Spatial Expression Research Articles

An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis

Spiders are a diverse order of chelicerates that diverged from other arthropods over 500 million years ago. Research on spider embryogenesis, particularly studies using the common house spider Parasteatoda tepidariorum, has made important contributions to understanding the evolution of animal development, including axis formation, segmentation, and patterning. However, we lack knowledge about the cells that build spider embryos, their gene expression profiles and fate. Single-cell transcriptomic analyses have been revolutionary in describing these complex landscapes of cellular genetics in a range of animals. Therefore, we carried out single-cell RNA sequencing of P. tepidariorum embryos at stages 7, 8 and 9, which encompass the establishment and patterning of the body plan, and initial differentiation of many tissues and organs. We identified 20 cell clusters, from 18.5 k cells, which were marked by many developmental toolkit genes, as well as a plethora of genes not previously investigated. We found differences in the cell cycle transcriptional signatures, suggestive of different proliferation dynamics, which related to distinctions between endodermal and some mesodermal clusters, compared with ectodermal clusters. We identified many Hox genes as markers of cell clusters, and Hox gene ohnologs were often present in different clusters. This provided additional evidence of sub- and/or neo-functionalisation of these important developmental genes after the whole genome duplication in an arachnopulmonate ancestor (spiders, scorpions, and related orders). We also examined the spatial expression of marker genes for each cluster to generate a comprehensive cell atlas of these embryonic stages. This revealed new insights into the cellular basis and genetic regulation of head patterning, hematopoiesis, limb development, gut development, and posterior segmentation. This atlas will serve as a platform for future analysis of spider cell specification and fate, and studying the evolution of these processes among animals at cellular resolution.

Unfolding the ventral nerve center of chaetognaths

BackgroundChaetognaths are a clade of marine worm-like invertebrates with a heavily debated phylogenetic position. Their nervous system superficially resembles the protostome type, however, knowledge regarding the molecular processes involved in neurogenesis is lacking. To better understand these processes, we examined the expression profiles of marker genes involved in bilaterian neurogenesis during post-embryonic stages of Spadella cephaloptera. We also investigated whether the transcription factor encoding genes involved in neural patterning are regionally expressed in a staggered fashion along the mediolateral axis of the nerve cord as it has been previously demonstrated in selected vertebrate, insect, and annelid models.MethodsThe expression patterns of genes involved in neural differentiation (elav), neural patterning (foxA, nkx2.2, pax6, pax3/7, and msx), and neuronal function (ChAT and VAChT) were examined in S. cephaloptera hatchlings and early juveniles using whole-mount fluorescent in situ hybridization and confocal microscopy.ResultsThe Sce-elav+ profile of S. cephaloptera hatchlings reveals that, within 24 h of post-embryonic development, the developing neural territories are not limited to the regions previously ascribed to the cerebral ganglion, the ventral nerve center (VNC), and the sensory organs, but also extend to previously unreported CNS domains that likely contribute to the ventral cephalic ganglia. In general, the neural patterning genes are expressed in distinct neural subpopulations of the cerebral ganglion and the VNC in hatchlings, eventually becoming broadly expressed with reduced intensity throughout the CNS in early juveniles. Neural patterning gene expression domains are also present outside the CNS, including the digestive tract and sensory organs. ChAT and VAChT domains within the CNS are predominantly observed in specific subpopulations of the VNC territory adjacent to the ventral longitudinal muscles in hatchlings.ConclusionsThe observed spatial expression domains of bilaterian neural marker gene homologs in S. cephaloptera suggest evolutionarily conserved roles in neurogenesis for these genes among bilaterians. Patterning genes expressed in distinct regions of the VNC do not show a staggered medial-to-lateral expression profile directly superimposable to other bilaterian models. Only when the VNC is conceptually laterally unfolded from the longitudinal muscle into a flat structure, an expression pattern bearing resemblance to the proposed conserved bilaterian mediolateral regionalization becomes noticeable. This finding supports the idea of an ancestral mediolateral patterning of the trunk nervous system in bilaterians.

