Genetic Diversity and Population Differentiation of Pinus koraiensis in China

Pinus koraiensis is a well-known precious tree species in East Asia with high economic, ornamental and ecological value. More than fifty percent of the P. koraiensis forests in the world are distributed in northeast China, a region with abundant germplasm resources. However, these natural P. koraiensis sources are in danger of genetic erosion caused by continuous climate changes, natural disturbances such as wildfire and frequent human activity. Little work has been conducted on the population genetic structure and genetic differentiation of P. koraiensis in China because of the lack of genetic information. In this study, 480 P. koraiensis individuals from 16 natural populations were sampled and genotyped. Fifteen polymorphic expressed sequence tag-simple sequence repeat (EST-SSR) markers were used to evaluate genetic diversity, population structure and differentiation in P. koraiensis. Analysis of molecular variance (AMOVA) of the EST-SSR marker data showed that 33% of the total genetic variation was among populations and 67% was within populations. A high level of genetic diversity was found across the P. koraiensis populations, and the highest levels of genetic diversity were found in HH, ZH, LS and TL populations. Moreover, pairwise Fst values revealed significant genetic differentiation among populations (mean Fst = 0.177). According to the results of the STRUCTURE and Neighbor-joining (NJ) tree analyses and principal component analysis (PCA), the studied geographical populations cluster into two genetic clusters: cluster 1 from Xiaoxinganling Mountains and cluster 2 from Changbaishan Mountains. These results are consistent with the geographical distributions of the populations. The results provide new genetic information for future genome-wide association studies (GWAS), marker-assisted selection (MAS) and genomic selection (GS) in natural P. koraiensis breeding programs and can aid the development of conservation and management strategies for this valuable conifer species

ADBench: Anomaly Detection Benchmark

Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and (iii) noisy and corrupted data? In this work, we answer these key questions by conducting (to our best knowledge) the most comprehensive anomaly detection benchmark with 30 algorithms on 57 benchmark datasets, named ADBench. Our extensive experiments (98,436 in total) identify meaningful insights into the role of supervision and anomaly types, and unlock future directions for researchers in algorithm selection and design. With ADBench, researchers can easily conduct comprehensive and fair evaluations for newly proposed methods on the datasets (including our contributed ones from natural language and computer vision domains) against the existing baselines. To foster accessibility and reproducibility, we fully open-source ADBench and the corresponding results.Comment: NeurIPS 2022. All authors contribute equally and are listed alphabetically. Code available at https://github.com/Minqi824/ADBenc

Morphological and Comparative Transcriptome Analysis of Three Species of Five-Needle Pines: Insights Into Phenotypic Evolution and Phylogeny

Pinus koraiensis, Pinus sibirica, and Pinus pumila are the major five-needle pines in northeast China, with substantial economic and ecological values. The phenotypic variation, environmental adaptability and evolutionary relationships of these three five-needle pines remain largely undecided. It is therefore important to study their genetic differentiation and evolutionary history. To obtain more genetic information, the needle transcriptomes of the three five-needle pines were sequenced and assembled. To explore the relationship of sequence information and adaptation to a high mountain environment, data on needle morphological traits [needle length (NL), needle width (NW), needle thickness (NT), and fascicle width (FW)] and 19 climatic variables describing the patterns and intensity of temperature and precipitation at six natural populations were recorded. Geographic coordinates of altitude, latitude, and longitude were also obtained. The needle morphological data was combined with transcriptome information, location, and climate data, for a comparative analysis of the three five-needle pines. We found significant differences for needle traits among the populations of the three five-needle pine species. Transcriptome analysis showed that the phenotypic variation and environmental adaptation of the needles of P. koraiensis, P. sibirica, and P. pumila were related to photosynthesis, respiration, and metabolites. Analysis of orthologs from 11 Pinus species indicated a closer genetic relationship between P. koraiensis and P. sibirica compared to P. pumila. Our study lays a foundation for genetic improvement of these five-needle pines and provides insights into the adaptation and evolution of Pinus species

Variations in Growth and Photosynthetic Traits of Polyploid Poplar Hybrids and Clones in Northeast China

