Power-law Behavior of the Alternative Splicing of Exons in Human Transcriptome

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Published Sep 2, 2019
DOI https://doi.org/10.9734/arrb/2019/v32i630105
    Page: 1-13

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Vasily V. Grinev
Department of Genetics, Faculty of Biology, Belarusian State University, Minsk, Republic of Belarus.
Petr V. Nazarov
Proteome and Genome Research Unit, Luxembourg Institute of Health, Strassen, Luxembourg.
Eugene A. Klimov
Department of Genetics, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation and Center of Experimental Embryology and Reproductive Biotechnologies, Moscow, Russian Federation.

Abstract

Aims: To establish the common rules of exon combinatorics during RNA splicing.

Study Design: Inferring a plausible statistical model of exon combinatorics from the annotated models of human genes during RNA splicing.

Place and Duration of Study: Department of Genetics (Belarusian State University), Proteome and Genome Research Unit (Luxembourg Institute of Health), Department of Genetics (Lomonosov Moscow State University) and Moscow Center of Experimental Embryology and Reproductive Biotechnologies, between January 2017 and July 2019.

Methodology: We used human mRNA and EST sequences from GenBank (1093522 unique records in total) and linear models of the human genes from Ensembl (58051 genes), AceView (72384 genes), ECgene (57172 genes), NCBI RefSeq (54262 genes), UCSC Genome Browser (58037 genes) and VEGA (54950 genes) to calculate a combinatorial index of human exons. We inferred the most plausible statistical model describing the distribution of combinatorial index of human exons using Clauset’s mathematical formalism. Predictors of the combinatorial index values and functional outcomes of the predefined behavior of exons during splicing were also determined.

Results: Power-law is the most plausible statistical model describing the combinatorics of exons during RNA splicing. The combinatorial index of human exons is defined by more than 90% by the 138 features that have different importance. The most important of these features are the abundance of exon in transcripts, the strength of splice sites, the rank of exon in transcripts and the type of exon. Analysis of the marginal effects shows that different values of the same feature have unequal influence on the combinatorial index of human exons. Power-law behavior of exons during RNA splicing pre-determines structural diversity of transcripts, low sensitivity of splicing process to random perturbations and its high vulnerability to manipulation with highly combinative exons.

Conclusion: Exons widely involved in alternative splicing are a part of the common power-law phenomenon in human cells. The power-law behavior of exons during RNA splicing gives the unique characteristics to human genes.

Keywords:
Human exons, RNA splicing, combinatorics, statistical modeling, power-law, predictors, functional outcomes.

Article Details

How to Cite
Grinev, V., Nazarov, P., & Klimov, E. (2019). Power-law Behavior of the Alternative Splicing of Exons in Human Transcriptome. Annual Research & Review in Biology, 32(6), 1-13. https://doi.org/10.9734/arrb/2019/v32i630105
Issue
2019 - Volume 32 [Issue 6]
Section
Original Research Article

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