Project description:Genetic TNFAIP3 (A20) inactivation is a classical somatic lymphoma lesion and the genomic trait in haploinsufficiency of A20 (HA20). Single-cell sequencing reveals “pre-lymphoma” transcription signatures in lymphocytes of HA20 patients.
Project description:Single cell RNA-Seq analysis of A20 tumors indicated that the IFN1 signature was derived primarily from monocytes and T cells, not the B cell population which includes A20 tumor cells. Single cell RNA-Seq analysis characterized the effect of TAK-981 on B cells (n=4513, includes both A20 B lymphoma tumor cells and WT B cells), erythrocytes (n=238), monocytes (n=85) and T cells (n=107) from A20 tumors responding to treatment with TAK-981. Tumors were harvested 8 h after treatment of A20 tumor-bearing Balb/c mice with either vehicle or 7.5 mg/kg TAK-981 and subjected to scRNA-Seq.
Project description:Generating sufficient DNA for high-throughput genetic analysis has always been a challenge for clinical settings where the amount of source DNA is limited. Multiple displacement amplification (MDA) has been proposed as a promising candidate for such situations. Previous work with lower-resolution arrays confirmed the utility of single-cell MDA products for large-size (~30 Mb) genome variation screening. We tested the performance of single-cell MDA products on the SNP 6.0 arrays to examine the performance of single-cell MDA in SNP genotyping, copy number polymorphism, de novo copy number variation (CNV) and loss of heterozygosity (LOH) analysis. Our data show that for SNP genotyping, single-cell MDA did not obtain complete genome coverage or high sequence fidelity. For CNV calling, single-cell MDA introduced stochastic amplification artifacts in log2 ratio profiles, reducing the robustness of CNV calling; however, by adjusting smooth window size, it is still possible to analyze large chromosomal aberrations, and homozygous deletions as small as 500 kb can still be identified from the noisy log2 ratio profiles. Our results also suggest that even with a modified protocol (reduction of reaction volume, addition of a molecular crowding reagent, minimization of reaction time), single-cell MDA presented little improvement over the unmodified protocol, but by increasing the number of cells as template to 5M-bM-^@M-^S10 cells, SNP 6.0 array results comparable to those of 10 ng genomic DNA MDA could be obtained. Algorithms like PICNIC improved the CNV calling, suggesting that better algorithms can better utilize single-cell MDA array results. Affymetrix SNP arrays were performed according to the manufacturer's directions on DNA extracted from cell line samples, and multiple displacement samples. Genotyping, Copy number and LOH analysis of Affymetrix SNP 6.0 arrays was performed for 3 samples of unamplified cell line genomic DNA, 2 samples of DNA obtained by multiple displacement amplification from 10ng genomic DNA, 3 single-cell multiple displacement amplification (MDA) products, single cell modified MDA amplification product, 5-cell modified MDA amplification product, 10-cell modified MDA amplification product.
Project description:Test data used for the evaluation of ESAT performance and results files for data from 3' and 5' end-sequencing RNA-Seq protocols and droplet-based single-cell RNA-Seq. Quantification and analysis of Tophat-aligned (v2.0.9) samples from mouse bone-marrow derived dendritic cells (mBMDC) timecourse (0, 2, 4 and 6 hours) post LPS stimulation and non-diabetic BBDR rat pancreatic islet cells. Since end-sequencing (3' or 5') is used for all samples, alignments are only required for the R2 (sequence-containing) read.
Project description:Droplet-based single cell transcriptome sequencing (scRNA-seq) technology is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data, which will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries.
Project description:DNA barcodes can be used to identify single cells in a sequencing data space while optical codes can be used to track single live cells in an image data space. We have developed dual image and DNA (ID)-coding, which identifies individual single cells in both live image and sequencing data spaces. Samples provided here are relevant to proof-of-concept studies of ID-coding presented in the associated publication. DNA barcoded micro-particles were encapsulated in hydrogel droplets with or without single cells. The hydrogel droplets were then subjected to “single-droplet sequencing” where whole polyA-bearing nucleic acid components within a hydrogel droplet (i.e. mRNA from cells and synthetic DNA on beads) were concatenated by the same cell barcodes.
