G protein γ subunit modulates expression of plant-biomass-degrading enzyme genes and mycelial-development-related genes in Penicillium oxalicum.

Heterotrimeric-G-protein-mediated signaling pathways modulate the expression of the essential genes in many fundamental cellular processes in fungi at the transcription level. However, these processes remain unclear in Penicillium oxalicum. In this study, we generated knockout and knockout-complemented strains of gng-1 (POX07071) encoding the Gγ protein and found that GNG-1 modulated the expression of genes encoding plant-biomass-degrading enzymes (PBDEs) and sporulation-related activators. Interestingly, GNG-1 affected expression of the cxrB that encodes a known transcription factor required for the expression of major cellulase and xylanase genes. Constitutive overexpression of cxrB in ∆gng-1 circumvented the dependence of PBDE production on GNG-1. Further evidence indicated that CxrB indirectly regulated the transcription levels of key amylase genes by controlling the expression of the regulatory gene amyR. These data extended the diversity of Gγ protein functions and provided new insight into the signal transduction and regulation of PBDE gene expression in filamentous fungi. KEY POINTS: • GNG-1 modulates the expression of PBDE genes and sporulation-related genes. • GNG-1 controls expression of the key regulatory gene cxrB. • Overexpression of cxrB circumvents dependence of PBDE production on GNG-1.

A mitogen-activated protein kinase PoxMK1 mediates regulation of the production of plant-biomass-degrading enzymes, vegetative growth, and pigment biosynthesis in Penicillium oxalicum.

Mitogen-activated protein kinase (MAPK) cascades are broadly conserved and play essential roles in multiple cellular processes, including fungal development, pathogenicity, and secondary metabolism. Their function, however, also exhibits species and strain specificity. Penicillium oxalicum secretes plant-biomass-degrading enzymes (PBDEs) that contribute to the carbon cycle in the natural environment and to utilization of lignocellulose in industrial processes. However, knowledge of the MAPK pathway in P. oxalicum has been relatively limited. In this study, comparative transcriptomic analysis of P. oxalicum, cultured on different carbon sources, found ten putative kinase genes with significantly modified transcriptional levels. Six of these putative kinase genes were knocked out in the parental strain ∆PoxKu70, and deletion of the gene, Fus3/Kss1-like PoxMK1 (POX00158), resulted in the largest reduction (91.1%) in filter paper cellulase production. Further tests revealed that the mutant ∆PoxMK1 lost 37.1 to 92.2% of PBDE production, under both submerged- and solid-state fermentation conditions, compared with ∆PoxKu70. In addition, the mutant ∆PoxMK1 had reduced vegetative growth and increased pigment biosynthesis. Comparative transcriptomic analysis showed that PoxMK1 deletion from P. oxalicum downregulated the expression of major PBDE genes and known regulatory genes such as PoxClrB and PoxCxrB, whereas the transcription of pigment biosynthesis-related genes was upregulated. Comparative phosphoproteomic analysis revealed that PoxMK1 deletion considerably modified phosphorylation of key transcription- and signal transduction-associated proteins, including transcription factors Mcm1 and Atf1, RNA polymerase II subunits Rpb1 and Rpb9, MAPK-associated Hog1 and Ste7, and cyclin-dependent kinase Kin28. These findings provide novel insights into understanding signal transduction and regulation of PBDE gene expression in fungi.Key points• PoxMK1 is involved in expression of PBDE- and pigment synthesis-related genes.• PoxMK1 is required for vegetative growth of P. oxalicum.• PoxMK1 is involved in phosphorylation of key TFs, kinases, and RNA polymerase II.

Probucol decreases homocysteine-stimulated CRP production in rat aortic smooth muscle cells via regulating HO-1/NADPH oxidase/ROS/p38 pathway.

