Rhapsody

Manufactured by BD

The BD Rhapsody is a single-cell analysis system designed for high-throughput, multi-omic profiling of individual cells. It enables the isolation, processing, and molecular analysis of single cells to gain insights into cellular heterogeneity and function.

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Lab products found in correlation

Novaseq 6000 sequencer, by Illumina (3 mentions) Rhapsody analysis pipeline, by BD (3 mentions) Rhapsody whole transcriptome analysis amplification kit, by BD (3 mentions) Novaseq platform, by Illumina (2 mentions) Human single cell multiplexing kit, by BD (1 mentions) Rhapsody targeted mrna abseq amplification kit, by BD (1 mentions) Rhapsody cdna kit, by BD (1 mentions) Liberase, by Roche (1 mentions) Novaseq s4 200 cycles v1.5 kit, by Illumina (1 mentions) Percoll plus, by Cytiva (1 mentions) Nextseq platform, by Illumina (1 mentions) Rhapsody single cell analysis system, by BD (1 mentions) Hiseq 4000 sequencer, by Illumina (1 mentions) High sensitivity dna chip, by Agilent Technologies (1 mentions) Qubit high sensitivity dna analysis, by Thermo Fisher Scientific (1 mentions) Bioanalyzer 2200, by Thermo Fisher Scientific (1 mentions) Rhapsody system, by BD (1 mentions) Hiseq 3000, by Illumina (1 mentions) Rhapsody pipeline, by BD (1 mentions) Rhapsody cartridge, by BD (1 mentions)

Spelling variants of this product

BD Rhapsody system (19 citations) BD Rhapsody cDNA Kit (14 citations) BD Rhapsody Scanner (10 citations) BD Rhapsody Targeted Analysis Pipeline (5 citations) BD Rhapsody WTA Amplification Kit (5 citations) BD Rhapsody platform (4 citations) BD Rhapsody analysis system (3 citations) BD Rhapsody Express system (3 citations) BD Rhapsody Targeted mRNA and AbSeq Amplification Kit (3 citations) BD Rhapsody Immune Response Targeted Panel for Human (2 citations)

17 protocols using rhapsody

Correcting Background Noise in scRNA-seq

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To reduce background read counts of each gene that were possibly derived from RNA diffusion during cell lysis step within BD Rhapsody cartridge and reverse transcription, we performed distribution-based error correction (DBEC) that is included in BD Rhapsody targeted scRNA-seq workflow. To estimate background and signal read count distribution, we used the Gaussian mixture model previously used to estimate the gene-expression distribution of scRNA-seq datasets^{50 (link)}. First, genes of which log₂(x + 1)-transformed maximum expression over 8 were selected, and biexponential transformation was applied to each gene count by using FlowTrans package⁵¹ in R-4.1.2. Next, Gaussian mixture components (model E, from one to three components) were detected using mclust package^{52 (link)} in R-4.1.2, and the average expression of each component was calculated. Genes of which the maximum average expression of each component was over 5.5 (for shallow-sequenced data) or over 6 (for deep-sequenced data) were selected. Then, if the difference of the average expression of each component against their maximum expression was greater than 5 (for shallow-sequenced data) or over 5.5 (for deep-sequenced data), the expression level of the components was considered to be background gene expression and converted expression of the components to 0.

Shichino S., Ueha S., Hashimoto S., Ogawa T., Aoki H., Wu B., Chen C.Y., Kitabatake M., Ouji-Sageshima N., Sawabata N., Kawaguchi T., Okayama T., Sugihara E., Hontsu S., Ito T., Iwata Y., Wada T., Ikeo K., Sato T.A, & Matsushima K. (2022). TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq. Communications Biology, 5, 602.

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Single-Cell Multiplexing and Sequencing

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All PBMC samples were thawed on the same day and loaded onto a BD Rhapsody cartridge. The cell concentration and viability were determined using a BD Rhapsody™ scanner (BD Biosciences). Then, the cells of each sample were labelled with Human Single-Cell Multiplexing Kit (BD Biosciences Cat# 633,781), which utilizes cell-hashing technology for single-cell library preparation and sequencing. Pooled samples were loaded into a BD Rhapsody microwell cartridge. After lysing the cells with lysis buffer, cell capture beads were retrieved and washed. Microbead-captured single-cell transcriptomes and SampleTag molecules were generated in a cDNA library. The SampleTag library contains cell labels and unique molecular identifiers (UMI) information. The procedures were performed using the BD Rhapsody cDNA Kit (BD Biosciences Cat# 633,773) and BD Rhapsody Targeted mRNA & AbSeq Amplification Kit (BD Biosciences Cat#. 633,801). Libraries were sequenced in the PE150 mode.