Spatially revealed roles for lncRNAs in Drosophila spermatogenesis, Y chromosome function and evolution

Unlike coding genes, the number of lncRNA genes in organism genomes is relatively proportional to organism complexity. From plants to humans, the tissues with highest numbers and levels of lncRNA gene expression are the male reproductive organs. To learn why, we initiated a genome-wide analysis of Drosophila lncRNA spatial expression patterns in these tissues. The numbers of genes and levels of expression observed greatly exceed those previously reported, due largely to a preponderance of non-polyadenylated transcripts. In stark contrast to coding genes, the highest numbers of lncRNAs expressed are in post-meiotic spermatids. Correlations between expression levels, localization and previously performed genetic analyses indicate high levels of function and requirement. More focused analyses indicate that lncRNAs play major roles in evolution by controlling transposable element activities, Y chromosome gene expression and sperm construction. A new type of lncRNA-based particle found in seminal fluid may also contribute to reproductive outcomes.

Abstract PO3-14-01: Heterogeneity of tumor immune microenvironment to predict everolimus efficacy in premenopausal women with hormone receptor-positive/human epidermal growth factor receptor 2-negative adavanced breast cancer

Abstract Objective Everolimus (EVE), a mammalian target of rapamycin (mTOR) inhibitor, has been shown to prolong survival of patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-), advanced breast cancer (ABC) with endocrine resistance. Preclinical studies have suggested that mTOR is closely associated with the tumor immune microenvironment (TME). We aimed to explore the tumor heterogeneity of TME between patients with different response to everolimus (EVE), and identify potential markers to predict efficacy of EVE in premenopausal patients with HR+/HER2−, advanced breast cancer (ABC) suffering endocrine resistance. Methods Patients were divided into two groups according to the best response to EVE: the responsive subgroup (RS) and the non-responsive subgroup (NRS). Postoperative tumor tissue from patients who received EVE was collected for whole exome sequencing. Transcript abundance of 126 distinct tumor regions of interest (ROIs) were quantitated using digital spatial profiling, including 42 tumor cell zones (TCZs), 42 immune cell zones (ICZs), and 42 stroma cell zones (SCZs). Based on investigation in multiple discrete areas, differences in cell components, function and pathway, gene expression and immune cell infiltration between RS and NRS were investigated. Results Totally, 93 differentially expressed genes (DEGs) were identified in the ICZs, 174 DEGs in the TCZs, and 197 DEGs in the SCZs, using p< 0.05 and |log2FC >1| as the screening criterion. Among all the subgroup analyses on different ROIs, the statistical significance of PIP gene was the highest (ICZs: p=2.6E-12, TCZs: p=1.25E-20, SCZs: p=2.0E-18) in the comparison of RS and NRS. Moreover, we found that PIP was highly expressed in NRS and patients with a progression-free survival < 1 year. The receptor-legend analysis showed that, the intra-and inter-cellular communication in RS was mainly mediated by interaction between CCL-CCR family, while NRS mainly by COL family complex. Comparing all cell components extracted from each ROI, no statistical differences were found between RS and NRS, only a statistical trend in the SCZs (p=0.098). Further cell classification analysis showed fibroblasts highest in TCZs and SCZs, macrophages in ICZs. Compared to NRS, in TCZs, fibroblasts were significantly increased (p=0.01), and plasma cells (p=0.02) and neutrophils (p=0.03) were decreased in RS. In SCZs, the downregulated fibroblasts (p=0.04) and enhanced plasma cells (p=0.01) were observed in NRS. In ICZs, pDCs (p=0.048) and neutrophils (p=0.006) were significantly elevated in NRS compared with RS. Conclusion The utility of digital spatial gene expression profiling might provide some references to predict the efficacy of EVE in premenopausal patients with HR+/HER2- ABC with endocrine resistance. Citation Format: Yujing Tan, Fei Ma, Jiayu Wang, Pin Zhang, Binghe Xu, Liyan Xue, Ying Fan. Heterogeneity of tumor immune microenvironment to predict everolimus efficacy in premenopausal women with hormone receptor-positive/human epidermal growth factor receptor 2-negative adavanced breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-01.

Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system.

