A tRNA 3' sequencing adapter with a recognition tag, its constructed library, and a method for analyzing aminoacylation levels.

Abstract

The present application belongs to the field of biotechnology and gene sequencing technology, and particularly relates to a tRNA 3' end sequencing adaptor with a recognition tag, a library constructed by the tRNA 3' end sequencing adaptor and an aminoacylation level analysis method. In the process of constructing the tRNA library, a T or G fixed recognition tag is introduced into the 3' end adaptor, a stable 3' end boundary mark is provided for each sequencing read without changing the existing tRNA library construction process, so that the accurate analysis of the real 3' end of the sequencing read is realized. After screening and end trimming of the read carrying the recognition tag, the interference of 3' end recognition noise on the tRNA aminoacylation level analysis can be significantly reduced, the CCA proportion calculation result is improved compared with the traditional adaptor system without introducing the recognition tag, and the tRNA end state analysis ability and data correction ability are stronger.

Description

Technical Field

[0001] This invention belongs to the fields of biotechnology and gene sequencing technology, specifically relating to a tRNA 3' end sequencing adapter with a recognition tag, a library constructed therefrom, and a method for analyzing aminoacylation levels. Background Technology

[0002] Transfer RNA (tRNA) is a class of non-coding RNA (ncRNA) widely distributed in organisms, accounting for approximately 10%–12% of total cellular RNA (DOI: 10.1038 / s41580-026-00963-3). During protein biosynthesis, mature tRNA is catalyzed by aminoacyl-tRNA synthetase to form aminoacyl-tRNA, which then enters the ribosome. Its anticodon pairs with the codon on messenger RNA (mRNA), accurately delivering the corresponding amino acid to the nascent polypeptide chain, thus achieving accurate translation of genetic information into a protein sequence. The copy number of tRNA genes varies among individuals, and tRNA abundance also varies widely among different cells and tissues. Research has found that, in addition to participating in classical protein translation, tRNA and its derived small RNAs (tRNA-derived small RNAs, tsRNAs) are also widely involved in translation regulation, cellular stress response, and various biological processes such as tumors and neurodegenerative diseases (DOI: 10.1093 / nar / gkx005).

[0003] tRNAs possess a highly conserved cloverleaf secondary structure and an inverted L-shaped tertiary structure, and also contain abundant post-transcriptional modifications, such as m 1 A、m 1 G, ac 4Modifications such as C and Ψ. The complex secondary structure and diverse modifications of tRNA can hinder reverse transcriptase elongation, causing problems such as incorrect base incorporation and premature termination of reverse transcription, thus making it difficult to obtain complete and accurate tRNA sequences. In addition, as a multi-copy gene, tRNA transcripts exhibit high sequence similarity, further increasing the difficulty of library construction and data analysis. To address these challenges, researchers have developed a series of tRNA sequencing methods in recent years. For example, Cozen et al. proposed ARM-seq (AlkB-facilitated RNA Methylation sequencing), the first tRNA sequencing method using demethylation modification as its core strategy (DOI: 10.1038 / nmeth.3508); Zheng et al. proposed DM-tRNA-seq (Demethylase-TGIRT sequencing), using heat-resistant Group II intron reverse transcriptase (TGIRT) for reverse transcription to achieve near-full-length reverse transcription (DOI: 10.1038 / nmeth.3478); Shigematsu et al. developed YAMAT-seq (Y-shaped Adapter-ligated MAture tRNA sequencing), which improved the ligation efficiency of mature tRNA adapters by designing Y-shaped double linkers, achieving full-length sequencing of mature tRNA (DOI: 10.1093 / nar / gkx005); and Behrens et al. developed mim-tRNAseq (modification-induced misincorporation sequencing). This method, combining full-length tRNA sequencing with a full-length tRNA library construction workflow, TGIRT reverse transcriptase, and accompanying bioinformatics analysis tools, can simultaneously analyze the expression abundance and modification status of mature tRNAs (DOI: 10.1016 / j.molcel.2021.01.028). In previous research (patent CN119876146A), our research group developed a high-throughput sequencing method for full-length tRNA with single-nucleotide precision, establishing a relatively efficient high-throughput full-length tRNA sequencing protocol.

