A high-precision and high-coverage pedigree tree tracking method

Abstract

The application discloses a high-precision and high-coverage pedigree tree tracking method, and relates to the technical field of cell pedigree tracking, and specifically comprises the following steps: selecting single-direction RNA1, single-direction RNA2, single-direction RNA3 and single-direction RNA4 which are completely different in sequence as backups, and selecting single-cell clone amplification to prepare a pedigree barcode with 13 editing sites as a backup; and adopting a cell pedigree barcode technology to match the single-direction RNA1, the single-direction RNA2, the single-direction RNA3 and the single-direction RNA4 with the 13 editing sites of the pedigree barcode respectively. The high-precision and high-coverage pedigree tree tracking method increases the average expression amount of the pedigree barcode in all cells, reduces the speed of consumption of the editing sites, increases the traceable time, simultaneously reduces the proportion of cross-site deletion mutations, and obtains a high proportion of single leaves of a cell pedigree tree, so that a pedigree tree determination method with a single-cell level resolution is realized, and the mortality of cells in clone amplification and the loss rate in cell digestion are reduced.

Description

Technical Field

[0001] This invention relates to the field of cell lineage tracing technology, specifically to a high-precision and high-coverage lineage tree tracing method. Background Technology

[0002] Tracking phenotypic differences and evolutionary trends among cells is one of the fundamental goals of cell biology and evolutionary biology. Recent advances in high-throughput single-cell sequencing have enabled us to describe the complete transcriptome atlas of normal human tissues and tumors / cancers at the level of millions of single cells. Rethinking this from an evolutionary biological perspective, relying on comparative analysis of gene expression differences yields similarities between cell types, but not the history of cell mitosis. Extending the "species evolution tree" concept of biological population evolution to the "cell lineage tree" method of cell population evolution allows us to map mitotic relationships between cells to the complete transcriptome atlas, enabling detailed comparisons between gene expression differences and mitotic history. Therefore, the powerful tool for accurately revealing general laws and patterns in life processes is cell lineage tree technology, rather than simply single-cell complete transcriptome mapping.

[0003] The cell lineage tree technique, based on tracing the mitotic history between cells, was first successfully used in nematodes approximately 40 years ago. To date, cell lineage tree technology can be broadly categorized into two types: methods based on optical microscopy and methods reconstructed from DNA lineage barcode sequencing results. Optical microscopy methods mainly include: direct observation and recording, methods based on tracer dyes (in vivo tracer dyes and dextran / carbocyanine dyes), and the Brainbow series of fluorescence microscopy. The advantage of these techniques is the intuitiveness of the results, but they also have significant disadvantages, such as lower resolution and difficulty in directly observing non-transparent tissues. Methods reconstructed from DNA lineage barcode sequencing results are not limited by tissue / embryo transparency, and due to the high diversity of DNA barcodes, their resolution is usually far superior to the former. DNA barcode technology can be further divided into two categories: Clonal barcode technology, which does not rely on DNA mutations, and Lineage barcode technology, which does rely on DNA mutations. Clonal barcode technology is primarily used for high-throughput tracking of the proliferation rate or differentiation fate of individual progenitor cells, without concern for the phylogenetic relationships between their progeny cells. Lineage barcode technology is used to track the phylogenetic relationships between progeny cells of the same origin, with successful examples including GESTALT and CARLIN technologies based on CRISPR / Cas9 random insertion and deletion mutations. Although the combination of clonal and lineage barcode technologies has successfully achieved high-throughput tracking of single-cell-level cell phylogenetic maps during lung cancer cell proliferation and metastasis, the low resolution / coverage makes this data insufficient for detailed comparisons of gene expression differences and mitotic history using tree alignment methods (excluding the influence of common ancestor on gene expression and phenotypic correlations among daughter cells).

[0004] Based on the above description, the accuracy and coverage of the original cell population in existing phylogenetic trees are both low, and there is a significant lack of tracking of the mitotic history of the entire cell population. This is due to the following reasons: the number of cells used for sequencing is too small, reducing the coverage of the phylogenetic tree; the expression level of lineage barcodes used for lineage tracking is too low, leading to their loss in single-cell sequencing, further reducing the coverage of the phylogenetic tree; most lineage barcodes contain long deletion mutations spanning editing sites, which reduces the number of sites that can be further edited and may prune already occurred editing events, reducing the accuracy of the phylogenetic tree; most sites are typically edited within 2-4 days, resulting in too short a lineage tracking time; and most genotypes of lineage barcodes exist in multiple cells, making them indistinguishable, which limits the comparison of single-cell expression differences dependent on the tree. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a high-precision and high-coverage phylogenetic tree tracing method, which solves the problems of low accuracy and coverage of the original cell population in existing phylogenetic trees, and significant gaps in the tracing of the mitotic history of the entire cell population.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a high-precision and high-coverage phylogenetic tree tracing method, specifically comprising the following steps:

[0009] S1. Select unidirectional RNA1, unidirectional RNA2, unidirectional RNA3 and unidirectional RNA4 with completely different sequences for later use; select single-cell clones to amplify and prepare pedigree barcodes with 13 editing sites for later use.