Spatial transcriptomics (ST) provides insights into the tumor microenvironment (TME), which is closely associated with cancer prognosis, but ST has limited clinical availability. In this study, we provide a powerful deep learning system to augment TME information based on histological images for patients without ST data, thereby empowering precise cancer prognosis. The system provides two connections to bridge existing gaps. The first is the integrated graph and image deep learning (IGI-DL) model, which predicts ST expression based on histological images with a 0.171 increase in mean correlation across three cancer types compared with five existing methods. The second connection is the cancer prognosis prediction model, based on TME depicted by spatial gene expression. Our survival model, using graphs with predicted ST features, achieves superior accuracy with a concordance index of 0.747 and 0.725 for The Cancer Genome Atlas breast cancer and colorectal cancer cohorts, outperforming other survival models. For the external Molecular and Cellular Oncologycolorectal cancer cohort, our survival model maintains a stable advantage.

The changing of α5-GABAA receptors expression and distribution participate in sevoflurane-induced learning and memory impairment in young mice.

Sevoflurane is a superior agent for maintaining anesthesia during surgical procedures. However, the neurotoxic mechanisms of clinical concentration remain poorly understood. Sevoflurane can interfere with the normal function of neurons and synapses and impair cognitive function by acting on α5-GABAAR. Using MWM test, we evaluated cognitive abilities in mice following 1 h of anesthesia with 2.7%-3% sevoflurane. Based on hippocampal transcriptome analysis, we analyzed the differential genes and IL-6 24 h post-anesthesia. Western blot and RT-PCR were performed to measure the levels of α5-GABAAR, Radixin, P-ERM, P-Radixin, Gephyrin, IL-6, and ROCK. The spatial distribution and expression of α5-GABAAR on neuronal somata were analyzed using histological and three-dimensional imaging techniques. MWM test indicated that partial long-term learning and memory impairment. Combining molecular biology and histological analysis, our studies have demonstrated that sevoflurane induces immunosuppression, characterized by reduced IL-6 expression levels, and that enhanced Radixin dephosphorylation undermines the microstructural stability of α5-GABAAR, leading to its dissociation from synaptic exterior and resulting in a disordered distribution in α5-GABAAR expression within neuronal cell bodies. On the synaptic cleft, the expression level of α5-GABAAR remained unchanged, the spatial distribution became more compact, with an increased fluorescence intensity per voxel. On the extra-synaptic space, the expression level of α5-GABAAR decreased within unchanged spatial distribution, accompanied by an increased fluorescence intensity per voxel. Dysregulated α5-GABAAR expression and distribution contributes to sevoflurane-induced partial long-term learning and memory impairment, which lays the foundation for elucidating the underlying mechanisms in future studies.

Msx genes delineate a novel molecular map of the developing cerebellar neuroepithelium.

In the early cerebellar primordium, there are two progenitor zones, the ventricular zone (VZ) residing atop the IVth ventricle and the rhombic lip (RL) at the lateral edges of the developing cerebellum. These zones give rise to the several cell types that form the GABAergic and glutamatergic populations of the adult cerebellum, respectively. Recently, an understanding of the molecular compartmentation of these zones has emerged. To add to this knowledge base, we report on the Msx genes, a family of three transcription factors, that are expressed downstream of Bone Morphogenetic Protein (BMP) signaling in these zones. Using fluorescent RNA in situ hybridization, we have characterized the Msx (Msh Homeobox) genes and demonstrated that their spatiotemporal pattern segregates specific regions within the progenitor zones. Msx1 and Msx2 are compartmentalized within the rhombic lip (RL), while Msx3 is localized within the ventricular zone (VZ). The relationship of the Msx genes with an early marker of the glutamatergic lineage, Atoh1, was examined in Atoh1-null mice and it was found that the expression of Msx genes persisted. Importantly, the spatial expression of Msx1 and Msx3 altered in response to the elimination of Atoh1. These results point to the Msx genes as novel early markers of cerebellar progenitor zones and more importantly to an updated view of the molecular parcellation of the RL with respect to the canonical marker of the RL, Atoh1.

Unveiling the Genomic Landscape of Intraductal Carcinoma of the Prostate Using Spatial Gene Expression Analysis.

