Displaying publications 61 - 80 of 366 in total

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  1. Mohamed Yusoff A, Tan TK, Hari R, Koepfli KP, Wee WY, Antunes A, et al.
    Sci Rep, 2016 09 13;6:28199.
    PMID: 27618997 DOI: 10.1038/srep28199
    Pangolins are scale-covered mammals, containing eight endangered species. Maintaining pangolins in captivity is a significant challenge, in part because little is known about their genetics. Here we provide the first large-scale sequencing of the critically endangered Manis javanica transcriptomes from eight different organs using Illumina HiSeq technology, yielding ~75 Giga bases and 89,754 unigenes. We found some unigenes involved in the insect hormone biosynthesis pathway and also 747 lipids metabolism-related unigenes that may be insightful to understand the lipid metabolism system in pangolins. Comparative analysis between M. javanica and other mammals revealed many pangolin-specific genes significantly over-represented in stress-related processes, cell proliferation and external stimulus, probably reflecting the traits and adaptations of the analyzed pregnant female M. javanica. Our study provides an invaluable resource for future functional works that may be highly relevant for the conservation of pangolins.
    Matched MeSH terms: Gene Expression Profiling/methods*
  2. Vincent-Chong VK, Salahshourifar I, Woo KM, Anwar A, Razali R, Gudimella R, et al.
    PLoS One, 2017;12(4):e0174865.
    PMID: 28384287 DOI: 10.1371/journal.pone.0174865
    BACKGROUND: Cancers of the oral cavity are primarily oral squamous cell carcinomas (OSCCs). Many of the OSCCs present at late stages with an exceptionally poor prognosis. A probable limitation in management of patients with OSCC lies in the insufficient knowledge pertaining to the linkage between copy number alterations in OSCC and oral tumourigenesis thereby resulting in an inability to deliver targeted therapy.

    OBJECTIVES: The current study aimed to identify copy number alterations (CNAs) in OSCC using array comparative genomic hybridization (array CGH) and to correlate the CNAs with clinico-pathologic parameters and clinical outcomes.

    MATERIALS AND METHODS: Using array CGH, genome-wide profiling was performed on 75 OSCCs. Selected genes that were harboured in the frequently amplified and deleted regions were validated using quantitative polymerase chain reaction (qPCR). Thereafter, pathway and network functional analysis were carried out using Ingenuity Pathway Analysis (IPA) software.

    RESULTS: Multiple chromosomal regions including 3q, 5p, 7p, 8q, 9p, 10p, 11q were frequently amplified, while 3p and 8p chromosomal regions were frequently deleted. These findings were in confirmation with our previous study using ultra-dense array CGH. In addition, amplification of 8q, 11q, 7p and 9p and deletion of 8p chromosomal regions showed a significant correlation with clinico-pathologic parameters such as the size of the tumour, metastatic lymph nodes and pathological staging. Co-amplification of 7p, 8q, 9p and 11q regions that harbored amplified genes namely CCND1, EGFR, TPM2 and LRP12 respectively, when combined, continues to be an independent prognostic factor in OSCC.

    CONCLUSION: Amplification of 3q, 5p, 7p, 8q, 9p, 10p, 11q and deletion of 3p and 8p chromosomal regions were recurrent among OSCC patients. Co-alteration of 7p, 8q, 9p and 11q was found to be associated with clinico-pathologic parameters and poor survival. These regions contain genes that play critical roles in tumourigenesis pathways.

