Verticillium dahliae is an important fungal pathogen affecting cotton yield and quality.Therefore,the mining of V.dahlia-resistance genes is urgently needed.Proteases and protease inhibitors play crucial roles in plan...Verticillium dahliae is an important fungal pathogen affecting cotton yield and quality.Therefore,the mining of V.dahlia-resistance genes is urgently needed.Proteases and protease inhibitors play crucial roles in plant defense responses.However,the functions and regulatory mechanisms of the protease inhibitor PR6 gene family remain largely unknown.This study provides a comprehensive analysis of the PR6 gene family in the cotton genome.We performed genome-wide identification and functional characterization of the cotton GhPR6 gene family,which belongs to the potato protease inhibitor I family of inhibitors.Thirty-nine PR6s were identified in Gossypium arboreum,G.raimondii,G.barbadense,and G.hirsutum,and they were clustered into four groups.Based on the analysis of pathogen-induced and Ghlmm transcriptome data,Gh PR6-5b was identified as the key gene for V.dahliae resistance.Virus-induced gene silencing experiments revealed that cotton was more sensitive to V.dahliae V991after PR6-5b silencing.The present study established that GhWRKY75 plays an important role in resistance to Verticillium wilt in cotton by positively regulating GhPR6-5b expression by directly binding to the W-box TTGAC(T/C).Our findings established that GhWRKY75 is a potential candidate for improving cotton resistance to V.dahliae,and provide primary information for further investigations and the development of specific strategies to bolster the defense mechanisms of cotton against V.dahliae.展开更多
Desertification in degraded grasslands is manifested through the development of bare sandy patches,which eventually lead to habitat fragmentation.The ability of these bare sandy patches to regenerate naturally through...Desertification in degraded grasslands is manifested through the development of bare sandy patches,which eventually lead to habitat fragmentation.The ability of these bare sandy patches to regenerate naturally through in-situ soil seed banks is not well understood.To fill this knowledge gap,we randomly selected 24 bare sandy patches with areas ranging from 19 to 898 m^(2) in a desertified grassland of the Horqin sandy land,Northern China to determine whether soil seed bank can be used for natural regeneration of bare sandy patches.Species composition and density of soil seed bank as well as aboveground vegetation composition,abundance and coverage were investigated.We then determined their relationships with in-situ habitat characteristics.Our observations showed that the studied area had low soil seed bank density and species richness,as well as depauperate soil seed bank communities.Consequently,local soil seed bank was not able to provide sufficient seed source for natural regeneration.This was indicated by the relationships between aboveground vegetation,soil seed bank and the in-situ habitat characteristics.For bare patches with an area between 300 m^(2) and 900 m^(2),increase the soil seed bank density and species richness should be the main restoration measures.For bare patches with a small area of less than 50 m^(2),restoration of vegetation density should be the main measure.Our data highlighted that different extents of desertification,indicated by different bare patches,are requiring distinct restoration measures.展开更多
This paper develops sequence-based methods for identifying novel protein-protein interactions （PPIs） by means of support vector machines （SVMs）. The authors encode proteins ont only in the gene level but also in t...This paper develops sequence-based methods for identifying novel protein-protein interactions （PPIs） by means of support vector machines （SVMs）. The authors encode proteins ont only in the gene level but also in the amino acid level, and design a procedure to select negative training set for dealing with the training dataset imbalance problem, i.e., the number of interacting protein pairs is scarce relative to large scale non-interacting protein pairs. The proposed methods are validated on PPIs data of Plasmodium falciparum and Escherichia coli, and yields the predictive accuracy of 93.8% and 95.3%, respectively. The functional annotation analysis and database search indicate that our novel predictions are worthy of future experimental validation. The new methods will be useful supplementary tools for the future proteomics studies.展开更多
基金supported by the National Key R&D Program of China(2022YFD1200300)the National Nature Science Youth Science Fund Project,China(31801412)+2 种基金the Key R&D Program of Shandong Province,China(2021LZGC026)the Agricultural Science and Technology Innovation Project of Shandong Academy of Agricultural Sciences,China(CXGC2023G02)the Shandong Provincial Program,China(WST2020011)。
