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Profiling gene expression while preserving cell locations aids in the comprehensive understanding of cell fates in multicellular organisms. However, simple and flexible isolation of microregions of interest (mROIs) for spatial transcriptomics is still challenging. We present a laser-induced forward transfer (LIFT)-based method combined with a full-length mRNA-sequencing protocol (LIFT-seq) for profiling region-specific tissues. LIFT-seq demonstrated that mROIs from two adjacent sections could reliably and sensitively detect and display gene expression. In addition, LIFT-seq can identify region-specific mROIs in the mouse cortex and hippocampus. Finally, LIFT-seq identified marker genes in different layers of the cortex with very similar expression patterns. These genes were then validated using in situ hybridization (ISH) results. Therefore, LIFT-seq will be a valuable and efficient technique for profiling the spatial transcriptome in various tissues.
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Perfilación de la Expresión Génica , Transcriptoma , Animales , Perfilación de la Expresión Génica/métodos , Ratones , Rayos Láser , Hipocampo/metabolismo , ARN Mensajero/genética , ARN Mensajero/metabolismo , Hibridación in Situ/métodos , Corteza Cerebral/metabolismo , Análisis de Secuencia de ARN/métodosRESUMEN
Coastal wetlands are key players in mitigating global climate change by sequestering soil organic matter. Soil organic matter consists of less stable particulate organic matter (POM) and more stable mineral-associated organic matter (MAOM). The distribution and drivers of MAOM and POM in coastal wetlands have received little attention, despite the processes and mechanisms differ from that in the upland soils. We explored the distribution of POM and MAOM, their contributions to SOM, and the controlling factors along a salinity gradient in an estuarine wetland. In the estuarine wetland, POM C and N were influenced by soil depth and vegetation type, whereas MAOM C and N were influenced only by vegetation type. In the estuarine wetland, SOM was predominantly in the form of MAOM (> 70 %) and increased with salinity (70 %-76 %), leading to long-term C sequestration. Both POM and MAOM increased with SOM, and the increase rate of POM was higher than that of MAOM. Aboveground plant biomass decreased with increasing salinity, resulted in a decrease in POM C (46 %-81 %) and N (52 %-82 %) pools. As the mineral amount and activity, and microbial biomass decreased, the MAOM C (2.5 %-64 %) and N pool (8.6 %-59 %) decreased with salinity. When evaluating POM, the most influential factors were microbial biomass carbon (MBC) and dissolved organic carbon (DOC). Key parameters, including MBC, DOC, soil salinity, soil water content, aboveground plant biomass, mineral content and activity, and bulk density, were identified as influencing factors for both MAOM abundance. Soil water content not only directly controlled MAOM, but together with salinity also indirectly regulated POM and MAOM by controlling microbial biomass and aboveground plant biomass. Our findings have important implications for improving the accumulation and increased stability of soil organic matter in coastal wetlands, considering the global sea level rise and increased frequency of inundation.
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The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its development. Pre-compressing the data is recognized as one of the most effective approaches for reducing storage costs. However, different compression methods yield varying compression ratios for the same file, and compressing a large number of files with a single method may not achieve the maximum compression ratio. This study proposes a multi-file dynamic compression method based on machine learning classification algorithms that selects the appropriate compression method for each file to minimize the amount of data stored into DNA as much as possible. Firstly, four different compression methods are applied to the collected files. Subsequently, the optimal compression method is selected as a label, as well as the file type and size are used as features, which are put into seven machine learning classification algorithms for training. The results demonstrate that k-nearest neighbor outperforms other machine learning algorithms on the validation set and test set most of the time, achieving an accuracy rate of over 85% and showing less volatility. Additionally, the compression rate of 30.85% can be achieved according to k-nearest neighbor model, more than 4.5% compared to the traditional single compression method, resulting in significant cost savings for DNA storage in the range of $0.48 to 3 billion/TB. In comparison to the traditional compression method, the multi-file dynamic compression method demonstrates a more significant compression effect when compressing multiple files. Therefore, it can considerably decrease the cost of DNA storage and facilitate the widespread implementation of DNA storage technology.
