In the field of life science, with the deepening of research, it is difficult to fully analyze complex biological processes with single-omics technology. As the core technology of studying RNA-protein interaction, the integration of eCLIP-seq with transcriptomics (RNA-seq), chromatin accessibility (ATAC-seq), and protein omics provides a more systematic and in-depth perspective for revealing the molecular mechanism of gene expression regulation.

With its high resolution and specificity, eCLIP-seq technology can accurately capture the interaction site between RNA and protein in the natural state of cells, providing key clues for exploring the post-transcriptional regulatory mechanism.

• By integrating it with RNA-seq, we can obtain the gene expression profile and analyze the regulation of RNA-binding proteins on transcript stability and alternative splicing.
• Combined with ATAC-seq, it can construct a regulatory pathway from DNA to RNA and then to protein from chromatin opening state to RNA transcription and then to protein, revealing the synergistic relationship between RNA-protein interaction and chromatin accessibility during transcription initiation and extension.
• Combined with protein omics data, we can further clarify the effect of RNA-protein interaction on the expression and function of protein, and realize the whole chain analysis from gene transcription to protein function.

This article discusses the integration of eCLIP-seq with RNA-seq, ATAC-seq, and proteomics, covering their combined insights into RNA-protein interactions, regulatory mechanisms, analysis workflows, future directions, and challenges.

Introduction to Multi-Omics Integration with eCLIP-seq

The integration of multi-level genomics can provide a more comprehensive and systematic perspective for the study of life phenomena, and it is of great significance to combine eCLIP-seq with RNA-seq, ATAC-seq, and protein genomics. eCLIP-seq focuses on RNA-protein interaction, RNA-seq reflects the post-transcriptional expression of genes, ATAC-seq reveals the open state of chromatin to understand the transcriptional regulatory potential, and protein genomics shows the expression and modification of proteins. This combination can break the limitation of single technology, build a complete regulatory network from different molecular levels, and deeply analyze the complex mechanisms of life activities.

The integration of eCLIP-seq and Multiomics can help solve many key biological problems.

• First, we can deeply understand the post-transcriptional regulation and clarify how RNA-binding protein (RBP) affects the splicing, translation, and stability of mRNA through its interaction with RNA.
• Secondly, it is helpful to explore the specific effect of RBP on isomers and understand how RBP recognizes different RNA isomers and produces differentiated regulation effects.
• Thirdly, a more comprehensive RNA-protein network can be drawn to reveal the interactions and regulatory laws.

MOMIC pipeline steps (Madrid-Márquez et al., 2022)

There are many challenges in the process of data integration. On the technical level, there is a batch effect, and the data of different experimental batches may be biased due to differences in experimental conditions. The resolution is different, and the fineness of data obtained by each technology is different, which increases the difficulty of integration. At the computing level, data coordination is a big problem. How to standardize data from different sources, formats, and scales so that they can be analyzed under the same framework is a key obstacle to effective integration.

eCLIP-seq and RNA-seq: Decoding Post-Transcriptional Regulation

The integration of eCLIP-seq and RNA-seq provides a powerful technical combination for in-depth analysis of post-transcriptional regulation mechanisms. By associating the binding information of RBP with the expression and processing changes of RNA, the core role of RBP in post-transcriptional regulation can be accurately revealed.

Identification of Functional RBP Target

It is the key to identifying functional RBP targets by associating RBP binding sites identified by eCLIP-seq with differential expression data detected by RNA-seq. When eCLIP-seq shows that an RBP binds to the mRNA of a specific gene, if the gene in RNA-seq data shows significant splicing changes or mRNA stability changes after RBP knockout, it suggests that the gene may be a functional target of the RBP. This association analysis can exclude non-specific binding and focus on RNA molecules that are really regulated by RBP, thus targeting the follow-up mechanism research.

Isomer-specific RNA-protein Interaction

By correlating the binding peak of eCLIP-seq with alternative splicing events detected by RNA-seq (with the help of rMATS, LeafCutter, and other tools), the isomer-specific RNA-protein interaction can be revealed. Specifically, rMATS can quantitatively analyze the differences of alternative splicing events between different samples, and LeafCutter can identify co-regulated splicing modules through cluster analysis. In practical application, researchers have found that PTBP1 protein plays a key role in nerve development by binding intron-reserved isomers and inhibiting neuron-specific splicing procedures.

