The Chinese pine genome and methylome unveil key features of conifer evolution.

Conifers dominate the world's forest ecosystems and are the most widely planted tree species. Their giant and complex genomes present great challenges for assembling a complete reference genome for evolutionary and genomic studies. We present a 25.4-Gb chromosome-level assembly of Chinese pine (Pinus tabuliformis) and revealed that its genome size is mostly attributable to huge intergenic regions and long introns with high transposable element (TE) content. Large genes with long introns exhibited higher expressions levels. Despite a lack of recent whole-genome duplication, 91.2% of genes were duplicated through dispersed duplication, and expanded gene families are mainly related to stress responses, which may underpin conifers' adaptation, particularly in cold and/or arid conditions. The reproductive regulation network is distinct compared with angiosperms. Slow removal of TEs with high-level methylation may have contributed to genomic expansion. This study provides insights into conifer evolution and resources for advancing research on conifer adaptation and development.

Transcriptome profiles reveal response mechanisms and key role of PsNAC1 in Pinus sylvestris var. mongolica to drought stress.

BACKGROUND: Drought stress severely impedes plant growth, and only a limited number of species exhibit long-term resistance to such conditions. Pinus sylvestris var. mongolica, a dominant tree species in arid and semi-arid regions of China, exhibits strong drought resistance and plays a crucial role in the local ecosystem. However, the molecular mechanisms underlying this resistance remain poorly understood. RESULTS: Here, we conducted transcriptome sequence and physiological indicators analysis of needle samples during drought treatment and rehydration stages. De-novo assembly yielded approximately 114,152 unigenes with an N50 length of 1,363 bp. We identified 6,506 differentially expressed genes (DEGs), with the majority being concentrated in the heavy drought stage (4,529 DEGs). Functional annotation revealed enrichment of drought-related GO terms such as response to water (GO:0009415: enriched 108 genes) and response to water deprivation (GO:0009414: enriched 106 genes), as well as KEGG categories including MAPK signaling pathway (K04733: enriched 35 genes) and monoterpenoid biosynthesis (K21374: enriched 27 genes). Multiple transcription factor families and functional protein families were differentially expressed during drought treatment. Co-expression network analysis identified a potential drought regulatory network between cytochrome P450 genes (Unigene4122_c1_g1) and a core regulatory transcription factor Unigene9098_c3_g1 (PsNAC1) with highly significant expression differences. We validated PsNAC1 overexpression in Arabidopsis and demonstrated enhanced drought resistance. CONCLUSIONS: These findings provide insight into the molecular basis of drought resistance in P. sylvestris var. mongolica and lay the foundation for further exploration of its regulatory network.

Temporal dynamics of genetic architecture governing leaf development in Populus.

Leaf development is a multifaceted and dynamic process orchestrated by a myriad of genes to shape the proper size and morphology. The dynamic genetic network underlying leaf development remains largely unknown. Utilizing a synergistic genetic approach encompassing dynamic genome-wide association study (GWAS), time-ordered gene co-expression network (TO-GCN) analyses and gene manipulation, we explored the temporal genetic architecture and regulatory network governing leaf development in Populus. We identified 42 time-specific and 18 consecutive genes that displayed different patterns of expression at various time points. We then constructed eight TO-GCNs that covered the cell proliferation, transition, and cell expansion stages of leaf development. Integrating GWAS and TO-GCN, we postulated the functions of 27 causative genes for GWAS and identified PtoGRF9 as a key player in leaf development. Genetic manipulation via overexpression and suppression of PtoGRF9 revealed its primary influence on leaf development by modulating cell proliferation. Furthermore, we elucidated that PtoGRF9 governs leaf development by activating PtoHB21 during the cell proliferation stage and attenuating PtoLD during the transition stage. Our study provides insights into the dynamic genetic underpinnings of leaf development and understanding the regulatory mechanism of PtoGRF9 in this dynamic process.

Comparative transcriptome profiling reveals cold stress responsiveness in two contrasting Chinese jujube cultivars.

