PUBLICATION

Genome wide analysis of 3'-UTR sequence elements and proteins regulating mRNA stability during maternal-to-zygotic transition in zebrafish

Authors
Vejnar, C.E., Abdelmessih, M., Takacs, C., Yartseva, V., Oikonomou, P., Christiano, R., Stoeckius, M., Lau, S., Lee, M., Beaudoin, J.D., Musaev, D., Darwich-Codore, H., Walther, T., Tavazoie, S., Cifuentes, D., Giraldez, A.
ID
ZDB-PUB-190624-2
Date
2019
Source
Genome research   29(7): 1100-1114 (Journal)
Registered Authors
Cifuentes, Daniel, Giraldez, Antonio, Lee, Miler, Takacs, Carter M., Vejnar, Charles
Keywords
none
MeSH Terms
  • 3' Untranslated Regions*
  • Amino Acid Motifs
  • Animals
  • Binding Sites
  • Gene Expression Regulation, Developmental*
  • Machine Learning
  • Models, Genetic
  • RNA Stability/genetics*
  • RNA-Binding Proteins/metabolism*
  • Regulatory Sequences, Ribonucleic Acid
  • Zebrafish/embryology
  • Zebrafish/genetics
  • Zygote
PubMed
31227602 Full text @ Genome Res.
Abstract
Post-transcriptional regulation plays a crucial role in shaping gene expression. During the Maternal-to-Zygotic Transition (MZT), thousands of maternal transcripts are regulated. However, how different cis-elements and trans-factors are integrated to determine mRNA stability remains poorly understood. Here, we show that most transcripts are under combinatorial regulation by multiple decay pathways during zebrafish MZT. Using a massively parallel reporter assay, we identified cis-regulatory sequences in the 3'-UTR, including U-rich motifs that are associated with increased mRNA stability. In contrast, miR-430 target sequences, UAUUUAUU AU-rich elements (ARE), CCUC and CUGC elements emerged as destabilizing motifs, with miR-430 and AREs causing mRNA deadenylation upon genome activation. We identified trans-factors by profiling RNA-protein interactions and found that poly(U) binding proteins are preferentially associated with 3'-UTR sequences and stabilizing motifs. We demonstrate that this activity is antagonized by C-rich motifs and correlated with protein binding. Finally, we integrated these regulatory motifs into a machine learning model that predicts reporter mRNA stability in vivo.
Genes / Markers
Figures
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Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping