Genetic Engineering & Biotechnology News

JAN15 2018

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10 | JANUARY 15, 2018 | | Genetic Engineering & Biotechnology News Taming the Transcriptome with RNA-Seq Richard A. Stein, Ph.D., M.D. There's a new RNA-seq in town. Although the old RNA-seq administered a certain rough justice, profiling RNA species well enough to support a relatively crude conception of the transcriptome, the new RNA-seq is more refined. Yet, like the old RNA-seq, the new RNA-seq is quick on the draw. In fact, the new RNA-seq is compatible with the newest high-throughput technologies. But the new RNA-seq is also bioinformatically up to date, capable of single-cell and single-nucleus analyses, and alert to all sorts of transcripts—even shifty splice variants, unstable pre-mRNA species, and elusive post-translational forms. The new RNA-seq, or RNA sequencing, is what research- ers and translational scientists need to develop a more so- phisticated conception of the transcriptome. RNA-seq is characterizing previously unknown cell types and recogniz- ing intermediate developmental states. It is uncovering epi- genetic modifications that culminate in cancer. And it is re- lating the maturation and decay of RNA species to processes that underlie health and disease. Getting a Bead on Single Nuclei At the Broad Institute of MIT and Harvard, scientists have developed a droplet microfluidic and DNA-barcoding tech- nique called DroNc-seq. Designed for the analysis of single nuclei, DroNc-seq combines single-nucleus RNA sequenc- ing (sNuc-seq) with Drop-seq, a technology first reported in 2015. 1 In Drop-seq, messenger RNA transcripts are profiled simultaneously from thousands of individual cells by associ- ating them with a unique barcode for each cell and partition- ing them into nanoliter-sized aqueous droplets. "When we developed DroNc-seq, we built on a huge knowledge base and transferred the droplet-microfluidics approach to the nuclei technology to achieve the next level of scale," says Naomi Habib, Ph.D., a postdoctoral fellow in laboratories led by Aviv Regev, Ph.D., and Feng Zhang, Ph.D., at the Broad Institute. Dr. Habib participated in a proof-of-concept study that used DroNc-seq to interrogate gene expression in over 39,000 nuclei from mouse and human brain samples (Figure 1). 2 "We found expression patterns that correlated very well with previous expression patterns that investigators found using more low-throughput methods," asserts Dr. Habib. In the study, DroNc-seq was able to cluster neurons of the same class originating from different anatomical regions of the brain, and it allowed different glial cell types to be dif- ferentiated from one another, despite the lower nuclear RNA content and the lower number of detected genes. DroNc-seq also captured more discrete differences between cells. For ex- ample, it distinguished between different types of GABAergic neurons that expressed different gene signatures. "As part of our work, we also presented proof of concept that we can apply our strategy to frozen, archived brain sam- ples," notes Dr. Habib. On frozen 3–5-year-old postmortem archival human tissue, and despite variations in the sample quality, DroNc-seq generated high-quality libraries from both neurons and glial cells, including some rare cell types. "This means that we can utilize frozen tissue banks to explore sam- ples at the single-cell level," suggests Dr. Habib. To accommodate the lower amount of RNA in nuclei compared to cells, the investigators found that they had to modify the Drop-seq technique. For example, the investi- gators changed the microfluidic device to generate smaller droplets and increase the efficiency of RNA capture. The technical differences between the lysing of nuclei and the lysing of cells—differences related to the distinct proper- ties of these membrane types—opened additional challenges. "This required knowledge from both the molecular biology side and the microfluidic side to be combined, to generate an optimal setup," recalls Dr. Habib. A very different type of technological challenge is that even though RNA can provide ample information about single cells, understanding the various functions of a cell requires several additional types of data to be extracted. "We would like to be able to obtain, from the same cell, knowledge about the epigen- etic state, the chromatin state, and proteins, along with other types of information, such as [the cell's] special position and its neighboring