Thidiazuron combined with cyclanilide modulates hormone pathways and ROS systems in cotton, increasing defoliation at low temperatures.

Low temperatures decrease the thidiazuron (TDZ) defoliation efficiency in cotton, while cyclanilide (CYC) combined with TDZ can improve the defoliation efficiency at low temperatures, but the mechanism is unknown. This study analyzed the effect of exogenous TDZ and CYC application on cotton leaf abscissions at low temperatures (daily mean temperature: 15°C) using physiology and transcriptomic analysis. The results showed that compared with the TDZ treatment, TDZ combined with CYC accelerated cotton leaf abscission and increased the defoliation rate at low temperatures. The differentially expressed genes (DEGs) in cotton abscission zones (AZs) were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to compare the enriched GO terms and KEGG pathways between the TDZ treatment and TDZ combined with CYC treatment. TDZ combined with CYC could induce more DEGs in cotton leaf AZs at low temperatures, and these DEGs were related to plant hormone and reactive oxygen species (ROS) pathways. CYC is an auxin transport inhibitor. TDZ combined with CYC not only downregulated more auxin response related genes but also upregulated more ethylene and jasmonic acid (JA) response related genes at low temperatures, and it decreased the indole-3-acetic acid (IAA) content and increased the JA and 1-aminocyclopropane-1-carboxylic acid (ACC) contents, which enhanced cotton defoliation. In addition, compared with the TDZ treatment alone, TDZ combined with CYC upregulated the expression of respiratory burst oxidase homologs (RBOH) genes and the hydrogen peroxide content in cotton AZs at low temperatures, which accelerated cotton defoliation. These results indicated that CYC enhanced the TDZ defoliation efficiency in cotton by adjusting hormone synthesis and response related pathways (including auxin, ethylene, and JA) and ROS production at low temperatures.

Respiratory complex I regulates dendritic cell maturation in explant model of human tumor immune microenvironment.

BACKGROUND: Combining cytotoxic chemotherapy or novel anticancer drugs with T-cell modulators holds great promise in treating advanced cancers. However, the response varies depending on the tumor immune microenvironment (TIME). Therefore, there is a clear need for pharmacologically tractable models of the TIME to dissect its influence on mono- and combination treatment response at the individual level. METHODS: Here we establish a patient-derived explant culture (PDEC) model of breast cancer, which retains the immune contexture of the primary tumor, recapitulating cytokine profiles and CD8+T cell cytotoxic activity. RESULTS: We explored the immunomodulatory action of a synthetic lethal BCL2 inhibitor venetoclax+metformin drug combination ex vivo, discovering metformin cannot overcome the lymphocyte-depleting action of venetoclax. Instead, metformin promotes dendritic cell maturation through inhibition of mitochondrial complex I, increasing their capacity to co-stimulate CD4+T cells and thus facilitating antitumor immunity. CONCLUSIONS: Our results establish PDECs as a feasible model to identify immunomodulatory functions of anticancer drugs in the context of patient-specific TIME.

Nematic Spin Correlations Pervading the Phase Diagram of FeSe_{1-x}S_{x}.

We use resonant inelastic x-ray scattering (RIXS) at the Fe-L_{3} edge to study the spin excitations of uniaxial-strained and unstrained FeSe_{1-x}S_{x} (0≤x≤0.21) samples. The measurements on unstrained samples reveal dispersive spin excitations in all doping levels, which show only minor doping dependence in energy dispersion, lifetime, and intensity, indicating that high-energy spin excitations are only marginally affected by sulfur doping. RIXS measurements on uniaxial-strained samples reveal that the high-energy spin-excitation anisotropy observed previously in FeSe is also present in the doping range 0200 K in x=0.18 and reaches a maximum around the nematic quantum critical doping (x_{c}≈0.17). Since the spin-excitation anisotropy directly reflects the existence of nematic spin correlations, our results indicate that high-energy nematic spin correlations pervade the regime of nematicity in the phase diagram and are enhanced by the nematic quantum criticality. These results emphasize the essential role of spin fluctuations in driving electronic nematicity and highlight the capability of uniaxial strain in tuning spin excitations in quantum materials hosting strong magnetoelastic coupling and electronic nematicity.

Hub Genes in Stable QTLs Orchestrate the Accumulation of Cottonseed Oil in Upland Cotton via Catalyzing Key Steps of Lipid-Related Pathways.

