Method for detecting expression quantity of porcine circular RNA circTCP1 and application

Abstract

The invention relates to a method for detecting the expression quantity of porcine circular RNA circTCP1, and belongs to the technical field of molecular biological detection. The technical problem to be solved by the method is to accurately detect the expression quantity of the circular RNA circTCP1 of the pig and judge the physiological status of the pig according to the expression quantity of the circular RNA circTCP1 of the pig. According to the technical scheme, the method is characterized by comprising the following steps: extracting total RNA (Ribonucleic Acid) from a pig tissue or cell sample, performing RNase R digestion treatment, performing reverse transcription on digested and undigested RNA to obtain cDNA (Complementary Deoxyribonucleic Acid), performing PCR (Polymerase Chain Reaction) amplification by using a specific primer, performing quantitative analysis by using a real-time fluorescent quantitative PCR technology, performing normalization treatment by using a reference gene to obtain the relative expression quantity of circTCP1, and comparing the relative expression quantity with a normal range to judge the physiological status of the pig. The method is mainly used for evaluating porcine reproductive performance and the like.

Description

Technical Field

[0001] This invention belongs to the field of molecular biology detection technology, specifically relating to a method for detecting the expression level of porcine circular RNA circTCP1 and judging the physiological state of pigs accordingly. Background Technology

[0002] In the field of molecular biology research on pigs, the accurate detection of circular RNA (circRNA), a class of non-coding RNAs with closed circular structures, is crucial for revealing the regulatory mechanisms of pig physiological states. However, current technologies face several challenges in detecting the expression level of porcine circTCP1: Firstly, the circular structure of circRNA allows it to coexist with linear RNA in samples, and conventional RNA extraction and detection methods struggle to specifically distinguish between the two, leading to detection results that are easily interfered with by linear RNA and cannot accurately reflect the true expression level of circTCP1. Secondly, in the RNA quality control stage, the lack of systematic purity and integrity testing standards can reduce the reliability of subsequent reverse transcription and PCR amplification steps, thus affecting the accuracy of expression level data.

[0003] Existing methods for assessing pig physiological status using circRNA expression levels have significant limitations. Due to the complexity of the pig's physiological regulatory network, relying solely on traditional linear RNA detection indicators is insufficient to comprehensively reflect the organism's true state. Furthermore, research on the association between circRNAs, as novel regulatory molecules, and physiological status is still in its early stages. Current technologies have failed to establish an effective correlation model between circRNA expression levels and pig physiological status, making it impossible to accurately infer the pig's physiological condition based on circRNA expression levels. This is particularly problematic in important applications such as reproductive performance assessment, where the lack of molecular marker-assisted methods based on circRNA expression levels hinders the precise screening of economic traits such as high litter size.

[0004] Furthermore, at the level of experimental data processing and analysis, existing technologies lack standardized procedures for quantifying circRNA expression levels. For example, in real-time quantitative PCR, inappropriate selection of internal reference genes or non-standardized design of replicate experiments can lead to significant data errors and poor reproducibility, making it difficult to obtain reliable expression level analysis results. Simultaneously, the lack of unified data analysis and storage standards makes it difficult to comprehensively compare data from different batches, limiting the application of circRNA expression level data in long-term monitoring of pig physiological status. These problems essentially stem from insufficient understanding of the structural characteristics and regulatory mechanisms of circRNAs, as well as the limitations of existing detection techniques, resulting in difficulties such as low detection accuracy, unsystematic correlation analysis, and poor data reliability when addressing the technical challenges of assessing pig physiological status through circRNA expression levels. Summary of the Invention

[0005] One object of the present invention is to solve at least the above-mentioned problems and to provide at least the advantages that will be described later.

[0006] Another objective of this invention is to provide a method for detecting the expression level of porcine circular RNA circTCP1, which can accurately detect the expression level of porcine circular RNA circTCP1 and thereby determine the physiological state of pigs.