Overview and results for benchmarking workflow on ENCODE eCLIP datasets for proteins with known RNA sequence motifs (Schwarzl et al., 2024)

Integration Tools

A variety of tools provide technical support for the integration of eCLIP-seq and RNA-seq. For example, the analysis process of CLIPper combined with DESeq2 can perform differential expression analysis on the basis of considering RBP binding and identify the genes regulated by RBP more accurately. In addition, the co-expression network analysis tool can explore the potential modules of RBP regulation by constructing the co-expression network of RBP and target genes, and reveal the overall mode of action of RBP in the post-transcriptional regulatory network. The application of these tools has greatly improved the efficiency and accuracy of data integration and promoted the analysis of post-transcriptional regulation mechanisms.

Bridging Transcription and RNA Processing Through eCLIP-seq and ATAC-seq

ECLIP-seq focuses on the interaction between RNA-binding protein (RBP) and RNA, while ATAC-seq reveals the open area of chromatin. The integration of the two provides a unique perspective for analyzing the continuous regulation process from transcription initiation to RNA processing, and builds a bridge between transcription and RNA processing.

Correlation Between Chromatin Accessibility and RBP Binding

The open area of chromatin is a sign of active transcription, and the binding of RBP is involved in the subsequent processing of RNA. Studying the relationship between them is helpful to understand the synergistic regulation of transcription and RNA processing. For example, RBP located in the intron region may be related to the open chromatin near the enhancer chromatin opening in the enhancer region, which promotes gene transcription, while the adjacent RBP may quickly combine with new RNA during transcription and start processing steps such as splicing or modification. By comparing the RBP binding site of eCLIP-seq with the open chromatin region of ATAC-seq, we can explore this spatio-temporal correlation and reveal the potential coupling mechanism between transcription and RNA processing.

RBP association at retrotransposable and other repetitive elements (Van Nostrand et al., 2020)

Discovery of Regulatory Hotspots

By overlapping the binding peak of eCLIP-seq with that of ATAC-seq in non-coding regions (such as long-chain non-coding RNA (lncRNAs) and untranslated region (UTRs)), important regulatory hotspots can be found. These regions are not only the transcriptional regulatory regions of chromatin opening, but also the binding targets of RBP, which may play a core regulatory role through the "transcription-processing" coupling mechanism. The overlapping of open chromatin (ATAC-seq peak) and RBP binding (eCLIP-seq peak) in the promoter region of lncRNA suggests that this region may participate in transcriptional activation and post-transcriptional processing regulation of lncRNA at the same time, and become a key regulatory node related to cell fate determination or disease.

Analysis Flow

The integration analysis of eCLIP-seq and ATAC-seq can follow the standardized process:

• Firstly, the peak overlap analysis is carried out by BEDtools to quantify the co-location degree of RBP binding sites and open chromatin regions.
• Then, the motif enrichment analysis was carried out by tools such as HOMER to explore whether there are specific transcription factors or RBP binding motifs in the co-location region, suggesting potential synergistic regulatory factors.
• Finally, visual tools such as Integrative Genomics Viewer(IGV) were used to visually show the positional relationship between RBP binding peak, open chromatin region and gene structure on the genome, and to assist the proposal and verification of mechanism hypothesis.

This process provides a systematic analytical framework for analyzing the relationship between transcription and RNA processing.

eCLIP enrichment for rRNA links RBPs with ribosomal RNA processing (Van Nostrand et al., 2020)

eCLIP-seq and Proteomics to Map RNA-Protein Complexes

RBP does not work in isolation, but often forms a complex with other proteins to participate in RNA regulation. eCLIP-seq can capture the binding information of RBP and RNA, and protein omics can analyze the protein interaction network. The integration of eCLIP-seq provides a key means for systematically mapping RNA-protein complexes.

