How Can A Single Mutation Affect Splicing Regulation?

Alternative splicing is a highly orchestrated process that uses a multitude of regulatory mechanisms. Splicing specificity involves a precise interaction between cis- and trans-acting regulatory elements, and factors that disrupt these interactions can result in aberrant splicing. There are multiple ways in which mutations can affect splicing fidelity:

• A point mutation in the cis-acting splice element can either enhance or impair binding to splicing factors or inhibitors and thus change the skipping or inclusion of a particular exon.
• A point mutation can introduce a new cis-acting element located in the middle of an exon or an intron.
• Point mutations can introduce stop codons that target the transcript for degradation by the nonsense-mediated decay pathway.
• Other mutations around the 5’ or 3’ splice site positions can also lead to incorrect splicing, such as exon skipping, activation of a cryptic splice site, or intron retention.
• Loss of function mutations in the trans-acting factors as well as the spliceosome machinery components can severely impact isoform balance.

Global analysis of alternative splicing is essential to establish the functional and physiological consequences of alternative splicing and aberrant splice isoforms. Recent advances in high-throughput technologies have facilitated studies of genome-wide alternative splicing. To address the challenge of variations in splicing, several splice-sensitive platforms, such as microarrays and high-throughput sequencing, have been developed.

Microarray-based detection of gene splicing

Microarray-based gene splicing detection poses some unique challenges in designing probes for isoforms with a high degree of homology. To differentiate between these isoforms, microarrays can use a combination of exon and exon-exon junction probes. Three microarray designs for genome-wide splicing analysis are exon arrays, splice junction arrays, and tiled arrays.

• Exon Arrays

In contrast to traditional expression arrays that measure overall transcript abundance, exon arrays, such as Affymetrix GeneChip Human Exon 1.0 ST Arrays, can detect genome-wide gene expression and alternative exon usage simultaneously. This is made possible by increasing resolution with multiple exon-centric probes within every annotated and predicted exon. Multiple probes cover each exon, distinguishing between different isoforms. While this technology permits a comprehensive and unbiased global transcriptome coverage, it focuses on detection of transcribed regions, not splice junctions, and therefore does not contain splice-junction probes. However, because exon arrays consist of multiple probes within every annotated and predicted exon, they permit discovery of novel variations in splicing.

• Splice Junction Arrays

Splice junction microarrays contain annotated exon–exon junction probes exclusive to individual splice isoforms and are used to measure a predetermined set of alternative splicing events. Junction probes are position-constrained and are usually located within constitutive exons to first detect transcript expression within a sample and then assess alternative exon splicing. Studies using these arrays have repeatedly shown that transcripts regulated at the level of alternative splicing comprise a distinct population from those regulated at the level of transcript abundance.

• Tiled Genomic Arrays

Genome tiling microarrays use a set of overlapping probes representing the whole genome. This allows mapping of transcribed regions to a very high resolution, from several base pairs to approximately 100 bp. The overlapping probe design can produce an unbiased look at gene and exon expression because previously non-annotated genes, exons, non-polyadenylated transcripts, and splicing events can still be incorporated and interrogated. These arrays provide comprehensive coverage and eliminate the need for prior knowledge of exon coordinates, thus allowing de novo discovery. However, the added amount of information comes at a significant expense and posses a computational challenge for analysis.

Detecting splice variants with Next Generation Sequencing technology

The recent development of the high-throughput sequencing (HTS) technologies has opened a new frontier for massively parallel and unbiased analyses of entire transcriptomes by deep-sequencing. RNA-sequencing (RNA-seq) uses adapter-tagged libraries of short cDNAs prepared from fragmented total RNA, and generates tens to hundreds of millions of short sequence reads in just a few days. RNA-seq provides several advantages over microarray technology, including avoiding background noise due to cross-hybridization and bad probe design, while providing unbiased sequence determination without a priori knowledge of genome composition, adding tremendous profiling coverage and quantitative accuracy. RNA-seq allows the detection of novel splice variants and genome-wide splice junctions. While RNA-seq offers unprecedented coverage for reduced cost, the greatest challenge it faces is the handling, processing, and analysis of unprecedentedly huge amounts of data. Because exons span 200 to 300 bp on average, due to the nature of short sequencing reads, high read numbers are required to sufficiently profile exon boundaries and distinguish different splice isoform levels. Nonetheless, a rapid development of technologies that can simultaneously analyze genome-wide gene expression and alternative exon usage should enrich our understanding of the functional consequences of alternative splicing and the regulatory splicing factors. In the end, the ultimate goal is to be able to predict how particular changes in the sequence of cis or trans regulatory elements can affect splicing and produce an altered functional state, such as disease.