Time-series Expression Research Articles

Time-Dependent Transcriptional Dynamics of Contextual Fear Memory Retrieval Reveals the Function of Dipeptidyl Peptidase 9 in Reconsolidation

AbstractNumerous studies on the formation and consolidation of memory have shown that memory processes are characterized by phase-dependent and dynamic regulation. Memory retrieval, as the only representation of memory content and an active form of memory processing that induces memory reconsolidation, has attracted increasing attention in recent years. Although the molecular mechanisms specific to memory retrieval-induced reconsolidation have been gradually revealed, an understanding of the time-dependent regulatory mechanisms of this process is still lacking. In this study, we applied a transcriptome analysis of memory retrieval at different time points in the recent memory stage. Differential expression analysis and Short Time-series Expression Miner (STEM) depicting temporal gene expression patterns indicated that most differential gene expression occurred at 48 h, and the STEM cluster showing the greatest transcriptional upregulation at 48 h demonstrated the most significant difference. We then screened the differentially-expressed genes associated with that met the expression patterns of those cluster-identified genes that have been reported to be involved in learning and memory processes in addition to dipeptidyl peptidase 9 (DPP9). Further quantitative polymerase chain reaction verification and pharmacological intervention suggested that DPP9 is involved in 48-h fear memory retrieval and viral vector-mediated overexpression of DPP9 countered the 48-h retrieval-induced attenuation of fear memory. Taken together, our findings suggest that temporal gene expression patterns are induced by recent memory retrieval and provide hitherto undocumented evidence of the role of DPP9 in the retrieval-induced reconsolidation of fear memory.

Construction and Analysis of miRNA-mRNA Interaction Network in Ovarian Tissue of Wanxi White Geese Across Different Breeding Stages.

Ovarian development significantly influences the laying performance of geese. In this study, the transcriptome analysis was conducted on the ovarian tissues of Wanxi White Geese during the pre-laying (KL), laying (CL), and ceased-laying period (XL). Short Time-series Expression Miner (STEM) analysis and miRNA-mRNA regulatory network construction were performed to identify the key genes and miRNAs regulating laying traits. Comparative analysis of KL vs. CL, CL vs. XL, and XL vs. KL groups resulted in the identification of 337, 136, and 525 differentially expressed genes (DEGs), and 258, 1131, and 909 differentially expressed miRNAs (DEMs), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (p < 0.05) revealed that the main enrichment pathways of DEGs and DEMs at different breeding periods were Neuroactive ligand-receptor interaction, GnRH signaling pathway and Wnt signaling pathway, all associated with ovarian development. According to the three groups of common pathways, four DEGs were screened out, including INHBB, BMP5, PRL, and CGA, along with five DEMs, including let-7-x, miR-124-y, miR-1-y, and miR-10926-z, all of them may affect ovarian development. A miRNA-mRNA regulatory network was constructed through integrated analysis of DEGs and DEMs, revealing nine miRNAs highly associated with ovarian development: miR-101-y, let-7-x, miR-1-x, miR-17-y, miR-103-z, miR-204-x, miR-101-x, miR-301-y, and miR-151-x. The dual-luciferase reporter gene verified the target relationship between WIF1 and miR-204-x, suggesting that these miRNAs may influence ovarian development in Wanxi White Goose by regulating the expression levels of their target genes within ovarian tissue. This study provides a theoretical foundation for analyzing the mechanisms of ovarian development across different breeding periods and accelerating the cultivation of new breeds through post-transcriptional regulation levels.

Metabolic Differences among Patients with Cirrhosis Using Q Exactive Hybrid Quadrupole Orbitrap Mass Spectrometry Technology.

