Every step, from sample selection to cryopreservation, is critical in ensuring that tRNA molecules can accurately convey the cellular "life codes" during sequencing. This article systematically delineates the complete technological workflow involved in tRNA sequencing, encompassing key phases such as sample preparation, library construction, and high-throughput sequencing. Additionally, it elucidates the methodologies employed in data analysis to uncover the roles of tRNA in disease pathogenesis and cellular regulation. The sections that follow provide an in-depth examination of crucial experimental procedures and highlight specific case studies demonstrating the application of this technology in tumor research and the exploration of cellular functions.
Quantitative tRNA sequencing
tRNA sequencing sample preparation
1. Sample type selection
Samples suitable for tRNA sequencing are diverse, each with its own characteristics and applicability. Total RNA is a common sample type; the directly extracted total RNA contains various RNAs within cells, including tRNAs. Its advantage lies in providing a direct reflection of the overall RNA profile within cells, making it ideal for comprehensive analysis of cellular RNA composition. Tissue samples offer a macroscopic view of tRNA levels in specific tissues. The tRNA expression profiles can vary across different tissues, such as tumor tissue versus normal tissue, which makes them useful for studying tissue-specific tRNA functions. Cell samples exhibit high homogeneity, facilitating precise research on tRNA in specific cell types. For studies involving cell lines or specific cells isolated from blood, cell samples provide more accurate information, aiding in the exploration of tRNA regulatory mechanisms within cells.
2. Sample collection and preservation
The sample collection process requires extra caution. When collecting tissue samples, materials should be taken quickly to avoid prolonged exposure to air, reducing the risk of RNA degradation. Use sterile instruments to prevent contamination of the sample. For cell samples, pay attention to the cells active state and avoid collection when cell growth is abnormal. When collecting total RNA, ensure the extraction process is standardized to preventRNA enzyme contamination. Sample preservation is also crucial; to maintain sample quality, they are generally stored at low temperatures. Total RNA can be preserved in a-80℃ freezer, effectively inhibiting RNA enzyme activity and preventing RNA degradation. Tissue samples can first be rapidly frozen in liquid nitrogen before being transferred to-80℃ storage. If cell samples need long-term preservation, they can be cryopreserved in a liquid nitrogen tank using a cryoprotectant solution. Appropriate storage methods can maximize the integrity of tRNA in the sample, providing a reliable foundation for subsequent sequencing experiments.
tRNA sequencing experimental process
1. library construction
Library construction is a critical step in tRNA sequencing experiments. First, modifications are removed; tRNA modifications can interfere with subsequent reactions. Specific enzymes or chemical methods are used to remove these modifications, such as using demethylation enzymes to restore tRNA to an "operable" state, laying the foundation for subsequent steps. Next, ligation adapters are added, attaching specific adapters to both ends of the tRNA. These adapters carry special sequences that play important roles in subsequent reactions, such as providing a starting point for reverse transcription and helping the library fix and recognize on the sequencing platform. The ligation process requires precise control of reaction conditions to ensure correct ligation and high efficiency. Then, cDNA is synthesized through reverse transcription, using the tRNA with the attached adapters as templates. The choice of reverse transcriptase is crucial, considering its adaptability to tRNA structure and the accuracy of cDNA synthesis. The synthesized cDNA duplexes are further processed, including end repair and A-tailing, to meet sequencing requirements. After these steps, a sequencing library containing tRNA information is constructed, preparing for high-throughput sequencing.
2. high-throughput sequencing
Taking the Illumina platform as an example, its sequencing principle and process are as follows. First, the constructed library is added to the sequencing system containing a flow cell (flow cell). The flow cell is where the sequencing reaction takes place, with many short sequences on its surface. The DNA fragments in the library will bind to these short sequences through base pairing, which is the initial step of sequencing. Next, bridge PCR amplification is performed, where a series of chemical reactions amplify the DNA fragments bound to the flow cell, forming DNA clusters that increase signal intensity for subsequent detection. Then, dNTPs with azide groups and polymerase, labeled with different fluorescent markers, are added. Due to the presence of azide groups, each cycle can only extend one base. After each base is bound, it is scanned by laser, and the type of base is determined based on the fluorescence color, then the result is deduced according to the complementary principle. Once the azide group is cleaved, the next cycle begins, and this process is repeated continuously to sequentially determine the DNA sequence. In this way, high-throughput sequencing platforms can rapidly and efficiently obtain large amounts of tRNA sequencing data, providing rich information for subsequent data analysis.