[0007] To achieve these objectives and other advantages according to the present invention, a method for detecting the expression level of porcine circular RNA circTCP1 is provided, comprising the following steps: First, total RNA was extracted from pig tissue or cell samples. The obtained RNA samples were resuspended in DEPC water. The resuspended RNA samples were divided into two equal parts. One part was digested with RNase R, and the other part was used as a control. After digestion, phenol-chloroform-isoamyl alcohol was added to the RNase R digested sample, and the mixture was shaken to terminate the digestion. Then, the sample was centrifuged at 13000×g and 4°C for 5 min. Next, undigested control RNA samples and RNA samples digested with RNase R were reverse transcribed to obtain cDNA; random primers or oligo (dT) primers were used during the reverse transcription process. Then, using the obtained cDNA as a template, PCR amplification was performed using specific primers designed for circTCP1, with the annealing temperature of the specific primers between 55°C and 65°C. The amplification products were then quantitatively analyzed using real-time quantitative PCR. A stable linear RNA of pigs was used as an internal reference gene. The expression level of circTCP1 was normalized using the expression level of the internal reference gene to obtain the relative expression level of circTCP1. The relative expression level of circTCP1 obtained is compared with the range of relative expression level of circTCP1 in normal pig samples to determine whether the pigs are in an abnormal physiological state.

[0008] Preferably, the total RNA extracted is subjected to quality testing before reverse transcription. Specifically, the absorbance at 260 nm and 280 nm is measured, and the OD260 / OD280 ratio is calculated. When this ratio is between 1.8 and 2.2, the RNA sample is considered to be of acceptable purity. Simultaneously, agarose gel electrophoresis is used to detect RNA integrity, showing clear 28S and 18S segments in the electrophoretic pattern. When an rRNA band appears, and the 28S band is approximately twice as bright as the 18S band, the RNA integrity is considered good. Only when the purity and integrity of the RNA sample meet these standards will the subsequent reverse transcription step be performed. For real-time quantitative PCR, at least three technical replicates and at least three biological replicates should be set up to reduce experimental error. For each technical replicate of each sample, ROX reference dye should be added to the reaction system to correct the fluorescence signal and ensure the comparability of fluorescence intensity measurements. During the data analysis phase, statistical methods should be used to analyze the data from each replicate, calculating the mean and standard deviation. If the standard deviation exceeds 10% of the mean, the real-time quantitative PCR experiment for that sample should be repeated. Reliable circTCP1 relative expression data obtained from multiple experiments should be entered into a database for long-term storage, facilitating comprehensive comparative analysis of data from different batches of experiments.

[0009] An application of a method for detecting the expression level of porcine circular RNA circTCP1 in assessing porcine reproductive performance includes the following steps: The relative expression level of circTCP1 was correlated with the litter size data of pigs to establish a correlation model between circTCP1 expression level and litter size. Specifically, ovarian tissue samples were collected from at least 100 sows with different litter sizes, and the expression level of circTCP1 was detected according to the methods of claims 1 and 2. At the same time, reproductive performance indicators such as the total litter size and the number of live piglets produced for each sow were recorded. The correlation coefficient between circTCP1 expression level and reproductive performance indicators was calculated using statistical methods. When the absolute value of the correlation coefficient was greater than 0.5, it was determined that the expression level of circTCP1 was significantly correlated with the reproductive performance indicator. Based on the aforementioned correlation model, the expression level of circTCP1 is detected in new individual sows, and the detection results are substituted into the model to predict the range of litter size for the sows. When the predicted litter size is more than 10% higher than the population average, the sow is determined to have high litter size potential. The reproductive performance of sows was comprehensively evaluated by combining the results of circTCP1 expression level detection with the results of granulosa cell proliferation detection in sow ovaries. The proliferation capacity of granulosa cells in ovaries was detected by EdU staining or CCK-8 assay. When the circTCP1 expression level was high and the granulosa cell proliferation capacity was strong, the sow was considered to have good reproductive performance. The above evaluation results were applied to molecular marker-assisted breeding of pigs to screen sows with high litter size potential and improve the overall reproductive performance of the pig herd.

