Meng Xu

Reference gene selection for quantitative real-time polymerase chain reaction in Populus

Accurate quantification of gene expression with quantitative real-time polymerase chain reaction (qRT-PCR) relies on the choice of an appropriate reference gene. In this study, nine candidate reference genes were selected to study the expression stability for qRT-PCR normalization in adventitious rooting of Populus hardwood cuttings. geNorm, NormFinder, and BestKeeper analysis revealed that actin isoform B (ACT) was the most unstable gene across developmental stages, whereas elongation factor 1 alpha (EF1a) and 18S recombinant RNA (18S) emerged as the most appropriate reference genes for qRT-PCR analysis in this complex developmental process.

A dynamic model for genome-wide association studies

Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.

Transient expression for functional gene analysis using Populus protoplasts

Despite the availability of the Populus genome sequence and the development of genetic, genomic, and transgenic approaches for its improvement, the lengthy life span of Populus and the cumbersome process required for its transformation have impeded rapid characterization of gene functions in Populus. Protoplasts provide a versatile and physiologically relevant cell system for high-throughput analysis and functional characterization of plant genes. Here, a highly efficient transient expression system using Populus mesophyll protoplasts was developed based on the following three steps. The first step involved formulating a new enzyme cocktail containing 2xa0% Cellulase C2605 and 0.5xa0% Pectinase P2611, which was shown to enable efficient large-scale isolation of homogenous Populus mesophyll protoplasts. The second step involved optimization of transfection conditions, such as the polyethylene glycol concentration and amount of plasmid DNA to ensure a >80xa0% transfection efficiency for Populus protoplasts. The third step involved using the Populus protoplast transient expression system to successfully determine the subcellular localizations of proteins, emulate signaling events during pathogen infection, and prepare protein extracts for Western blotting and protein–protein interaction assays. This rapid and highly efficient transient gene expression system in Populus mesophyll protoplasts will facilitate the rapid identification of gene functions and elucidation of signaling pathways in Populus.

How to cluster gene expression dynamics in response to environmental signals

Organisms usually cope with change in the environment by altering the dynamic trajectory of gene expression to adjust the complement of active proteins. The identification of particular sets of genes whose expression is adaptive in response to environmental changes helps to understand the mechanistic base of gene-environment interactions essential for organismic development. We describe a computational framework for clustering the dynamics of gene expression in distinct environments through Gaussian mixture fitting to the expression data measured at a set of discrete time points. We outline a number of quantitative testable hypotheses about the patterns of dynamic gene expression in changing environments and gene-environment interactions causing developmental differentiation. The future directions of gene clustering in terms of incorporations of the latest biological discoveries and statistical innovations are discussed. We provide a set of computational tools that are applicable to modeling and analysis of dynamic gene expression data measured in multiple environments.

Sequencing the genome of Marssonina brunnea reveals fungus-poplar co-evolution

BackgroundThe fungus Marssonina brunnea is a causal pathogen of Marssonina leaf spot that devastates poplar plantations by defoliating susceptible trees before normal fall leaf drop.ResultsWe sequence the genome of M. brunnea with a size of 52 Mb assembled into 89 scaffolds, representing the first sequenced Dermateaceae genome. By inoculating this fungus onto a poplar hybrid clone, we investigate how M. brunnea interacts and co-evolves with its host to colonize poplar leaves. While a handful of virulence genes in M. brunnea, mostly from the LysM family, are detected to up-regulate during infection, the poplar down-regulates its resistance genes, such as nucleotide binding site domains and leucine rich repeats, in response to infection. From 10,027 predicted proteins of M. brunnea in a comparison with those from poplar, we identify four poplar transferases that stimulate the host to resist M. brunnea. These transferas-encoding genes may have driven the co-evolution of M. brunnea and Populus during the process of infection and anti-infection.ConclusionsOur results from the draft sequence of the M. brunnea genome provide evidence for genome-genome interactions that play an important role in poplar-pathogen co-evolution. This knowledge could help to design effective strategies for controlling Marssonina leaf spot in poplar.

Functional mapping of genotype-environment interactions for soybean growth by a semiparametric approach.

BackgroundFunctional mapping is a powerful approach for mapping quantitative trait loci (QTLs) that control biological processes. Functional mapping incorporates mathematical aspects of growth and development into a general QTL mapping framework and has been recently integrated with composite interval mapping to build up a so-called composite functional mapping model, aimed to separate multiple linked QTLs on the same chromosomal region.ResultsThis article reports the principle of using composite functional mapping to estimate the effects of QTL-environment interactions on growth trajectories by parametrically modeling the tested QTL in a marker interval and nonparametrically modeling the markers outside the interval as co-factors. With this new model, we can characterize the dynamic patterns of the genetic effects of QTLs governing growth trajectories, estimate the global effects of the underlying QTLs during the course of growth and development, and test the differentiation in the shapes of QTL genotype-specific growth curves between different environments. By analyzing a real example from a soybean genome project, our model detects several QTLs that cause significant genotype-environment interactions for plant height growth processes.ConclusionsThe model provides a basis for deciphering the genetic architecture of trait expression adjusted to different biotic and abiotic environments for any organism.

