A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq

被引:5
作者
Brown, Daniel, V [1 ,2 ]
Anttila, Casey J. A. [1 ]
Ling, Ling [1 ]
Grave, Patrick [1 ]
Baldwin, Tracey M. [1 ]
Munnings, Ryan [1 ,2 ]
Farchione, Anthony J. [1 ,2 ]
Bryant, Vanessa L. [1 ,2 ,3 ]
Dunstone, Amelia [1 ]
Biben, Christine [1 ,2 ]
Taoudi, Samir [1 ,2 ]
Weber, Tom S. [1 ,2 ]
Naik, Shalin H. [1 ,2 ]
Hadla, Anthony [1 ,2 ]
Barker, Holly E. [1 ,2 ]
Vandenberg, Cassandra J. [1 ,2 ]
Dall, Genevieve [1 ,2 ]
Scott, Clare L. [1 ,2 ]
Moore, Zachery [1 ,2 ]
Whittle, James R. [1 ,2 ,4 ]
Freytag, Saskia [1 ,2 ]
Best, Sarah A. [1 ,2 ]
Papenfussa, Anthony T. [1 ,2 ,4 ]
Olechnowicza, Sam W. Z. [1 ,2 ]
Macrailda, Sarah E. [1 ]
Wilcox, Stephen [1 ]
Hickey, Peter F. [1 ,2 ]
Amann-Zalcenstein, Daniela [1 ,2 ]
Bowden, Rory [1 ,2 ]
机构
[1] Walter & Eliza Hall Inst Med Res, 1G Royal Parade, Melbourne, Vic 3052, Australia
[2] Univ Melbourne, Dept Med Biol, Melbourne, Vic 3010, Australia
[3] Royal Melbourne Hosp, 300 Grattan St, Melbourne, Vic 3010, Australia
[4] Peter MacCallum Canc Ctr, 305 Grattan St, Melbourne, Vic 3000, Australia
基金
英国医学研究理事会;
关键词
Single-cell; RNA-seq; Sample multiplexing; Fixed; CRISPRclean;
D O I
10.1016/j.ygeno.2024.110793
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNA-Seq experiments, facilitating more accurate and cost-effective studies.
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页数:13
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共 34 条
  • [1] Role of miRNA-495 and NRXN-1 and CNTN-1 mRNA Expression and Its Prognostic Importance in Breast Cancer Patients
    Alkhathami, Ali G.
    Verma, Amit Kumar
    Alfaifi, Mohammed
    Kumar, Lalit
    Alshahrani, Mohammad Yahya
    Hakami, Abdulrahim R.
    Alshehri, Osama M.
    Asiri, Mohammed
    Ali Beg, Mirza Masroor
    [J]. JOURNAL OF ONCOLOGY, 2021, 2021
  • [2] In vivo clonal tracking reveals evidence of haemangioblast and haematomesoblast contribution to yolk sac haematopoiesis
    Biben, C.
    Weber, T. S.
    Potts, K. S.
    Choi, J.
    Miles, D. C.
    Carmagnac, A.
    Sargeant, T.
    de Graaf, C. A.
    Fennell, K. A.
    Farley, A.
    Stonehouse, O. J.
    Dawson, M. A.
    Hilton, D. J.
    Naik, S. H.
    Taoudi, S.
    [J]. NATURE COMMUNICATIONS, 2023, 14 (01)
  • [3] BFF and cellhashR: analysis tools for accurate demultiplexing of cell hashing data
    Boggy, Gregory J.
    McElfresh, G. W.
    Mahyari, Eisa
    Ventura, Abigail B.
    Hansen, Scott G.
    Picker, Louis J.
    Bimber, Benjamin N.
    [J]. BIOINFORMATICS, 2022, 38 (10) : 2791 - 2801
  • [4] Multiplexing Methods for Simultaneous Large-Scale Transcriptomic Profiling of Samples at Single-Cell Resolution
    Cheng, Junyun
    Liao, Jie
    Shao, Xin
    Lu, Xiaoyan
    Fan, Xiaohui
    [J]. ADVANCED SCIENCE, 2021, 8 (17)
  • [5] Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows
    Denisenko, Elena
    Guo, Belinda B.
    Jones, Matthew
    Hou, Rui
    de Kock, Leanne
    Lassmann, Timo
    Poppe, Daniel
    Clement, Olivier
    Simmons, Rebecca K.
    Lister, Ryan
    Forrest, Alistair R. R.
    [J]. GENOME BIOLOGY, 2020, 21 (01)
  • [6] Molecular logic of cellular diversification in the mouse cerebral cortex
    Di Bella, Daniela J.
    Habibi, Ehsan
    Stickels, Robert R.
    Scalia, Gabriele
    Brown, Juliana
    Yadollahpour, Payman
    Yang, Sung Min
    Abbate, Catherine
    Biancalani, Tommasso
    Macosko, Evan Z.
    Chen, Fei
    Regev, Aviv
    Arlotta, Paola
    [J]. NATURE, 2021, 595 (7868) : 554 - +
  • [7] Epigenetic loss of heterogeneity from low to high grade localized prostate tumours
    Eksi, Sebnem Ece
    Chitsazan, Alex
    Sayar, Zeynep
    Thomas, George, V
    Fields, Andrew J.
    Kopp, Ryan P.
    Spellman, Paul T.
    Adey, Andrew C.
    [J]. NATURE COMMUNICATIONS, 2021, 12 (01)
  • [8] CASB: a concanavalin A-based sample barcoding strategy for single-cell sequencing
    Fang, Liang
    Li, Guipeng
    Sun, Zhiyuan
    Zhu, Qionghua
    Cui, Huanhuan
    Li, Yunfei
    Zhang, Jingwen
    Liang, Weizheng
    Wei, Wencheng
    Hu, Yuhui
    Chen, Wei
    [J]. MOLECULAR SYSTEMS BIOLOGY, 2021, 17 (04)
  • [9] Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular proteins
    Gehring, Jase
    Park, Jong Hwee
    Chen, Sisi
    Thomson, Matthew
    Pachter, Lior
    [J]. NATURE BIOTECHNOLOGY, 2020, 38 (01) : 35 - +
  • [10] CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics
    Guo, Chuner
    Kong, Wenjun
    Kamimoto, Kenji
    Rivera-Gonzalez, Guillermo C.
    Yang, Xue
    Kirita, Yuhei
    Morris, Samantha A.
    [J]. GENOME BIOLOGY, 2019, 20 (1)