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Biology subjects

Zinzen, R.

Publications and source records attributed to Zinzen, R..

2 recordsLinked to original sources

Single-cell transcriptomics of enriched rare neural lineages of Tribolium castaneum

Background Single-cell transcriptomic atlases have transformed our understanding of cell diversity. However, studies designed to profile entire tissues or organisms often omit or underrepresent rare cell populations. Enriching selected populations before sequencing offers a powerful approach to overcoming this limitation, but its application in insects has largely focused on Drosophila, limiting opportunities for comparative studies. Here, we establish complementary workflows for targeted transcriptomic profiling of rare neural populations in the red flour beetle, Tribolium castaneum. Results We developed two workflows combining population enrichment with single-cell or single-nucleus RNA sequencing. First, we generated cell suspensions from a transgenic reporter line labelling embryonic neuroblasts, enriched fluorescently labelled cells by fluorescence-activated cell sorting, and performed single-cell RNA sequencing. Second, we immunolabelled first-instar larval brains with an antibody against the nuclear transcription factor Rx, isolated and sorted labelled nuclei, and performed single-nucleus RNA sequencing. Both workflows yielded material suitable for transcriptomic profiling, demonstrating complementary reporter-based and antibody-based strategies for accessing selected neural populations at different developmental stages. Conclusions These workflows establish a methodological framework for targeted single-cell and single-nucleus transcriptomic studies of rare or specific neural populations in Tribolium. They provide practical starting points for adaptation to other insect systems, expanding opportunities for comparative investigations of neural development and cell-type evolution.

developmental biology↗

RoCK and ROI: Single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing

Various tools have been developed to reliably identify, trace and analyze single cells in complex tissues. In recent years, these technologies have been combined with transcriptomic profiling approaches to explore molecular mechanisms that drive development, health, and disease. However, current methods still fall short of profiling single cell transcriptomes comprehensively, with one major challenge being high non-detection rates of specific transcripts and transcript regions. Such information is often crucial to understanding the biology of cells or tissues and includes lowly expressed transcripts, sequence variations and exon junctions. Here, we developed a scRNAseq workflow, RoCK and ROI (Robust Capture of Key transcripts and Regions Of Interest), that tackles these limitations. RoCKseq uses targeted capture to enrich for key transcripts, thereby supporting the detection and identification of cell types and complex phenotypes in scRNAseq experiments. ROIseq directs a subset of reads to a specific region of interest via selective priming to ensure detection. Importantly, RoCK and ROI guarantees efficient retrieval of specific sequence information without compromising overall single cell transcriptome information and our workflow is supported by a novel bioinformatics pipeline to analyze the multimodal information. RoCK and ROI represents a significant enhancement over non-targeted single cell sequencing, particularly when cell categorization depends on transcripts that are missed in standard scRNAseq experiments. In addition, it also allows exploration of biological questions that require assessment of specific sequence elements along the targets to be addressed.

genomics↗