Comparative evaluation of linear and exponential amplification techniques for expression profiling at the single-cell level

Background: Single-cell microarray expression profiling requires 10(8)-10(9)-fold amplification of the picogram amounts of total RNA typically found in eukaryotic cells. Several methods for RNA amplification are in general use, but little consideration has been given to the comparative analysis of those methods in terms of the overall validity of the data generated when amplifying from single-cell amounts of RNA, rather than their empirical performance in single studies.|Results: We tested the performance of three methods for amplifying single-cell amounts of RNA under ideal conditions: T7-based in vitro transcription; switching mechanism at 5' end of RNA template ( SMART) PCR amplification; and global PCR amplification. All methods introduced amplification-dependent noise when mRNA was amplified 10(8)-fold, compared with data from unamplified cDNA. PCR-amplified cDNA demonstrated the smallest number of differences between two parallel replicate samples and the best correlation between independent amplifications from the same cell type, with SMART outperforming global PCR amplification. SMART had the highest true-positive rate and the lowest false-positive rate when comparing expression between two different cell types, but had the lowest absolute discovery rate of all three methods. Direct comparison of the performance of SMART and global PCR amplification on single-cell amounts of total RNA and on single neural stem cells confirmed these findings.|Conclusion: Under the conditions tested, PCR amplification was more reliable than linear amplification for detecting true expression differences between samples. SMART amplification had a higher true-positive rate than global amplification, but at the expense of a considerably lower absolute discovery rate and a systematic compression of observed expression ratios

A systems biology approach uncovers the core gene regulatory network governing iridophore fate choice from the neural crest.

Multipotent neural crest (NC) progenitors generate an astonishing array of derivatives, including neuronal, skeletal components and pigment cells (chromatophores), but the molecular mechanisms allowing balanced selection of each fate remain unknown. In zebrafish, melanocytes, iridophores and xanthophores, the three chromatophore lineages, are thought to share progenitors and so lend themselves to investigating the complex gene regulatory networks (GRNs) underlying fate segregation of NC progenitors. Although the core GRN governing melanocyte specification has been previously established, those guiding iridophore and xanthophore development remain elusive. Here we focus on the iridophore GRN, where mutant phenotypes identify the transcription factors Sox10, Tfec and Mitfa and the receptor tyrosine kinase, Ltk, as key players. Here we present expression data, as well as loss and gain of function results, guiding the derivation of an initial iridophore specification GRN. Moreover, we use an iterative process of mathematical modelling, supplemented with a Monte Carlo screening algorithm suited to the qualitative nature of the experimental data, to allow for rigorous predictive exploration of the GRN dynamics. Predictions were experimentally evaluated and testable hypotheses were derived to construct an improved version of the GRN, which we showed produced outputs consistent with experimentally observed gene expression dynamics. Our study reveals multiple important regulatory features, notably a sox10-dependent positive feedback loop between tfec and ltk driving iridophore specification; the molecular basis of sox10 maintenance throughout iridophore development; and the cooperation between sox10 and tfec in driving expression of pnp4a, a key differentiation gene. We also assess a candidate repressor of mitfa, a melanocyte-specific target of sox10. Surprisingly, our data challenge the reported role of Foxd3, an established mitfa repressor, in iridophore regulation. Our study builds upon our previous systems biology approach, by incorporating physiologically-relevant parameter values and rigorous evaluation of parameter values within a qualitative data framework, to establish for the first time the core GRN guiding specification of the iridophore lineage

Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions

Accurate Expression Profiling of Very Small Cell Populations

BACKGROUND: Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because available cell numbers are limited. Currently available alternative methods for expression profiling from nanograms of RNA or from very small cell populations lack a broad validation of results to provide accurate information about the measured transcripts. METHODS AND FINDINGS: We provide evidence that currently available methods for expression profiling of very small cell populations are prone to technical noise and therefore cannot be used efficiently as discovery tools. Furthermore, we present Pico Profiling, a new expression profiling method from as few as ten cells, and we show that this approach is as informative as standard techniques from thousands to millions of cells. The central component of Pico Profiling is Whole Transcriptome Amplification (WTA), which generates expression profiles that are highly comparable to those produced by others, at different times, by standard protocols or by Real-time PCR. We provide a complete workflow from RNA isolation to analysis of expression profiles. CONCLUSIONS: Pico Profiling, as presented here, allows generating an accurate expression profile from cell populations as small as ten cells

