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Populus has a wide ecogeographical range spanning the Northern Hemisphere, and interspecific hybrids are common. Populus tomentosa Carr. is widely distributed and cultivated in the eastern region of Asia, where it plays multiple important roles in forestry, agriculture, conservation, and urban horticulture. Reference genomes are available for several Populus species, however, our goals were to produce a very high quality de novo chromosome-level genome assembly in P. tomentosa genome that could serve as a reference for evolutionary and ecological studies of hybrid speciation throughout the genus. Here, combining long-read sequencing and Hi-C scaffolding, we present a high-quality, haplotype-resolved genome assembly. The genome size was 740.2 Mb, with a contig N50 size of 5.47 Mb and a scaffold N50 size of 46.68 Mb, consisting of 38 chromosomes, as expected with the known diploid chromosome number (2n = 2x = 38). A total of 59,124 protein-coding genes were identified. Phylogenomic analyses revealed that P. tomentosa is comprised of two distinct subgenomes, which we deomonstrate is likely to have resulted from hybridization between Populus adenopoda as the female parent and Populus alba var. pyramidalis as the male parent, with an origin of approximately 3.93 Ma. Although highly colinear, significant structural variation was found between the two subgenomes. Our study provides a valuable resource for ecological genetics and forest biotechnology.

Heterophylly is an adaptive strategy used by some plants in response to environmental changes. Due to the lack of representative plants with typical heteromorphic leaves, little is known about the genetic architecture of heterophylly in plants and the genes underlying its control. Here, we investigated the genetic characteristics underlying changes in leaf shape based on the model species, Populus euphratica, which exhibits typical heterophylly. A set of 401,571 single-nucleotide polymorphisms (SNPs) derived from whole-genome sequencing of 860 genotypes were associated with nine leaf traits, which were related to descriptive and shape data using single- and multi-leaf genome-wide association studies (GWAS). Multi-leaf GWAS allows for a more comprehensive understanding of the genetic architecture of heterophylly by considering multiple leaves simultaneously. The single-leaf GWAS detected 140 significant SNPs, whereas the multi-leaf GWAS detected 200 SNP-trait associations. Markers were found across 19 chromosomes, and 21 unique genes were implicated in traits and serve as potential targets for selection. Our results provide novel insights into the genomic architecture of heterophylly, and provide candidate genes for breeding or engineering P. euphratica. Our observations also improve understanding of the intrinsic mechanisms of plant growth, evolution, and adaptation in response to climate change.

Developmental modularity, i.e., coherent organization and function of developmentally related traits, is an emergent property of organismic development and evolution. However, knowledge about how modular variation and evolution are driven genetically is still limited. Here, using ornamental plants as an example, we propose a computational framework to map, visualize and annotate the genetic architecture of trait modularity by integrating modularity theory into system mapping, a statistical model for multifaceted genetic mapping of complex traits. A developmental module can be viewed as an ecosystem, in which the constituting components compete for space and resources or cooperate symbiotically to organize its function and behavior. This interactive process is quantified by mathematical models and evolutionarily interpreted by game theory. The proposed framework can test whether and how genes regulate the coordination of different but interconnected traits through their competition or cooperation to downstream developmental modularity.

Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai–Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high‐ to low‐altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high‐altitude adaptation in Tibetan poplar.

Phenotypic plasticity is the capacity to change the phenotype in response to different environments without alteration of the genotype. Despite sufficient evidence that microorganisms have a major role in the fitness and sickness of eukaryotes, there has been little research regarding microbial phenotypic plasticity. In this study, 45 strains of Staphylococcus aureus were grown for 12 days in both monoculture and in coculture with the same strain of Escherichia coli to create a competitive environment. Cell abundance was determined by quantitative PCR every 24 h, and growth curves of each S. aureus strain under the two sets of conditions were generated. Combined with whole-genome resequencing data, bivariate genome-wide association study (GWAS) was performed to analyze the growth plasticity of S. aureus in coculture. Finally, 20 significant single-nucleotide polymorphisms (eight annotated, seven unannotated, and five non-coding regions) were obtained, which may affect the competitive growth of S. aureus. This study advances genome-wide bacterial growth plasticity research and demonstrates the potential of bivariate GWAS for bacterial phenotypic plasticity research. KEY POINTS: • Growth plasticity of S. aureus was analyzed by bivariate GWAS. • Twenty significant SNPs may affect the growth plasticity of S. aureus.

In recent years, the emergence of next generation sequencing (NGS) makes it possible to obtain the data of microbial genome accurately in a short period of time, and it has become a powerful tool for microbial molecular ecology research. NGS has the advantage of non-sequence dependence and it can simultaneously detect nearly all culturable and non-culturable microorganisms which have high or low contents. With the explosion of sequencing data generated by NGS and multi-omics techniques, there is a growing need for the powerful genetic statistical models to generate meaningful hypotheses about the mechanisms underlying biological interaction. In this paper, we mainly discuss the application and prospect of NGS combined with the genetic statistical models in microbial molecular ecology. The combination of the two in promoting the study of microbial interspecific interaction is discussed. Then we analyze the application of the combination in the study of bacterial phenotypic plasticity. Finally, we describe its application in constructing gene regulatory network of microbe-plant interaction, which aims to identify key genes to enhance the disease resistance of plants.