    Matched MeSH terms: Gene Expression Profiling*
  3. Tan GW, Tan LP
    Methods Mol Biol, 2017;1580:7-19.
    PMID: 28439823 DOI: 10.1007/978-1-4939-6866-4_2
    Reverse transcription followed by real-time or quantitative polymerase chain reaction (RT-qPCR) is the gold standard for validation of results from transcriptomic profiling studies such as microarray and RNA sequencing. The current need for most studies, especially biomarker studies, is to evaluate the expression levels or fold changes of many transcripts in a large number of samples. With conventional low to medium throughput qPCR platforms, many qPCR plates would have to be run and a significant amount of RNA input per sample will be required to complete the experiments. This is particularly challenging when the size of study material (small biopsy, laser capture microdissected cells, biofluid, etc.), time, and resources are limited. A sensitive and high-throughput qPCR platform is therefore optimal for the evaluation of many transcripts in a large number of samples because the time needed to complete the entire experiment is shortened and the usage of lab consumables as well as RNA input per sample are low. Here, the methods of high-throughput RT-qPCR for the analysis of circulating microRNAs are described. Two distinctive qPCR chemistries (probe-based and intercalating dye-based) can be applied using the methods described here.
    Matched MeSH terms: Gene Expression Profiling/methods
  4. Rosli R, Amiruddin N, Ab Halim MA, Chan PL, Chan KL, Azizi N, et al.
    PLoS One, 2018;13(4):e0194792.
    PMID: 29672525 DOI: 10.1371/journal.pone.0194792
    Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops.
    Matched MeSH terms: Gene Expression Profiling*
  5. Mirsafian H, Ripen AM, Leong WM, Manaharan T, Mohamad SB, Merican AF
    Genomics, 2017 Oct;109(5-6):463-470.
    PMID: 28733102 DOI: 10.1016/j.ygeno.2017.07.003
    Differential gene and transcript expression pattern of human primary monocytes from healthy young subjects were profiled under different sequencing depths (50M, 100M, and 200M reads). The raw data consisted of 1.3 billion reads generated from RNA sequencing (RNA-Seq) experiments. A total of 17,657 genes and 75,392 transcripts were obtained at sequencing depth of 200M. Total splice junction reads showed an even more significant increase. Comparative analysis of the expression patterns of immune-related genes revealed a total of 217 differentially expressed (DE) protein-coding genes and 50 DE novel transcripts, in which 40 DE protein-coding genes were related to the immune system. At higher sequencing depth, more genes, known and novel transcripts were identified and larger proportion of reads were allowed to map across splice junctions. The results also showed that increase in sequencing depth has no effect on the sequence alignment.
    Matched MeSH terms: Gene Expression Profiling/methods*
  6. Wong YC, Teh HF, Mebus K, Ooi TEK, Kwong QB, Koo KL, et al.
    BMC Genomics, 2017 06 21;18(1):470.
    PMID: 28637447 DOI: 10.1186/s12864-017-3855-7
    BACKGROUND: The oil yield trait of oil palm is expected to involve multiple genes, environmental influences and interactions. Many of the underlying mechanisms that contribute to oil yield are still poorly understood. In this study, we used a microarray approach to study the gene expression profiles of mesocarp tissue at different developmental stages, comparing genetically related high- and low- oil yielding palms to identify genes that contributed to the higher oil-yielding palm and might contribute to the wider genetic improvement of oil palm breeding populations.

    RESULTS: A total of 3412 (2001 annotated) gene candidates were found to be significantly differentially expressed between high- and low-yielding palms at at least one of the different stages of mesocarp development evaluated. Gene Ontologies (GO) enrichment analysis identified 28 significantly enriched GO terms, including regulation of transcription, fatty acid biosynthesis and metabolic processes. These differentially expressed genes comprise several transcription factors, such as, bHLH, Dof zinc finger proteins and MADS box proteins. Several genes involved in glycolysis, TCA, and fatty acid biosynthesis pathways were also found up-regulated in high-yielding oil palm, among them; pyruvate dehydrogenase E1 component Subunit Beta (PDH), ATP-citrate lyase, β- ketoacyl-ACP synthases I (KAS I), β- ketoacyl-ACP synthases III (KAS III) and ketoacyl-ACP reductase (KAR). Sucrose metabolism-related genes such as Invertase, Sucrose Synthase 2 and Sucrose Phosphatase 2 were found to be down-regulated in high-yielding oil palms, compared to the lower yield palms.

    CONCLUSIONS: Our findings indicate that a higher carbon flux (channeled through down-regulation of the Sucrose Synthase 2 pathway) was being utilized by up-regulated genes involved in glycolysis, TCA and fatty acid biosynthesis leading to enhanced oil production in the high-yielding oil palm. These findings are an important stepping stone to understand the processes that lead to production of high-yielding oil palms and have implications for breeding to maximize oil production.