[0010] The present invention has at least the following beneficial effects: First, RNase R digestion specifically degrades linear RNA while preserving circular RNA. The digestion is terminated and purified using phenol-chloroform-isoamyl alcohol, effectively eliminating linear RNA interference and ensuring the detection of the true expression level of circTCP1. Specific primers combined with PCR amplification at annealing temperatures of 55°C to 65°C improve amplification specificity. Normalization using stably expressed linear RNA as an internal reference eliminates experimental errors, resulting in more accurate quantification. Comparison of the detection results with normal ranges helps determine the physiological state of pigs, providing a molecular-level basis for assessing their physiological condition. This method's interconnected steps form a complete technical chain from sample processing to data interpretation, solving the problems of linear RNA interference and inaccurate quantification in existing circRNA detection techniques, and providing a reliable detection method for pig physiological state research.

[0011] Secondly, by detecting the OD260 / OD280 ratio of RNA and performing agarose gel electrophoresis analysis, the purity and integrity of the RNA used in subsequent experiments are ensured, avoiding experimental errors caused by RNA quality issues. Setting up at least three technical and biological replicates, combined with ROX reference dye correction of fluorescence signals, effectively reduces random errors during the experiment and improves data reliability. When the standard deviation exceeds 10% of the mean, the experiment is repeated to ensure data accuracy. Data is entered into a database for long-term storage, facilitating comprehensive comparison of data from different batches and providing data support for long-term research. These technical features solve the problems of uncontrollable RNA quality, large data errors, and lack of comparability during experiments, making the detection results more scientific and reliable, and laying a solid data foundation for subsequent research.

[0012] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Detailed Implementation

[0013] The present invention will now be described in further detail so that those skilled in the art can implement it based on the description.

[0014] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0015] It should be noted that, unless otherwise specified, the experimental methods described in the following implementation plan are all conventional methods, and the reagents and materials described are all commercially available unless otherwise specified.

[0016] <Example 1> The specific implementation method of this invention is as follows: First, samples were collected from porcine ovarian tissue. Total RNA was extracted using TRIzol reagent. After resuspending the RNA in DEPC water, the samples were divided into two equal parts. One part was digested with RNase R, and the other part served as a control. After digestion, phenol-chloroform-isoamyl alcohol was added to the digested sample, and after vortexing and mixing, the sample was centrifuged at 13000×g and 4℃ for 5 minutes to complete RNA purification. Subsequently, the quality of the two RNA samples was tested. The OD ratio was calculated by measuring the absorbance at 260nm and 280nm, and agarose gel electrophoresis was performed simultaneously. After ensuring that the RNA purity and integrity met the standards, reverse transcription was performed using random primers to obtain cDNA. Using cDNA as a template, PCR amplification was performed using specific primers designed for circTCP1. The primer annealing temperature was set to 60℃. Quantitative analysis was performed using real-time quantitative PCR technology. Porcine β-actin was used as an internal reference gene for normalization to obtain the relative expression level of circTCP1.

[0017] When applying this detection method to assess pig reproductive performance, ovarian tissue samples were collected from 150 sows with different litter sizes. The expression level of circTCP1 was detected using the method described above. Simultaneously, the total litter size and live birth number of each sow were recorded. Statistical methods were used to calculate the correlation between expression levels and reproductive indicators, and a predictive model was established based on the correlation analysis results. The expression level of circTCP1 was detected in newborn sows, and the results were substituted into the model to predict the litter size range. EdU staining was combined with tests to detect the proliferation capacity of ovarian granulosa cells. A comprehensive assessment of reproductive performance was conducted, and individuals with high reproductive potential were selected for marker-assisted breeding.

[0018] Compared to the closest existing technologies, current methods typically do not employ an RNase R digestion step, making it difficult to effectively distinguish between circular and linear RNA. This results in detection results being interfered with by linear RNA, making it difficult to accurately reflect the true expression level of circTCP1. Furthermore, existing technologies have not established a correlation model between circTCP1 expression levels and pig reproductive performance, thus failing to predict litter size and perform marker-assisted breeding. This implementation method specifically removes linear RNA through RNase R digestion, combined with standardized quality control and quantitative procedures, improving detection accuracy. Simultaneously, through large-scale sample data correlation analysis, a reliable reproductive performance evaluation model is established, filling the gap in existing technologies for the application of circRNA in pig molecular breeding.