Heterophylly is an adaptive strategy used by some plants in response to environmental changes. Due to the lack of representative plants with typical heteromorphic leaves, little is known about the genetic architecture of heterophylly in plants and the genes underlying its control. Here, we investigated the genetic characteristics underlying changes in leaf shape based on the model species

Background: Neonatal respiratory distress syndrome (RDS), due to surfactant deficiency in preterm infants, is the most common cause of respiratory morbidity. The surfactant proteins (SFTP) genetic variants have been well-studied in association with RDS; however, the impact of SNP-SNP (single nucleotide polymorphism) interactions on RDS has not been addressed. Therefore, this study utilizes a newer statistical model to determine the association of SFTP single SNP model and SNP-SNP interactions in a two and a three SNP interaction model with RDS susceptibility.Methods: This study used available genotype and clinical data in the Floros biobank at Penn State University. The patients consisted of 848 preterm infants, born SFTPA1, SFTPA2, SFTPB, SFTPC, and SFTPD SNPs were investigated. Wang's statistical model was employed to test and identify significant associations in a case-control study.Results: Only the rs17886395 (C allele) of the SFTPA2 was associated with protection for RDS in a single-SNP model (Odd's Ratio 0.16, 95% CI 0.06–0.43, adjusted p = 0.03). The highest number of interactions (n = 27) in the three SNP interactions were among SFTPA1 and SFTPA2. The three SNP models showed intergenic and intragenic interactions among all SFTP SNPs except SFTPC.Conclusion: The single SNP model and SNP interactions using the two and three SNP interactions models identified SFTP-SNP associations with RDS. However, the large number of significant associations containing SFTPA1 and/or SFTPA2 SNPs point to the importance of SFTPA1 and SFTPA2 in RDS susceptibility.

Summary Community ecology theory suggests that an individual's phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities., Graphical Abstract, Highlights • We develop a new theory for complex-trait mapping by integrating behavioral ecology • This theory can characterize how QTL drive cooperation or competition in populations • It can also illustrate how the activation of QTL is driven by ecological interactions • The new theory leverages interdisciplinary studies of genetics, ecology, and evolution, Biological Sciences; Evolutionary Ecology; Mathematical Biosciences

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.

Populus has a wide ecogeographical range spanning the Northern Hemisphere, and exhibits abundant distinct species and hybrids globally. Populus tomentosa Carr. is widely distributed and cultivated in the eastern region of Asia, where it plays multiple important roles in forestry, agriculture, conservation, and urban horticulture. Reference genomes are available for several Populus species, however, our goals were to produce a very high quality de novo, chromosome-level genome assembly in P. tomentosa genome that could serve as a reference for evolutionary and ecological studies of hybrid speciation. Here, combining long-read sequencing and Hi-C scaffolding, we present a high-quality, haplotype-resolved genome assembly. The genome size was 740.2 Mb, with a contig N50 size of 5.47 Mb and a scaffold N50 size of 46.68 Mb, consisting of 38 chromosomes, as expected with the known diploid chromosome number (2n=2x=38). A total of 59,124 protein-coding genes were identified. Phylogenomic analyses revealed that P. tomentosa is comprised of two distinct subgenomes, which we deomonstrate is likely to have resulted from hybridization between Populus adenopoda as the female parent and Populus alba var. pyramidalis as the male parent, approximately 3.93 Mya. Although highly colinear, significant structural variation was also found between the two subgenomes. Our study provides a valuable resource for ecological genetics and forest biotechnology.

How genes interact with the environment to shape phenotypic variation and evolution is a fundamental question interesting to biologists from various fields. Existing linear models built on single genes are inadequate to reveal the complexity of gene-environment (G-E) interactions. Here, we develop a conceptual model for mechanistically dissecting G-E interplay by integrating previously disconnected theories and methods. Under this integration, evolutionary game theory, developmental modularity theory, and variable selection method allow us to reconstruct environment-induced, maximally informative, sparse, and casual multilayer genetic networks. We design and conduct a mapping experiment using a salt-resistant tree species to validate the biological application of the new model. The model identifies previously uncharacterized molecular mechanisms that mediate trees’ response to saline stress. Our model provides a tool to comprehend the genetic architecture of trait variation and evolution and trace the information flow of each gene toward phenotypes within omnigenic networks.