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Staining frozen sections is often required to distinguish cell types for spatial transcriptomic studies of the brain. The impact of the staining methods on the RNA integrity of the cells becomes one of the limitations of spatial transcriptome technology with microdissection. However, there is a lack of systematic comparisons of different staining modalities for the pretreatment of frozen sections of brain tissue as well as their effects on transcriptome sequencing results. In this study, four different staining methods were analyzed for their effect on RNA integrity in frozen sections of brain tissue. Subsequently, differences in RNA quality in frozen sections under different staining conditions and their impact on transcriptome sequencing results were assessed by RNA-seq. As one of the most commonly used methods for staining pathological sections, HE staining seriously affects the RNA quality of frozen sections of brain tissue. In contrast, the homemade cresyl violet staining method developed in this study has the advantages of short staining time, low cost, and less RNA degradation. The homemade cresyl violet staining proposed in this study can be applied instead of HE staining as an advance staining step for transcriptome studies in frozen sections of brain tissue. In the future, this staining method may be suitable for wide application in brain-related studies of frozen tissue sections. Moreover, it is expected to become a routine step for staining cells before sampling in brain science.
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Encéfalo , Secciones por Congelación , Coloración y Etiquetado , Animales , Encéfalo/metabolismo , Coloración y Etiquetado/métodos , Secciones por Congelación/métodos , Crioultramicrotomía/métodos , Ratones , Transcriptoma , Masculino , ARN/análisis , Benzoxazinas , Ratones Endogámicos C57BL , OxazinasRESUMEN
Practical gas sensing application requires sensors to quantify target analytes with high sensitivity and reproducibility. However, conventional surface enhanced Raman scattering (SERS) sensor lacks reproducibility and quantification arising from variations of "hot spot" distribution and measurement conditions. Here, a ratio-dependent SERS sensor was developed for quantitative label-free gas sensing. Au@Ag-Au nanoparticles (NPs) were filtered onto anodic aluminum oxide (AAO) forming Au@Ag-Au@AAO SERS substrate. 4-MBA was encapsulated in the gap of Au@Ag-Au and served as the internal standard (IS) to calibrate SERS signal fluctuation for improved quantification ability. Combined with headspace sampling method, SO2 residue in traditional Chinese medicine (TCM) can be extracted and captured on the immediate vicinity of Au@Ag-Au surface. The intensity ratio I613 cm-1/I1078 cm-1 showed excellent linearity within the range of 0.5 mg/kg-500 mg/kg, demonstrating superior quantification performance for SO2 detection. Signals for concentration as low as 0.05 mg/kg of SO2 could be effectively collected, much lower than the strictest limit 10 mg/kg in Chinese Pharmacopoeia. Combined with a handheld Raman spectrometer, handy and quantitative TCM quality evaluation in aspect of SO2 residue was realized. This ratiometric SERS sensor functioned well in rapid on-site SO2 quantification, exhibiting excellent sensitivity and simple operability.
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Nanopartículas del Metal , Nanopartículas del Metal/química , Oro/química , Reproducibilidad de los Resultados , Plata/química , Medicina Tradicional ChinaRESUMEN
Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq data can provide a novel possibility in the biomedical field. In this study, a novel approach based on a deep learning algorithm and cloud model was developed, named Deep-Cloud. Its main advantage is not only using a convolutional neural network and long short-term memory to extract original data features and estimate gene expression of RNA-seq data but also combining the statistical method of the cloud model to quantify the uncertainty and carry out in-depth analysis of the DEGs between the disease groups and the control groups. Compared with traditional analysis software of DEGs, the Deep-cloud model further improves the sensitivity and accuracy of obtaining DEGs from RNA-seq data. Overall, the proposed new approach Deep-cloud paves a new pathway for mining RNA-seq data in the biomedical field.
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Algoritmos , Redes Neurales de la Computación , RNA-Seq , Programas InformáticosRESUMEN
The combination of single-cell RNA sequencing and microdissection techniques that preserves positional information has become a major tool for spatial transcriptome analyses. However, high costs and time requirements, especially for experiments at the single cell scale, make it challenging for this approach to meet the demand for increased throughput. Therefore, we proposed combinational DNA barcode (CDB)-seq as a medium-throughput, multiplexed approach combining Smart-3SEQ and CDB magnetic microbeads for transcriptome analyses of microdissected tissue samples. We conducted a comprehensive comparison of conditions for CDB microbead preparation and related factors and then applied CDB-seq to RNA extracts, fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) mouse brain tissue samples. CDB-seq transcriptomic profiles of tens of microdissected samples could be obtained in a simple, cost-effective way, providing a promising method for future spatial transcriptomics.