    Matched MeSH terms: Gene Expression Profiling*
  7. Vikashini B, Shanthi A, Ghosh Dasgupta M
    Gene, 2018 Nov 15;676:37-46.
    PMID: 30201104 DOI: 10.1016/j.gene.2018.07.012
    Casuarina equisetifolia L. is an important multi-purpose, fast growing and widely planted tree species native to tropical and subtropical coastlines of Australia, Southeast Asia, Malaysia, Melanesia, Polynesia and New Caledonia. It is a nitrogen-fixing tree mainly used for charcoal making, construction poles, landscaping, timber, pulp, firewood, windbreaks, shelterbelts, soil erosion and sand dune stabilization. Casuarina wood is presently used for paper and pulp production. Raw material with reduced lignin is highly preferred to increase the pulp yield. Hence, understanding the molecular regulation of wood formation in this tree species is vital for selecting industrially suitable phenotypes for breeding programs. The lignin biosynthetic pathway has been extensively studied in tree species like Eucalypts, poplars, pines, Picea, Betula and Acacia sp. However, studies on wood formation at molecular level is presently lacking in casuarinas. Hence, in the present study, the transcriptome of the developing secondary tissues of 15 years old Casuarina equiseitfolia subsp. equisetifolia was sequenced, de novo assembled, annotated and mapped to functional pathways. Transcriptome sequencing generated a total of 26,985 transcripts mapped to 31 pathways. Mining of the annotated data identified nine genes involved in lignin biosynthesis pathway and relative expression of the transcripts in four tissues including scale-like leaves, needle-like brachlets, wood and root were documented. The expression of CeCCR1 and CeF5H were found to be significantly high in wood tissues, while maximum expression of CeHCT was documented in stem. Additionally, CeTUBA and CeH2A were identified as the most stable reference transcript for normalization of qRT-PCR data in C. equisetifolia. The present study is the first wood genomic resource in C. equisetifolia, which will be valuable for functional genomics research in this genus.
    Matched MeSH terms: Gene Expression Profiling/methods
  8. Kong SL, Abdullah SNA, Ho CL, Musa MHB, Yeap WC
    BMC Genom Data, 2021 02 05;22(1):6.
    PMID: 33568046 DOI: 10.1186/s12863-021-00962-7
    BACKGROUND: Phosphorus (P), in its orthophosphate form (Pi) is an essential macronutrient for oil palm early growth development in which Pi deficiency could later on be reflected in lower biomass production. Application of phosphate rock, a non-renewable resource has been the common practice to increase Pi accessibility and maintain crop productivity in Malaysia. However, high fixation rate of Pi in the native acidic tropical soils has led to excessive utilization of P fertilizers. This has caused serious environmental pollutions and cost increment. Even so, the Pi deficiency response mechanism in oil palm as one of the basic prerequisites for crop improvement remains largely unknown.

    RESULTS: Using total RNA extracted from young roots as template, we performed a comparative transcriptome analysis on oil palm responding to 14d and 28d of Pi deprivation treatment and under adequate Pi supply. By using Illumina HiSeq4000 platform, RNA-Seq analysis was successfully conducted on 12 paired-end RNA-Seq libraries and generated more than 1.2 billion of clean reads in total. Transcript abundance estimated by fragments per kilobase per million fragments (FPKM) and differential expression analysis revealed 36 and 252 genes that are differentially regulated in Pi-starved roots at 14d and 28d, respectively. Genes possibly involved in regulating Pi homeostasis, nutrient uptake and transport, hormonal signaling and gene transcription were found among the differentially expressed genes.

    CONCLUSIONS: Our results showed that the molecular response mechanism underlying Pi starvation in oil palm is complexed and involved multilevel regulation of various sensing and signaling components. This contribution would generate valuable genomic resources in the effort to develop oil palm planting materials that possess Pi-use efficient trait through molecular manipulation and breeding programs.