The hospitalization and mortality rates of patients gradually increase following the onset and progression of liver cirrhosis (LC). We aimed to help define clinical stage and better target interventions by detecting the expression of specific metabolites in patients with different stages of LC via Q Exactive hybrid quadrupole orbitrap mass spectrometry (UPLC-Q-Exactive) technology. This noninterventional observation case-control study involved 139 patients with LC or acute-on-chronic liver failure (ACLF) in a Chinese hospital between October 2022 and April 2023. Serum specimens were analyzed for multiple metabolite levels using UPLC-Q-Exactive. Data were processed to screen for differentially accumulated metabolites (DAMs). Short time-series expression miner (STEM) analysis and enrichment analysis were performed to assess cirrhosis progression biomarkers. Following univariate and multivariate analyses, a Venn diagram indicated nine significant DAMs in common among groups. STEM analysis showed 8'-hydroxyabscisic acid, HDCA, pyruvate-3-phosphate, indospicine, eplerenone, and DEHP as significant; their levels first peaked [Child-Turcotte-Pugh (CTP) class B peaked] and then decreased with CTP grade aggravation. Significant differences among 8'-hydroxyabscisic acid, eplerenone, and DEHP were observed among LC comorbidities and between subgroups. Therefore, serum levels of six DAMs may characterize metabolomic changes, determine the severity of LC, and predict the development of ACLF.

Modeling of Liquefied Natural Gas Cold Power Generation for Access to the Distribution Grid

Cold energy generation is an important part of liquefied natural gas (LNG) cold energy cascade utilization, and existing studies lack a specific descriptive model for LNG cold energy transmission to the AC subgrid. Therefore, this paper proposes a descriptive model for the grid-connected process of cold energy generation at LNG stations. First, the expansion kinetic energy transfer of the intermediate work mass is derived and analyzed in the LNG unipolar Rankine cycle structure, the mathematical relationship between the turbine output mechanical power and the variation in the work mass flow rate and pressure is established, and the variations in the LNG heat exchanger temperature difference, seawater flow rate, and the turbine temperature difference in the cycle system are investigated. Secondly, based on the fifth-order equation of state of the synchronous generator, the expressions of its electromagnetic power, output AC frequency, and voltage were analyzed. Finally, the average equivalent models of the machine-side and grid-side converters are established using a direct-fed grid-connected structure, thus forming a descriptive model of the overall drive process. The ORC model is built in Aspen HYSIS to obtain the time series expression of the torque output of the turbine; based on the ORC output torque, the permanent magnet synchronous generator (PMGSG) as well as the direct-fed grid-connected structure are built in MATLAB/Simulink, and the active power and current outputs of the grid-following-type voltage vector control method and the grid-forming-type power-angle synchronous control method are also verified.

A systematic regulatory network related to bulbil formation in Lilium lancifolium based on metabolome and transcriptome analyses

BackgroundLilium lancifolium is a special wild triploid species native to China and can produce abundant bulbils on its stem under natural conditions, which is very valuable to study bulbil organogenesis in plants. Although similar to the lateral and tillering principles, the molecular mechanism underlying bulbil formation has remained incompletely understood.ResultsThe metabolome and transcriptome of L. lancifolium bulbils across four development stages were analyzed. The pairwise comparison of metabolomes across the four stages identified 17 differential hormones, predominantly auxin (IAA), cytokinin (CK), and jasmonic acid (JA). Short Time-series Expression Miner (STEM) trend analysis of differential genes revealed four significant trends across these stages. The KEGG enrichment analysis of the four clusters highlighted pathways, such as plant hormone signal transduction, which were speculated to play a crucial role in development stages. these pathways were speculated to play a crucial role in development stages. To explore the key differential expressed genes and transcription factors associated with bulbil occurrence, two periods were focused on: Ll_UN and Ll_DN, which represented the stages with and without bulbils, respectively. Through correlation analysis and qRT-PCR analysis, 11 candidate differentially expressed genes and 27 candidate transcription factors were selected. By spraying exogenous hormones to validate these candidates, LlbHLH128, LlTIFY10A, LlbHLH93, and LlMYB108, were identified as the key genes for L. lancifolium bulbils.ConclusionA regulatory network of L. lancifolium bulbil development was predicted. LlTIFY10A and LlbHLH93 might be involved in the JA and auxin signal transduction pathways, which jointly formed a regulatory network to affect the occurrence of L. lancifolium bulbil. This study not only provided more information about the differentially expressed genes and metabolites through transcriptome and metabolomics analyses, but also provided a clearer understanding of the effect of hormones on bulbil formation in lily.