Tu X., Chen L., Zheng Y., Mu C., Zhang Z., Wang F., Ren Y., Duan Y., Zhang H., Tong Z., Liu L., Sun X., Zhao P., Wang L., Feng X., Fang W, & Liu X. (2024). S100A9+CD14+ monocytes contribute to anti-PD-1 immunotherapy resistance in advanced hepatocellular carcinoma by attenuating T cell-mediated antitumor function. Journal of Experimental & Clinical Cancer Research : CR, 43, 72.

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Single-Cell RNA-seq Analysis of Mouse Ears

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For single-cell RNA-seq analysis, excised ears were cut into small pieces by using razors, and incubated with Liberase TM (0.25 mg/mL; Roche) in RPMI complete medium at 37 °C for 50 min. After the removal of dead cells and red blood cells through density separation with 25% and 65% Percoll PLUS (Cytiva), isolated cells were incubated with TotalSeq anti-mouse Hashtag-A antibodies [BioLegend, clone: M1/42, 30-F11, dilution 1:400; Hashtag antibody A0311 (catalog #: 155821), A0312 (catalog #: 155823), A0313 (catalog#: 155825) and A0314 (catalog #: 155827)]. Ten thousand labeled cells (approximately 2,500 cells for each condition) were trapped and reverse-transcribed using BD Rhapsody (BD) according to the manufacturer’s instructions, followed by the preparation of cDNA libraries and hashtag libraries by TAS-Seq method^{50 (link)}. The sequencing analysis was conducted by ImmunoGeneTeqs, Inc by using Novaseq 6000 sequencer (Illumina) and Novaseq S4 200 cycles v1.5 kit (Illumina, catalog #: 20028313).

Miyake K., Ito J., Takahashi K., Nakabayashi J., Brombacher F., Shichino S., Yoshikawa S., Miyake S, & Karasuyama H. (2024). Single-cell transcriptomics identifies the differentiation trajectory from inflammatory monocytes to pro-resolving macrophages in a mouse skin allergy model. Nature Communications, 15, 1666.

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Single-cell RNA-seq of FGF21-treated mice

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FACS isolated cells were then loaded on the BD Rhapsody where capture of the single cells was performed per manufacturer instructions. Following lysis of the cells and capture of mRNA on oligonucleotide barcoded beads the cDNA synthesis was performed and cDNA libraries with Illumina sequencing adapters were generated per manufacturer instructions using the BD Rhapsody whole transcriptome analysis amplification kit. cDNA libraries were then sequenced on Illumina NovaSeq 6000 sequencers at the University of Iowa Genomics Core. Sequencing data was then quality filtered and annotated using the BD Rhapsody analysis pipeline while also correcting for artifacts which arise during library construction. Filtered and annotated data from vehicle and FGF21 treated mice were then normalized in the R package Seurat. Imputation was performed using the Seurat Wrapper ALRA on the normalized dataset before final clustering (clustering resolution was set at 0.5 based on the number of cells sequenced) and gene expression analysis to account for dropout associated with 3′-barcoding-based approaches. “Cell type” classification of the clusters was determined based on expression of previously identified marker genes (mousebrain.org) for neuronal and non-neuronal cell types.

Zhou B., Claflin K.E., Flippo K.H., Sullivan A.I., Asghari A., Tadinada S.M., Jensen-Cody S.O., Abel T, & Potthoff M.J. (2022). Central FGF21 production regulates memory but not peripheral metabolism. Cell reports, 40(8), 111239.

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Single-cell Transcriptomics of PTC

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We performed single-cell RNA-sequencing (scRNA-seq) based on BD Rhapsody and characterized the first single-cell transcriptomic landscape of PTC involving gender. Single-cell libraries were prepared using the BD Rhapsody Single-Cell Analysis System (BD, USA), according to the manufacturer’s protocol. Libraries were sequenced using multiple runs on an Illumina NextSeq platform. The differential cell clusters and their gene profiles were identified and analyzed via a multi-resolution network in male and female patients. The interactions of fibroblasts and endothelial cells with malignant epithelial cells and the difference in the immune infiltration of B as well as T lymphocytes according to gender were assessed.