Upland cotton is the fifth-largest oil crop in the world, with an average supply of nearly 20% of vegetable oil production. Cottonseed oil is also an ideal alternative raw material to be efficiently converted into biodiesel. However, the improvement in kernel oil content (KOC) of cottonseed has not received sufficient attention from researchers for a long time, due to the fact that the main product of cotton planting is fiber. Previous studies have tagged QTLs and identified individual candidate genes that regulate KOC of cottonseed. The regulatory mechanism of oil metabolism and accumulation of cottonseed are still elusive. In the current study, two high-density genetic maps (HDGMs), which were constructed based on a recombinant inbred line (RIL) population consisting of 231 individuals, were used to identify KOC QTLs. A total of forty-three stable QTLs were detected via these two HDGM strategies. Bioinformatic analysis of all the genes harbored in the marker intervals of the stable QTLs revealed that a total of fifty-one genes were involved in the pathways related to lipid biosynthesis. Functional analysis via coexpression network and RNA-seq revealed that the hub genes in the co-expression network that also catalyze the key steps of fatty acid synthesis, lipid metabolism and oil body formation pathways (ACX4, LACS4, KCR1, and SQD1) could jointly orchestrate oil accumulation in cottonseed. This study will strengthen our understanding of oil metabolism and accumulation in cottonseed and contribute to KOC improvement in cottonseed in the future, enhancing the security and stability of worldwide food supply.

Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development.

INTRODUCTION: Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. OBJECTIVES: The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. METHODS: A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. RESULTS: An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. CONCLUSION: Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.

QTL Verification and Candidate Gene Screening of Fiber Quality and Lint Percentage in the Secondary Segregating Population of Gossypium hirsutum.

Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70-10.15 Mb), A07 (85.48-93.43 Mb), and D12 (0.40-1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton fiber development.

Recovery of spatially varying acoustical properties via automated partial differential equation identification.

Observable dynamics, such as waves propagating on a surface, are generally governed by partial differential equations (PDEs), which are determined by the physical properties of the propagation media. The spatial variations of these properties lead to spatially dependent PDEs. It is useful in many fields to recover the variations from the observations of dynamical behaviors on the material. A method is proposed to form a map of the physical properties' spatial variations for a material via data-driven spatially dependent PDE identification and applied to recover acoustical properties (viscosity, attenuation, and phase speeds) for propagating waves. The proposed data-driven PDE identification scheme is based on ℓ1-norm minimization. It does not require any PDE term that is assumed active from the prior knowledge and is the first approach that is capable of identifying spatially dependent PDEs from measurements of phenomena. In addition, the method is efficient as a result of its non-iterative nature and can be robust against noise if used with an integration transformation technique. It is demonstrated in multiple experimental settings, including real laser measurements of a vibrating aluminum plate. Codes and data are available online at https://tinyurl.com/4wza8vxs.

Altered B cell immunoglobulin signature exhibits potential diagnostic values in human colorectal cancer.

Antibody-secreting B cells have long been considered the central element of gut homeostasis; however, tumor-associated B cells in human colorectal cancer (CRC) have not been well characterized. Here, we show that the clonotype, phenotype, and immunoglobulin subclasses of tumor-infiltrating B cells have changed compared to adjacent normal tissue B cells. Remarkably, the tumor-associated B cell immunoglobulin signature alteration can also be detected in the plasma of patients with CRC, suggesting that a distinct B cell response was also evoked in CRC. We compared the altered plasma immunoglobulin signature with the existing method of CRC diagnosis. Our diagnostic model exhibits improved sensitivity compared to the traditional biomarkers, CEA and CA19-9. These findings disclose the altered B cell immunoglobulin signature in human CRC and highlight the potential of using the plasma immunoglobulin signature as a non-invasive method for the assessment of CRC.

Fine mapping and candidate gene analysis of qFL-A12-5: a fiber length-related QTL introgressed from Gossypium barbadense into Gossypium hirsutum.

KEY MESSAGE: The fiber length-related qFL-A12-5 identified in CSSLs introgressed from Gossypium barbadense into Gossypium hirsutum was fine-mapped to an 18.8 kb region on chromosome A12, leading to the identification of the GhTPR gene as a potential regulator of cotton fiber length. Fiber length is a key determinant of fiber quality in cotton, and it is a key target of artificial selection for breeding and domestication. Although many fiber length-related quantitative trait loci have been identified, there are few reports on their fine mapping or candidate gene validation, thus hampering efforts to understand the mechanistic basis of cotton fiber development. Our previous study identified the qFL-A12-5 associated with superior fiber quality on chromosome A12 in the chromosome segment substitution line (CSSL) MBI7747 (BC4F3:5). A single segment substitution line (CSSL-106) screened from BC6F2 was backcrossed to construct a larger segregation population with its recurrent parent CCRI45, thus enabling the fine mapping of 2852 BC7F2 individuals using denser simple sequence repeat markers to narrow the qFL-A12-5 to an 18.8 kb region of the genome, in which six annotated genes were identified in Gossypium hirsutum. Quantitative real-time PCR and comparative analyses led to the identification of GH_A12G2192 (GhTPR) encoding a tetratricopeptide repeat-like superfamily protein as a promising candidate gene for qFL-A12-5. A comparative analysis of the protein-coding regions of GhTPR among Hai1, MBI7747, and CCRI45 revealed two non-synonymous mutations. The overexpression of GhTPR resulted in longer roots in Arabidopsis, suggesting that GhTPR may regulate cotton fiber development. These results provide a foundation for future efforts to improve cotton fiber length.

