Opportunities for Innovation in Genetic Transformation of Forest Trees.
Ontology highlight
ABSTRACT:
SUBMITTER: Nagle M
PROVIDER: S-EPMC6176273 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Opportunities for Innovation in Genetic Transformation of Forest Trees.
Nagle Michael M Déjardin Annabelle A Pilate Gilles G Strauss Steven H SH
Frontiers in plant science 20181002
The incorporation of DNA into plant genomes followed by regeneration of non-chimeric stable plants (transformation) remains a major challenge for most plant species. Forest trees are particularly difficult as a result of their biochemistry, aging, desire for clonal fidelity, delayed reproduction, and high diversity. We review two complementary approaches to transformation that appear to hold promise for forest trees. ...[more]
Similar Datasets
Project description:Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF-predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.
| S-EPMC8965365 | biostudies-literature
Project description:Mapping the spatial distribution of a plant is a current challenge in ecology. Here, a convolutional neural network (CNN) and 33,798 Sentinel-2 satellite images were used to detect and map forest stands dominated by trees of the genus Pleroma by their magenta-to-deep-purple blossoms in the entire Brazilian Atlantic Forest domain, from June 2016 to July 2020. The Pleroma genus, known for its pioneer behaviour, was detected in an area representing 10.8% of the Atlantic Forest, associated negatively with temperature and positively with elevation, slope, tree cover and precipitation. The detection of another genus by the model, 18% of all the detections contained only pink blooming Handroanthus trees, highlighted that botanical identification from space must be taken with caution, particularly outside the known distribution range of the species. The Pleroma blossom seasonality occurred over a period of ~5-6 months centered on the March equinox and populations with distinct blossom timings were found. Our results indicate that in the Atlantic Forest, the remaining natural forest is less diverse than expected but is at least recovering from degradation. Our study suggests a method to produce ecological-domain scale maps of tree genera and species based on their blossoms that could be used for tree studies and biodiversity assessments.
| S-EPMC8517022 | biostudies-literature
Project description:Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.
| S-EPMC5829188 | biostudies-literature
Project description:We report the discovery of a beta-glucosidase gene (PgM-NM-2glu-1) whose expression underpins natural resistance to a major forest pest, the spruce budworm (SBW) in white spruce (Picea glauca (Voss.) Moench). We performed a microarray experiment to compare resistant (R) and non-resistant (N-R) trees. PgM-NM-2glu-1 transcripts levels uniquely were up to 1000 times higher in phenotypically resistant trees and correlated with accumulation of acetophenones compounds that reduce SBW development. These resistance traits were heritable, temporally correlated with the emergence of the most damaging larval stages and were highly variable in the natural population across a large geographic area. The recombinant gene product specifically catalyzed the release of biologically active acetophenones from their glucoside precursors. SBW outbreaks have become more frequent and intense; therefore, the phenotypic diversity resulting from variation in PgM-NM-2glu-1 expression may be a key for the adaptability of spruce populations. Transcriptome profiling was carried out with needles from 7 resistant and 7 non-resistant trees (harvested on June 17th, 2010), and 3 samples per tree (n=42) with a custom microarray developed for spruce species and comprising oligonucleotide probes for 23,853 unique P. glauca gene sequences (Raherison et al., 2012).
2014-05-06 | E-GEOD-57301 | biostudies-arrayexpress
Project description:We report the discovery of a beta-glucosidase gene (Pgβglu-1) whose expression underpins natural resistance to a major forest pest, the spruce budworm (SBW) in white spruce (Picea glauca (Voss.) Moench). We performed a microarray experiment to compare resistant (R) and non-resistant (N-R) trees. Pgβglu-1 transcripts levels uniquely were up to 1000 times higher in phenotypically resistant trees and correlated with accumulation of acetophenones compounds that reduce SBW development. These resistance traits were heritable, temporally correlated with the emergence of the most damaging larval stages and were highly variable in the natural population across a large geographic area. The recombinant gene product specifically catalyzed the release of biologically active acetophenones from their glucoside precursors. SBW outbreaks have become more frequent and intense; therefore, the phenotypic diversity resulting from variation in Pgβglu-1 expression may be a key for the adaptability of spruce populations.
2014-05-06 | GSE57301 | GEO
Project description:In the course of evolution, both flowering plants and some gymnosperms have developed such an adaptation to winter and unfavorable living conditions as deciduousness. Of particular interest is Siberian larch (Larix sibirica Ledeb.), which is the only species in the pine family (Pinaceae) with a seasonal deciduousness. New generation sequencing technologies make it possible to study this phenomenon at the genomic level and to reveal the genetic mechanisms of leaf and needle aging in angiosperms and gymnosperms. Using a comparative analysis of the genomes of evergreen and deciduous trees, it was found that the genes that control EXORDIUM LIKE 2 (EXL2) and DORMANCY-ASSOCIATED PROTEIN 1 (DRM1) proteins are most represented in Siberian larch, while an excess of genes that control proteins acting as immune receptors were found in evergreens. Orthologs from the family of genes that control leucine-rich repeat receptor-like kinases (LRR-RLK) contributed mostly to the distinction between evergreens and deciduous plants.
