Nutrient allocation patterns of Picea crassifolia on the eastern margin of the Qinghai-Tibet Plateau.

It can provide a basis for decision making for the conservation and sustainable use of forest ecosystems in mountains to understand the stoichiometric properties and nutrient allocation strategies of major tree species. However, the plant nutrient allocation strategies under different environmental gradients in forest systems of arid and semi-arid mountains are not fully understand. Therefore, three typical regions in the Qilian Mountains on the eastern edge of the Qinghai-Tibet Plateau were selected based on precipitation and temperature gradients, and the stoichiometric characteristics and nutrient allocation strategies of Qinghai spruce (Picea crassifolia) of the dominant tree species under different environmental gradients were investigated. The results showed that (1) the stoichiometric characteristics of plant tissues were different in the three regions. (2) The importance of each tissue in the plant nutrient allocation varied in different regions, showing that the plant roots are more important in the warm-wet region, while the plant leaves, branches and trunks are more important in the transition and hot-dry regions. (3) The influencing factors affecting plant nutrient allocation strategies were inconsistent across regions, which showed that plant nutrient allocation strategies in the warm-wet and transition region were mainly influenced by soil factors, while they were more influenced by climatic factors in the hot-dry region. The patterns of plant nutrient allocation strategies and drivers under different environmental gradients could help us better understand the ecological adaptation mechanism and physiological adjustment mechanism of forest ecosystem in mountains.

Spatial characteristics of nutrient allocation for Picea crassifolia in soil and plants on the eastern margin of the Qinghai-Tibet Plateau.

BACKGROUND: Understanding the stoichiometric characteristics and nutrient allocation strategies of dominant tree species in montane forest systems can provide a basis for decision-making in relation to montane system management. Therefore, according to precipitation and temperature gradients, we selected three typical areas in the Qilian Mountains on the eastern margin of the Qinghai-Tibet Plateau to analyse the spatial relations of plant-soil stoichiometric characteristics and nutrient allocation strategies of plant tissues for Qinghai spruce (Picea crassifolia) along different environmental gradients. RESULTS: 1) The plant and soil stoichiometric characteristics had similar spatial patterns. The C content of plants and soils tended to decrease with increasing latitude, and the N and P contents and the N:P ratio tended to increase with increasing latitude. 2) The stoichiometric characteristics of the plant tissues also interacted with each other and showed synergistic trade-offs. Nutrient allocation in the eastern section of the Qilian Mountains was similar to that in the western section, while more N and P in the plant stems were allocated to maintain plant growth in the relatively arid western Sect. 3) The nutrient allocation strategies in the plant tissues were mainly regulated by soil and climate. CONCLUSIONS: Information on plant-soil stoichiometric characteristics along different gradients can help us better understand the nutrient patterns and dynamics of forest ecosystems under arid and semiarid conditions at a wide geographic scale from the perspective of plant nutrient partitioning.

Hormonal Regulation and Stimulation Response of Jatropha curcas L. Homolog Overexpression on Tobacco Leaf Growth by Transcriptome Analysis.

The Flowering locus T (FT) gene encodes the florigen protein, which primarily regulates the flowering time in plants. Recent studies have shown that FT genes also significantly affect plant growth and development. The FT gene overexpression in plants promotes flowering and suppresses leaf and stem development. This study aimed to conduct a transcriptome analysis to investigate the multiple effects of Jatropha curcas L. homolog (JcFT) overexpression on leaf growth in tobacco plants. The findings revealed that JcFT overexpression affected various biological processes during leaf development, including plant hormone levels and signal transduction, lipid oxidation metabolism, terpenoid metabolism, and the jasmonic-acid-mediated signaling pathway. These results suggested that the effects of FT overexpression in plants were complex and multifaceted, and the combination of these factors might contribute to a reduction in the leaf size. This study comprehensively analyzed the effects of JcFT on leaf development at the transcriptome level and provided new insights into the function of FT and its homologous genes.

np2 QTL: networking phenotypic plasticity quantitative trait loci across heterogeneous environments.

Despite its critical importance to our understanding of plant growth and adaptation, the question of how environment-induced plastic response is affected genetically remains elusive. Previous studies have shown that the reaction norm of an organism across environmental index obeys the allometrical scaling law of part-whole relationships. The implementation of this phenomenon into functional mapping can characterize how quantitative trait loci (QTLs) modulate the phenotypic plasticity of complex traits to heterogeneous environments. Here, we assemble functional mapping and allometry theory through Lokta-Volterra ordinary differential equations (LVODE) into an R-based computing platform, np2 QTL, aimed to map and visualize phenotypic plasticity QTLs. Based on LVODE parameters, np2 QTL constructs a bidirectional, signed and weighted network of QTL-QTL epistasis, whose emergent properties reflect the ecological mechanisms for genotype-environment interactions over any range of environmental change. The utility of np2 QTL was validated by comprehending the genetic architecture of phenotypic plasticity via the reanalysis of published plant height data involving 3502 recombinant inbred lines of maize planted in multiple discrete environments. np2 QTL also provides a tool for constructing a predictive model of phenotypic responses in extreme environments relative to the median environment.

