High-throughput single-cell transcriptome and gene mutation integration analysis coding chip

Abstract

The invention discloses a high-throughput single-cell transcriptome and gene mutation integration analysis coding chip. According to the chip, a substrate is provided with a plurality of microholes, the micropores have a size and a shape which can only accommodate a single cell in a micropore, each micropore has a unique spatial coordinate encoding, the micropores are internally modified with a plurality of known nucleic acid sequences, the nucleic acid sequences successively include Spacer sequences, universal primer sequences, cell labels, molecular labels, and Ploy T, wherein the universalprimer sequences are used as primer-binding regions when a PCR is augmented, the cell labels are used for labeling cells from which the RNA originated, and the molecular labels are used for labeling combinative RNA. The invention provides the chip capable of being used for high-throughput single-cell transcriptomes and gene mutation integration analysis. By adopting a triple coding technique of microporous space coordinates, cell nucleic acid labels and molecular nucleic acid labels, gene mutation, the transcriptomes and protein expression information of a single cell can be matched one by one.

Description

technical field [0001] The invention relates to the field of biological detection, in particular to a high-throughput single-cell transcriptome and gene mutation integrated analysis coding chip. Background technique [0002] Tumor is one of the major diseases that seriously affect human health. There are great differences in tumor cells from genotype to phenotype (high heterogeneity of tumors), and this high heterogeneity is related to the degree of malignancy and drug resistance of tumors. Sex, recurrence and metastasis are closely related, which is one of the root causes of difficult early diagnosis of tumors, complicated clinical diagnosis and treatment, drug-resistant recurrence and poor prognosis. A comprehensive analysis of tumor heterogeneity is the key to precise tumor treatment. [0003] The development of high-throughput sequencing technology brings hope for the analysis of heterogeneous tumor populations. At present, conventional high-throughput sequencing at va...

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Problems solved by technology

However, the three-generation sequencing technology used in this study to detect mutations has great limitations. The mutation detection rate is limited by the specific mutation site. The highest single mutation detection rate is only 23%, and the average number of cells that can detect mutations does not exceed 5%, the author finally used the random forest machine learning algorithm to predict the tumor population, which could not realize the direct identification of the tumor cell population, and did not correspond well to the heterogeneity of the genome and transcriptome

Moreover, the technique is cumbersome to operate, requires a high sample volume, and costs a lot, making it unsuitable for general promotion.

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