Ribo-seq-based method and system for analyzing HBV protein translation level

Abstract

The invention provides a Ribo-seq-based method and a Ribo-seq-based system for analyzing an HBV protein translation level, and belongs to the technical field of bioinformatics and virology. The method comprises the following steps: constructing a linear HBV reference genome sequence and optimizing a starting point of the linear HBV reference genome sequence; the Ribo-seq sequencing data is compared to a linear HBV reference genome sequence, and a P-site signal of each nucleotide position is obtained; separating the P-site signals according to the reading frames to obtain respective signal intensity distribution of the reading frames; calculating the median signal density and the signal leakage rate of the protein in the pure region of the HBV protein; correcting the observation signal of the target reading frame in the mixing region of the overlapping protein; and outputting the corrected translation signal intensity of the HBV protein. By adopting the Ribo-seq-based method and system for analyzing the HBV protein translation level, the HBV protein translation level can be accurately quantified.

Description

Technical Field

[0001] This invention relates to the fields of bioinformatics and virology, and in particular to a method and system for analyzing HBV protein translation levels based on Ribo-seq. Background Technology

[0002] Ribosomal sequencing (Ribo-seq) is a high-throughput sequencing technology that captures intracellular mRNA fragments (RPFs) being translated with single-nucleotide precision and identifies translational activity by inferring the location of ribosome P-sites. In typical eukaryotic genes, the translation region usually exhibits a distinct "trinucleotide periodicity" signal, meaning that the signal is enriched at the first nucleotide of the codon, forming a "high-low-low" periodic pattern. This periodicity is a key feature distinguishing true translation from background noise and is the core basis for existing Ribo-seq analysis tools (such as RiboWave) to identify translation events and quantify translation efficiency.

[0003] However, the hepatitis B virus (HBV) genome has a unique structure. Its approximately 3.2 kb circular DNA contains four main, overlapping genes located in different open reading frames (ORFs), encoding the core protein (C), polymerase protein (P), surface antigen (S), and X protein, respectively. Figure 1 These ORFs are located in different reading frames and share parts of the RNA sequence, leading to the possibility of multiple translation events occurring simultaneously on the same nucleic acid sequence. This signal superposition caused by multiplexed, frameshift translation completely masks and disrupts the trinucleotide periodicity unique to a single translation event, rendering traditional Ribo-seq analysis tools, which rely on finding a single dominant periodicity, completely ineffective. They cannot distinguish which reading frame is the actual translation, nor can they accurately quantify the translation level of each overlapping protein. Figure 2 ).

[0004] Existing Ribo-seq analysis methods are typically based on the assumption that "one coding region corresponds to one dominant periodicity," which cannot handle the mixed signals caused by multiple and frameshift translation in HBV. Therefore, traditional tools often fail when analyzing HBV data, unable to accurately identify the reading frames of each ORF, let alone quantify the translation levels of overlapping proteins, which greatly limits in-depth research on the regulatory mechanisms of HBV translation.

[0005] Therefore, there is an urgent need in this field for a Ribo-seq data analysis method and system that can effectively separate HBV overlapping translation signals and accurately analyze HBV protein translation activity. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for analyzing HBV protein translation levels based on Ribo-seq. By constructing an optimized linear HBV reference genome sequence and based on median signal density, signal leakage rate, and signal-to-noise ratio, the invention achieves accurate separation of mixed Ribo-seq signals, thereby outputting independent and accurate translation signal intensities for HBV proteins. This not only significantly improves the accuracy and reliability of overlapping translation signal analysis but also provides an effective tool for in-depth research on HBV translation regulation mechanisms and the development of antiviral drugs.

[0007] To achieve the above objectives, this invention provides a method for analyzing HBV protein translation levels based on Ribo-seq, comprising the following steps: Step S1: Construct a linear HBV reference genome sequence and optimize its starting point; Step S2: Align the Ribo-seq sequencing data to the linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; according to the reading frame assignment of each nucleotide position on the linear HBV reference genome sequence, separate the P-site signal into three reading frames to obtain the signal intensity distribution of each of the three reading frames. Step S3: For each HBV protein, within a pure region on its genome that encodes only a single protein, calculate the median signal density of the protein and its signal leakage rate to other reading frames based on the signal intensity distribution of the three reading frames. Step S4: In the mixed region of overlapping proteins, for the target reading frame at the target nucleotide position, perform: The P-site signal on the target reading frame at this location is used as the observation signal; Based on the median signal density and signal leakage rate, the expected signal of the target protein and the expected interference noise of overlapping proteins are estimated, and the signal-to-noise ratio is calculated. The signal correction strategy is selected based on the ratio of signal-to-noise ratio to a preset threshold to correct the observed signal; Step S5: Output the corrected translation signal intensity of HBV protein.

