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.

Spatial acoustic properties recovery with deep learning.

The physics-informed neural network (PINN) can recover partial differential equation (PDE) coefficients that remain constant throughout the spatial domain directly from measurements. We propose a spatially dependent physics-informed neural network (SD-PINN), which enables recovering coefficients in spatially dependent PDEs using one neural network, eliminating the requirement for domain-specific physical expertise. The network is trained by minimizing a combination of loss functions involving data-fitting and physical constraints, in which the requirement for satisfying the assumed governing PDE is encoded. For the recovery of spatially two-dimensional (2D) PDEs, we store the PDE coefficients at all locations in the 2D region of interest into a matrix and incorporate a low-rank assumption for this matrix to recover the coefficients at locations without measurements. We apply the SD-PINN to recovering spatially dependent coefficients of the wave equation to reveal the spatial distribution of acoustic properties in the inhomogeneous medium.

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.

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.

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.

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.

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.

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.

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.

Transcriptomic and biochemical analysis of upland cotton (Gossypium hirsutum) and a chromosome segment substitution line from G. hirsutum × G. barbadense in response to Verticillium dahliae infection.

BACKGROUND: Verticillium wilt (VW), also known as "cotton cancer," is one of the most destructive diseases in global cotton production that seriously impacts fiber yield and quality. Despite numerous attempts, little significant progress has been made in improving the VW resistance of upland cotton. The development of chromosome segment substitution lines (CSSLs) from Gossypium hirsutum × G. barbadense has emerged as a means of simultaneously developing new cotton varieties with high-yield, superior fiber, and resistance to VW. RESULTS: In this study, VW-resistant investigations were first conducted in an artificial greenhouse, a natural field, and diseased nursery conditions, resulting in the identification of one stably VW-resistant CSSL, MBI8255, and one VW-susceptible G. hirsutum, CCRI36, which were subsequently subjected to biochemical tests and transcriptome sequencing during V991 infection (0, 1, and 2 days after inoculation). Eighteen root samples with three replications were collected to perform multiple comparisons of enzyme activity and biochemical substance contents. The findings indicated that VW resistance was positively correlated with peroxidase and polyphenol oxidase activity, but negatively correlated with malondialdehyde content. Additionally, RNA sequencing was used for the same root samples, resulting in a total of 77,412 genes, of which 23,180 differentially expressed genes were identified from multiple comparisons between samples. After Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on the expression profiles identified using Short Time-series Expression Miner, we found that the metabolic process in the biological process, as well as the pathways of phenylpropanoid biosynthesis and plant hormone signal transduction, participated significantly in the response to VW. Gene functional annotation and expression quantity analysis indicated the important roles of the phenylpropanoid metabolic pathway and oxidation-reduction process in response to VW, which also provided plenty of candidate genes related to plant resistance. CONCLUSIONS: This study concentrates on the preliminary response to V991 infection by comparing the VW-resistant CSSL and its VW-susceptible recurrent parent. Not only do our findings facilitate the culturing of new resistant varieties with high yield and superior performance, but they also broaden our understanding of the mechanisms of cotton resistance to VW.

QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum × Gossypium barbadense.

Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC4F3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC5F2 and BC5F2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.

Sorghum tiller bud growth is repressed by contact with the overlying leaf.

Basal branching in grasses, or tillering, is an important trait determining both form and function of crops. Although similarities exist between eudicot and grass branching programs, one notable difference is that the tiller buds of grasses are covered by the subtending leaf, whereas eudicot buds are typically unconstrained. The current study shows that contact with the leaf sheath represses sorghum bud growth by providing a mechanical signal that cues the bud to refrain from rapid growth. Leaf removal resulted in massive reprogramming of the bud transcriptome that included signatures of epigenetic modifications and also implicated several hormones in the response. Bud abscisic acid transiently increased, then decreased following leaf removal relative to controls, and abscisic acid was necessary to repress bud growth in the presence of the leaf. Jasmonic acid (JA) levels and signalling increased in buds following leaf removal. Remarkably, application of JA to buds in situ promoted growth. The repression of bud growth by leaf contact shares characteristics of thigmomorphogenic responses in other systems, including the involvement of JA, though the JA effect is opposite. The repression of bud growth by leaf contact may represent a mechanism to time tillering to an appropriate developmental stage of the plant.

Chemokine (C-X-C motif) receptor 3-positive B cells link interleukin-17 inflammation to protumorigenic macrophage polarization in human hepatocellular carcinoma.

UNLABELLED: B cells consistently represent abundant cellular components in tumors; however, direct evidence supporting a role for B cells in the immunopathogenesis of human cancers is lacking, as is specific knowledge of their trafficking mechanisms. Here, we demonstrate that chemokine (C-X-C motif) receptor 3-positive (CXCR3(+)) B cells constitute approximately 45% of B-cell infiltrate in human hepatocellular carcinoma (HCC) and that their levels are positively correlated with early recurrence of HCC. These cells selectively accumulate at the invading edge of HCC and undergo further somatic hypermutation and immunoglobulin G-secreting plasma cell differentiation. Proinflammatory interleukin-17(+) cells are important for the induction of epithelial cell-derived CXCR3 ligands CXCL9, CXCL10, and CXCL11, which subsequently promote the sequential recruitment and further maturation of CXCR3(+) B cells. More importantly, we provide evidence that CXCR3(+) B cells, but not their CXCR3(-) counterparts, may operate in immunoglobulin G-dependent pathways to induce M2b macrophage polarization in human HCC. Depletion of B cells significantly suppresses M2b polarization and the protumorigenic activity of tumor-associated macrophages and restores the production of antitumorigenic interleukin-12 by those cells in vivo. CONCLUSION: Selective recruitment of CXCR3(+) B cells bridges proinflammatory interleukin-17 response and protumorigenic macrophage polarization in the tumor milieu, and blocking CXCR3(+) B-cell migration or function may help defeat HCC.

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.

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.

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.

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.

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.