【共享】RNAi相关新闻
丁香园论坛
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【2005年3月】
2005-03-14: Oxford BioMedica用RNAi慢病毒治疗家族ALS动物模型
http://www.oxfordbiomedica.co.uk/news/2005-ob-09.htm
http://www.nature.com/nm/journal/vaop/ncurrent/abs/nm1205.html
Oxford BioMedica (LSE:OXB.L), the leading gene therapy company, announced today the publication, in the journal Nature Medicine, of a paper demonstrating efficacy of the Company’s LentiVector technology in an animal model of inherited (familial) amyotrophic lateral sclerosis (ALS) or motor neuron disease. The paper describes the delivery, by the LentiVector technology, of a specific RNAi molecule that shuts down the gene that causes the disease.
2005-03-16: MIT、Harvard等11家单位欲投资$18M构建全球共享的RNAi文库
http://bio.com/newsfeatures/newsfeatures_research.jhtml;jsessionid=KYYVE5OLC24YBR3FQLMSFEWHUWBNQIV0?cid=9100034
Eleven leading biomedical organizations announced today the formation of a unique $18M, three-year public-private consortium to create a comprehensive library of gene inhibitors to be made available to the entire scientific community. Based on the method of RNA interference (RNAi), this library will give scientists worldwide the tools to knock down expression of virtually all human and mouse genes, accelerating the growth of basic knowledge of gene function in normal physiology and disease.
2005-03-24: 麻省总院发现80条RNAi关键基因
http://www.eurekalert.org/pub_releases/2005-03/mgh-sig032305.php
http://www.sciencemag.org/cgi/content/abstract/1109267v1
A research team based at Massachusetts General Hospital (MGH) has identified 80 new genes essential to the process of RNA interference (RNAi), a powerful new research tool for inactivating genes in plants or animals. They used the RNAi process itself to find new genes that participate in the gene-silencing mechanism, which someday may help to fight human disease. The report will appear in the journal Science and is receiving early online release on the Science Express website at http://www.sciencexpress.org.
2005-03-24: 高通量RNAi揭示线虫细胞分裂所需基因
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v434/n7032/abs/nature03353_fs.html
A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.
2005-03-14: Oxford BioMedica用RNAi慢病毒治疗家族ALS动物模型
http://www.oxfordbiomedica.co.uk/news/2005-ob-09.htm
http://www.nature.com/nm/journal/vaop/ncurrent/abs/nm1205.html
Oxford BioMedica (LSE:OXB.L), the leading gene therapy company, announced today the publication, in the journal Nature Medicine, of a paper demonstrating efficacy of the Company’s LentiVector technology in an animal model of inherited (familial) amyotrophic lateral sclerosis (ALS) or motor neuron disease. The paper describes the delivery, by the LentiVector technology, of a specific RNAi molecule that shuts down the gene that causes the disease.
2005-03-16: MIT、Harvard等11家单位欲投资$18M构建全球共享的RNAi文库
http://bio.com/newsfeatures/newsfeatures_research.jhtml;jsessionid=KYYVE5OLC24YBR3FQLMSFEWHUWBNQIV0?cid=9100034
Eleven leading biomedical organizations announced today the formation of a unique $18M, three-year public-private consortium to create a comprehensive library of gene inhibitors to be made available to the entire scientific community. Based on the method of RNA interference (RNAi), this library will give scientists worldwide the tools to knock down expression of virtually all human and mouse genes, accelerating the growth of basic knowledge of gene function in normal physiology and disease.
2005-03-24: 麻省总院发现80条RNAi关键基因
http://www.eurekalert.org/pub_releases/2005-03/mgh-sig032305.php
http://www.sciencemag.org/cgi/content/abstract/1109267v1
A research team based at Massachusetts General Hospital (MGH) has identified 80 new genes essential to the process of RNA interference (RNAi), a powerful new research tool for inactivating genes in plants or animals. They used the RNAi process itself to find new genes that participate in the gene-silencing mechanism, which someday may help to fight human disease. The report will appear in the journal Science and is receiving early online release on the Science Express website at http://www.sciencexpress.org.
2005-03-24: 高通量RNAi揭示线虫细胞分裂所需基因
http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v434/n7032/abs/nature03353_fs.html
A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.
