Xuli Zhu

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.

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.

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.

A unifying experimental design for dissecting tree genomes.

Linkage mapping and association mapping are adopted as an approach of choice for dissecting complex traits, but each shows a limitation when used alone. We propose an open-pollinated (OP) family design to integrate these two approaches into an organizing framework. The design unifies the strengths of population and quantitative genetic studies for evolutionary inference and high-resolution gene mapping. It particularly suits genome dissection of forest trees given their extant populations that are mostly undomesticated.

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.

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.

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.

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.