Libo Jiang

Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition.

Epigenetic reprogramming is thought to play a critical role in maintaining the normal development of embryos. How the methylation state of paternal and maternal genomes regulates embryogenesis depends on the interaction and coordination of the gametes of two sexes. While there is abundant research in exploring the epigenetic interactions of sperms and oocytes, a knowledge gap exists in the mechanistic quantitation of these interactions and their impact on embryo development. This review aims at formulating a modeling framework to address this gap through the integration and synthesis of evolutionary game theory and the latest discoveries of the epigenetic control of embryo development by next-generation sequencing. This framework, named epigenetic game theory or epiGame, views embryogenesis as an ecological system in which two highly distinct and specialized gametes coordinate through either cooperation or competition, or both, to maximize the fitness of embryos under Darwinian selection. By implementing a system of ordinary differential equations, epiGame quantifies the pattern and relative magnitude of the methylation effects on embryogenesis by the mechanisms of cooperation and competition. epiGame may gain new insight into reproductive biology and can be potentially applied to design personalized medicines for genetic disorder intervention.

Plant grafting: how genetic exchange promotes vascular reconnection

Grafting has been widely used to improve horticultural traits. It has also served increasingly as a tool to investigate the long-distance transport of molecules that is an essential part for key biological processes. Many studies have revealed the molecular mechanisms of graft-induced phenotypic variation in anatomy, morphology and production. Here, we review the phenomena and their underlying mechanisms by which macromolecules, including RNA, protein, and even DNA, are transported between scions and rootstocks via vascular tissues. We further propose a conceptual framework that characterizes and quantifies the driving mechanisms of scion-rootstock interactions toward vascular reconnection and regeneration.

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

Summary 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.

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.

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.

Cloning of the Cryptochrome-Encoding PeCRY1 Gene from Populus euphratica and Functional Analysis in Arabidopsis

Cryptochromes are photolyase-like blue/UV-A light receptors that evolved from photolyases. In plants, cryptochromes regulate various aspects of plant growth and development. Despite of their involvement in the control of important plant traits, however, most studies on cryptochromes have focused on lower plants and herbaceous crops, and no data on cryptochrome function are available for forest trees. In this study, we isolated a cryptochrome gene, PeCRY1, from Euphrates poplar (Populus euphratica), and analyzed its structure and function in detail. The deduced PeCRY1 amino acid sequence contained a conserved N-terminal photolyase-homologous region (PHR) domain as well as a C-terminal DQXVP-acidic-STAES (DAS) domain. Secondary and tertiary structure analysis showed that PeCRY1 shares high similarity with AtCRY1 from Arabidopsis thaliana. PeCRY1 expression was upregulated at the mRNA level by light. Using heterologous expression in Arabidopsis, we showed that PeCRY1 overexpression rescued the cry1 mutant phenotype. In addition, PeCRY1 overexpression inhibited hypocotyl elongation, promoted root growth, and enhanced anthocyanin accumulation in wild-type background seedlings grown under blue light. Furthermore, we examined the interaction between PeCRY1 and AtCOP1 using a bimolecular fluorescence complementation (BiFc) assay. Our data provide evidence for the involvement of PeCRY1 in the control of photomorphogenesis in poplar.

A skellam model to identify differential patterns of gene expression induced by environmental signals

BackgroundRNA-seq, based on deep-sequencing techniques, has been widely employed to precisely measure levels of transcripts and their isoforms expressed under different conditions. However, robust statistical tools used to analyze these complex datasets are lacking. By grouping genes with similar expression profiles across treatments, cluster analysis provides insight into gene functions and networks that have become increasingly important.ResultsWe proposed and verified a cluster algorithm based on a skellam model for grouping genes into distinct groups based on the pattern of gene expression in response to changing conditions or in different tissues. This algorithm capitalizes on the skellam distribution to capture the count property of RNA-seq data and clusters genes in different environments. A two-stage hierarchical expectation-maximization (EM) algorithm was implemented to estimate the optimal number of groups and mean expression levels of each group across two environments. A procedure was formulated to test whether and how a given group shows a plastic response to environmental changes. The model was used to analyze an RNA-seq dataset measured from reciprocal crosses of early Arabidopsis thaliana embryos that respond differently based on the extent of maternal and paternal genome contributions, from which genes associated with maternal and paternal contributions were identified. Simulation studies were also performed to validate the statistical behavior of the model.ConclusionsThis model is a useful tool for clustering gene expression data by RNA-seq, thus facilitating our understanding of gene functions and networks.