The elevated homocysteine level is an independent risk factor for atherosclerosis, which is characterized as a chronic inflammatory disease associated with oxidative stress. We have confirmed that homocysteine can stimulate the production of C-reactive protein (CRP) in rat aortic smooth muscle cells (RASMCs). In the present study, we investigated the role of probucol in homocysteine-induced CRP expression in cultured RASMCs and high-methionine-diet-induced hyperhomocysteinemic rats. The results showed that probucol decreased homocysteine-induced CRP mRNA and protein expression in RASMCs in a concentration-dependent manner. In addition, the animal experiment showed that probucol not only inhibited CRP expression in the vessel wall but also reduced the circulating CRP level in hyperhomocysteinemic rats. Further investigations revealed that probucol markedly increased heme oxygenase-1 activity, suppressed nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity, diminished superoxide anion generation, and decreased p38 phosphorylation in RASMCs and hyperhomocysteinemic rat aorta. These data demonstrate that probucol can inhibit homocysteine-induced CRP generation by interfering with the NADPH oxidase/p38 signal pathway in RASMCs, which will provide new evidence for the anti-inflammatory and anti-atherosclerotic effects of probucol.

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.

TIPE1 promotes cervical cancer progression by repression of p53 acetylation and is associated with poor cervical cancer outcome.

Previous studies have shown that TIPE1 inhibits tumor proliferation and metastasis in certain cancers; however, increased expression of TIPE1 is observed in cervical cancer cell lines and tissues, indicating it might exert a distinctive role in cervical cancer. Cell and xenograft tumorigenicity assays showed that TIPE1 facilitates cervical cancer progression in this study. Further investigation demonstrated that TIPE1 binds to p53 and impairs its activity via inhibition of its acetylation. In addition, TIPE1 promoted cell proliferation and suppressed cisplatin susceptibility in a p53-dependent manner, indicating that TIPE1 facilitates cervical cancer progression primarily through the p53 pathway. TIPE1 expression in clinical samples also demonstrated that its upregulation predicts poor prognosis in patients with cervical cancer. Taken together, the results of this study showed that TIPE1 serves as an oncogene by restricting p53 activity in the development of cervical cancer, suggesting that TIPE1 will provide a new potential target for cervical cancer therapy and can be used as a biomarker to predict patient prognosis.

Genome-wide identification, characterization, and expression analysis of the expansin gene family in Chinese jujube (Ziziphus jujuba Mill.).

Main conclusion 30 expansin genes were identified in the jujube genome. Phylogenetic analysis classified expansins into 17 subgroups. Closely related expansins share a conserved gene structure. ZjEXPs had different expression patterns in different tissues. Plant-specific expansins were first discovered as pH-dependent cell-wall-loosening proteins involved in diverse physiological processes. No comprehensive analysis of the expansin gene family has yet been carried out at the whole genome level in Chinese jujube (Ziziphus jujuba Mill.). In this study, 30 expansin genes were identified in the jujube genome. These genes, which were distributed with varying densities across 10 of the 12 jujube chromosomes, could be divided into four subfamilies: 19 ZjEXPAs, 3 ZjEXPBs, 1 ZjEXLA, and 7 ZjEXLBs. Phylogenetic analysis of expansin genes in Arabidopsis, rice, apple, grape, and jujube classified these genes into 17 subgroups. Members of the same subfamily and subgroup shared conserved gene structure and motif compositions. Homology analysis identified 20 homologous gene pairs between jujube and Arabidopsis. Further analysis of ZjEXP gene promoter regions uncovered various growth, development and stress-responsive cis-acting elements. Expression analysis and transcript profiling revealed that ZjEXPs had different expression patterns in different tissues at various developmental stages. ZjEXPA4 and ZjEXPA6 were highly expressed in young fruits, ZjEXPA3 and ZjEXPA5 were significantly expressed in flowers, and ZjEXPA7 was specifically expressed in young leaves. The results of this study, the first systematic analysis of the jujube expansin gene family, can serve as a strong foundation for further elucidation of the physiological functions and biological roles of jujube expansin genes.

The Jujube Genome Provides Insights into Genome Evolution and the Domestication of Sweetness/Acidity Taste in Fruit Trees.