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Antiinfecciosos , Transcriptoma , Ratones , Animales , Transcriptoma/genética , Microesferas , Código de Barras del ADN Taxonómico , Fijación del Tejido/métodos , Perfilación de la Expresión Génica/métodos , ADN , FormaldehídoRESUMEN
Coastal wetland sediment is important reservoir for silicon (Si), and plays an essential role in controlling its biogeochemical cycling. However, little is known about Si fractionations and the associated factors driving their transformations in coastal wetland sediments. In this study, we applied an optimized sequential Si extraction method to separate six sub-fractions of non-crystalline Si (Sinoncry) in sediments from two coastal wetlands, including Si in dissolved silicate (Sidis), Si in the adsorbed silicate (Siad), Si bound to organic matter (Siorg), Si occluded in pedogenic oxides and hydroxides (Siocc), Si in biogenic amorphous silica (Siba), and Si in pedogenic amorphous silica (Sipa). The results showed that the highest proportion of Si in the Sinoncry fraction was Siba (up to 6.6 % of total Si (Sitot)), followed by the Sipa (up to 1.8 % of Sitot). The smallest proportion of Si was found in the Sidis and Siad fractions with the sum of both being <0.1 % of the Sitot. We found a lower Siocc content (188 ± 96.1 mg kg-1) when compared to terrestrial soils. The Sidis was at the center of the inter-transformation among Si fractions, regulating the biogeochemical Si cycling of coastal wetland sediments. Redundancy analysis (RDA) combined with Pearson's correlations further showed that the basic biogenic elements (total organic carbon and total nitrogen), pH, and sediment salinity collectively controlled the Si fractionations in coastal wetland sediments. Our research optimizes sediment Si fractionation procedure and provides insights into the role of sedimentary Si fractions in controlling Si dynamics and knowledge for unraveling the biogeochemical Si cycling in coastal ecosystems.
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Coastal wetlands play a vital role in mitigating climate change, yet the characteristics of buried organic carbon (OC) and carbon cycling are limited due to difficulties in assessing the composition of OC from different sources (allochthonous vs. autochthonous). In this study, we analyzed the total organic carbon (TOC) to total nitrogen (TN) ratio (C/N), stable carbon isotope (δ13C) composition, and n-alkane content to distinguish different sources of OC in the surface sediments of the coastal wetlands on the western coast of the Bohai Sea. The coupling of the C/N ratio with δ13C and n-alkane biomarkers has been proved to be an effective tool for revealing OC sources. The three end-member Bayesian mixing model based on coupling C/N ratios with δ13C showed that the sedimentary OC was dominated by the contribution of terrestrial particulate organic matter (POM), followed by freshwater algae and marine phytoplankton, with relative contributions of 47 ± 21 %, 41 ± 18 % and 12 ± 17 %, respectively. The relative contributions of terrestrial plants, aquatic macrophytes and marine phytoplankton assessed by n-alkanes were 56 ± 8 %, 35 ± 9 % and 9 ± 5 % in the study area, respectively. The relatively high salinity levels and strong hydrodynamic conditions of the Beidagang Reservoir led to higher terrestrial plants source and lower aquatic macrophytes source than these of Qilihai Reservoir based on the assessment of n-alkanes. Both methods showed that sedimentary OC was mainly derived from terrestrial sources (plant-dominated), suggesting that vegetation plays a crucial role in storing carbon in coastal wetlands, thus, the coastal vegetation management needs to be strengthened in the future. Our findings provide insights into the origins and dynamics of OC in coastal wetlands on the western coast of the Bohai Sea and a significant scientific basis for future monitoring of the blue carbon budget balance in coastal wetlands.