    Matched MeSH terms: Gene Expression Profiling*
  9. Ng WL, Marinov GK, Chin YM, Lim YY, Ea CK
    Sci Rep, 2017 09 25;7(1):12227.
    PMID: 28947785 DOI: 10.1038/s41598-017-12550-w
    Circular RNAs (circRNAs) have recently emerged as a large class of novel non-coding RNA species. However, the detailed functional significance of the vast majority of them remains to be elucidated. Most functional characterization studies targeting circRNAs have been limited to resting cells, leaving their role in dynamic cellular responses to stimuli largely unexplored. In this study, we focus on the LPS-induced cytoplasmic circRNA, mcircRasGEF1B, and combine targeted mcircRasGEF1B depletion with high-throughput transcriptomic analysis to gain insight into its function during the cellular response to LPS stimulation. We show that knockdown of mcircRasGEF1B results in altered expression of a wide array of genes. Pathway analysis revealed an overall enrichment of genes involved in cell cycle progression, mitotic division, active metabolism, and of particular interest, NF-κB, LPS signaling pathways, and macrophage activation. These findings expand the set of functionally characterized circRNAs and support the regulatory role of mcircRasGEF1B in immune response during macrophage activation and protection against microbial infections.
    Matched MeSH terms: Gene Expression Profiling*
  10. Ng GYL, Tan SC, Ong CS
    PLoS One, 2023;18(10):e0292961.
    PMID: 37856458 DOI: 10.1371/journal.pone.0292961
    Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell types. Therefore, gene selection, also known as feature selection in data science, plays an important role in selecting informative genes for scRNA-seq cell type identification. Generally speaking, feature selection methods are categorized into filter-, wrapper-, and embedded-based approaches. From the existing literature, methods from filter- and embedded-based approaches are widely applied in scRNA-seq gene selection tasks. The wrapper-based method that gives promising results in other fields has yet been extensively utilized for selecting gene features from scRNA-seq data; in addition, most of the existing wrapper methods used in this field are clustering instead of classification-based. With a large number of annotated data available today, this study applied a classification-based approach as an alternative to the clustering-based wrapper method. In our work, a quantum-inspired differential evolution (QDE) wrapped with a classification method was introduced to select a subset of genes from twelve well-known scRNA-seq transcriptomic datasets to identify cell types. In particular, the QDE was combined with different machine-learning (ML) classifiers namely logistic regression, decision tree, support vector machine (SVM) with linear and radial basis function kernels, as well as extreme learning machine. The linear SVM wrapped with QDE, namely QDE-SVM, was chosen by referring to the feature selection results from the experiment. QDE-SVM showed a superior cell type classification performance among QDE wrapping with other ML classifiers as well as the recent wrapper methods (i.e., FSCAM, SSD-LAHC, MA-HS, and BSF). QDE-SVM achieved an average accuracy of 0.9559, while the other wrapper methods achieved average accuracies in the range of 0.8292 to 0.8872.
    Matched MeSH terms: Gene Expression Profiling/methods
  11. Zhang Y, Miao G, Fazhan H, Waiho K, Zheng H, Li S, et al.
    Physiol Genomics, 2018 05 01;50(5):393-405.
    PMID: 29570432 DOI: 10.1152/physiolgenomics.00016.2018
    The crucifix crab, Charybdis feriatus, which mainly inhabits Indo-Pacific region, is regarded as one of the most high-potential species for domestication and incorporation into the aquaculture sector. However, the regulatory mechanisms of sex determination and differentiation of this species remain unclear. To identify candidate genes involved in sex determination and differentiation, high throughput sequencing of transcriptome from the testis and ovary of C. feriatus was performed by the Illumina platform. After removing adaptor primers, low-quality sequences and very short (<50 nt) reads, we obtained 80.9 million and 66.2 million clean reads from testis and ovary, respectively. A total of 86,433 unigenes were assembled, and ~43% (37,500 unigenes) were successfully annotated to the NR, NT, Swiss-Prot, KEGG, COG, GO databases. By comparing the testis and ovary libraries, we obtained 27,636 differentially expressed genes. Some candidate genes involved in the sex determination and differentiation of C. feriatus were identified, such as vasa, pgds, vgr, hsp90, dsx-f, fem-1, and gpr. In addition, 88,608 simple sequence repeats were obtained, and 61,929 and 77,473 single nucleotide polymorphisms from testis and ovary were detected, respectively. The transcriptome profiling was validated by quantitative real-time PCR in 30 selected genes, which showed a good consistency. The present study is the first high-throughput transcriptome sequencing of C. feriatus. These findings will be useful for future functional analysis of sex-associated genes and molecular marker-assisted selections in C. feriatus.
    Matched MeSH terms: Gene Expression Profiling/methods
  12. Seow P, Wong JHD, Ahmad-Annuar A, Mahajan A, Abdullah NA, Ramli N
    Br J Radiol, 2018 Dec;91(1092):20170930.
    PMID: 29902076 DOI: 10.1259/bjr.20170930
    OBJECTIVE:: The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features.