[0004] Besides obtaining high-precision full-length tRNA expression profiles, tRNA aminoacylation level is another important biological functional indicator. Mature tRNA needs to maintain an intact 3' CCA tail structure and is catalyzed by aminoacyl-tRNA synthetase to connect with the corresponding amino acids. Only aminoacyl-tRNAs carrying amino acids can participate in protein biosynthesis. Therefore, quantifying the aminoacylation level of tRNA can directly reflect the proportion of functional tRNAs with translational activity in the cell. Evans et al. established a tRNA aminoacylation level analysis method based on DM-tRNA-seq (DOI: 10.1093 / nar / gkx514). This method utilizes the selective oxidation of the cis-diol structure at the 3' end of unaminoacylated tRNA by sodium periodate, while aminoacyl-tRNAs are protected by the ester bond formed between the adenosine and amino acid at the 3' end and do not undergo oxidation. Subsequently, combined with β-elimination treatment, unaminoacylated tRNA loses its terminal A and changes from CCA to CC, while aminoacylated tRNA retains its intact CCA end. Finally, by counting the number of tRNA reads at the CCA and CC ends, the aminoacylation level of different tRNAs can be calculated.

[0005] Therefore, it is necessary to design a tRNA 3' end sequencing adapter with a stable recognition tag. While ensuring efficient ligation of mature tRNA, this adapter provides a unified end recognition tag for the library, improves the resolution of reads from different tRNA 3' end structures, reduces the impact of end sequence heterogeneity on tRNA aminoacylation level analysis, and thus improves the accuracy and reproducibility of tRNA high-throughput sequencing results.

[0006] Although existing tRNA sequencing technologies can achieve high-throughput analysis of mature tRNA and aminoacylation levels, their accuracy depends on the complete preservation of the 3' end information during library construction. In Induro-tRNAseq technology (DOI: 10.1038 / s41467-025-56348-1), researchers further pointed out that the integrity of the 3' CCA end during library construction has become an important indicator for evaluating the quality of tRNA sequencing libraries. Since the terminal adenosine (A76) in the 3' CCA sequence of mature tRNA is the site of aminoacylation, protruding outside the three-dimensional structure of tRNA, it is more susceptible to degradation or processing during RNA extraction, library construction, and sequencing. Therefore, whether the CCA end in the library can be completely preserved directly affects the reliability of subsequent mature tRNA state analysis and aminoacylation level calculations. After periodic acid oxidation and β-elimination treatment, mature tRNA mainly exhibits two end forms: CCA or CC. However, in actual library construction and high-throughput sequencing, various factors such as sample processing, adapter ligation efficiency, ligase preference, partial RNA degradation, and sequencing accuracy can lead to the observation of other unexpected 3' end forms besides CCA and CC at the 3' end of sequencing reads. These situations increase the complexity of tRNA 3' end sequence identification and read classification, thereby affecting the accuracy and reproducibility of different tRNA aminoacylation levels and data analysis.

[0007] Therefore, the existing technology still has the following shortcomings:

[0008] (1) The 3' end information of mature tRNA is easily affected by various factors such as ligation efficiency, sample processing and sequencing process during library construction;

[0009] (2) The coexistence of CCA, CC and other unexpected 3' end structures in actual tRNA-seq sequencing data increases the difficulty of tRNA end recognition and read classification;

[0010] (3) Existing adapters lack tag designs for stable identification of the 3' end tRNA and adapter connection boundary, which is not conducive to the standardized processing of library end information. Summary of the Invention

[0011] The purpose of this invention is to address existing problems by providing a tRNA 3' end sequencing adapter with a recognition tag, a library constructed from it, and a method for analyzing aminoacylation levels.

[0012] This invention is achieved through the following technical solution:

[0013] In a first aspect, the present invention provides a tRNA 3' end sequencing adapter with a recognition tag, wherein the 3' end adapter is a single-stranded DNA oligonucleotide that comprises the following structure from the 5' end to the 3' end: recognition tag - random base - barcode sequence - universal sequence;

[0014] The identification tags are guanine (G) and thymine (T).