Peng M., Wei G., Zhang Y., Li H., Lai Y., Guo Y., Chen Y., Liu L., Xiao H., Guan H, & Li Y. (2021). Single‐cell transcriptomic landscape reveals the differences in cell differentiation and immune microenvironment of papillary thyroid carcinoma between genders. Cell & Bioscience, 11, 39.

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Single-cell Transcriptome and Antibody Capture

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Single-cell capture was achieved by Poisson distribution of a single-cell suspension across >200,000 microwells (BD Rhapsody™). Beads with oligonucleotide barcodes were added to saturation to pair with the beads with the cells in the microwells. Cell-lysis buffer was added to lyse the cell to allow barcode conjugated beads to capture poly-adenylated molecules, including mRNA, AbSeq targets and sample tag. Reverse transcription was performed on beads for WTA and AbSeq and Sample Tag Library Preparation. Finally, the library was sequenced using Novaseq platform (Illumina, San Diego, CA) on a 150 bp paired-end run.

Han Y., Bian Z.H., Yang S.Y., Wang C.B., Li L., Yang Y.Q., Ansari A.A., Gershwin M.E., Zeng X., Lian Z.X, & Zhao Z.B. (2022). Single-Cell Characterization of Hepatic CD8+ T Cells in a Murine Model of Primary Biliary Cholangitis. Frontiers in Immunology, 13, 860311.

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Single-Cell RNA-Seq of FGF21-Treated Mice

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FACS isolated cells were then loaded on the BD Rhapsody where capture of the single cells was performed per manufacturer instructions. Following lysis of the cells and capture of mRNA on oligonucleotide barcoded beads the cDNA synthesis was performed and cDNA libraries with Illumina sequencing adapters were generated per manufacturer instructions using the BD Rhapsody whole transcriptome analysis amplification kit. cDNA libraries were then sequenced on Illumina HiSeq 4000 sequencers at the University of Iowa Genomics Core. Sequencing data was then quality filtered and annotated using the BD Rhapsody analysis pipeline while also correcting for artifacts which arise during library construction. Filtered and annotated data from vehicle and FGF21 treated mice were then normalized in the R package Seurat using SCTransform and integrated using Seurat scRNA-seq integration (Stuart et al., 2019 (link)). Imputation was performed using the Seurat Wrapper ALRA on the integrated data set before final clustering (clustering resolution was set at 0.5 based on the number of cells sequenced)(Table S2) and gene expression analysis to account for dropout associated with 3’-barcoding-based approaches (Ziegenhain et al., 2017 (link)). “Cell type” classification of the clusters was determined based on expression of previously identified marker genes for neuronal and non-neuronal cell types.

Flippo K.H., Trammell S.A., Gillum M.P., Aklan I., Perez M.B., Yavuz Y., Smith N.K., Jensen-Cody S.O., Zhou B., Claflin K.E., Beierschmitt A., Fink-Jensen A., Knop F.K., Palmour R.M., Grueter B.A., Atasoy D, & Potthoff M.J. (2022). FGF21 suppresses alcohol consumption through an amygdalo-striatal circuit. Cell metabolism, 34(2), 317-328.e6.

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Single-cell Transcriptome Analysis via BD Rhapsody

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Single-cell transcriptome information was captured (from 20 sample sources) using the BD Rhapsody system. The single-cell suspension was randomly assigned to 200,000 micropores by a limited dilution method. The beads with oligonucleotide barcodes were added to the saturated state and paired with cells in the micropores. The cells were cleaved in micropores to hybridize mRNA molecules and the oligonucleotides on the beads were captured by bar code. Then reverse transcription and ExoI digestion were performed in a test tube. During cDNA synthesis, a unique molecular identifier (UMI) was bound to each cDNA molecule at the 5’ end to indicate the origin of the cell. The BD Rhapsody single-cell full transcriptome workflow includes random primer and extension (RPE), RPE amplification PCR and WTA index PCR to prepare a full transcriptome library. The high-sensitivity DNA chip (Agilent) on the bioanalyzer 2200 and the qubit high-sensitivity DNA analysis (Thermo Fisher Scientific) were used to quantify the library. Sequencing was performed by illumina sequencer (Illumina, San Diego, CA) on a 150 bp paired-end run.

