Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish

Rubin, Sara A.; Baron, Chloé S.; Rodrigues, Cecília Pessoa; Duran, Madeleine; Corbin, Alexandra; Yang, Song; Trapnell, Cole; Zon, Leonard I.

doi:10.1084/jem.20220038

Cited by 33 publications

(28 citation statements)

References 203 publications

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“…Two useful tools for applying SNP-based demultiplexing are available for zebrafish, a high quality genome (Howe et al 2013) a common SNP variant Variant Call Format (VCF) file for the species (LaFave et al 2014). A recent study collected single animal scRNA-seq datasets from the thymus of zebrafish (Rubin et al 2022). These data present an opportunity to synthetically pool samples to test SNP-based demultiplexing on data from a non-human species.…”

Section: Resultsmentioning

confidence: 99%

“…Overall we successfully applied SNP-based methods to demultiplex pooled single cell data from multiple species including in silico pooled scRNA-seq and snRNA-seq data from zebrafish (Rubin et al 2022) African green monkey (Speranza et al 2021), and axolotl (Lust et al 2022) respectively, as well as experimentally pooled scRNA-seq data from Xenopus (Lin et al 2021), Pleurodeles , and experimentally pooled dual salamander species scRNA-seq. Our benchmarking results suggest that SNP-based demultiplexing in these species is accurate relative to other available demultiplexing approaches.…”

Section: Discussionmentioning

confidence: 99%

“…Fastq files from a previously published paper (Rubin et al 2022) (SRA accessions: SRR17218111, SRR17218113, SRR17218114, SRR17218091, SRR17218092) were downloaded from SRA using prefetch followed by fasterq-dump with flags split-files and include-technical. Files were renamed to 10X fastq format (e.g., sample_S1_L001_I1_001.fastq.gz) and then aligned using Cell Ranger v7.0.0 count to GRCz11 with the corresponding gtf for GRCz11 filtered via Cell Ranger mkgtf for protein_coding genes.…”

Section: Methodsmentioning

confidence: 99%

Section: Zebrafish Souporcell Demultiplexingmentioning

confidence: 99%

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Accurate genotype-based demultiplexing of single cell RNA sequencing samples from non-human animals

Cardiello

Araus

Giatrellis

et al. 2022

Preprint

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Single cell sequencing technologies (scRNA-seq, scATAC-seq, etc.) have revolutionized the study of complex tissues and unique organisms, providing researchers with a much needed species agnostic tool to study biological processes at the cellular level. To date, scRNA-seq technologies are expensive, require sufficient cell quantities, and need biological replicates to avoid batch effects or artifactual results. Pooling cells from multiple individuals into a single scRNA-seq library can address these problems. However, sample labeling protocols for facilitating the computational separation of pooled scRNA-seq samples, termed demultiplexing, have undesirable limitations, particularly in resource-limited organisms. One promising solution developed for use in humans exploits the genetic diversity between individuals (i.e., single nucleotide polymorphisms (SNP)) to demultiplex pooled scRNA-seq samples. The use of SNP-based demultiplexing methods has not been validated for use in non-human species, but the widespread use of SNP-based demuxers would greatly facilitate research in commonly used, emerging, and more obscure species. In this study we applied SNP-based demultiplexing algorithms to pooled scRNA-seq datasets from numerous species and applied diverse ground truth confirmation assays to validate genetic demultiplexing results. SNP-based demultiplexers were found to accurately demultiplex pooled scRNA-seq data from species including zebrafish, African green monkey, Xenopus laevis, axolotl, Pleurodeles waltl, and Notophthalmus viridescens. Our results demonstrate that SNP-based demultiplexing of unlabeled, pooled scRNA-seq samples can be used with confidence in all of the species studied in this work. Further, we show that the only genomic resource required for this approach is the single-cell sequencing data and a de novo transcriptome. The incorporation of pooling and SNP-demultiplexing into scRNA-seq study designs will greatly increase the reproducibility and experimental options for studying species previously limited by technical uncertainties, computational hurdles, or limited tissue or cell quantities.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Zebrafish Souporcell Demultiplexingmentioning

confidence: 99%

See 2 more Smart Citations

Accurate genotype-based demultiplexing of single cell RNA sequencing samples from non-human animals

Cardiello

Araus

Giatrellis

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…To identify cell types and states at chosen clustering resolution (0.6 for Control only, 0.5 for Control and Infected integrated), we performed differential expression analysis using Wilcoxon rank sum-based method (log2 fold change > 0.25, % of expressing cells > 0.25). Known markers were used to identify T cells (cd247l, lck, il7r, and cxcr4a) (53)(54)(55), dendritic cell-like populations (ctsbb, tlr7) (56,57), B cells (cd37, pax5) (58,59), macrophages (mpeg1.1, grn1) (60,61), neutrophils (mpx, il6r) (11,62), erythrocytes (hbba2, hemgn) (63), thrombocytes (thbs1b, fn1b) (57), superficial epithelial cells (krt1-19d, cldne) (64), ionocytes (trpv6, foxi3b) (65), intermediate epithelial cells (cldna, tp63) (64), basal epithelial cells (cldn1, cldni) (64), mesenchymal cells (vcana, clu) (66), lateral line-like cells (prox1a, prr15la) (67), and epidermal mucous cells (agr2, cldnh) (64). We found one population with some cells locating closer to the T cell populations but without clear enrichment for known signatures and included this population for a subclustering analysis with other T cells.…”

Section: Unsupervised Clustering and Cell Type Identificationmentioning

confidence: 99%

A tessellated lymphoid network provides whole-body T cell surveillance in zebrafish

Robertson

Hou

Shen

et al. 2023

Preprint

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Homeostatic trafficking to lymph nodes allows T cells to efficiently survey the host for cognate antigen. Non-mammalian jawed vertebrates lack lymph nodes but maintain similarly diverse T cell pools. Here, we exploit in vivo imaging of transparent zebrafish to investigate how T cells organize and survey for antigen in an animal devoid of lymph nodes. We find that naive-like T cells in zebrafish organize into a previously undescribed whole-body lymphoid network that supports streaming migration and coordinated trafficking through the host. This network has the cellular hallmarks of a mammalian lymph node, including naive T cells and CCR7-ligand expressing non-hematopoietic cells, and facilitates rapid collective migration. During infection, T cells transition to a random walk that supports antigen presenting cell interactions and subsequent activation. Our results reveal that T cells can toggle between collective migration and individual random walks to prioritize either large-scale trafficking or antigen search in situ. This novel lymphoid network thus facilitates whole-body T cell trafficking and antigen surveillance in the absence of a lymph node system.

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Cross-organ single-cell transcriptome profiling reveals macrophage and dendritic cell heterogeneity in zebrafish

et al. 2023

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Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish

Cited by 33 publications

References 203 publications

Accurate genotype-based demultiplexing of single cell RNA sequencing samples from non-human animals

Accurate genotype-based demultiplexing of single cell RNA sequencing samples from non-human animals

A tessellated lymphoid network provides whole-body T cell surveillance in zebrafish

Cross-organ single-cell transcriptome profiling reveals macrophage and dendritic cell heterogeneity in zebrafish

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