    METHODS:: A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.

    RESULTS:: Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.

    CONCLUSION:: The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine.

    ADVANCES IN KNOWLEDGE:: Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.

    Matched MeSH terms: Gene Expression Profiling*
  13. Chan KL, Rosli R, Tatarinova TV, Hogan M, Firdaus-Raih M, Low EL
    BMC Bioinformatics, 2017 Jan 27;18(Suppl 1):1426.
    PMID: 28466793 DOI: 10.1186/s12859-016-1426-6
    BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion.

    RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure).

    CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

    Matched MeSH terms: Gene Expression Profiling*
  14. Ong SS, Wickneswari R
    BMC Genomics, 2011 Nov 30;12 Suppl 3(Suppl 3):S13.
    PMID: 22369296 DOI: 10.1186/1471-2164-12-S3-S13
    BACKGROUND: Lignin, after cellulose, is the second most abundant biopolymer accounting for approximately 15-35% of the dry weight of wood. As an important component during wood formation, lignin is indispensable for plant structure and defense. However, it is an undesirable component in the pulp and paper industry. Removal of lignin from cellulose is costly and environmentally hazardous process. Tremendous efforts have been devoted to understand the role of enzymes and genes in controlling the amount and composition of lignin to be deposited in the cell wall. However, studies on the impact of downregulation and overexpression of monolignol biosynthesis genes in model species on lignin content, plant fitness and viability have been inconsistent. Recently, non-coding RNAs have been discovered to play an important role in regulating the entire monolignol biosynthesis pathway. As small RNAs have critical functions in various biological process during wood formation, small RNA profiling is an important tool for the identification of complete set of differentially expressed small RNAs between low lignin and high lignin secondary xylem.

    RESULTS: In line with this, we have generated two small RNAs libraries from samples with contrasting lignin content using Illumina GAII sequencer. About 10 million sequence reads were obtained in secondary xylem of Am48 with high lignin content (41%) and a corresponding 14 million sequence reads were obtained in secondary xylem of Am54 with low lignin content (21%). Our results suggested that A. mangium small RNAs are composed of a set of 12 highly conserved miRNAs families found in plant miRNAs database, 82 novel miRNAs and a large proportion of non-conserved small RNAs with low expression levels. The predicted target genes of those differentially expressed conserved and non-conserved miRNAs include transcription factors associated with regulation of the lignin biosynthetic pathway genes. Some of these small RNAs play an important role in epigenetic silencing. Differential expression of the small RNAs between secondary xylem tissues with contrasting lignin content suggests that a cascade of miRNAs play an interconnected role in regulating the lignin biosynthetic pathway in Acacia species.

    CONCLUSIONS: Our study critically demonstrated the roles of small RNAs during secondary wall formation. Comparison of the expression pattern of small RNAs between secondary xylem tissues with contrasting lignin content strongly indicated that small RNAs play a key regulatory role during lignin biosynthesis. Our analyses suggest an evolutionary mechanism for miRNA targets on the basis of the length of their 5' and 3' UTRs and their cellular roles. The results obtained can be used to better understand the roles of small RNAs during lignin biosynthesis and for the development of gene constructs for silencing of specific genes involved in monolignol biosynthesis with minimal effect on plant fitness and viability. For the first time, small RNAs were proven to play an important regulatory role during lignin biosynthesis in A. mangium.