Polyploidy is a common phenomenon among willow species. In this study, genome sequencing was conducted for Salix matsudana Koidz (also named Chinese willow), an important greening and arbor tree species, and the genome of this species was compared with those of four other tree species in Salicaceae. The total genome sequence of S. matsudana was 655.72 Mb in size, with repeated sequences accounting for 45.97% of the total length. In total, 531.43 Mb of the genome sequence could be mapped onto 38 chromosomes using the published genetic map as a reference. The genome of S. matsudana could be divided into two groups, the A and B genomes, through homology analysis with the genome of Populus trichocarpa, and the A and B genomes contained 23,985 and 25,107 genes, respectively. 4DTv combined transposon analysis predicted that allotetraploidy in S. matsudana appeared ~4 million years ago. The results from this study will help reveal the evolutionary history of S. matsudana and lay a genetic basis for its breeding.

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N-deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N-induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high-throughput phenotyping data of yield-related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N-induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N-deficiency tolerant wheat varieties.

Populus tomentosais widely distributed and cultivated in the Northern and Central China, where it is of great economic and ecological importance. However, the origin ofP. tomentosaremains controversial. Here, we used a PacBio+Hi-C+Illumina strategy to sequence and assemble its 740.2 Mb (2n) genome. The assembly accounts for greater than 92.1% of the 800-megabase genome, comprises 38 chromosomes, and contains 59,124 annotated protein-coding genes. Phylogenomic analyses elucidated dynamic genome evolution events among its closely related white poplars, and revealed thattomentosais comprised of two subgenomes, which we deomonstrate is likely to have resulted from hybridization betweenPopulus adenopodaas the female, andPopulus albavar.pyramidalisas the male, around 3.93 Mya. We also detected structural variations and allele-indels across genome. Our study presents a high quality and well assembled genome, unveils the origin of the widely distributed and plantedP. tomentosa, and provides a powerful resource for comparative plant biology, breeding, and biotechnology.

BackgroundTo maximize photosynthetic efficiency, plants have evolved a capacity by which leaf area scales allometrically with leaf mass through interactions with the environment. However, our understanding of genetic control of this allometric relationship remains limited.ResultsWe integrated allometric scaling laws expressed at static and ontogenetic levels into genetic mapping to identify the quantitative trait loci (QTLs) that mediate how leaf area scales with leaf mass and how such leaf allometry, under the control of these QTLs, varies as a response to environment change. A major QTL detected by the static model constantly affects the allometric growth of leaf area vs. leaf mass for the common bean (Phaseolus vulgaris) in two different environments. The ontogenetic model identified this QTL plus a few other QTLs that determine developmental trajectories of leaf allometry, whose expression is contingent heavily upon the environment.ConclusionsOur results gain new insight into the genetic mechanisms of how plants program their leaf morphogenesis to adapt to environmental perturbations.

Genome-wide association studies have been increasingly used to map and characterize genes that contribute to interindividual variation in drug response. Some studies have integrated the pharmacokinetic (PK) and pharmacodynamic (PD) processes of drug reactions into association mapping, gleaning new insight into how genes determine the dynamic relationship of drug effect and drug dose. Here, we present an evolutionary framework by which two distinct concepts, chronopharmacodynamics and heterochrony (describing variation in the timing and rate of developmental events), are married to comprehend the pharmacogenetic architecture of drug response. The resulting new concept, heterochronopharmacodynamics (HCPD), can better interpret how genes influence drug efficacy and drug toxicity according to the circadian rhythm of the body and changes in drug concentration.

Additional file 2. The profile of log-likelihood ratio (LR) test statistics over 11 chromosomes for testing the existence of QTLs governing leaf area vs. leaf mass ontogenetic allometry for the common bean grown at Palmira (red) and Popayan (blue), with the LR values besides the most significant QTLs. The slash horizontal line denotes the genome-wide critical threshold determined from 1000 permutation tests.

Additional file 1. The profile of log-likelihood ratio (LR) test statistics over 11 chromosomes for testing the existence of QTLs governing leaf area vs. leaf mass static allometry at different time points 1–5 for the common bean grown at Palmira (red) and Popayan (blue), with the LR values besides the most significant QTLs. The slash horizontal line denotes the genome-wide critical threshold determined from 1000 permutation tests.

Additional file 4 The ontogenetic allometry fitting (curve) of leaf area and leaf mass data (dots) at 5 tome points for each RIL grown at Palmira (red) and Popayan (blue) by the intercepted power eq. (5) A(t) = αMβ(t) – d.

