| Extraction of Total Proteins from Rice Plant
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Author:
Date:
2014-11-05
[Abstract] This protocol provides an efficient method for preparation of high-quality proteins from rice leaves and grains. The method involves phenol extraction to separate proteins from the non-protein components such as polysaccharides, lipids and phenolic compounds that are commonly enriched in plant tissues. Following isolation, proteins are precipitated with ammonium acetate/methanol and then solubilized for proteomic analysis. As the protocol is simple, universal, and most importantly compatible with silver staining, it has been applied to our routine protein extraction from rice and many other plant tissues and it even works fine in animal tissues for the requirement of electrophoretic separation.
[摘要] 这个协议提供了一种从稻叶和谷物制备高质量蛋白质的有效方法。 该方法包括酚提取以从通常富含植物组织的非蛋白质组分如多糖，脂质和酚类化合物中分离蛋白质。 分离后，用乙酸铵/甲醇沉淀蛋白质，然后溶解用于蛋白质组分析。 由于协议简单，通用，最重要的是与银染色兼容，它已经应用于我们从水稻和许多其他植物组织的常规蛋白质提取，甚至在动物组织中对于电泳分离的要求很好。
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| RNA-Seq Library Generation from Rare Human Cells Isolated by FACS
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Author:
Date:
2013-06-20
[Abstract] High throughput RNA Sequencing has revolutionized transcriptome analyses. However, most available protocols require micrograms of RNA rendering this technique not feasible for analyzing small numbers of cells, including precious rare cell types isolated from human tissues or organs. Here, we used an RNA Amplification System and describe a method for preparing RNA sense-strand cDNA libraries compatible with an Illumina sequencing platform starting from limited numbers of human fetal germ cells as well as human embryonic stem cells (hESCs) isolated using Fluorescence Activated Cell Sorting (FACS). With this protocol we generated seven RNA-Seq libraries starting from 4,000 germ cells sorted from fetal ovaries (n = 2) and fetal testes (n = 2) at 16-16.5 weeks of development and 4,000 sorted ...
[摘要] 高通量RNA测序革新了转录组分析。 然而，大多数可用的协议需要微克RNA，使得这种技术不可能用于分析少量的细胞，包括从人体组织或器官分离的珍贵的稀有细胞类型。 在这里，我们使用RNA扩增系统，并描述了一种制备RNA有义链cDNA文库的方法，其与Illumina测序平台相容，从有限数目的人胎儿生殖细胞以及使用荧光活化细胞分离的人胚胎干细胞（hESC） 排序（FACS）。 使用这个协议，我们生成七个RNA Seq库开始从4,000生殖细胞从胎儿卵巢（n = 2）和胎儿睾丸（n = 2）在16-16.5周的发展和4,000分选hESCs（n = 3）排序。 我们预测多重文库也可以通过用多重兼容的3'衔接子和索引的PCR引物替换这里使用的单重3'衔接子来产生。
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