Displaying publications 1 - 20 of 366 in total

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  1. Toh C, Mohd-Hairul AR, Ain NM, Namasivayam P, Go R, Abdullah NAP, et al.
    BMC Res Notes, 2017 Nov 02;10(1):554.
    PMID: 29096695 DOI: 10.1186/s13104-017-2872-6
    BACKGROUND: Vanda Mimi Palmer (VMP) is commercially valuable for its strong fragrance but little is known regarding the fragrance production and emission sites on the flowers.

    RESULTS: Olfactory perception detected fragrance only from the petals and sepals. Light and Environmental Scanning Electron microscopy analyses on fresh tissues showed distributions of stomata and trichomes concentrated mostly around the edges. These results paralleled the rich starch deposits and intense neutral red stain, indicating strong fragrance and trichomes as potential main fragrance release sites. Next Generation Sequencing (NGS) transcriptomic data of adaxial and abaxial layers of the tissues showed monoterpene synthase transcripts specifically linalool and ocimene synthases distributed throughout the tissues. qPCR analyses taken at different time points revealed high levels of linalool and ocimene synthases transcripts in the early morning with maximal level at 4.00 am but remained low throughout daylight hours.

    CONCLUSIONS: Knowledge of the VMP floral anatomy and its fragrance production characteristics, which complemented our previous molecular and biochemical data on VMP, provided additional knowledge on how fragrance and flower morphology are closely intertwined. Further investigation on the mechanisms of fragrance biosynthesis and interaction of potential pollinators would elucidate the evolution of the flower morphology to maximize the reproduction success of this plant.