[0015] The random bases are 1 to 6 degenerate bases (N), preferably 2, to reduce linkage bias;

[0016] The barcode sequence is a specific sequence used to distinguish different samples;

[0017] The universal sequence is a sequence that can bind to primers used in sequencing platforms.

[0018] Furthermore, the sequence of the 3' end structure is shown in SEQ ID NO.1 or SEQ ID NO.2:

[0019] SEQ ID NO.1 (tML type): 5'-Phos-TNNGATGCATACAAGATCGGAAGAGCACACGTCTGAA-3'-ddC;

[0020] SEQ ID NO.2 (gML type): 5'-Phos-GNNGATGCATACAAGATCGGAAGAGCACACGTCTGAA-3'-ddC;

[0021] In this sequence, the first base T or G is the identification tag, NN is a random base, the italicized sequence is an exemplary barcode sequence, the rest is a universal sequence, 5'-Phos is a 5' end phosphorylation modification, and 3'-ddC is a 3' end dideoxycytidine modification.

[0022] This invention selects T and G as recognition tags because the natural 3' end sequence of the tRNA molecule (usually CCA) does not contain T and G bases. If A or C were used, it would be impossible to effectively distinguish whether the signal originates from the tRNA itself or the adapter tag, leading to tag recognition failure.

[0023] In a second aspect, the present invention provides a kit for constructing tRNA high-throughput sequencing libraries, the kit comprising a 3' adapter as described in the first aspect.

[0024] Thirdly, the present invention provides a method for analyzing tRNA aminoacylation levels, the method comprising the following steps:

[0025] (1) Extraction of tRNA samples: Total RNA is extracted from biological samples;

[0026] (2) Chemical treatment: The extracted total RNA was subjected to sodium periodate oxidation and β-elimination treatment to distinguish between aminoacylated tRNA (retaining CCA ends) and non-aminoacylated tRNA (converted to CC ends).

[0027] (3) Library construction: The processed product was purified by gel electrophoresis and the tRNA was recovered and enriched. Then, a high-throughput sequencing library was constructed using the 3' adapter as described in the first aspect.

[0028] The library construction steps include: 3' adapter ligation, 5' adapter ligation, reverse transcription, and PCR amplification;

[0029] (4) High-throughput sequencing: The constructed library is subjected to high-throughput sequencing to obtain sequencing reads;

[0030] (5) Data analysis, which includes:

[0031] a. Read selection: Based on the identification tag (T or G), the raw sequencing reads are selected and the reads containing the correct identification tag are retained;

[0032] b. Tag trimming: Remove the identified tag sequence from the selected read segments;

[0033] c. Sequence alignment: The pruned reads are aligned with a reference tRNA sequence database;

[0034] d. End statistics: Count the 3' end sequence of each tRNA alignment read, and calculate the aminoacylation level based on the number of reads with CCA (aminoacylated) or CC (unaminoacylated) ends.

[0035] Furthermore, step (5) also includes: evaluating the adapter ligation efficiency of the library construction by statistically analyzing the number of reads from the identification tags (T and G). When the trend of CCA ratio changes is consistent in the sequencing data of two independent libraries (using T-tag and G-tag adapters, respectively), it indicates that the results have higher reliability.

[0036] Fourthly, the present invention provides the use of the 3' adapter as described in the first aspect or the kit as described in the second aspect in the preparation of products for detecting tRNA aminoacylation levels.

[0037] The present invention has the following advantages over the prior art:

[0038] This invention establishes a complete quality control system from library construction to aminoacylation level analysis by introducing T and G molecular recognition tags into the 3' adapter of tRNA sequencing libraries. Without altering the existing tRNA library construction process, the following key technological breakthroughs have been achieved:

[0039] (1) It provides a quantitative evaluation index for the efficiency of library construction and connection, so that the quality of the library can be directly evaluated in the preliminary quality control analysis stage;

[0040] (2) By filtering and discarding untagged reads through T and G tags, the accuracy of the CCA ratio of tRNA in the library is effectively improved, providing a purer and more reliable data basis for downstream tRNA aminoacylation level analysis.

