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DOI 10.1093/nargab/lqag079

Медицинская библиотека · NAR genomics and bioinformatics · 2026

The challenges of single cell transcriptomics on difficult human tissue: the placenta.

Xenakis Theodoros, Hall George T, Moreno-Villena Jose J, Hillman Sara L, Sanchez-Corrales Yara E, Castellano Sergi

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Аннотация

Demand for the application of single cell transcriptomics on difficult tissues, processed and stored in disparate conditions, has led to the development of various single cell modalities. We focus on the placenta, a challenging tissue to transcriptomically interrogate due to senescence, intermittent hypoxia, high levels of RNase activity and tissue trauma at delivery. We performed single cell and nuclei transcriptomics on two samples with probe-based and native molecule transcript capture, droplet-based and in situ plate-based cell isolation. We explored sample and storage variations, including freshly dissociated tissues, fixed cells, snap frozen, and formalin fixed paraffin embedded processing. We find that variations in sample processing and storage have a much larger effect on cell-type proportions than differences in chemistry, impacting the biology that can be learned or the identification of disease markers. Further, the transcriptomic output of in situ combinatorial indexing consistently overlaps with single-nucleus transcriptomics, sharing little with other modalities. This may limit combinatorial indexing for sampling cytoplasmic messenger RNAs. Our comprehensive analysis of the technical variance between single cell transcriptomic modalities, including their sample management strategies, provides novel and essential considerations for the experimental design and analysis of single cell transcriptomics applicable to challenging tissues, offering actionable guidance for future experiments.

Для цитирования: Xenakis Theodoros, Hall George T, Moreno-Villena Jose J, Hillman Sara L, Sanchez-Corrales Yara E, Castellano Sergi. The challenges of single cell transcriptomics on difficult human tissue: the placenta.. NAR genomics and bioinformatics. 2026. DOI: 10.1093/nargab/lqag079.

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