Researchers at UCLA have made a significant advance in understanding how genes influence RNA splicing, a fundamental process that determines how genetic information is used to make proteins. RNA splicing occurs after DNA is transcribed into RNA, trimming out non-coding regions (introns) and joining together the coding parts (exons). However, this process isn’t one-size-fits-all. Different combinations of exons can be joined together in a process called alternative splicing, which allows a single gene to produce multiple versions of a protein. Errors in splicing regulation have been linked to many diseases, including neurodegenerative and autoimmune disorders.

The challenge in studying RNA splicing lies in understanding how genetic variation influences which splicing events occur. Some splicing events are governed by cis-acting elements, which are DNA sequences located near the gene being spliced. Others are influenced by trans-acting factors, such as proteins or RNAs that can regulate multiple genes from a distance. Disentangling these two mechanisms has been difficult, particularly with older short-read sequencing methods that break RNA into small fragments, obscuring the full picture of how exons are arranged.

To address this, the researchers applied long-read RNA sequencing combined with a new computational tool called isoLASER. This approach captures entire RNA molecules in single reads, allowing the full structure of spliced transcripts to be observed. The isoLASER method then separates splicing events into cis- or trans-directed categories within individual samples, revealing how each person’s unique genetic makeup shapes their RNA splicing landscape.

isoLASER overview and benchmarking

a Variant calling performance of isoLASER, GATK HaplotypeCaller (HC), DeepVariant, and Clair3 with the HG002 data. Precision and Recall are shown for different read coverage cutoffs. The dashed curves indicate F1 score thresholds. b Phasing comparison of heterozygous variants in HG002 between isoLASER, HapCUT2, and the diploid genome assembly-based phasing from the Human Pangenome Research Consortium (HPRC). Bar plots show the number of variants successfully phased by either or both methods. The pie charts above each bar depict the switch-error rate for isoLASER relative to HapCUT2 and HPRC, respectively. The very small orange wedge represents the low frequency of small errors, indicating high phasing accuracy. No variants were observed that were phased by isoLASER only. c Number of genes with at least one cis-directed splicing event identified by isoLASER or with allele-specific transcript expression identified by LORALS in the ENCODE human tissue dataset. d A cis-directed event identified in the gene WASHC2C. No allele-specific transcript expression was identified for this gene using LORALS. The cis- and trans-directed exonic parts are highlighted in blue and red, respectively. The delta PSI of the cis-directed event calculated by isoLASER is shown on the side.

One of the most striking findings from the study was that splicing patterns influenced by genetic variation are highly individual-specific rather than tissue-specific. In other words, the genetic control of splicing depends more on who you are than on which tissue the RNA comes from. This insight highlights the deeply personal nature of genetic regulation and could help explain why people respond differently to diseases or therapies.

Using this method, the team analyzed data from both human and mouse samples and discovered thousands of cis-directed splicing events that appear to be influenced by genetic variants. These events were found in many genes across the genome, including some with strong links to human disease. In particular, the researchers identified previously undetected splicing variations in genes associated with Alzheimer’s disease, such as MAPT and BIN1, which play roles in the formation of tau proteins and neuronal health.

The study also shed new light on the HLA (human leukocyte antigen) genes, which are key to immune system function. Because these genes are highly variable and complex, they have historically been difficult to study with short-read sequencing. The long-read approach allowed the researchers to clearly see how cis-regulated splicing events occur within these challenging regions.

By distinguishing between cis- and trans-directed mechanisms, the research provides a powerful new framework for understanding how genetic differences affect RNA processing. This knowledge could ultimately improve our ability to interpret genetic variants linked to disease and inform more personalized approaches to diagnosis and treatment.

The use of long-read sequencing technologies, combined with innovative analytical tools like isoLASER, is transforming how scientists explore the relationship between genetic variation, RNA splicing, and disease. As sequencing technologies continue to advance, these insights will play a crucial role in unraveling the molecular complexity of human health and paving the way for precision medicine.

Availability – The source code for isoLASER is publicly available at https://github.com/gxiaolab/isoLASER.