Intraductal carcinoma of the prostate (IDCP) has recently attracted increasing interest owing to its unfavorable prognoses. To effectively identify the IDCP-specific gene expression profile, we took a novel approach of characterizing a typical IDCP case using spatial gene expression analysis. A formalin-fixed, paraffin-embedded sample was subjected to Visium CytAssist Spatial Gene Expression analysis. IDCP within invasive prostate cancer sites was recognized as a distinct cluster separate from other invasive cancer clusters. Highly expressed genes defining the IDCP cluster, such as MUC6, MYO16, NPY, and KLK12, reflected the aggressive nature of high-grade prostate cancer. IDCP sites also showed increased hypoxia markers HIF1A, BNIP3L, PDK1, and POGLUT1; decreased fibroblast markers COL1A2, DCN, and LUM; and decreased immune cell markers CCR5 and FCGR3A. Overall, these findings indicate that the hypoxic tumor microenvironment and reduced recruitment of fibroblasts and immune cells, which reflect morphological features of IDCP, may influence the aggressiveness of high-grade prostate cancer.

SpatialSPM: statistical parametric mapping for the comparison of gene expression pattern images in multiple spatial transcriptomic datasets.

Spatial transcriptomic (ST) techniques help us understand the gene expression levels in specific parts of tissues and organs, providing insights into their biological functions. Even though ST dataset provides information on the gene expression and its location for each sample, it is challenging to compare spatial gene expression patterns across tissue samples with different shapes and coordinates. Here, we propose a method, SpatialSPM, that reconstructs ST data into multi-dimensional image matrices to ensure comparability across different samples through spatial registration process. We demonstrated the applicability of this method by kidney and mouse olfactory bulb datasets as well as mouse brain ST datasets to investigate and directly compare gene expression in a specific anatomical region of interest, pixel by pixel, across various biological statuses. Beyond traditional analyses, SpatialSPM is capable of generating statistical parametric maps, including T-scores and Pearson correlation coefficients. This feature enables the identification of specific regions exhibiting differentially expressed genes across tissue samples, enhancing the depth and specificity of ST studies. Our approach provides an efficient way to analyze ST datasets and may offer detailed insights into various biological conditions.

Tomato root specialized metabolites evolved through gene duplication and regulatory divergence within a biosynthetic gene cluster.

Tremendous plant metabolic diversity arises from phylogenetically restricted specialized metabolic pathways. Specialized metabolites are synthesized in dedicated cells or tissues, with pathway genes sometimes colocalizing in biosynthetic gene clusters (BGCs). However, the mechanisms by which spatial expression patterns arise and the role of BGCs in pathway evolution remain underappreciated. In this study, we investigated the mechanisms driving acylsugar evolution in the Solanaceae. Previously thought to be restricted to glandular trichomes, acylsugars were recently found in cultivated tomato roots. We demonstrated that acylsugars in cultivated tomato roots and trichomes have different sugar cores, identified root-enriched paralogs of trichome acylsugar pathway genes, and characterized a key paralog required for root acylsugar biosynthesis, SlASAT1-LIKE (SlASAT1-L), which is nested within a previously reported trichome acylsugar BGC. Last, we provided evidence that ASAT1-L arose through duplication of its paralog, ASAT1, and was trichome-expressed before acquiring root-specific expression in the Solanum genus. Our results illuminate the genomic context and molecular mechanisms underpinning metabolic diversity in plants.

Bayesian hidden mark interaction model for detecting spatially variable genes in imaging-based spatially resolved transcriptomics data.

Recent technology breakthroughs in spatially resolved transcriptomics (SRT) have enabled the comprehensive molecular characterization of cells whilst preserving their spatial and gene expression contexts. One of the fundamental questions in analyzing SRT data is the identification of spatially variable genes whose expressions display spatially correlated patterns. Existing approaches are built upon either the Gaussian process-based model, which relies on ad hoc kernels, or the energy-based Ising model, which requires gene expression to be measured on a lattice grid. To overcome these potential limitations, we developed a generalized energy-based framework to model gene expression measured from imaging-based SRT platforms, accommodating the irregular spatial distribution of measured cells. Our Bayesian model applies a zero-inflated negative binomial mixture model to dichotomize the raw count data, reducing noise. Additionally, we incorporate a geostatistical mark interaction model with a generalized energy function, where the interaction parameter is used to identify the spatial pattern. Auxiliary variable MCMC algorithms were employed to sample from the posterior distribution with an intractable normalizing constant. We demonstrated the strength of our method on both simulated and real data. Our simulation study showed that our method captured various spatial patterns with high accuracy; moreover, analysis of a seqFISH dataset and a STARmap dataset established that our proposed method is able to identify genes with novel and strong spatial patterns.

