Displaying publications 21 - 40 of 384 in total

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  1. Zhang X, Liew KJ, Cao L, Wang J, Chang Z, Tan MCY, et al.
    J Med Microbiol, 2024 Jul;73(7).
    PMID: 38967406 DOI: 10.1099/jmm.0.001841
    Introduction. Cold plasma is frequently utilized for the purpose of eliminating microbial contaminants. Under optimal conditions, it can function as plasma medicine for treating various diseases, including infections caused by Candida albicans, an opportunistic pathogen that can overgrow in individuals with weakened immune system.Gap Statement. To date, there has been less molecular study on cold plasma-treated C. albicans.Research Aim. The study aims to fill the gap in understanding the molecular response of C. albicans to cold plasma treatment.Methodology. This project involved testing a cold plasma generator to determine its antimicrobial effectiveness on C. albicans' planktonic cells. Additionally, the cells' transcriptomics responses were investigated using RNA sequencing at various treatment durations (1, 3 and 5 min).Results. The results show that our cold plasma effectively eliminates C. albicans. Cold plasma treatment resulted in substantial downregulation of important pathways, such as 'nucleotide metabolism', 'DNA replication and repair', 'cell growth', 'carbohydrate metabolism' and 'amino acid metabolism'. This was an indication of cell cycle arrest of C. albicans to preserve energy consumption under unfavourable conditions. Nevertheless, C. albicans adapted its GSH antioxidant system to cope with the oxidative stress induced by reactive oxygen species, reactive nitrogen species and other free radicals. The treatment likely led to a decrease in cell pathogenicity as many virulence factors were downregulated.Conclusion. The study demonstrated the major affected pathways in cold plasma-treated C. albicans, providing valuable insights into the molecular response of C. albicans to cold plasma treatment. The findings contribute to the understanding of the antimicrobial efficiency of cold plasma and its potential applications in the field of microbiology.
    Matched MeSH terms: Gene Expression Profiling*
  2. Govender N, Senan S, Sage EE, Mohamed-Hussein ZA, Mackeen MM, Wickneswari R
    PLoS One, 2018;13(9):e0203441.
    PMID: 30240391 DOI: 10.1371/journal.pone.0203441
    Jatropha curcas is an oil-rich seed crop with huge potentials for bioenergy production. The inflorescence carries a number of processes that are likely to affect the overall yield potentials; floral development, male-to-female flower ratio, floral abscission and fruit set. In this study, a weighted gene co-expression network analysis which integrates the transcriptome, physical and simple sugar data of J. curcas inflorescence was performed and nine modules were identified by means of hierarchical clustering. Among them, four modules (green4, antiquewhite2, brown2 and lightskyblue4) showed significant correlation to yield factors at p≤0.01. The four modules are categorized into two clusters; cluster 1 of green4 and antiquewhite2 modules correspond to number of flowers/inflorescence, total seed weight/plant, number of seeds/plant, and number of fruits/plant, whereas cluster 2 of brown2 and lightskyblue4 modules correspond to glucose and fructose. Descriptive characterizations of cluster 1 show putative involvement in gibberellin signaling and responses, whereas cluster 2 may have been involved in sugar signaling, signal transductions and regulation of flowerings. Our findings present a list of hub genes for J. curcas yield improvement and reproductive biology enhancement strategies.
    Matched MeSH terms: Gene Expression Profiling*
  3. Das S, Kumar S
    J Med Virol, 2023 Sep;95(9):e29077.
    PMID: 37675861 DOI: 10.1002/jmv.29077
    Long coronavirus disease (COVID) has emerged as a global health issue, affecting a substantial number of people worldwide. However, the underlying mechanisms that contribute to the persistence of symptoms in long COVID remain obscure, impeding the development of effective diagnostic and therapeutic interventions. In this study, we utilized computational methods to examine the gene expression profiles of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and their associations with the wide range of symptoms observed in long COVID patients. Using a comprehensive data set comprising over 255 symptoms affecting multiple organ systems, we identified differentially expressed genes and investigated their functional similarity, leading to the identification of key genes with the potential to serve as biomarkers for long COVID. We identified the participation of hub genes associated with G-protein-coupled receptors (GPCRs), which are essential regulators of T-cell immunity and viral infection responses. Among the identified common genes were CTLA4, PTPN22, KIT, KRAS, NF1, RET, and CTNNB1, which play a crucial role in modulating T-cell immunity via GPCR and contribute to a variety of symptoms, including autoimmunity, cardiovascular disorders, dermatological manifestations, gastrointestinal complications, pulmonary impairments, reproductive and genitourinary dysfunctions, and endocrine abnormalities. GPCRs and associated genes are pivotal in immune regulation and cellular functions, and their dysregulation may contribute to the persistent immune responses, chronic inflammation, and tissue abnormalities observed in long COVID. Targeting GPCRs and their associated pathways could offer promising therapeutic strategies to manage symptoms and improve outcomes for those experiencing long COVID. However, the complex mechanisms underlying the condition require continued study to develop effective treatments. Our study has significant implications for understanding the molecular mechanisms underlying long COVID and for identifying potential therapeutic targets. In addition, we have developed a comprehensive website (https://longcovid.omicstutorials.com/) that provides a curated list of biomarker-identified genes and treatment recommendations for each specific disease, thereby facilitating informed clinical decision-making and improved patient management. Our study contributes to the understanding of this debilitating disease, paving the way for improved diagnostic precision, and individualized therapeutic interventions.
    Matched MeSH terms: Gene Expression Profiling*
  4. Chia WK, Yeoh HXY, Mustangin M, Khong TY, Wong YP, Tan GC
    Malays J Pathol, 2023 Dec;45(3):353-362.
    PMID: 38155377
    INTRODUCTION: Hydatidiform mole is one of the gestational trophoblastic disease and comprises complete (CM) and partial moles (PM), which carries a risk of developing persistence disease, invasive mole or choriocarcinoma. MicroRNAs (miRNAs) have been discovered in various tissues, including neoplastic tissues. Its role in the pathogenesis of molar pregnancy or as biomarkers are still largely uncertain. The aim of this study is to identify the differentially expressed miRNAs in CM and PM.

