Editing Alternative splicing (section)

==Genome-scale (transcriptome-wide) analysis==
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.<ref name="Stromme">{{cite journal | vauthors = Strømme JM, Johannessen B, Skotheim RI | title = Deviating alternative splicing as a molecular subtype of microsatellite stable colorectal cancer | journal = JCO Clinical Cancer Informatics | volume = 7 | pages = e2200159 | date = 2023 | issue = 7 | pmid = 36821799 | doi = 10.1200/CCI.22.00159 | doi-access = free | hdl = 10852/108838 | hdl-access = free }}</ref>

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.<ref name=Pan2008/> 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.<ref name=Eksi/> 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.<ref>{{cite journal | vauthors = Taggart AJ, DeSimone AM, Shih JS, Filloux ME, Fairbrother WG | title = Large-scale mapping of branchpoints in human pre-mRNA transcripts in vivo | journal = Nature Structural & Molecular Biology | volume = 19 | issue = 7 | pages = 719–21 | date = June 2012 | pmid = 22705790 | pmc = 3465671 | doi = 10.1038/nsmb.2327 }}</ref>

More historically, alternatively spliced transcripts have been found by comparing [[Expressed sequence tag|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.<ref name=Lim/><ref name=Wang/><ref>{{cite journal | vauthors = Fairbrother WG, Yeh RF, Sharp PA, Burge CB | title = Predictive identification of exonic splicing enhancers in human genes | journal = Science | volume = 297 | issue = 5583 | pages = 1007–13 | date = August 2002 | pmid = 12114529 | doi = 10.1126/science.1073774 | s2cid = 8689111 | bibcode = 2002Sci...297.1007F | doi-access = free }}</ref>

In microarray analysis, arrays of DNA fragments representing individual [[exon]]s (''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.<ref name=Pan2004>{{cite journal | vauthors = Pan Q, Shai O, Misquitta C, Zhang W, Saltzman AL, Mohammad N, Babak T, Siu H, Hughes TR, Morris QD, Frey BJ, Blencowe BJ | display-authors = 6 | title = Revealing global regulatory features of mammalian alternative splicing using a quantitative microarray platform | journal = Molecular Cell | volume = 16 | issue = 6 | pages = 929–41 | date = December 2004 | pmid = 15610736 | doi = 10.1016/j.molcel.2004.12.004 | doi-access = free }}</ref>

CLIP ([[Cross-link]]ing 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.<ref name=David/> 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<ref>{{cite journal | vauthors = Watkins KH, Stewart A, Fairbrother W | title = A rapid high-throughput method for mapping ribonucleoproteins (RNPs) on human pre-mRNA | journal = Journal of Visualized Experiments | volume = 34 | issue = 34 | pages = 1622 | date = December 2009 | pmid = 19956082 | pmc = 3152247 | doi = 10.3791/1622 }}</ref> This method involves an adaptation of the "Systematic Evolution of Ligands by Exponential Enrichment (SELEX)" method<ref>{{cite journal | vauthors = Tuerk C, Gold L | title = Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase | journal = Science | volume = 249 | issue = 4968 | pages = 505–10 | date = August 1990 | pmid = 2200121 | doi = 10.1126/science.2200121 | bibcode = 1990Sci...249..505T }}</ref> 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.<ref>{{cite journal | vauthors = Chang B, Levin J, Thompson WA, Fairbrother WG | title = High-throughput binding analysis determines the binding specificity of ASF/SF2 on alternatively spliced human pre-mRNAs | journal = Combinatorial Chemistry & High Throughput Screening | volume = 13 | issue = 3 | pages = 242–52 | date = March 2010 | pmid = 20015017 | pmc = 3427726 | doi = 10.2174/138620710790980522 }}</ref> This approach has also been used to aid in determining the relationship between RNA secondary structure and the binding of splicing factors.<ref name="ncbi.nlm.nih.gov"/>

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.<ref name=David>{{cite journal | vauthors = David CJ, Manley JL | title = The search for alternative splicing regulators: new approaches offer a path to a splicing code | journal = Genes & Development | volume = 22 | issue = 3 | pages = 279–85 | date = February 2008 | pmid = 18245441 | pmc = 2731647 | doi = 10.1101/gad.1643108 }}</ref>

Recent advancements in protein structure prediction have facilitated the development of new tools for genome annotation and alternative splicing analysis. 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.<ref>{{Cite journal |last1=Sommer |first1=Markus J. |last2=Cha |first2=Sooyoung |last3=Varabyou |first3=Ales |last4=Rincon |first4=Natalia |last5=Park |first5=Sukhwan |last6=Minkin |first6=Ilia |last7=Pertea |first7=Mihaela |last8=Steinegger |first8=Martin |last9=Salzberg |first9=Steven L. |date=2022-12-15 |title=Structure-guided isoform identification for the human transcriptome |journal=eLife |volume=11 |pages=e82556 |language=en |doi=10.7554/eLife.82556|pmid=36519529 |pmc=9812405 |doi-access=free }}</ref>