Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby inc...
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| Format: | Article |
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MDPI AG
2024-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/25/7/3828 |
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| author | Yi Xie Huimei Chen Vasuki Ranjani Chellamuthu Ahmad bin Mohamed Lajam Salvatore Albani Andrea Hsiu Ling Low Enrico Petretto Jacques Behmoaras |
| author_facet | Yi Xie Huimei Chen Vasuki Ranjani Chellamuthu Ahmad bin Mohamed Lajam Salvatore Albani Andrea Hsiu Ling Low Enrico Petretto Jacques Behmoaras |
| author_sort | Yi Xie |
| collection | DOAJ |
| description | Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10x Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10x data where samples were not multiplexed. Despite relatively lower cell capture affecting library preparation, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, a comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies. |
| first_indexed | 2024-04-24T10:43:42Z |
| format | Article |
| id | doaj.art-bec439f169424ea680043f137d3c61d2 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-04-24T10:43:42Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-bec439f169424ea680043f137d3c61d22024-04-12T13:19:52ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672024-03-01257382810.3390/ijms25073828Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample MultiplexingYi Xie0Huimei Chen1Vasuki Ranjani Chellamuthu2Ahmad bin Mohamed Lajam3Salvatore Albani4Andrea Hsiu Ling Low5Enrico Petretto6Jacques Behmoaras7Programme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, SingaporeProgramme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, SingaporeTranslational Immunology Institute, SingHealth/Duke-NUS Academic Medical Centre, Academia, Singapore 169856, SingaporeTranslational Immunology Institute, SingHealth/Duke-NUS Academic Medical Centre, Academia, Singapore 169856, SingaporeTranslational Immunology Institute, SingHealth/Duke-NUS Academic Medical Centre, Academia, Singapore 169856, SingaporeDepartment of Rheumatology and Immunology, Singapore General Hospital, Academia, Singapore 169856, SingaporeProgramme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, SingaporeProgramme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, SingaporeSingle-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10x Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10x data where samples were not multiplexed. Despite relatively lower cell capture affecting library preparation, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, a comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies.https://www.mdpi.com/1422-0067/25/7/3828single-cell RNA sequencingmultiplexingSPLiT-seq10xPBMC |
| spellingShingle | Yi Xie Huimei Chen Vasuki Ranjani Chellamuthu Ahmad bin Mohamed Lajam Salvatore Albani Andrea Hsiu Ling Low Enrico Petretto Jacques Behmoaras Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing International Journal of Molecular Sciences single-cell RNA sequencing multiplexing SPLiT-seq 10x PBMC |
| title | Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing |
| title_full | Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing |
| title_fullStr | Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing |
| title_full_unstemmed | Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing |
| title_short | Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing |
| title_sort | comparative analysis of single cell rna sequencing methods with and without sample multiplexing |
| topic | single-cell RNA sequencing multiplexing SPLiT-seq 10x PBMC |
| url | https://www.mdpi.com/1422-0067/25/7/3828 |
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