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Retinitis pigmentosa (RP) is the leading cause of inherited blindness with a genetically heterogeneous disorder. Currently, there is no effective treatment that can protect vision for those with RP. In recent decades, the rd1 mouse has been used to study the pathological mechanisms of RP. Molecular biological studies using rd1 mice have clarified the mechanism of the apoptosis of photoreceptor cells in the early stage of RP. However, the pathological changes in RP over time remain unclear. The unknown pathology mechanism of RP over time and the difficulty of clinical treatment make it urgent to perform more refined and spatially informed molecular biology studies of RP. In this study, spatial transcriptomic analysis is used to study the changes in different retinal layers of rd1 mice at different ages. The results demonstrate the pattern of photoreceptor apoptosis between rd1 mice and the control group. Not only was oxidative stress enhanced in the late stage of RP, but it was accompanied by an up-regulation of the VEGF pathway. Analysis of temporal kinetic trends has further identified patterns of changes in the key pathways of the early and late stages, to help understand the important pathogenesis of RP. Overall, the application of spatial transcriptomics to rd1 mice can help to elucidate the important pathogenesis of RP involving photoreceptor apoptosis and retinal remodeling.
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Degeneración Retiniana , Retinitis Pigmentosa , Ratones , Animales , Transcriptoma , Retinitis Pigmentosa/metabolismo , Retina/metabolismo , Apoptosis/genética , Perfilación de la Expresión Génica , Modelos Animales de Enfermedad , Degeneración Retiniana/patologíaRESUMEN
Single-cell sequencing (scRNA-seq) has revolutionized our ability to explore heterogeneity and genetic variations at the single-cell level, opening up new avenues for understanding disease mechanisms and cell-cell interactions. Single-nucleus RNA-sequencing (snRNA-seq) is emerging as a promising solution to scRNA-seq due to its reduced ionized transcription bias and compatibility with richer samples. This approach will provide an exciting opportunity for in-depth exploration of billions of formalin-fixed paraffin-embedded (FFPE) tissues. Recent advancements in single-cell/nucleus gene expression workflows tailored for FFPE tissues have demonstrated their feasibility and provided crucial guidance for future studies utilizing FFPE specimens. In this review, we provide a broad overview of the nuclear preparation strategies, the latest technologies of snRNA-seq applicable to FFPE samples. Finally, the limitations and potential technical developments of snRNA-seq in FFPE samples are summarized. The development of snRNA-seq technologies for FFPE samples will lay a foundation for transcriptomic studies of valuable samples in clinical medicine and human sample banks.
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Single-cell transcriptome sequencing (scRNA-seq) can resolve the expression characteristics of cells in tissues with single-cell precision, enabling researchers to quantify cellular heterogeneity within populations with higher resolution, revealing potentially heterogeneous cell populations and the dynamics of complex tissues. However, the presence of a large number of technical zeros in scRNA-seq data will have an impact on downstream analysis of cell clustering, differential genes, cell annotation, and pseudotime, hindering the discovery of meaningful biological signals. The main idea to solve this problem is to make use of the potential correlation between cells and genes, and to impute the technical zeros through the observed data. Based on this, this paper reviewed the basic methods of imputing technical zeros in the scRNA-seq data and discussed the advantages and disadvantages of the existing methods. Finally, recommendations and perspectives on the use and development of the method were provided.
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Transcriptoma , Análisis por ConglomeradosRESUMEN
The respiratory system's complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies.
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Perfilación de la Expresión Génica , Transcriptoma , Humanos , Biología Computacional , MultiómicaRESUMEN
Soil formation by rock weathering is driven by a combination of parent material, climate, organisms, topography, and time. Among these soil-forming factors, time plays a pivotal role in the weathering of carbonatite but it is a challenging factor to study quantitatively. A method for determining the weathering duration of carbonatite based on its weathering characteristics over a century-scale time period has not been clearly established. In this study, we selected abandoned carbonatite tombstones commonly found in the karst region of southwest China for investigation, using the date when the tombstones were erected as the onset of weathering. Chemical weathering indices were used to evaluate the weathering degree of different oxide contents produced by the carbonatite weathering process. In order to explore the weathering characteristics over time, the relationship between weathering duration and weathering degree was established. The results showed the following: (1) magnesium (Mg), aluminum (Al), silicon (Si), iron (Fe), titanium (Ti) are gradually enriched in the carbonatite regolith, and calcium (Ca) is gradually reduced. (2) The chemical indices of alteration (CIA), leaching coefficient (Lc), alumina-to-calcium ratio (AC) and mobiles index (Imob) can be successfully used for evaluation of the weathering degree of the carbonatite in different weathering time periods. (3) During the weathering of carbonatite, the weathering rate is a logarithmic function of time. Our research shows that over a period of more than 100 years of weathering, the carbonatite weathering process is characterized by fast weathering rates and low weathering degree in the early stages, but slow weathering rates in the later stages.