BACKGROUND: Low temperature is a major factor influencing the growth and development of Chinese jujube (Ziziphus jujuba Mill.) in cold winter and spring. Little is known about the molecular mechanisms enabling jujube to cope with different freezing stress conditions. To elucidate the freezing-related molecular mechanism, we conducted comparative transcriptome analysis between 'Dongzao' (low freezing tolerance cultivar) and 'Jinsixiaozao' (high freezing tolerance cultivar) using RNA-Seq. RESULTS: More than 20,000 genes were detected at chilling (4 °C) and freezing (- 10 °C, - 20 °C, - 30 °C and - 40 °C) stress between the two cultivars. The numbers of differentially expressed genes (DEGs) between the two cultivars were 1831, 2030, 1993, 1845 and 2137 under the five treatments. Functional enrichment analysis suggested that the metabolic pathway, response to stimulus and catalytic activity were significantly enriched under stronger freezing stress. Among the DEGs, nine participated in the Ca2+ signal pathway, thirty-two were identified to participate in sucrose metabolism, and others were identified to participate in the regulation of ROS, plant hormones and antifreeze proteins. In addition, important transcription factors (WRKY, AP2/ERF, NAC and bZIP) participating in freezing stress were activated under different degrees of freezing stress. CONCLUSIONS: Our research first provides a more comprehensive understanding of DEGs involved in freezing stress at the transcriptome level in two Z. jujuba cultivars with different freezing tolerances. These results may help to elucidate the molecular mechanism of freezing tolerance in jujube and also provides new insights and candidate genes for genetically enhancing freezing stress tolerance.

Mapping morphological shape as a high-dimensional functional curve.

Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000-4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of 'function' instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do.

The genetic architecture of shoot-root covariation during seedling emergence of a desert tree, Populus euphratica.

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.

Allotetraploid and autotetraploid models of linkage analysis.

As a group of important plant species in agriculture and biology, polyploids have been increasingly studied in terms of their genome structure and organization. There are two types of polyploids, allopolyploids and autopolyploids, each resulting from a different genetic origin, which undergo meiotic divisions of a distinct complexity. A set of statistical models has been developed for linkage analysis, respectively for each type, by taking into account their unique meiotic behavior, i.e. preferential pairing for allopolyploids and double reduction for autopolyploids. We synthesized these models and modified them to accommodate the linkage analysis of less informative dominant markers. By reanalysing a published data set of varying ploidy in Arabidopsis, we corrected the estimates of the meiotic recombination frequency aimed to study the significance of polyploidization.

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.

A QTL model to map the common genetic basis for correlative phenotypic plasticity.

As an important mechanism for adaptation to heterogeneous environment, plastic responses of correlated traits to environmental alteration may also be genetically correlated, but less is known about the underlying genetic basis. We describe a statistical model for mapping specific quantitative trait loci (QTLs) that control the interrelationship of phenotypic plasticity between different traits. The model is constructed by a bivariate mixture setting, implemented with the EM algorithm to estimate the genetic effects of QTLs on correlative plastic response. We provide a series of procedure that test (1) how a QTL controls the phenotypic plasticity of a single trait; and (2) how the QTL determines the correlation of environment-induced changes of different traits. The model is readily extended to test how epistatic interactions among QTLs play a part in the correlations of different plastic traits. The model was validated through computer simulation and used to analyse multi-environment data of genetic mapping in winter wheat, showing its utilization in practice.

An allometric model for mapping seed development in plants.

Despite a tremendous effort to map quantitative trait loci (QTLs) responsible for agriculturally and biologically important traits in plants, our understanding of how a QTL governs the developmental process of plant seeds remains elusive. In this article, we address this issue by describing a model for functional mapping of seed development through the incorporation of the relationship between vegetative and reproductive growth. The time difference of reproductive from vegetative growth is described by Reeve and Huxley's allometric equation. Thus, the implementation of this equation into the framework of functional mapping allows dynamic QTLs for seed development to be identified more precisely. By estimating and testing mathematical parameters that define Reeve and Huxley's allometric equations of seed growth, the dynamic pattern of the genetic effects of the QTLs identified can be analyzed. We used the model to analyze a soybean data, leading to the detection of QTLs that control the growth of seed dry weight. Three dynamic QTLs, located in two different linkage groups, were detected to affect growth curves of seed dry weight. The QTLs detected may be used to improve seed yield with marker-assisted selection by altering the pattern of seed development in a hope to achieve a maximum size of seeds at a harvest time.

Shape mapping: genetic mapping meets geometric morphometrics.

Knowledge about biological shape has important implications in biology and biomedicine, but the underlying genetic mechanisms for shape variation have not been well studied. Statistical models play a pivotal role in mapping specific quantitative trait loci (QTLs) that contribute to biological shape and its developmental trajectories. We describe and assess a statistical framework for shape gene identification that incorporates shape and image analysis into a mixture-model framework for QTL mapping. Statistical parameters that define genotype-specific differences in biological shape are estimated by implementing statistical and computational algorithms. A state-of-the-art procedure is described to examine the control patterns of specific QTLs on the origin, properties and functions of biological shape. The statistical framework described will help to address many integrative biological and genetic questions and challenges in shape variation faced by the life sciences community.

Systems mapping: how to map genes for biomass allocation toward an ideotype.