A unified DNA sequence and non-DNA sequence mapping model of complex traits.

Increasing evidence shows that quantitative inheritance is based on both DNA sequence and non-DNA sequence variants. However, how to simultaneously detect these variants from a mapping study has been unexplored, hampering our effort to illustrate the detailed genetic architecture of complex traits. We address this issue by developing a unified model of quantitative trait locus (QTL) mapping based on an open-pollinated design composed of randomly sampling maternal plants from a natural population and their half-sib seeds. This design forms a two-level hierarchical platform for a joint linkage-linkage disequilibrium analysis of population structure. The EM algorithm was implemented to estimate and test DNA sequence-based effects and non-DNA sequence-based effects of QTLs. We applied this model to analyze genetic mapping data from the OP design of a gymnosperm coniferous species, Torreya grandis, identifying 25 significant DNA sequence and non-DNA sequence QTLs for seedling height and diameter growth in different years. Results from computer simulation show that the unified model has good statistical properties and is powerful for QTL detection. Our model enables the tests of how a complex trait is affected differently by DNA-based effects and non-DNA sequence-based transgenerational effects, thus allowing a more comprehensive picture of genetic architecture to be charted and quantified.

HpQTL: a geometric morphometric platform to compute the genetic architecture of heterophylly.

Heterophylly, i.e. morphological changes in leaves along the axis of an individual plant, is regarded as a strategy used by plants to cope with environmental change. However, little is known of the extent to which heterophylly is controlled by genes and how each underlying gene exerts its effect on heterophyllous variation. We described a geometric morphometric model that can quantify heterophylly in plants and further constructed an R-based computing platform by integrating this model into a genetic mapping and association setting. The platform, named HpQTL, allows specific quantitative trait loci mediating heterophyllous variation to be mapped throughout the genome. The statistical properties of HpQTL were examined and validated via computer simulation. Its biological relevance was demonstrated by results from a real data analysis of heterophylly in a wood plant, mei (Prunus mume). HpQTL provides a powerful tool to analyze heterophylly and its underlying genetic architecture in a quantitative manner. It also contributes a new approach for genome-wide association studies aimed to dissect the programmed regulation of plant development and evolution.

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation.

AlloMap6: an R package for genetic linkage analysis in allohexaploids.

Allopolyploids are a group of polyploids with more than two sets of chromosomes derived from different species. Previous linkage analysis of allopolyploids is based on the assumption that different chromosomes pair randomly during meiosis. A more sophisticated model to relax this assumption has been developed for allotetraploids by incorporating the preferential pairing behavior of homologous over homoeologous chromosomes. Here, we show that the basic principle of this model can be extended to perform linkage analysis of higher-ploidy allohexaploids, where multiple preferential pairing factors are used to characterize chromosomal-pairing meiotic features between different constituent species. We implemented the extended model into an R package, called AlloMap6, allowing the recombination fractions and preferential pairing factors to be estimated simultaneously. Allomap6 has two major functionalities, computer simulation and real-data analysis. By analyzing a real data from a full-sib family of allohexaploid persimmon, we tested and validated the usefulness and utility of this package. AlloMap6 lays a foundation for allohexaploid genetic mapping and provides a new horizon to explore the chromosomal kinship of allohexaploids.

A computing platform to map ecological metabolism by integrating functional mapping and the metabolic theory of ecology.

Whole-organism metabolic rate co-varies allometrically with body mass, and is also affected by temperature through different biochemical mechanisms. Here we implement a computational platform to map specific quantitative trait loci (QTLs) that govern the dependence of metabolic rate on size and temperature. The model was formulated within settings of genetic mapping or genome-wide association studies through a mapping population genotyped by a set of molecular markers throughout the genome and phenotyped for metabolic parameters over a range of temperature. The model, estimated by a maximum-likelihood approach, allows a genome-wide search for the underlying metabolic QTLs and the estimation of genotype-specific parameters that specify the metabolism of an organism. Our model provides a tool to detect pleiotropy and epistasis that cause the size- and temperature-dependent change of metabolic rate.

2HiGWAS: a unifying high-dimensional platform to infer the global genetic architecture of trait development.

