Summary： This study aimed to identify the differentially expressed genes after silencing of β-catenin in multiple myeloma transduced with β-catenin shRNA. The DNA microarray dataset GSE17385 was downloaded from Gen...Summary： This study aimed to identify the differentially expressed genes after silencing of β-catenin in multiple myeloma transduced with β-catenin shRNA. The DNA microarray dataset GSE17385 was downloaded from Gene Expression Omnibus, including 3 samples of MM1.S （human multiple mye- loma cell lines） cells transduced with control shRNA and 3 samples of MM1.S cells transduced with β-catenin shRNA. Then the differentially expressed genes （DEGs） were screened by using Limma. Their underlying functions were analyzed by employing Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Moreover, DEGs annotation was conducted based on the databases of tumor associated genes, tumor suppressed genes and the transcriptional regulation from patterns to profiles. Furthermore, the protein-protein interaction （PPI） relationship was obtained from STRING and the protein-protein interaction network and the functional modules were visual- ized by Cytoscape. Then, the pathway enrichment for the DEGs in the functional module was per- formed. A total of 301 DEGs, including 124 up-regulated and 117 down-regulated DEGs, were screened. Functional enrichment showed that CCNB1 and CDK1 were significantly related to the function of cell proliferation. FOS and JUN were related to innate immune response-activating signal transduction. Pathway enrichment analysis indicated that CCNB 1 and CDK1 were most significantly enriched in the pathway of cell cycle. Besides, FOS and JUN were significantly enriched in the Toll-like receptor signaling pathway. FOXM1 was identified as a transcription factor. Moreover, there existed interactions among CCNB1, FOXM1 and CDK1 in PPI network. The expression of FOS, JUN, CCNB1, FOXM1 and CDK1 may be affected by β-catenin in multiple myeloma.展开更多
Melon （Cucumis melo L.） is an important horticultural crop worldwide. Ethylene regulates the ripening process and affects the ripening rate. To screen genes that are differentially expressed at the burst of ethylene...Melon （Cucumis melo L.） is an important horticultural crop worldwide. Ethylene regulates the ripening process and affects the ripening rate. To screen genes that are differentially expressed at the burst of ethylene climacteric in melon fruit, we performed suppression subtractive hybridization （SSH） to generate forward and reverse libraries, for which we sequenced 439 and 445 clones, respectively. Our BLAST analysis showed that the genes from the 2 libraries were involved in metabolism, signal transduction, cell structure, transcription, translation, and defense. Six genes were analyzed by qRT-PCR during the differential developmental stage of melon fruit. Our results provide new insight into the understanding of climacteric ripening of melon fruit.展开更多
Identification of differentially expressed genes （DEGs） in time course studies is very useful for understanding gene function, and can help determine key genes during specific stages of plant development. A few exis...Identification of differentially expressed genes （DEGs） in time course studies is very useful for understanding gene function, and can help determine key genes during specific stages of plant development. A few existing methods focus on the detection of DEGs within a single biological group, enabling to study temporal changes in gene expression. To utilize a rapidly increasing amount of single-group time-series expression data, we propose a two-step method that integrates the temporal characteristics of time-series data to obtain a B-spline curve fit. Firstly, a fiat gene filter based on the Ljung-Box test is used to filter out flat genes. Then, a B-spline model is used to identify DEGs. For use in biological experiments, these DEGs should be screened, to determine their biological importance. To identify high-confidence promising DEGs for specific biological processes, we propose a novel gene prioritization approach based on the partner evaluation principle. This novel gene prioritization ap- proach utilizes existing co-expression information to rank DEGs that are likely to be involved in a specific biological process/condition. The proposed method is validated on the Arabidopsis thaliana seed germination dataset and on the rice anther development expression dataset.展开更多
基金supported by a grant from the National High-tech Research & Development Program(No.2011AA030101)
文摘Summary： This study aimed to identify the differentially expressed genes after silencing of β-catenin in multiple myeloma transduced with β-catenin shRNA. The DNA microarray dataset GSE17385 was downloaded from Gene Expression Omnibus, including 3 samples of MM1.S （human multiple mye- loma cell lines） cells transduced with control shRNA and 3 samples of MM1.S cells transduced with β-catenin shRNA. Then the differentially expressed genes （DEGs） were screened by using Limma. Their underlying functions were analyzed by employing Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Moreover, DEGs annotation was conducted based on the databases of tumor associated genes, tumor suppressed genes and the transcriptional regulation from patterns to profiles. Furthermore, the protein-protein interaction （PPI） relationship was obtained from STRING and the protein-protein interaction network and the functional modules were visual- ized by Cytoscape. Then, the pathway enrichment for the DEGs in the functional module was per- formed. A total of 301 DEGs, including 124 up-regulated and 117 down-regulated DEGs, were screened. Functional enrichment showed that CCNB1 and CDK1 were significantly related to the function of cell proliferation. FOS and JUN were related to innate immune response-activating signal transduction. Pathway enrichment analysis indicated that CCNB 1 and CDK1 were most significantly enriched in the pathway of cell cycle. Besides, FOS and JUN were significantly enriched in the Toll-like receptor signaling pathway. FOXM1 was identified as a transcription factor. Moreover, there existed interactions among CCNB1, FOXM1 and CDK1 in PPI network. The expression of FOS, JUN, CCNB1, FOXM1 and CDK1 may be affected by β-catenin in multiple myeloma.
基金supported by the National Natural Science Foundation of China(30960159)the Specialized Research Foundation for the Doctoral Program of Higher Education(200801260002)
文摘Melon （Cucumis melo L.） is an important horticultural crop worldwide. Ethylene regulates the ripening process and affects the ripening rate. To screen genes that are differentially expressed at the burst of ethylene climacteric in melon fruit, we performed suppression subtractive hybridization （SSH） to generate forward and reverse libraries, for which we sequenced 439 and 445 clones, respectively. Our BLAST analysis showed that the genes from the 2 libraries were involved in metabolism, signal transduction, cell structure, transcription, translation, and defense. Six genes were analyzed by qRT-PCR during the differential developmental stage of melon fruit. Our results provide new insight into the understanding of climacteric ripening of melon fruit.
文摘Identification of differentially expressed genes （DEGs） in time course studies is very useful for understanding gene function, and can help determine key genes during specific stages of plant development. A few existing methods focus on the detection of DEGs within a single biological group, enabling to study temporal changes in gene expression. To utilize a rapidly increasing amount of single-group time-series expression data, we propose a two-step method that integrates the temporal characteristics of time-series data to obtain a B-spline curve fit. Firstly, a fiat gene filter based on the Ljung-Box test is used to filter out flat genes. Then, a B-spline model is used to identify DEGs. For use in biological experiments, these DEGs should be screened, to determine their biological importance. To identify high-confidence promising DEGs for specific biological processes, we propose a novel gene prioritization approach based on the partner evaluation principle. This novel gene prioritization ap- proach utilizes existing co-expression information to rank DEGs that are likely to be involved in a specific biological process/condition. The proposed method is validated on the Arabidopsis thaliana seed germination dataset and on the rice anther development expression dataset.
