Project description:Smart-seq3xpress was carefully optimized and >1,000 conditions were evaluated. This data submission is organized in 15 datasets that each contain fastq files, unmapped bam files, read count tables, UMI count tables and a barcode annotation file. The barcode_annotation.txt files contain the exact factors/variables tested. Below a short description of each set of experiments: K562_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was K562 cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. HEK_lowvolume: Evaluation of scaling volumes of Smart-seq3 (indicated volume refers to total volume in PCR), whether overlay was used and if cDNA was bead-cleaned or diluted prior to tagmentation. Cell input was HEK293FT cells. The columns \\"treatment\\", \\"volume\\" and \\"VL\\" indicate the experimental parameters. overlays: Evaluation of the effect of various overlays when generating HEK293FT libraries in 1 uL total volume. The column \\"condition\\" indicates the applied overlay. tagmentations: Evaluation of input cDNA vs Tn5 amount during tagmentation. Purified cDNA from one 384-well plate was used as input into various conditions of tagmentations. The experiments contain evaluation of cDNA amount with fixed Tn5 amount or varying Tn5 amount while keeping the default volume (2 uL) of the tagmentation reaction or scaling the reaction volume. The column \\"condition\\" contains a string indicating reaction volume, cDNA input and Tn5 ATM enzyme amount. If no volume is indicated, reaction was performed in 2 uL. HomeTn5: Evaluation of tagmentation using in-house produced Tn5 enzyme (Picelli et al., 2015) when tagmenting cDNA generated from HEK293FT cells in 1 uL total volume. The column \\"Tn5concentration\\" indicates the Tn5 reaction concentration at 2 uL reaction volume. cycles_cleanups: Optimization of Smart-seq3xpress (column \\"experiment\\" shows \\"direct_tag\\") in regards to clean-ups after cDNA synthesis (column \\"condition\\": noclean, Exo+FastAP, ExoSAP) and dilution volume (9 or 19 uL); PCR cycle numbers (column \\"pcr_input\\") and ATM Tn5 enzyme amount (column \\"ATM\\"). Cell input was HEK293FT cells. PreAmp_Polymerase: Evaluation of various PCR polymerases during initial cDNA amplification. The polymerases are indicated in column \\"polymerase\\". We also evaluated several TSO concentrations (concentration in RT is given) and fwd/rev PCR primers (concentration given in PCR reaction). Cell input was HEK293FT cells. TDE1: Large optimization of tagmentation conditions using the TDE1 Tn5 enzyme. We varied reactions by changing PCR polymerase (KAPA / SeqAmp), PCR extension time and the number of PCR cycles during cDNA amplification. During tagmentation, we varied the amount of TDE1 enzyme, the amount of DMF in the tagmentation reaction buffer and the presence of Tween-20 in the final post-tagmentation PCR. Cell input was HEK293FT cells. TSOs_RT_v1-7: Large scale evaluation of conditions relating to RT and PCR, with a focus on new template-switching oligo (TSO) designs. In total, >20,000 cells and >500 conditions are contained in these datasets. The barcode annotation file contains precise information on the reaction conditions of Lysis, RT, PCR as well as utilized TSO designs. Data was generated from HEK293FT cells and hPBMC (Lonza).
Project description:Plate-based single-cell RNA-sequencing methods with full-transcript coverage typically excel at sensitivity but are more resource and time-consuming. Using miniaturized and streamlined Smart-seq3xpress protocol, we sequence >26,000 human peripheral blood mononuclear cells to generate a highly granular gene- and isoform-level atlas.
Project description:We want to investigate how cells in the specific zones in murine liver are affected by age-related changes of the microenvironment. To this end, we generated high-quality scRNA-seq dataset of hepatocytes using Smart-seq3express from 2 young (3-5 months) and 2 old (18-20 months) male mice. Livers were perfused and viable hepatocytes were FACS-sorted based on size. In addition, we recorded ploidy levels of hepatocytes. We retained 545 hepatocytes in total after initial filtering.