[0041] (3) The present invention is easy to operate and highly compatible, and has good promotional value and application prospects. Attached Figure Description

[0042] Figure 1 This is the library structure of the present invention;

[0043] Figure 2 This refers to the 3' terminal base composition after quality control;

[0044] Figure 3 The 3' end base composition after trimming tags from all read segments of the library;

[0045] Figure 4 The distribution of library read lengths;

[0046] Figure 5 The 3' end base composition of the tagged read segment after tagged trimming;

[0047] Figure 6 This is a comparison of documents with other documents.

[0048] Figure 7 Cytoplasmic tRNA coverage;

[0049] Figure 8 This represents the proportion of CCA at the 3' end of cytoplasmic tRNA. Detailed Implementation

[0050] To further explain the present invention, the following specific embodiments are described.

[0051] This invention designs two types of 3' linkers with sequences of 5'-Phos-TNNGATGCATACAAGATCGGAAGAGCACACGTCTGAA-3'-ddC (tML type) and 5'-Phos-GNNGATGCATACAAGATCGGAAGAGCACACGTCTGAA-3'-ddC (gML type); where T or G is an identification tag, N is a random base to reduce linkage bias, and the italicized portion is a barcode sequence. The constructed library structure is as follows. Figure 1 As shown.

[0052] It should be noted that the reason why T and G were chosen as identification tags, rather than A or C, is based on the sequence characteristics of the 3' end of the tRNA molecule. If A or C were used as adapter tags, it would be impossible to effectively distinguish whether the signal originated from the terminal bases of the tRNA itself or from the adapter tag in the sequencing data, resulting in tag identification failure. T and G are not natural constituent bases of the 3' end of tRNA. Using them as identification tags can achieve clear distinction from the tRNA sequence itself. At the same time, the two tags, T and G, can be mutually verified in the same data analysis process, further improving the reliability of tag identification.

[0053] This invention uses the African green monkey kidney cell line as the research object and sets up two library construction groups: a tML library constructed using a T-tag 3' adapter and a gML library constructed using a G-tag 3' adapter; both libraries were constructed using the same library construction procedure. Subsequently, the libraries were sequenced using the Illumina high-throughput sequencing platform. By statistically analyzing the 3' end sequence base composition of each library and combining it with tRNA aminoacylation level analysis, the quality of tML and gML libraries, adapter ligation ratio, and aminoacylation level were evaluated and compared, demonstrating the feasibility and effectiveness of the method for tRNA library quality assessment and aminoacylation level analysis based on 3' T and G recognition tags. The advantages of this method for adapter optimization are as follows:

[0054] 1. By introducing T and G molecular recognition tags into the 3' adapter, the real tRNA ligation product is given a distinguishable terminal feature sequence, thereby enabling accurate differentiation and quantification of reads during the sequencing data analysis stage;

[0055] 2. The introduction of T and G tags does not change the main steps of the existing tRNA library construction process. It can provide endogenous evaluation indicators of library quality without increasing additional experimental costs. The efficiency of adapter ligation and the quality of library construction can be directly reflected by the statistics of the proportion of T and G tag reads.

[0056] 3. The combined use of T and G tags with tRNA aminoacylation level analysis can improve the quantification of tRNA aminoacylation levels.

[0057] Example 1: Construction of tRNAseq library

[0058] African green monkey kidney cell line was selected as the experimental sample, and the tRNA library was prepared according to the tRNA library construction procedure of patent (CN119876146A). First, total RNA was extracted using the TRIzol method, followed by oxidation and β-elimination. tRNA molecules ranging from 60 to 100 nt in length were separated by gel electrophoresis, and then demethylation and 3' and 5' end repair were performed. Next, a 3' adapter carrying a T or G molecular recognition tag designed in this invention was ligated to the 3' end of the tRNA molecule. After gel purification and recovery of the ligation product, a 5' adapter was ligated to the 5' end, and full-length cDNA was synthesized using Induro reverse transcriptase. The library was then enriched by PCR amplification. The primer sequences used are shown in Table 1. The amplification product was purified and recovered by 10% TBE-PAGE gel electrophoresis, thus completing the construction of a high-quality tRNA-seq library suitable for the Illumina high-throughput sequencing platform.