[0010] S2. Using lineage barcoding technology, unidirectional RNA1, unidirectional RNA2, unidirectional RNA3 and unidirectional RNA4 were matched with 13 editing sites of the lineage barcode to obtain the lineage barcode sequence;

[0011] S3. Combine the pedigree barcode described in S1 with the green fluorescent protein gene and the resistance gene to form a fusion gene;

[0012] S4. Use a single-cell sequencing platform to capture the lineage barcodes with fusion genes described in S3.

[0013] Preferably, in step S1, the single cell is a single HEK293 cell, and the lineage barcode is obtained by clonal expansion of the single HEK293 cell under continuous division for 10 days.

[0014] Preferably, in step S2, the unidirectional RNA1 mismatches with more than two of the 13 editing sites of the lineage barcode, reducing the proportion of cross-site deletion mutations and increasing the traceability time; the obtained cell lineage tree has a high proportion of individual leaves, realizing a lineage tree determination method with resolution at the single cell level.

[0015] Preferably, in step S2, the one-way RNA2, one-way RNA3 and one-way RNA4 are matched with the 9th, 12th and 13th editing sites of the lineage barcode, respectively, and the matching editing efficiency of the 9th, 12th and 13th editing sites is relatively low.

[0016] Preferably, in step S2, based on the differences in the number and type of mismatched bases, the editing efficiency of unidirectional RNA1, unidirectional RNA2 and the 13 editing sites of the lineage barcode gradually decreases, thereby reducing the proportion of cross-site deletion mutations.

[0017] Preferably, in step S2, based on the CFD scoring strategy, the proportion of lineage barcode deletion mutations across editing sites is 8.8%, and the proportion of single-cell leaves is 90%.

[0018] Preferably, in step S3, using a high concentration of antibiotics to screen for fusion genes is beneficial for screening cell clones with higher expression of fusion genes.

[0019] Preferably, in step S3, observing the brightness of the green fluorescent protein gene is beneficial for screening samples with higher expression of the fusion gene.

[0020] Preferably, in step S4, the probability of capturing a lineage barcode with a fusion gene using a single-cell sequencing platform is approximately 90%.

[0021] Beneficial effects

[0022] This invention provides a high-precision and high-coverage phylogenetic tree tracing method. Compared with existing technologies, it has the following advantages:

[0023] 1. This high-precision and high-coverage pedigree tree tracing method improves the accuracy of pedigree trees, increases the average expression level of pedigree barcodes in all cells, and shows more than two mismatches in the 13 editing sites and unidirectional RNA of the pedigree barcodes, reducing the rate at which editing sites are consumed and increasing the traceability time. At the same time, it reduces the proportion of cross-site deletion mutations and obtains a high proportion of individual leaves in the obtained cell pedigree trees, realizing a pedigree tree determination method with resolution at the single cell level.

[0024] 2. This high-precision and high-coverage phylogenetic tree tracing method improves the coverage of the phylogenetic tree, reduces cell mortality during clonal expansion, and reduces the loss rate during cell digestion. Furthermore, all single cells are used for cell phylogenetic tracing. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the gene structure contained in the lineage tracing system of the present invention;

[0026] Figure 2 This is a schematic diagram illustrating the cell state observation during continuous single-cell culture according to the present invention.

[0027] Figure 3 This is an experimental flowchart illustrating the simultaneous capture of lineage barcode and transcriptome data according to the present invention.

[0028] Figure 4This is a phylogenetic tree quality parameter verification diagram for the expression level of phylogenetic barcodes in a single cell according to the present invention;

[0029] Figure 5 This is an example diagram illustrating the accuracy of the phylogenetic tree in this invention;

[0030] Figure 6 This is an example diagram of the ancestral barcode of the present invention;

[0031] Figure 7 This is a phylogenetic tree quality parameter verification diagram for the ancestral barcode representation of the present invention;

[0032] Figure 8 This is a diagram verifying the phylogenetic quality parameters of the intercellular kinship relationship in this invention.