[0008] Preferably, in step S2, for any nucleotide position, its corresponding reading frame is: ; in, This indicates a reading box. Indicates any nucleotide position. This indicates the modulo operation.

[0009] Preferably, in step S3, the formula for calculating the signal leakage rate is: ; in, Indicates the signal leakage rate. This indicates the main reading box. Indicates other reading boxes, This refers to a pure region on the genome that encodes only a single protein. Indicates any nucleotide position The observed signal.

[0010] Preferably, in step S4, the formula for calculating the signal-to-noise ratio is: ; ; ; in, This indicates the expected signal for target protein A. Indicates the codon length of the overlapping region A. This represents the median signal density of target protein A. This represents the expected interference noise of overlapping protein B. This indicates the mixing region of overlapping proteins. Indicates any nucleotide position in the reading frame of overlapping protein B. The observed signal, This indicates the signal leakage rate from overlapping protein B to target protein A. This indicates the signal-to-noise ratio.

[0011] Preferably, in step S4, the signal correction strategy includes: When the signal-to-noise ratio is greater than or equal to the preset threshold, interference noise is directly subtracted for signal correction. ; When the signal-to-noise ratio is less than a preset threshold, a density estimation method is used for signal correction. ; in, Indicates the signal after correction. This indicates any nucleotide position within the reading frame of target protein A. The observed signal, The Poisson distribution represents the median signal density of target protein A.

[0012] Preferably, the HBV protein includes at least one of the following: core protein, polymerase protein, surface antigen protein, and X protein.

[0013] This invention also provides a system for analyzing HBV protein translation levels based on Ribo-seq, comprising: The data input module is used to construct a linear HBV reference genome sequence and optimize its starting point; The signal separation module is used to align Ribo-seq sequencing data to a linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; based on the reading frame assignment of each nucleotide position in the linear HBV reference genome sequence, the P-site signal is separated into three reading frames to obtain the signal intensity distribution of each of the three reading frames. The baseline modeling module is used to calculate the median signal density of each HBV protein and its signal leakage rate to other reading frames based on the signal intensity distribution of three reading frames within a pure region on its genome that encodes only a single protein. The signal correction module is used to correct the observed signal of the target reading frame in the mixed region of overlapping proteins based on the median signal density and signal leakage rate. The output module is used to output the corrected translation signal intensity of the HBV protein.

[0014] Preferably, the signal correction module includes: The signal observation unit uses the P-site signal on the target reading frame at the target nucleotide position as the observation signal; The signal-to-noise ratio (SNR) analysis unit estimates the expected signal of the target protein and the expected interference noise of overlapping proteins based on the median signal density and signal leakage rate, and calculates the SNR. The signal correction strategy execution unit selects a signal correction strategy based on the ratio of the signal-to-noise ratio to a preset threshold and corrects the observed signal.

[0015] Therefore, the present invention employs the above-mentioned method and system for analyzing HBV protein translation levels based on Ribo-seq, and the beneficial technical effects are as follows: (1) By constructing an optimized linear HBV reference genome sequence and combining median signal density, signal leakage rate and signal-to-noise ratio, this invention can effectively separate the mixed Ribo-seq signals of multiple overlapping HBV ORFs, breaking through the limitations of traditional methods and realizing independent and accurate quantification of HBV protein translation level.