Whole-genome search of genes is an essential approach to dissecting complex traits, but a marginal one-single-nucleotide polymorphism (SNP)/one-phenotype regression analysis widely used in current genome-wide association studies fails to estimate the net and cumulative effects of SNPs and reveal the developmental pattern of interplay between genes and traits. Here we describe a computational framework, which we refer to as two-side high-dimensional genome-wide association studies (2HiGWAS), to associate an ultrahigh dimension of SNPs with a high dimension of developmental trajectories measured across time and space. The model is implemented with a dual dimension-reduction procedure for both predictors and responses to select a sparse but full set of significant loci from an extremely large pool of SNPs and estimate their net time-varying effects on trait development. The model can not only help geneticists to precisely identify an entire set of genes underlying complex traits but also allow them to elucidate a global picture of how genes control developmental and dynamic processes of trait formation. We investigated the statistical properties of the model via extensive simulation studies. With the increasing availability of GWAS in various organisms, 2HiGWAS will have important implications for genetic studies of developmental compelx traits.

An open-pollinated design for mapping imprinting genes in natural populations.

With the increasing recognition of its role in trait and disease development, it is crucial to account for genetic imprinting to illustrate the genetic architecture of complex traits. Genetic mapping can be innovated to test and estimate effects of genetic imprinting in a segregating population derived from experimental crosses. Here, we describe and assess a design for imprinting detection in natural plant populations. This design is to sample maternal plants at random from a natural population and collect open-pollinated (OP) seeds randomly from each maternal plant and germinate them into seedlings. A two-stage hierarchical platform is constructed to jointly analyze maternal and OP progeny markers. Through tracing the segregation and transmission of alleles from the parental to progeny generation, this platform allows parent-of-origin-dependent gene expression to be discerned, providing an avenue to estimate the effect of imprinting genes on a quantitative trait. The design is derived to estimate imprinting effects expressed at the haplotype level. Its usefulness and utilization were validated through computer simulation. This OP-based design provides a tool to detect the genomic distribution and pattern of imprinting genes as an important component of heritable variation that is neglected in traditional genetic studies of complex traits.

Shape mapping: genetic mapping meets geometric morphometrics.

Knowledge about biological shape has important implications in biology and biomedicine, but the underlying genetic mechanisms for shape variation have not been well studied. Statistical models play a pivotal role in mapping specific quantitative trait loci (QTLs) that contribute to biological shape and its developmental trajectories. We describe and assess a statistical framework for shape gene identification that incorporates shape and image analysis into a mixture-model framework for QTL mapping. Statistical parameters that define genotype-specific differences in biological shape are estimated by implementing statistical and computational algorithms. A state-of-the-art procedure is described to examine the control patterns of specific QTLs on the origin, properties and functions of biological shape. The statistical framework described will help to address many integrative biological and genetic questions and challenges in shape variation faced by the life sciences community.

A statistical model for QTL mapping in polysomic autotetraploids underlying double reduction.

As a group of economically important species, linkage mapping of polysomic autotetraploids, including potato, sugarcane and rose, is difficult to conduct due to their unique meiotic property of double reduction that allows sister chromatids to enter into the same gamete. We describe and assess a statistical model for mapping quantitative trait loci (QTLs) in polysomic autotetraploids. The model incorporates double reduction, built in the mixture model-based framework and implemented with the expectation-maximization algorithm. It allows the simultaneous estimation of QTL positions, QTL effects and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We performed computer simulation to examine the statistical properties of the method and validate its use through analyzing real data in tetraploid switchgrass.

A reciprocal cross design to map the genetic architecture of complex traits in apomictic plants.

Many higher plants of economic and biological importance undergo apomixis in which the maternal tissue of the ovule forms a seed, without experiencing meiosis and fertilization. This feature of apomixis has made it difficult to perform linkage mapping which relies on meiotic recombination. Here, we describe a computational model for mapping quantitative trait loci (QTLs) that control complex traits in apomictic plants. The model is founded on the mixture model-based likelihood in which maternal genotypes are dissolved into two possible components generated by meiotic and apomictic processes, respectively. The EM algorithm was implemented to discern meiotic and apomictic genotypes and, therefore, allow the marker-QTL linkage relationship to be estimated. By capitalizing on reciprocal crosses, the model is renovated to estimate and test imprinting effects of QTLs, providing a better gateway to characterize the genetic architecture of complex traits. The model was validated through computer simulation and further demonstrated for its usefulness by analyzing a real data for an apomictic woody plant. The model has for the first time provided a unique tool for genetic mapping in apomictic plants.

