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

Modelling and measuring single cell RNA expression levels find considerable transcriptional differences among phenotypically identical cells.

BACKGROUND: Phenotypically identical cells demonstrate predictable, robust behaviours. However, there is uncertainty as to whether phenotypically identical cells are equally similar at the underlying transcriptional level or if cellular systems are inherently noisy. To answer this question, it is essential to distinguish between technical noise and true variation in transcript levels. A critical issue is the contribution of sampling effects, introduced by the requirement to globally amplify the single cell mRNA population, to observed measurements of relative transcript abundance. RESULTS: We used single cell microarray data to develop simple mathematical models, ran Monte Carlo simulations of the impact of technical and sampling effects on single cell expression data, and compared these with experimental microarray data generated from single embryonic neural stem cells in vivo. We show that the actual distribution of measured gene expression ratios for pairs of neural stem cells is much broader than that predicted from our sampling effect model. CONCLUSION: Our results confirm that significant differences in gene expression levels exist between phenotypically identical cells in vivo, and that these differences exceed any noise contribution from global mRNA amplification.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Exploring future opportunities and challenges of Demand Side Management with Agent Based Modelling

Electricity systems worldwide are transforming in-line with the global decarbonisation goals. On the supply side, renewable energy resources are replacing fossil fuels which introduces uncertainty in electricity generation. On the demand side, heating and transport electrification coupled with continuous integration of small scale renewables and energy storage are transforming the interactions between consumers and generators. These changes are raising new challenges for system operators in terms of balancing electricity in the grid. Demand-side management (DSM), whereby electricity consumption is coordinated with variable supply from renewables, has been shown to offer a promising solution to the above problem. However, the extent to which the future impact of DSM has been holistically assessed is arguable. Current model-based assessment of DSM primarily focuses on its benefits, ignoring the potential challenges since the testing tends to be carried out in an isolated and idealistic setting. This work proposes a model for Electricity System Management using an Agent based approach (or ESMA), which includes heterogeneous consumers, aggregators, the system operator, and market. The main feature of the model is its capability to simulate different regimes of DSM: decentralised (performed by consumers), semi-centralised (performed by aggregators), and centralised (performed by the system operator). The impact of each DSM regime is assessed in terms system costs, greenhouse gas emissions and consumer bills in the context of the British electricity system for 2015-2050. It is found that a trade-off exists between consumer autonomy and system optimality with regards to DSM. It is argued that the level of information sharing between consumers and the system can be minimised, as better learning and predicting algorithms are developed. The thesis is concluded with a discussion on the potential consumer tariff structure which would reward consumer flexibility

Silencing of Transgene Expression: A Gene Therapy Perspective

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Evaluating consumer investments in distributed energy technologies

The adoption of solar photovoltaic and electrical energy storage by end users depends on their economic attractiveness, which is typically assessed with metrics of future cash flow such as Net Present Value (NPV). Yet analyses using NPV typically do not account for the evolution towards low-carbon electricity systems in the short and long term. We show this to be of critical importance for accurately calculating the profitability of these technologies. By linking an energy system model with a power system model, we observe substantial differences between NPV estimates calculated with and without representing potential evolutions of the electricity system. Our results suggest that not accounting for short- and long-run changes in the electricity system could underestimate the NPV of an investment in photovoltaic and storage by around 20%, especially in scenarios with high levels of renewables, moderate flexibility, and high electrification in the energy system. Using system-dependent cash flow metrics can have a major impact on end-users' energy technology profitability

Evaluating consumer investments in distributed energy technologies

The adoption of solar photovoltaic and electrical energy storage by end users depends on their economic attractiveness, which is typically assessed with metrics of future cash flow such as Net Present Value (NPV). Yet analyses using NPV typically do not account for the evolution towards low-carbon electricity systems in the short and long term. We show this to be of critical importance for accurately calculating the profitability of these technologies. By linking an energy system model with a power system model, we observe substantial differences between NPV estimates calculated with and without representing potential evolutions of the electricity system. Our results suggest that not accounting for short- and long-run changes in the electricity system could underestimate the NPV of an investment in photovoltaic and storage by around 20%, especially in scenarios with high levels of renewables, moderate flexibility, and high electrification in the energy system. Using system-dependent cash flow metrics can have a major impact on end-users' energy technology profitability

Grouping and Classifying Electrophysiologically-Defined Classes of Neocortical Neurons by Single Cell, Whole-Genome Expression Profiling

The diversity of neuronal cell types and how to classify them are perennial questions in neuroscience. The advent of global gene expression analysis raised the possibility that comprehensive transcription profiling will resolve neuronal cell types into groups that reflect some or all aspects of their phenotype. This approach has been successfully used to compare gene expression between groups of neurons defined by a common property. Here we extend this approach to ask whether single neuron gene expression profiling can prospectively resolve neuronal subtypes into groups, independent of any phenotypic information, and whether those groups reflect meaningful biological properties of those neurons. We applied methods we have developed to compare gene expression among single neural stem cells to study global gene expression in 18 randomly picked neurons from layer II/III of the early postnatal mouse neocortex. Cells were selected by morphology and by firing characteristics and electrical properties, enabling the definition of each cell as either fast- or regular-spiking, corresponding to a class of inhibitory interneurons or excitatory pyramidal cells. Unsupervised clustering of young neurons by global gene expression resolved the cells into two groups and those broadly corresponded with the two groups of fast- and regular-spiking neurons. Clustering of the entire, diverse group of 18 neurons of different developmental stages also successfully grouped neurons in accordance with the electrophysiological phenotypes, but with more cells misassigned among groups. Genes specifically enriched in regular spiking neurons were identified from the young neuron expression dataset. These results provide a proof of principle that single-cell gene expression profiling may be used to group and classify neurons in a manner reflecting their known biological properties and may be used to identify cell-specific transcripts

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

Case report of sclerochoroidal calcification

Background. Sclerochoroidal calcification is an idiopathic rare benign lesion of the sclera or choroid characterized by histological deposition of calcium pyrophosphate. Taking into consideration its similar clinical manifestations with other diseases of the sclera, the most dangerous of which are malignant, timely verification of the diagnosis with the appointment of a further observation period is important.The aim. The description of a clinical case of sclerochoroidal calcification to improve the efficiency of disease detection through the use of multimodal diagnostics.Material and methods. A 62-year-old patient with complaints of “bright flashes” in her left eye for the past few months, who underwent a standard complex of ophthalmological examinations, supplemented according to indications by optical coherence tomography of peripapillary nerve fibers, macular zone, B-scan, Dopplerography in color Doppler mapping mode. Auxiliary diagnostic methods were magnetic resonance imaging of the orbits and extraocular muscles, computed tomography of the orbits and a biochemical blood test.Results. Considering the anamnesis, the absence of progression of complaints, the data of instrumental diagnostic methods, the absence of pathological blood flow in the area of both eyes formations, the correct diagnosis is most likely to be sclerochoroidal calcification of both eyes, despite the difficulties of the diagnostic process, which consisted in the absence of visualization of foci during ophthalmoscopy. Conclusion. Sclerochoroidal calcification is of interest to practicing ophthalmologists due to the difficulties of diagnostic search and differential diagnosis with malignant neoplasms. Modern medicine has a sufficient set of instrumental and laboratory research methods for making an accurate diagnosis