The role of RNA structure at 5′ untranslated region in microRNA-mediated gene regulation

Gu, Wanjun; Xu, Yuming; Xie, Xueying; Wang, Ting; Ko, Jae Hong; Zhou, Tong

doi:10.1261/rna.044792.114

Cited by 95 publications

(84 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It already has been suggested that secondary structures or upstream open reading frames in the 59 UTR can play a role in mRNA degradation (Oliveira and McCarthy, 1995). The GC content of the 59 UTR and 59 UTR length can influence mRNA structure near the 59 cap, thus regulating posttranscriptional processes (Gu et al, 2014). In particular, the competition between the formation of the translation initiation complex and the degradation machinery at the 59 UTR has been shown to regulate the stability of various transcripts (de la Cruz et al, 2002;Dvir et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

5′ to 3′ mRNA Decay Contributes to the Regulation of Arabidopsis Seed Germination by Dormancy

et al. 2017

View full text Add to dashboard Cite

The regulation of plant gene expression, necessary for development and adaptive responses, relies not only on RNA transcription but also on messenger RNA (mRNA) fate. To understand whether seed germination relies on the degradation of specific subsets of mRNA, we investigated whether the 5' to 3' RNA decay machinery participated in the regulation of this process. Arabidopsis () seeds of () and () mutants displayed distinct dormancy phenotypes. Transcriptome analysis and mutant seeds allowed us to identify genes that are likely to play a role in the control of germination. Study of 5' untranslated region features of these transcripts revealed that specific motifs, secondary energy, and GC content could play a role in their degradation by XRN4 and VCS, and Gene Ontology clustering revealed novel actors of seed dormancy and germination. Several specific transcripts identified as being putative targets of XRN4 and VCS in seeds (, ,, and ) were further studied by reverse genetics, and their functional roles in the germination process were confirmed by mutant analysis. These findings suggest that completion of germination and its regulation by dormancy also depend on the degradation of specific subsets of mRNA.

show abstract

Section: Discussionmentioning

confidence: 99%

5′ to 3′ mRNA Decay Contributes to the Regulation of Arabidopsis Seed Germination by Dormancy

et al. 2017

View full text Add to dashboard Cite

show abstract

“…These elements are the 5′ UTR [69,70], the open reading frames (ORFs) [71,72] and the coding sequence (CDS) for mRNAs [73], which have been included in the search of certain miRNA target prediction tools. For example, the new version of DIANA microT (v5.0) includes the prediction of miRNA:MRE recognition in the CDS region [66].…”

Section: Biological Elements For Computational Analysismentioning

confidence: 99%

Tools for Sequence-Based miRNA Target Prediction: What to Choose?

Riffo‐Campos

Riquelme

Brebi-Mieville

2016

IJMS

352

232

View full text Add to dashboard Cite

MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.

show abstract

“…The mechanism(s) by which mRNA structure regulates gene expression comprise virtually any step of the gene expression process (Mortimer et al, 2014) including transcription (Frieda and Block, 2012), splicing (Warf and Berglund, 2010), stability (Ferre-D’Amare, 2011), and translation (Mauger et al, 2013, Mandal and Breaker, 2004). mRNA structure is also required for proper miRNA-mediated regulation (Meijer et al, 2013, Gu et al, 2014b), and mRNA cellular localization (Jambor et al, 2014, Martin and Ephrussi, 2009). Most significantly, it has been demonstrated that mRNA conformation governs the expression of their encoded proteins both in vitro (Wan et al, 2011, Kertesz et al, 2010) and in vivo , as indicated by genome-wide mRNA structural profiling (Ding et al, 2014).…”

Section: Mechanisms By Which Synonymous Mutations Contribute To Gene mentioning

confidence: 99%

Decoding mechanisms by which silent codon changes influence protein biogenesis and function

Bali

Bebök

2015

The International Journal of Biochemistry & Cell Biology

112

View full text Add to dashboard Cite

Scope Synonymous codon usage has been a focus of investigation since the discovery of the genetic code and its redundancy. The occurrences of synonymous codons vary between species and within genes of the same genome, known as codon usage bias. Today, bioinformatics and experimental data allow us to compose a global view of the mechanisms by which the redundancy of the genetic code contributes to the complexity of biological systems from affecting survival in prokaryotes, to fine tuning the structure and function of proteins in higher eukaryotes. Studies analyzing the consequences of synonymous codon changes in different organisms have revealed that they impact nucleic acid stability, protein levels, structure and function without altering amino acid sequence. As such, synonymous mutations inevitably contribute to the pathogenesis of complex human diseases. Yet, fundamental questions remain unresolved regarding the impact of silent mutations in human disorders. In the present review we describe developments in this area concentrating on mechanisms by which synonymous mutations may affect protein function and human health. Purpose This synopsis illustrates the significance of synonymous mutations in disease pathogenesis. We review the different steps of gene expression affected by silent mutations, and assess the benefits and possible harmful effects of codon optimization applied in the development of therapeutic biologics. Physiological and medical relevance Understanding mechanisms by which synonymous mutations contribute to complex diseases such as cancer, neurodegeneration and genetic disorders, including the limitations of codon-optimized biologics, provides insight concerning interpretation of silent variants and future molecular therapies.

show abstract

The role of RNA structure at 5′ untranslated region in microRNA-mediated gene regulation

Cited by 95 publications

References 35 publications

5′ to 3′ mRNA Decay Contributes to the Regulation of Arabidopsis Seed Germination by Dormancy

5′ to 3′ mRNA Decay Contributes to the Regulation of Arabidopsis Seed Germination by Dormancy

Tools for Sequence-Based miRNA Target Prediction: What to Choose?

Decoding mechanisms by which silent codon changes influence protein biogenesis and function

Contact Info

Product

Resources

About