Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments.
Structure probing coupled with high-throughput sequencing could revolutionize our understanding of the role of RNA structure in regulation of gene expression. Despite recent technological advances, intrinsic noise and high sequence coverage requirements greatly limit the applicability of these techniques. Here we describe a probabilistic modeling pipeline that accounts for biological variability and biases in the data, yielding statistically interpretable scores for the probability of nucleotide modification transcriptome wide. Using two yeast data sets, we demonstrate that our method has increased sensitivity, and thus our pipeline identifies modified regions on many more transcripts than do existing pipelines. Our method also provides confident predictions at much lower sequence coverage levels than those recommended for reliable structural probing. Our results show that statistical modeling extends the scope and potential of transcriptome-wide structure probing experiments.
School of Informatics, University of Edinburgh, Edinburgh, UK.
Alina
A
Selega
Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, UK.
Christel
C
Sirocchi
Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, UK.
Ira
I
Iosub
Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, UK.
Sander
0000-0003-4387-1271
S
Granneman
School of Informatics, University of Edinburgh, Edinburgh, UK.|Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, UK.
Guido
G
Sanguinetti
D000465:Algorithms; D020029:Base Pairing; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry* / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D059467:Transcriptome / Q000235:genetics*
D012313:RNA