Jujube (Ziziphus jujuba Mill.) belongs to the Rhamnaceae family and is a popular fruit tree species with immense economic and nutritional value. Here, we report a draft genome of the dry jujube cultivar 'Junzao' and the genome resequencing of 31 geographically diverse accessions of cultivated and wild jujubes (Ziziphus jujuba var. spinosa). Comparative analysis revealed that the genome of 'Dongzao', a fresh jujube, was ~86.5 Mb larger than that of the 'Junzao', partially due to the recent insertions of transposable elements in the 'Dongzao' genome. We constructed eight proto-chromosomes of the common ancestor of Rhamnaceae and Rosaceae, two sister families in the order Rosales, and elucidated the evolutionary processes that have shaped the genome structures of modern jujubes. Population structure analysis revealed the complex genetic background of jujubes resulting from extensive hybridizations between jujube and its wild relatives. Notably, several key genes that control fruit organic acid metabolism and sugar content were identified in the selective sweep regions. We also identified S-locus genes controlling gametophytic self-incompatibility and investigated haplotype patterns of the S locus in the jujube genomes, which would provide a guideline for parent selection for jujube crossbreeding. This study provides valuable genomic resources for jujube improvement, and offers insights into jujube genome evolution and its population structure and domestication.

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.

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.

Genome-Wide Organization and Expression Profiling of the SBP-Box Gene Family in Chinese Jujube (Ziziphus jujuba Mill.).

Transcription factors play vital roles in the developmental processes of plants. The SQUAMOSA promoter binding protein (SBP) genes encode a family of plant-specific transcription factors and plays many crucial roles in plant development. In this study, 16 SBP-box gene family members were identified in Ziziphus jujuba Mill. Dongzao (Dongzao), which were distributed over 8 chromosomes. They were classified into seven groups according to their phylogenetic relationships with other SBP-box gene families. Within each group, genes shared similar exon-intron structures and motif locations. The number of exons varied among the groups. We identified 12 homologous gene pairs between Dongzao and Arabidopsis. Expression profiling revealed that ZjSBP02 and ZjSBP14 expressed highly in mature fruits, ZjSBP01 expressed higher in mature leaves than other tissues and the expression level of ZjSBP12 was much higher in the flowers. The transcriptome analysis indicated that ZjSBPs had different expression patterns in various tissues. This study represents the first systematic analysis of the SBP-box gene family in Z. jujuba. The data presented here provides a foundation for understanding the crucial roles of ZjSBP genes in plant growth and development.

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.

Structural mapping: how to study the genetic architecture of a phenotypic trait through its formation mechanism.

Traditional approaches for genetic mapping are to simply associate the genotypes of a quantitative trait locus (QTL) with the phenotypic variation of a complex trait. A more mechanistic strategy has emerged to dissect the trait phenotype into its structural components and map specific QTLs that control the mechanistic and structural formation of a complex trait. We describe and assess such a strategy, called structural mapping, by integrating the internal structural basis of trait formation into a QTL mapping framework. Electrical impedance spectroscopy (EIS) has been instrumental for describing the structural components of a phenotypic trait and their interactions. By building robust mathematical models on circuit EIS data and embedding these models within a mixture model-based likelihood for QTL mapping, structural mapping implements the EM algorithm to obtain maximum likelihood estimates of QTL genotype-specific EIS parameters. The uniqueness of structural mapping is to make it possible to test a number of hypotheses about the pattern of the genetic control of structural components. We validated structural mapping by analyzing an EIS data collected for QTL mapping of frost hardiness in a controlled cross of jujube trees. The statistical properties of parameter estimates were examined by simulation studies. Structural mapping can be a powerful alternative for genetic mapping of complex traits by taking account into the biological and physical mechanisms underlying their formation.

A statistical model for QTL mapping in polysomic autotetraploids underlying double reduction.

As a group of economically important species, linkage mapping of polysomic autotetraploids, including potato, sugarcane and rose, is difficult to conduct due to their unique meiotic property of double reduction that allows sister chromatids to enter into the same gamete. We describe and assess a statistical model for mapping quantitative trait loci (QTLs) in polysomic autotetraploids. The model incorporates double reduction, built in the mixture model-based framework and implemented with the expectation-maximization algorithm. It allows the simultaneous estimation of QTL positions, QTL effects and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We performed computer simulation to examine the statistical properties of the method and validate its use through analyzing real data in tetraploid switchgrass.