As an important functional organ of plants, leaves alter their shapes in response to a changing environment. The variation of leaf shape has long been an important evolutionary and developmental force in plants. Despite an increasing amount of investigations into the genetic controls of leaf morphology, few have systematically studied the genetic architecture controlling shape differences among distinct altitudes. Altitude denotes a comprehensive complex of environmental factors affecting plant growth in many aspects, e.g., UV-light radiation, temperature, and humidity. To reveal how plants alter ecological adaptation to altitude through genes, we used Populus szechuanica var. tibetica growing on the Qinghai-Tibetan plateau. FST between the low- and high- altitude population was 0.00748, QST for leaf width, length and area were 0.00924, 0.1108, 0.00964 respectively. With the Elliptic Fourier-based morphometric model, association study of leaf shape was allowed, the dissection of the pleiotropic expression of genes mediating altitude-derived leaf shape variation was performed. For high and low altitudes, 130 and 131 significant single-nucleotide polymorphisms (SNPs) were identified. QTLs that affected leaf axis length and leaf width were expressed in both-altitude population, while QTLs regulating “leaf tip” and “leaf base” were expressed in low-altitude population. Pkinase and PRR2 were common significant genes in both types of populations. Auxin-related and differentiation-related genes included PIN1, CDK-like, and CAK1AT at high altitude, whereas they included NAP5, PIN-LIKES, and SCL1 at low altitude. The presence of Stress-antifung gene, CIPK3 and CRPK1 in high-altitude population suggested an interaction between genes and harsh environment in mediating leaf shape, while the senescence repression-related genes (EIN2 and JMJ18) and JMT in jasmonic acid pathway in low-altitude population suggested their crucial roles in ecological adaptability. These data provide new information that strengthens the understanding of genetic control with respect to leaf shape and constitute an entirely novel perspective regarding leaf adaptation and development in plants.

De novo shoot regeneration is one of the important manifestations of cell totipotency in organogenesis, which reflects a survival strategy organism evolved when facing natural selection. Compared with tissue regeneration, and somatic embryogenesis, de novo shoot regeneration denotes a shoot regeneration process directly from detatched or injured tissues of plant. Studies on plant shoot regeneration had identified key genes mediating shoot regeneration. However, knowledge was derived from Arabidopsis; the regeneration capacity is hugely distinct among species. To achieve a comprehensive understanding of the shoot regeneration mechanism from tree species, we select four genetic lines of Populus euphratica from a natural population to be sequenced at transcriptome level. On the basis of the large difference of differentiation capacity, between the highly differentiated (HD) and low differentiated (LD) groups, the analysis of differential expression identified 4920 differentially expressed genes (DEGs), which were revealed in five groups of expression patterns by clustering analysis. Enrichment showed crucial pathways involved in regulation of regeneration difference, including “plant hormone signal transduction”, “cell differentiation”, "cellular response to auxin stimulus", and “auxin-activated signaling pathway”. The expression of nine genes reported to be associated with shoot regeneration was validated using quantitative real-time PCR (qRT-PCR). For the specificity of regeneration mechanism with P. euphratica, large amount of DEGs involved in "plant-pathogen interaction", ubiquitin-26S proteosome mediated proteolysis pathway, stress-responsive DEGs, and senescence-associated DEGs were summarized to possibly account for the differentiation difference with distinct genotypes of P. euphratica. The result in this study helps screening of key regulators in mediating the shoot differentiation. The transcriptomic characteristic in P. euphratica further enhances our understanding of key processes affecting the regeneration capacity of de novo shoots among distinct species.

Plant adaptation to high altitudes has long been a substantial focus of ecological and evolutionary research. However, the genetic mechanisms underlying such adaptation remain poorly understood. Here, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed from low (~2,000 m) to high altitudes (~3,000 m) of Sejila Mountain on the Qinghai–Tibet Plateau. Population structure analyses allow clear classification of two groups according to their altitudinal distributions. However, in contrast to the genetic variation within each population, differences between the two populations only explain a small portion of the total genetic variation (3.64%). We identified asymmetrical gene flow from high‐ to low‐altitude populations. Integrating population genomic and landscape genomic analyses, we detected two hotspot regions, one containing four genes associated with altitudinal variation, and the other containing ten genes associated with response to solar radiation. These genes participate in abiotic stress resistance and regulation of reproductive processes. Our results provide insight into the genetic mechanisms underlying high‐altitude adaptation in Tibetan poplar., In this article, we address this issue by sampling, genotyping, and comparing populations of Tibetan poplar, Populus szechuanica var. tibetica, distributed at low (~2,000 m) and high altitudes (~3,000 m) of Sejila Mountain on the Qinghai‐Tibet Plateau. We identified clearly classification of these two populations according to altitudinal distribution, and we also detected low population divergence and robust asymmetry gene flows between them. Finally, we identified a hot spot region under selection and associated with environmental variables through scanning of the whole Tibetan poplar genome.

How genes interact with the environment to shape phenotypic variation and evolution is a fundamental question intriguing to biologists from various fields. Existing linear models built on single genes are inadequate to reveal the complexity of genotype-environment (G-E) interactions. Here, we develop a conceptual model for mechanistically dissecting G-E interplay by integrating previously disconnected theories and methods. Under this integration, evolutionary game theory, developmental modularity theory, and a variable selection method allow us to reconstruct environment-induced, maximally informative, sparse, and casual multilayer genetic networks. We design and conduct two mapping experiments by using a desert-adapted tree species to validate the biological application of the model proposed. The model identifies previously uncharacterized molecular mechanisms that mediate trees' response to saline stress. Our model provides a tool to comprehend the genetic architecture of trait variation and evolution and trace the information flow of each gene toward phenotypes within omnigenic networks.

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.

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.