Screening and expression validation of key proteins for secondary hair follicle growth in cashmere goats based on iTRAQ quantitative proteomics technology.

The growth of secondary hair follicles (SHFs) in cashmere goats has periodic changes, including telogen, anagen, and catagen, during which proteins play important roles as the executor of life activities. In this study, the skin tissues of cashmere goats at three different growth stages of SHFs were collected for proteome sequencing and validation experiments. Through protein differential expression analysis and time series analysis, FKBP prolyl isomerase 10 (FKBP10) and fibrillin 2 (FBN2) were screened as the key proteins for SHF cycle growth of cashmere goats, and albumin (ALB), collagen type I alpha 1 chain (COL1A1) and elastin (ELN) were predicted to be their interacting proteins. The results of quantitative real-time PCR (qRT-PCR), western blot, and immunohistochemistry experiments showed that the mRNA and protein expression levels of FKBP10, FBN2, COL1A1, ELN and ALB were higher in anagen and lower in telogen. They were all highly expressed in the outer root sheath of SHFs in anagen. FKBP10, FBN2, COL1A1, ELN, and ALB can promote the growth of SHFs in cashmere goats. This study lays the foundation for analyzing the growth cycle regulatory mechanism of SHFs in cashmere goats, and provides new ideas for further improving cashmere yield and quality.

Comparative transcriptomic analysis of goose astrovirus genotype 1 and 2 in goose embryonic fibroblasts

Gout in goslings has become widespread and caused huge economic losses for the goose industry. Emerging evidence suggests that goose astrovirus (GAstV) is a prominent etiological factor of gout in goslings. At present, 2 genotypes of GAstV have been identified named GAstV-1 and GAstV-2. Here, we isolated the GAstV-1 HBLY strain and GAstV-2 XT1 strain from HeBei province of China. The genome and proliferation characteristics of GAstV-1 and GAstV-2 were analyzed and the results showed that the whole genome identity was 53.8% to 55.8%, especially the nucleotide and amino acids identity of ORF2 and Cap protein was only 49.5% to 50.5% and 19.6% to 22.6 %. Interestingly, GAstV-1 and GAstV-2 with such low homology both can cause gout in goslings. To further explore this phenomenon, the whole genomic expression profile of goose embryonic fibroblasts (GEFs) infected with GAstV-1 was investigated in comparison with GAstV-2. The results revealed that 126 differentially expressed genes (DEGs) were identified between GAstV-1-infected and uninfected cells at 48 h postinfection (hpi), and 262 DEGs between GAstV-2 and uninfected. Among these, there are 15 commonly up-regulated genes and 19 commonly down-regulated genes. Gene ontology (GO) enrichment analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and short time-series expression miner (STEM) analysis suggested that GAstV-1 can induce a higher innate immune response to GEFs, while GAstV-2 has a more pronounced effect on GEFs metabolic pathways. The transcriptomic analysis results significantly enhance our comprehension of the pathogenic mechanisms of GAstV.

Quantitative Aspect of Bacillus subtilis σB Regulatory Network on a Proteome Level-A Computational Simulation.

Bacillus subtilis is a model organism used to study molecular processes in Gram-positive bacteria. Sigma factor B, which associates with RNA polymerase, is one of the transcriptional regulators involved in the cell's response to environmental stress. Experiments have proven that the amounts of free σB (SigB) are controlled by a system of anti- (RsbW) and anti-anti-sigma (RsbV) factors expressed from the same operon as SigB. Moreover, the phosphorylation state of RsbV is controlled by phosphatases RsbP and RsbU, which directly dephosphorylate RsbV. A set of chemical equations describing the network controlling the levels of free SigB was converted to a set of differential equations quantifying the dynamics of the network. The solution of these equations allowed the simulation of the kinetic behavior of the network and its components under real conditions reflected in the time series of protein expression. In this study, the time series of protein expression measured by mass spectrometry were utilized to investigate the role of phosphatases RsbU/RsbP in transmitting the environmental signal. Additionally, the influence of kinetic constants and the amounts of other network components on the functioning of the network was investigated. A comparison with the same simulation performed using a transcriptomic dataset showed that while the time series between the proteomic and transcriptomic datasets are not correlated, the results are the same. This indicates that when modeling is performed within one dataset, it does not matter whether the data come from the mRNA or protein level. In summary, the computational results based on experimental data provide a quantitative insight into the functioning of the SigB-dependent circuit and offer a template for the quantitative study of similar systems.