Plastic expression of heterochrony quantitative trait loci (hQTLs) for leaf growth in the common bean (Phaseolus vulgaris).

Heterochrony, that is, evolutionary changes in the relative timing of developmental events and processes, has emerged as a key concept that links evolution and development. Genes associated with heterochrony encode molecular components of developmental timing mechanisms. However, our understanding of how heterochrony genes alter the expression of heterochrony in response to environmental changes remains very limited. We applied functional mapping to find quantitative trait loci (QTLs) responsible for growth trajectories of leaf area and leaf mass in the common bean (Phaseolus vulgaris) grown in two contrasting environments. We identified three major QTLs pleiotropically expressed under the two environments. Further characterization of the temporal pattern of these QTLs indicates that they are heterochrony QTLs (hQTLs) in terms of their role in influencing four heterochronic parameters: the timing of the inflection point, the timing of maximum acceleration and deceleration, and the duration of linear growth. The pattern of gene action by the hQTLs on each parameter was unique, being environmentally dependent and varying between two allometrically related leaf growth traits. These results provide new insights into the complexity of genetic mechanisms that control trait formation in plants and provide novel findings that will be of use in studying the evolutionary trends.

Genetic control of juvenile growth and botanical architecture in an ornamental woody plant, Prunus mume Sieb. et Zucc. as revealed by a high-density linkage map.

Mei, Prunus mume Sieb. et Zucc., is an ornamental plant popular in East Asia and, as an important member of genus Prunus, has played a pivotal role in systematic studies of the Rosaceae. However, the genetic architecture of botanical traits in this species remains elusive. This paper represents the first genome-wide mapping study of quantitative trait loci (QTLs) that affect stem growth and form, leaf morphology and leaf anatomy in an intraspecific cross derived from two different mei cultivars. Genetic mapping based on a high-density linkage map constricted from 120 SSRs and 1,484 SNPs led to the detection of multiple QTLs for each trait, some of which exert pleiotropic effects on correlative traits. Each QTL explains 3-12% of the phenotypic variance. Several leaf size traits were found to share common QTLs, whereas growth-related traits and plant form traits might be controlled by a different set of QTLs. Our findings provide unique insights into the genetic control of tree growth and architecture in mei and help to develop an efficient breeding program for selecting superior mei cultivars.

Competition-cooperation mechanism between Escherichia coli and Staphylococcus aureus based on systems mapping.

Introduction: Interspecies interactions are a crucial driving force of species evolution. The genes of each coexisting species play a pivotal role in shaping the structure and function within the community, but how to identify them at the genome-wide level has always been challenging. Methods: In this study, we embed the Lotka-Volterra ordinary differential equations in the theory of community ecology into the systems mapping model, so that this model can not only describe how the quantitative trait loci (QTL) of a species directly affects its own phenotype, but also describe the QTL of the species how to indirectly affect the phenotype of its interacting species, and how QTL from different species affects community behavior through epistatic interactions. Results: By designing and implementing a co-culture experiment for 100 pairs of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), we mapped 244 significant QTL combinations in the interaction process of the two bacteria using this model, including 69 QTLs from E. coli and 59 QTLs from S. aureus, respectively. Through gene annotation, we obtained 57 genes in E. coli, among which the genes with higher frequency were ypdC, nrfC, yphH, acrE, dcuS, rpnE, and ptsA, while we obtained 43 genes in S. aureus, among which the genes with higher frequency were ebh, SAOUHSC_00172, capF, gdpP, orfX, bsaA, and phnE1. Discussion: By dividing the overall growth into independent growth and interactive growth, we could estimate how QTLs modulate interspecific competition and cooperation. Based on the quantitative genetic model, we can obtain the direct genetic effect, indirect genetic effect, and genome-genome epistatic effect related to interspecific interaction genes, and then further mine the hub genes in the QTL networks, which will be particularly useful for inferring and predicting the genetic mechanisms of community dynamics and evolution. Systems mapping can provide a tool for studying the mechanism of competition and cooperation among bacteria in co-culture, and this framework can lay the foundation for a more comprehensive and systematic study of species interactions.

PTX3/TWIST1 Feedback Loop Modulates Lipopolysaccharide-Induced Inflammation via PI3K/Akt Signaling Pathway.