[Characterization of sequences, expression profiling, and natural allelic variation analysis of the MYC gene family in sorghum (Sorghum bicolor)].

Sorghum aphid (Melanaphis sacchari) and head smut fungi (Sporisorium reilianum) infesting sorghum cause delayed growth and development, and reduce yield and quality. This study use bioinformatics and molecular biological approaches to profile the gene expression pattern during sorghum development and under pest infestation, and analyzed the natural allelic DNA variation of sorghum MYC gene family. The findings provide insights for potential application in breeding the stress resistant and high productivity sorghum varieties. The results indicated that there are 28 MYC genes identified in sorghum genome, distributed on 10 chromosomes. The bHLH_MYC_N and HLH domains are the conserved domains of the MYC gene in sorghum. Gene expression analysis showed that SbbHLH35.7g exhibited high expression levels in leaves, SbAbaIn showed strong expression in early grains, and SbMYC2.1g showed high expression levels in mature pollen. In anti-aphid strains at the 5-leaf stage, SbAbaIn, SbLHW.4g and SbLHW.2g were significantly induced in leaves, while SbbHLH35.7g displayed the highest expression level in panicle tissue, which was significantly induced by the infection of head smut. Promoter cis-element analysis identified methyl jasmonate (MJ), abscisic acid (ABA), salicylic acid (SA) and MYB-binding sites related to drought-stress inducibility. Furthermore, genomic resequencing data analysis revealed natural allelic DNA variations such as single nucleotide polymorphism (SNP) and insertion-deletion (INDEL) for the key SbMYCs. Protein interaction network analysis using STRING indicated that SbAbaIn interacts with TIFYdomain protein, and SbbHLH35.7g interacts with MDR and imporin. SbMYCs exhibited temporal and spatial expression patterns and played vital roles during the sorghum development. Infestation by sugarcane aphids and head smut fungi induced the expression of SbAbaIn and SbbHLH35.7g, respectively. SbAbaIn modulated the jasmonic acid (JA) pathway to regulate the expression of defensive genes, conferring resistance to insects. On the other hand, SbbHLH35.7g participated in detoxification reactions to defend against pathogens.

Identification and function analysis of steroid hormone synthesis pathway-related gene—Hsd3b in Scylla paramamosain

Mud crab (Scylla paramamosain) has become an important mariculture crab along the southeast coast of China due to its strong adaptability, delicious taste, and rich nutrition. Several vertebrate steroid hormones and their synthesis-related genes and receptors have been found in crustaceans, but there are few reports on their synthesis process and mechanism. 3-beta-hydroxysteroid dehydrogenase (HSD3B) is a member of the Short-chain Dehydrogenase/Reductase (SDR) family, and an indispensable protein in vertebrates' steroid hormone synthesis pathway. In this study, the SpHsd3b gene sequence was obtained from the transcriptome data of S. paramamosain, and its full-length open reading frame (ORF) was cloned. The spatial and temporal expression pattern of SpHsd3b was performed by quantitative real-time PCR (qRT-PCR). SpHsd3b dsRNA interference (RNAi) and HSD3B inhibitor (trilostane) were used to analyze the function of SpHSD3B. The results showed that the SpHsd3b gene has an 1113 bp ORF encoding 370 amino acids with a 3β-HSD domain. SpHSD3B has lower homology with HSD3B of vertebrates and higher homology with HSD3B of crustaceans. SpHsd3b was expressed in all examined tissues in mature crabs, and its expression was significantly higher in the testes than in the ovaries. SpHsd3b expression level was highest in the middle stage of testicular development, while its expression was higher in the early and middle stages of ovarian development. RNAi experiment and trilostane injection results showed that SpHSD3B had regulatory effects on several genes related to gonadal development and steroid hormone synthesis. 15-day trilostane suppression could also inhibit ovarian development and progesterone level of hemolymph. According to the above results, crustaceans may have steroid hormone synthesis pathways like vertebrates, and the Hsd3b gene may be involved in the gonadal development of crabs. This study provides further insight into the function of genes involved in steroid hormone synthesis in crustaceans.