Short time-series expression transcriptome data reveal the gene expression patterns and potential biomarkers of blood infection with LPS and poly (I:C) in Mandarin fish (Siniperca chuatsi)

Blood transcriptomics has emerged as a vital tool for tracking the immune system and supporting disease diagnosis, prognosis, treatment, and research. The present study was conducted to analyze the gene expression profile and potential biomarker candidates using the whole blood of mandarin fish (Siniperca chuatsi) infected with LPS or poly (I:C) at 0 h, 3 h, 6 h, and 12 h. Our data suggest that 310 shared differentially expressed genes (DEGs) were identified among each comparison group after LPS infection, and 137 shared DEGs were identified after poly (I:C) infection. A total of 62 shared DEGs were differentially expressed in all compared groups after LPS or poly (I:C) infection. Pathways analysis for DEGs in all different compared groups showed that cytokine-cytokine receptor interaction was the most enrichment pathway. The expression levels of genes C-X-C chemokine receptor type 2-like (cxcr2), chemokine (C-C motif) receptor 9a (ccr9a), chemokine (C-C motif) receptor 9b (ccr9b), chemokine (C-X-C motif) receptor 4b (cxcr4b), and interleukin 10 receptor alpha (il10ra) were significantly different in all compared groups and most enriched in cytokine-cytokine receptor interaction pathway. The protein-protein interactions analysis among all shared DEGs showed that cxcr4 was the hub gene with the highest degree. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring mandarin fish diseases.

Quantification of circadian rhythms in mammalian lung tissue snapshot data

Healthy mammalian cells have a circadian clock, a gene regulatory network that allows them to schedule their physiological processes to optimal times of the day. When healthy cells turn into cancer cells, the circadian clock often becomes cancer specifically disturbed, so there is an interest in the extraction of circadian features from gene expression data of cancer. This is challenging, as clinical gene expression samples of cancer are snapshot-like and the circadian clock is best examined using gene expression time series. In this study, we obtained lists of intersecting circadian genes in public gene expression time series data of lung tissue of mouse and baboon. We base our circadian gene lists on correlations of gene expression levels of circadian genes, which are closely associated to the phase differences between them. Combining circadian gene expression patterns of diurnal and nocturnal species of different ages provides circadian genes that are also important in healthy and cancerous human lung tissue. We tested the quality of the representation of the circadian clock in our gene lists by PCA-based reconstructions of the circadian times of the mouse and baboon samples. Then we assigned potential circadian times to the human lung tissue samples and find an intact circadian clock in the healthy human lung tissue, but an altered, weak clock in the adjacent cancerous lung tissue.

Liver transcriptome changes in pearl gentian grouper in response to acute high-temperature stress

Pearl gentian grouper is the main cultivated grouper variety along the southeast coast of China. However, the coastal waters often experience prolonged of high temperatures during summer due to global climate warming and frequent extreme high-temperature events near the coast. As a result, the high-temperature stress seriously hinders the development and growth of grouper aquaculture. In this study, SMRT-Seq and RNA-Seq sequencing techniques were used to analyze the gene expression changes in the pearl gentian grouper liver under room temperature (25 °C) and acute high temperatures (30, 34, 38, and 38 °C for 6 h). Based on the differential expression analysis, Short Time-series Expression Miner (STEM), and Weighted Gene Co-expression Network Analysis (WGCNA), 4144 differentially expressed genes (DEGs), two significantly expressed gene profiles (Profile0 and Profile19), and two high-temperature specific modules (Blue and Turquoise) were identified. The results revealed that the grouper responded to acute high-temperature stress by regulating genes enriched in biological processes, such as protein homeostasis, oxidative defense, apoptosis, and glucose and lipid metabolisms. Furthermore, 34 °C and 38 °C were confirmed as the key temperature points for the significant alterations in the physiological and metabolic processes of pearl gentian grouper under high-temperature stress, corresponding to the critical suitable growth temperature and high-temperature tolerance, respectively. The findings in this study provide a solid theoretical basis for understanding the high-temperature adaptation mechanism of pearl gentian grouper. They also provide important guidelines for promoting the development of the grouper aquaculture industry and molecular breeding high-temperature resistant grouper varieties.