    MATERIALS AND METHODS: Using next-generation sequencing, the miRNAs profiles of CM (n=3) and PM (n=3) moles, including placenta of non-molar abortus (n=3) as control were determined. The differentially expressed miRNAs between each group were analysed. Subsequently, bioinformatics analysis using miRDB and Targetscan was utilised to predict target genes.

    RESULTS: We found 10 differentially expressed miRNAs in CMs and PMs, compared to NMAs, namely miR- 518a-5p, miR-423-3p, miR-503-5p, miR-302a-3p, and miR-1323. The other 5 miRNAs were novel, not listed in the known database. The 3 differentially expressed miRNAs in CMs were predicted to commonly target ZTBT46 and FAM73B mRNAs.

    DISCUSSION: miR-518 was consistently observed to be downregulated in CM versus PM, and CM versus NMA. Further bioinformatic analysis to provide insight into the possible role of these miRNAs in the pathogenesis of HMs, progression of disease and as potential diagnostic biomarkers as well as therapeutic targets for HMs is needed.

    Matched MeSH terms: Gene Expression Profiling
  5. Sahebi M, Hanafi MM, Azizi P, Hakim A, Ashkani S, Abiri R
    Mol Biotechnol, 2015 Oct;57(10):880-903.
    PMID: 26271955 DOI: 10.1007/s12033-015-9884-z
    Suppression subtractive hybridization (SSH) is an effective method to identify different genes with different expression levels involved in a variety of biological processes. This method has often been used to study molecular mechanisms of plants in complex relationships with different pathogens and a variety of biotic stresses. Compared to other techniques used in gene expression profiling, SSH needs relatively smaller amounts of the initial materials, with lower costs, and fewer false positives present within the results. Extraction of total RNA from plant species rich in phenolic compounds, carbohydrates, and polysaccharides that easily bind to nucleic acids through cellular mechanisms is difficult and needs to be considered. Remarkable advancement has been achieved in the next-generation sequencing (NGS) field. As a result of progress within fields related to molecular chemistry and biology as well as specialized engineering, parallelization in the sequencing reaction has exceptionally enhanced the overall read number of generated sequences per run. Currently available sequencing platforms support an earlier unparalleled view directly into complex mixes associated with RNA in addition to DNA samples. NGS technology has demonstrated the ability to sequence DNA with remarkable swiftness, therefore allowing previously unthinkable scientific accomplishments along with novel biological purposes. However, the massive amounts of data generated by NGS impose a substantial challenge with regard to data safe-keeping and analysis. This review examines some simple but vital points involved in preparing the initial material for SSH and introduces this method as well as its associated applications to detect different novel genes from different plant species. This review evaluates general concepts, basic applications, plus the probable results of NGS technology in genomics, with unique mention of feasible potential tools as well as bioinformatics.
    Matched MeSH terms: Gene Expression Profiling/economics; Gene Expression Profiling/methods
  6. Wong MY, Govender NT, Ong CS
    BMC Res Notes, 2019 Sep 24;12(1):631.
    PMID: 31551084 DOI: 10.1186/s13104-019-4652-y
    OBJECTIVE: Basal stem rot disease causes severe economic losses to oil palm production in South-east Asia and little is known on the pathogenicity of the pathogen, the basidiomyceteous Ganoderma boninense. Our data presented here aims to identify both the house-keeping and pathogenicity genes of G. boninense using Illumina sequencing reads.

