The eukaryotic transcription process is the key link of gene expression regulation, and its precise regulation is important for cell growth, differentiation, development, and response to external environmental stimuli. The core purpose of sequencing eukaryotic transcription is to deeply understand the key biological processes, such as transcription activity, splicing variation, and promoter use. This information is important in revealing the basic laws of life activities, exploring the mechanism of disease occurrence and development, and developing new therapeutic strategies.
This paper mainly introduces the transcription and sequencing technology of eukaryotes, discusses its application, analyzes the limitations of the current technology, and looks forward to the future development direction.
Why Sequence Eukaryotic Transcription
The occurrence and development of diseases are closely related to the abnormality of the transcription process. Taking cancer as an example, uncontrolled proliferation, invasion, and metastasis of tumor cells are often accompanied by a series of changes in gene transcription activity and abnormal splicing variation. By sequencing eukaryotic transcription, scientists can accurately capture these abnormal changes, discover key genes and transcription regulatory factors related to cancer, provide specific biomarkers for early diagnosis of tumors, and also point out the direction for targeted therapy strategies.
Transcriptome sequencing is of great significance for understanding gene regulatory networks. Promoter, as a key regulatory element of gene transcription initiation, has a high spatial-temporal specificity. Under different cell types, developmental stages, and environmental conditions, there are differences in the selection and activation of promoters, which is important for cells to achieve functional specificity and maintain internal balance. With the help of transcriptome sequencing technology, researchers can accurately identify promoters, analyze their usage rules, and then deeply explore the regulation mechanism of gene expression in time and space dimensions, and build a more perfect gene regulation network model.
Eukaryotic transcriptome sequencing not only helps to analyze the basic laws of life activities, but also provides strong technical support and theoretical basis for overcoming major diseases and promoting medical development, and occupies an irreplaceable important position in life science research.
The identification of differential exon splicing by RNA-seq (Cloonan et al., 2008)
Overview of Key Eukaryotic Transcriptome Sequencing Technologies
Key sequencing technology is an indispensable core tool in the process of eukaryotic transcription research. From analyzing RNA-seq of the total RNA expression level, to accurately locating the transcription start site, and then to analyzing the complex transcript structure, they have developed synergistically, providing solid technical support for the transcription regulation mechanism.
RNA-seq
RNA-seq is one of the most widely used transcriptome sequencing technologies, capable of comprehensively analyzing the total RNA in samples. According to different analysis objects, it can be divided into PolyA+ RNA-seq and total RNA-seq.
A. PolyA+ RNA-seq
a) Analysis object: Mainly sequences mature mRNA with a polyA tail.
b) Enrichment Method: Most eukaryotic mRNAs undergo tail-adding modification after transcription to form a polyA tail, enabling enrichment of polyA-tailed mRNA using oligo (dT) magnetic beads.
c) Applications: Accurately determines mRNA expression levels. Identifies new transcripts. Analyzes alternative splicing events.
d) Advantages: Focuses on mature mRNA, providing clear gene expression information. It plays a critical role in gene expression profile analysis and differential expression gene screening.
B. Total RNA-seq
a) Analysis Object: Sequences all RNA molecules in the sample, including mRNA, rRNA, tRNA, lncRNA, and miRNA.
b) Advantage：Provides more comprehensive transcriptome information compared to PolyA+ RNA-seq. Enables analysis of mRNA expression and variations, as well as in-depth study of non-coding RNA (ncRNA) functions. It also can identify new lncRNAs, study their interactions with mRNA, and their roles in gene expression regulation.
c) Challenges: Due to the high proportion of rRNA in total RNA (usually >80%), special rRNA depletion technologies are required to improve the coverage of other RNA molecules and the accuracy of analyses.
Overview of RNA-seq experiment (Mathew et al., 2015)
CAGE-seq
Cap Analysis of Gene Expression Sequencing (CAGE-seq) is a sequencing technique specially used to precisely locate the transcription initiation site (TSS). Its principle is based on the specific recognition and analysis of the hat structure at the 5' end of mRNA. In eukaryotes, the 5' end of mRNA usually has a special hat structure. CAGE-seq cuts the mRNA into short fragments using an enzyme that specifically recognizes the hat structure, then sequences these short fragments.
Because the initial positions of these short fragments correspond to the transcription initiation sites, through the analysis of sequencing data, the transcription initiation sites within the whole genome can be accurately identified, and the frequency of using different promoters can be determined. CAGE-seq can not only identify the transcription initiation sites of known genes, but also find new transcription initiation sites and promoters, which is of great significance for further study on the molecular mechanism of gene transcription regulation.
CAGE-seq identifies TBX3-regulated drivers of metastasis (Amaia et al., 2023)
Long-read sequencing, represented by PacBio and Oxford Nanopore, shows unique advantages in the field of transcriptome research. Traditional short-read sequencing is limited by read length, making it difficult to span complex transcript structures. In contrast, long-read sequencing can directly sequence full-length transcripts, preserving complete information from the 5' to 3' ends.