Low Temperature Inhibits the Defoliation Efficiency of Thidiazuron in Cotton by Regulating Plant Hormone Synthesis and the Signaling Pathway.

Thidiazuron (TDZ) is the main defoliant used in production to promote leaf abscission for machine-picked cotton. Under low temperatures, the defoliation rate of cotton treated with TDZ decreases and the time of defoliation is delayed, but there is little information about this mechanism. In this study, RNA-seq and physiological analysis are performed to reveal the transcriptome profiling and change in endogenous phytohormones upon TDZ treatment in abscission zones (AZs) under different temperatures (daily mean temperatures: 25 °C and 15 °C). Genes differentially expressed in AZs between TDZ treatment and control under different temperatures were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to compare the enriched GO terms and KEGG pathways between the two temperature conditions. The results show that, compared with the corresponding control group, TDZ induces many differentially expressed genes (DEGs) in AZs, and the results of the GO and KEGG analyses show that the plant hormone signaling transduction pathway is significantly regulated by TDZ. However, under low temperature, TDZ induced less DEGs, and the enriched GO terms and KEGG pathways were different with those under normal temperature condition. Many genes in the plant hormone signal transduction pathway could not be induced by TDZ under low temperature conditions. In particular, the upregulated ethylene-signaling genes and downregulated auxin-signaling genes in AZs treated with TDZ were significantly affected by low temperatures. Furthermore, the expression of ethylene and auxin synthesis genes and their content in AZs treated with TDZ were also regulated by low temperature conditions. The upregulated cell wall hydrolase genes induced by TDZ were inhibited by low temperatures. However, the inhibition of low temperature on genes in AZs treated with TDZ was relieved with the extension of the treatment time. Together, these results indicate that the responses of ethylene and auxin synthesis and the signaling pathway to TDZ are inhibited by low temperatures, which could not induce the expression of cell wall hydrolase genes, and then inhibit the separation of AZ cells and the abscission of cotton leaves. This result provides new insights into the mechanism of defoliation induced by TDZ under low temperature conditions.

Computational Analysis of Pathological Image Enables Interpretable Prediction for Microsatellite Instability.

Background: Microsatellite instability (MSI) is associated with several tumor types and has become increasingly vital in guiding patient treatment decisions; however, reasonably distinguishing MSI from its counterpart is challenging in clinical practice. Methods: In this study, interpretable pathological image analysis strategies are established to help medical experts to identify MSI. The strategies only require ubiquitous hematoxylin and eosin-stained whole-slide images and perform well in the three cohorts collected from The Cancer Genome Atlas. Equipped with machine learning and image processing technique, intelligent models are established to diagnose MSI based on pathological images, providing the rationale of the decision in both image level and pathological feature level. Findings: The strategies achieve two levels of interpretability. First, the image-level interpretability is achieved by generating localization heat maps of important regions based on deep learning. Second, the feature-level interpretability is attained through feature importance and pathological feature interaction analysis. Interestingly, from both the image-level and feature-level interpretability, color and texture characteristics, as well as their interaction, are shown to be mostly contributed to the MSI prediction. Interpretation: The developed transparent machine learning pipeline is able to detect MSI efficiently and provide comprehensive clinical insights to pathologists. The comprehensible heat maps and features in the intelligent pipeline reflect extra- and intra-cellular acid-base balance shift in MSI tumor.

Linkage and association analyses reveal that hub genes in energy-flow and lipid biosynthesis pathways form a cluster in upland cotton.

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In 'CCRI70' RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In '0-153' RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

Multi-environment Evaluations Across Ecological Regions Reveal That the Kernel Oil Content of Cottonseed Is Equally Determined by Genotype and Environment.