    DESCRIPTION: The hemibiotroph G. boninense establishes via root contact during early stage of colonization and subsequently kills the host tissue as the disease progresses. Information on the pathogenicity factors/genes that causes BSR remain poorly understood. In addition, the molecular expressions corresponding to G. boninense growth and pathogenicity are not reported. Here, six transcriptome datasets of G. boninense from two contrasting conditions (three biological replicates per condition) are presented. The first datasets, collected from a 7-day-old axenic condition provide an insight onto genes responsible for sustenance, growth and development of G. boninense while datasets of the infecting G. boninense collected from oil palm-G. boninense pathosystem (in planta condition) at 1 month post-inoculation offer a comprehensive avenue to understand G. boninense pathogenesis and infection especially in regard to molecular mechanisms and pathways. Raw sequences deposited in Sequence Read Archive (SRA) are available at NCBI SRA portal with PRJNA514399, bioproject ID.

    Matched MeSH terms: Gene Expression Profiling/methods*; Gene Expression Profiling/statistics & numerical data
  7. Bhalla R, Narasimhan K, Swarup S
    Plant Cell Rep, 2005 Dec;24(10):562-71.
    PMID: 16220342
    A natural shift is taking place in the approaches being adopted by plant scientists in response to the accessibility of systems-based technology platforms. Metabolomics is one such field, which involves a comprehensive non-biased analysis of metabolites in a given cell at a specific time. This review briefly introduces the emerging field and a range of analytical techniques that are most useful in metabolomics when combined with computational approaches in data analyses. Using cases from Arabidopsis and other selected plant systems, this review highlights how information can be integrated from metabolomics and other functional genomics platforms to obtain a global picture of plant cellular responses. We discuss how metabolomics is enabling large-scale and parallel interrogation of cell states under different stages of development and defined environmental conditions to uncover novel interactions among various pathways. Finally, we discuss selected applications of metabolomics.
    Matched MeSH terms: Gene Expression Profiling/methods; Gene Expression Profiling/trends*
  8. Selvarajah GT, Bonestroo FAS, Timmermans Sprang EPM, Kirpensteijn J, Mol JA
    BMC Vet Res, 2017 Nov 25;13(1):354.
    PMID: 29178874 DOI: 10.1186/s12917-017-1281-3
    BACKGROUND: Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental conditions. No studies have validated specific reference genes in canine osteosarcoma (OS). Previous gene expression studies involving canine OS have used one or two reference genes to normalize gene expression. This study aimed to validate a panel of reference genes commonly used for normalization of canine OS gene expression data using the geNorm algorithm. qPCR analysis of nine canine reference genes was performed on 40 snap-frozen primary OS tumors and seven cell lines.

    RESULTS: Tumors with a variety of clinical and pathological characteristics were selected. Gene expression stability and the optimal number of reference genes for gene expression normalization were calculated. RPS5 and HNRNPH were highly stable among OS cell lines, while RPS5 and RPS19 were the best combination for primary tumors. Pairwise variation analysis recommended four and two reference genes for optimal normalization of the expression data of canine OS tumors and cell lines, respectively.