[0059] Table 1 PCR primer sequences

[0060] P5 primer 5'-AATGATACGGCGACCACCGAGATCTACACTGTTCCTACACTCTTTCCCTACACGACGCTCTTCCGATC*T-3' P7 primer_tML 5'-CAAGCAGAAGACGGCATACGAGATGATCTGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATC*T-3' P7 primer_gML 5'-CAAGCAGAAGACGGCATACGAGATTCAAGTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATC*T-3'

[0061] Note: "*" indicates modification of the thiophosphate bond.

[0062] Example 2: Data Analysis Process

[0063] Quality control was performed on the raw data from the PCR machine: adapter sequences, random bases, and short fragments were removed, while T and G recognition tags on the adapter sequences were retained. For the processed reads, the last base of the 3' end of each read was extracted, and the proportion of reads with a 3' end ending in T in the tML library and G in the gML library was calculated to evaluate the ligation efficiency of T and G tags. Subsequently, the cutadapt software was used to trim reads with a last base ending in T in the tML library and to trim reads with a last base ending in G in the gML library, obtaining clean tRNA reads with the true 3' end. Two analysis methods were employed: one retaining reads without recognition tags and the other retaining only reads with recognition tags. The "mim-tRNAseq" software package was used for systematic downstream analysis. Specific analysis included: aligning the reads with the tRNA annotation sequences of the African green monkey (Chlorocebus sabaeus) reference genome, and calculating the unique alignment rate, multiple alignment rate, and non-alignment rate. Full-length tRNA coverage analysis was performed using a uniquely aligned read. Furthermore, the 3' end configuration of each tRNA was analyzed based on the alignment results, and the aminoacylation level of tRNA was assessed using the CCA ratio. The CCA ratio calculation formula was determined according to the mim-tRNAseq criteria as follows:

[0064]

[0065] Example 3: Experimental Results and Effect Analysis

[0066] Table 2 shows the data quality control results of tML and gML samples constructed using this method. Both the original data and the final tRNA read count reached the millions, indicating high sequencing depth. Specifically, the number of 3' adapter reads in the tML library accounted for approximately 51.8% of the original data, while the number of 3' adapter reads in the gML library accounted for approximately 85.4%. Based on this metric, the ligation efficiency of 3' adapters carrying the T tag may be slightly lower than that carrying the G tag.

[0067] Table 2 Data for tML and gML

[0068] sample Original number of segments read Connect 3' connector to read segment number Number of segments read after quality control Number of tagged segments tML 7,768,313 4,026,132 3,513,800 2,918,697 gML 7,162,957 6,117,315 5,687,551 5,480,680

[0069] Note: The number of reads connecting the 3' adapter refers to the number of reads that are identified and retained by the adapter core sequence through cutadapt; the number of reads after quality control refers to the number of reads after removing random bases and short fragments.

[0070] The 3' end base composition of the two samples is as follows Figure 2 As shown, the 3' end bases of both libraries consisted of five types: A, C, G, T, and N. In the tML library, T was the predominant 3' end base, accounting for 83.1%, while A, C, G, and N accounted for 4.4%, 9.7%, 2.8%, and <0.1%, respectively. In the gML library, G was the predominant 3' end base, accounting for 96.4%, while A, C, T, and N accounted for 1.6%, 1.4%, 0.7%, and <0.1%, respectively. These results indicate that both T and G recognition tags were successfully ligated to the 3' end of the tRNA, and the proportion of unexpected tags in the gML library was lower than that in the tML library, suggesting that the G tag may have a lower non-specific ligation background.

[0071] Tags were pruned from tagged reads, while reads without T or G identification tags were retained. The 3' end base composition of each library was analyzed, such as... Figure 3 As shown, the proportion of N in both libraries is less than 0.1%. At this point, the library structure is equivalent to the unoptimized 3' adapter structure. The 3' ends of both libraries are predominantly A bases, consistent with the CCA end characteristics of mature tRNA. Read length distribution is as follows... Figure 4 As shown, the peak values ​​are all at 76bp, which is consistent with the characteristics of mature full-length tRNA.

