Single-cell RNA Sequencing of Peripheral Blood Links Cell-Type-Specific Regulation of Splicing to Autoimmune and Inflammatory Diseases

Single-cell RNA Sequencing Reveals Cell-type-specific Splicing Regulation in Peripheral Blood Linked to Autoimmune and Inflammatory Diseases

Background

In recent years, rapid advancements in genomics research have provided deeper insights into the genetic basis of complex traits. However, the functional mechanisms underlying most disease-associated genomic loci identified through genome-wide association studies (GWAS loci) remain largely elusive. These loci are predominantly located in non-coding regions of the genome, rather than protein-coding regions. Therefore, understanding post-transcriptional events, such as alternative splicing (AS), and their impact on gene expression and genetic risk for complex diseases is crucial. Alternative splicing is a key mechanism for regulating gene function and generating diverse gene expression profiles, but its role in specific cell types and genetic backgrounds remains insufficiently studied.

Furthermore, large-scale single-cell RNA sequencing (scRNA-seq) technology provides an opportunity for unbiased analysis of gene expression patterns at the single-cell level. This technique enables the characterization of genomic regulatory features across different cell types within heterogeneous populations. However, traditional scRNA-seq methods, due to their 3′-biased sequencing libraries, have limitations in detecting alternative splicing events at high resolution.

To address these gaps, researchers from multiple Asian institutions focused on exploring alternative splicing within peripheral blood mononuclear cells (PBMCs) and its relationships with autoimmune and inflammatory diseases. By leveraging high-throughput 5′-biased single-cell transcriptomics, the team comprehensively analyzed splicing regulation across cell types and genetic backgrounds.

Source of the Publication

This study, titled “Single-cell RNA sequencing of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases,” was published in the December 2024 issue of Nature Genetics. It was carried out by an international collaborative team involving researchers from the National University of Singapore, RIKEN, the Samsung Medical Center, and other institutions. The study is based on the Asian Immune Diversity Atlas and aims to elucidate the genetic mechanisms underpinning immune-related diseases at the single-cell resolution level.


Research Process

Data Generation and Study Design

The research team utilized peripheral blood samples from 474 healthy donors in the Asian Immune Diversity Atlas (AIDA) dataset. The donors represented multiple ethnic groups from East Asia, Southeast Asia, and South Asia (e.g., Japan, Singapore, and Korea). On average, 1,959 single cells were sampled per individual, generating nearly one million single-cell transcriptomes. By employing 5′-biased scRNA-seq technology and leveraging endogenous mRNA stochastic cleavage and recapping phenomena, the researchers significantly extended exon coverage, allowing for fine-grained analyses of splicing changes.

After data generation, the team classified 32 PBMC subtypes and analyzed alternative splicing patterns at both single-cell and pseudobulk levels. They identified diverse differential splicing events (DSEs) and thousands of splicing quantitative trait loci (sQTLs) across single-cell and pseudobulk datasets.


Data Analysis and Experimental Approach

The study consisted of the following key steps:

1. Classifying Cell Types and Quantifying Alternative Splicing Events

Using gene expression profiles, the researchers classified 34 PBMC types, with sufficient sample sizes for 21 subtypes. Alternative splicing events per cell were quantified using the tool SpliZ at both single-cell and pseudobulk levels. Compared to 3′-biased scRNA-seq methods, the 5′-biased approach detected more than four times as many spliced genes.

2. Impact of Sex and Ancestry on Splicing

The study revealed significant effects of sex and ancestry on splicing patterns. For example, in specific T cell subtypes, a short isoform of the FLNA gene was more highly expressed in female samples than in male samples. Additionally, ancestry-biased DSEs were identified, with SNP rs11064437 showing strong associations with splicing preferences in the SPSB2 gene, driven by differences in allele frequencies across populations.

3. Detection of cis-sQTLs and trans-sQTLs

By integrating 5′-biased sequencing with advanced statistical modeling, the study identified 10,874 cis-sQTLs for protein-coding genes and 703 for long non-coding RNA genes. Moreover, 607 trans-sgenes regulated by distal loci were discovered. Notably, the team uncovered a T cell-specific regulatory relationship in which HNRNPLL expression modulated splicing of PTPRC.

4. Association Analysis and Mechanistic Studies

The researchers demonstrated significant enrichment of cis-sQTL effects in the heritability of multiple autoimmune diseases such as systemic lupus erythematosus (SLE) and Graves’ disease. For instance, they identified an Asian-specific 5′ splice site variant (rs74416240) that leads to intron retention in TCHP exon 4, which increases the risk of Graves’ disease. A minigene validation experiment confirmed how rs74416240 disrupts the canonical 5′ splice site to alter splicing.

5. Dynamic Splicing Events in B Cell Development

Dynamic splicing changes were observed during B cell development. Genes like PAX5, a transcription factor essential for B cell differentiation, exhibited shifts in isoform ratios. Similarly, splicing in PTPRC aligned with the functional progression of B cells.


Results and Key Findings

Major Findings

  1. Sex- and Ancestry-Specific Splicing Regulation
    The study identified marked differences in exon usage driven by sex and genetic background, especially in immune-related genes such as FLNA and SPSB2.

  2. Extensive cis-sQTLs and trans-sQTLs
    The research uncovered widespread splicing regulatory signals in specific cell types. For instance, HNRNPLL extensively influenced PTPRC splicing across T cell subtypes through trans effects.

  3. Splicing Mechanisms Associated with Diseases
    Many cis-sQTLs were found to colocalize with genetic risks for autoimmune and inflammatory diseases. The causal mechanism of an Asian-specific Graves’ disease risk variant (TCHP rs74416240) was elucidated.

  4. Dynamic Splicing Regulation in B Cell Development
    Splicing events dynamically regulated during B cell maturation indicate vital gene regulatory mechanisms underlying immune cell development.


Significance and Highlights

This study provides single-cell resolution insights into the interplay between alternative splicing, ancestry, and disease susceptibility with the following key contributions: - Technological Innovation: The adoption of 5′-biased single-cell RNA sequencing significantly improved exon coverage and the detection of alternative splicing events. - Population Diversity: The inclusion of rare Southeast Asian and South Asian populations adds critical diversity to GWAS studies. - Novel Disease Mechanisms: The identification of splicing mechanisms underlying diseases such as Graves’ disease and SLE deepens our understanding of the genetic regulatory networks of complex diseases.

This study not only highlights the critical role of splicing in immune function and disease but also provides a blueprint for future research into single-cell splicing and genetic variation, laying the foundation for advancements in precision medicine.