    Matched MeSH terms: Gene Expression Profiling*
  15. Kozlov SA, Lazarev VN, Kostryukova ES, Selezneva OV, Ospanova EA, Alexeev DG, et al.
    Sci Data, 2014;1:140023.
    PMID: 25977780 DOI: 10.1038/sdata.2014.23
    A comprehensive transcriptome analysis of an expressed sequence tag (EST) database of the spider Dolomedes fimbriatus venom glands using single-residue distribution analysis (SRDA) identified 7,169 unique sequences. Mature chains of 163 different toxin-like polypeptides were predicted on the basis of well-established methodology. The number of protein precursors of these polypeptides was appreciably numerous than the number of mature polypeptides. A total of 451 different polypeptide precursors, translated from 795 unique nucleotide sequences, were deduced. A homology search divided the 163 mature polypeptide sequences into 16 superfamilies and 19 singletons. The number of mature toxins in a superfamily ranged from 2 to 49, whereas the diversity of the original nucleotide sequences was greater (2-261 variants). We observed a predominance of inhibitor cysteine knot toxin-like polypeptides among the cysteine-containing structures in the analyzed transcriptome bank. Uncommon spatial folds were also found.
    Matched MeSH terms: Gene Expression Profiling/methods
  16. Boo SY, Tan SW, Alitheen NB, Ho CL, Omar AR, Yeap SK
    Sci Rep, 2020 05 22;10(1):8561.
    PMID: 32444639 DOI: 10.1038/s41598-020-65474-3
    Due to the limitations in the range of antibodies recognising avian viruses, quantitative real-time PCR (RT-qPCR) is still the most widely used method to evaluate the expression of immunologically related genes in avian viruses. The objective of this study was to identify suitable reference genes for mRNA expression analysis in chicken intraepithelial lymphocyte natural killer (IEL-NK) cells after infection with very-virulent infectious bursal disease virus (vvIBDV). Fifteen potential reference genes were selected based on the references available. The coefficient of variation percentage (CV%) and average count of these 15 genes were determined by NanoString technology for control and infected samples. The M and V values for shortlisted reference genes (ACTB, GAPDH, HMBS, HPRT1, SDHA, TUBB1 and YWHAZ) were calculated using geNorm and NormFinder. GAPDH, YWHAZ and HMBS were the most stably expressed genes. The expression levels of three innate immune response related target genes, CASP8, IL22 and TLR3, agreed in the NanoString and RNA sequencing (RNA-Seq) results using one or two reference genes for normalisation (not HMBS). In conclusion, GAPDH and YWHAZ could be used as reference genes for the normalisation of chicken IEL-NK cell gene responses to infection with vvIBDV.
    Matched MeSH terms: Gene Expression Profiling/methods; Gene Expression Profiling/standards*
  17. Mirakholi M, Mahmoudi T, Heidari M
    Acta Med Iran, 2013;51(12):823-9.
    PMID: 24442535
    In the retinoblastoma research, it is of great interest to identify molecular markers associated with the genetics of tumorigenesis. microRNAs (miRNAs) are small non-coding RNA molecules that play a regulatory role in many crucial cellular pathways such as differentiation, cell cycle progression, and apoptosis. A body of evidences showed dysregulation of miRNAs in tumor biology and many diseases. They potentially play a significant role in tumorigenesis processes and have been the subject of research in many types of cancers including retinal tumorigenesis. miRNA expression profiling was found to be associated with tumor development, progression and treatment. These associations demonstrate the putative applications of miRNAs in monitoring of different aspect of tumors consisting diagnostic, prognostic and therapeutic. Herein, we review the current literature concerning to the study of miRNA target recognition, function to tumorigenesis and treatment in retinoblastoma. Identification the specific miRNA biomarkers associated with retinoblastoma cancer may help to establish new therapeutic approaches for salvage affected eyes in patients.
    Matched MeSH terms: Gene Expression Profiling
  18. Austin CM, Tan MH, Harrisson KA, Lee YP, Croft LJ, Sunnucks P, et al.
    Gigascience, 2017 08 01;6(8):1-6.
    PMID: 28873963 DOI: 10.1093/gigascience/gix063
    One of the most iconic Australian fish is the Murray cod, Maccullochella peelii (Mitchell 1838), a freshwater species that can grow to ∼1.8 metres in length and live to age ≥48 years. The Murray cod is of a conservation concern as a result of strong population contractions, but it is also popular for recreational fishing and is of growing aquaculture interest. In this study, we report the whole genome sequence of the Murray cod to support ongoing population genetics, conservation, and management research, as well as to better understand the evolutionary ecology and history of the species. A draft Murray cod genome of 633 Mbp (N50 = 109 974bp; BUSCO and CEGMA completeness of 94.2% and 91.9%, respectively) with an estimated 148 Mbp of putative repetitive sequences was assembled from the combined sequencing data of 2 fish individuals with an identical maternal lineage; 47.2 Gb of Illumina HiSeq data and 804 Mb of Nanopore data were generated from the first individual while 23.2 Gb of Illumina MiSeq data were generated from the second individual. The inclusion of Nanopore reads for scaffolding followed by subsequent gap-closing using Illumina data led to a 29% reduction in the number of scaffolds and a 55% and 54% increase in the scaffold and contig N50, respectively. We also report the first transcriptome of Murray cod that was subsequently used to annotate the Murray cod genome, leading to the identification of 26 539 protein-coding genes. We present the whole genome of the Murray cod and anticipate this will be a catalyst for a range of genetic, genomic, and phylogenetic studies of the Murray cod and more generally other fish species of the Percichthydae family.
    Matched MeSH terms: Gene Expression Profiling
  19. Ali SS, Asman A, Shao J, Firmansyah AP, Susilo AW, Rosmana A, et al.
    PMID: 31583107 DOI: 10.1186/s40694-019-0077-6
    Background: Ceratobasidium theobromae, a member of the Ceratobasidiaceae family, is the causal agent of vascular-streak dieback (VSD) of cacao, a major threat to the chocolate industry in the South-East Asia. The fastidious pathogen is very hard to isolate and maintain in pure culture, which is a major bottleneck in the study of its genetic diversity and genome.