A. Detection of Splicing Isoforms
a) Long-read sequencing excels in identifying splicing isomers by accurately detecting alternative splicing events, such as exon skipping and intron retention.
b) It enables analysis of various mRNA subtypes generated from the same gene through transcription, providing direct evidence for understanding post-transcriptional regulatory mechanisms.
B. Comprehensive Transcript Analysis
a) By obtaining complete transcript sequences, long-read sequencing can identify new transcripts and precisely determine transcription start and termination sites.
b) This facilitates in-depth analysis of transcript structures and expression patterns.
C. Potential for Base Modification Detection
a) PacBio's single-molecule real-time sequencing and Oxford Nanopore's nanopore sequencing technologies have the potential to detect base modifications (e.g., methylation).
b) This expands transcriptome research from simple sequence analysis to the epigenomic level, significantly advancing studies on gene expression regulatory mechanisms in eukaryotes.
scRNA-seq
Single-cell RNA-seq (scRNA-seq) technology can analyze the transcriptome at the single-cell level and reveal the heterogeneity between cells. In traditional transcriptome sequencing, the mixed RNA of cells is analyzed, which will cover up the differences between cells. ScRNA-seq can obtain the unique transcription profile of each cell by isolating, amplifying, and sequencing the RNA of a single cell.
At present, scRNA-seq technology has developed different experimental methods and platforms, such as Drop-seq, 10x genomics, etc. These technologies can realize Qualcomm's single-cell transcriptome analysis. ScRNA-seq is widely used in the study of cell differentiation, embryonic development, tumor heterogeneity, and other fields. It can identify different cell subsets, reveal the molecular mechanism of cell fate, and discover the heterogeneity and potential therapeutic targets in tumor cells.
Overview of various analyses for scRNA-seq data (Chen et al., 2019)
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Applications in Eukaryotic Transcriptome Sequencing Studies
The application of eukaryotic transcription and sequencing technology has greatly promoted the development of life sciences. Through in-depth analysis of transcriptome, this technology can reveal the transcription regulation mechanism from gene expression, alternative splicing, transcription factor regulation, and other aspects, and provide key information and research ideas for exploring important biological processes such as biological development and disease occurrence.
Gene Expression Profile
Gene expression profile analysis is one of the important applications of eukaryotic transcriptome sequencing. Through RNA-seq and other technologies, the gene expression level of cells, tissues, or organisms in different physiological states, developmental stages, or environmental conditions can be comprehensively determined, and the gene expression map can be drawn. In tumor research, differentially expressed genes can be screened by comparing the gene expression profiles of tumor tissues and normal tissues, which may be closely related to the occurrence and development of tumors. Further functional enrichment and signal pathway analysis of these differentially expressed genes can reveal the molecular mechanism of tumor occurrence and provide potential biomarkers and therapeutic targets for tumor diagnosis and treatment.
Phylogenetic expression profiling reveals coordinated evolution within gene sets (Martin et al., 2018)
Alternative Splicing and lncRNA Discovery
Transcriptome sequencing technology plays a key role in alternative splicing and lncRNA discovery. RNA-seq and long-read and long sequencing techniques can comprehensively identify the alternative splicing events of genes and analyze the expression patterns of different splicing isomers in different cell types, tissues, or physiological states. Through the in-depth study of alternative splicing events, we can reveal their regulatory mechanism in the process of biological development and disease occurrence.
At the same time, transcriptome sequencing technology is also an important means to discover new lncRNAs. Total RNA-seq and single-cell RNA-seq can detect low-abundance lncRNA and predict its function through bioinformatics analysis. Many studies have shown that lncRNA plays an important role in gene expression regulation, chromatin modification, and cell differentiation. The discovery of new lncRNAs and the study of their interaction with other genes will help to understand the complex network of gene expression regulation.
Transcription Factor Target Recognition
Transcription factors are the key proteins to regulate gene transcription. They regulate gene expression by binding to specific sequences on DNA. Transcriptome sequencing technology combined with ChIP-seq technology can effectively identify the target genes of transcription factors. ChIP-seq enriched the DNA fragments bound to transcription factors by using specific antibodies, then sequenced and analyzed them to determine the binding sites of transcription factors on the genome. Combined with the gene expression data determined by RNA-seq, the relationship between transcription factor binding sites and gene expression can be further analyzed to identify the target gene of a transcription factor.
Modularity in the eukaryotic transcriptional regulation (Becskei et al., 2020)
Analysis of Transcription Regulation Mechanism
scRNA-seq provides a powerful tool for spatio-temporal transcription regulation mechanisms. scRNA-seq can reveal the transcription heterogeneity between cells at the single-cell level, and combined with the spatial location information of cells (such as through spatial transcriptomics technology), we can study the spatial distribution and transcription dynamic changes of cells in tissues. For example, in the study of tumor microenvironment, scRNA-seq can identify the transcription characteristics of different cell subsets, such as tumor cells, immune cells, and stromal cells, analyze the interaction between them, and reveal the temporal and spatial regulation mechanism of tumor occurrence, development, and metastasis.