[0033] In the diagram: 1. Unidirectional RNA1; 2. Unidirectional RNA2; 3. Unidirectional RNA3; 4. Unidirectional RNA4; 5. Lineage barcode. Detailed Implementation

[0034] The technical solutions in the embodiments of the present invention have been clearly and completely described. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figure 1-8 This invention provides a technical solution: a high-precision and high-coverage pedigree tree tracing method, specifically including the following steps: S1, selecting unidirectional RNA1, unidirectional RNA2, unidirectional RNA3, and unidirectional RNA4 with completely different sequences for later use, and selecting single-cell clones to amplify and prepare a pedigree barcode 5 with 13 editing sites for later use; S2, using cell pedigree barcoding technology to match unidirectional RNA1, unidirectional RNA2, unidirectional RNA3, and unidirectional RNA4 with the 13 editing sites of pedigree barcode 5 respectively, to obtain the pedigree barcode 5 sequence; S3, combining the pedigree barcode 5 from S1 with the green fluorescent protein gene and the resistance gene to form a fusion gene; S4, using a single-cell sequencing platform to capture the pedigree barcode 5 with the fusion gene from S3.

[0036] See attached document Figure 4In the diagram, part B represents the 36 weights of the maximum parsimony algorithm, and part C represents the 190 weights of the maximum likelihood algorithm. The weights are determined based on the probability of an edit event occurring. If there are too few weights, edit events with similar probabilities will be defined with the same weight, making them indistinguishable. The advantage of having more weights is that it can distinguish between edit events with similar probabilities, resulting in higher resolution. The maximum parsimony and maximum likelihood tree construction process is as follows: After quality control of the phylogenetic barcode sequencing data, the data is linked according to the middle 40bp overlapping sequence and compared with the reference sequence. The types and frequencies of edit events are statistically analyzed. Based on the frequency of edit events, a weight is defined for each edit event. There are two methods for defining weights: the maximum parsimony algorithm and the maximum likelihood algorithm. Based on the type of edit event and the weight of each edit event, a sequence file and a corresponding weight file are generated for each sequence. Based on the weight file and the sequence file, a phylogenetic tree is generated using the maximum parsimony algorithm and the maximum likelihood algorithm, respectively.

[0037] In step S1, a single HEK293 cell was used as the single cell. The single HEK293 cell underwent continuous clonal expansion for 10 days to obtain lineage barcode 5. In step S2, unidirectional RNA1 mismatched with more than two of the 13 editing sites of lineage barcode 5, reducing the proportion of cross-site deletion mutations and increasing the traceability time. The obtained cell lineage tree had a high proportion of individual leaves, achieving a lineage tree determination method with single-cell resolution. In step S2, unidirectional RNA2, unidirectional RNA3, and unidirectional RNA4 matched with editing sites 9, 12, and 13 of lineage barcode 5, respectively. The matching editing efficiency of editing sites 9, 12, and 13 was relatively low. In step S2, based on the differences in the number and type of mismatched bases, the editing efficiency of unidirectional RNA1 and unidirectional RNA2 with the 13 editing sites of lineage barcode 5 gradually decreased, reducing the proportion of cross-site deletion mutations. In step S2, based on the CFD scoring strategy, the proportion of lineage barcode 5-span deletion mutations across editing sites was 8.8%, and the proportion of single-cell leaves was 90%. In step S3, using high concentrations of antibiotics to screen for fusion genes is beneficial for screening cell clones with higher fusion gene expression. In step S3, observing the brightness of the green fluorescent protein gene is beneficial for screening samples with higher fusion gene expression. In step S4, the probability of capturing lineage barcodes 5 with fusion genes using a single-cell sequencing platform is approximately 90%. The main idea of ​​barcode-based single-cell identification is to add a unique DNA sequence to each cell. During sequencing, sequences carrying the same barcode are considered to come from the same cell. This strategy can obtain information from hundreds or thousands of single cells in a single library construction. Cell barcodes and RT lysis reagents are co-encapsulated in microfluidic droplets. After collecting the required number of cells, barcode primers are released from the hydrogel beads through photolysis to initiate reverse transcription of mRNA. The scale bar is 100 μm. After the cells and hydrogel beads are encapsulated, barcode cDNA primers are released from the beads using >350 nm ultraviolet light, followed by mRNA capture and reverse transcription.

