Short Time-series Expression Miner Research Articles

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.

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.

Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis.

The goal of the present study was to identify different transcriptome expression profiles involved in the pathogenesis of deep vein thrombosis (DVT), and to illustrate the diagnostic and therapeutic potential of circular RNAs (circRNAs) and mRNAs in DVT progression. A Sprague-Dawley rat model of DVT was successfully established through the stenosis method and samples were sequenced at four time points (1, 6 and 12 h, and 3 days after ligation) to observe the dynamic changes in circRNAs and mRNAs during DVT progression. RNA sequencing was used to analyze the circRNA and mRNA expression profiles, and associated functions and pathways, in the blood of DVT rats at the four time points. In addition, Short Time Series Expression Miner (STEM) analysis was performed to explore temporal gene expression. Differential expression of 1,680, 4,018, 3,724, and 3,036 circRNAs, and 400, 1,176, 373, and 573 mRNAs was observed in the 1, 6 and 12 h, and 3-day groups, respectively, compared with the sham group (fold change >2.0 or <-2.0, P<0.05). Functional enrichment analysis indicated that differentially expressed mRNAs were associated with the following terms: Immune response, cell activation, blood stasis facilitated organelle, extracellular membrane-bounded organelle, and blood microparticle, oxygen transporter activity. STEM analysis indicated that the expression of 366 circRNAs in circRNA profile 45 and 270 mRNAs in mRNA profile 45 was consistent with thrombus progression. Enrichment analysis was performed on mRNA profile 45. The main Gene Ontology annotations were chromosome segregation, mitotic sister chromatid segregation, cell cycle process, and ligand-dependent nuclear receptor transcription coactivator activity. Pathway enrichment analysis identified the platelet-associated pathway, immune-associated pathway, and inflammation-relation pathway. According to the enriched platelet-associated pathways, four mRNAs and ten candidate circRNAs were selected for reverse transcription-quantitative PCR verification. The expression of nine of the ten circRNAs and all four mRNAs was consistent with the sequencing results. In summary, differentially expressed circRNAs and mRNAs are dynamically involved in DVT development. Dysregulated transcriptome profiles and the corresponding functions and pathways may provide mechanistic insights into DVT diagnosis and treatment.

Transcriptomic Analysis Reveals the Impact of the Biopesticide Metarhizium anisopliae on the Immune System of Major Workers in Solenopsis invicta.

The red imported fire ant (Solenopsis invicta Buren, 1972) is a globally significant invasive species, causing extensive agricultural, human health, and biodiversity damage amounting to billions of dollars worldwide. The pathogenic fungus Metarhizium anisopliae (Metchnikoff) Sorokin (1883), widely distributed in natural environments, has been used to control S. invicta populations. However, the interaction between M. anisopliae and the immune system of the social insect S. invicta remains poorly understood. In this study, we employed RNA-seq to investigate the effects of M. anisopliae on the immune systems of S. invicta at different time points (0, 6, 24, and 48 h). A total of 1313 differentially expressed genes (DEGs) were identified and classified into 12 expression profiles using short time-series expression miner (STEM) for analysis. Weighted gene co-expression network analysis (WGCNA) was employed to partition all genes into 21 gene modules. Upon analyzing the statistically significant WGCNA model and conducting Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the modules, we identified key immune pathways, including the Toll and Imd signaling pathways, lysosomes, autophagy, and phagosomes, which may collectively contribute to S. invicta defense against M. anisopliae infection. Subsequently, we conducted a comprehensive scan of all differentially expressed genes and identified 33 immune-related genes, encompassing various aspects such as recognition, signal transduction, and effector gene expression. Furthermore, by integrating the significant gene modules derived from the WGCNA analysis, we constructed illustrative pathway diagrams depicting the Toll and Imd signaling pathways. Overall, our research findings demonstrated that M. anisopliae suppressed the immune response of S. invicta during the early stages while stimulating its immune response at later stages, making it a potential biopesticide for controlling S. invicta populations. These discoveries lay the foundation for further understanding the immune mechanisms of S. invicta and the molecular mechanisms underlying its response to M. anisopliae.

Transcriptome-Wide Identification and Response Pattern Analysis of the Salix integra NAC Transcription Factor in Response to Pb Stress.

