Serial analysis of gene expression (SAGE) is an effective method of determining gene expression profiles of tissues and organs under different conditions. In this paper, the detail protocol of SAGE was introduced and some modified procedure of SAGE was reviewed.
Gene Expression Profiling ; methods

No abstract available.
Gene Expression Profiling* ; RNA ; Transcriptome*

Humans ; Transcriptome ; Gene Expression Profiling

OBJECTIVE: To screen differentially expressed gene (DEG) related to myelodysplastic syndrome (MDS) based on Gene Expression Omnibus (GEO) database, and explore the core genes and pathogenesis of MDS by analyzing the biological functions and related signaling pathways of DEG. METHODS: The expression profiles of GSE4619, GSE19429, GSE58831 including MDS patients and normal controls were downloaded from GEO database. The gene expression analysis tool (GEO2R) of GEO database was used to screen DEG according to | log FC (fold change) |≥1 and P<0.01. David online database was used to annotate gene ontology function (GO). Metascape online database was used to enrich and analyze differential genes in Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction network (PPI) was constructed by using STRING database. CytoHubba and Mcode plug-ins of Cytoscape were used to analyze the key gene clusters and hub genes. R language was used to diagnose hub genes and draw the ROC curve. GSEA enrichment analysis was performed on GSE19429 according to the expression of LEF1. RESULTS: A total of 74 co-DEG were identified, including 14 up-regulated genes and 60 down regulated genes. GO enrichment analysis indicated that BP of down regulated genes was mainly enriched in the transcription and regulation of RNA polymerase II promoter, negative regulation of cell proliferation, and immune response. CC of down regulated genes was mainly enriched in the nucleus, transcription factor complexes, and adhesion spots. MF was mainly enriched in protein binding, DNA binding, and β-catenin binding. KEGG pathway was enriched in primary immunodeficiency, Hippo signaling pathway, cAMP signaling pathway, transcriptional mis-regulation in cancer and hematopoietic cell lineage. BP of up-regulated genes was mainly enriched in type I interferon signaling pathway and viral response. CC was mainly enriched in cytoplasm. MF was mainly enriched in RNA binding. Ten hub genes and three important gene clusters were screened by STRING database and Cytoscape software. The functions of the three key gene clusters were closely related to immune regulation. ROC analysis showed that the hub genes had a good diagnostic significance for MDS. GSEA analysis indicated that LEF1 may affect the normal function of hematopoietic stem cells by regulating inflammatory reaction, which further revealed the pathogenesis of MDS. CONCLUSION Bioinformatics can effectively screen the core genes and key signaling pathways of MDS, which provides a new strategy for the diagnosis and treatment of MDS.
Computational Biology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Ontology ; Humans ; Myelodysplastic Syndromes/genetics*

Benzene ; toxicity ; Gene Expression Profiling ; Oligonucleotide Array Sequence Analysis

It is generally considered that various regulatory activities between genes are contained in the gene expression datasets. Therefore, the underlying gene regulatory relationship and the biologically useful information can be found by modeling the gene regulatory network from the gene expression data. In our study, two unsupervised matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF), were proposed to identify significant genes and model the regulatory network using the microarray gene expression data of Alzheimer's disease (AD). By bio-molecular analyzing of the pathways, the differences between ICA and NMF have been explored and the fact, which the inflammatory reaction is one of the main pathological mechanisms of AD, is also emphasized. It was demonstrated that our study gave a novel and valuable method for the research of early detection and pathological mechanism, biomarkers' findings of AD.
Algorithms ; Alzheimer Disease ; genetics ; Gene Expression Profiling ; methods ; Humans

OBJECTIVETo develop the methodology of gene chip to analyse genes involved in aflatoxin biosynthesis.

METHODSIn comparing reversed transcriptional PCR with gene chip, the gene chip was used to detect genes involved in aflatoxin biosynthesis.

RESULTSAfter arrayed the slide was incubated in water for 2 hours, exposed to a 650 mJ/cm2 of ultraviolet irradiation in the strata-linker for 30 s, roasted under 80 degrees C for 2 hours in oven, pre-hybridized for 45 minutes and dealt with other procedures. Finally, the slide was hybridized with fluor-derivatized sample at 42 degrees C for 16 hours.

CONCLUSIONWith the reasonable probe design and applicable protocol, the gene chip was prepared effectively for research on genes involved in aflatoxin biosynthesis.

The rhizome of Panax japonicus var. major have been used as the natural medicinal agent by Chinese traditional doctors for more than thousand years. Most of the therapeutic effects of P. japonicus var. major had been reported due to the presence of tetracyclic or pentacyclic triterpene saponins. In this study, Illumina pair-end RNA-sequencing and de novo splicing were done in order to understand the pathway of triterpenoid saponins in this species. The valid reads data of 15. 6 Gb were obtained. The 62 240 unigenes were finally obtained by de novo splicing. After annotation, we discovered 19 unigenes involved in ginsenoside backbone biosynthesis. Additionally, 69 unigenes and 18 unigenes were predicted to have potential function of cytochrome P450 and UDP-glycosyltransferase based on the annotation results, which may encode enzymes responsible for ginsenoside backbone modification. This study provides global expressed datas for P. japonicus var. major, which will contribute significantly to further genome-wide research and analysis for this species.
Gene Expression Profiling ; Panax ; genetics ; Saponins ; biosynthesis ; Sequence Analysis, RNA

BACKGROUNDClustering is a useful exploratory technique for interpreting gene expression data to reveal groups of genes sharing common functional attributes. Biologists frequently face the problem of choosing an appropriate algorithm. We aimed to provide a standalone, easily accessible and biologically oriented criterion for expression data clustering evaluation.

METHODSAn external criterion utilizing annotation based similarities between genes is proposed in this work. Gene ontology information is employed as the annotation source. Comparisons among six widely used clustering algorithms over various types of gene expression data sets were carried out based on the criterion proposed.

RESULTSThe rank of these algorithms given by the criterion coincides with our common knowledge. Single-linkage has significantly poorer performance, even worse than the random algorithm. Ward's method archives the best performance in most cases.

CONCLUSIONSThe criterion proposed has a strong ability to distinguish among different clustering algorithms with different distance measurements. It is also demonstrated that analyzing main contributors of the criterion may offer some guidelines in finding local compact clusters. As an addition, we suggest using Ward's algorithm for gene expression data analysis.

Pear is one of the main fruits with thousands of years of cultivation history in China. There are more than 2000 varieties of pear cultivars around the world, including more than 1200 varieties or cultivars in China (Legrand et al., 2016). Xinjiang Uygur Autonomous Region is an important pear production region in China with 30 of varieties or cultivars. Pyrus sinkiangensis is the most popular variety, which is mainly distributed in Xinjiang (Zhou et al., 2018). Chlorogenic acid (CGA), p-coumaric acid, and arbutin are the main polyphenols in pear fruit, and their levels show great differences among different varieties (Li et al., 2014). CGA is a potential chemo-preventive agent, which possesses many important bioactivities including antioxidant, diabetes attenuating, and anti-obesity (Wang et al., 2021). Therefore, the specific CGA content of a variety is considered the embodiment of the functional nutritional value of pears.
Chlorogenic Acid ; Fruit ; Gene Expression Profiling ; Pyrus/genetics* ; Transcriptome