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High-quality single-cell transcriptomics from ovarian histological sections during folliculogenesis

High-quality, straightforward single-cell RNA sequencing (RNA-seq) with spatial resolution remains challenging. Here, we developed DRaqL (direct RNA recovery and quenching for laser capture microdissection), an experimental approach for efficient cell lysis of tissue sections, directly applicable to...

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Detalles Bibliográficos
Autores principales: Ikeda, Hiroki, Miyao, Shintaro, Nagaoka, So, Takashima, Tomoya, Law, Sze-Ming, Yamamoto, Takuya, Kurimoto, Kazuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Life Science Alliance LLC 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10507249/
https://www.ncbi.nlm.nih.gov/pubmed/37722727
http://dx.doi.org/10.26508/lsa.202301929
Descripción
Sumario:High-quality, straightforward single-cell RNA sequencing (RNA-seq) with spatial resolution remains challenging. Here, we developed DRaqL (direct RNA recovery and quenching for laser capture microdissection), an experimental approach for efficient cell lysis of tissue sections, directly applicable to cDNA amplification. Single-cell RNA-seq combined with DRaqL allowed transcriptomic profiling from alcohol-fixed sections with efficiency comparable with that of profiling from freshly dissociated cells, together with effective exon–exon junction profiling. The combination of DRaqL with protease treatment enabled robust and efficient single-cell transcriptome analysis from formalin-fixed tissue sections. Applying this method to mouse ovarian sections, we were able to predict the transcriptome of oocytes by their size and identified an anomaly in the size–transcriptome relationship relevant to growth retardation of oocytes, in addition to detecting oocyte-specific splice isoforms. Furthermore, we identified differentially expressed genes in granulosa cells in association with their proximity to the oocytes, suggesting distinct epigenetic regulations and cell-cycle activities governing the germ–soma relationship. Thus, DRaqL is a versatile, efficient approach for high-quality single-cell RNA-seq from tissue sections, thereby revealing histological heterogeneity in folliculogenic transcriptome.