Chronic inflammation of nasal mucosal tissue is an obvious feature of allergic rhinitis. Pentraxin 3 (PTX3) is a member of the pentraxin family and plays important roles in inflammation. We aimed to investigate the roles and mechanisms of PTX3 in inflammatory factors and MUC5AC production in human nasal epithelia cells. Loss- and gain-of-function experiments were performed. We found that the silencing of PTX3 dramatically blocked the expression of interleukin (IL)-6, IL-8, IL-1ß, and MUC5AC induced by lipopolysaccharide (LPS). Gain-of-function of PTX3 displayed the opposite results. Interestingly, the ablation of PTX3 blocked activation of the PI3K/Akt signaling pathway, whereas the administration of an agonist of PI3K, 740Y-P, partially reversed the inhibitory functions of PTX3 silencing on inflammation and MUC5AC production. Moreover, PTX3 was a positive regulator of TWIST1, which is one of the transcription factors of PTX3. We noticed that TWIST1 downregulation reduced the expression of PTX3. Furthermore, chromatin immunoprecipitation assay and dual-luciferase reporter assay demonstrated that TWIST1 could bind to the promoter of PTX3. Importantly, the depletion of TWIST1 attenuated the LPS-mediated expression and secretion of inflammatory cytokines, whereas these effects were partially abolished upon PTX3 overexpression. Taken together, our findings revealed that the PTX3/TWIST1 feedback loop modulates LPS-induced inflammation and MUC5AC production via the PI3K/Akt signaling pathway.

Genome-Wide Identification and Analysis of the NAC Transcription Factor Gene Family in Garden Asparagus (Asparagus officinalis).

As a large plant-specific gene family, the NAC (NAM, ATAF1/2, and CUC2) transcription factor is related to plant growth, development, and response to abiotic stresses. Although the draft genome of garden asparagus (Asparagus officinalis) has been released, the genome-wide investigation of the NAC gene family is still unavailable. In this study, a total of 85 A. officinalis NAC genes were identified, and a comprehensive analysis of the gene family was performed, including physicochemical properties, phylogenetic relationship, chromosome localization, gene structure, conserved motifs, intron/exon, cis-acting elements, gene duplication, syntenic analysis, and differential gene expression analysis. The phylogenetic analysis demonstrated that there were 14 subgroups in both A. officinalis and Arabidopsis thaliana, and the genes with a similar gene structure and motif distribution were clustered in the same group. The cis-acting regulatory analysis of AoNAC genes indicated four types of cis-acting elements were present in the promoter regions, including light-responsive, hormone-responsive, plant-growth-and-development-related, and stress-responsive elements. The chromosomal localization analysis found that 81 NAC genes in A. officinalis were unevenly distributed on nine chromosomes, and the gene duplication analysis showed three pairs of tandem duplicated genes and five pairs of segmental duplications, suggesting that gene duplication is possibly associated with the amplification of the A. officinalis NAC gene family. The differential gene expression analysis revealed one and three AoNAC genes that were upregulated and downregulated under different types of salinity stress, respectively. This study provides insight into the evolution, diversity, and characterization of NAC genes in garden asparagus and will be helpful for future understanding of their biological roles and molecular mechanisms in plants.

Comprehensive Effects of Flowering Locus T-Mediated Stem Growth in Tobacco.

In flowering plants, Flowering locus T (FT) encodes a major florigen. It is a key flowering hormone in controlling flowering time and has a wide range of effects on plant development. Although the mechanism by which FT promotes flowering is currently clearly understood, comprehensive effects of the FT gene on plant growth have not been evaluated. Therefore, the effects of FT on vegetative growth need to be explored for a complete understanding of the molecular functions of the FT gene. In this study, the Jatropha curcas L. FT gene was overexpressed in tobacco (JcFTOE) in order to discover multiple aspects and related mechanisms of how the FT gene affects plant development. In JcFTOE plants, root, stem, and leaf development was strongly affected. Stem tissues were selected for further transcriptome analysis. In JcFTOE plants, stem growth was affected because of changes in the nucleus, cytoplasm, and cell wall. In the nucleus of JcFTOE plants, the primary effect was to weaken all aspects of DNA replication, which ultimately affected the cell cycle and cell division. The number of stem cells decreased significantly in JcFTOE plants, which decreased the thickness and height of tobacco stems. In the cell wall of JcFTOE plants, hemicellulose and cellulose contents increased, with the increase in hemicellulose associated with up-regulation of xylan synthase-related genes expression. In the cytoplasm of JcFTOE plants, the primary effects were on biogenesis of ribonucleoprotein complexes, photosynthesis, carbohydrate biosynthesis, and the cytoskeleton. In addition, in the cytoplasm of JcFTOE plants, there were changes in certain factors of the core oscillator, expression of many light-harvesting chlorophyll a/b binding proteins was down-regulated, and expression of fructose 1,6-bisphosphatase genes was up-regulated to increase starch content in tobacco stems. Changes in the xylem and phloem of JcFTOE plants were also identified, and in particular, xylem development was affected by significant increases in expression of irregular xylem genes.