Linkage analysis has played an important role in understanding genome structure and evolution. However, two-point linkage analysis widely used for genetic map construction can rarely chart a detailed picture of genome organization because it fails to identify the dependence of crossovers distributed along the length of a chromosome, a phenomenon known as crossover interference. Multi-point analysis, proven to be more advantageous in gene ordering and genetic distance estimation for dominant markers than two-point analysis, is equipped with a capacity to discern and quantify crossover interference. Here, we review a statistical model for four-point analysis, which, beyond three-point analysis, can characterize crossover interference that takes place not only between two adjacent chromosomal intervals, but also over multiple successive intervals. This procedure provides an analytical tool to elucidate the detailed landscape of crossover interference over the genome and further infer the evolution of genome structure and organization.

Background: Plants have evolved the dual capacity for maximizing light assimilation through stem growth (phototropism) and maximizing water and nutrient absorption through root growth (gravitropism). Previous studies have revealed the physiological and molecular mechanisms of these two processes, but the genetic basis for how gravitropism and phototropism interact and coordinate with one another to determine plant growth remains poorly understood. Methods: We designed a seed germination experiment using a full-sib F1 family of Populus euphratica to simultaneously monitor the gravitropic growth of the radicle and the phototropic growth of the plumule throughout seedling ontogeny. We implemented three functional mapping models to identify quantitative trait loci (QTLs) that regulate gravitropic and phototropic growth. Univariate functional mapping dissected each growth trait separately, bivariate functional mapping mapped two growth traits simultaneously, and composite functional mapping mapped the sum of gravitropic and phototropic growth as a main axis. Results: Bivariate model detected 8 QTLs for gravitropism and phototropism (QWRF, GLUR, F-box, PCFS4, UBQ, TAF12, BHLH95, TMN8), composite model detected 7 QTLs for growth of main axis (ATL8, NEFH, PCFS4, UBQ, SOT16, MOR1, PCMP-H), of which, PCFS4 and UBQ were pleiotropically detected with the both model. Many of these QTLs are situated within the genomic regions of candidate genes. Conclusions: The results from our models provide new insight into the mechanisms of genetic control of gravitropism and phototropism in a desert tree, and will stimulate our understanding of the relationships between gravity and light signal transduction pathways and tree adaptation to arid soil.

Phenotypic plasticity enables individuals to develop different phenotypes in a changing environment and promotes adaptive evolution. Genome-wide association study (GWAS) facilitates the study of the genetic basis of bacterial phenotypes, and provides a new opportunity for bacterial phenotypic plasticity research. To investigate the relationship between growth plasticity and genotype in bacteria, 41

Surfactant proteins (SP) are involved in surfactant function and innate immunity in the human lung. Both lung function and innate immunity are altered in CF, and altered SP levels and genetic association are observed in Cystic Fibrosis (CF). We hypothesized that single nucleotide polymorphisms (SNPs) within the SP genes associate with CF or severity subgroups, either through single SNP or via SNP-SNP interactions between two SNPs of a given gene (intragenic) and/or between two genes (intergenic). We genotyped a total of 17 SP SNPs from 72 case-trio pedigree (SFTPA1 (5), SFTPA2 (4), SFTPB (4), SFTPC (2), and SFTPD (2)), and identified SP SNP associations by applying quantitative genetic principles. The results showed (a) Two SNPs, SFTPB rs7316 (p = 0.0083) and SFTPC rs1124 (p = 0.0154), each associated with CF. (b) Three intragenic SNP-SNP interactions, SFTPB (rs2077079, rs3024798), and SFTPA1 (rs1136451, rs1059057 and rs4253527), associated with CF. (c) A total of 34 intergenic SNP-SNP interactions among the 4 SP genes to be associated with CF. (d) No SNP-SNP interaction was observed between SFTPA1 or SFTPA2 and SFTPD. (e) Equal number of SNP-SNP interactions were observed between SFTPB and SFTPA1/SFTPA2 (n = 7) and SP-B and SFTPD (n = 7). (f) SFTPC exhibited significant SNP-SNP interactions with SFTPA1/SFTPA2 (n = 11), SFTPB (n = 4) and SFTPD (n = 3). (g) A single SFTPB SNP was associated with mild CF after Bonferroni correction, and several intergenic interactions that are associated (p < 0.01) with either mild or moderate/severe CF were observed. These collectively indicate that complex SNP-SNP interactions of the SP genes may contribute to the pulmonary disease in CF patients. We speculate that SPs may serve as modifiers for the varied progression of pulmonary disease in CF and/or its severity.

Many quantitative traits are composites of other traits that contribute differentially to genetic variation. Quantitative trait locus (QTL) mapping of these composite traits can benefit by incorporating the mechanistic process of how their formation is mediated by the underlying components. We propose a dissection model by which to map these interconnected components traits under a joint likelihood setting. The model can test how a composite trait is determined by pleiotropic QTLs for its component traits or jointly by different sets of QTLs each responsible for a different component. The model can visualize the pattern of time-varying genetic effects for individual components and their impacts on composite traits. The dissection model was used to map two composite traits, stemwood volume growth decomposed into its stem height, stem diameter and stem form components for Euramerican poplar adult trees, and total lateral root length constituted by its average lateral root length and lateral root number components for Euphrates poplar seedlings. We found the pattern of how QTLs for different components contribute to phenotypic variation in composite traits. The detailed understanding of the genetic machineries of composite traits will not only help in the design of molecular breeding in plants and animals, but also shed light on the evolutionary processes of quantitative traits under natural selection.

