It has been suggested that alternative splicing plays a forefront role in creating a complex collection of expressed sequences (mRNA) from a smaller number of genes in humans. In fact, Walter Gilbert had expressed that a variety of mRNA isoforms of one gene arises from different combinations of exon-splicing known as alternative splicing (Modrek & Lee, 2002). Alternative splicing can be classified into several types, with each type being different among species. Exon skipping is a type wherein a cassette exon and its bordering introns are spliced out of the transcript. This type is prevalent in higher eukaryotic forms. Two other types of alternative splicing are alternative 3’ splice site (3’ SS) and 5’ SS selection in which two or more splice sites are identified at one end of an exon. These two types account for a small percentage of alternative splicing in higher eukaryotes. Another type of alternative splicing is intron retention, characterized by an intron persisting in the mature mRNA transcript. It is the rarest type of alternative splicing in both vertebrates and invertebrates, but the most prevalent in plants, fungi, and protozoa (Keren et al., 2010).

In the wake of discovering these alternative mRNA forms that diversify protein functions of the same gene, there, however, exists a problem of how to differentiate truly functional forms from those that are not, biologically or otherwise, which further opens up an avenue towards the risk of outright designating a discovered form as functionless mainly because it is perceived to have no obvious function. In this instance, it may be entirely possible that an alternative form causing the inactivity of a protein product may actually be a crucial regulator; hence, a more detailed study should be employed to ascertain this kind of event soundly. This is where bioinformatics may come into play, as it is able to deduce the most probable functional impacts and provide the disease- or tissue-specific trajectories of any form. These predictions may be compiled to create a repository or a community annotated database that would provide base data for specific functional studies (Modrek & Lee, 2002). Ultimately, bioinformatics aims to pinpoint the particular exons alternatively spliced from pre-mRNAs, to determine the pattern at which exons are temporally and spatially regulated, and to discern the splicing factors pertaining to exon regulation (Nilsen & Gravely, 2010).

Within the arsenal of bioinformatics is comparative genomics. This is a tool rooted upon the concept that the degree of similarity between genomes allows the attainment of information with respect to their function. It is utilized in order to identify the possibility of an exon to be constitutive or alternative, and in the process, recognize undiscovered alternative exons, as well as to characterize splicing enhancers or silencers. Moreover, comparative genomics can identify sequences that are involved in RNA structures that control alternative splicing. Despite these powerful applications, comparative genomics still encounters limitations in that the functional significance of a splicing pattern may not necessarily reflect evolutionary conservation despite the reverse being valid. In other words, alternative splicing, through the lens of comparative genomics, exhibits a high degree of evolutionary plasticity. Elements that govern splicing can be easily modified by point mutations in exons or introns; hence, it may be expected that splicing patterns are constantly evolving. This may translate to phenotypic diversity as a phenomenon that stems from non-conserved changes in splicing patterns (Nilsen & Gravely, 2010).

Proteome expansion as a result of alternative splicing has been thoroughly concluded; however, some have mistaken this to bridge a perceived complexity gap. Though proteome size is indeed a factor to take into account with regards to complexity, there are also the components of interactions and regulation to consider (Lareau et al., 2004). Fully understanding alternative splicing entails molecular characterization of the spliceosome structure as well as the analysis of RNA regulators, and due to the complexity of alternative splicing regulation becoming more apparent, epigenetic components such as chromatin structure and histone modifications may also be assessed to elucidate the mechanisms revolving around alternative splicing further. Chromatin structure has been suggested to engage in alternative splicing regulation due to evidences wherein splicing was found to be affected only by specific hormone receptor coregulators that remodeled chromatin. In this case, splicing was not affected by changes in transcription rate, RNA Polymerase II density, promoter strength, or even the saturation of splicing machinery. It has also been suggested that chromatin complexes enact the proper assembly of the pre-spliceosome on pre-mRNA; thus, leading to the notion that splicing factor recruitment directly involves chromatin structure. Moreover, it has been proposed that nucleosomes, which determine the conformation and compaction of chromatin, mark the junction between exons and are purposefully positioned along genes. Thus, the variation in exon length that comprises the formation of different isoforms comes from modifications in chromatin structure facilitated by nucleosome arrangement. Histone modifications have also been put forward as alternative splicing regulators due to evidences that point towards their preferential distribution in exons, indicating a higher density of nucleosomes at these sites. In addition, there is also the disparity of histone modification levels with respect to transcriptional activity that further supports the regulatory role of histone modifications in alternative splicing (Luco et al., 2011).

References:
KEREN H, LEV-MAOR G, AST G. 2010. Alternative splicing and evolution: diversification, exon definition and function. Nature Review Genetics 11(5): 345-355.

LAREAU LF, GREEN RE, BHATNAGAR RS, BRENNER SE. 2004. The evolving roles of alternative splicing. Current Opinion in Structural Biology 14: 273-282.

LUCO RF, ALLO M, SCHOR IE, KORNBLIHTT AR, MISTELI T. 2011. Epigenetics in alternative pre-mRNA splicing. Cell 144(1): 16-26.

MODREK B, LEE C. 2002. A genomic view of alternative splicing. Nature Genetics 30(1): 13-19.

NILSEN TW, GRAVELY BR. 2010. Expansion of the eukaryotic proteome by alternative splicing. Nature 463(7280): 457-463