Limitation and Future Prospect of Eukaryotic Transcriptome Sequencing
Eukaryotic transcription and sequencing technology has greatly promoted the development of biology sciences and brought the research on gene expression regulation into a new stage. However, this technology has limitations in single cell resolution, quantitative accuracy of transcripts and data depth mining.
Accuracy, Coverage and Cost
Although remarkable progress has been made in transcriptome sequencing technology, it still faces challenges in accuracy, coverage, and cost.
- In terms of accuracy, due to the short reading length, short reading length sequencing technology is prone to errors in transcript assembly and splicing isomer identification, especially for complex gene structures and highly similar transcripts. Although long-read and long-sequence technology can improve the accuracy of transcript structure analysis, its sequencing error rate is relatively high, so it is necessary to further optimize sequencing technology and data analysis methods to improve the accuracy.
- As for coverage, due to the differences in complexity and abundance of RNA molecules, it is difficult for current sequencing technology to achieve comprehensive coverage of all RNA molecules. Low-abundance RNA molecules often need higher sequencing depth to be detected, which not only increases the sequencing cost but also may lead to incomplete data. In addition, for some RNA molecules with special structures, such as circular RNA and highly modified RNA, the current sequencing technology still has some limitations.
Validation of the transcript catalog (Yassour et al., 2009)
- Cost is also one of the important factors that restricts the wide application of transcription and sequencing technology. From sample preparation, sequencing experiment to data analysis, the whole transcriptome sequencing process needs a lot of manpower, material resources, and financial resources. Reducing sequencing cost and improving sequencing efficiency are the keys to promoting the wide application of transcriptome sequencing technology in basic research, clinical diagnosis, and drug research and development.
Multiomics Fusion
In the future, multi-omics integration and artificial intelligence (AI)-assisted analysis will become an important development direction of eukaryotic transcription and sequencing research.
- Multiomics integration refers to the combination of transcriptomics data with other omics data, such as ChIP-seq, ATAC-seq, Hi-C, etc., and comprehensively analyzes the molecular mechanism of gene expression regulation from multiple levels.
- ChIP-seq can provide the binding information of transcription factors and chromatin-modifying proteins on the genome, ATAC-seq can reveal the open state and accessibility of chromatin, and Hi-C can study the three-dimensional spatial structure of chromosomes.
- By integrating these data with transcriptome data, we can build a more complete gene expression regulation network and deeply understand the complex mechanism of gene transcription regulation.
Conclusion
As the core tool of functional genomics research, eukaryotic transcriptome sequencing technology plays an irreplaceable role in revealing the regulation mechanism of gene expression and exploring the law of disease occurrence and development. Through the comprehensive application of RNA-seq, CAGE-seq, and other sequencing technologies, scientists can deeply study key biological processes such as transcription activity, splicing variation, and promoter use, which provides rich information and profound insights for life science research.
Although there are still limitations in accuracy, coverage, and cost of transcription and sequencing technology, these problems will be gradually solved with the continuous innovation and development of technology and the application of new methods such as multi-group integration and AI-assisted analysis.
References:
- Ogbourne S, Antalis TM. "Transcriptional control and the role of silencers in transcriptional regulation in eukaryotes." Biochem J. 1998 331: 1-14 https://doi.org/10.1042/bj3310001
- Cloonan, N., Grimmond, S.M. "Transcriptome content and dynamics at single-nucleotide resolution." Genome Biol 2008 9: (234) https://doi.org/10.1186/gb-2008-9-9-234
- Amaia JM, Simon S., et al. "The Developmental Transcription Factor TBX3 Physically Engages with the Wnt/β-catenin Transcriptional Complex in Human Colorectal Cancer Cells to Regulate Metastasis Genes." bioRxiv 2023 19 https://doi.org/10.1101/2023.12.18.571901
- Chen G, Ning B, Shi T. "Single-Cell RNA-Seq Technologies and Related Computational Data Analysis." Front Genet. 2019 10:317 https://doi.org/10.3389/fgene.2019.00317
- Martin T, Fraser HB. "Comparative expression profiling reveals widespread coordinated evolution of gene expression across eukaryotes." Nat Commun. 2018 9(1): 4963 https://doi.org/10.1038/s41467-018-07436-y
- Becskei A. "Tuning up Transcription Factors for Therapy. Molecules." 2020 25(8): 1902 https://doi.org/10.3390/molecules25081902
- Yassour M, Kaplan T, et al. "Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing." Proc Natl Acad Sci U S A. 2009 106(9): 3264-9 https://doi.org/10.1073/pnas.0812841106
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