Huang J., Zhu Z., Ji D., Sun R., Yang Y., Liu L., Shao Y., Chen Y., Li L, & Sun B. (2022). Single-Cell Transcriptome Profiling Reveals Neutrophil Heterogeneity and Functional Multiplicity in the Early Stage of Severe Burn Patients. Frontiers in Immunology, 12, 792122.

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Single-Cell Immune Profiling of T Cells

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LPMC were freshly prepared from surgically resected samples and stained with FITC anti-human CD3 antibody (clone HIT3a; BioLegend) for 30 min at 4 °C, followed by dead cell staining, after which cells were sorted on a Becton, Dickinson and Company (BD) FACSAria. Sorted live CD3⁺ cells were incubated with BD AbSeq antibodies (BD Biosciences) conjugated with oligonucleotides (SI Appendix, Table S4) for 30 min at 4 °C and washed in PBS. Subsequently, a single-cell suspension was loaded onto BD Rhapsody (BD Biosciences), followed by the loading of a bead library onto the cartridge. The cells were lysed to hybridize mRNAs onto barcoded capture oligos on the beads. The beads were collected into a single tube for the subsequent steps of complementary DNA (cDNA) synthesis, exonuclease I digestion, and multiplex PCR-based library construction. The BD Rhapsody Immune Response Panel for human and a custom primer set (SI Appendix, Table S4) were used for library generation. Libraries were sequenced on the Illumina HiSeq 3000 platform (2 × 100 bp).

Yokoi T., Murakami M., Kihara T., Seno S., Arase M., Wing J.B., Søndergaard J.N., Kuwahara R., Minagawa T., Oguro-Igashira E., Motooka D., Okuzaki D., Mori R., Ikeda A., Sekido Y., Amano T., Iijima H., Ozono K., Mizushima T., Hirota S., Ikeuchi H, & Takeda K. (2022). Identification of a unique subset of tissue-resident memory CD4+ T cells in Crohn’s disease. Proceedings of the National Academy of Sciences of the United States of America, 120(1), e2204269120.

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Comparative Single-cell Analysis of T-cell Subsets in SLE, T1D, and Healthy Controls

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Single-cell RNA sequencing data, was obtained from one SLE patient with an expanded CD25^lowFOXP3⁺ Treg population, one type 1 diabetes (T1D) patient and one healthy control (HC), presented in Trzupek et al. (29 (link)). Briefly, simultaneous mRNA expression of 397 genes (Human Response Panel; BD Biosciences) and protein expression of 24 T-cell expressed targets (see Supplementary Table 1), were assessed at the single-cell level using the BD Rhapsody and AbSeq system (BD Biosciences), as previously described (29 (link)). Flow sorted CD4⁺ T-cell subsets from each donor were barcoded using oligo-conjugated antibodies (single-cell multiplexing kit; BD Biosciences). For this study, we extracted and reanalyzed the data from sorted CD127^lowCD25^low (N = 7,115) and CD127^lowCD25^hi (N = 7,711) T cells passing QC. Detailed description of sorting strategy, library preparation and sequencing is presented in Trzupek et al. (29 (link)). Data analysis and QC was performed following the BD Biosciences Rhapsody pipeline (BD Biosciences) and the R package Seurat 3.0 (30 (link)). Uniform Manifold Approximation and Projection (UMAP) was used for dimensionality reduction. Differential expression analysis was performed using a tailored hurdle model from MAST package (31 (link)) used by Seurat.

Ferreira R.C., Castro Dopico X., Oliveira J.J., Rainbow D.B., Yang J.H., Trzupek D., Todd S.A., McNeill M., Steri M., Orrù V., Fiorillo E., Crouch D.J., Pekalski M.L., Cucca F., Tree T.I., Vyse T.J., Wicker L.S, & Todd J.A. (2019). Chronic Immune Activation in Systemic Lupus Erythematosus and the Autoimmune PTPN22 Trp620 Risk Allele Drive the Expansion of FOXP3+ Regulatory T Cells and PD-1 Expression. Frontiers in Immunology, 10, 2606.

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