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Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling.
Yamawaki, Tracy M; Lu, Daniel R; Ellwanger, Daniel C; Bhatt, Dev; Manzanillo, Paolo; Arias, Vanessa; Zhou, Hong; Yoon, Oh Kyu; Homann, Oliver; Wang, Songli; Li, Chi-Ming.
Afiliación
  • Yamawaki TM; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Lu DR; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Ellwanger DC; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Bhatt D; Oncology/Inflammation, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, United States.
  • Manzanillo P; Oncology/Inflammation, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, United States.
  • Arias V; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Zhou H; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Yoon OK; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Homann O; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Wang S; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA.
  • Li CM; Genome Analysis Unit, Amgen Research, 1120 Veterans Blvd, South San Francisco, CA, 94080, USA. CHIMINGL@amgen.com.
BMC Genomics ; 22(1): 66, 2021 Jan 20.
Article en En | MEDLINE | ID: mdl-33472597
ABSTRACT

BACKGROUND:

Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation.

RESULTS:

Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5' v1 and 3' v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures.

CONCLUSION:

Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Análisis de la Célula Individual Tipo de estudio: Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Perfilación de la Expresión Génica / Análisis de la Célula Individual Tipo de estudio: Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos