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OMICS Gene Expression To gain information about transcription- al profiles at the single-cell level, investiga- tors in Dr. Fan's lab, in collaboration with researchers from the Karolinska Institute led by Sten Linnarsson, described a highly mul- tiplexed genome-wide strategy using single- cell RNA-Seq. In this protocol, ideally suited for single- cell analysis, 96 cells placed into the individ- ual wells of a 96-well plate were simultane- Continued from page 34 ously lysed. The mRNAs were converted to cDNAs, and after barcodes and primer bind- ing sequences were introduced by the tem- plate-switching activity of reverse transcrip- tase, the cDNAs were pooled and processed for 5´-end sequencing on the Illumina next- gen sequencing platform. This technique can use as little as a few picograms of starting mRNA, and is appropriate for the transcrip- tional profiling of rare cells. Dr. Fan, in a collaboration with Kun Zhang, Ph.D., at the University of Califor- nia, San Diego, is currently developing a strategy to generate a high-resolution three- dimensional map of transcriptional activities in single cells. In the past, after being iso- lated, human tissue samples were trypsinized and the resulting cell suspensions were used to examine individual cells. But during this procedure, the spatial relationship among TECH TIPS High-throughput screens help researchers better understand the regulation of gene expression as well as the role of gene deregulation in causing disease. Luchschen/ShutterStock Your solution. Choose NEBsolutions™ :: RESPONSIVENESS :: FLEXIBILITY QUALITY for your life science OEM and custom product needs. EXPERTISE Nearly 40 years of experience in enzyme technologies Dedicated team of scientists and business professionals :: Capacity to accomodate all of your formulation, scale-up and kitting needs :: Proven track record of unsurpassed product quality; ISO 13485-certified Contact us at NEBsolutions@neb.com to experience what NEBsolutions can do for you. cells from the original tissue sample was lost. "An important aspect of the technology that we are working on is the additional layer of information that it provides. It does not re- quire prior knowledge about the identity of the specific cell types and will be fundamen- tal for understanding cellular functions that shape development and disease," says Dr. Fan. While data analysis promises to be chal- lenging, and might require the development of new types of protocols, a new level of spa- tial organization that has not been available before is about to emerge. "Mapping the specific individual cells back to the three-dimensional organ or tissue is challenging, but this is the future direction into which single-cell gene expression profil- ing will develop," explains Dr. Zhang. High-Resolution 3D Map Recently, particularly with the develop- ments in the field of epigenetics, the interface between DNA methylation and gene expres- sion has become a vibrant research topic. For many years, it has been known that genes can become switched off by abnormal methylation in cancer. Subsequently, stud- ies that examined the methylome identified many genes that exhibit aberrant methyla- tion in cancer cells, when compared to their untransformed counterparts. www.neb.com NEBSolutions is a trademark of New England Biolabs, Inc. 36 | October 1, 2012 | genengnews.com | Genetic Engineering & Biotechnology News "Most of these events are probably irrele- vant and, in all likelihood, they represent the consequence of the cell being a cancer cell, just as it also happens with mutations, many of which are known to be passengers," says Peter A. Jones, Ph.D., D.Sc., distinguished professor of urology and biochemistry at the University of Southern California. While the presence of aberrant DNA methylation changes in cancer cells has be- come relatively easy to explore, a much more challenging aspect is to determine whether these methylation changes are driving the process of malignant transformation or whether their emergence is consequential to it. Dr. Jones and colleagues recently described an approach that facilitates the identification of the epigenetic driver events required for