We studied the interactions in a co-culture of two bacteria.By pairwise co-culturing of 36 Escherichia coli and 36 Staphylococcus aureus strains, we monitored the growth of each species in an interaction environment. We identified numerous Single Nucleotide Polymorphisms (SNPs) by whole-genome sequencing used as genetic markers to predict variations in phenotypic traits. Genome-wide association study (GWAS) was applied to identify loci that controlled competition between the two species.In E. coli, 162 significant SNPs affected the change of maximum growth rate by comparing initials strains with those grown in co-culture, and 36 significant SNPs affected the change of maximum growth rate comparing monoculture and co-culture strains. Five of the significant E. coli genes we identified after annotation this time were also reported in other evolutionary studies. We also identified 85 significant SNPs in S. aureus that affected the change of maximum growth rate by comparing initial strains with those grown in monoculture. About the change of bacterial numbers, we found that 706 significant SNPs were associated in E. coli and 129 in S. aureus. Thirteen of the E. coli significant genes in this study were also verified in previous evolutionary reportsWe found several significant genes both in monoculture and co-culture affecting the interaction of E. coli and S. aureus. GWAS has the potential to study interspecific interactions of bacteria.

APETALA1 plays a crucial role in the transition from vegetative to reproductive phase and in floral development. In this study, to determine the effect of AP1 expression on flowering time and floral organ development, transgenic Arabidopsis and poplar overexpressing of AtAP1M3 (Arabidopsis AP1 mutant by dominant negative mutation) were generated. Transgenic Arabidopsis with e35Spro::AtAP1M3 displayed phenotypes with delayed-flowering compared to wild-type and flowers with abnormal sepals, petals and stamens. In addition, transgenic Arabidopsis plants exhibited reduced growth vigor compared to the wild-type plants. Ectopic expression of AtAP1M3 in poplar resulted in up- or down-regulation of some endogenous key flowering-related genes, including floral meristems identity gene LFY, B-class floral organ identity genes AP3 and PI, flowering pathway integrator FT1 and flower repressors TFL1 and SVP. These results suggest that AtAP1M3 regulates flowering time and floral development in plants.

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, np

How a species responds to such a biotic environment in the community, ultimately leading to its evolution, has been a topic of intense interest to ecological evolutionary biologists. Until recently, limited knowledge was available regarding the genotypic changes that underlie phenotypic changes. Our study implemented GWAS (Genome-Wide Association Studies) to illustrate the genetic architecture of ecological interactions that take place in microbial populations. By choosing 45 such interspecific pairs of Escherichia coli and Staphylococcus aureus strains that were all genotyped throughout the entire genome, we employed Q-ROADTRIPS to analyze the association between single SNPs and microbial abundance measured at each time point for bacterial populations reared in monoculture and co-culture, respectively. We identified a large number of SNPs and indels across the genomes (35.69 G clean data of E. coli and 50.41 G of S. aureus). We reported 66 and 111 SNPs that were associated with interaction in E. coli and S. aureus, respectively. 23 out of 66 polymorphic changes resulted in amino acid alterations.12 significant genes, such as murE, treA, argS, and relA, which were also identified in previous evolutionary studies. In S. aureus, 111 SNPs detected in coding sequences could be divided into 35 non-synonymous and 76 synonymous SNPs. Our study illustrated the potential of genome-wide association methods for studying rapidly evolving traits in bacteria. Genetic association study methods will facilitate the identification of genetic elements likely to cause phenotypes of interest and provide targets for further laboratory investigation.

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.

How a species responds to such a biotic environment in the community, ultimately leading to its evolution, has been a topic of intense interest to ecological evolutionary biologists. Until recently, limited knowledge was available regarding the genotypic changes that underlie phenotypic changes. Our study implemented GWAS (Genome-Wide Association Studies) to illustrate the genetic architecture of ecological interactions that take place in microbial populations. By choosing 45 such interspecific pairs of Escherichia coli and Staphylococcus aureus strains that were all genotyped throughout the entire genome, we employed Q-ROADTRIPS to analyze the association between single SNPs and microbial abundance measured at each time point for bacterial populations reared in monoculture and co-culture, respectively. We identified a large number of SNPs and indels across the genomes (35.69 G clean data of E. coli and 50.41 G of S. aureus). We reported 66 and 111 SNPs that were associated with interaction in E. coli and S. aureus, respectively. 23 out of 66 polymorphic changes resulted in amino acid alterations.12 significant genes, such as murE, treA, argS, and relA, which were also identified in previous evolutionary studies. In S. aureus, 111 SNPs detected in coding sequences could be divided into 35 non-synonymous and 76 synonymous SNPs. Our study illustrated the potential of genome-wide association methods for studying rapidly evolving traits in bacteria. Genetic association study methods will facilitate the identification of genetic elements likely to cause phenotypes of interest and provide targets for further laboratory investigation.