Cotton is the fifth-largest oil crop in the world. A high kernel oil content (KOC) and high stability are important cottonseed attributes for food security. In this study, the phenotype of KOC and the genotype-by-environment interaction factors were collectively dissected using 250 recombinant inbred lines, their parental cultivars sGK156 and 901-001, and CCRI70 across multi-environments. ANOVA and correlation analysis showed that both genotype and environment contributed significantly to KOC accumulation. Analyses of additive main effect multiplicative interaction and genotype-by-environment interaction biplot models presented the effects of genotype, environment, and genotype by environment on KOC performance and the stability of the experimental materials. Interaction network analysis revealed that meteorological and geographical factors explained 38% of the total KOC variance, with average daily rainfall contributing the largest positive impact and cumulative rainfall having the largest negative impact on KOC accumulation. This study provides insight into KOC accumulation and could direct selection strategies for improved KOC and field management of cottonseed in the future.

Automated partial differential equation identification.

Inspired by recent developments in data-driven methods for partial differential equation (PDE) estimation, we use sparse modeling techniques to automatically estimate PDEs from data. A dictionary consisting of hypothetical PDE terms is constructed using numerical differentiation. Given data, PDE terms are selected assuming a parsimonious representation, which is enforced using a sparsity constraint. Unlike previous PDE identification schemes, we make no assumptions about which PDE terms are responsible for a given field. The approach is demonstrated on synthetic and real video data, with physical phenomena governed by wave, Burgers, and Helmholtz equations. Codes are available at https://github.com/NoiseLab-RLiu/Automate-PDE-identification.

Multi-responses of O-methyltransferase genes to salt stress and fiber development of Gossypium species.

BACKGROUND: O-methyltransferases (OMTs) are an important group of enzymes that catalyze the transfer of a methyl group from S-adenosyl-L-methionine to their acceptor substrates. OMTs are divided into several groups according to their structural features. In Gossypium species, they are involved in phenolics and flavonoid pathways. Phenolics defend the cellulose fiber from dreadful external conditions of biotic and abiotic stresses, promoting strength and growth of plant cell wall. RESULTS: An OMT gene family, containing a total of 192 members, has been identified and characterized in three main Gossypium species, G. hirsutum, G. arboreum and G. raimondii. Cis-regulatory elements analysis suggested important roles of OMT genes in growth, development, and defense against stresses. Transcriptome data of different fiber developmental stages in Chromosome Substitution Segment Lines (CSSLs), Recombination Inbred Lines (RILs) with excellent fiber quality, and standard genetic cotton cultivar TM-1 demonstrate that up-regulation of OMT genes at different fiber developmental stages, and abiotic stress treatments have some significant correlations with fiber quality formation, and with salt stress response. Quantitative RT-PCR results revealed that GhOMT10_Dt and GhOMT70_At genes had a specific expression in response to salt stress while GhOMT49_At, GhOMT49_Dt, and GhOMT48_At in fiber elongation and secondary cell wall stages. CONCLUSIONS: Our results indicate that O-methyltransferase genes have multi-responses to salt stress and fiber development in Gossypium species and that they may contribute to salt tolerance or fiber quality formation in Gossypium.

Circular RNA GLIS2 promotes colorectal cancer cell motility via activation of the NF-κB pathway.

Circular RNAs (circRNAs) are a newly discovered type of biological molecule that belongs to the noncoding RNA family. Abundant evidence has shown that circRNAs are involved in the progression of various cancers. However, the particular functions of circRNAs in colorectal cancer (CRC) remain elusive. In this study, we investigated the differentially expressed circRNAs in three pairs of cancer tissue and adjacent normal tissue of CRC. We revealed that circGLIS2 expression was higher in CRC tissue and cell lines. Gain-and-loss function assays showed that circGLIS2 was involved in the regulation of cell migration. Moreover, overexpressing circGLIS2 in CRC cells activated the NF-κB pathway and induced pro-inflammatory chemokine production, which evoked tumor-associated inflammation through recruiting leukocytes. In turn, when the cancer cells were exposed to the supernatant of circGLIS2 overexpressed cancer cells, they were endowed with the ability of migration and chemokines production. Furthermore, the rescue assay confirmed that circGLIS2 activated NF-κB signaling and promoted cell migration by sponging miR-671. Overall, our study reveals that circGLIS2, acting as a potential oncogene, maintains the abnormal activation state of the NF-κB signaling pathway via the miR-671 sponge mechanism in CRC cells. This study provides a scientific basis for targeting circGLIS2 in colorectal cancer interventions.

Toosendanin-induced apoptosis in colorectal cancer cells is associated with the κ-opioid receptor/ß-catenin signaling axis.

