Short Time-series Expression Miner Research Articles

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

Numerous 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.

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.

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.

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.

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.

Genome-wide analysis of the KNOX gene family in Moso bamboo: insights into their role in promoting the rapid shoot growth

BackgroundKNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown.ResultsThe expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein–Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation.ConclusionsIn the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family.

Time-series analysis of hematopoietic stem cells.

This study aimed to investigate the molecular mechanisms underlying the aging of hematopoietic stem cells (HSCs). Gene expression profile GSE32719 was downloaded from the Gene Expression Omnibus database, including 14 young, 5 middle, and 8 old HSCs. Differential expression analysis, short time-series expression miner analysis, and weighted co-expression network analysis were conducted to screen for hub genes whose expression changed over time during HSC aging. Subsequently, functional enrichment and multiple regulatory network analyses of the hub genes were performed. A total of 124 intersecting time-dependent differentially expressed and module genes were obtained, which were considered hub genes whose expression changed over time during HSC aging. Hub genes were significantly enriched in pathways such as the Hippo and AMP-activated protein kinase (AMPK) signaling pathways. Moreover, AP-1 Transcription Factor Subunit (FOS) and sirtuin 1 (SIRT1) had higher degrees in the protein-protein interaction network, were regulated by more transcription factors (TFs), such as Sp1 transcription factor (SP1) and BRCA1 DNA repair-associated (BRCA1), in the TF-mRNA-miRNA network, were associated with more diseases in the disease-gene network, and could be targeted by more drugs in the drug-gene network. Furthermore, SIRT1 was targeted by miR-9-5p in the TF-mRNA-miRNA network. Hub genes such as FOS and SIRT1 and key pathways such as the Hippo and AMPK signaling pathways may play crucial roles in HSC aging. Moreover, FOS and SIRT1 were regulated by SP1 and BRCA1, respectively, during HSC aging. Furthermore, miR-9-5p may modulate HSC aging by targeting SIRT1. Thus, FOS and SIRT1 may be potential therapeutic targets for age-related hematopoietic dysfunction.

Transcriptome analysis reveals the molecular mechanisms of rubber biosynthesis and laticifer differentiation during rubber seed germination.

The molecular mechanisms underlying the initiation of natural rubber synthesis and laticifer differentiation have not been fully elucidated. In this study, we conducted a time-series transcriptome analysis of five rubber tree tissues at four stages of seed germination. A total of 161,199 DEGs were identified between the two groups, including most 16,673 DEGs (A3 vs B3 and A3 vs C3) and lest 1,210 DEGs (C2 vs D2). We found that the maturation of the seed is accompanied by the formation of laticifer cells in cotyledon. Meanwhile, the analysis of hormones related genes expression may provide effective clues for us to promote the differentiation of laticifer cells in seeds by hormones in the future. In this study, hormone-related gene enrichment analyses revealed that IAA, GA, and CTK were activated in laticifer containing tissues. Similarly, GO and GEGG analysis showed that hormone pathways, especially the auxin pathway, are enriched. Gene expression clustering was analyzed using the short time-series expression miner (STEM), and the analysis revealed four distinct trends in the gene expression profiles. Moreover, we enriched transcription factor (TF) enrichment in cotyledon and embryonic axis tissues, and the MYB type exhibited the most significant difference. Furthermore, our findings revealed that genes related to rubber synthesis exhibited tissue-specific expression patterns during seed germination. Notably, key genes associated with rubber biosynthesis, specifically small rubber particle protein (SRPP) and cis-prenyltransferase (CPT), exhibited significant changes in expression in cotyledon and embryonic axis tissues, suggesting synchronous rubber synthesis with seed germination. Our staining results reveled that laticifer cells were exits in the cotyledon before seed imbibition stage. In conclusion, these results lay the foundation for exploring the molecular mechanisms underlying laticifer differentiation and rubber synthesis during seed germination, deepening our understanding of the initiation stages of rubber biosynthesis and laticifer differentiation.