[0016] (2) The signal correction strategy is selected based on the ratio of signal-to-noise ratio to preset threshold. This not only ensures direct denoising in strong signal regions, but also allows for robust density estimation in weak signal regions, improving the adaptability of the algorithm and providing technical support for the study of HBV translation regulation mechanism and the development of antiviral drugs. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the open reading frame of HBV protein in the background art; Figure 2The images show sequencing signal diagrams of conventional Ribo-seq and Ribo-seq with double reading frameshift translation in the background technology. Figure 3 This example compares and evaluates the error between the Ribo-seq simulated signal decomposition prediction results and the actual translated signal intensity of the HBV protein translatome in Example 1. Figure 3 In this context, A represents the comparison between the actual signal strength of each open reading frame and the decomposed corrected signal strength. Figure 3 In this context, B represents the error of the decomposed correction signal for each open reading frame; Figure 4 The image shows the signal intensity distribution of the Ribo-seq simulated signal and the decomposed predicted signal of the HBV protein translatome in Example 1. Figure 4 In this context, A represents the original signal (analog). Figure 4 B in the equation represents the decomposition correction signal; Figure 5 This is a distribution diagram of the raw sequencing signal and decomposed signal from the Ribo-seq sequencing results of Huh7.5.1 cells transfected with PrcccDNA plasmid in Example 1. Figure 5 In this context, A represents the original HBV translation signal. Figure 5 B in the equation represents the decomposition correction signal. Detailed Implementation

[0018] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0020] Example 1 A method for analyzing HBV protein translation levels based on Ribo-seq includes the following steps: Step S1: Construct a linear HBV reference genome sequence and optimize its starting point.

[0021] Using a linear HBV reference genome sequence of the same length as the genome (1X), rather than an excessively long linear HBV reference genome sequence (such as 1.2X or 2X) that would lead to serious multiple alignment problems, fundamentally avoids the ambiguity of signal origin. Traditionally, using the EcoRI restriction site as the starting point truncates the ORFs of polymerase protein (P) and surface antigen (S) proteins. This invention selects 1801 nt (using HBV ayw strain as an example) as the new starting point for the linear HBV reference genome sequence, optimizing the position to maintain the integrity of the major overlapping open reading frames while avoiding multiple alignments. In this optimized linear HBV reference genome sequence, the translation signals of the three major proteins—core protein (C), polymerase protein (P), and surface antigen (S)—are all intact, with only a slight truncation of the X protein (X), representing an optimized trade-off to ensure overall analytical accuracy.

[0022] Step S2: Align the Ribo-seq sequencing data to the linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; according to the reading frame assignment of each nucleotide position on the linear HBV reference genome sequence, separate the P-site signal into three reading frames to obtain the signal intensity distribution of each of the three reading frames.

[0023] For any nucleotide position, its corresponding reading frame is: ; in, This indicates a reading box. Indicates any nucleotide position. This indicates the modulo operation.

[0024] Step S3: For each HBV protein, within a pure region on its genome that encodes only a single protein, calculate the median signal density of the protein and its signal leakage rate to other reading frames based on the signal intensity distribution of the three reading frames.

[0025] (1) Median signal density: represents the typical translation efficiency of the protein under interference-free conditions.

[0026] (2) Signal leakage rate: This is obtained by calculating the ratio of the signals from other reading frames in the "clean region" to the signal from the main reading frame. For example, for a main reading frame... The protein, which travels to other reading frames The formula for calculating the leakage rate is: ; in, Indicates the signal leakage rate. This indicates the main reading box. Indicates other reading boxes, This refers to a pure region on the genome that encodes only a single protein. Indicates any nucleotide position The observed signal.

[0027] Step S4: In the mixed region of overlapping proteins (encoding multiple proteins), for the target reading frame at the target nucleotide position, perform the following operations: (1) The P-site signal on the target reading frame at this location is taken as the observation signal.

[0028] ; in, This represents the true translation signal of the C protein. This represents the true translation signal of the P protein. This indicates signal leakage. This indicates background noise.

[0029] (2) Estimate the expected signal of target protein A based on median signal density and signal leakage rate. And the expected interference noise from overlapping protein B .

[0030] ; ; in, This indicates the expected signal for target protein A. Indicates the codon length of the overlapping region A. This represents the median signal density of target protein A. This represents the expected interference noise of overlapping protein B. This indicates the mixing region of overlapping proteins. Indicates any nucleotide position in the reading frame of overlapping protein B. The observed signal, This represents the signal leakage rate from overlapping protein B to target protein A.

[0031] (3) Calculate the signal-to-noise ratio.

[0032] ; in, This indicates the signal-to-noise ratio.

[0033] (4) Based on the ratio of signal-to-noise ratio to a preset threshold, a signal correction strategy is selected to correct the observed signal of each reading frame. Preset threshold The user can decide for themselves; the default value in this embodiment is 3.

[0034] Signal correction strategies include: 1) When When the signal is strong enough, it indicates that the target signal is strong enough to be corrected by directly subtracting interference noise.

