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HIPSD&R-seq技术可实现可扩展的基因组拷贝数和转录组分析。

HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling.

作者信息

Otoničar Jan, Lazareva Olga, Mallm Jan-Philipp, Simovic-Lorenz Milena, Philippos George, Sant Pooja, Parekh Urja, Hammann Linda, Li Albert, Yildiz Umut, Marttinen Mikael, Zaugg Judith, Noh Kyung Min, Stegle Oliver, Ernst Aurélie

机构信息

Group Genome Instability in Tumors, German Cancer Research Center (DKFZ), Heidelberg, Germany.

German Cancer Consortium (DKTK), DKFZ, Core Center, Heidelberg, Germany.

出版信息

Genome Biol. 2024 Dec 18;25(1):316. doi: 10.1186/s13059-024-03450-0.

DOI:10.1186/s13059-024-03450-0
PMID:39696535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11657747/
Abstract

Single-cell DNA sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on a modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 17,000 cells.

摘要

单细胞DNA测序(scDNA-seq)能够解码体细胞癌症变异。现有方法受到低通量的限制,或者无法与同一细胞中的转录组测序相结合。我们提出了HIPSD&R-seq(高通量单细胞DNA和RNA测序),这是一种可扩展、简单且易于操作的检测方法,可并行分析数千个细胞中的低覆盖度DNA和RNA。我们的方法基于对10X Genomics平台进行修改,用于scATAC和多组学分析。在应用于人类细胞模型和原代组织时,我们证明了检测罕见克隆的可行性,并将该检测方法与组合索引相结合,以分析超过17,000个细胞。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/768e05c70a5b/13059_2024_3450_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/3fdd0f01d3ff/13059_2024_3450_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/204189f9b1f9/13059_2024_3450_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/768e05c70a5b/13059_2024_3450_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/3fdd0f01d3ff/13059_2024_3450_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/204189f9b1f9/13059_2024_3450_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8c4/11657747/768e05c70a5b/13059_2024_3450_Fig3_HTML.jpg

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Multi-omic and single-cell profiling of chromothriptic medulloblastoma reveals genomic and transcriptomic consequences of genome instability.多组学和单细胞分析揭示了染色体重排型髓母细胞瘤基因组不稳定性的基因组和转录组后果。
Nat Commun. 2024 Nov 23;15(1):10183. doi: 10.1038/s41467-024-54547-w.
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epiAneufinder identifies copy number alterations from single-cell ATAC-seq data.epiAneufinder 可从单细胞 ATAC-seq 数据中识别拷贝数改变。
Nat Commun. 2023 Sep 20;14(1):5846. doi: 10.1038/s41467-023-41076-1.
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Complex Analysis of Single-Cell RNA Sequencing Data.
单细胞 RNA 测序数据分析的复杂性。
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Best practices for single-cell analysis across modalities.多模态单细胞分析的最佳实践。
Nat Rev Genet. 2023 Aug;24(8):550-572. doi: 10.1038/s41576-023-00586-w. Epub 2023 Mar 31.
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SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data.SEACells 从单细胞基因组学数据推断转录和表观基因组细胞状态。
Nat Biotechnol. 2023 Dec;41(12):1746-1757. doi: 10.1038/s41587-023-01716-9. Epub 2023 Mar 27.
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scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors.scONE-seq:一种单细胞多组学方法,可从冷冻肿瘤中同时解析表型和基因型异质性。
Sci Adv. 2023 Jan 4;9(1):eabp8901. doi: 10.1126/sciadv.abp8901.
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Single-cell genomic variation induced by mutational processes in cancer.癌症中突变过程引起的单细胞基因组变异。
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