[0019] <Example 2> The specific implementation method is as follows: After extracting total RNA from porcine ovarian tissue, a portion of the RNA sample was taken and the absorbance values ​​at 260 nm and 280 nm were measured using ultraviolet spectrophotometry. The OD260 / OD280 ratio was calculated. When the ratio was between 1.8 and 2.2, the RNA purity was considered to meet the requirements. Simultaneously, 1% agarose gel electrophoresis was performed. If clear 28S and 18S rRNA bands were observed in the electrophoresis pattern, and the brightness of the 28S band was approximately twice that of the 18S band, the RNA integrity was considered good. Only RNA samples that simultaneously met the purity and integrity standards were used for subsequent reverse transcription experiments.

[0020] In real-time quantitative PCR experiments, three technical replicates and three biological replicates were set up for each sample. ROX reference dye was added to the reaction system to correct the fluorescence signal. After the experiment, statistical analysis was performed on the data of each replicate, and the mean and standard deviation were calculated. If the standard deviation of any sample exceeded 10% of the mean, the real-time quantitative PCR experiment for that sample was repeated. Reliable data obtained from multiple experiments were entered into a database for long-term storage and management.

[0021] Compared to the closest existing technologies, current methods for detecting porcine circular RNA expression levels typically lack systematic RNA quality control steps and fail to rigorously screen RNA purity and integrity, leading to errors in subsequent experiments due to RNA quality issues. In real-time quantitative PCR, sufficient technical and biological replicates are often not set up, and reference dyes are not used to correct fluorescence signals, making it difficult to effectively reduce experimental errors. Furthermore, existing technologies lack standardized data processing and management procedures, and do not perform statistical analysis or database storage of data, resulting in the inability to comprehensively compare experimental data from different batches. This implementation method addresses the problems of large experimental errors, low data reliability, and lack of comparability in existing technologies by adding RNA quality control, optimizing experimental replicate settings, introducing fluorescence correction, and standardizing data management, thereby improving the accuracy and reliability of the detection results.

[0022] <Example 3> The specific implementation method is as follows: Ovarian tissue samples were collected from 120 Large White / Landrace crossbred sows with different litter sizes. Total RNA was extracted according to the methods described in claims 1 and 2 and digested with RNase R. The relative expression level of circTCP1 was detected by real-time quantitative PCR. Simultaneously, reproductive performance indicators such as total litter size and live piglet count were recorded for each sow. Statistical methods were used to analyze the correlation between circTCP1 expression level and reproductive indicators. When the absolute value of the correlation coefficient between circTCP1 expression level and total litter size was found to be greater than 0.5, a significant correlation was determined, and a predictive model for circTCP1 expression level and litter size was established.

[0023] For new sows, RNA was extracted from their ovarian tissue, and the expression level of circTCP1 was detected. The results were then substituted into the aforementioned prediction model to obtain the predicted range for the sow's litter size. Simultaneously, the proliferation capacity of ovarian granulosa cells was assessed using EdU staining. Sows with high litter size potential were identified when circTCP1 expression was higher than the population average and granulosa cell proliferation was strong. These selected sows were then used for marker-assisted breeding to establish a core herd of high-livestock sows.

[0024] Compared to the closest existing technologies, current methods primarily assess pig reproductive performance through traditional morphological observations or linear RNA markers, failing to establish a correlation between the expression level of circular RNA circTCP1 and litter size, thus unable to accurately predict sow reproductive potential at the molecular level. Existing technologies also lack a comprehensive evaluation system that combines circRNA expression levels with cellular function detection, making it difficult to fully reflect the reproductive physiological state of sows. Furthermore, traditional breeding methods rely on phenotypic data screening, lacking molecular marker-assisted methods, resulting in low selection efficiency and insufficient accuracy. This implementation method establishes a correlation model between circTCP1 expression levels and litter size, combined with granulosa cell proliferation capacity detection, providing a molecular-level quantitative indicator for pig reproductive performance assessment. This enables precise screening of high-livestock sows, overcoming the shortcomings of existing technologies in molecular marker-assisted breeding, which lack effective targets and evaluation systems.

[0025] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details.