cells," declares Dr. Habib. "This is a major and fascinating challenge that people are already working on." Oncofetal Epigenetic Control "We need the most comprehensive and the most accurate and informative approach to look at gene expression, and RNA-seq provides that for many cancer types," says Gary S. Stein, Ph.D., professor and chair of the department of biochem- istry at the University of Vermont Larner College of Medicine, and director of the University of Vermont Cancer Center. Investigators in Dr. Stein's lab use RNA-seq for applica- tions such as gene-expression analysis. This particular appli- cation helps Dr. Stein's lab assess developmental processes, malignant transformations, and therapeutic responses. "RNA-seq not only provides an opportunity to look at the mRNA that encodes proteins, it also provides informa- tive about the full spectrum of transcripts, including noncod- ing RNA species such as microRNA (miRNA), transfer RNA (tRNA), toxic small RNA (tsRNA), and long noncoding RNA (lncRNA)—and we look at all of that," explains Dr. Stein. In the 1980s, Dr. Stein and colleagues cloned the human histone genes for the first time, and for the past few decades, these investigators have devoted much of their work to inter- rogating the genetic and epigenetic mechanisms of cell-cycle control that influence development and malignancy. One of the recent advances in Dr. Stein's laboratory has been the finding that the early stages of some cancers recapitulate cer- tain mitosis-specific bivalent histone modifications seen in pluripotent stem cells (PSCs). Bivalent chromatin marks, which are defined as the pres- ence of both the activating trimethylated histone 3 lysine 4 and the repressive trimethylated histone 3 lysine 27 modifi- cations at gene promoters, were described over a decade ago in PSCs. Bivalent chromatin landscapes help establish the cancer state or the pluripotent fate in cells, notes Dr. Stein, through a process he calls "oncofetal epigenetic control." Studying this process could improve the mechanistic un- derstanding of malignancies and lead to the development of novel diagnostic and therapeutic interventions. In a recent effort to identify histone modifications that oc- cur as part of differentiation programs in mesenchymal stromal cells, Dr. Stein and colleagues combined the study of several post-translational histone marks at a genome-wide level with RNA-seq. 3 This approach demonstrated the complexity and the dynamics of the gene expression programs that characterize os- teoblast differentiation from mesenchymal stromal cells. Unlike other studies of bivalent histone modification, the new study found no active mechanism of gene repression in osteoblastogenesis. Instead, the new study suggests that epigen- etic gene repression results from the loss of activation marks. "It will be important to see additional developments in bioinformatics of how to interrogate RNA-seq data," con- cludes Dr. Stein. "While there are some very good approach- es right now, they are going to get even better." Splice Variant Bioinformatic Analysis "As a bioinformatics team, we help generate novel scien- tific insights either through reanalysis of public datasets from sequencing archives or through our scientific collaborations with researchers all over the world," says Jean-Noel Billaud, Ph.D., senior principal scientist at Qiagen. Using their bioinformatics software portfolio, scientists at Qiagen extract expression profiles from RNA-seq sequenc- ing reads and send them for biological exploration to their flagship software, Ingenuity ® Pathway Analysis (IPA ® ). IPA, a software for analyzing and interpreting omics data, is widely used by academic institutions, government labora- tories, and pharmaceutical companies. "We use IPA, along with data derived from RNA-seq, microarray profiling, me- Drug Discovery Feature Justin Knight Figure 1. At the Broad Institute of MIT and Harvard, researchers Tyler Burks, Ph.D., and Naomi Habib, Ph.D., participated in a study that demonstrated the usefulness of DroNc-seq, a technology that combines single-nucleus RNA sequencing (sNuc- seq) and droplet-generating microfluidics. DroNc-seq, which puts sNuc-sec on a massively parallel basis, allowed Broad scientists to profile more than 39,000 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient, and unbiased classification of cell types. According to the scientists, DroNc-seq paves the way for systematic charting of cell atlases.

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