Exploring the effect of part differences on metabolite molecule changes in refrigerated pork: Identifying key metabolite compounds and their conversion pathways

Effect of part differences on metabolite molecule alterations in refrigerated pork was investigated. A metabolomics methodology combined with chemometric analysis was successfully established to identify key compounds and their conversion pathways, including precursors and volatile metabolites, in the Longissimus lumborum as well as the breast and flank stored for 11 days. In total, 12 discriminative precursors were identified using the Short Time-series Expression Miner. In tandem with Random Forest and ANOVA analyses, nine volatile metabolites were identified as key compounds that could be attributed to differences in pork sections. Bidirectional orthogonal partial least squares analysis revealed a potential correlation between these key metabolites and discriminative precursors. Metabolic pathway enrichment analysis demonstrated that the primary metabolic process affected by variations in pork sections is linoleic acid metabolism, which participates in the metabolism of cysteine and glutamic acid to produce methoxy-phenyl-oxime. This study provides valuable insights into the identification of differential metabolites.

Improving iPSC Differentiation Using a Nanodot Platform.

Differentiation of induced pluripotent stem cells (iPSCs) is an extremely complex process that has proven difficult to study. In this research, we utilized nanotopography to elucidate details regarding iPSC differentiation by developing a nanodot platform consisting of nanodot arrays of increasing diameter. Subjecting iPSCs cultured on the nanodot platform to a cardiomyocyte (CM) differentiation protocol revealed several significant gene expression profiles that were associated with poor differentiation. The observed expression trends were used to select existing small-molecule drugs capable of modulating differentiation efficiency. BRD K98 was repurposed to inhibit CM differentiation, while iPSCs treated with NSC-663284, carmofur, and KPT-330 all exhibited significant increases in not only CM marker expression but also spontaneous beating, suggesting improved CM differentiation. In addition, quantitative polymerase chain reaction was performed to determine the gene regulation responsible for modulating differentiation efficiency. Multiple genes involved in extracellular matrix remodeling were correlated with a CM differentiation efficiency, while genes involved in the cell cycle exhibited contrasting expression trends that warrant further studies. The results suggest that expression profiles determined via short time-series expression miner analysis of nanodot-cultured iPSC differentiation can not only reveal drugs capable of enhancing differentiation efficiency but also highlight crucial sets of genes related to processes such as extracellular matrix remodeling and the cell cycle that can be targeted for further investigation. Our findings confirm that the nanodot platform can be used to reveal complex mechanisms behind iPSC differentiation and could be an indispensable tool for optimizing iPSC technology for clinical applications.

SCG5 and MITF may be novel markers of copper metabolism immunorelevance in Alzheimer’s disease