Developing new drugs for killing colorectal cancer (CRC) cells is urgently needed. Here, we explored the antitumor effects of toosendanin (TSN) in CRC, as well as explored its antitumor mechanisms and direct targets. Cell proliferation and apoptosis were analyzed by CCK8, colony formation, real-time cell impedance and flow cytometry. The signaling pathway and Wnt activity were analyzed by Wnt luciferase activity assay, quantitative real-time PCR and western blot. The interaction between TSN and the κ-opioid receptor was analyzed by a molecular docking simulation. BALB/c nude mice were used to detect the effects of TSN on tumor growth in vivo. We found that TSN inhibited proliferation, induced G1 phase arrest and caused caspase-dependent apoptosis in both 5-FU-sensitive and 5-FU-resistant CRC cells. Moreover, TSN effectively inhibited CRC growth in vivo. In terms of the mechanism, TSN inhibited Wnt/ß-catenin signaling in CRC cells, and the molecular docking results showed that TSN could bind to κ-opioid receptors directly. Additionally, TSN-induced apoptosis and ß-catenin decline were both reversed by the selective κ-opioid receptor agonist U50,488H. Our data demonstrate that TSN-induced apoptosis in CRC cells is associated with the κ-opioid receptor/ß-catenin signaling axis, and TSN has promising potential as an antitumor agent for CRC treatment.

Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population.

Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.

Genome-wide characterization of the UDP-glycosyltransferase gene family in upland cotton.

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) involved in many metabolic processes are ubiquitous in plants, animals, microorganisms and other organisms and are essential for their growth and development. Upland cotton contains a large number of UGT genes. In this study, we aimed to identify UGT family members in the genome of upland cotton (Gossypium hirsutum L.) and analyze their expression patterns. Bioinformatics methods were used to identify UGT genes from the whole genome of upland cotton (Gossypium hirsutum L. acc. TM-1). Phylogenetic analysis was conducted based on alignment of UGT proteins from upland cotton, and the gene structure, motif and chromosome localization were analyzed for the H subgroup of the UGT family. And the physical and chemical properties and expressions of the genes in the H subgroup of this family were also analyzed. A total of 274 UGT genes were identified from the whole genome of upland cotton and were divided into nine subgroups based on phylogenetic analyses. In subgroup H, 36 genes were distributed on 18 chromosomes. The subfamily genes were simple in the structure, 19 of its members contained two introns, and the others contained only one intron. The qRT-PCR results and transcriptomic data indicated that most of the genes had a wide range of tissue expression characteristics. And the phylogenetic analysis results and expression profiles of these genes revealed tissues and different UGT genes from this crop. Taking RNA-seq, RT-qPCR, and quantitative trait locus (QTL) mapping together, our results suggested that GhUGT6 and GhUGT105 in subgroup H of the GhUGT gene family could be potential candidate genes for cotton yield, and GhUGT16, GhUGT103 might play a vital role in fiber development.

Melatonin facilitates lateral root development by coordinating PAO-derived hydrogen peroxide and Rboh-derived superoxide radical.

Melatonin, a phytochemical, can regulate lateral root (LR) formation, but the downstream signaling of melatonin remains elusive. Here we investigated the roles of hydrogen peroxide (H2O2) and superoxide radical (O2•‾) in melatonin-promoted LR formation in tomato (Solanum lycopersicum) roots by using physiological, histochemical, bioinformatic, and biochemical approaches. The increase in endogenous melatonin level stimulated reactive oxygen species (ROS)-dependent development of lateral root primordia (LRP) and LR. Melatonin promoted LRP/LR formation and modulated the expression of cell cycle genes (SlCDKA1, SlCYCD3;1, and SlKRP2) by stimulating polyamine oxidase (PAO)-dependent H2O2 production and respiratory burst oxidase homologue (Rboh)-dependent O2•‾ production, respectively. Screening of SlPAOs and SlRbohs gene family combined with gene expression analysis suggested that melatonin-promoted LR formation was correlated to the upregulation of SlPAO1, SlRboh3, and SlRboh4 in LR-emerging zone. Transient expression analysis confirmed that SlPAO1 was able to produce H2O2 while SlRboh3 and SlRboh4 were capable of producing O2•‾. Melatonin-ROS signaling cassette was also found in the regulation of LR formation in rice root and lateral hyphal branching in fungi. These results suggested that SlPAO1-H2O2 and SlRboh3/4-O2•‾ acted as downstream of melatonin to regulate the expression of cell cycle genes, resulting in LRP initiation and LR development. Such findings uncover one of the regulatory pathways for melatonin-regulated LR formation, which extends our knowledge for melatonin-regulated plant intrinsic physiology.