Spatial enrichment and genomic analyses reveal the link of NOMO1 with amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a severe motor neuron disease with uncertain genetic predisposition in most sporadic cases. Spatial architecture of cell types and gene expression is the basis of cell-cell interactions, biological function and disease pathology, but is not well investigated in human motor cortex, a key ALS relevant brain region. Recent studies indicated single nucleus transcriptomic features of motor neuron vulnerability in ALS motor cortex. However, it remains largely unclear what is the brain regional vulnerability of ALS-associated genes, and what is the genetic link between region-specific genes and ALS risk. Here, we developed an entropy-weighted differential gene expression matrix-based tool (SpatialE) to identify the spatial enrichment of gene sets in spatial transcriptomics (ST). We benchmarked SpatialE against another enrichment tool (Multimodal Intersection Analysis, MIA) using ST data from both human and mouse brain tissues. To investigate regional vulnerability, we analyzed three human motor cortex and two dorsolateral prefrontal cortex tissues for spatial enrichment of ALS-associated genes. We also used Cell2location to estimate the abundance of cell types in ALS-related cortex layers. To dissect the link of regionally expressed genes and ALS risk, we performed burden analyses of rare loss-of-function (LOF) variants detected by whole-genome sequencing in ALS patients and controls, and then analyzed differential gene expression in the TargetALS RNA-seq dataset. SpatialE showed more accurate and specific spatial enrichment of regional cell type markers than MIA in both mouse brain and human dorsolateral prefrontal cortex. Spatial transcriptomic analyses of human motor cortex showed heterogenous cell types and spatial gene expression profiles. We found that 260 manually curated ALS-associated genes are significantly enriched in layer 5 (L5) motor cortex, with abundant expression of upper motor neurons and L5 excitatory neurons. Burden analyses of rare LOF variants in L5-associated genes nominated NOMO1 as a novel ALS-associated gene in a combined sample set of 6,814 ALS patients and 3,324 controls (P = 0.029). Gene expression analyses in central nervous system tissues revealed down-regulation of NOMO1 in ALS, which is consistent with a LOF disease mechanism. In conclusion, our integrated ST and genomic analyses identified regional brain vulnerability in ALS and the association of a L5 gene (NOMO1) with ALS risk.

SpVC for the detection and interpretation of spatial gene expression variation

Spatially resolved transcriptomics technologies have opened new avenues for understanding gene expression heterogeneity in spatial contexts. However, existing methods for identifying spatially variable genes often focus solely on statistical significance, limiting their ability to capture continuous expression patterns and integrate spot-level covariates. To address these challenges, we introduce spVC, a statistical method based on a generalized Poisson model. spVC seamlessly integrates constant and spatially varying effects of covariates, facilitating comprehensive exploration of gene expression variability and enhancing interpretability. Simulation and real data applications confirm spVC’s accuracy in these tasks, highlighting its versatility in spatial transcriptomics analysis.

SPADE: spatial deconvolution for domain specific cell-type estimation

Understanding gene expression in different cell types within their spatial context is a key goal in genomics research. SPADE (SPAtial DEconvolution), our proposed method, addresses this by integrating spatial patterns into the analysis of cell type composition. This approach uses a combination of single-cell RNA sequencing, spatial transcriptomics, and histological data to accurately estimate the proportions of cell types in various locations. Our analyses of synthetic data have demonstrated SPADE’s capability to discern cell type-specific spatial patterns effectively. When applied to real-life datasets, SPADE provides insights into cellular dynamics and the composition of tumor tissues. This enhances our comprehension of complex biological systems and aids in exploring cellular diversity. SPADE represents a significant advancement in deciphering spatial gene expression patterns, offering a powerful tool for the detailed investigation of cell types in spatial transcriptomics.

CHD4 and SMYD1 repress common transcriptional programs in the developing heart.

Regulation of chromatin states is essential for proper temporal and spatial gene expression. Chromatin states are modulated by remodeling complexes composed of components that have enzymatic activities. CHD4 is the catalytic core of the Nucleosome Remodeling and Deacetylase (NuRD) complex that represses gene transcription. However, it remains to be determined how CHD4, a ubiquitous enzyme that remodels chromatin structure, functions in cardiomyocytes to maintain heart development. Particularly, there exists controversy as to whether other proteins besides the NuRD components interact with CHD4 in the heart. Using quantitative proteomics, we identified that CHD4 interacts with SMYD1, a striated muscle-restricted histone methyltransferase that is essential for cardiomyocyte differentiation and cardiac morphogenesis. Comprehensive transcriptomic and chromatin accessibility studies of Smyd1 and Chd4 null embryonic hearts revealed that SMYD1 and CHD4 repress a group of common genes and pathways that included glycolysis, response to hypoxia, and angiogenesis. Our study reveals a novel mechanism by which CHD4 functions during heart development, and we have revealed an uncharacterized mechanism regarding how SMYD1 represses cardiac transcription in the developing heart.