    CONCLUSIONS: Appropriate combinations of reference genes are recommended to normalize mRNA levels in canine OS tumors and cell lines to facilitate standardized and reliable quantification of target gene expression, which is essential for investigating key genes involved in canine OS metastasis and for comparative biomarker discovery.

    Matched MeSH terms: Gene Expression Profiling/methods; Gene Expression Profiling/veterinary*
  9. Zhang Y, Wu Q, Fang S, Li S, Zheng H, Zhang Y, et al.
    BMC Genomics, 2020 Aug 14;21(1):559.
    PMID: 32795331 DOI: 10.1186/s12864-020-06965-5
    BACKGROUND: Mud crab, Scylla paramamosain, a euryhaline crustacean species, mainly inhabits the Indo-Western Pacific region. Wild mud crab spawn in high-salt condition and the salinity reduced with the growth of the hatching larvae. When the larvae grow up to megalopa, they migrate back to estuaries and coasts in virtue of the flood tide, settle and recruit adult habitats and metamorphose into the crablet stage. Adult crab can even survive in a wide salinity of 0-35 ppt. To investigate the mRNA profile after salinity stress, S. paramamosain megalopa were exposed to different salinity seawater (low, 14 ppt; control, 25 ppt; high, 39 ppt).

    RESULTS: Firstly, from the expression profiles of Na+/K+/2Cl- cotransporter, chloride channel protein 2, and ABC transporter, it turned out that the 24 h might be the most influenced duration in the short-term stress. We collected megalopa under different salinity for 24 h and then submitted to mRNA profiling. Totally, 57.87 Gb Clean Data were obtained. The comparative genomic analysis detected 342 differentially expressed genes (DEGs). The most significantly DEGs include gamma-butyrobetaine dioxygenase-like, facilitated trehalose transporter Tret1, sodium/potassium-transporting ATPase subunit alpha, rhodanese 1-like protein, etc. And the significantly enriched pathways were lysine degradation, choline metabolism in cancer, phospholipase D signaling pathway, Fc gamma R-mediated phagocytosis, and sphingolipid signaling pathway. The results indicate that in the short-term salinity stress, the megalopa might regulate some mechanism such as metabolism, immunity responses, osmoregulation to adapt to the alteration of the environment.

    CONCLUSIONS: This study represents the first genome-wide transcriptome analysis of S. paramamosain megalopa for studying its stress adaption mechanisms under different salinity. The results reveal numbers of genes modified by salinity stress and some important pathways, which will provide valuable resources for discovering the molecular basis of salinity stress adaptation of S. paramamosain larvae and further boost the understanding of the potential molecular mechanisms of salinity stress adaptation for crustacean species.