Identification of altered immune cell types and molecular mechanisms in Alzheimer's disease progression by single-cell RNA sequencing.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by gradual loss of cognitive function. Understanding the molecular mechanisms is crucial for developing effective therapies. Data from single-cell RNA sequencing (scRNA-seq) in the GSE181279 dataset and gene chips in the GSE63060 and GSE63061 datasets were collected and analyzed to identify immune cell types and differentially expressed genes. Cell communication, pseudotime trajectory, enrichment analysis, co- expression network, and short time-series expression miner were analyzed to identify disease-specific molecular and cellular mechanisms. We identified eight cell types (B cells, monocytes, natural killer cells, gamma-delta T cells, CD8+ T cells, Tem/Temra cytotoxic T cells, Tem/Trm cytotoxic T cells, and mucosal-associated invariant T cells) using scRNA-seq. AD samples were enriched in monocytes, CD8+ T cells, Tem/Temra cytotoxic T cells, and Tem/Trm cytotoxic T cells, whereas samples from healthy controls were enriched in natural killer and mucosal-associated invariant T cells. Five co-expression modules that were identified through weighted gene correlation network analysis were enriched in immune- inflammatory pathways. Candidate genes with higher area under the receiver operating characteristic curve values were screened, and the expression trend of Ubiquitin-Fold Modifier Conjugating Enzyme 1 (UFC1) gradually decreased from healthy controls to mild cognitive impairment and then to AD. Our study suggests that peripheral immune cells may be a potential therapeutic target for AD. Candidate genes, particularly UFC1, may serve as potential biomarkers for progression of AD.

Dynamic mRNA network profiles in macrophages challenged with lipopolysaccharide.

To elucidate the transcriptome of macrophages in an inflammation model induced by lipopolysaccharide (LPS), providing insight into the molecular basis of inflammation. We utilized RNA sequencing (RNA-seq) to analyze dynamic changes in gene expression in RAW264.7 macrophages treated with LPS at multiple time points. Differentially expressed genes (DEGs) were identified using the edgeR package. Short Time-series Expression Miner (STEM) and KEGG pathway enrichment analyses were conducted to determine temporal expression patterns during inflammation. We identified 2,512 DEGs, with initial inflammatory responses occurring in two distinct phases at 1 h and 3 h. Venn diagram analysis revealed 78 consistently dysregulated genes throughout the inflammatory process. A key module of 18 dysregulated genes was identified, including Irg1, which may exert an inhibitory effect on inflammation. Further, a second metabolic shift in activated macrophages was observed at the late middle stage (12 h). Multi-omics analysis highlighted the ribosome's potential regulatory role in the inflammatory response. This study provides a detailed view of the molecular mechanisms underlying inflammation in macrophages and reveals a dynamic genetic landscape crucial for further research. Our findings underscore the complex interaction between gene expression, metabolic shifts, and ribosomal functions in response to LPS-induced inflammation.

Proteomic and Metabolomic Profiling Elucidate the Impact of PEDV on Yorkshire Piglets and Reveal the Underlying Molecular Mechanism of PEDV Response

Porcine epidemic diarrhea virus (PEDV) is an RNA virus causing acute diarrhea, vomiting, dehydration and high mortality in piglets, and poses significant challenges for the global pig industry. However, the molecular mechanism underlying PEDV in piglets has not been well comprehended. In this study, we constructed the Yorkshire piglet model (control, resistance, and susceptible groups) to perform the proteomics of jejunum and metabolomics of serum. In total, 734 differentially expressed proteins (DEPs) and 208 significant differentially accumulated metabolites (DAMs) were identified, and the functional annotation showed that they were mainly involved in metabolic and signal transduction pathways. Further, we used weighted gene co-expression network analysis (WGCNA), short timeseries expression miner (STEM) and random forest analyses to detect key promising biomarkers for each corresponding group. By constructing the relationships between proteins and metabolites, we excavated the biomarkers and explained their molecular mechanism of the PEDV response. These data and results might be good resources for the PEDV infection and offer valuable insights into the molecular PEDV response mechanisms.

Comparative transcriptome analysis of major lodging resistant factors in hulless barley.

Hulless barley (Hordeum vulgare L. var. nudum Hook. f.), belonging to the genus Gramineae, has high and steady output and thus considered as a principal food crop by Tibetan people. Hulless barley grain can be used for food, brewing, and functional health product development, while its straw serves as an essential supplementary forage and is a crucial cereal crop. Lodging can reduce the yield and quality of barley grain and straw, and it hinders mechanical harvesting. It is a significant factor affecting high and stable yields of barley. Unlike other Poaceae plants (such as rice, wheat), hulless barley is mainly grown in high-altitude regions, where it is susceptible to low temperatures, strong winds, and heavy rainfall. As a result, its stem lodging resistance is relatively weak, making it prone to lodging during the growth period. In this study, we observed that the lignin concentration and the contents of lignin monomers (H, S, and G), and neutral detergent fibre of the lodging-resistant variety Kunlun14 were substantially greater than those of the lodging-sensitive variety Menyuanlianglan. We performed the weighted gene co-expression network analysis (WGCNA) and Short Time-series Expression Miner (STEM) analysis of both the lodging-resistant and lodging-sensitive varieties. Through transcriptome sequencing analysis at different developmental stages, combined with the previously annotated genes related to lodging resistance, a total of 72 DEGs were identified. Among these DEGs, 17 genes were related to lignin, cellulose, and hemicellulose synthesis or regulation, including five transcription factors about NAC, MYB and WRKY. Our results provide a basis for further exploring the molecular mechanism of stem lodging resistance in hulless barley and provide valuable gene resources for stem lodging resistance molecular breeding.