The NAC (NAM-ATAF1/2-CUC) transcription factor family is one of the largest plant-specific transcription factor families, playing an important role in plant growth and development and abiotic stress response. As a short-rotation woody plant, Salix integra (S. integra) has high lead (Pb) phytoremediation potential. To understand the role of NAC in S. integra Pb tolerance, 53 SiNAC transcripts were identified using third-generation and next-generation transcriptomic data from S. integra exposed to Pb stress, and a phylogenetic analysis revealed 11 subfamilies. A sequence alignment showed that multiple subfamilies represented by TIP and ATAF had a gene that produced more than one transcript under Pb stress, and different transcripts had different responses to Pb. By analyzing the expression profiles of SiNACs at 9 Pb stress time points, 41 of 53 SiNACs were found to be significantly responsive to Pb. Short time-series expression miner (STEM) analysis revealed that 41 SiNACs had two significant Pb positive response patterns (early and late), both containing 10 SiNACs. The SiNACs with the most significant Pb response were mainly from the ATAF and NAP subfamilies. Therefore, 4 and 3 SiNACs from the ATAF and NAP subfamilies, respectively, were selected as candidate Pb-responsive SiNACs for further structural and functional analysis. The RT-qPCR results of 7 transcripts also confirmed the different Pb response patterns of the ATAF and NAP subfamilies. SiNAC004 and SiNAC120, which were randomly selected from two subfamilies, were confirmed to be nuclear localization proteins by subcellular localization experiments. Functional prediction analysis of the associated transcripts of seven candidate SiNACs showed that the target pathways of ATAF subfamily SiNACs were "sulfur metabolism" and "glutathione metabolism", and the target pathways of NAP subfamily SiNACs were "ribosome" and "phenylpropanoid biosynthesis". This study not only identified two NAC subfamilies with different Pb response patterns but also identified Pb-responsive SiNACs that could provide a basis for subsequent gene function verification.

Identification and evaluation of a risk model predicting the prognosis of breast cancer based on characteristic signatures.

Breast cancer (BC) is one of the most common fatal cancers in women. Identifying new biomarkers is thus of great significance for the diagnosis and prognosis of BC. In this study, 1,030 BC cases from The Cancer Genome Atlas (TCGA) were obtained for differential expression analysis and Short Time-series Expression Miner (STEM) analysis to identify characteristic BC development genes, which were further divided into upregulated and downregulated genes. Two predictive prognosis models were both defined by Least Absolute Shrinkage and Selection Operator (LASSO). Survival analysis and receiver operating characteristic (ROC) curve analysis were used to determine the diagnostic and prognostic capabilities of the two gene set model scores, respectively. Our findings from this study suggested that both the unfavorable (BC1) and favorable (BC2) gene sets are reliable biomarkers for the diagnosis and prognosis of BC, although the BC1 model presents better diagnostic and prognostic value. Associations between the models and M2 macrophages and sensitivity to Bortezomib were also found, indicating that unfavorable BC genes are significantly involved in the tumor immune microenvironment. We successfully established one predictive prognosis model (BC1) based on characteristic gene sets of BC to diagnose and predict the survival time of BC patients using a cluster of 12 differentially expressed genes (DEGs).

Gene expression changes reveal the impact of the space environment on the skin of International Space Station astronauts.

The various types of ionizing radiation and altered gravity in the space environment present a risk to humans during space missions. Changes in the space environment lead to skin diseases, affecting the status of the aviators to fly. Therefore, it is important to explore the molecular-level changes in the skin during space missions. Bioinformatics analysis of gene arrays from hair follicle tissue of 10 astronauts was performed to explore changes in gene expression before, during and after space missions. First, STEM (Short Time-series Expression Miner) software was used to identify the expression patterns of hair follicle genes of astronauts pre-, in- and postflight. Gene Ontology Enrichment Analysis was then performed to explore the gene functions within the module. Protein-protein interaction network analysis was performed on skin-related genes. The transcriptional regulatory network within the module was constructed using the TRRUST database. The circadian rhythm-related genes within the module were screened using the MSigDB (Molecular Signatures Database). Based on differential expression analysis between the two groups, there were 327 differentially expressed genes after the astronauts entered space compared with preflight, and only 54 differentially expressed genes after returning to Earth. This outcome suggests that the expression of most genes can be recovered on return to the ground, but there are a small number of genes whose expression cannot be recovered in a short period of time. Based on time series analysis, 311 genes showed increased expression on entry into space and decreased expression on return to Earth. The genes of this expression pattern were associated with skin development, keratinocyte differentiation and cornification. Ten hub genes were identified as skin-related genes within the module, as well as nine transcription factors and three circadian genes. One hundred and seventy-nine genes decreased in expression after entry into space and increased on return to Earth. By reviewing the literature, we found that four of the genes, CSCD2, HP, CXCR1 and SSTR4, are associated with skin diseases. Through bioinformatics analysis, we found that the space environment affects skin keratinocyte differentiation, leading to skin barrier damage and inflammatory responses, and that this effect was decreased after return to Earth.

