Decoding TDP-43 Dependent Cryptic Splicing in Amyotrophic Lateral Sclerosis and Identifying Novel Disease-causing Genes
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Abstract
\sectionBackground Amyotrophic lateral sclerosis (ALS), is a neurodegenerative disease that primarily effects motor neurons in both brain and spinal cord \citezarei2015comprehensive. Several independent studies conformed the deposition of TAR DNA-binding protein (TDP)-43 aggregates in the cytoplasm of the effected cells suggesting the role of TDP-43 in ALS. However, the molecular mechanism of TDP-43 in ALS is not well established. It is only recently reported that TDP-43 contributes to pre-mRNA splicing by inhibiting cryptic exons \citeling2015tdp. While this is a very interesting observation, it opens to several intriguing aspects of TDP-43 dependent splicing errors like preferential 5'/3' errors, enrichment of specific alternative splicing events and Intron retentions. A systematic characterization and decoding TDP-43 cryptic splicing is critical to better understanding of the molecular pathogenesis of ALS. However, none of the existing computational approaches are precisely designed for cryptic splice characterization, which advocates a strong need of robust genome-wise scalable pipeline. \sectionResults In this study we applied CrypSplice \citetan2016extensive, in-house novel cryptic splice site detection and characterization method on several publicly available TDP-43 datasets. Every junction is subjected to a beta binomial test and characterize to aid molecular inferences. Upon exploring 18 TDP-43 knock-down samples across different tissues and cell lines we found that genes that are targeted by cryptic splicing are enriched in cell cycle, autophagy and protein folding. While this is in good agreement with previous studies we uncovered a preferential enrichment of 5' splice site errors indicating a U1 spliceosome mediated mechanism. To infer a co-splicing network, similar cryptic splicing characterization was performed on a total of 236 samples covering 118 RNA binding proteins (RBPs) \citeyalamanchili2017data. A network of RBPs was constructed based on the induced cryptic load similarity w.r.t TDP-43 cryptic signature that are also validated by TDP-43 binding (eCLIP-Seq). We found other reported ALS genes like FUS, HNRNPA1 and TAF15 enriched in the neighboring genes of TDP-43 in the RBP network. Novel (putative) ALS-causing RBPs are identified and prioritized using Network Propagation, Guilt by association, and Cryptic signature similarity. \sectionConclusion Through a comprehensive CrypSplice analysis we uncovered a preferential enrichment of TDP-43 dependent 5' splice site errors. Network propagation and prioritization of RBP cryptic network yielded a list of (putative) novel ALS associated genes. Further follow-ups through genetic screening could discover more ALS causing genes and aid decoding the underlying molecular mechanism.
References
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Sara Zarei, Karen Carr, Luz Reiley, Kelvin Diaz, Orleiquis Guerra, Pablo Fernandez Altamirano, Wilfredo Pagani, Daud Lodin, Gloria Orozco, and Angel Chinea. A comprehensive review of amyotrophic lateral sclerosis. Surgical neurology international, 6, 2015.
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Jonathan P Ling, Olga Pletnikova, Juan C Troncoso, and Philip C Wong. Tdp-43 repression of nonconserved cryptic exons is compromised in als-ftd. Science, 349(6248):650--655, 2015.
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Qiumin Tan, Hari Krishna Yalamanchili, Jeehye Park, Antonia De Maio, HsiangChih Lu, Ying-Wooi Wan, Joshua J White, Vitaliy V Bondar, Layal S Sayegh, Xiuyun Liu, et al. Extensive cryptic splicing upon loss of rbm17 and tdp43 in neurodegeneration models. Human molecular genetics, 25(23):5083--5093, 2016.
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Hari Krishna Yalamanchili, Ying-Wooi Wan, and Zhandong Liu. Data analysis pipeline for rna-seq experiments: From differential expression to cryptic splicing. Current protocols in bioinformatics, pages 11--15, 2017.
Index Terms
- Decoding TDP-43 Dependent Cryptic Splicing in Amyotrophic Lateral Sclerosis and Identifying Novel Disease-causing Genes
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August 2018
727 pages
ISBN:9781450357944
DOI:10.1145/3233547
- General Chairs:
- Amarda Shehu,
- Cathy Wu,
- Program Chairs:
- Christina Boucher,
- Jing Li,
- Hongfang Liu,
- Mihai Pop
Copyright © 2018 Owner/Author.
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Published: 15 August 2018
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- National Institute of General Medical Sciences
- National Science Foundation - Division of Mathematical Sciences
- Houston Endowment (Z.L.)
- Huffington Foundation
- Cancer Prevention Research Institute of Texas
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BCB '18
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BCB '18: 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
August 29 - September 1, 2018
DC, Washington, USA
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BCB '18 Paper Acceptance Rate 46 of 148 submissions, 31%;
Overall Acceptance Rate 254 of 885 submissions, 29%
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