Genes have been thought to affect community ecology and evolution, but their identification at the whole-genome level is challenging. Here, we develop a conceptual framework for the genome-wide mapping of quantitative trait loci (QTLs) that govern interspecific competition and cooperation. This framework integrates the community ecology theory into systems mapping, a statistical model for mapping complex traits as a dynamic system. It can characterize not only how QTLs of one species affect its own phenotype directly, but also how QTLs from this species affect the phenotype of its interacting species indirectly and how QTLs from different species interact epistatically to shape community behavior. We validated the utility of the new mapping framework experimentally by culturing and comparing two bacterial species, Escherichia coli and Staphylococcus aureus, in socialized and socially isolated environments, identifying several QTLs from each species that may act as key drivers of microbial community structure and function., Genetic variation from coexisting species influences interspecific interactions in a community. Here, the authors develop a framework for identifying quantitative trait loci (QTLs) underlying community dynamics and validate the tool using data from co-culturing of two bacterial species.

Stem blister canker, caused by Botryosphaeria dothidea, is becoming the most serious disease of poplar in China. The molecular basis of the poplar in response to stem blister canker is not well understood. To reveal the global transcriptional changes of poplar to infection by B. dothidea, Solexa paired-end sequencing of complementary DNAs (cDNAs) from control (NB) and pathogen-treated samples (WB) was performed, resulting in a total of 339,283 transcripts and 183,881 unigenes. A total of 206,586 transcripts were differentially expressed in response to pathogen stress (false discovery rate ≤0.05 and an absolute value of log2Ratio (NB/WB) ≥1). In enrichment analysis, energy metabolism and redox reaction-related macromolecules were accumulated significantly in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses, indicating components of dynamic defense against the fungus. A total of 852 transcripts (575 upregulated and 277 downregulated transcripts) potentially involved in plant-pathogen interaction were also differentially regulated, including genes encoding proteins linked to signal transduction (putative leucine-rich repeat (LRR) protein kinases and calcium-binding proteins), defense (pathogenesis-related protein 1), and cofactors (jasmonate-ZIM-domain-containing proteins and heat shock proteins). Moreover, transcripts encoding glutathione S-transferase (GST) were accumulated to high levels, revealing key genes and proteins potentially related to pathogen resistance. Poplar RNA sequence data were validated by quantitative real-time PCR (RT-qPCR), which revealed a highly reliability of the transcriptomic profiling data.

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms.

De novo shoot regeneration is one of the important manifestations of cell totipotency in organogenesis, which reflects a survival strategy organism evolved when facing natural selection. Compared with tissue regeneration, and somatic embryogenesis, de novo shoot regeneration denotes a shoot regeneration process directly from detatched or injured tissues of plant. Studies on plant shoot regeneration had identified key genes mediating shoot regeneration. However, knowledge was derived from Arabidopsis, the regeneration capacity is hugely distinct among species. To achieve a comprehensive understanding of the shoot regeneration mechanism from tree species, we select four genetic lines of Populus euphratica from a natural population to be sequenced at transcriptome level. On the basis of the large difference of differentiation capacity, between the highly differentiated (HD) and low differentiated (LD) groups, the analysis of differential expression identified 4920 differentially expressed genes (DEGs), which were revealed in five groups of expression patterns by clustering analysis. Enrichment showed crucial pathways involved in regulation of regeneration difference, including &ldquo, plant hormone signal transduction&rdquo, &ldquo, cell differentiation&rdquo, "cellular response to auxin stimulus", and &ldquo, auxin-activated signaling pathway&rdquo, The expression of nine genes reported to be associated with shoot regeneration was validated using quantitative real-time PCR (qRT-PCR). For the specificity of regeneration mechanism with P. euphratica, large amount of DEGs involved in "plant-pathogen interaction", ubiquitin-26S proteosome mediated proteolysis pathway, stress-responsive DEGs, and senescence-associated DEGs were summarized to possibly account for the differentiation difference with distinct genotypes of P. euphratica. The result in this study helps screening of key regulators in mediating the shoot differentiation. The transcriptomic characteristic in P. euphratica further enhances our understanding of key processes affecting the regeneration capacity of de novo shoots among distinct species.

Vegetative phase changes in plants describes the transition between juvenile and adult phases of vegetative growth before flowering. It is one of the most fundamental mechanisms for plants to sense developmental signals, presenting a complex process involving many still-unknown determinants. Several studies in annual and perennial plants have identified the conservative roles of miR156 and its targets, SBP/SPL genes, in guiding the switch of plant growth from juvenile to adult phases. Here, we review recent progress in understanding the regulation of miR156 expression and how miR156-SPLs mediated plant age affect other processes in Arabidopsis. Powerful high-throughput sequencing techniques have provided rich data to systematically study the regulatory mechanisms of miR156 regulation network. From this data, we draw an expanded miR156-regulated network that links plant developmental transition and other fundamental biological processes, gaining novel and broad insight into the molecular mechanisms of plant-age-related processes in Arabidopsis.