    Result: This study describes for the first time, a 33.90 Mbp de novo assembled genome of a putative C. theobromae isolate from cacao. Ab initio gene prediction identified 9264 protein-coding genes, of which 800 are unique to C. theobromae when compared to Rhizoctonia spp., a closely related group. Transcriptome analysis using RNA isolated from 4 independent VSD symptomatic cacao stems identified 3550 transcriptionally active genes when compared to the assembled C. theobromae genome while transcripts for only 4 C. theobromae genes were detected in 2 asymptomatic stems. De novo assembly of the non-cacao associated reads from the VSD symptomatic stems uniformly produced genes with high identity to predicted genes in the C. theobromae genome as compared to Rhizoctonia spp. or genes found in Genbank. Further analysis of the predicted C. theobromae transcriptome was carried out identifying CAZy gene classes, KEGG-pathway associated genes, and 138 putative effector proteins.

    Conclusion: These findings put forth, for the first time, a predicted genome for the fastidious basidiomycete C. theobromae causing VSD on cacao providing a model for testing and comparison in the future. The C. theobromae genome predicts a pathogenesis model involving secreted effector proteins to suppress plant defense mechanisms and plant cell wall degrading enzymes.

    Matched MeSH terms: Gene Expression Profiling
  20. Roslan HA, Anji SB
    3 Biotech, 2011 Jul;1(1):27-33.
    PMID: 22558533
    Chitinase is an enzyme that catalyzes the degradation of chitin, commonly induced upon the attack of pathogens and other stresses. A cDNA (MsChi1) was isolated from Metroxylon sagu and expressed predominantly in the inflorescence tissue of M. sagu, suggesting its role in developmental processes. The chitinase cDNA was detected and isolated via differential display and rapid amplification of cDNA ends (RACE). Primers specific to M. saguchitinase were used as probes to amplify the 3'-end and 5'-end regions of chitinase cDNA. Transcript analysis showed that chitinase is expressed in inflorescence and meristem tissues but was not detected in the leaf tissue. Sequence analysis of amplified cDNA fragments of 3'-end and 5'-end regions indicated that the chitinase cDNA was successfully amplified. The M. saguchitinase cDNA isolated was approximately 1,143 bp long and corresponds to 312 predicted amino acids. Alignments of nucleotide and amino acid have grouped this chitinase to family 19 class I chitinase.
    Matched MeSH terms: Gene Expression Profiling
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