[0072] Tag-tipped libraries are pruned, and untagged reads are discarded. The 3' end base composition of the library is as follows: Figure 5 As shown, it can be seen that compared to Figure 3Although the tML library discarded 16.9% of the reads and the gML library discarded 3.6% of the reads, the proportion of A bases in both libraries increased. Since the present invention performed oxidation and β-elimination treatments during library construction, the high proportion of A bases reflects that most tRNAs in the cell exist in the form of aminoacyl-tRNAs carrying amino acids. This indicates that the terminal bases are further concentrated in the CCA terminal feature of mature tRNAs, proving the necessity of designing a 3' end recognition tag.

[0073] The alignment of tML and gML data to the reference tRNA sequence of African green monkeys is as follows: Figure 6 As shown, cytoplasmic tRNA coverage is as follows Figure 7 As shown, the unique alignment rate of the tML library was 68%, and that of the gML library was 75%. The coverage curves were relatively flat, indicating high coverage from 5' to 3', allowing for the acquisition of full-length tRNA molecules. These results demonstrate that both tML and gML libraries exhibit good construction quality. A comparison was made between two data processing strategies: retaining all reads after trimming T and G tags, and discarding tag-free reads. The results showed no significant difference in alignment rate or coverage between the two strategies. Therefore, discarding tag-free reads before quantification is an effective strategy to improve library purity and quantification accuracy without sacrificing tRNA detection sensitivity.

[0074] After comparing whether unlabeled data was discarded, the proportion of terminal CCA of cytoplasmic tRNAs in the library was analyzed, and the results are as follows: Figure 8 As shown, in the tML library, the overall CCA ratio was 61.98% when all reads were retained, while the CCA ratio increased to 72.44% after discarding reads without T tags, an increase of 10.46 percentage points. In the gML library, the overall CCA ratio was 83.58% when all reads were retained, while the CCA ratio increased to 84.70% after discarding reads without G tags, an increase of 1.12 percentage points. Further stratification analysis according to the amino acid isotypes carried by tRNAs showed that the CCA ratio of almost all isotypes increased after discarding reads without tags. This significant increase in aminoacylation levels in the tML library demonstrates that when there are many self-ligated or non-specific ligation products in the library, T or G tag screening can effectively remove this background noise and significantly improve the accuracy of downstream aminoacylation level analysis. Therefore, the T or G tags described in this invention are not only suitable for libraries with ideal ligation efficiency, but also play a key role in cases of poor ligation or low library quality, providing a reliable data quality control method for tRNA aminoacylation level analysis.

[0075] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A tRNA 3' adapter with a recognition tag, characterized in that, The 3' adapter is a single-stranded DNA, which contains an identification tag, random bases, a barcode, and a universal sequence from the 5' end to the 3' end; The identification tag is either G or T.

2. The tRNA 3' adapter according to claim 1, characterized in that, The random bases are 1 to 6 degenerate bases N.

3. The tRNA 3' adapter according to claim 1, characterized in that, The sequence of the 3' end connector is shown in SEQ ID NO.1 or SEQ ID NO.

2.

4. A kit for constructing tRNA high-throughput sequencing libraries, characterized in that, The kit contains a 3' end connector as described in any one of claims 1 to 3.

5. A method for analyzing tRNA aminoacylation levels, characterized in that, The method includes the following steps: (1) Using the 3' adapter as described in any one of claims 1 to 3, construct a high-throughput sequencing library from tRNA samples that have undergone oxidation and β-elimination treatment; (2) Sequencing the constructed library to obtain sequencing reads; (3) Data analysis, which includes: screening sequencing reads based on the identification tags and calculating the proportion of CCA-terminal reads to calculate the tRNA aminoacylation level.

6. The method according to claim 5, characterized in that, The data analysis also includes: evaluating the linker efficiency of the library construction by statistically analyzing the number of read segments identified by tags T and G.

7. The method according to claim 5, characterized in that, The data analysis also includes: discarding read segments that do not contain the identification tag, and only comparing and performing subsequent quantitative analysis on read segments that contain the identification tag.

8. The method according to claim 5, characterized in that, The library construction steps include: 3' adapter ligation, 5' adapter ligation, reverse transcription, and PCR amplification.

9. The use of the 3' end adapter as described in any one of claims 1 to 3 or the kit as described in claim 4 in the preparation of a product for detecting tRNA aminoacylation levels.

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