Project description:Sample multiplexed scRNA-seq is a promising strategy to overcome current barriers in high cost and potential technical variations by multiple scRNA-seq tests. In this study, we developed a highly efficienct novel sample barcode labeling method using DNA-encoded Lipid Nanoparticles ('Nanocoding') that could label cells with minimal dependence on their type or sample conditions. This method provids a roubust and general protocol for sample barcoding and multiplexing in scRNA-seq. We demonstrated the performance of Nanocoding through three scRNA-seq studies, which include: 1. mouse spleen cells mix (one dataset including 6 mouse spleen tissues samples); 2. HeLa-mouse Stromal Vascular Fraction(SVF) cells mix (one dataset containing mixed HeLa cell and SVF cell); 3. Aged-Young SVF cells mix (one dataset containing two SVF samples) tests. These studies showcased the biomodal distribution of barcode counts in different models with high signal-to-background ratio, as well as pan-cell labeling activity for efficient and accurate sample-multiplexing. By using Nanocoding, we profiled obsity and age related change in lipid metabolism associated genes or inflammatory related features, in various cell types from spleen or adipose tissues.
Project description:Considerable variation in gene expression data from different DNA microarray platforms has been demonstrated. However, no characterization of the source of variation arising from labeling protocols has been performed. To analyze the variation associated with T7-based RNA amplification/labeling methods, aliquots of the Stratagene Human Universal Reference RNA were labeled using 3 eukaryotic target preparation methods and hybridized to a single array type (Affymetrix U95Av2). Variability was measured in yield and size distribution of labeled products, as well as in the gene expression results. All methods showed a shift in cRNA size distribution, when compared to un-amplified mRNA, with a significant increase in short transcripts for methods with long IVT reactions. Intra-method reproducibility showed correlation coefficients >0.99, while inter-method comparisons showed coefficients ranging from 0.94 to 0.98 and a nearly two-fold increase in coefficient of variation. Fold amplification for each method was positively correlated with the number of present genes. Two factors that introduced significant bias in gene expression data were observed: a) number of labeled nucleotides that introduces sequence dependent bias, and b) the length of the IVT reaction that introduces a transcript size dependent bias. This study provides evidence of amplification method dependent biases in gene expression data. Keywords: method validation study
Project description:To characterize the properties and evaluate the performance of the TAcKLE procedure, a novel method providing effective transcriptome amplification for expression analyses on oligonucleotide microarrays, we performed 20 two-color hybridizations using self-spotted Operon 27k arrays. A single source of universal human reference RNA (pooled from 10 cell lines) and RNA extracted from healthy breast tissue was used for all experiments to avoid differences in transcript abundance imposed by the RNA preparation. RNA was either amplified by one or two rounds of linear isothermal RNA amplification (starting from 2000 ng, 200 ng, 20 ng or 2 ng), followed by Cy-dUTP incorporation using Klenow fragment, or labeled directly by reverse transcription of 40 µg RNA with Cy-dUTP. For all quantities of starting material, one co-hybridization of reference RNA, two hybridizations of breast versus reference RNA as well as one hybridization of reference versus breast RNA were performed. In case of amplified RNA, all dye labeling reactions were made from distinct target preparations. Hybridizations were performed for 16 h at 42 °C in a GeneTAC Hybridization Station (Genomic Solutions) using UltraHyb hybridization buffer (Ambion). Hybridized microarrays were scanned at 5 µm resolution on a GenePix 4000B microarray scanner (Axon Instruments). For all hybridizations, raw signal intensities were normalized applying variance stabilization (W. Huber et al., Bioinformatics 18 Suppl 1, 2002). Keywords = amplification Keywords = labeling Keywords = protocol Keywords = spotted Keywords = human Keywords = long oligonucleotide Keywords = oligo Keywords = 70mer Keywords = Operon Keywords: other