Molecular Characterization Related to Ovary Early Development Mechanisms after Eyestalk Ablation in Exopalaemon carinicauda.

Eyestalk ablation is an effective method to promote ovarian development in crustaceans. Herein, we performed transcriptome sequencing of ovary and hepatopancreas tissues after eyestalk ablation in Exopalaemon carinicauda to identify genes related to ovarian development. Our analyses led to the identification of 97,383 unigenes and 190,757 transcripts, with an average N50 length of 1757 bp. In the ovary, four pathways related to oogenesis and three related to oocyte rapid growth were enriched. In the hepatopancreas, two vitellogenesis-associated transcripts were identified. Furthermore, short time-series expression miner (STEM) and gene ontology (GO) enrichment analyses revealed five terms related to gamete generation. In addition, two-color fluorescent in situ hybridization results suggested that dmrt1 might play a vital role in oogenesis during the early stage of ovarian development. Overall, our insights should support future studies focusing on investigating oogenesis and ovarian development in E. carinicauda.

Transcriptome Profiling of Different Developmental Stages on Longissimus Dorsi to Identify Genes Underlying Intramuscular Fat Content in Wannanhua Pigs.

Intramuscular fat (IMF) is a key index to measure the tenderness and flavor of pork. Wannanhua pig, a famous indigenous pig breed in Anhui Province, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model for investigating the lipid position trait mechanisms in pigs. However, the regulatory mechanisms of lipid deposition and development in pigs remain unclear. Furthermore, the temporal differences in gene regulation are based on muscle growth and IMF deposition. The purpose of this study was to study the expression changes of longissimus dorsi (LD) at different growth stages of WH pigs at the molecular level, to screen the candidate genes and signaling pathways related to IMF during development by transcriptome sequencing technology, and to explore the transcriptional regulation mechanism of IMF deposition-related genes at different development stages. In total, 616, 485, and 1487 genes were differentially expressed between LD60 and LD120, LD120 and LD240, and LD60 and LD240, respectively. Numerous differentially expressed genes (DEGs) associated with lipid metabolism and muscle development were identified, and most of them were involved in IMF deposition and were significantly up-regulated in LD120 and LD240 compared to LD60. STEM (Short Time-series Expression Miner) analysis indicated significant variations in the mRNA expression across distinct muscle development stages. The differential expression of 12 selected DEGs was confirmed by RT-qPCR. The results of this study contribute to our understanding of the molecular mechanism of IMF deposition and provide a new way to accelerate the genetic improvement of pork quality.

Dynamic and systemic regulatory mechanisms in rainbow trout (Oncorhynchus mykiss) in response to acute hypoxia and reoxygenation stress

Hypoxia frequently occurs in natural aquatic systems and aquaculture environments due to extreme climate fluctuations, high-density farming, environmental pollution and global warming, resulting in serious ecological damage and enormous economic losses. Rainbow trout (Oncorhynchus mykiss), a key economic fish species worldwide, is extremely sensitive to hypoxia. However, the regulatory mechanisms in response to environmental hypoxia and reoxygenation stress remain unknown. Herein, rainbow trout liver transcriptomes and biochemical parameters were investigated in response to hypoxia for different durations (3, 12 and 24 h), reoxygenation (hypoxia for 24 h followed by reoxygenation for 3 h) and normoxia to highlight dynamic changes in molecular regulation and oxidative stress. In RNA-seq analysis, 5906 differentially expressed genes, two significantly expressed gene sets (profiles 10 and 12) and two hypoxia specific modules (MEgreen and MEturquoise) were screened by differential expression analysis, short time-series expression miner (STEM) and weighted gene co-expression network analysis (WGCNA), respectively. The intersection of the above analyses further identified several key hub genes related to hypoxia, including hif-1α, epo, igfbp1, ddit4, pck1, g6pc, cyp1a1 and dusp1. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed different metabolic strategies at different stress stages; signal transmission and protein synthesis process were strongly influenced by hypoxia. The immune system was inhibited, and a switch from programmed to pathological cell death was observed from hypoxia for 12 h to 24 h. After reoxygenation for 3 h, mitochondrial oxidative phosphorylation was strongly activated to provide more cellular ATP. Enzymatic and non-enzymatic antioxidant systems clearly coordinate to alleviate oxidative stress injury caused by hypoxia. This study reveals dynamic and systemic regulatory mechanisms in rainbow trout liver, and lays a foundation for further study on the molecular mechanisms governing responses to environmental hypoxia and reoxygenation stress.

