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The NAC (NAM, ATAF1/2 and CUC2) is a large gene family of plant-specific transcription factors that play a pivotal role in various physiological processes and abiotic stresses. Due to the lack of genome-wide characterization, intraspecific and interspecific synteny, and drought-responsive expression pattern of NAC genes in poplar, the functional characterization of drought-related NAC genes have been scarcely reported in Populus species. Here, we identified a total of 170 NAC domain-containing genes in the P. trichocarpa genome, 169 of which were unevenly distributed on its nineteen chromosomes. These NAC genes were phylogenetically divided into twenty subgroups, some of which exhibited a similar pattern of exon–intron architecture. The synteny and Ka/Ks analysis indicated that the expansion of NAC genes in poplar was mainly due to gene duplication events occurring before and after the divergence of Populus and Salix. Ten PdNAC (P. deltoids × P. euramericana cv.'Nanlin895') genes were randomly selected and cloned. Their drought-responsive expression profiles showed a tissue-specific pattern. The transcription factor PdNAC013 was verified to be localized in the nucleus. Our research results provide genomic information for the expansion of NAC genes in the poplar genome, and for further characterizing putative poplar NAC genes associated with water-deficit. [ABSTRACT FROM AUTHOR]

Developmental instability or noise, defined as the phenotypic imprecision of an organism in the face of internal or external stochastic disturbances, has been thought to play an important role in shaping evolutionary processes and patterns. The genetic studies of developmental instability have been based on fluctuating asymmetry (FA) that measures random differences between the left and the right sides of bilateral traits. In this article, we frame an experimental design characterized by a spatial autocorrelation structure for determining the genetic control of developmental instability for those traits that cannot be bilaterally measured. This design allows the residual environmental variance of a quantitative trait to be dissolved into two components due to permanent and random environmental factors. The degree of developmental instability is quantified by the relative proportion of the random residual variance to the total residual variance. We formulate a mixture model to estimate and test the genetic effects of quantitative trait loci (QTL) on the developmental instability of the trait. The genetic parameters including the QTL position, the QTL effects, and spatial autocorrelations are estimated by implementing the EM algorithm within the mixture model framework. Simulation studies were performed to investigate the statistical behavior of the model. A live example for poplar trees was used to map the QTL that control root length growth and its developmental instability from cuttings in water culture.

Abstract Background Genetic mapping has proven to be powerful for studying the genetic architecture of complex traits by characterizing a network of the underlying interacting quantitative trait loci (QTLs). Current statistical models for genetic mapping were mostly founded on the biallelic epistasis of QTLs, incapable of analyzing multiallelic QTLs and their interactions that are widespread in an outcrossing population. Results Here we have formulated a general framework to model and define the epistasis between multiallelic QTLs. Based on this framework, we have derived a statistical algorithm for the estimation and test of multiallelic epistasis between different QTLs in a full-sib family of outcrossing species. We used this algorithm to genomewide scan for the distribution of mul-tiallelic epistasis for a rooting ability trait in an outbred cross derived from two heterozygous poplar trees. The results from simulation studies indicate that the positions and effects of multiallelic QTLs can well be estimated with a modest sample and heritability. Conclusions The model and algorithm developed provide a useful tool for better characterizing the genetic control of complex traits in a heterozygous family derived from outcrossing species, such as forest trees, and thus fill a gap that occurs in genetic mapping of this group of important but underrepresented species.

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. [ABSTRACT FROM AUTHOR]

This project proposes an approach to identify significant single nucleotide polymorphism ( SNP) effects, both additive and dominant, on the dynamic growth of poplar in diameter and height. The annual changes in yearly phenotypes based on regular observation periods are considered to represent multiple responses. In total 156,362 candidate SNPs are studied, and the phenotypes of 64 poplar trees are recorded. To address this ultrahigh dimensionality issue, this paper adopts a two-stage approach. First, the conventional genome-wide association studies ( GWAS) and the distance correlation sure independence screening ( DC- SIS) methods (Li et al., 2012) were combined to reduce the model dimensions at the sample size; second, a grouped penalized regression was applied to further refine the model and choose the final sparse SNPs. The multiple response issue was also carefully addressed. The SNP effects on the dynamic diameter and height growth patterns of poplar were systematically analyzed. In addition, a series of intensive simulation studies was performed to validate the proposed approach. [ABSTRACT FROM AUTHOR]