The recent availability of high-throughput genetic and genomic data allows the genetic architecture of complex traits to be systematically mapped. The application of these genetic results to design and breed new crop types can be made possible through systems mapping. Systems mapping is a computational model that dissects a complex phenotype into its underlying components, coordinates different components in terms of biological laws through mathematical equations and maps specific genes that mediate each component and its connection with other components. Here, we present a new direction of systems mapping by integrating this tool with carbon economy. With an optimal spatial distribution of carbon fluxes between sources and sinks, plants tend to maximize whole-plant growth and competitive ability under limited availability of resources. We argue that such an economical strategy for plant growth and development, once integrated with systems mapping, will not only provide mechanistic insights into plant biology, but also help to spark a renaissance of interest in ideotype breeding in crops and trees.

A statistical procedure to map high-order epistasis for complex traits.

Genetic interactions or epistasis have been thought to play a pivotal role in shaping the formation, development and evolution of life. Previous work focused on lower-order interactions between a pair of genes, but it is obviously inadequate to explain a complex network of genetic interactions and pathways. We review and assess a statistical model for characterizing high-order epistasis among more than two genes or quantitative trait loci (QTLs) that control a complex trait. The model includes a series of start-of-the-art standard procedures for estimating and testing the nature and magnitude of QTL interactions. Results from simulation studies and real data analysis warrant the statistical properties of the model and its usefulness in practice. High-order epistatic mapping will provide a routine procedure for charting a detailed picture of the genetic regulation mechanisms underlying the phenotypic variation of complex traits.

A synthetic framework for modeling the genetic basis of phenotypic plasticity and its costs.

The phenotype of an individual is controlled not only by its genes, but also by the environment in which it grows. A growing body of evidence shows that the extent to which phenotypic changes are driven by the environment, known as phenotypic plasticity, is also under genetic control, but an overall picture of genetic variation for phenotypic plasticity remains elusive. Here, we develop a model for mapping quantitative trait loci (QTLs) that regulate environment-induced plastic response. This model enables geneticists to test whether there exist actual QTLs that determine phenotypic plasticity and, if there are, further test how plasticity QTLs control the costs of plastic response by dissecting the genetic correlation of phenotypic plasticity and trait value. The model was used to analyze real data for grain yield of winter wheat (Triticum aestivum), leading to the detection of pleiotropic QTLs and epistatic QTLs that affect phenotypic plasticity and its cost in this crop.

Genetic diversity and population structure of the Tibetan poplar (Populus szechuanica var. tibetica) along an altitude gradient.

BACKGROUND: The Tibetan poplar (Populus szechuanica var. tibetica Schneid), which is distributed at altitudes of 2,000-4,500 m above sea level, is an ecologically important species of the Qinghai-Tibet Plateau and adjacent areas. However, the genetic adaptations responsible for its ability to cope with the harsh environment remain unknown. RESULTS: In this study, a total of 24 expressed sequence tag microsatellite (EST-SSR) markers were used to evaluate the genetic diversity and population structure of Tibetan poplars along an altitude gradient. The 172 individuals were of genotypes from low-, medium- and high-altitude populations, and 126 alleles were identified. The expected heterozygosity (HE) value ranged from 0.475 to 0.488 with the highest value found in low-altitude populations and the lowest in high-altitude populations. Genetic variation was low among populations, indicating a limited influence of altitude on microsatellite variation. Low genetic differentiation and high levels of gene flow were detected both between and within the populations along the altitude gradient. An analysis of molecular variance (AMOVA) showed that 6.38% of the total molecular variance was attributed to diversity between populations, while 93.62% variance was associated with differences within populations. There was no clear correlation between genetic variation and altitude, and a Mantel test between genetic distance and altitude resulted in a coefficient of association of r = 0.001, indicating virtually no correlation. CONCLUSION: Microsatellite genotyping results showing genetic diversity and low differentiation suggest that extensive gene flow may have counteracted local adaptations imposed by differences in altitude. The genetic analyses carried out in this study provide new insight for conservation and optimization of future arboriculture.

Genome-wide analysis of salt-responsive and novel microRNAs in Populus euphratica by deep sequencing.

BACKGROUND: Populus euphratica is a representative model woody plant species for studying resistance to abiotic stresses such as drought and salt. Salt stress is one of the most common environmental factors that affect plant growth and development. MicroRNAs (miRNAs) are small, noncoding RNAs that have important regulatory functions in plant growth, development, and response to abiotic stress. RESULTS: To investigate the miRNAs involved in the salt-stress response, we constructed four small cDNA libraries from P. euphratica plantlets treated with or without salt (300 mM NaCl, 3 days) in either the root or leaf. Using high-throughput sequencing to identify miRNAs, we found 164 conserved miRNAs belonging to 44 families. Of these, 136 novel miRNAs were from the leaf, and 128 novel miRNAs were from the root. In response to salt stress, 95 miRNAs belonging to 46 conserved miRNAs families changed significantly, with 56 miRNAs upregulated and 39 miRNAs downregulated in the leaf. A comparison of the leaf and root tissues revealed 155 miRNAs belonging to 63 families with significantly altered expression, including 84 upregulated and 71 downregulated miRNAs. Furthermore, 479 target genes in the root and 541 targets of novel miRNAs in the leaf were predicted, and functional information was annotated using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. CONCLUSIONS: This study provides a novel visual field for understanding the regulatory roles of miRNAs in response to salt stress in Populus.