Inferring the evolutionary history of outcrossing populations through computing a multiallelic linkage–linkage disequilibrium map

Summary Linkage disequilibrium (LD), the non-random association of alleles at different loci, has been used as an important parameter to study the genetic diversity and evolutionary history of natural populations. A joint analysis of LD with the linkage of the same marker pair has proven to gain more insight into the genetic signature of population diversification than LD analysis alone. We develop a unifying framework for simultaneously estimating the linkage and LD across pairs of multiallelic markers. The framework has particular power to construct the LD map from any markers with an arbitrary number of alleles per locus. We provide an efficient strategy to manipulate disequilibrium parameters whose number increases exponentially with the number of alleles. The model was tested through extensive simulation studies and validated by analysing a real marker data set from a population genetic research project of euphrates poplar, a desert tree, distributed in the north-western China. For widespread undomesticated natural populations, compared with biallelic markers, multiallelic markers with a high level of polymorphism are more powerful to study their genetic structure and organization of an outcrossing population. The model developed will potentially have an immediate implication for population and evolutionary genetic studies.

How trees allocate carbon for optimal growth: insight from a game-theoretic model

How trees allocate photosynthetic products to primary height growth and secondary radial growth reflects their capacity to best use environmental resources. Despite substantial efforts to explore tree height-diameter relationship empirically and through theoretical modeling, our understanding of the biological mechanisms that govern this phenomenon is still limited. By thinking of stem woody biomass production as an ecological system of apical and lateral growth components, we implement game theory to model and discern how these two components cooperate symbiotically with each other or compete for resources to determine the size of a tree stem. This resulting allometry game theory is further embedded within a genetic mapping and association paradigm, allowing the genetic loci mediating the carbon allocation of stemwood growth to be characterized and mapped throughout the genome. Allometry game theory was validated by analyzing a mapping data of stem height and diameter growth over perennial seasons in a poplar tree. Several key quantitative trait loci were found to interpret the process and pattern of stemwood growth through regulating the ecological interactions of stem apical and lateral growth. The application of allometry game theory enables the prediction of the situations in which the cooperation, competition or altruism is an optimal decision of a tree to fully use the environmental resources it owns.

Computational identification of genes modulating stem height–diameter allometry

Summary The developmental variation in stem height with respect to stem diameter is related to a broad range of ecological and evolutionary phenomena in trees, but the underlying genetic basis of this variation remains elusive. We implement a dynamic statistical model, functional mapping, to formulate a general procedure for the computational identification of quantitative trait loci (QTLs) that control stem height–diameter allometry during development. Functional mapping integrates the biological principles underlying trait formation and development into the association analysis of DNA genotype and endpoint phenotype, thus providing an incentive for understanding the mechanistic interplay between genes and development. Built on the basic tenet of functional mapping, we explore two core ecological scenarios of how stem height and stem diameter covary in response to environmental stimuli: (i) trees pioneer sunlit space by allocating more growth to stem height than diameter and (ii) trees maintain their competitive advantage through an inverse pattern. The model is equipped to characterize ‘pioneering’ QTLs (pi QTLs) and ‘maintaining’ QTLs (mi QTLs) which modulate these two ecological scenarios, respectively. In a practical application to a mapping population of full‐sib hybrids derived from two Populus species, the model has well proven its versatility by identifying several pi QTLs that promote height growth at a cost of diameter growth and several mi QTLs that benefit radial growth at a cost of height growth. Judicious application of functional mapping may lead to improved strategies for studying the genetic control of the formation mechanisms underlying trade‐offs among quantities of assimilates allocated to different growth parts.