[0035] ; in, Indicates the signal after correction. This indicates any nucleotide position within the reading frame of target protein A. The observed signal.

[0036] 2) When When the signal is weak, a more robust density estimation method should be used for signal correction.

[0037] ; in, The Poisson distribution represents the median signal density of target protein A.

[0038] Step S5: Output the corrected translation signal intensity of HBV protein.

[0039] The invention will be further illustrated below with specific examples.

[0040] To verify the accuracy of the algorithm of this invention, a computational model capable of generating HBV Ribo-seq simulated data was constructed. This is existing technology and will not be described in detail here. The model can preset the actual translation signal intensity of each protein and introduce various random perturbations such as signal attenuation, local bursts, signal leakage, and background noise.

[0041] In multiple independent simulation tests, different simulated signals were tested, including nine different scenarios: average expression of four proteins, high C expression, high P expression, high S expression, high X expression, low C expression, low P expression, low S expression, and low X expression. As shown in Table 1, the error of each protein signal level separated and estimated by the process of this invention compared with the preset real signal level was consistently controlled within ±25%. Figure 3 , Figure 4 As shown, the simulation results strongly demonstrate that even under extreme conditions of severe signal overlap and high noise, the algorithm of this invention can still reliably decompose and accurately quantify the translation levels of individual HBV proteins.

[0042] Table 1. Error levels of HBV simulated Ribo-seq signal decomposition and protein translation level estimation at different expression levels. ;

[0043] To verify the application value of this invention in real biological samples, the GSE135860 dataset (Ribo-seq data of Huh7.5.1 cells transfected with HBV cccDNA plasmid) was downloaded from the public database GEO.

[0044] After preprocessing the raw data, it is applied to the model in this embodiment. For example... Figure 5 As shown, the results demonstrate that this embodiment successfully separated the original, highly mixed, and uninterpretable translation signal into four proteins: the core protein (C), polymerase protein (P), surface antigen (S), and X protein (X) of HBV, revealing their respective independent translation maps with clear trinucleotide periodicity.

[0045] The results of this preclinical data analysis demonstrate that the method in this embodiment is effective and can accurately analyze real and complex biological sample data, which is impossible with traditional analysis methods.

[0046] Example 2 Systems based on Ribo-seq for analyzing HBV protein translation levels include: (1) Data input module, used to construct a linear HBV reference genome sequence and optimize its starting point.

[0047] (2) Signal separation module, used to align Ribo-seq sequencing data to the linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; according to the reading frame assignment of each nucleotide position on the linear HBV reference genome sequence, the P-site signal is separated into three reading frames to obtain the signal intensity distribution of each of the three reading frames.

[0048] (3) Benchmark modeling module, used for each HBV protein, to calculate the median signal density of the protein and its signal leakage rate to other reading frames based on the signal intensity distribution of the three reading frames in a pure region on its genome that encodes only a single protein.

[0049] (4) A signal correction module, used to correct the observed signal of the target reading frame in the mixed region of overlapping proteins based on the median signal density and signal leakage rate; specifically including the following units: The signal observation unit uses the P-site signal at the target nucleotide position within the target reading frame as the observation signal.

[0050] The signal-to-noise ratio (SNR) analysis unit estimates the expected signal of the target protein and the expected interference noise of overlapping proteins based on the median signal density and signal leakage rate, and calculates the SNR.

[0051] The signal correction strategy execution unit selects a signal correction strategy based on the ratio of the signal-to-noise ratio to a preset threshold and corrects the observed signal.

[0052] (5) Output module, used to output the translation signal intensity of the HBV protein after correction.

[0053] It is worth noting that all contents not described in detail in this invention are existing technologies and are well known to those skilled in the art.