    Matched MeSH terms: Gene Expression Profiling/methods*
  2. Aizat WM, Ismail I, Noor NM
    Adv Exp Med Biol, 2018 11 2;1102:1-9.
    PMID: 30382565 DOI: 10.1007/978-3-319-98758-3_1
    The central dogma of molecular biology (DNA, RNA, protein and metabolite) has engraved our understanding of genetics in all living organisms. While the concept has been embraced for many decades, the development of high-throughput technologies particularly omics (genomics, transcriptomics, proteomics and metabolomics) has revolutionised the field to incorporate big data analysis including bioinformatics and systems biology as well as synthetic biology area. These omics approaches as well as systems and synthetic biology areas are now increasingly popular as seen by the growing numbers of publication throughout the years. Several journals which have published most of these related fields are also listed in this chapter to overview their impact and target journals.
    Matched MeSH terms: Gene Expression Profiling/trends*
  3. Tan MS, Tan JW, Chang SW, Yap HJ, Abdul Kareem S, Zain RB
    PeerJ, 2016;4:e2482.
    PMID: 27688975 DOI: 10.7717/peerj.2482
    The potential of genetic programming (GP) on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis.
    Matched MeSH terms: Gene Expression Profiling
  4. Prabhakaran P, Nazir MYM, Thananusak R, Hamid AA, Vongsangnak W, Song Y
    PMID: 37625782 DOI: 10.1016/j.bbalip.2023.159381
    Aurantiochytrium sp., a marine thraustochytrid possesses a remarkable ability to produce lipid rich in polyunsaturated fatty acids (PUFAs), such as docosahexaenoic acid (DHA). Although gene regulation underlying lipid biosynthesis has been previously reported, proteomic analysis is still limited. In this study, high DHA accumulating strain Aurantiochytrium sp. SW1 has been used as a study model to elucidate the alteration in proteome profile under different cultivation phases i.e. growth, nitrogen-limitation and lipid accumulation. Of the total of 5146 identified proteins, 852 proteins were differentially expressed proteins (DEPs). The largest number of DEPs (488 proteins) was found to be uniquely expressed between lipid accumulating phase and growth phase. Interestingly, there were up-regulated proteins involved in glycolysis, glycerolipid, carotenoid and glutathione metabolism which were preferable metabolic routes towards lipid accumulation and DHA production as well as cellular oxidative defence. Integrated proteomic and transcriptomic data were also conducted to comprehend the gene and protein regulation underlying the lipid and DHA biosynthesis. A significant up-regulation of acetyl-CoA synthetase was observed which suggests alternative route of acetate metabolism for acetyl-CoA producer. This study presents the holistic routes underlying lipid accumulation and DHA production in Aurantiochytrium sp. SW1 and other relevant thraustochytrid.
    Matched MeSH terms: Gene Expression Profiling
  5. Mohandas S, Shete A, Sarkale P, Kumar A, Mote C, Yadav P
    Virulence, 2023 Dec;14(1):2224642.
    PMID: 37312405 DOI: 10.1080/21505594.2023.2224642
    Nipah virus (NiV) is a high-risk pathogen which can cause fatal infections in humans. The Indian isolate from the 2018 outbreak in the Kerala state of India showed ~ 4% nucleotide and amino acid difference in comparison to the Bangladesh strains of NiV and the substitutions observed were mostly not present in the region of any functional significance except for the phosphoprotein gene. The differential expression of viral genes was observed following infection in Vero (ATCC® CCL-81™) and BHK-21 cells. Intraperitoneal infection in the 10-12-week-old, Syrian hamster model induced dose dependant multisystemic disease characterized by prominent vascular lesions in lungs, brain, kidney and extra vascular lesions in brain and lungs. Congestion, haemorrhages, inflammatory cell infiltration, thrombosis and rarely endothelial syncitial cell formation were seen in the blood vessels. Intranasal infection resulted in respiratory tract infection characterised by pneumonia. The model showed disease characteristics resembling the human NiV infection except that of myocarditis similar to that reported by NiV-Malaysia and NiV-Bangladesh isolates in hamster model. The variation observed in the genome of the Indian isolate at the amino acid levels should be explored further for any functional significance.
    Matched MeSH terms: Gene Expression Profiling
  6. Suhaimi AH, Kobayashi MJ, Satake A, Ng CC, Lee SL, Muhammad N, et al.
    PeerJ, 2023;11:e16368.
    PMID: 38047035 DOI: 10.7717/peerj.16368
    Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation.
    Matched MeSH terms: Gene Expression Profiling
  7. Sultan G, Zubair S
    Comput Biol Chem, 2024 Feb;108:107999.
    PMID: 38070457 DOI: 10.1016/j.compbiolchem.2023.107999
    Breast cancer continues to be a prominent cause for substantial loss of life among women globally. Despite established treatment approaches, the rising prevalence of breast cancer is a concerning trend regardless of geographical location. This highlights the need to identify common key genes and explore their biological significance across diverse populations. Our research centered on establishing a correlation between common key genes identified in breast cancer patients. While previous studies have reported many of the genes independently, our study delved into the unexplored realm of their mutual interactions, that may establish a foundational network contributing to breast cancer development. Machine learning algorithms were employed for sample classification and key gene selection. The best performance model further selected the candidate genes through expression pattern recognition. Subsequently, the genes common in all the breast cancer patients from India, China, Czech Republic, Germany, Malaysia and Saudi Arabia were selected for further study. We found that among ten classifiers, Catboost exhibited superior performance with an average accuracy of 92%. Functional enrichment analysis and pathway analysis revealed that calcium signaling pathway, regulation of actin cytoskeleton pathway and other cancer-associated pathways were highly enriched with our identified genes. Notably, we observed that these genes regulate each other, forming a complex network. Additionally, we identified PALMD gene as a novel potential biomarker for breast cancer progression. Our study revealed key gene modules forming a complex network that were consistently expressed in different populations, affirming their critical role and biological significance in breast cancer. The identified genes hold promise as prospective biomarkers of breast cancer prognosis irrespective of country of origin or ethnicity. Future investigations will expand upon these genes in a larger population and validate their biological functions through in vivo analysis.
    Matched MeSH terms: Gene Expression Profiling
  8. Lau NS, Foong CP, Kurihara Y, Sudesh K, Matsui M
    PLoS One, 2014;9(1):e86368.
    PMID: 24466058 DOI: 10.1371/journal.pone.0086368
    The photosynthetic cyanobacterium, Synechocystis sp. strain 6803, is a potential platform for the production of various chemicals and biofuels. In this study, direct photosynthetic production of a biopolymer, polyhydroxyalkanoate (PHA), in genetically engineered Synechocystis sp. achieved as high as 14 wt%. This is the highest production reported in Synechocystis sp. under photoautotrophic cultivation conditions without the addition of a carbon source. The addition of acetate increased PHA accumulation to 41 wt%, and this value is comparable to the highest production obtained with cyanobacteria. Transcriptome analysis by RNA-seq coupled with real-time PCR was performed to understand the global changes in transcript levels of cells subjected to conditions suitable for photoautotrophic PHA biosynthesis. There was lower expression of most PHA synthesis-related genes in recombinant Synechocystis sp. with higher PHA accumulation suggesting that the concentration of these enzymes is not the limiting factor to achieving high PHA accumulation. In order to cope with the higher PHA production, cells may utilize enhanced photosynthesis to drive the product formation. Results from this study suggest that the total flux of carbon is the possible driving force for the biosynthesis of PHA and the polymerizing enzyme, PHA synthase, is not the only critical factor affecting PHA-synthesis. Knowledge of the regulation or control points of the biopolymer production pathways will facilitate the further use of cyanobacteria for biotechnological applications.
    Matched MeSH terms: Gene Expression Profiling*
  9. Ng KH, Ho CK, Phon-Amnuaisuk S
    PLoS One, 2012;7(10):e47216.
    PMID: 23071763 DOI: 10.1371/journal.pone.0047216
    Clustering is a key step in the processing of Expressed Sequence Tags (ESTs). The primary goal of clustering is to put ESTs from the same transcript of a single gene into a unique cluster. Recent EST clustering algorithms mostly adopt the alignment-free distance measures, where they tend to yield acceptable clustering accuracies with reasonable computational time. Despite the fact that these clustering methods work satisfactorily on a majority of the EST datasets, they have a common weakness. They are prone to deliver unsatisfactory clustering results when dealing with ESTs from the genes derived from the same family. The root cause is the distance measures applied on them are not sensitive enough to separate these closely related genes.
    Matched MeSH terms: Gene Expression Profiling/methods*
  10. Saghir FS, Rose IM, Dali AZ, Shamsuddin Z, Jamal AR, Mokhtar NM
    Int. J. Gynecol. Cancer, 2010 Jul;20(5):724-31.
    PMID: 20973258
    INTRODUCTION: Malignant transformation of type I endometrium involves alteration in gene expression with subsequent uncontrolled proliferation of altered cells.