Analysis of transcriptome expression profiling data in oral leukoplakia and early and late‑stage oral squamous cell carcinoma.

The present study screened, potential prognostic biomarkers for oral carcinogenesis. The GSE85195 dataset, which consisted of oral leukoplakia (OL) and early and late-stage oral squamous cell carcinoma (OSCC) samples, was used. The differentially expressed genes (DEGs) in early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups were screened using the limma package in R. The Short Time-series Expression Miner software package was used to cluster DEGs with similar expression patterns in the course of disease progression (from OL to early and then late-stage OSCC). Moreover, the Database for Annotation, Visualization and Integrated Discovery online analysis tool was used to perform Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction (PPI) network was also constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Reverse transcription-quantitative PCR was performed to assess the mRNA expression levels of hub node genes in clinical samples, and receiver operating characteristic curve analysis was performed to assess the prognostic value of the hub genes. A total of 4,595, 6,042 and 2,738 DEGs were screened in the early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups, respectively. A total of 665 overlapping genes were identified when the screened DEGs were compared. Cluster 1 and cluster 7 were identified as the significant clusters, which contained 496 and 341 DEGs, respectively. A PPI network was constructed with 440 interaction pairs. There were five differentially expressed hub nodes identified in different stages from OL to OSCC. The results of the present study indicated that fibronectin 1, signal transducer and activator of transcription 1, collagen type II α1 chain, collagen type X α1 chain and collagen type IV α6 chain might serve as independent diagnostic factors for OL and OSCC, and as prognostic biomarkers for OL carcinogenesis.

Transcriptome sequencing leads to an improved understanding of the infection mechanism of Alternaria solani in potato

BackgroundAlternaria solani (A. solani), the main pathogen of potato early blight, causes serious yield reductions every year. The application of fungicides is the most common and effective method of controlling Alternaria-caused diseases. The differentially expressed transcripts of A. solani infecting potato were identified, revealing a group of valuable candidate genes for a systematic analysis to increase the understanding of the molecular pathogenesis of A. solani, and providing scientific data for formulating additional measures to prevent and control potato early blight. In this study, a deep RNA-sequencing approach was applied to gain insights into A. solani pathogenesis. At 3, 4, and 5 days post inoculation (dpi), RNA samples from the susceptible potato cultivar Favorita infected with A. solani strain HWC-168, were sequenced and utilized for transcriptome analysis, and compared to the transcriptome obtained 0 dpi.ResultsA total of 4430 (2167 upregulated, 2263 downregulated), 4736 (2312 upregulated, 2424 downregulated), and 5043 (2411 upregulated, 2632 downregulated) genes were differentially expressed 3, 4 and 5 dpi, respectively, compared with genes analysed at 0 dpi. KEGG enrichment analysis showed that genes involved in the pathways of amino acid metabolism, glucose metabolism, and enzyme activity were significantly differentially expressed at the late infection stage. Correspondingly, symptoms developed rapidly during the late stage of A. solani infection. In addition, a short time-series expression miner (STEM) assay was performed to analyse the gene expression patterns of A. solani and Profile 17 and 19 showed significant change trends 3, 4 and 5 dpi. Both profiles, but especially Profile 17, included enzymes, including transferases, oxidoreductases, hydrolases and carbohydrate-active enzymes (CAZYmes), which may play important roles in late fungal infection. Furthermore, possible candidate effectors were identified through the adopted pipelines, with 137 differentially expressed small secreted proteins identified, including some enzymes and proteins with unknown functions.ConclusionsCollectively, the data presented in this study show that amino acid metabolism, and glucose metabolism pathways, and specific pathway-related enzymes may be key putative pathogenic factors, and play important roles in late stage A. solani infection. These results contribute to a broader base of knowledge of A. solani pathogenesis in potato, as indicated by the transcriptional level analysis, and provide clues for determining the effectors of A. solani infection.

