sannio influenced by the geographical distance and key ecological factors between the Sichuan Basin and its surrounding mountain ranges.These results lay the groundwork for future research on the molecular systematics of continental islands.
基金This work is supported by the National Natural Science Foundation of China(Nos.72071150,71871174).
文摘As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their customer resources,it is crucial for banks to accurately predict customers with a tendency to churn.Aiming at the typical binary classification problem like customer churn,this paper establishes an early-warning model for credit card customer churn.That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm(GSA)and an Improved Beetle Antennae Search(IBAS)is proposed to optimize the parameters of the CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.
文摘In higher plants, WRKY gene family plays a significant role in transcriptional regulation. They are widely involved in biotic stress, abiotic stress, growth, development and metabolism regulation. In this study WRKY6 from tobacco is cloned by homology cloning. 1647 nucleotide sequences were obtained. The deduced protein sequences show that this protein belongs to the second group of WRKY family, only have one WRKY structure, and the zinc-finger structure is C-X4-C-X23-H-X1-H. Phylogeny results show NtWRKY6 is much closer to NtWRKY1 generated 97% amino acids similarity. RT-PCR analysis has revealed that expression levels of NtWRKY6 has increased rapidly at 3 h under NaCI and PEG treatment. The results suggest that NtWRKY6 is an early responder and may be involved in NaCl and PEG abiotic stress in tobacco.
