Alternative Splice Site Selection

2012 ◽  
pp. 93-107
Author(s):  
Miguel B. Coelho ◽  
Christopher W. J. Smith
Keyword(s):  
Alternative Splice ◽  
Splice Site ◽  
Site Selection ◽  
Splice Site Selection ◽  
Alternative Splice Site

Factors That Influence Alternative Splice Site Selection in Vitro

1987 ◽  
pp. 97-112 ◽  
Author(s):  
JAMES L. MANLEY ◽  
JONATHAN C.S. NOBLE ◽  
XIN-YUAN FU ◽  
HUI GE
Keyword(s):  
Alternative Splice ◽  
Splice Site ◽  
Site Selection ◽  
Splice Site Selection ◽  
Alternative Splice Site

scholarly journals Splicing Factor SRp30c Interaction with Y-box Protein-1 Confers Nuclear YB-1 Shuttling and Alternative Splice Site Selection

2003 ◽  
Vol 278 (20) ◽  
pp. 18241-18248 ◽  
Author(s):  
Ute Raffetseder ◽  
Björn Frye ◽  
Thomas Rauen ◽  
Karsten Jürchott ◽  
Hans-Dieter Royer ◽  
...  
Keyword(s):  
Alternative Splice ◽  
Splice Site ◽  
Site Selection ◽  
Splicing Factor ◽  
Splice Site Selection ◽  
Alternative Splice Site

scholarly journals COSSMO: Predicting Competitive Alternative Splice Site Selection using Deep Learning

2018 ◽  
Author(s):  
Hannes Bretschneider ◽  
Shreshth Gandhi ◽  
Amit G Deshwar ◽  
Khalid Zuberi ◽  
Brendan J Frey
Keyword(s):  
Alternative Splice ◽  
Splice Site ◽  
Site Selection ◽  
Donor Site ◽  
High Specificity ◽  
Supplementary Information ◽  
Acceptor Site ◽  
Splice Site Selection ◽  
Competitive Effects ◽  
Alternative Splice Site

AbstractMotivationAlternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends strongly on the strength of neighboring sites. Here we present a new model named Competitive Splice Site Model (COSSMO), which explicitly models these competitive effects and predict the PSI distribution over any number of putative splice sites. We model an alternative splicing event as the choice of a 3’ acceptor site conditional on a fixed upstream 5’ donor site, or the choice of a 5’ donor site conditional on a fixed 3’ acceptor site. We build four different architectures that use convolutional layers, communication layers, LSTMS, and residual networks, respectively, to learn relevant motifs from sequence alone. We also construct a new dataset from genome annotations and RNA-Seq read data that we use to train our model.ResultsCOSSMO is able to predict the most frequently used splice site with an accuracy of 70% on unseen test data, and achieve an R2 of 60% in modeling the PSI distribution. We visualize the motifs that COSSMO learns from sequence and show that COSSMO recognizes the consensus splice site sequences as well as many known splicing factors with high specificity.AvailabilityOur dataset is available from http://cossmo.deepgenomics.com.Contactfrey@deepgenomics.comSupplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals COSSMO: predicting competitive alternative splice site selection using deep learning

2018 ◽  
Vol 34 (13) ◽  
pp. i429-i437 ◽  
Author(s):  
Hannes Bretschneider ◽  
Shreshth Gandhi ◽  
Amit G Deshwar ◽  
Khalid Zuberi ◽  
Brendan J Frey
Keyword(s):  
Deep Learning ◽  
Alternative Splice ◽  
Splice Site ◽  
Site Selection ◽  
Splice Site Selection ◽  
Alternative Splice Site

scholarly journals The anti-angiogenic isoforms of VEGF in health and disease

2009 ◽  
Vol 37 (6) ◽  
pp. 1207-1213 ◽  
Author(s):  
Yan Qiu ◽  
Coralie Hoareau-Aveilla ◽  
Sebastian Oltean ◽  
Steven J. Harper ◽  
David O. Bates
Keyword(s):  
Splice Site ◽  
Site Selection ◽  
Age Related Macular Degeneration ◽  
Splicing Factor ◽  
Splice Site Selection ◽  
Age Related ◽  
Normal Human ◽  
Radical Revision

Anti-angiogenic VEGF (vascular endothelial growth factor) isoforms, generated from differential splicing of exon 8, are widely expressed in normal human tissues but down-regulated in cancers and other pathologies associated with abnormal angiogenesis (cancer, diabetic retinopathy, retinal vein occlusion, the Denys–Drash syndrome and pre-eclampsia). Administration of recombinant VEGF165b inhibits ocular angiogenesis in mouse models of retinopathy and age-related macular degeneration, and colorectal carcinoma and metastatic melanoma. Splicing factors and their regulatory molecules alter splice site selection, such that cells can switch from the anti-angiogenic VEGFxxxb isoforms to the pro-angiogenic VEGFxxx isoforms, including SRp55 (serine/arginine protein 55), ASF/SF2 (alternative splicing factor/splicing factor 2) and SRPK (serine arginine domain protein kinase), and inhibitors of these molecules can inhibit angiogenesis in the eye, and splice site selection in cancer cells, opening up the possibility of using splicing factor inhibitors as novel anti-angiogenic therapeutics. Endogenous anti-angiogenic VEGFxxxb isoforms are cytoprotective for endothelial, epithelial and neuronal cells in vitro and in vivo, suggesting both an improved safety profile and an explanation for unpredicted anti-VEGF side effects. In summary, C-terminal distal splicing is a key component of VEGF biology, overlooked by the vast majority of publications in the field, and these findings require a radical revision of our understanding of VEGF biology in normal human physiology.

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