To evaluate differences among 19 different ploidy hybrid poplar clones grown in northeast China, 21 traits related to growth traits and photosynthetic characteristics were detected and analyzed. Abundant phenotypic variations exist among and within populations, and these variations are the basis of forest tree genetic improvements. In this research, variance analysis showed that the traits except the net photosynthesis rate among the different ploidies and all the other traits exhibited significant differences among the ploidies or clones (p < 0.01). Estimation of phenotypic coefficients of variation, genotypic coefficients of variation, and repeatability is important for selecting superior materials. The larger the value, the greater the potential for material selection improvement. The repeatability of the different traits ranged from 0.88 to 0.99. The phenotypic and genotypic coefficients of variation of all the investigated traits ranged from 6.88% to 57.40% and from 4.85% to 42.89%, respectively. Correlation analysis showed that there were significant positive correlations between tree height, diameter, and volume. Transpiration rate, intercellular carbon dioxide concentration, and stomatal conductance were significantly positively correlated with each other but negatively correlated with instantaneous water use efficiency. Growth traits were weakly correlated with photosynthetic indexes. The rank correlation coefficient showed that most of the growth indicators reached a significant correlation level among different years (0.40-0.98), except 1-year-old tree height with 4-year-old tree height and 1-year-old ground diameter with 3-year-old tree height, which indicated the potential possibility for early selection of elite clones. Principal analysis results showed that the contribution rate of the first principal component was 46.606%, and 2-year-old tree height, 2-year-old ground diameter, 3-year-old tree height, 3-year-old ground diameter, 3-year-old diameter at breast height, 3-year-old volume, 4-year-old tree height, 4-year-old ground diameter, 4-year-old diameter at breast height, and 4-year-old volume showed higher vector values than other traits. With the method of multiple-trait comprehensive evaluation to evaluate clones, SX3.1, SY3.1, and XY4.2 were selected as elite clones, and the genetic gains of height, basal diameter, diameter at breast height, and volume of selected clones ranged from 12.85% to 64.87% in the fourth growth year. The results showed fundamental information for selecting superior poplar clones, which might provide new materials for the regeneration and improvement of forests in Northeast China

Morphological growth performance and genetic parameters on Korean pine in Northeastern China

Korean pine (Pinus koraiensis) is an economically valuable species owing to its excellent timber quality and nuts useful for various purposes. But few studies have been made on growth performance, and aspects combining the genetic gain and classification method on phenotypic similarity in the selection process of superior families. Thus, the present study aimed at analyzing the genetic variation and highlight suitable morphological traits for family selection; establishing trait correlations and families' ordination based on similarities in phenotypic characters, and selecting elite families and suitable parent trees. Full-sib families from 28 crosses established in randomized complete block design from Naozhi orchard in Northeast China were used, and 11 morphological traits were investigated. Significant differences were observed among families for all traits. The traits coefficients of variation ranged from 6.07 to 56.25 % and from 0.029 to 15.213 % in phenotype and genotypic variation, respectively. A moderate level of inherited genetic control was observed (broad sense heritability H-2, varied from 0.155 to 0.438). Traits related to stem growth were highly positively correlated to each other whereas crown traits showed a weak correlation with stem traits (Pearson correlation r, ranged from -0.161 to 0.956). Based on multi-trait comprehensive analysis, we selected six elite families and six parents, which resulted in a genetic gain of 5.6 %, 16.9 %, and 36.4 % in tree height, diameter at breast height, and volume, respectively. These results make a theoretical basis for selecting excellent families and establish orchards of Korean pine from improved seeds

Variations in growth traits and wood physicochemical properties among Pinus koraiensis families in Northeast China