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Suelo , Tiempo (Meteorología) , Suelo/química , Hierro , Clima , MagnesioRESUMEN
Introduction: Microorganisms, including the pioneer microorganisms that play a role in the early colonization of rock, are extremely important biological factors in rock deterioration. The interaction of microorganisms with limestone leads to biodeterioration, accelerates soil formation, and plays an important role in the restoration of degraded ecosystems that cannot be ignored. However, the process of microbial colonization of sterile limestone in the early stages of ecological succession is unclear, as are the factors that affect the colonization. Acid erosion (both organic and inorganic), nutrient availability, and water availability are thought to be key factors affecting the colonization of lithobiontic microorganisms. Methods: In this study, organic acid (Oa), inorganic acid (Ia), inorganic acid + nutrient solution (Ia + Nut), nutrient solution (Nut), and rain shade (RS) treatments were applied to sterilized limestone, and the interaction between microorganisms and limestone was investigated using high-throughput sequencing techniques to assess the microorganisms on the limestone after 60 days of natural placement. Results: The results were as follows: (1) The abundance of fungi was higher than that of bacteria in the early colonization of limestone, and the dominant bacterial phyla were Proteobacteria, Bacteroidota, and Actinobacteriota, while the dominant fungal phyla were Ascomycota, Basidiomycota, and Chytridiomycota. (2) Acid erosion and nutrient availability shaped different microbial communities in different ways, with bacteria being more sensitive to the environmental stresses than fungi, and the higher the acidity (Ia and Oa)/nutrient concentration, the greater the differences in microbial communities compared to the control (based on principal coordinate analysis). (3) Fungal communities were highly resistant to environmental stress and competitive, while bacterial communities were highly resilient to environmental stress and stable. Discussion: In conclusion, our results indicate that limestone exhibits high bioreceptivity and can be rapidly colonized by microorganisms within 60 days in its natural environment, and both nutrient availability and acid erosion of limestone are important determinants of early microbial colonization.
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Beta-agonist pharmaceuticals are widely used in humans and livestock for disease treatment, legal or illegal growth promotion in food animals, bodybuilding, weight loss, and sports doping. The occurrence of beta-agonists in wastewater treatment plants and their subsequent environmental impacts require greater attention. This study determined the levels of 12 beta-agonists in a wastewater treatment plant and evaluated their ecotoxicological risks as well as consumption levels and risks to human health. Among the 12 selected beta-agonists, all were detected in wastewater and 11 in sludge. In most cases, the concentrations of beta-agonists were higher in spring than in summer. Their total average daily mass loads per capita in the influent and effluent were 1.35 µg/d/p and 2.11 µg/d/p, respectively. The overall removal efficiencies of individual beta-agonists ranged from -295.3 to 71.2%. Ecotoxicological risk assessment revealed a low risk to daphnid and green algae from the levels of fenoterol and the mixture of 12 selected beta-agonists in the effluent. The daily consumption levels of individual beta-agonists per capita were 0.028-1.200 µg/d/p. Regular monitoring of beta-agonists in municipal sewage systems and their risk assessment based on toxicological data are urgently required in the future.
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Contaminantes Químicos del Agua , Purificación del Agua , Animales , Humanos , Eliminación de Residuos Líquidos , Ecotoxicología , Contaminantes Químicos del Agua/análisis , Monitoreo del Ambiente , Aguas del Alcantarillado , China , Preparaciones FarmacéuticasRESUMEN
With the development of single-cell RNA sequencing technology (scRNA-seq), we have the ability to study biological questions at the level of the individual cell transcriptome. Nowadays, many analysis tools, specifically suitable for single-cell RNA sequencing data, have been developed. In this review, the currently commonly used scRNA-seq protocols are discussed. The upstream processing flow pipeline of scRNA-seq data, including goals and popular tools for reads mapping and expression quantification, quality control, normalization, imputation, and batch effect removal is also introduced. Finally, methods to evaluate these tools in both cellular and genetic dimensions, clustering and differential expression analysis are presented.