Identification and characterization of three PeSHRs and one PeSCR involved in adventitious root development of Populus

The plant-specific GRAS family transcription factors, SHORT-ROOT (SHR) and SCARECROW (SCR), are key regulators of both the specification of the root stem cell niche and the differentiation potential of a subset of stem cells in the Arabidopsis root. Our previous microarray study indicated that SHR and SCR genes were involved in adventitious root development from hardwood cuttings in Populus. Here, we isolated and characterized three genes encoding SHR proteins and one gene encoding SCR proteins: PeSHR1, PeSHR2, PeSHR3 and PeSCR. Sequence and structure analysis showed that these proteins contained five well-conserved domains: leucine heptad repeat I (LHR I), the VHIID motif, leucine heptad repeat II (LHR II), the PFYRE motif, and the SAM motif. Temporal and spatial expression patterns of these genes were profiled during adventitious root development. Subcellular localization demonstrated that PeSHR1, PeSHR2 and PeSCR were localized to the nucleus, while PeSHR3 was localized to the cytoplasm. Finally, we adapted bimolecular fluorescence complementation to demonstrate that there was interaction between PeSHR1 and PeSCR. Collectively, these results contribute to improving our understanding of conserved and divergent aspects of SHR and SCR in various species.

Identification and expression analysis of twenty ARF genes in Populus

The auxin response factor (ARF) family of transcription factors is a crucial component of auxin signaling and plays important roles regulating numerous growth and developmental processes in plants. We isolated and characterized 20 ARF genes involved in adventitious root development of Populus. Multiple protein sequence alignments revealed that the PeARF proteins contained a highly conserved region in their N-terminal portion corresponding to the DNA-binding domain of the Arabidopsis ARF family. Except for PeARF3.1, PeARF3.2, PeARF17.1 and PeARF17.2, the PeARF proteins contained a carboxyl-terminal domain related to the Arabidopsis domains III and IV, which are involved in homo- and heterodimerization. The exon-intron structures of the PeARF genes were determined by aligning cDNA and genomic sequences. As expected, most PeARF genes had a similar distribution of exon-intron structures. Temporal expression patterns of these genes were profiled during adventitious root development. All 20 PeARF genes were expressed in root, stem and leaf in a dynamic manner. Transient expression assays with Populus protoplasts demonstrated that these PeARFs were localized to the nucleus. These results suggest that PeARFs may play diverse regulatory roles in adventitious root development of Populus and contribute to improving our understanding of conserved and divergent aspects of auxin signaling in various species.

A quantitative model of transcriptional differentiation driving host–pathogen interactions

Despite our expanding knowledge about the biochemistry of gene regulation involved in host-pathogen interactions, a quantitative understanding of this process at a transcriptional level is still limited. We devise and assess a computational framework that can address this question. This framework is founded on a mixture model-based likelihood, equipped with functionality to cluster genes per dynamic and functional changes of gene expression within an interconnected system composed of the host and pathogen. If genes from the host and pathogen are clustered in the same group due to a similar pattern of dynamic profiles, they are likely to be reciprocally co-evolving. If genes from the two organisms are clustered in different groups, this means that they experience strong host-pathogen interactions. The framework can test the rates of change for individual gene clusters during pathogenic infection and quantify their impacts on host-pathogen interactions. The framework was validated by a pathological study of poplar leaves infected by fungal Marssonina brunnea in which co-evolving and interactive genes that determine poplar-fungus interactions are identified. The new framework should find its wide application to studying host-pathogen interactions for any other interconnected systems.

A computational framework for mapping the timing of vegetative phase change

Phase change plays a prominent role in determining the form of growth and development. Although considerable attention has been focused on identifying the regulatory control mechanisms of phase change, a detailed understanding of the genetic architecture of this phenomenon is still lacking. We address this issue by deriving a computational model. The model is founded on the framework of functional mapping aimed at characterizing the interplay between quantitative trait loci (QTLs) and development through biologically meaningful mathematical equations. A multiphasic growth equationxa0was implemented into functional mapping, which, via a series of hypothesis tests, allows the quantification of how QTLs regulate the timing and pattern of vegetative phase transition between independently regulated, temporally coordinated processes. The model was applied to analyze stem radial growth data of an interspecific hybrid family derived from two Populus species during the first 24xa0yr of ontogeny. Several key QTLs related to phase change have been characterized, most of which were observed to be in the adjacent regions of candidate genes. The identification of phase transition QTLs, whose expression is regulated by endogenous and environmental signals, may enhance our understanding of the evolution of development in changing environments.