CSINet: Channel–Spatial Fusion Networks for Asymmetric Facial Expression Recognition

Occlusion or posture change of the face in natural scenes has typical asymmetry; however, an asymmetric face plays a key part in the lack of information available for facial expression recognition. To solve the problem of low accuracy of asymmetric facial expression recognition, this paper proposes a fusion of channel global features and a spatial local information expression recognition network called the “Channel–Spatial Integration Network” (CSINet). First, to extract the underlying detail information and deepen the network, the attention residual module with a redundant information filtering function is designed, and the backbone feature-extraction network is constituted by module stacking. Second, considering the loss of information in the local key area of face occlusion, the channel–spatial fusion structure is constructed, and the channel features and spatial features are combined to enhance the accuracy of occluded facial recognition. Finally, before the full connection layer, more local spatial information is embedded into the global channel information to capture the relationship between different channel–spatial targets, which improves the accuracy of feature expression. Experimental results on the natural scene facial expression data sets RAF-DB and FERPlus show that the recognition accuracies of the modeling approach proposed in this paper are 89.67% and 90.83%, which are 13.24% and 11.52% higher than that of the baseline network ResNet50, respectively. Compared with the latest facial expression recognition methods such as CVT, PACVT, etc., the method in this paper obtains better evaluation results of masked facial expression recognition, which provides certain theoretical and technical references for daily facial emotion analysis and human–computer interaction applications.

Visualisation of gene expression within the context of tissues using an X-ray computed tomography-based multimodal approach

The development of an organism is orchestrated by the spatial and temporal expression of genes. Accurate visualisation of gene expression patterns in the context of the surrounding tissues offers a glimpse into the mechanisms that drive morphogenesis. We developed correlative light-sheet fluorescence microscopy and X-ray computed tomography approach to map gene expression patterns to the whole organism`s 3D anatomy. We show that this multimodal approach is applicable to gene expression visualized by protein-specific antibodies and fluorescence RNA in situ hybridisation offering a detailed understanding of individual phenotypic variations in model organisms. Furthermore, the approach offers a unique possibility to identify tissues together with their 3D cellular and molecular composition in anatomically less-defined in vitro models, such as organoids. We anticipate that the visual and quantitative insights into the 3D distribution of gene expression within tissue architecture, by multimodal approach developed here, will be equally valuable for reference atlases of model organisms development, as well as for comprehensive screens, and morphogenesis studies of in vitro models.

Functional characterization of Fagopyrum tataricum ZIP gene family as a metal ion transporter.

The zinc/iron-regulated transporter-like proteins (ZIP) family acts as an important transporter for divalent metal cations such as Zn, Fe, Mn, Cu, and even Cd. However, their condition is unclear in Tartary buckwheat (Fagopyrum tataricum). Here, 13 ZIP proteins were identified and were predicted to be mostly plasma membrane-localized. The transient expressions of FtZIP2 and FtZIP6 in tobacco confirmed the prediction. Multiple sequence alignment analysis of FtZIP proteins revealed that most of them had 8 putative transmembrane (TM) domains and a variable region rich in histidine residues between TM3 and TM4, indicating the reliable affinity to metal ions. Gene expression analysis by qRT-PCR showed that FtZIP genes were markedly different in different organs, such as roots, stems, leaves, flowers, fruits and seeds. However, in seedlings, the relative expression of FtZIP10 was notably induced under the CdCl2 treatment, while excessive Zn2+, Fe2+, Mn2+ and Cd2+ increased the transcript of FtZIP5 or FtZIP13, in comparison to normal conditions. Complementation of yeast mutants with the FtZIP family genes demonstrate that FtZIP7/10/12 transport Zn, FtZIP5/6/7/9/10/11 transport Fe, FtZIP12 transports Mn and FtZIP2/3/4/7 transport Cd. Our data suggest that FtZIP proteins have conserved functions of transportation of metal ions but with distinct spatial expression levels.