文摘Verticillium dahliae is an important fungal pathogen affecting cotton yield and quality.Therefore,the mining of V.dahlia-resistance genes is urgently needed.Proteases and protease inhibitors play crucial roles in plant defense responses.However,the functions and regulatory mechanisms of the protease inhibitor PR6 gene family remain largely unknown.This study provides a comprehensive analysis of the PR6 gene family in the cotton genome.We performed genome-wide identification and functional characterization of the cotton GhPR6 gene family,which belongs to the potato protease inhibitor I family of inhibitors.Thirty-nine PR6s were identified in Gossypium arboreum,G.raimondii,G.barbadense,and G.hirsutum,and they were clustered into four groups.Based on the analysis of pathogen-induced and Ghlmm transcriptome data,Gh PR6-5b was identified as the key gene for V.dahliae resistance.Virus-induced gene silencing experiments revealed that cotton was more sensitive to V.dahliae V991after PR6-5b silencing.The present study established that GhWRKY75 plays an important role in resistance to Verticillium wilt in cotton by positively regulating GhPR6-5b expression by directly binding to the W-box TTGAC(T/C).Our findings established that GhWRKY75 is a potential candidate for improving cotton resistance to V.dahliae,and provide primary information for further investigations and the development of specific strategies to bolster the defense mechanisms of cotton against V.dahliae.
基金This study was supported by National Natural Science Foundation of China(41601588)Natural Science Foundation of Liaoning province(2019-MS-340)National Natural Science Foundation of China(31971732,41501573).
文摘Desertification in degraded grasslands is manifested through the development of bare sandy patches,which eventually lead to habitat fragmentation.The ability of these bare sandy patches to regenerate naturally through in-situ soil seed banks is not well understood.To fill this knowledge gap,we randomly selected 24 bare sandy patches with areas ranging from 19 to 898 m^(2) in a desertified grassland of the Horqin sandy land,Northern China to determine whether soil seed bank can be used for natural regeneration of bare sandy patches.Species composition and density of soil seed bank as well as aboveground vegetation composition,abundance and coverage were investigated.We then determined their relationships with in-situ habitat characteristics.Our observations showed that the studied area had low soil seed bank density and species richness,as well as depauperate soil seed bank communities.Consequently,local soil seed bank was not able to provide sufficient seed source for natural regeneration.This was indicated by the relationships between aboveground vegetation,soil seed bank and the in-situ habitat characteristics.For bare patches with an area between 300 m^(2) and 900 m^(2),increase the soil seed bank density and species richness should be the main restoration measures.For bare patches with a small area of less than 50 m^(2),restoration of vegetation density should be the main measure.Our data highlighted that different extents of desertification,indicated by different bare patches,are requiring distinct restoration measures.
基金This research is supported by the Key Project of the National Natural Science Foundation of China under Grant No. 10631070, the National Natural Science Foundation of China under Grant Nos. 10801112, 10971223, 11071252, and the Ph.D Graduate Start Research Foundation of Xinjiang University Funded Project under Grant No. BS080101. Thank Dr. Yong Wang from Institute of Systems Science, Academy of Mathematics and Systems Science for kind discussion and good suggestions.
文摘This paper develops sequence-based methods for identifying novel protein-protein interactions （PPIs） by means of support vector machines （SVMs）. The authors encode proteins ont only in the gene level but also in the amino acid level, and design a procedure to select negative training set for dealing with the training dataset imbalance problem, i.e., the number of interacting protein pairs is scarce relative to large scale non-interacting protein pairs. The proposed methods are validated on PPIs data of Plasmodium falciparum and Escherichia coli, and yields the predictive accuracy of 93.8% and 95.3%, respectively. The functional annotation analysis and database search indicate that our novel predictions are worthy of future experimental validation. The new methods will be useful supplementary tools for the future proteomics studies.
