Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.3389/ftox.2022.821116
In this report, we compare the outcomes and limitations of two methods of transcriptomic inquiry on adult zebrafish testes exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) during sexual differentiation: conventional or bulk RNA-seq (bulk-seq) and single cell RNA sequencing (scRNA-seq) data. scRNA-seq has emerged as a valuable tool for uncovering cell type-specific transcriptome dynamics which exist in heterogeneous tissue. Our lab previously showed the toxicological value of the scRNA-seq pipeline to characterize the sequelae of TCDD exposure in testes, demonstrating that loss of spermatids and spermatozoa, but not other cell types, contributed to the pathology of infertility in adult male zebrafish exposed during sexual differentiation. To investigate the potential for technical artifacts in scRNA-seq such as cell dissociation effects and reduced transcriptome coverage, we compared bulk-sequenced and scRNA-seq-paired samples from control and TCDD-exposed samples to understand what is gained and lost in scRNA-seq vs bulk-seq, both transcriptomically and toxicologically. We hypothesized that the testes may be sensitive to tissue disruption as they contain multiple cell types under constant division and/or maturation, and that TCDD exposure may mediate the extent of sensitivity. Thus, we sought to understand the extent to which this dissociation impacts the toxicological value of data returned from scRNA-seq. We confirm that the required dissociation of individual cells from intact tissue has a significant impact on gene expression, affecting gene pathways with the potential to confound toxicogenomics studies on exposures if findings are not well-controlled and well-situated in context. Additionally, a common scRNA-seq method using cDNA amplified from the 3’ end of mRNA under-detects low-expressing transcripts including transcription factors. We confirm this, and show TCDD-related genes may be overlooked by scRNA-seq, however, this under-detection effect is not mediated by TCDD exposure. Even so, scRNA-seq generally extracted toxicologically relevant information better than the bulk-seq method in the present study. This report aims to inform future experimental design for transcriptomic investigation in the growing field of toxicogenomics by demonstrating the differential information extracted from sequencing cells—despite being from the same tissue and exposure scheme—is influenced by the specific protocol used, with implications for the interpretation of exposure-induced risk.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/ftox.2022.821116
- https://www.frontiersin.org/articles/10.3389/ftox.2022.821116/pdf
- OA Status
- gold
- Cited By
- 8
- References
- 64
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4229370411
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4229370411Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/ftox.2022.821116Digital Object Identifier
- Title
-
Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular TissueWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-05-09Full publication date if available
- Authors
-
Alex Haimbaugh, Danielle Meyer, Camille Akemann, Katherine Gurdziel, Tracie R. BakerList of authors in order
- Landing page
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https://doi.org/10.3389/ftox.2022.821116Publisher landing page
- PDF URL
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https://www.frontiersin.org/articles/10.3389/ftox.2022.821116/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/articles/10.3389/ftox.2022.821116/pdfDirect OA link when available
- Concepts
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Transcriptome, RNA-Seq, Biology, Toxicogenomics, Zebrafish, Cell, RNA, Cell type, Gene expression, Gene, Computational biology, Cell biology, Genetics, Andrology, MedicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 4, 2022: 2Per-year citation counts (last 5 years)
- References (count)
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64Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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