Viridiplantae
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB20739 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Climate change forecasts increase the susceptibility of forest due to longer drier seasons. The adaptive management protocols have highlighted the reduction of the forest densification to improve their vulnerability to extreme climate events (i.g. drought). One of this sensitive woody species to climate change is the Abies pinsapo, a relic conifer tree endemic from the southern Spain. Previous works have shown changes in their trends because of the climate change action, being carried out experimental thinning management in their lowest distribution limit, in Sierra de las Nieves Natural Park (Malaga). Our objective is to evaluate the water improvements of thinned trees in terms of light availability by means of a shading treatment in those thinned trees. To do that we have evaluated the synergic effect of ecophysiology, metabolomics and transcriptomics in control, thinning and thinning+shading plots in wet and dry seasons for two years. The results showed strong differences between summer and spring seasons at the three studied levels. The water deficit shows a greater influence than light exposure in the ecophysiology and metabolomics tree response. And the transcriptomics suggested an improvement of thinned trees when light exposure was reduced. Our results support the necessity of adaptive forest management in order to improve the conservation status of A. pinsapo forest. The combination of different levels of tree response is paramount to understand and predict the tree physiology under water and light stress conditions.
2022-07-17 | GSE208073 | GEO
Project description:Deadwood plays a crucial role in forest ecosystems, but we have limited information about the specific fungal taxa and extracellular lignocellulolytic enzymes that are actively involved in the decomposition process in situ. To investigate this, we studied the fungal metaproteome of twelve deadwood tree species in a replicated, eight-year experiment. Key fungi observed included genera of white-rot fungi (Basidiomycota, e.g. Armillaria, Hypholoma, Mycena, Ischnoderma, Resinicium), brown-rot fungi (Basidiomycota, e.g. Fomitopsis, Antrodia), diverse Ascomycota including xylariacous soft-rot fungi (e.g. Xylaria, Annulohypoxylon, Nemania) and various wood-associated endophytes and saprotrophs (Ascocoryne, Trichoderma, Talaromyces). These fungi used a whole range of extracellular lignocellulolytic enzymes, such as peroxidases, peroxide-producing enzymes, laccases, cellulases, glucosidases, hemicellulases (xylanases) and lytic polysaccharide monooxygenases (LPMOs). Both the fungi and enzymes were tree-specific, with specialists and generalists being distinguished by network analysis. The extracellular enzymatic system was highly redundant, with many enzyme classes of different origins present simultaneously in all decaying logs. Strong correlations were found between peroxide-producing enzymes (oxidases) and peroxidases as well as LPMOs, and between ligninolytic, cellulolytic and hemicellulolytic enzymes. The overall protein abundance of lignocellulolytic enzymes was reduced by up to -30% in gymnosperm logs compared to angiosperm logs, and gymnosperms lacked ascomycetous enzymes, which may have contributed to the lower decomposition of gymnosperm wood. In summary, we have obtained a comprehensive and detailed insight into the enzymatic machinery of wood-inhabiting fungi in several temperate forest tree species, which can help to improve our understanding of the complex ecological processes in forest ecosystems.
2024-04-22 | PXD041962 | Pride
Project description:The dataset comprises the most abundant and largest (by stem diameter) tree species in the Barro Colorado Island 50-ha forest dynamics plot in Panama, as well as all local species in 7 of the most species-rich genera in the plot: Eugenia (Myrtaceae), Inga (Moraceae), Miconia/Clidemia (Melastomataceae), Ocotea/Nectandra (Lauraceae), Piper (Piperaceae), Protium (Burseraceae), Psychotria/Palicourea (Rubiaceae). Leaf samples were extracted with 90:10 methanol:water pH 5 and analyzed using methods described in Sedio et al. 2017 Applications in Plant Sciences (doi:10.1002/aps3.1033).
2019-12-09 | MSV000084666 | MassIVE
Project description:Biotic and abiotic stresses are predicted to be the main drivers of forest tree decline and mortality in a climatic change scenario. It occurs, for example, in Quercus ilex, the main component of the Mediterranean forest, becoming a major environmental, economic and social concern. The decline syndrome is the result of factors interrelated in time and space. Breeding, through variability and elite genotype selection, is the only plausible strategy for forest management and conservation in nondomesticated, orphan species as is the case of the genus Quercus. By using a shotgun proteomics approach, the effect and the responses to combined drought stress and pathogen (Phytophthora cinnamomi) have been analyzed in two Holm oak populations with contrasting responses to each individual stress. Proteomics data are correlated with that of plant survival, damage symptoms, leaf chemical composition and physiological phenotypes (water content and photosynthetic activity). Changes in the protein profile depended on the population, stress, and time, with some consistent upaccumulated proteins related to synthesis, primary and secondary metabolism, and cell wall are discussed.