[Analysis and Evaluation of Heavy Metal Pollution in Farmland Soil in China：A Meta-analysis].

In this study, a Meta-analysis was used to investigate the pollution status of eight farmland soil heavy metal elements (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in China. Meanwhile, their spatiotemporal changes and differences between different types of cultivated land were explored. The research data were chosen from 449 relevant literature data collected by CNKI and Web of Science from 2005 to 2021, and the Meta-analysis used a weighted method based on "sampling numbers", "study area", and "standard deviation". The results showed that the national average values of the eight heavy metal elements in Chinese farmland soil were ω(As)11.00 mg·kg-1, ω(Cd)0.350 2 mg·kg-1, ω(Cr)62.91 mg·kg-1, ω(Cu)28.87 mg·kg-1, ω(Hg)0.135 1 mg·kg-1, ω(Ni)28.91 mg·kg-1, ω(Pb)34.67 mg·kg-1,and ω(Zn)90.24 mg·kg-1. Compared with their background values, all elements except As accumulated to some extent, and Cd and Hg accumulated the most, exceeding their background values by 177.9% and 340.3%, respectively. The research results indicated that Cd and Hg were the main pollution elements in farmland soil in China, and their accumulation was mainly influenced by human activities. In terms of their temporal and spatial changes, the Yunnan-Guizhou Plateau and the eastern coast were the most concentrated areas of pollution cases, and the pollution center shifted from the middle reaches of the Yangtze River to the southwest over time. The accumulation of heavy metals in farmland soil was affected by crop planting types, and the accumulation of heavy metals in vegetable and paddy soil was significantly greater than that in other cultivated land types.

Identification of Key Genes of Fruit Shape Variation in Jujube with Integrating Elliptic Fourier Descriptors and Transcriptome.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

Volatile Profile Characterization of Jujube Fruit via HS-SPME-GC/MS and Sensory Evaluation.

Current research does not fully elucidate the key compounds and their mechanisms that define the aroma profile of fresh jujube fruits. Therefore, this study conducted a comprehensive analysis of both free and glycosidically bound aroma compounds in fresh jujube fruits of ten cultivars. Utilizing gas chromatography-mass spectrometry (GC-MS), we identified 76 volatile free aroma compounds and 19 glycosidically bound volatile compounds, with esters, aldehydes, and ketones emerging as the predominant volatile compounds in the jujube fruits. Odor activity value (OAV) analysis revealed that the primary aroma profile of the jujubes is characterized by fruity and fatty odors, with ß-damascenone being a key contributor to the fruity aroma, and (E)-2-oct-en-1-al and nonanal significantly influencing the fatty aroma. Moreover, the integration of sensory evaluation and partial least squares regression (PLSR) analysis pinpointed octanal, (E)-2-oct-en-1-al, nonanal, ß-damascenone, and pentanal as significant contributors to the jujube's characteristic aroma, while isoamyl acetate was identified as significantly influencing the fatty acid taste. This study not only underscores the complexity of the jujube aroma composition but also highlights the impact of environmental factors on aroma profiles, offering valuable insights into the sensory characteristics of jujube fruits.

HPLC-MS/MS-based and transcriptome analysis reveal the effects of ABA and MeJA on jujube (Ziziphus jujuba Mill.) cracking.

Fruit cracking is a physiological disease that occurs during the development of jujube, abscisic acid (ABA) and jasmonic acid (JA) mainly regulate the cell wall metabolic pathway and induce fruit cracking. Here, we used high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) to detect phytohormone-related metabolites at different developmental stages in cracking-susceptible (CS-15) and cracking-resistant (CR-04) individuals of full-sibling hybrid offspring. The fruit of 'Pingshunbenzao' jujube was treated with ABA and MeJA at the white-ripening stage, and the 48-h fruit cracking index was significantly increased compared to that of CK (water). Furthermore, RNA-seq of semi-red stage fruits identified several differentially expressed genes, related to the cell wall, such as SBT1.7 (Contig21.0.484), EXPA (Contig12.0.7) and QRT3 (newGene_1935), and transcription factors (TFs). These results reveal the relationship between the levels of different hormones and fruit cracking, identify genes associated with fruit cracking, and provide new insights to solve the problem of fruit cracking through hormonal regulation.