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Análisis de Expresión Génica de una Sola Célula , Programas Informáticos , Análisis de Secuencia de ARN/métodos , Análisis de la Célula Individual/métodos , Análisis de DatosRESUMEN
Although transcranial magnetic stimulation (TMS) has been approved for the treatment of major depression, few studies have analyzed the ability of low-frequency TMS (LF-TMS) to treat depressive symptoms. Our study confirmed that LF-TMS protects the cognitive function,which can play a certain reference role in the future clinical treatment. The effectiveness of high-frequency TMS therapy has been well documented. However, the use of low-frequency TMS (LF-TMS) in the treatment of depression is rarely reported. This study aims to evaluate whether LF-TMS can reverse depression-induced cognitive impairment. We created a mouse model of depression using the chronic unpredictable mild stress (CUMS) paradigm. Male C57BL/6J mice,6-8 weeks old,were randomly divided into four groups: a CON (control) group, a CUMS group, a CUMS+LF-TMS group, and a CUMS+LF-TMS+RAP (rapamycin) group. The CUMS was maintained for 28 days. LF-TMS (1 Hz) and Rap were administered for 28 days from the first day of CUMS. The mice in all groups except the control demonstrated evidence of anhedonia, anxiety, and cognitive decline on behavioral tests during the four weeks of CUMS.All the experiments were carried out under a 12-h light/dark cycle (lights on at 7 a.m.) except for the dark/light cycle reversal stimulation of CUMS. LF-TMS at 20 Mt, 1 Hz for 1 min alleviated damage to spatial cognition and synaptic plasticity in the hippocampus. Western blot analysis showed that LF-TMS reduced the down-regulation of autophagy signals in the CUMS+LF-TMS group, and enhanced the expression of synaptic plasticity-related factors, thereby improving the spatial cognitive impairment resulting from the CUMS. We concluded that LF-TMS can effectively relieve depressive behavior and cognitive dysfunction in mice subjected to CUMS by regulating autophagy signals and synaptic proteins.
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Disfunción Cognitiva , Estimulación Magnética Transcraneal , Ratones , Masculino , Animales , Ratones Endogámicos C57BL , Cognición , Plasticidad Neuronal/fisiología , Estrés Psicológico/metabolismo , Hipocampo/metabolismo , Depresión/tratamiento farmacológico , Modelos Animales de EnfermedadRESUMEN
The hippocampus is an important part of the limbic system in the human brain that has essential roles in spatial navigation and cognitive functions. It is still unknown how gene expression changes in single-cell in different spatial locations of the hippocampus of Parkinson's disease. The purpose of this study was to analyze the gene expression features of single cells in different spatial locations of mouse hippocampus, and to explore the effects of gene expression regulation on learning and memory mechanisms. Here, we obtained 74 single-cell samples from different spatial locations in a mouse hippocampus through microdissection technology, and used single-cell RNA-sequencing and spatial transcriptome sequencing to visualize and quantify the single-cell transcriptome features of tissue sections. The results of differential expression analysis showed that the expression of Sv2b, Neurod6, Grp and Stk32b genes in a hippocampus single cell at different locations was significantly different, and the marker genes of CA1, CA3 and DG subregions were identified. The results of gene function enrichment analysis showed that the up-regulated differentially expressed genes Tubb2a, Eno1, Atp2b1, Plk2, Map4, Pex5l, Fibcd1 and Pdzd2 were mainly involved in neuron to neuron synapse, vesicle-mediated transport in synapse, calcium signaling pathway and neurodegenerative disease pathways, thus affecting learning and memory function. It revealed the transcriptome profile and heterogeneity of spatially located cells in the hippocampus of PD for the first time, and demonstrated that the impaired learning and memory ability of PD was affected by the synergistic effect of CA1 and CA3 subregions neuron genes. These results are crucial for understanding the pathological mechanism of the Parkinson's disease and making precise treatment plans.