Transcriptome profiling in rumen, reticulum, omasum, and abomasum tissues during the developmental transition of pre-ruminant to the ruminant in yaks.

The development of the four stomachs of yak is closely related to its health and performance, however the underlying molecular mechanisms are largely unknown. Here, we systematically analyzed mRNAs of four stomachs in five growth time points [0 day, 20 days, 60 days, 15 months and 3 years (adult)] of yaks. Overall, the expression patterns of DEmRNAs were unique at 0 d, similar at 20 d and 60 d, and similar at 15 m and adult in four stomachs. The expression pattern in abomasum was markedly different from that in rumen, reticulum and omasum. Short Time-series Expression Miner (STEM) analysis demonstrated that multi-model spectra are drastically enriched over time in four stomachs. All the identified mRNAs in rumen, reticulum, omasum and abomasum were classified into 6, 4, 7, and 5 cluster profiles, respectively. Modules 9, 38, and 41 were the most significant three colored modules. By weighted gene co-expression network analysis (WGCNA), a total of 5,486 genes were categorized into 10 modules. CCKBR, KCNQ1, FER1L6, and A4GNT were the hub genes of the turquoise module, and PAK6, TRIM29, ADGRF4, TGM1, and TMEM79 were the hub genes of the blue module. Furthermore, functional KEGG enrichment analysis suggested that the turquoise module was involved in gastric acid secretion, sphingolipid metabolism, ether lipid metabolism, etc., and the blue module was enriched in pancreatic secretion, pantothenate and CoA biosynthesis, and starch and sucrose metabolism, etc. Our study aims to lay a molecular basis for the study of the physiological functions of rumen, reticulum, omasum and abomasum in yaks. It can further elucidate the important roles of these mRNAs in regulation of growth, development and metabolism in yaks, and to provide a theoretical basis for age-appropriate weaning and supplementary feeding in yaks.

Comparative transcriptional and co-expression network analysis of two upland cotton accessions with extreme phenotypic differences reveals molecular mechanisms of fiber development.

Upland cotton (Gossypium hirsutum) is the main source of natural fiber in the global textile industry, and thus its fiber quality and yield are important parameters. In this study, comparative transcriptomics was used to analyze differentially expressed genes (DEGs) due to its ability to effectively screen candidate genes during the developmental stages of cotton fiber. However, research using this method is limited, particularly on fiber development. The aim of this study was to uncover the molecular mechanisms underlying the whole period of fiber development and the differences in transcriptional levels. Comparative transcriptomes are used to analyze transcriptome data and to screen for differentially expressed genes. STEM and WGCNA were used to screen for key genes involved in fiber development. qRT-PCR was performed to verify gene expression of selected DEGs and hub genes. Two accessions of upland cotton with extreme phenotypic differences, namely EZ60 and ZR014121, were used to carry out RNA sequencing (RNA-seq) on fiber samples from different fiber development stages. The results identified 704, 376, 141, 269, 761, and 586 genes that were upregulated, and 1,052, 476, 355, 259, 702, and 847 genes that were downregulated at 0, 5, 10, 15, 20, and 25 days post anthesis, respectively. Similar expression patterns of DEGs were monitored using short time-series expression miner (STEM) analysis, and associated pathways of DEGs within profiles were investigated. In addition, weighted gene co-expression network analysis (WGCNA) identified five key modules in fiber development and screened 20 hub genes involved in the development of fibers. Through the annotation of the genes, it was found that the excessive expression of resistance-related genes in the early fiber development stages affects the fiber yield, whereas the sustained expression of cell elongation-related genes is critical for long fibers. This study provides new information that can be used to improve fibers in newly developed upland cotton genotypes.