This study aimed to explore and improve the different economic values of Pinus koraiensis (Siebold and Zucc.) by examining the variations in 6 growth traits and 9 physicochemical wood properties among 53 P. koraiensis half-sib families. Growth traits assessed included height, diameter at breast height, volume, degree of stem straightness, stem form, and branch number per node, while wood properties assessed included density, fiber length and width, fiber length to width ratio, and cellulose, hemicellulose, holocellulose, lignin, and ash contents. Except for degree of stem straightness and branch number per node, all other traits exhibited highly significant variations (P < 0.01) among families. The coefficients of variation ranged from 5.3 (stem form) to 66.7% (ash content), whereas, the heritability ranged from 0.136 (degree of stem straightness) to 0.962 (ash content). Significant correlations were observed among growth traits and wood physicochemical properties. Principal component analysis identified four distinct groups representing growth traits, wood chemical and physical properties, and stem form traits. Multi-trait comprehensive evaluation identified three groups of elite families based on breeding objectives, including rapid growth, improved timber production for building and furniture materials, and pulpwood production. These specific families should be used to establish new plantations

ADGym: Design Choices for Deep Anomaly Detection

Deep learning (DL) techniques have recently found success in anomaly detection (AD) across various fields such as finance, medical services, and cloud computing. However, most of the current research tends to view deep AD algorithms as a whole, without dissecting the contributions of individual design choices like loss functions and network architectures. This view tends to diminish the value of preliminary steps like data preprocessing, as more attention is given to newly designed loss functions, network architectures, and learning paradigms. In this paper, we aim to bridge this gap by asking two key questions: (i) Which design choices in deep AD methods are crucial for detecting anomalies? (ii) How can we automatically select the optimal design choices for a given AD dataset, instead of relying on generic, pre-existing solutions? To address these questions, we introduce ADGym, a platform specifically crafted for comprehensive evaluation and automatic selection of AD design elements in deep methods. Our extensive experiments reveal that relying solely on existing leading methods is not sufficient. In contrast, models developed using ADGym significantly surpass current state-of-the-art techniques.Comment: NeurIPS 2023. The first three authors contribute equally. Code available at https://github.com/Minqi824/ADGy

Metabolome and Transcriptome Analyses Unravels Molecular Mechanisms of Leaf Color Variation by Anthocyanidin Biosynthesis in Acer triflorum

Acer triflorum Komarov is an important ornamental tree, and its seasonal change in leaf color is the most striking feature. However, the quantifications of anthocyanin and the mechanisms of leaf color change in this species remain unknown. Here, the combined analysis of metabolome and transcriptome was performed on green, orange, and red leaves. In total, 27 anthocyanin metabolites were detected and cyanidin 3-O-arabinoside, pelargonidin 3-O-glucoside, and peonidin 3-O-gluside were significantly correlated with the color development. Several structural genes in the anthocyanin biosynthesis process, such as chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), and dihydroflavonol 4-reductase (DFR), were highly expressed in red leaves compared to green leaves. Most regulators (MYB, bHLH, and other classes of transcription factors) were also upregulated in red and orange leaves. In addition, 14 AtrMYBs including AtrMYB68, AtrMYB74, and AtrMYB35 showed strong interactions with the genes involved in anthocyanin biosynthesis, and, thus, could be further considered the hub regulators. The findings will facilitate genetic modification or selection for further improvement in ornamental qualities of A. triflorum

Comparison of genetic impact on growth and wood traits between seedlings and clones from the same plus trees of Pinus koraiensis

To evaluate the relationships among clones and open pollinated families from the same plus trees and to select elite breeding materials, growth, and wood characteristics of 33-year-old Pinus koraiensis clones and families were measured and analyzed. The results show that growth and wood characters varied significantly. The variation due to clonal effects was higher than that of family effects. The ratio of genetic to phenotypic coefficient of variation of clones in growth and wood traits was above 90%, and the repeatability of these characteristics was more than 0.8, whereas the ratio of genetic to phenotypic coefficient of variation of families was above 90%. The broad-sense heritability of all characteristics exceeded 0.4, and the narrow-sense family heritability of growth traits was less than 0.3. Growth characteristics were positively correlated with each other, but most wood properties were weakly correlated in both clones and families. Fiber length and width were positively correlated between clones and families. Using the membership function method, eleven clones and four families were selected as superior material for improved diameter growth and wood production, and two families from clonal and open-pollinated trees showed consistently better performance. Generally, selection of the best clones is an effective alternative to deployment of families as the repeatability estimates from clonal trees were higher than narrow-sense heritability estimates from open pollinated families. The results provide valuable insight for improving P. koraiensis breeding programs and subsequent genetic improvement