    OBJECTIVE: The main objective of the present study was to identify the cancer-related genes and gene pathways in the endometrium of healthy and cancer patients.

    MATERIALS AND METHODS: Thirty endometrial tissues from healthy and type I EC patients were subjected to total RNA isolation. The RNA samples with good integrity number were hybridized to a new version of Affymetrix Human Genome GeneChip 1.0 ST array. We analyzed the results using the GeneSpring 9.0 GX and the Pathway Studio 6.1 software. For validation assay, quantitative real-time polymerase chain reaction was used to analyze 4 selected genes in normal and EC tissue.

    RESULTS: Of the 28,869 genes profiled, we identified 621 differentially expressed genes (2-fold) in the normal tissue and the tumor. Among these genes, 146 were up-regulated and 476 were down-regulated in the tumor as compared with the normal tissue (P < 0.001). Up-regulated genes included the v-erb-a erythroblastic leukemia viral oncogene homolog 3 (ErbB3), ErbB4, E74-like factor 3 (ELF3), and chemokine ligand 17 (CXCL17). The down-regulated genes included signal transducer and activator transcription 5B (STAT5b), transforming growth factor A receptor III (TGFA3), caveolin 1 (CAV1), and protein kinase C alpha (PKCA). The gene set enrichment analysis showed 10 significant gene sets with related genes (P < 0.05). The quantitative polymerase chain reaction of 4 selected genes using similar RNA confirmed the microarray results (P < 0.05).