    Matched MeSH terms: Gene Expression Profiling
  10. Lee XW, Mat-Isa MN, Mohd-Elias NA, Aizat-Juhari MA, Goh HH, Dear PH, et al.
    PLoS One, 2016;11(12):e0167958.
    PMID: 27977777 DOI: 10.1371/journal.pone.0167958
    Rafflesia is a biologically enigmatic species that is very rare in occurrence and possesses an extraordinary morphology. This parasitic plant produces a gigantic flower up to one metre in diameter with no leaves, stem or roots. However, little is known about the floral biology of this species especially at the molecular level. In an effort to address this issue, we have generated and characterised the transcriptome of the Rafflesia cantleyi flower, and performed a comparison with the transcriptome of its floral bud to predict genes that are expressed and regulated during flower development. Approximately 40 million sequencing reads were generated and assembled de novo into 18,053 transcripts with an average length of 641 bp. Of these, more than 79% of the transcripts had significant matches to annotated sequences in the public protein database. A total of 11,756 and 7,891 transcripts were assigned to Gene Ontology categories and clusters of orthologous groups respectively. In addition, 6,019 transcripts could be mapped to 129 pathways in Kyoto Encyclopaedia of Genes and Genomes Pathway database. Digital abundance analysis identified 52 transcripts with very high expression in the flower transcriptome of R. cantleyi. Subsequently, analysis of differential expression between developing flower and the floral bud revealed a set of 105 transcripts with potential role in flower development. Our work presents a deep transcriptome resource analysis for the developing flower of R. cantleyi. Genes potentially involved in the growth and development of the R. cantleyi flower were identified and provide insights into biological processes that occur during flower development.
    Matched MeSH terms: Gene Expression Profiling
  11. Han Z, Sun J, Lv A, Xian JA, Sung YY, Sun X, et al.
    Fish Shellfish Immunol, 2018 Sep;80:291-301.
    PMID: 29886138 DOI: 10.1016/j.fsi.2018.06.007
    To better understand gene expression in the intestine after Shewanella algae infection and provide insights into its immune roles in the tongue sole, Cynoglossus semilaevis, sequencing-based high-throughput RNA analysis (RNA-Seq) for the intestines between the control group and 12 h post-injection group was performed. After assembly, there was an average of 23,957,159 raw sequencing reads, and 23,943,491 clean reads were obtained after filtering out low-quality reads. Then, 383 differentially expressed genes (DEGs) in the intestines in response to S. algae infection were identified. Subsequently, gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the DEGs were conducted to further explore their functions. Among all of the pathways involved, sixteen pathways were related to the immune system, among which the complement and coagulation cascades pathway was the most prominent for immunity-related DEGs, followed by the leukocyte transendothelial migration pathway. Furthermore, the expression levels of twelve selected DEGs in the immune-related pathways were identified by quantitative real-time polymerase chain reaction, substantiating the reliability and reproducibility of the RNA-Seq results. In summary, this study represents an important genomic resource for understanding the potential immune role of the tongue sole intestine from the perspective of gene expression.
    Matched MeSH terms: Gene Expression Profiling
  12. Suppiah, J., Sakinah, S., Chan, S.Y., Wong, Y.P., Subbiah, S.K., Chee, H.Y., et al.
    MyJurnal
    Human platelets are anucleate cells that lack in deoxyribonucleic acid (DNA), thus hampering genomic study on them. However, the presence of their own messenger ribonucleic acid (mRNA) transcript allows functional study via the transcriptome approach. Transcriptome not only allows profiling of platelet but also aids in studying gene regulation in virus infections and other diseases that have an impact on platelets. Some viruses are known to affect the platelet either by causing a reduction or destruction. Dengue virus is one of the most postulated virus having such effect and frequently linked to platelet reduction. The transcriptome approach has a pivotal role in providing a deeper insight to link certain diseases and their effect on platelets. This review critically discusses role of platelet in dengue and other viral diseases of public health relevance, with a specific focus on the methods currently used in platelet transcriptome profiling.
    Matched MeSH terms: Gene Expression Profiling
  13. Chong PP, Chin VK, Wong WF, Madhavan P, Yong VC, Looi CY
    Genes (Basel), 2018 Nov 07;9(11).
    PMID: 30405082 DOI: 10.3390/genes9110540
