N Hamasaki-Katagiri1, B C Lin1, J Simon1, R C Hunt1, T Schiller1, E Russek-Cohen2, A A Komar3, H Bar4, C Kimchi-Sarfaty1. 1. Laboratory of Hemostasis, Division of Hematology Research and Review, Center for Biologics Evaluation & Research, United States Food and Drug Administration, Silver Spring, MD, USA. 2. Division of Biostatistics, Center for Biologics Evaluation & Research, United States Food and Drug Administration, Silver Spring, MD, USA. 3. Center for Gene Regulation in Health and Disease, Department of Biological, Geological & Environmental Sciences, Cleveland State University, Cleveland, OH, USA. 4. Department of Statistics, College of Liberal Arts and Sciences, University of Connecticut, Storrs, CT, USA.
Abstract
INTRODUCTION: Mutational analysis is commonly used to support the diagnosis and management of haemophilia. This has allowed for the generation of large mutation databases which provide unparalleled insight into genotype-phenotype relationships. Haemophilia is associated with inversions, deletions, insertions, nonsense and missense mutations. Both synonymous and non-synonymous mutations influence the base pairing of messenger RNA (mRNA), which can alter mRNA structure, cellular half-life and ribosome processivity/elongation. However, the role of mRNA structure in determining the pathogenicity of point mutations in haemophilia has not been evaluated. AIM: To evaluate mRNA thermodynamic stability and associated RNA prediction software as a means to distinguish between neutral and disease-associated mutations in haemophilia. METHODS: Five mRNA structure prediction software programs were used to assess the thermodynamic stability of mRNA fragments carrying neutral vs. disease-associated and synonymous vs. non-synonymous point mutations in F8, F9 and a third X-linked gene, DMD (dystrophin). RESULTS: In F8 and DMD, disease-associated mutations tend to occur in more structurally stable mRNA regions, represented by lower MFE (minimum free energy) levels. In comparing multiple software packages for mRNA structure prediction, a 101-151 nucleotide fragment length appears to be a feasible range for structuring future studies. CONCLUSION: mRNA thermodynamic stability is one predictive characteristic, which when combined with other RNA and protein features, may offer significant insight when screening sequencing data for novel disease-associated mutations. Our results also suggest potential utility in evaluating the mRNA thermodynamic stability profile of a gene when determining the viability of interchanging codons for biological and therapeutic applications.
INTRODUCTION: Mutational analysis is commonly used to support the diagnosis and management of haemophilia. This has allowed for the generation of large mutation databases which provide unparalleled insight into genotype-phenotype relationships. Haemophilia is associated with inversions, deletions, insertions, nonsense and missense mutations. Both synonymous and non-synonymous mutations influence the base pairing of messenger RNA (mRNA), which can alter mRNA structure, cellular half-life and ribosome processivity/elongation. However, the role of mRNA structure in determining the pathogenicity of point mutations in haemophilia has not been evaluated. AIM: To evaluate mRNA thermodynamic stability and associated RNA prediction software as a means to distinguish between neutral and disease-associated mutations in haemophilia. METHODS: Five mRNA structure prediction software programs were used to assess the thermodynamic stability of mRNA fragments carrying neutral vs. disease-associated and synonymous vs. non-synonymous point mutations in F8, F9 and a third X-linked gene, DMD (dystrophin). RESULTS: In F8 and DMD, disease-associated mutations tend to occur in more structurally stable mRNA regions, represented by lower MFE (minimum free energy) levels. In comparing multiple software packages for mRNA structure prediction, a 101-151 nucleotide fragment length appears to be a feasible range for structuring future studies. CONCLUSION: mRNA thermodynamic stability is one predictive characteristic, which when combined with other RNA and protein features, may offer significant insight when screening sequencing data for novel disease-associated mutations. Our results also suggest potential utility in evaluating the mRNA thermodynamic stability profile of a gene when determining the viability of interchanging codons for biological and therapeutic applications.
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