[0038] The sequence characteristics of phylogenetic barcodes are known to be the primary factor determining the accuracy of phylogenetic trees. Existing methods typically use 10 completely different unidirectional RNAs, each matching 100% of the editing sites of the phylogenetic barcode. This results in a high probability that two or more unidirectional RNAs simultaneously target different editing sites of the phylogenetic barcode during cell proliferation, leading to rapid depletion of these editing sites, often resulting in long deletion mutations spanning multiple editing sites. This not only reduces the time available for phylogenetic tracing but also decreases the distinguishability between cells. To address these issues, the phylogenetic tree of this invention includes only unidirectional RNA1, unidirectional RNA2, unidirectional RNA3, and unidirectional RNA4. Unidirectional RNA1 has at least two mismatches with each of the 13 editing sites of phylogenetic barcode 5. Unidirectional RNA2, unidirectional RNA3, and unidirectional RNA4 match the 9th, 12th, and 13th editing sites, respectively, which have lower editing efficiency. Based on the differences in the number and type of mismatched bases, and using a CFD scoring strategy, unidirectional RNA1, unidirectional RNA2, and unidirectional RNA4 are matched with the phylogenetic barcode 5. The editing efficiency of the 13 editing sites gradually decreases. Based on this, the present invention reduces the proportion of cross-site deletion mutations to 8.8% and increases the proportion of single-cell leaves to 90%. The capture rate and cell capture rate of the lineage barcode are the primary factors determining the coverage of the lineage tree. In existing methods, lineage barcodes are usually difficult to transcribe into a large number of mRNA molecules, so the capture probability of their single-cell sequencing platforms is 5%-25%. The method of the present invention combines lineage barcode 5 with the green fluorescent protein gene and the antibiotic resistance gene into a fusion gene. Screening with high concentrations of antibiotics is beneficial for screening cell clones with higher expression of the fusion gene. During lineage tracking, the observation of the brightness of green fluorescent protein is beneficial for screening samples with higher expression of the fusion gene. The above measures increase the capture probability of lineage barcode 5 to approximately 90%. Existing methods typically digest all cells from zebrafish embryos or a specific mouse tissue, then only a small number of cells are sequenced for single-cell sequencing. Since single-cell sequencing has a cell capture rate of approximately 60%, the resulting phylogenetic tree has even lower coverage of the cell population. This is equivalent to low-abundance random sampling from a complete phylogenetic tree, which cannot accurately describe the general patterns in the life process. The method of this invention, however, is primarily applied to phylogenetic tracing starting from a single cell. After optimization and quality control of cell culture conditions, digestion conditions, and single-cell sequencing conditions, this invention successfully obtained the phylogenetic tree of approximately 50% of the cells involved in the 10-day single-cell clonal expansion process.This invention improves the accuracy of phylogenetic trees, increases the average expression level of phylogenetic barcode 5 in all cells, and identifies more than two mismatches in both the 13 editing sites and unidirectional RNA of phylogenetic barcode 5, reducing the rate at which editing sites are consumed and increasing the traceability time. It also reduces the proportion of cross-site deletion mutations, resulting in a high proportion of individual leaves in the obtained cell phylogenetic tree, achieving a phylogenetic tree determination method with single-cell resolution. Furthermore, it improves the coverage of the phylogenetic tree, reduces cell mortality during clonal expansion, and decreases the loss rate during cell digestion. All single cells are used for cell lineage tracing.

[0039] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0040] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0041] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-precision and high-coverage phylogenetic tree tracing method, characterized in that: Specifically, the following steps are included: S1. Select unidirectional RNA1(1), unidirectional RNA2(2), unidirectional RNA3(3) and unidirectional RNA4(4) with completely different sequences for later use. Select a single-cell clone amplification to prepare a lineage barcode with 13 editing sites (5) for later use. S2. Using cell lineage barcoding technology, unidirectional RNA1(1), unidirectional RNA2(2), unidirectional RNA3(3) and unidirectional RNA4(4) were matched with 13 editing sites of the lineage barcode (5) to obtain the lineage barcode (5) sequence; S3. Combine the lineage barcode (5) described in S1 with the green fluorescent protein gene and the resistance gene to form a fusion gene; S4. The lineage barcodes with fusion genes described in S3 were captured using a single-cell sequencing platform (5); In step S2, the unidirectional RNA1 (1) has more than two mismatches with each of the 13 editing sites of the lineage barcode (5). The unidirectional RNA2 (2), unidirectional RNA3 (3), and unidirectional RNA4 (4) are matched with the 9th, 12th, and 13th editing sites with lower editing efficiency, respectively. Based on the difference in the number and type of mismatched bases, and according to the CFD scoring strategy, the editing efficiency of the unidirectional RNA1 (1), unidirectional RNA2 (2), and the 13 editing sites of the lineage barcode (5) gradually decreases.

2. The high-precision and high-coverage phylogenetic tree tracing method according to claim 1, characterized in that: In step S1, the single-cell clone amplification time is 10 days.

3. The high-precision and high-coverage phylogenetic tree tracing method according to claim 1, characterized in that: In step S3, using high concentrations of antibiotics to screen for fusion genes is beneficial for screening cell clones with higher expression of fusion genes.

4. The high-precision and high-coverage phylogenetic tree tracing method according to claim 1, characterized in that: In step S3, observing the brightness of the green fluorescent protein gene is helpful in screening samples with higher expression of the fusion gene.

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