Homozygous genotypes are valuable for genetic and genomic studies in higher plants. However, obtaining homozygous perennial woody plants using conventional breeding techniques is currently a challenge due to a long juvenile period, high heterozygosity, and substantial inbreeding depression. In vitro androgenesis has been used to develop haploid and doubled haploid plants. In the present study, we report the regeneration of haploid lines of poplar (Populus × beijingensis) via anther culture. Anthers at the uninucleate stage were induced to produce callus using three basic media. Two auxins (naphthalene acetic acid [NAA] and 2,4-dichloro-phenoxyacetic acid [2,4-D]), and two cytokinin (kinetin [KT] and 6-benzyladenine [BA]) were tested to explore the influence of plant growth regulators on callus response. H medium (Bourgin and Nitsch 1967) supplemented with 1.0 mg/L NAA and 1.0 mg/L KT induced the highest rate of callus formation. When callus obtained from anthers were subcultured in MS medium containing 1.0 mg/L BA and 0.2 mg/L NAA, followed by transfer to half-strength MS medium supplemented with indole-3-butyric acid (0.2–0.5 mg/L), the formation of regenerated plantlets increased dramatically. Inclusion of gibberellic acid (0.02–0.2 mg/L) in addition to a combination of BA (0.6 mg/L)-NAA (0.2 mg/L) in the culture medium resulted in enhanced frequency of shoot development, as well as greater internode elongation. Ploidy analysis of 580 regenerated plants, using both flow cytometry and chromosome counting, revealed 10.3 % haploid and 1.0 % triploid plantlets. The remaining plantlets were all diploid.

Mei (Prunus mume) is an ornamental woody plant that has been domesticated in East Asia for thousands of years. High diversity in floral traits, along with its recent genome sequence, makes mei an ideal model system for studying the evolution of woody plants. Here, we investigate the genetic architecture of floral traits in mei and its domestication history by sampling and resequencing a total of 351 samples including 348 mei accessions and three other Prunus species at an average sequencing depth of 19.3×. Highly-admixed population structure and introgression from Prunus species are identified in mei accessions. Through a genome-wide association study (GWAS), we identify significant quantitative traits locus (QTLs) and genomic regions where several genes, such as MYB108, are positively associated with petal color, stigma color, calyx color, and bud color. Results from this study shed light on the genetic basis of domestication in flowering plants, particularly woody plants., Mei (Prunus mume) is a woody tree that produces ornamental blossoms which symbolize spring in East Asia. Here, Zhang et al. resequence wild and domesticated mei to reveal considerable admixture and introgression from other Prunus species and identify loci associated with floral traits.

Summary The coordination of shoots and roots is critical for plants to adapt to changing environments by fine-tuning energy production in leaves and the availability of water and nutrients from roots. To understand the genetic architecture of how these two organs covary during developmental ontogeny, we conducted a mapping experiment using Euphrates poplar (Populus euphratica), a so-called hero tree able to grow in the desert. We geminated intraspecific F1 seeds of Euphrates Poplar individually in a tube to obtain a total of 370 seedlings, whose shoot and taproot lengths were measured repeatedly during the early stage of growth. By fitting a growth equation, we estimated asymptotic growth, relative growth rate, the timing of inflection point and duration of linear growth for both shoot and taproot growth. Treating these heterochronic parameters as phenotypes, a univariate mapping model detected 19 heterochronic quantitative trait loci (hQTLs), of which 15 mediate the forms of shoot growth and four mediate taproot growth. A bivariate mapping model identified 11 pleiotropic hQTLs that determine the covariation of shoot and taproot growth. Most QTLs detected reside within the region of candidate genes with various functions, thus confirming their roles in the biochemical processes underlying plant growth.

Abscisic acid (ABA) plays a fundamental role in plant response and adaptation to abiotic stresses, such as drought, high salinity and low temperature. Populus hopeiensis exhibits exceptional tolerance to water-deficit environments and is therefore an excellent choice for studying drought tolerance in trees. This study provides a global view of transcriptome dynamics in P. hopeiensis in response to exogenous ABA using Illumina RNA-sequencing. Endogenous ABA content increased and reached a peak at 8 h after ABA treatment and then significantly decreased at latter time points. Differential expression analysis and Gene ontology enrichment revealed that the number of transcripts exhibited significant increase during the first 8 hours after ABA treatment, which then significantly decreased at 12 and 24 h. Transcription factors (TFs) analysis showed that six different patterns were observed based on the expression of the six TFs families (AP2/ERF, NAC, MYB, MYB-related, bZIP and WRKY) and the majority of differentially expressed TFs increased rapidly after ABA treatment. This study provides a robust resource for investigating the functions of genes induced by ABA and will help to develop a better understanding of the molecular regulatory mechanism in response to drought in poplar.

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.