Project description:Individual HEK cells were dispensed using an F.SIGHT into individual wells while recording cell diameters. Each well contained 0.0321 pg of molecular spike-ins, a highly complex set of 264 molecular spikes, based on 11 unique spike sequences spanning different lengths (570 to 3070 nts) and GC contents (40-60%). Libraries were generated with Smart-seq3xpress protocol.
Project description:To study cancer cells heterogeneity at the single cell level we grew cancer cells as spheroids and extracted their RNA preform SmartSeq3xpress. We grew MDA-MB-231 cells on agar coated plates for 5-10 days in DMEM 10% FBS. The spheroids were incubated for 2 hours with Calcein AM and Vybrant Dye 10uM at 37C and washed twice with PBS. After dissociation with trypsinLE 0.25% the cells were facs sorted and the fluorescence intensity for each cell was recorded. The RNA were extracted and the cDNA libraries were built according to the SmartSeq3xpress protocol.
Project description:Single-cell RNA-sequencing (scRNAseq) is revolutionizing biomedicine, propelled by advances in methodology, ease of use, and cost reduction of library preparation. Over the past decade, there have been remarkable technical improvements in most aspects of single-cell transcriptomics. Yet, there has been little to no progress in advancing RNase inhibition despite that maintained RNA integrity is critical during cell collection, storage, and cDNA library generation. Here, we demonstrate that a synthetic thermostable RNase inhibitor yield single-cell libraries of equal or superior quality compared to ubiquitously used protein-based recombinant RNase inhibitors (RRIs). Importantly, the synthetic RNase inhibitor provide additional unique improvements in reproducibility and throughput, enable new experimental workflows including heat cycles, and can reduce the need for dry-ice transports. In summary, replacing RRIs represents a substantial advancement in the field of single-cell transcriptomics.
Project description:A highly complex set of 264 molecular spikes, based on 11 unique spike sequences spanning different lengths (570 to 3070 nts) and GC contents (40-60%) was designed. In order to be able to precisely evaluate quantification over different expression levels, transcript lengths and GC contents, barcodes of 7 nucleotides in 2-fold abundance steps were cloned into each spike sequence (12 steps in duplicates; 24 barcodes per sequence) creating a standard curve for each spike sequence. To determine the molecular abundance of each of the 264 molecular spike-ins (i.e., the ‘ground truth’), we performed an exhaustive sequencing across the spike barcodes and spUMIs and determined the total complexity in the pool to be 76 million unique molecules
Project description:An increasing number of long non-coding RNAs (lncRNAs) have confirmed important functions, yet little is known about their transcriptional dynamics and it remains challenging to determine their regulatory functions. Here, allele-sensitive single-cell RNA-seq was used to demonstrate that lncRNAs have lower burst frequencies compared to mRNAs. We observed an increased cell-to-cell variability in lncRNA expression that was due to more sporadic bursting (lower frequency) with larger numbers of RNA molecules being produced. Exploiting heterogeneity in asynchronously growing cells, we identified and experimentally validated lncRNAs with cell-state specific functions involved in cell cycle progression and apoptosis. Finally, we identified cis-functioning lncRNAs and knockdown of these lncRNAs modulated either transcriptional burst frequency or size of the nearby protein-coding gene. Collectively, we identify distinct transcriptional regulation of lncRNAs and we demonstrate a role for lncRNAs in the regulation of transcriptional bursting of mRNAs.
Project description:Allele-sensitive RNA sequencing of single-cells can be used to infer the kinetics of transcriptional bursts in eukaryotic cells. Here, we used the Smart-seq3 protocol to prepare libraries from two 384-well plates of primary mouse fibroblasts. The fibroblasts were derived from tail explants of a male adult mouse (F1 offspring of C57 x CAST cross). The samples were sequenced to high depth using MGI's DNBSEQ G400RS platform using paired-end 100 bp reads.
Project description:Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.