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De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data
Published on: February 18, 2022
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Analysis of human upstream open reading frames and impact on gene expression
Yuhua Ye1, Yidan Liang, Qiuxia Yu
1Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
Human Genetics
|March 25, 2015
Summary
Upstream open reading frames (uORFs) regulate gene translation. This study identifies uORF-altering mutations in human genetic variations, linking them to altered protein expression and potential disease associations.
Area of Science:
- Molecular Biology
- Genetics
- Bioinformatics
Background:
- Upstream open reading frames (uORFs) are regulatory elements in 5' untranslated regions (5'UTRs) controlling main open reading frame (mORF) translation.
- Dysregulated uORF activity is implicated in genetic disorders.
- A systematic investigation into patient variations and uORF status was lacking.
Purpose of the Study:
- To systematically examine the impact of uORFs on human transcripts.
- To investigate the relationship between genetic variations, uORF status, and gene expression.
- To identify disease-associated mutations affecting uORF function.
Main Methods:
- Analysis of gene ontology (GO) annotations and sequence features.
- Examination of human transcript datasets.
- Screening of disease variation databases (3,740,225 variations).
- Experimental validation of identified mutations.
Main Results:
- uORF-containing genes are enriched in functions like oncogenes and transcription factors.
- uORFs influence translation initiation site (TIS) determination.
- Genes with uORFs exhibit lower protein expression levels across human tissues.
- Identified uORF-altering mutations suspected to alter gene expression levels.
- Experimental validation confirmed mutations significantly impacting protein expression with modest transcriptional changes.
Conclusions:
- uORFs play a significant role in modulating protein expression in human genes.
- uORF-altering mutations are identified in human variation data and linked to altered protein levels.
- These findings offer new insights into the role of mutations in disease pathogenesis.
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