    CONCLUSIONS: Identification of molecular pathways with their genes related to type I EC contribute to the understanding of pathophysiology of this cancer, probably leading to identifying potential biomarkers of the cancer.

    Matched MeSH terms: Gene Expression Profiling*
  11. Azlina A, Samsudin AR
    Med J Malaysia, 2004 May;59 Suppl B:166-7.
    PMID: 15468870
    In Malaysia, the field of genomics in toxicology is still in infancy. The purpose of this study is to focus on the use of toxicogenomics for determination of gene expressions changes in cultured human fibroblast cells treated with genotoxicology free biomaterial (using Ames test), a locally produced hyroxyapatite. Dose and time response is similar to Ames test with time interval up to 21 days. mRNA is extracted, followed with RT-PCR and polyacrilamide gel electrophoresis. Changes of the gene expressions compared to the non-treated fibroblast mRNA would suggest some gene interactions in the molecule level associated with the exposure of the fibroblast cell line to the biomaterials. Further analysis (cloning & sequencing) shall be carried out to investigate the genes involved as simple changes might not signified toxicity.
    Matched MeSH terms: Gene Expression Profiling*
  12. Moorthy K, Jaber AN, Ismail MA, Ernawan F, Mohamad MS, Deris S
    Methods Mol Biol, 2019;1986:255-266.
    PMID: 31115893 DOI: 10.1007/978-1-4939-9442-7_12
    In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al., Cell 173(2):371-385, 2018); thus, it is necessary to resolve the problem of missing-values imputation. This chapter presents a review of the research on missing-values imputation approaches for gene expression data. By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. Additionally, this chapter presents suitable assessments of the different approaches. The purpose of this review is to focus on developments in the current techniques for scientists rather than applying different or newly developed algorithms with identical functional goals. The aim was to adapt the algorithms to the characteristics of the data.
    Matched MeSH terms: Gene Expression Profiling*
  13. Reza Etemadi M, Ling KH, Zainal Abidin S, Chee HY, Sekawi Z
    PLoS One, 2017;12(5):e0176947.
    PMID: 28558071 DOI: 10.1371/journal.pone.0176947
    Human rhinovirus (HRV) is the common virus that causes acute respiratory infection (ARI) and is frequently associated with lower respiratory tract infections (LRTIs). We aimed to investigate whether HRV infection induces a specific gene expression pattern in airway epithelial cells. Alveolar epithelial cell monolayers were infected with HRV species B (HRV-B). RNA was extracted from both supernatants and infected monolayer cells at 6, 12, 24 and 48 hours post infection (hpi) and transcriptional profile was analyzed using Affymetrix GeneChip and the results were subsequently validated using quantitative Real-time PCR method. HRV-B infects alveolar epithelial cells which supports implication of the virus with LRTIs. In total 991 genes were found differentially expressed during the course of infection. Of these, 459 genes were up-regulated whereas 532 genes were down-regulated. Differential gene expression at 6 hpi (187 genes up-regulated vs. 156 down-regulated) were significantly represented by gene ontologies related to the chemokines and inflammatory molecules indicating characteristic of viral infection. The 75 up-regulated genes surpassed the down-regulated genes (35) at 12 hpi and their enriched ontologies fell into discrete functional entities such as regulation of apoptosis, anti-apoptosis, and wound healing. At later time points of 24 and 48 hpi, predominated down-regulated genes were enriched for extracellular matrix proteins and airway remodeling events. Our data provides a comprehensive image of host response to HRV infection. The study suggests the underlying molecular regulatory networks genes which might be involved in pathogenicity of the HRV-B and potential targets for further validations and development of effective treatment.
    Matched MeSH terms: Gene Expression Profiling*
  14. Ealam Selvan M, Lim KS, Teo CH, Lim YY
    J Vis Exp, 2022 Oct 21.
    PMID: 36342167 DOI: 10.3791/64565
    Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via back-splicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wet-lab techniques. To solve this issue, a step-by-step protocol of in silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions.
    Matched MeSH terms: Gene Expression Profiling/methods
  15. 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*
  16. 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
  17. 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
  18. 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
  19. 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*
  20. 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*
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