The slow-developing neurological disorder Alzheimer’s disease (AD) has no recognized etiology. A bioinformatics investigation verified copper metabolism indicators for AD development. GEO contributed AD-related datasets GSE1297 and GSE5281. Differential expression analysis and WGCNA confirmed biomarker candidate genes. Each immune cell type in AD and control samples was scored using single sample gene set enrichment analysis. Receiver Operating Characteristic (ROC) analysis, short Time-series Expression Miner (STEM) grouping, and expression analysis between control and AD samples discovered copper metabolism indicators that impacted AD progression. We test clinical samples and cellular function to ensure study correctness. Biomarker-targeting miRNAs and lncRNAs were predicted by starBase. Trust website anticipated biomarker-targeting transcription factors. In the end, Cytoscape constructed the TF/miRNA-mRNA and lncRNA-miRNA networks. The DGIdb database predicted biomarker-targeted drugs. We identified 57 differentially expressed copper metabolism-related genes (DE-CMRGs). Next, fourteen copper metabolism indicators impacting AD progression were identified: CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38. A TF/miRNA-mRNA regulation network was then established with two miRNAs (hsa-miR-34a-5p and 34c-5p), six TFs (NFKB1, RELA, MYC, HIF1A, JUN, and SP1), and four biomarkers. The DGIdb database contained 171 drugs targeting ten copper metabolism-relevant biomarkers (BRCA1, MITF, NFKBIA, CD38, CCK2, HPRT1, SPHK1, LDHA, SCG5, and SYT1). Copper metabolism biomarkers CCK, ATP6V1E1, SYT1, LDHA, PAM, HPRT1, SCG5, ATP6V1D, GOT1, NFKBIA, SPHK1, MITF, BRCA1, and CD38 alter AD progression, laying the groundwork for disease pathophysiology and novel AD diagnostic and treatment.

Integrated analysis of muscle transcriptome, miRNA, and proteome of Chinese indigenous breed Ningxiang pig in three developmental stages.

The Ningxiang pig, a distinguished local breed in China, is recognized for its good meat quality traits. This study examines the proteomics of Ningxiang pigs at three developmental stages and delves into the upstream transcriptomics of these proteomics. Such an analysis facilitates a deeper understanding of the molecular interplay between proteins and transcriptomes in the Ningxiang pig muscle, influencing muscle growth and development. In this research, we analyzed the muscles of Ningxiang pigs at three developmental stages: 30days in weaned piglets, 90days in nursery pigs, and 210days in late fattening pigs. There a total of 16 differentially co-expressed miRNAs (ssc-miRNA-1, ssc-miRNA-378, ssc-miRNA-143, ssc-miRNA-30e, etc.), 74 differentially co-expressed mRNA (PLIN3, CPT2, IGF2 and HSP90AB1, etc.) have been identified in the three stages. 572 differentially abundant proteins (DAPs) (APOC3, NDUFA2, HSPD1, ATP5E, PDHA1, etc.) were readily identified by comparing different time periods. According to the KEGG enrich pathway results that DAPs most enriched in growth and development pathways, immune mechanism pathways and maintaining functions of physical. Through short time-series expression miner (STEM) association analysis, a total of 571 negative miRNA-mRNA interaction pairs and 2 negative miRNA-mRNA-protein (Chr05_11955-Pig.17268.1-ATP5F1B, ssc-miR-194a-3p-Pig.15802.1-ACY1) interaction pairs were found. Our study provides a theoretical basis on molecular mechanism for the study of IMF deposition, muscle growth and immunity in Ningxiang pig breed.

A time-resolved multi-omics atlas of transcriptional regulation in response to high-altitude hypoxia across whole-body tissues

High-altitude hypoxia acclimatization requires whole-body physiological regulation in highland immigrants, but the underlying genetic mechanism has not been clarified. Here we use sheep as an animal model for low-to-high altitude translocation. We generate multi-omics data including whole-genome sequences, time-resolved bulk RNA-Seq, ATAC-Seq and single-cell RNA-Seq from multiple tissues as well as phenotypic data from 20 bio-indicators. We characterize transcriptional changes of all genes in each tissue, and examine multi-tissue temporal dynamics and transcriptional interactions among genes. Particularly, we identify critical functional genes regulating the short response to hypoxia in each tissue (e.g., PARG in the cerebellum and HMOX1 in the colon). We further identify TAD-constrained cis-regulatory elements, which suppress the transcriptional activity of most genes under hypoxia. Phenotypic and transcriptional evidence indicate that antenatal hypoxia could improve hypoxia tolerance in offspring. Furthermore, we provide time-series expression data of candidate genes associated with human mountain sickness (e.g., BMPR2) and high-altitude adaptation (e.g., HIF1A). Our study provides valuable resources and insights for future hypoxia-related studies in mammals.

