Simultaneous transcriptome and proteome profiling in a single mouse oocyte with a deep single-cell multi-omics approach Article Swipe

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Yirong Jiang , Le Zhu , Lan‐Rui Cao , Qiong Wu , Jianbo Chen , Yu Wang , Jie Wu , Tianyu Zhang , Zhaolun Wang , Zhi-Ying Guan , Qin‐Qin Xu , Qian‐Xi Fan , Shao-Wen Shi , Hui-Feng Wang , Jian‐Zhang Pan , Xudong Fu , Yongcheng Wang , Qun Fang ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.1101/2022.08.17.504335

Nowadays, although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing and mass spectrometry technology, to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level for the first time. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19948 genes and 2663 protein groups in single mouse oocytes. This reliable quantitative two-omics dataset of single cells provided an important resource for understanding the relationship between the transcriptome and the proteome in cells. Based on the correlation analysis of RNAs and proteins in the same single cell, we demonstrated the expressive heterogeneity of transcriptome and proteome during the cellular biological process. Specially, we analyzed the meiosis regulatory network during oocyte maturation with an unprecedented depth at the single-cell level, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, providing crucial insights into the regulatory features of transcription and translation during oocyte meiotic maturation.

Related Topics

Biology

Oocyte

Computational Biology

Concepts

Transcriptome Proteome Biology Oocyte Computational biology Gene expression profiling Cell biology Gene Bioinformatics Genetics Gene expression Embryo

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Type: preprint
Language: en
Landing Page: https://doi.org/10.1101/2022.08.17.504335
PDF: https://www.biorxiv.org/content/biorxiv/early/2022/08/18/2022.08.17.504335.full.pdf
OA Status: green
Cited By: 2
References: 43
Related Works: 10
OpenAlex ID: https://openalex.org/W4293749470

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DOI: https://doi.org/10.1101/2022.08.17.504335

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Title: Simultaneous transcriptome and proteome profiling in a single mouse oocyte with a deep single-cell multi-omics approach

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Type: preprint

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Language: en

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Publication year: 2022

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Publication date: 2022-08-18

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Authors: Yirong Jiang, Le Zhu, Lan‐Rui Cao, Qiong Wu, Jianbo Chen, Yu Wang, Jie Wu, Tianyu Zhang, Zhaolun Wang, Zhi-Ying Guan, Qin‐Qin Xu, Qian‐Xi Fan, Shao-Wen Shi, Hui-Feng Wang, Jian‐Zhang Pan, Xudong Fu, Yongcheng Wang, Qun Fang

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Landing page: https://doi.org/10.1101/2022.08.17.504335

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PDF URL: https://www.biorxiv.org/content/biorxiv/early/2022/08/18/2022.08.17.504335.full.pdf

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Concepts: Transcriptome, Proteome, Biology, Oocyte, Computational biology, Gene expression profiling, Cell biology, Gene, Bioinformatics, Genetics, Gene expression, Embryo

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Cited by: 2

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References (count): 43

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Related works (count): 10

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