From RNA Binding to Protein Complexes

The RBP identified by eCLIP-seq can be correlated with the protein data of mass spectrometry, which can be extended from RNA binding level to protein complex level. After eCLIP-seq determines the target RNA of an RBP, the protein component in the immunoprecipitated product of the RBP can be analyzed by mass spectrometry, and the RNP interactome groups (RNPs) of the RBP can be constructed. This association can not only reveal the interaction between RBP and other proteins, but also clarify how these protein complexes synergistically bind and regulate RNA, providing a basis for understanding the assembly mechanism and functional division of the complexes.

Verification of RBP Function

Protein omics can effectively verify the composition of RBP-related protein complexes, thus supporting the analysis of RBP function. When studying RBP related to stress particles, eCLIP-seq may suggest that an RBP is involved in RNA regulation under stress conditions, and protein omics analyzes its immunoprecipitate products. If known stress particle components such as G3BP1 are detected, it can be verified that the RBP is indeed located in stress particles and participates in the assembly or functional regulation of stress particles through interaction with these proteins. This verification can exclude nonspecific protein binding and strengthen the reliability of RBP function research.

Tools and Databases

A variety of tools and databases help integrate eCLIP-seq with protein omics. CRAPome database contains common protein omics contaminants information, which can be used to remove nonspecific binding proteins in experiments and improve data accuracy. STRING-DB integrates a large number of known protein interaction data. By querying the interaction network of RBP identified by eCLIP-seq in the database, the possible protein complexes can be quickly predicted, which provides a direction for subsequent experimental verification. These resources have significantly improved the efficiency and systematicness of RNA-protein complex research.

Results obtained from Microarray DE analysis (Madrid-Márquez et al., 2022)

Future Directions and Challenges

Although the current technology has been able to capture RNA-protein interaction, gene expression and chromatin state at single cell level, there are still significant limitations:

• The sequencing depth of sc-eCLIP is low, and it is difficult to detect the binding site of low abundance RBP. The experimental variation at single cell level is great, and the problem of data noise is prominent. However, recent progress has shown potential, such as improving single-cell capture efficiency through microfluidic technology, optimizing amplification methods, and improving sequencing depth, which is expected to realize the accurate correlation between RNA-protein interaction and transcription regulation and chromatin state at the single-cell level, and provide a new perspective for analyzing regulatory differences in cell heterogeneity.
• It is an important application of machine learning in this field to construct a prediction model of RBP-RNA interaction using integrated data sets. By integrating binding sites, RNA sequence characteristics, protein domain information, and multi-group data (such as gene expression and chromatin status) of eCLIP-seq, a machine learning algorithm can learn the potential law of RBP binding and predict the RBP-RNA interaction that has not been verified by experiments.
• This kind of model can not only reduce the experimental cost, but also reveal the hidden patterns that are difficult to find in traditional analysis, such as the relationship between RBP binding preference and RNA secondary structure and apparent modification, which provides a theoretical basis for designing drugs targeting RNA-protein interaction.
• Establishing a unified analysis process and sharing resources is the key to promoting the development of the field. At present, the differences in experimental scheme and data analysis process make it difficult to compare the results of different studies, so it is urgent to follow the standardization guidelines of ENCODE and other projects and standardize the experimental design and data analysis steps of eCLIP-seq and multi-group integration.
• At the same time, it is necessary to improve the shared resource database, such as eCLIPdb, which can integrate the published eCLIP-seq data to facilitate researchers' queries and reuse. In addition, the establishment of a multi-omics integrated data platform to realize the linkage retrieval of eCLIP-seq, RNA-seq, ATAC-seq, and protein omics data will greatly improve the efficiency of data utilization and promote cross-laboratory cooperation and results verification.

mRNA meta-gene profiles from eCLlP correspond to RBP regulatory roles (Van Nostrand et al., 2020)

Conclusion

The multi-omics integration of eCLIP-seq with RNA-seq, ATAC-seq, and protein genomics broke the limitation of single technology, and revealed the complex network of RNA-protein interaction from post-transcriptional regulation, the correlation between transcription and RNA processing, to the mapping of RNA-protein complex. Despite the technical and computational challenges of data integration, with the improvement of standardized processes, the innovation of tools, and the development of single-cell omics, this integration will provide stronger support for analyzing the mechanisms of life activities and exploring the molecular basis of diseases, and promote the leap from basic research to clinical application.

References

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