text: Transcriptome-wide analysis of alternative splicing is typically performed by high-throughput RNA-sequencing. Most commonly, by short-read sequencing, such as by Illumina instrumentation. But even more informative, by long-read sequencing, such as by Nanopore or PacBio instrumentation. Transcriptome-wide analyses can for example be used to measure the amount of deviating alternative splicing, such as in a cancer cohort.
  Deep sequencing technologies have been used to conduct genome-wide analyses of both unprocessed and processed mRNAs; thus providing insights into alternative splicing. For example, results from use of deep sequencing indicate that, in humans, an estimated 95% of transcripts from multiexon genes undergo alternative splicing, with a number of pre-mRNA transcripts spliced in a tissue-specific manner. Functional genomics and computational approaches based on multiple instance learning have also been developed to integrate RNA-seq data to predict functions for alternatively spliced isoforms. Deep sequencing has also aided in the in vivo detection of the transient lariats that are released during splicing, the determination of branch site sequences, and the large-scale mapping of branchpoints in human pre-mRNA transcripts.
  More historically, alternatively spliced transcripts have been found by comparing EST sequences, but this requires sequencing of very large numbers of ESTs. Most EST libraries come from a very limited number of tissues, so tissue-specific splice variants are likely to be missed in any case. High-throughput approaches to investigate splicing have, however, been developed, such as: DNA microarray-based analyses, RNA-binding assays, and deep sequencing. These methods can be used to screen for polymorphisms or mutations in or around splicing elements that affect protein binding. When combined with splicing assays, including in vivo reporter gene assays, the functional effects of polymorphisms or mutations on the splicing of pre-mRNA transcripts can then be analyzed.
  In microarray analysis, arrays of DNA fragments representing individual exons (e.g. Affymetrix exon microarray) or exon/exon boundaries (e.g. arrays from ExonHit or Jivan) have been used. The array is then probed with labeled cDNA from tissues of interest. The probe cDNAs bind to DNA from the exons that are included in mRNAs in their tissue of origin, or to DNA from the boundary where two exons have been joined. This can reveal the presence of particular alternatively spliced mRNAs.
  CLIP (Cross-linking and immunoprecipitation) uses UV radiation to link proteins to RNA molecules in a tissue during splicing. A trans-acting splicing regulatory protein of interest is then precipitated using specific antibodies. When the RNA attached to that protein is isolated and cloned, it reveals the target sequences for that protein. Another method for identifying RNA-binding proteins and mapping their binding to pre-mRNA transcripts is "Microarray Evaluation of Genomic Aptamers by shift (MEGAshift)".net This method involves an adaptation of the "Systematic Evolution of Ligands by Exponential Enrichment (SELEX)" method together with a microarray-based readout. Use of the MEGAshift method has provided insights into the regulation of alternative splicing by allowing for the identification of sequences in pre-mRNA transcripts surrounding alternatively spliced exons that mediate binding to different splicing factors, such as ASF/SF2 and PTB. This approach has also been used to aid in determining the relationship between RNA secondary structure and the binding of splicing factors.
  Use of reporter assays makes it possible to find the splicing proteins involved in a specific alternative splicing event by constructing reporter genes that will express one of two different fluorescent proteins depending on the splicing reaction that occurs. This method has been used to isolate mutants affecting splicing and thus to identify novel splicing regulatory proteins inactivated in those mutants.
  Recent advancements in protein structure prediction have facilitated the development of new tools for genome annotation and alternative splicing anlaysis. For instance, isoform.io, a platform guided by protein structure predictions, has evaluated hundreds of thousands of isoforms of human protein-coding genes assembled from numerous RNA sequencing experiments across a variety of human tissues. This comprehensive analysis has led to the identification of numerous isoforms with more confidently predicted structure and potentially superior function compared to canonical isoforms in the latest human gene database. By integrating structural predictions with expression and evolutionary evidence, this approach has demonstrated the potential of protein structure prediction as a tool for refining the annotation of the human genome.