[0054] Therefore, this invention employs the aforementioned method and system for analyzing HBV protein translation levels based on Ribo-seq. By constructing an optimized linear HBV reference genome sequence and based on median signal density, signal leakage rate, and signal-to-noise ratio, it achieves precise separation of mixed Ribo-seq signals, thereby outputting independent and accurate translation signal intensities for HBV proteins. This not only significantly improves the accuracy and reliability of overlapping translation signal analysis but also provides an effective tool for in-depth research on HBV translation regulation mechanisms and the development of antiviral drugs.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for analyzing HBV protein translation levels based on Ribo-seq, characterized in that, Includes the following steps: Step S1: Construct a linear HBV reference genome sequence and optimize its starting point; Step S2: Align the Ribo-seq sequencing data to the linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; according to the reading frame assignment of each nucleotide position on the linear HBV reference genome sequence, separate the P-site signal into three reading frames to obtain the signal intensity distribution of each of the three reading frames. Step S3: For each HBV protein, within a pure region on its genome that encodes only a single protein, calculate the median signal density of the protein and its signal leakage rate to other reading frames based on the signal intensity distribution of the three reading frames. Step S4: In the mixed region of overlapping proteins, for the target reading frame at the target nucleotide position, perform: The P-site signal on the target reading frame at this location is used as the observation signal; Based on the median signal density and signal leakage rate, the expected signal of the target protein and the expected interference noise of overlapping proteins are estimated, and the signal-to-noise ratio is calculated. The signal correction strategy is selected based on the ratio of signal-to-noise ratio to a preset threshold to correct the observed signal; Step S5: Output the corrected translation signal intensity of HBV protein.

2. The method for analyzing HBV protein translation levels based on Ribo-seq according to claim 1, characterized in that, In step S2, for any nucleotide position, its corresponding reading frame is: ； in, This indicates a reading box. Indicates any nucleotide position. This indicates the modulo operation.

3. The method for analyzing HBV protein translation levels based on Ribo-seq according to claim 1, characterized in that, In step S3, the formula for calculating the signal leakage rate is: ； in, Indicates the signal leakage rate. This indicates the main reading box. Indicates other reading boxes, This refers to a pure region on the genome that encodes only a single protein. Indicates any nucleotide position The observed signal.

4. The method for analyzing HBV protein translation levels based on Ribo-seq according to claim 3, characterized in that, In step S4, the formula for calculating the signal-to-noise ratio is: ； ； ； in, This indicates the expected signal for target protein A. Indicates the codon length of the overlapping region A. This represents the median signal density of target protein A. This represents the expected interference noise of the overlapping protein B. This indicates the mixing region of overlapping proteins. Indicates any nucleotide position in the reading frame of overlapping protein B. The observed signal, This indicates the signal leakage rate from overlapping protein B to target protein A. This indicates the signal-to-noise ratio.

5. The method for analyzing HBV protein translation levels based on Ribo-seq according to claim 4, characterized in that, In step S4, the signal correction strategy includes: When the signal-to-noise ratio is greater than or equal to the preset threshold, interference noise is directly subtracted for signal correction. ； When the signal-to-noise ratio is less than a preset threshold, a density estimation method is used for signal correction. ； in, Indicates the signal after correction. This indicates any nucleotide position within the reading frame of target protein A. The observed signal, The Poisson distribution represents the median signal density of target protein A.

6. The method for analyzing HBV protein translation levels based on Ribo-seq according to claim 1, characterized in that, HBV proteins include at least one of the following: core protein, polymerase protein, surface antigen protein, and X protein.

7. A system for analyzing HBV protein translation levels based on Ribo-seq, characterized in that, Performing the method for resolving HBV protein translation levels based on Ribo-seq as described in any one of claims 1 to 6, comprising: The data input module is used to construct a linear HBV reference genome sequence and optimize its starting point; The signal separation module is used to align Ribo-seq sequencing data to a linear HBV reference genome sequence to obtain the P-site signal at each nucleotide position; based on the reading frame assignment of each nucleotide position in the linear HBV reference genome sequence, the P-site signal is separated into three reading frames to obtain the signal intensity distribution of each of the three reading frames. The baseline modeling module is used to calculate the median signal density of each HBV protein and its signal leakage rate to other reading frames based on the signal intensity distribution of three reading frames within a pure region on its genome that encodes only a single protein. The signal correction module is used to correct the observed signal of the target reading frame in the mixed region of overlapping proteins based on the median signal density and signal leakage rate. The output module is used to output the corrected translation signal intensity of the HBV protein.

8. The system for analyzing HBV protein translation levels based on Ribo-seq according to claim 7, characterized in that, The signal correction module includes: The signal observation unit uses the P-site signal on the target reading frame at the target nucleotide position as the observation signal; The signal-to-noise ratio (SNR) analysis unit estimates the expected signal of the target protein and the expected interference noise of overlapping proteins based on the median signal density and signal leakage rate, and calculates the SNR. The signal correction strategy execution unit selects a signal correction strategy based on the ratio of the signal-to-noise ratio to a preset threshold and corrects the observed signal.

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