ArticleMolecular cell2017
A Massively Parallel Reporter Assay of 3' UTR Sequences Identifies In Vivo Rules for mRNA Degradation.
Article in Molecular cell, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 70 papers.
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Who cites it
70 citing papers in PubMed.
- Decoding RNA-protein interactions using high-throughput methods.RNA biology · 2026Review
- Promoter identity shapes splicing outcomes and fidelity.Nature communications · 2026Article
- Compression-induced metabolic adaptation drives confined tumor cell migration and distant metastasis via malate-dependent microtubule reinforcement.Cell research · 2026Article
- NaP-TRAP: A Versatile and Accessible Workflow to Dissect Principles of Translational Regulation and mRNA Stability.Current protocols · 2026Article
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Post-transcriptional regulatory networks: The dynamic interplay of RNA-binding proteins.The FEBS journal · 2026Review
- An in vivo parallelized reporter assay to uncover tissue-specific splicing regulatory sequences in a multicellular animal.Nucleic acids research · 2026Article
- NaP-TRAP: A versatile and accessible workflow to dissect principles of translational regulation and mRNA stability.bioRxiv : the preprint server for biology · 2026Article
- Major transitions in early coral development: novel insights enabled by visualisation of a comprehensive transcriptomic dataset for Acropora millepora.BMC biology · 2026Article
- Learning sequence-function relationships with scalable, interpretable Gaussian processes.bioRxiv : the preprint server for biology · 2025Article
- U-rich elements drive pervasive cryptic splicing in 3' UTR massively parallel reporter assays.Nature communications · 2025Article
- Quantitative modeling of mRNA degradation reveals tempo-dependent mRNA clearance in early embryos.Nucleic acids research · 2025Article
- The quantitative impact of 3'UTRs on gene expression.Nucleic acids research · 2025Article
- The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis.Developmental cell · 2025Article
- The maternal-to-zygotic transition: reprogramming of the cytoplasm and nucleus.Nature reviews. Genetics · 2025Review
- Article
- NaP-TRAP reveals the regulatory grammar in 5'UTR-mediated translation regulation during zebrafish development.Nature communications · 2024Article
- Decoding biology with massively parallel reporter assays and machine learning.Genes & development · 2024Review
- Review
- Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
The stability of mRNAs is regulated by signals within their sequences, but a systematic and predictive understanding of the underlying sequence rules remains elusive. Here we introduce UTR-seq, a combination of massively parallel reporter assays and regression models, to survey the dynamics of tens of thousands of 3' UTR sequences during early zebrafish embryogenesis. UTR-seq revealed two temporal degradation programs: a maternally encoded early-onset program and a late-onset program that accelerated degradation after zygotic genome activation. Three signals regulated early-onset rates: stabilizing poly-U and UUAG sequences and destabilizing GC-rich signals. Three signals explained late-onset degradation: miR-430 seeds, AU-rich sequences, and Pumilio recognition sites. Sequence-based regression models translated 3' UTRs into their unique decay patterns and predicted the in vivo effect of sequence signals on mRNA stability. Their application led to the successful design of artificial 3' UTRs that conferred specific mRNA dynamics. UTR-seq provides a general strategy to uncover the rules of RNA cis regulation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.