11 research outputs found
The complete genome sequence of Melia azedarach Linn. (Meliaceae): a multi-purpose pesticide species
The plant genus Melia has two or four species in the modern world, and is a natural source of a traditional pesticide, Toosendanin. In this study, we report the complete chloroplast genome of Melia azedarach, assembled from whole-genome high-throughput sequencing data, as a resource for future studies on the taxonomy and evolution of Melia. The chloroplast genome was 160,393 bp in length, with a large single-copy region of 87,598 bp, a small single-copy region of 18,709 bp, separated by two inverted repeat regions of 27,043 bp each. It was predicted to contain a total of 133 genes, with an overall GC content of 37.37%. Phylogenetic analysis placed M. azedarach closest to Azadirachta sp. in Meliaceae
The complete genome sequence of Sorbus insignis (Rosaceae: Amygdaloideae), an epiphytic shrub in this genus
Sorbus insignis (Hook. f.) Hedl., belonging to S. sect. Multijugae Yu is an epiphytic shrub. Its phylogenetic position is still poorly understood. In this study, we assembled its complete chloroplast genome from whole-genome high-throughput sequencing data. The chloroplast genome was 159, 993 bp in length, with a large single-copy (LSC) region of 87, 932 bp, a small single-copy (SSC) region of 19, 255 bp, separated by two inverted repeat (IR) regions of 26, 403 bp each. It was predicted to contain a total of 132 genes, with an overall GC content of 36.56%. Phylogenetic analysis suggested S. insignis belongs to S. L. sensu stricto and closest to S. prattii Koehne among the published chloroplast genome
Forest Fire Prediction with Imbalanced Data Using a Deep Neural Network Method
Forests suffer from heavy losses due to the occurrence of fires. A prediction model based on environmental condition, such as meteorological and vegetation indexes, is considered a promising tool to control forest fires. The construction of prediction models can be challenging due to (i) the requirement of selection of features most relevant to the prediction task, and (ii) heavily imbalanced data distribution where the number of large-scale forest fires is much less than that of small-scale ones. In this paper, we propose a forest fire prediction method that employs a sparse autoencoder-based deep neural network and a novel data balancing procedure. The method was tested on a forest fire dataset collected from the Montesinho Natural Park of Portugal. Compared to the best prediction results of other state-of-the-art methods, the proposed method could predict large-scale forest fires more accurately, and reduces the mean absolute error by 3–19.3 and root mean squared error by 0.95–19.3. The proposed method can better benefit the management of wildland fires in advance and the prevention of serious fire accidents. It is expected that the prediction performance could be further improved if additional information and more data are available
Metabolomic Study of Flavonoids in <i>Camellia drupifera</i> under Aluminum Stress by UPLC-MS/MS
Aluminum (Al) affects the yield of forest trees in acidic soils. The oil tea plant (Camellia drupifera Lour.) has high Al tolerance, with abundant phenolic compounds in its leaves, especially flavonoid compounds. The role of these flavonoids in the Al resistance of oil tea plants is unclear. In this metabolomic study of C. drupifera under Al stress, ultra-pressure liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) was utilized to identify metabolites, while principal component analysis, cluster analysis, and orthogonal partial least squares discriminant analysis were applied to analyze the data on the flavonoid metabolites. The leaf morphology of C. drupifera revealed significant damage by excess aluminum ions under each treatment compared with the control group. Under Al stress at 2 mmol/L (GZ2) and 4 mmol/L (GZ4), the total flavonoid content in C. drupifera leaves reached 24.37 and 35.64 mg/g, respectively, which are significantly higher than the levels measured in the control group (CK) (p C. drupifera. It was found that the abundance of the 24 differential flavonoid metabolites was gradually elevated with increasing concentrations of Al stress, including catechin, epicatechin, naringenin-7-glucoside, astilbin, taxifolin, miquelianin, quercitrin, and quercimeritrin. Moreover, the most significant increase in antioxidant activity (about 30%) was observed in C. drupifera precultured in leaf extracts containing 7.5 and 15 μg/mL of active flavonoids. The qRT-PCR results showed that the expression levels of key genes involved in the synthesis of flavonoids were consistent with the accumulation trends of flavonoids under different concentrations of Al. Therefore, our results demonstrate the key role of flavonoid compounds in the oil tea plant C. drupifera in response to Al stress, which suggests that flavonoid metabolites in C. drupifera, as well as other aluminum-tolerant plants, may help with detoxifying aluminum
Climate-Driven Adaptive Differentiation in Melia azedarach: Evidence from a Common Garden Experiment
Studies of local adaptation in populations of chinaberry (Melia azedarach L.) are important for clarifying patterns in the population differentiation of this species across its natural range. M. azedarach is an economically important timber species, and its phenotype is highly variable across its range in China. Here, we collected M. azedarach seeds from 31 populations across its range and conducted a common garden experiment. We studied patterns of genetic differentiation among populations using molecular markers (simple sequence repeats) and data on phenotypic variation in six traits collected over five years. Our sampled populations could be subdivided into two groups based on genetic analyses, as well as patterns of isolation by distance and isolation by environment. Significant differentiation in growth traits was observed among provenances and families within provenances. Geographic distance was significantly correlated with the quantitative genetic differentiation (QST) in height (HEIT) and crown breadth. Climate factors were significantly correlated with the QST for each trait. A total of 23 climatic factors were examined. There was a significant effect of temperature on all traits, and minimum relative humidity had a significant effect on the survival rate over four years. By comparing the neutral genetic differentiation (FST) with the QST, the mode of selection acting on survival rate varied, whereas HEIT and the straightness of the main trunk were subject to the same mode of selection. The variation in survival rate was consistent with the variation in genetic differentiation among populations, which was indicative of local adaptation. Overall, our findings provide new insights into the responses of the phenological traits of M. azedarach to changes in the climate conditions of China
Genetic Diversity and Population Structure of Toona Ciliata Roem. Based on Sequence-Related Amplified Polymorphism (SRAP) Markers
Sequence-related amplified polymorphism (SRAP) markers were used to investigate the genetic diversity among 30 populations of Toona ciliata Roem. sampled from the species’ distribution area in China. To analyze the polymorphism in the SRAP profiles, 1505 primer pairs were screened and 24 selected. A total of 656 SRAP bands ranging from 100 to 1500 bp were acquired, of these 505 bands (77%) were polymorphic. The polymorphism information content (PIC) values ranged from 0.32 to 0.45, with an average of 0.41. An analysis of molecular variance (AMOVA) indicated that the most significant variation was attributable to differences among the populations and that variation within the populations was small. STRUCTURE analysis divided the 30 populations into two parts. The unweighted pair group method of arithmetic averages (UPGMA) clustering and principal coordinates analysis (PCoA) showed that the 30 populations could be classified into four types. The results demonstrate a clear geographical trend for T. ciliata in China and provide a theoretical basis for future breeding and conservation strategy of T. ciliata