The Polycomb Protein and E3 Ubiquitin Ligase Ring1B Harbors an IRES in its Highly Conserved 5′ UTR

Ring1B is an essential member of the highly conserved Polycomb group proteins, which orchestrate developmental processes, cell growth and stem cell fate by modifying local chromatin structure. Ring1B was found to be the E3 ligase that monoubiquitinates histone H2A, which adds a new level of chromatin modification to Polycomb group proteins. Here we report that Ring1B belongs to the exclusive group of proteins that for their translation depend on a stable 5′ UTR sequence in their mRNA known as an Internal Ribosome Entry Site (IRES). In cell transfection assays the Ring1B IRES confers significantly higher expression levels of Ring1B than a Ring1B cDNA without the IRES. Also, dual luciferase assays show strong activity of the Ring1B IRES. Although our findings indicate Ring1B can be translated under conditions where cap-dependent translation is impaired, we found the Ring1B IRES to be cap-dependent. This raises the possibility that translational control of Ring1B is a multi-layered process and that translation of Ring1B needs to be maintained under varying conditions, which is in line with its essential role as an E3 ligase for monoubiquitination of histone H2A in the PRC1 Polycomb protein complex

Highly Parallel Genome-Wide Expression Analysis of Single Mammalian Cells

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology

Transcriptomic Analysis of the Salivary Glands of an Invasive Whitefly

<div><h3>Background</h3><p>Some species of the whitefly <em>Bemisia tabaci</em> complex cause tremendous losses to crops worldwide through feeding directly and virus transmission indirectly. The primary salivary glands of whiteflies are critical for their feeding and virus transmission. However, partly due to their tiny size, research on whitefly salivary glands is limited and our knowledge on these glands is scarce.</p> <h3>Methodology/Principal Findings</h3><p>We sequenced the transcriptome of the primary salivary glands of the Mediterranean species of <em>B. tabaci</em> complex using an effective cDNA amplification method in combination with short read sequencing (Illumina). In a single run, we obtained 13,615 unigenes. The quantity of the unigenes obtained from the salivary glands of the whitefly is at least four folds of the salivary gland genes from other plant-sucking insects. To reveal the functions of the primary glands, sequence similarity search and comparisons with the whole transcriptome of the whitefly were performed. The results demonstrated that the genes related to metabolism and transport were significantly enriched in the primary salivary glands. Furthermore, we found that a number of highly expressed genes in the salivary glands might be involved in secretory protein processing, secretion and virus transmission. To identify potential proteins of whitefly saliva, the translated unigenes were put into secretory protein prediction. Finally, 295 genes were predicted to encode secretory proteins and some of them might play important roles in whitefly feeding.</p> <h3>Conclusions/Significance:</h3><p>The combined method of cDNA amplification, Illumina sequencing and <em>de novo</em> assembly is suitable for transcriptomic analysis of tiny organs in insects. Through analysis of the transcriptome, genomic features of the primary salivary glands were dissected and biologically important proteins, especially secreted proteins, were predicted. Our findings provide substantial sequence information for the primary salivary glands of whiteflies and will be the basis for future studies on whitefly-plant interactions and virus transmission.</p> </div

Fluorescence-Activated Cell Sorting and NanoString Profiling of Single Neural Crest Cells and Pigment Cells

Neural crest cells are an important class of multipotent stem cells, generating highly diverse derivatives. Understanding the gene regulatory networks underlying this process is of great interest, but the highly migratory and thus widely dispersed nature of the differentiating cells makes isolation of cells difficult. Fluorescence-activated cell sorting (FACS) of transgenically labelled neural crest-derived cells after disaggregation of embryos is well-suited to purifying these cells. However, their diverse differentiation means that transcriptional analysis at single cell resolution is necessary to dissect the gene regulatory networks at play. NanoString technology provides a method for highly sensitive, quantitative transcriptional profiling for a pre-defined set of genes of interest. Here we provide a detailed protocol for FACS purification of neural crest-derived cells, sorted as single cells into a multi-well plate, and their subsequent NanoString profiling, using a predetermined gene set focused on pigment cells