    Candida albicans is an opportunistic fungal pathogen, which causes a plethora of superficial, as well as invasive, infections in humans. The ability of this fungus in switching from commensalism to active infection is attributed to its many virulence traits. Biofilm formation is a key process, which allows the fungus to adhere to and proliferate on medically implanted devices as well as host tissue and cause serious life-threatening infections. Biofilms are complex communities of filamentous and yeast cells surrounded by an extracellular matrix that confers an enhanced degree of resistance to antifungal drugs. Moreover, the extensive plasticity of the C. albicans genome has given this versatile fungus the added advantage of microevolution and adaptation to thrive within the unique environmental niches within the host. To combat these challenges in dealing with C. albicans infections, it is imperative that we target specifically the molecular pathways involved in biofilm formation as well as drug resistance. With the advent of the -omics era and whole genome sequencing platforms, novel pathways and genes involved in the pathogenesis of the fungus have been unraveled. Researchers have used a myriad of strategies including transcriptome analysis for C. albicans cells grown in different environments, whole genome sequencing of different strains, functional genomics approaches to identify critical regulatory genes, as well as comparative genomics analysis between C. albicans and its closely related, much less virulent relative, C. dubliniensis, in the quest to increase our understanding of the mechanisms underlying the success of C. albicans as a major fungal pathogen. This review attempts to summarize the most recent advancements in the field of biofilm and antifungal resistance research and offers suggestions for future directions in therapeutics development.
    Matched MeSH terms: Gene Expression Profiling
  14. Pinheiro TDM, Rego ECS, Alves GSC, Fonseca FCA, Cotta MG, Antonino JD, et al.
    Int J Mol Sci, 2022 Nov 05;23(21).
    PMID: 36362377 DOI: 10.3390/ijms232113589
    Banana (Musa spp.), which is one of the world's most popular and most traded fruits, is highly susceptible to pests and diseases. Pseudocercospora musae, responsible for Sigatoka leaf spot disease, is a principal fungal pathogen of Musa spp., resulting in serious economic damage to cultivars in the Cavendish subgroup. The aim of this study was to characterize genetic components of the early immune response to P. musae in Musa acuminata subsp. burmannicoides, var. Calcutta 4, a resistant wild diploid. Leaf RNA samples were extracted from Calcutta 4 three days after inoculation with fungal conidiospores, with paired-end sequencing conducted in inoculated and non-inoculated controls using lllumina HiSeq 4000 technology. Following mapping to the reference M. acuminata ssp. malaccensis var. Pahang genome, differentially expressed genes (DEGs) were identified and expression representation analyzed on the basis of gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes orthology and MapMan pathway analysis. Sequence data mapped to 29,757 gene transcript models in the reference Musa genome. A total of 1073 DEGs were identified in pathogen-inoculated cDNA libraries, in comparison to non-inoculated controls, with 32% overexpressed. GO enrichment analysis revealed common assignment to terms that included chitin binding, chitinase activity, pattern binding, oxidoreductase activity and transcription factor (TF) activity. Allocation to KEGG pathways revealed DEGs associated with environmental information processing, signaling, biosynthesis of secondary metabolites, and metabolism of terpenoids and polyketides. With 144 up-regulated DEGs potentially involved in biotic stress response pathways, including genes involved in cell wall reinforcement, PTI responses, TF regulation, phytohormone signaling and secondary metabolism, data demonstrated diverse early-stage defense responses to P. musae. With increased understanding of the defense responses occurring during the incompatible interaction in resistant Calcutta 4, these data are appropriate for the development of effective disease management approaches based on genetic improvement through introgression of candidate genes in superior cultivars.
    Matched MeSH terms: Gene Expression Profiling
  15. Mazlan O, Abdul-Rahman A, Goh HH, Aizat WM, Mohd Noor N
    Data Brief, 2018 Feb;16:90-93.
    PMID: 29188226 DOI: 10.1016/j.dib.2017.11.001
    Mangosteen (Garcinia mangostana L.) has exceptional potential for commercial and pharmaceutical applications due to its delicious fruit and medicinal properties. Nevertheless, the molecular mechanism of mangosteen seed development is poorly understood. In this study, we performed transcriptomic analysis of four seed developmental stages; eight, ten, twelve and fourteen weeks after anthesis. Illumina HiSeq™ 4000 sequencer was used to generate raw data of approximately 68 Gb in size. From 451,495,326 raw reads, 406,143,756 clean reads were obtained. The raw data were uploaded to SRA database and the BioProject ID is PRJNA395504. These data provide the basis for further exploration and understanding of the molecular mechanism in mangosteen seed development.
    Matched MeSH terms: Gene Expression Profiling
  16. Huang CJ, Choo KB
    Int J Mol Sci, 2023 Feb 25;24(5).
    PMID: 36901978 DOI: 10.3390/ijms24054549