Time-Series Expression Profile Analysis of Post-Traumatic Joint Contracture in Rats at the Early Stages of the Healing Process.

This study aimed to characterize the gene expression profile at the early stages of the healing process of post-traumatic joint contracture (PTJC). Twelve rats were used for PTJC model establishment and were divided into four groups according to the sampling time: S0d, S3d, S7d and S2w. Transcriptome sequencing was performed on fibrotic joint capsule samples in four groups followed by bioinformatics analyses including differentially expressed genes (DEGs) screening, Short Time-series Expression Miner (STEM) analysis, network construction, and pathway analysis. Five important genes were validated by qRT-PCR. A total of 1171, 1052 and 793 DEGs were screened in S3d vs S0d, S7d vs S0d, and S2w vs S0d comparison groups, respectively. A total of 383 overlapping genes were screened out, which were significantly enriched in some inflammatory functions and pathways. Through STEM analysis, three clusters were identified, including 105, 57 and 57 DEGs, respectively. Then, based on the cluster genes, 10 genes, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3, were further selected after PPI and pathway analyses. The expression levels of Il6, Timp1, Cxcl1, Cxcr4 and Mmp3 were validated by qRT-PCR. The present study screened out several genes with significant changes in expression levels at the early stages of the healing process in PTJC, such as Il6, Timp1, Cxcl1, Cxcr4 and Mmp3. Our study offers a valuable contribution to the understanding pathomechanism of PTJC.

A passage-dependent network for estimating the in vitro senescence of mesenchymal stromal/stem cells using microarray, bulk and single cell RNA sequencing.

Long-term in vitro culture of human mesenchymal stem cells (MSCs) leads to cell lifespan shortening and growth stagnation due to cell senescence. Here, using sequencing data generated in the public domain, we have established a specific regulatory network of "transcription factor (TF)-microRNA (miRNA)-Target" to provide key molecules for evaluating the passage-dependent replicative senescence of mesenchymal stem cells for the quality control and status evaluation of mesenchymal stem cells prepared by different procedures. Short time-series expression miner (STEM) analysis was performed on the RNA-seq and miRNA-seq databases of mesenchymal stem cells from various passages to reveal the dynamic passage-related changes of miRNAs and mRNAs. Potential miRNA targets were predicted using seven miRNA target prediction databases, including TargetScan, miRTarBase, miRDB, miRWalk, RNA22, RNAinter, and TargetMiner. Then use the TransmiR v2.0 database to obtain experimental-supported transcription factor for regulating the selected miRNA. More than ten sequencing data related to mesenchymal stem cells or mesenchymal stem cells reprogramming were used to validate key miRNAs and mRNAs. And gene set variation analysis (GSVA) was performed to calculate the passage-dependent signature. The results showed that during the passage of mesenchymal stem cells, a total of 29 miRNAs were gradually downregulated and 210 mRNA were gradually upregulated. Enrichment analysis showed that the 29 miRNAs acted as multipotent regulatory factors of stem cells and participated in a variety of signaling pathways, including TGF-beta, HIPPO and oxygen related pathways. 210 mRNAs were involved in cell senescence. According to the target prediction results, the targets of these key miRNAs and mRNAs intersect to form a regulatory network of "TF-miRNA-Target" related to replicative senescence of cultured mesenchymal stem cells, across 35 transcription factor, 7 miRNAs (has-mir-454-3p, has-mir-196b-5p, has-mir-130b-5p, has-mir-1271-5p, has-let-7i-5p, has-let-7a-5p, and has-let-7b-5p) and 7 predicted targets (PRUNE2, DIO2, CPA4, PRKAA2, DMD, DDAH1, and GATA6). This network was further validated by analyzing datasets from a variety of mesenchymal stem cells subculture and lineage reprogramming studies, as well as qPCR analysis of early passages mesenchymal stem cells versus mesenchymal stem cells with senescence morphologies (SA-β-Gal+). The "TF-miRNA-Target" regulatory network constructed in this study reveals the functional mechanism of miRNAs in promoting the senescence of MSCs during in vitro expansion and provides indicators for monitoring the quality of functional mesenchymal stem cells during the preparation and clinical application.