tRNA sequencing data analysis
1. Basic data analysis
tRNA expression quantification is the foundation of tRNA sequencing data analysis. By processing the sequencing data, it is possible to accurately calculate the expression level of each tRNA in the sample. A common method is to normalize the tRNA reads counts obtained from sequencing to eliminate differences between samples and the impact of sequencing depth, thereby accurately reflecting the true expression levels of tRNAs. Differential expression analysis focuses on comparing the expression differences of tRNAs across different samples. Using statistical methods such as DESeq2 software, tRNAs that exhibit significant changes under different conditions (such as disease versus normal samples, different developmental stages) can be identified. These differentially expressed tRNAs may play a crucial role in corresponding physiological or pathological processes.
When presenting these data, common statistical graphics include bar charts and heat maps. Bar charts can intuitively compare the expression levels of different samples or tRNAs, clearly showing the differences in expression levels. Heat maps, on the other hand, can visually represent the expression patterns of multiple tRNAs across various samples through varying shades of color. This makes it easy to quickly identify similarities and differences in expression, helping researchers grasp the overall trends in tRNA expression and provide clues for further in-depth research.
2. Characteristics data analysis
The analysis of tRNA expression levels for various anticodons can provide deep insights into the usage preferences of tRNA within cells. Different anticodons correspond to different amino acids, and by analyzing their expression levels, we can uncover the cellular demand for specific amino acids under particular physiological conditions, as well as the mechanisms of tRNA involvement in protein synthesis. Predicting mRNA translation efficiency is a significant feature of tRNA sequencing data analysis. As a key player in protein translation, the expression level of tRNA is closely related to mRNA translation efficiency. By integrating tRNA expression data with mRNA sequence information, we can predict mRNA translation efficiency, which aids in understanding the complex network of gene expression regulation.
The combined analysis of tRNA and mRNA expression profiles can further deepen research. TRNA and mRNA work together in protein synthesis; analyzing their expression profiles jointly can uncover potential regulatory relationships between them, such as whether changes in certain tRNAs affect the translation of specific mRNAs, thereby revealing new mechanisms of gene expression regulation within cells. These distinctive data analyses provide powerful tools for a deeper understanding of tRNA functions in cellular physiological processes.
Application of tRNA sequencing
1. Disease research
In tumor research, tRNA sequencing has revealed that the tRNA expression profile of tumor cells is significantly different from that of normal cells. Abnormally high expression of certain tRNAs may promote the proliferation and metastasis of tumor cells, making them promising biomarkers for cancer diagnosis and therapeutic targets. For type II diabetes, tRNA sequencing has uncovered the association between changes in tRNA within pancreatic cells and abnormalities in insulin synthesis and secretion, providing insights into disease mechanisms and guiding the development of new therapies. In Huntingtons disease studies, tRNA sequencing has shown that alterations in specific tRNAs affect the translation of mutant proteins, potentially contributing to neurodegenerative processes in the disease. This helps deepen our understanding of the molecular pathogenesis of the disease and lays the foundation for developing targeted treatment strategies. The application of tRNA sequencing in these disease studies offers new hope for early diagnosis, precision therapy, and drug development.
2. Cell physiology studies
tRNA sequencing plays a crucial role in cellular physiology research. During cell proliferation, tRNA sequencing can reveal changes in the expression of specific tRNAs, which are closely related to the regulation of the cell cycle and provide clues for a deeper understanding of cell proliferation mechanisms. In the study of cell differentiation, tRNA sequencing can uncover differences in tRNA expression profiles at various stages of differentiation, aiding in elucidating the mechanisms of gene expression regulation during cell differentiation. In apoptosis research, tRNA sequencing can detect changes in apoptotic-related tRNAs, which may be involved in signaling pathways of apoptosis. Tissue RNA sequencing provides a powerful tool for comprehensively analyzing cellular physiological states, driving continuous advancements in the field of cell biology.
Reference:
- Pinkard, O., McFarland, S., Sweet, T. et al. Quantitative tRNA-sequencing uncovers metazoan tissue-specific tRNA regulation. Nat Commun 11, 4104 (2020). https://doi.org/10.1038/s41467-020-17879-x