    Adipogenesis is an indispensable cellular process that involves preadipocyte differentiation into mature adipocyte. Dysregulated adipogenesis contributes to obesity, diabetes, vascular conditions and cancer-associated cachexia. This review aims to elucidate the mechanistic details on how circular RNA (circRNA) and microRNA (miRNA) modulate post-transcriptional expression of targeted mRNA and the impacted downstream signaling and biochemical pathways in adipogenesis. Twelve adipocyte circRNA profiling and comparative datasets from seven species are analyzed using bioinformatics tools and interrogations of public circRNA databases. Twenty-three circRNAs are identified in the literature that are common to two or more of the adipose tissue datasets in different species; these are novel circRNAs that have not been reported in the literature in relation to adipogenesis. Four complete circRNA-miRNA-mediated modulatory pathways are constructed via integration of experimentally validated circRNA-miRNA-mRNA interactions and the downstream signaling and biochemical pathways involved in preadipocyte differentiation via the PPARγ/C/EBPα gateway. Despite the diverse mode of modulation, bioinformatics analysis shows that the circRNA-miRNA-mRNA interacting seed sequences are conserved across species, supporting mandatory regulatory functions in adipogenesis. Understanding the diverse modes of post-transcriptional regulation of adipogenesis may contribute to the development of novel diagnostic and therapeutic strategies for adipogenesis-associated diseases and in improving meat quality in the livestock industries.
    Matched MeSH terms: Gene Expression Profiling
  17. Huang Z, Wang J, Lu X, Mohd Zain A, Yu G
    Brief Bioinform, 2023 Mar 19;24(2).
    PMID: 36733262 DOI: 10.1093/bib/bbad040
    Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
    Matched MeSH terms: Gene Expression Profiling
  18. Awuah WA, Roy S, Tan JK, Adebusoye FT, Qiang Z, Ferreira T, et al.
    J Cell Mol Med, 2024 Apr;28(7):e18159.
    PMID: 38494861 DOI: 10.1111/jcmm.18159
    Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.
    Matched MeSH terms: Gene Expression Profiling
  19. Hameed SS, Hassan R, Hassan WH, Muhammadsharif FF, Latiff LA
    PLoS One, 2021;16(1):e0246039.
    PMID: 33507983 DOI: 10.1371/journal.pone.0246039
    The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.
    Matched MeSH terms: Gene Expression Profiling
  20. Sahabudin E, Kubo S, Yuzir MAM, Othman N, Nadia Md Akhir F, Suzuki K, et al.
    Bioengineered, 2024 Dec;15(1):2314888.
    PMID: 38375815 DOI: 10.1080/21655979.2024.2314888
    Cadmium (Cd) has become a severe issue in relatively low concentration and attracts expert attention due to its toxicity, accumulation, and biomagnification in living organisms. Cd does not have a biological role and causes serious health issues. Therefore, Cd pollutants should be reduced and removed from the environment. Microalgae have great potential for Cd absorption for waste treatment since they are more environmentally friendly than existing treatment methods and have strong metal sorption selectivity. This study evaluated the tolerance and ability of the microalga Tetratostichococcus sp. P1 to remove Cd ions under acidic conditions and reveal mechanisms based on transcriptomics analysis. The results showed that Tetratostichococcus sp. P1 had a high Cd tolerance that survived under the presence of Cd up to 100 µM, and IC50, the half-maximal inhibitory concentration value, was 57.0 μM, calculated from the change in growth rate based on the chlorophyll content. Long-term Cd exposure affected the algal morphology and photosynthetic pigments of the alga. Tetratostichococcus sp. P1 removed Cd with a maximum uptake of 1.55 mg g-1 dry weight. Transcriptomic analysis revealed the upregulation of the expression of genes related to metal binding, such as metallothionein. Group A, Group B transporters and glutathione, were also found upregulated. While the downregulation of the genes were related to photosynthesis, mitochondria electron transport, ABC-2 transporter, polysaccharide metabolic process, and cell division. This research is the first study on heavy metal bioremediation using Tetratostichococcus sp. P1 and provides a new potential microalga strain for heavy metal removal in wastewater.[Figure: see text]Abbreviations:BP: Biological process; bZIP: Basic Leucine Zipper; CC: Cellular component; ccc1: Ca (II)-sensitive cross complementary 1; Cd: Cadmium; CDF: Cation diffusion facilitator; Chl: Chlorophyll; CTR: Cu TRansporter families; DAGs: Directed acyclic graphs; DEGs: Differentially expressed genes; DVR: Divinyl chlorophyllide, an 8-vinyl-reductase; FPN: FerroportinN; FTIR: Fourier transform infrared; FTR: Fe TRansporter; GO: Gene Ontology; IC50: Growth half maximal inhibitory concentration; ICP: Inductively coupled plasma; MF: molecular function; NRAMPs: Natural resistance-associated aacrophage proteins; OD: Optical density; RPKM: Reads Per Kilobase of Exon Per Million Reads Mapped; VIT1: Vacuolar iron transporter 1 families; ZIPs: Zrt-, Irt-like proteins.
    Matched MeSH terms: Gene Expression Profiling
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