Annotation of Alternatively Spliced Proteins and Transcripts with Protein-Folding Algorithms and Isoform-Level Functional Networks

Li, Hongdong; Zhang, Yang; Guan, Yuanfang; Menon, Rajasree; Omenn, Gilbert S.

doi:10.1007/978-1-4939-6783-4_20

Cited by 3 publications

(3 citation statements)

References 63 publications

(110 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…AS is widely implicated in development, aging, and diseases (van den Hoogenhof et al, 2016;Lee and Rio, 2015), but a fuller understanding requires knowing how isoforms alter protein structure and functions (Li et al, 2017). Only a minority of expressed transcripts have the potential to be translated (Hao et al, 2015), whereas the rest may be removed by nonsense-mediated decay (NMD) or co-translational proteolysis (Weatheritt et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…RNA-seq experiments have discovered over 100,000 AS transcripts in the human genome (Pan et al, 2008;Wang et al, 2008), but identifying which AS isoforms are functionally important is a major unmet goal, and critically, most have never been detected at the protein level. Although computational approaches can predict isoform conservation and function (Li et al, 2017;Rodriguez et al, 2013) and Ribo-seq can survey alternative transcripts engaged to ribosomes (Weatheritt et al, 2016;van Heesch et al, 2019), these techniques stop short of assessing AS protein products empirically.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

et al. 2019

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

et al. 2019

View full text Add to dashboard Cite

show abstract

“…On the other hand, other methods have been developed to predict biological functions at the isoform-level. These approaches are mainly based on the protein structure (3D model [51,52] or domains [53]), amino acid sequence, and expression [4,[29][30][31] to associate GO functions to each isoform. Surprisingly, none of the previous algorithms combined RNA expression with structural information.…”

Section: Functional Impact Of Alternative Splicingmentioning

confidence: 99%

Statistical, functional, upstream, and downstream analysis of Alternative Splicing.

Ferrer-Bonsoms¹

View full text Add to dashboard Cite

Alternative splicing (AS) is a post-transcriptional process by which a single gene can lead to different mRNAs and thus to different functional proteins. AS plays a key role in different diseases including cancer. In fact, all hallmarks of cancer have been associated with different mechanisms of abnormal AS. Therefore, AS has been studied as a source of novel biomarkers for survival or even as therapeutic targets. The advantage of RNA-Sequencing (RNA-Seq) technologies has improved the genetic analysis of the human transcriptome. With the recent advances, it is possible to estimate isoform concentrations with good accuracy. Further, several methodologies have been developed to statistically analyze alternative splicing events. However, some aspects of AS remain an active field of research. In this work I will focus on the reconstruction of the transcriptome, the statistical analysis, the functional impact of AS, and the regulation of AS. There are RNA-Seq methods that estimate the structure and concentration of the isoforms of a gene, but the accuracy of these methods is far from perfect. Theoretical conditions to state the conditions whether a gene can be identified do exist in the case of single-end reads. Nevertheless, no theoretical results are still available for paired-end reads. Regarding the functional impact of AS, the precise functions of many of the individual isoforms are still unknown. Multiple algorithms predict gene functions based on ontologies such as Gene Ontology, but most of these approaches do not distinguish the different functions of the gene transcripts. Besides, the biological impact of changes in aberrant AS is still an open question. The statistical analysis of AS is a challenging problem due to the different accuracy in the estimate of the abundance of the isoforms and therefore of the differential splicing between conditions under study. A statistical approach that does not take into account these different accuracies for different isoforms will not be optimal. Understanding the mechanism that regulates splicing is also a challenge. There are algorithms that predict which RNA-binding protein (RBP) is driving the splicing. In our group, we developed an algorithm that uses published data on cross-linking immunoprecipitation (CLIP) experiments and makes its predictions relying on an enrichment analysis. Some assumptions of the enrichment analysis do not fit with the data and thus some biases are introduced into the prediction. In this work we faced these challenges. We present a method to select the optimal read-fragment length combination to infer the structure and concentration of the isoforms of a gene for RNA-Seq using paired-end reads. This work also provides a framework to state whether the isoforms of a gene can be inferred from paired-end reads or not. We also developed a novel method to predict isoform specific GO functions. Moreover, we described a novel statistical analysis of Alternative Splicing events based on bootstrap. This statistical analysis can be augmented with a protein domain enrichment analysis that aims to explain the functional impact of alternative splicing. Finally, we developed a novel algorithm that performs an enriched analysis based on the Poisson- Binomial distribution that avoids the biases introduced by the Fisher’s exact test and is faster than the state-of-the-art algorithms. All the outcomes of these studies are available at public repositories.

show abstract

ISOGO: Functional annotation of protein-coding splice variants

Ferrer-Bonsoms

Cassol

Fernández-Acín

et al. 2020

Sci Rep

View full text Add to dashboard Cite

the advent of RnA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was developed to annotate gene products according to their biological processes, molecular functions and cellular components. Despite a single gene may have several gene products, most annotations are not isoform-specific and do not distinguish the functions of the different proteins originated from a single gene. Several approaches have tried to automatically annotate ontologies at the isoform level, but this has shown to be a daunting task. We have developed ISOGO (ISOform + GO function imputation), a novel algorithm to predict the function of coding isoforms based on their protein domains and their correlation of expression along 11,373 cancer patients. Combining these two sources of information outperforms previous approaches: it provides an area under precision-recall curve (AUPRC) five times larger than previous attempts and the median AUROC of assigned functions to genes is 0.82. We tested ISOGO predictions on some genes with isoform-specific functions (BRCA1, MADD,VAMP7 and ITSN1) and they were coherent with the literature. Besides, we examined whether the main isoform of each gene-as predicted by APPRIS-was the most likely to have the annotated gene functions and it occurs in 99.4% of the genes. We also evaluated the predictions for isoform-specific functions provided by the CAFA3 challenge and results were also convincing. To make these results available to the scientific community, we have deployed a web application to consult ISOGO predictions (https://biotecnun.unav. es/app/isogo). Initial data, website link, isoform-specific GO function predictions and R code is available at https://gitlab.com/icassol/isogo. Alternative splicing (AS) is a genetic process by which a single pre-mRNA can originate different mature mRNAs (called isoforms or transcripts) by including or excluding exons and introns 1-4. It is estimated that genes have on average 7 transcripts, that the whole transcriptome there are more than 100,000 AS events 5,6 and that over 90% of human genes contain one or more isoforms 7-10. From a functional point of view, AS is an intriguing process. Some studies show that a large number of sporadic splicing events produce alternative isoforms lowly expressed, and thus may be non-functional noise in the transcription process 11-13. On the other hand, other studies show and experimentally validate that different isoforms originated by alternative splicing may have distinct or even opposite functions 14,15. It is known that AS can cause cellular abnormalities that lead to diverse genetic diseases. All the hallmarks of cancer have their counterpart in AS 16-18. For example, BRCA1 is a tumor suppressor gene related to breast cancer susceptibility. Its isoform originated from skipping exon 11 (that includes a RAD51 inte...

show abstract

Annotation of Alternatively Spliced Proteins and Transcripts with Protein-Folding Algorithms and Isoform-Level Functional Networks

Cited by 3 publications

References 63 publications

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

Statistical, functional, upstream, and downstream analysis of Alternative Splicing.

ISOGO: Functional annotation of protein-coding splice variants

Contact Info

Product

Resources

About