| S-EPMC8998842 | biostudies-literature
Project description:Low nitrogen (N) availability is a major limiting factor for tree growth and development. N uptake, assimilation, storage and remobilization are key processes in the economy of this essential nutrient, and its efficient metabolic use largely determines vascular development, tree productivity and biomass production. Recently, advances have been made that improve our knowledge about the molecular regulation of acquisition, assimilation and internal recycling of N in forest trees. In poplar, a model tree widely used for molecular and functional studies, the biosynthesis of glutamine plays a central role in N metabolism, influencing multiple pathways both in primary and secondary metabolism. Moreover, the molecular regulation of glutamine biosynthesis is particularly relevant for accumulation of N reserves during dormancy and in N remobilization that takes place at the onset of the next growing season. The characterization of transgenic poplars overexpressing structural and regulatory genes involved in glutamine biosynthesis has provided insights into how glutamine metabolism may influence the N economy and biomass production in forest trees. Here, a general overview of this research topic is outlined, recent progress are analyzed and challenges for future research are discussed.
| S-EPMC6172323 | biostudies-literature
Project description:To provide evidence at the micro level for cracking the Solow productivity paradox, this paper deeply studies the impact of enterprise digital transformation on green innovation. In terms of theoretical research, three potential mechanisms are excavated for the first time; considering empirical research, a series of strict causal effect identification strategies are carried out. The results show that enterprise digital transformation can significantly promote green innovation, and it passes a series of robustness tests and endogenous tests. According to the theoretical and empirical results, the policy suggestions mainly include five points: helping enterprises to accelerate digital transformation; strengthening the green innovation ability of enterprises; reducing internal and external costs and promoting the professional division of labor; piloting the digital transformation policy; enhancing corporate social responsibility. It provides a reference of experience and a path for other countries to follow in implementing a digital transformation strategy and green sustainable development strategy.
| S-EPMC9269481 | biostudies-literature
Project description:Tropical agro-forest landscapes are global priority areas for biodiversity conservation. Little is known about the ability of these landscapes to sustain large late successional forest trees upon which much forest biodiversity depends. These landscapes are subject to fragmentation and additional habitat degradation which may limit tree recruitment and thus compromise numerous ecosystem services including carbon storage and timber production. Dysoxylum malabaricum is a large canopy tree species in the Meliaceae, a family including many important tropical timber trees. This species is found in highly fragmented forest patches within a complex agro-forest landscape of the Western Ghats biodiversity hot spot, South India. In this paper we combined a molecular assessment of inbreeding with ecological and demographic data to explore the multiple threats to recruitment of this tree species. An evaluation of inbreeding, using eleven microsatellite loci in 297 nursery-reared seedlings collected form low and high density forest patches embedded in an agro-forest matrix, shows that mating between related individuals in low density patches leads to reduced seedling performance. By quantifying habitat degradation and tree recruitment within these forest patches we show that increasing canopy openness and the increased abundance of pioneer tree species lead to a general decline in the suitability of forest patches for the recruitment of D. malabaricum. We conclude that elevated inbreeding due to reduced adult tree density coupled with increased degradation of forest patches, limit the recruitment of this rare late successional tree species. Management strategies which maintain canopy cover and enhance local densities of adult trees in agro-forest mosaics will be required to ensure D. malabaricum persists in these landscapes. Our study highlights the need for a holistic understanding of the incipient processes that threaten populations of many important and rare tropical tree species in human dominated agro-forest landscapes.
| S-EPMC3928449 | biostudies-literature
Project description:Trees, including minimum spanning trees (MSTs), are commonly used in phylogenetic studies. But, for the research community, it may be unclear that the presented tree is just a hypothesis, chosen from among many possible alternatives. In this scenario, it is important to quantify our confidence in both the trees and the branches/edges included in such trees. In this paper, we address this problem for MSTs by introducing a new edge betweenness metric for undirected and weighted graphs. This spanning edge betweenness metric is defined as the fraction of equivalent MSTs where a given edge is present. The metric provides a per edge statistic that is similar to that of the bootstrap approach frequently used in phylogenetics to support the grouping of taxa. We provide methods for the exact computation of this metric based on the well known Kirchhoff's matrix tree theorem. Moreover, we implement and make available a module for the PHYLOViZ software and evaluate the proposed metric concerning both effectiveness and computational performance. Analysis of trees generated using multilocus sequence typing data (MLST) and the goeBURST algorithm revealed that the space of possible MSTs in real data sets is extremely large. Selection of the edge to be represented using bootstrap could lead to unreliable results since alternative edges are present in the same fraction of equivalent MSTs. The choice of the MST to be presented, results from criteria implemented in the algorithm that must be based in biologically plausible models.
| S-EPMC4370493 | biostudies-literature