Biclustering analysis on tree-shaped time-series single cell gene expression data of Caenorhabditis elegans

BackgroundIn recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals. On the other hand, the influence of cell type heterogeneity should also be considered during clustering, aiming to obtain more biologically significant clustering results.ResultsA biclustering model is proposed for tree-shaped single-cell gene expression data of Caenorhabditis elegans. Detailedly, a tree-shaped piecewise polynomial function is first employed to fit non-pairwise gene expression time series data. Then, four factors are considered in the objective function, including Pearson correlation coefficients capturing gene correlations, p-values from the Kolmogorov-Smirnov test measuring the similarity between cells, as well as gene expression size and bicluster overlapping size. After that, Genetic Algorithm is utilized to optimize the function.ConclusionThe results on the small-scale dataset analysis validate the feasibility and effectiveness of our model and are superior to existing classical biclustering models. Besides, gene enrichment analysis is employed to assess the results on the complete real dataset analysis, confirming that the discovered biclustering results hold significant biological relevance.

Identification of Key Genes of Fruit Shape Variation in Jujube with Integrating Elliptic Fourier Descriptors and Transcriptome.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

Spock2 Functions as a Key Time-Series Gene of Endothelial Cells in Sepsis-Induced Cardiomyopathy.

The study aimed to investigate the pathogenesis of sepsis-induced cardiomyopathy, a leading cause of mortality in septic patients. Transcriptome data from cecal ligation and puncture-induced septic mice were analyzed at different time points (24, 48, and 72 hours) using GSE171546 data. Through weighted gene co-expression network analysis, time series, and differential expression analyses, key time-series differentially expressed genes were identified. In addition, single-cell sequencing data (GSE207363) were used for both differential and pseudotime analyses to pinpoint differentially expressed genes specific to endothelial cells. The study highlighted Spock2, S100a9, S100a8, and Xdh as differential genes specific to endothelial cells in a time-dependent manner. Immunofluorescence validation confirmed the increased expression of SPOCK2 in the endothelial cells of cecal ligation and puncture-induced septic mice. Furthermore, in vitrostudies showed that deletion of Spock2 significantly increased LPS-induced apoptosis and necrosis in human umbilical vein endothelial cells. In conclusion, SPOCK2 expression was increased in septic cardiac endothelial cells and LPS-induced human umbilical vein endothelial cells and may play a protective role.

Effects of Long-Term Cryopreservation on the Transcriptomes of Giant Grouper Sperm.

The giant grouper fish (Epinephelus lanceolatus), one of the largest and rarest groupers, is a fast-growing economic fish. Grouper sperm is often used for cross-breeding with other fish and therefore sperm cryopreservation is important. However, freezing damage cannot be avoided. Herein, we performed a transcriptome analysis to compare fresh and frozen sperm of the giant grouper with frozen storage times of 0, 23, 49, and 61 months. In total, 1911 differentially expressed genes (DEGs), including 91 in El-0-vs-El-23 (40 upregulated and 51 downregulated), 251 in El-0-vs-El-49 (152 upregulated and 69 downregulated), and 1569 in El-0-vs-El-61 (984 upregulated and 585 downregulated), were obtained in the giant grouper sperm. DEGs were significantly increased at 61 months of cryopreservation (p < 0.05). GO and KEGG enrichment analyses of the DEGs revealed significant enrichment in the pilus assembly, metabolic process, MAPK signaling pathway, apoptosis, and P53 signaling pathway. Time-series expression profiling of the DEGs showed that consistently upregulated modules were also significantly enriched in signaling pathways associated with apoptosis. Four genes, scarb1, odf3, exoc8, and atp5f1d, were associated with mitochondria and flagella in a weighted correlation network analysis. These genes may play an important role in the response to sperm freezing. The experimental results show that long-term cryopreservation results in freezing damage to the giant grouper sperm. This study provides rich data for studies of the mechanism underlying frozen fish sperm damage as well as a technical reference and evaluation index for the long-term cryopreservation of fish sperm.