Claims

1. A method for detecting the expression level of porcine circular RNA circTCP1, characterized in that, Includes the following steps: First, total RNA was extracted from pig tissue or cell samples. The obtained RNA samples were resuspended in DEPC water. The resuspended RNA samples were divided into two equal parts. One part was digested with RNase R, and the other part was used as a control. After digestion, phenol-chloroform-isoamyl alcohol was added to the RNase R digested sample, and the mixture was shaken to terminate the digestion. Then, the sample was centrifuged at 13000×g and 4°C for 5 min. Next, undigested control RNA samples and RNA samples digested with RNase R were reverse transcribed to obtain cDNA; random primers or oligo (dT) primers were used during the reverse transcription process. Then, using the obtained cDNA as a template, PCR amplification was performed using specific primers designed for circTCP1, with the annealing temperature of the specific primers between 55°C and 65°C. The amplification products were then quantitatively analyzed using real-time quantitative PCR. A stable linear RNA of pigs was used as an internal reference gene. The expression level of circTCP1 was normalized using the expression level of the internal reference gene to obtain the relative expression level of circTCP1. The relative expression level of circTCP1 obtained is compared with the range of relative expression level of circTCP1 in normal pig samples to determine whether the pigs are in an abnormal physiological state.

2. The method for detecting the expression level of porcine circular RNA circTCP1 as described in claim 1, characterized in that, Before reverse transcription, the extracted total RNA was quality-tested. Specifically, the absorbance at 260 nm and 280 nm was measured, and the OD260 / OD280 ratio was calculated. A ratio between 1.8 and 2.2 indicated that the RNA sample was of acceptable purity. Simultaneously, agarose gel electrophoresis was used to detect RNA integrity, resulting in clear 28S and 18S segments in the electrophoretic pattern. When an rRNA band appears, and the 28S band is approximately twice as bright as the 18S band, the RNA integrity is considered good. Only when the purity and integrity of the RNA sample meet these standards will the subsequent reverse transcription step be performed. For real-time quantitative PCR, at least three technical replicates and at least three biological replicates should be set up to reduce experimental error. For each technical replicate of each sample, ROX reference dye should be added to the reaction system to correct the fluorescence signal and ensure the comparability of fluorescence intensity measurements. During the data analysis phase, statistical methods should be used to analyze the data from each replicate, calculating the mean and standard deviation. If the standard deviation exceeds 10% of the mean, the real-time quantitative PCR experiment for that sample should be repeated. Reliable circTCP1 relative expression data obtained from multiple experiments should be entered into a database for long-term storage, facilitating comprehensive comparative analysis of data from different batches of experiments.

3. The application of a method for detecting the expression level of porcine circular RNA circTCP1 as described in claim 1 or 2 in evaluating porcine reproductive performance, characterized in that, Includes the following steps: The relative expression level of circTCP1 was correlated with the litter size data of pigs to establish a correlation model between circTCP1 expression level and litter size. Specifically, ovarian tissue samples were collected from at least 100 sows with different litter sizes, and the expression level of circTCP1 was detected according to the methods of claims 1 and 2. At the same time, reproductive performance indicators such as the total litter size and the number of live piglets produced for each sow were recorded. The correlation coefficient between circTCP1 expression level and reproductive performance indicators was calculated using statistical methods. When the absolute value of the correlation coefficient was greater than 0.5, it was determined that the expression level of circTCP1 was significantly correlated with the reproductive performance indicator. Based on the aforementioned correlation model, the expression level of circTCP1 is detected in new individual sows, and the detection results are substituted into the model to predict the range of litter size for the sows. When the predicted litter size is more than 10% higher than the population average, the sow is determined to have high litter size potential. The reproductive performance of sows was comprehensively evaluated by combining the results of circTCP1 expression level detection with the results of granulosa cell proliferation detection in sow ovaries. The proliferation capacity of granulosa cells in ovaries was detected by EdU staining or CCK-8 assay. When the circTCP1 expression level was high and the granulosa cell proliferation capacity was strong, the sow was considered to have good reproductive performance. The above evaluation results were applied to molecular marker-assisted breeding of pigs to screen sows with high litter size potential and improve the overall reproductive performance of the pig herd.