A dynamic framework for quantifying the genetic architecture of phenotypic plasticity.

Despite its central role in the adaptation and microevolution of traits, the genetic architecture of phenotypic plasticity, i.e. multiple phenotypes produced by a single genotype in changing environments, remains elusive. We know little about the genes that underlie the plastic response of traits to the environment, their number, chromosomal locations and genetic interactions as well as environment impact on their effects. Here we review key statistical approaches for analyzing the genetic variation of phenotypic plasticity due to genotype-environment interactions and describe the implementation of a dynamic model to map specific quantitative trait loci (QTLs) that affect the gradient expression of a quantitative trait across a range of environments. This dynamic model is distinct by incorporating mathematical aspects of phenotypic plasticity into a QTL mapping framework, thereby better unraveling the quantitative attribute of trait response to the environment. By testing the curve parameters that specify environment-dependent trajectories of the trait, the model allows a series of fundamental hypotheses to be tested in a quantitative way about the interplay between gene action/interaction and environmental sensitivity. The model can also make the dynamic prediction of genetic control over phenotypic plasticity within the context of changing environments. We demonstrate the usefulness of the model by reanalyzing a QTL data set for rice, gleaning new insights into the genetic basis for phenotypic plasticity in plant height growth.

A unifying framework for bivalent multilocus linkage analysis of allotetraploids.

An allotetraploid has four paired sets of chromosomes derived from different diploid species, whose meiotic behavior is qualitatively different from the underlying diploids. According to a traditional view, meiotic pairing occurs only between homologous chromosomes, but new evidence indicates that homoeologous chromosomes may also pair to a lesser extent compared with homolog pairing. Here, we describe and assess a unifying analytical framework that incorporates differential chromosomal pairing into a multilocus linkage model. The preferential pairing factor is used to quantify the probability difference of pairing occurring between homologous chromosomes and homoeologous chromosomes. The unifying framework allows simultaneous estimation of the linkage, genetic interference and preferential pairing factor using commonly existing multiplex markers. We compared the unifying approach and traditional approaches assuming random chromosomal pairing by analyzing marker data collected in a full-sib family of tetraploid switchgrass, a bioenergy species whose diploid origins are undefined, but with subgenomes that are genetically well differentiated. The unifying framework provides a better tool for estimating the meiotic linkage and constructing a genetic map for allotetraploids.

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 multivalent three-point linkage analysis model of autotetraploids.

Because of its widespread occurrence and role in shaping evolutionary processes in the biological kingdom, especially in plants, polyploidy has been increasingly studied from cytological to molecular levels. By inferring gene order, gene distances and gene homology, linkage mapping with molecular markers has proven powerful for investigating genome structure and organization. Here we review and assess a general statistical model for three-point linkage analysis in autotetraploids by integrating double reduction, a phenomenon that commonly occurs in autopolyploids whose chromosomes are derived from a single ancestral species. This model does not require any assumption on the distribution of the occurrence of double reduction and can handle the complexity of multilocus linkage in terms of crossover interference. Implemented with the expectation-maximization (EM) algorithms, the model can estimate and test the recombination fractions between less informative dominant markers, thus facilitating its practical implications for any autopolyploids in most of which inexpensive dominant markers are still used for their genetic and evolutionary studies. The model was applied to reanalyze a published data in tetraploid switchgrass, validating its practical usefulness and utilization.

Functional mapping of ontogeny in flowering plants.

All organisms face the problem of how to perform a sequence of developmental changes and transitions during ontogeny. We revise functional mapping, a statistical model originally derived to map genes that determine developmental dynamics, to take into account the entire process of ontogenetic growth from embryo to adult and from the vegetative to reproductive phase. The revised model provides a framework that reconciles the genetic architecture of development at different stages and elucidates a comprehensive picture of the genetic control mechanisms of growth that change gradually from a simple to a more complex level. We use an annual flowering plant, as an example, to demonstrate our model by which to map genes and their interactions involved in embryo and postembryonic growth. The model provides a useful tool to study the genetic control of ontogenetic growth in flowering plants and any other organisms through proper modifications based on their biological characteristics.

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.

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.