Learning the Sequence Determinants of Alternative Splicing from Millions of Random Sequences
Transcriptomics Dataset
FAIR Metrics
0 evaluations
General Information
AccessionGSE74070
TitleLearning the Sequence Determinants of Alternative Splicing from Millions of Random Sequences
DescriptionMost human transcripts are alternatively spliced, and many disease-causing mutations affect RNA splicing. Towards better modeling the sequence determinants of alternative splicing, we measured the splicing patterns of nearly 2 million (M) synthetic mini-genes, which include degenerate subsequences totaling to nearly 100M bases of variation. The massive size of these training data allowed us to improve upon current models of splicing as well as to gain new mechanistic insights. Our results show that a vast majority of hexamer sequence motifs measurably influence splice site selection when positioned within alternative exons, with multiple motifs acting additively rather than cooperatively. Intriguingly, motifs that enhance (suppress) exon inclusion in alternative 5 splicing also enhance (suppress) exon inclusion in alternative 3 or cassette exon splicing, suggesting a universal mechanism for alternative exon recognition. Finally, our empirically trained models are highly predictive of the effects of naturally occurring variants on alternative splicing in vivo.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE74070
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE74070
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
FAIR Evaluation
Sorry, you must be signed in to evaluate this object.