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Evaluation of genetic demultiplexing of single-cell sequencing data from model species

Cardiello, Joseph F LU ; Joven Araus, Alberto ; Giatrellis, Sarantis ; Helsens, Clement ; Simon, András and Leigh, Nicholas D LU orcid (2023) In Life Science Alliance 6(8).
Abstract

Single-cell sequencing (sc-seq) provides a species agnostic tool to study cellular processes. However, these technologies are expensive and require sufficient cell quantities and biological replicates to avoid artifactual results. An option to address these problems is pooling cells from multiple individuals into one sc-seq library. In humans, genotype-based computational separation (i.e., demultiplexing) of pooled sc-seq samples is common. This approach would be instrumental for studying non-isogenic model organisms. We set out to determine whether genotype-based demultiplexing could be more broadly applied among species ranging from zebrafish to non-human primates. Using such non-isogenic species, we benchmark genotype-based... (More)

Single-cell sequencing (sc-seq) provides a species agnostic tool to study cellular processes. However, these technologies are expensive and require sufficient cell quantities and biological replicates to avoid artifactual results. An option to address these problems is pooling cells from multiple individuals into one sc-seq library. In humans, genotype-based computational separation (i.e., demultiplexing) of pooled sc-seq samples is common. This approach would be instrumental for studying non-isogenic model organisms. We set out to determine whether genotype-based demultiplexing could be more broadly applied among species ranging from zebrafish to non-human primates. Using such non-isogenic species, we benchmark genotype-based demultiplexing of pooled sc-seq datasets against various ground truths. We demonstrate that genotype-based demultiplexing of pooled sc-seq samples can be used with confidence in several non-isogenic model organisms and uncover limitations of this method. Importantly, the only genomic resource required for this approach is sc-seq data and a de novo transcriptome. The incorporation of pooling into sc-seq study designs will decrease cost while simultaneously increasing the reproducibility and experimental options in non-isogenic model organisms.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Animals, Single cell RNA sequencing, Reproducibility of Results, Zebrafish/genetics, Transcriptome, Genomics/methods, Sequence Analysis, RNA/methods, demultiplexing, regeneration model, Developmental biology
in
Life Science Alliance
volume
6
issue
8
publisher
Rockefeller University Press
external identifiers
  • scopus:85159762723
  • pmid:37197983
ISSN
2575-1077
DOI
10.26508/lsa.202301979
language
English
LU publication?
yes
additional info
© 2023 Cardiello et al.
id
af998e66-894a-4545-bf05-b39eb55a5360
date added to LUP
2023-05-25 16:11:53
date last changed
2024-09-07 11:29:54
@article{af998e66-894a-4545-bf05-b39eb55a5360,
  abstract     = {{<p>Single-cell sequencing (sc-seq) provides a species agnostic tool to study cellular processes. However, these technologies are expensive and require sufficient cell quantities and biological replicates to avoid artifactual results. An option to address these problems is pooling cells from multiple individuals into one sc-seq library. In humans, genotype-based computational separation (i.e., demultiplexing) of pooled sc-seq samples is common. This approach would be instrumental for studying non-isogenic model organisms. We set out to determine whether genotype-based demultiplexing could be more broadly applied among species ranging from zebrafish to non-human primates. Using such non-isogenic species, we benchmark genotype-based demultiplexing of pooled sc-seq datasets against various ground truths. We demonstrate that genotype-based demultiplexing of pooled sc-seq samples can be used with confidence in several non-isogenic model organisms and uncover limitations of this method. Importantly, the only genomic resource required for this approach is sc-seq data and a de novo transcriptome. The incorporation of pooling into sc-seq study designs will decrease cost while simultaneously increasing the reproducibility and experimental options in non-isogenic model organisms.</p>}},
  author       = {{Cardiello, Joseph F and Joven Araus, Alberto and Giatrellis, Sarantis and Helsens, Clement and Simon, András and Leigh, Nicholas D}},
  issn         = {{2575-1077}},
  keywords     = {{Animals; Single cell RNA sequencing; Reproducibility of Results; Zebrafish/genetics; Transcriptome; Genomics/methods; Sequence Analysis, RNA/methods; demultiplexing; regeneration model; Developmental biology}},
  language     = {{eng}},
  number       = {{8}},
  publisher    = {{Rockefeller University Press}},
  series       = {{Life Science Alliance}},
  title        = {{Evaluation of genetic demultiplexing of single-cell sequencing data from model species}},
  url          = {{http://dx.doi.org/10.26508/lsa.202301979}},
  doi          = {{10.26508/lsa.202301979}},
  volume       = {{6}},
  year         = {{2023}},
}