2021-08-18 | PXD025704 | Pride
Project description:Purpose: The goal of this study is to evaluate transcriptional regulation of the accumulation of phenols and anthocyanins in young leaves of subtropical forest tree species by using NGS-derived RNA-seq. Methods: Leaf mRNA profiles of subtropical tree Schima superba and Cryptocarya concinna grown under contasting light were generated by deep sequencing, in triplicate, using Illumina. The sequence reads that passed quality filters were analyzed at the transcript isoform level with TopHat followed by Cufflinks. FPKM produced by RSEM are provided. Results: Assemblies of the sequence data yielded 61,618 and 64,413 unigenes for Schima superba and Cryptocarya concinna,respectively. Overall,75.14% and 66.46% of the unigenes were annotated in the protein database Nonredundant protein (Nr), Nonredundant nucleotide (Nt), Swiss-Prot、Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups of proteins (COG) and Gene Ontology (GO) for S. superba and C concinna,respectively.A total of 3896, 3488 and 266 genes were differentially expressed in full light-exposed young leaf (FLY), low light-exposed young leaf (LYL) and low light-exposed mature leaf (LML) relative to low light-exposed mature leaf (FML) of S. superba, respectively, and 2097, 2047 and 211 genes were differentially expressed in the corresponding leaves of C. concinna. Conclusions: Our study represents the first detailed analysis of transcriptomes in young and mature leaves of dorminant trees from a subtropical forest in China, with biologic replicates, generated by RNA-seq technology. Photosynthesis-related genes and phenol pathways-related genes were extensively down- and up-regulated in young versus mature leaves of the two species.
2018-10-01 | GSE104004 | GEO
Project description:Background:
To assist clinicians with diagnosis and optimal treatment decision-making, we attempted to develop and validate an artificial intelligence prediction model for lung metastasis (LM) in colorectal cancer (CRC) patients.
Method:
The clinicopathological characteristics of 46037 CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 2779 CRC patients from a multi-center external validation set were collected retrospectively. After feature selection by univariate and multivariate analyses, six machine learning (ML) models, including logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest, and balanced random forest (BRF), were developed and validated for the LM prediction. The optimization model with best performance was compared to the clinical predictor. In addition, stratified LM patients by risk score were utilized for survival analysis.
| 46649 | ecrin-mdr-crc
Project description:Castanopsis fissa is an evergreen broad-leaved species of the cone genus Castanopsis in the family Fagaceae, which is widely distributed and is an excellent native species in Guangdong Province of China. This species has a well-developed root system, excellent soil-fixing power, and better soil and water conservation ability and has the characteristics of barren tolerance, strong sprouting power, abundant and easily decomposed dead leaves, etc. Therefore, C. fissa is not only a pioneer species for postdestruction sprouting forests but also a highly potential ecological public welfare forest tree species. Moreover, due to its beautiful shape, wide canopy and various colors, it has become an ideal tree for landscaping and ornamental purposes. However, there is a basic gap in knowledge in the reports on the drought resistance or drought tolerance genes of C. fissa. Based on the above details, in this study, 2-year-old C. fissa seedlings were used as the study material to investigate the physiological response under drought stress by a potted drought experiment, and we also compared and analyzed the differentially expressed proteins (DEPs) under different periods of drought stress by TMT quantitative labeling protein to prepare a preliminary study on the physiological response and proteomic mechanism of C. fissa adaptation to drought stress.
2023-07-24 | PXD038837 | Pride
Project description:We examined published microarray data from 104 acute lymphoblastic leukaemia patient specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent cohort of 68 specimens that were assessed using Affymetrix HG-U133A arrays.
2007-05-11 | E-TABM-125 | biostudies-arrayexpress
Project description:Recent advances in molecular and genetic studies about flowering time control have been increasingly available to elucidate the physiological mechanism underlying masting, the intermittent and synchronized production of a large amount of flowers and seeds in plant populations. To identify unexplored developmental and physiological processes associated with masting, genome-wide transcriptome analysis is a promising tool, but such analyses have yet to be performed. We established a field transcriptome using a typical masting species, Japanese beech (Fagus crenata Blume), over two years, and analyzed the data using a nonlinear time-series analysis called convergent cross mapping. Our field transcriptome was found to undergo numerous changes depending on the status of floral induction and season. An integrated approach of high-throughput transcriptomics and causal inference was successful at detecting novel causal regulatory relationships between nitrate transport and florigen synthesis/transport in a forest tree species. The synergistic activation of nitrate transport and floral transition could be adaptive to simultaneously satisfy floral transition at the appropriate timing and the nitrogen demand needed for flower formation.
2019-02-27 | GSE126540 | GEO