Journal article
An efficient computational method for screening functional SNPs in plants
Journal of Theoretical Biology, Vol.265(1), pp.55-62
2010
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Abstract
<p><p id="x-x-x-">Granule Bound Starch Synthase I (GBSSI), which influences the grain quality of cereals and, particularly, rice, is one of the most important plant genes. Using GBSSI as a model plant gene in this study, we examined a number of different computational algorithm tools and programs to explore the functional SNPs of this important rice gene and the possible relationships between genetic mutation and phenotypic variation. A total of 51 SNPs/indels were retrieved from databases, including three important coding non-synonymous SNPs, namely those in exons 6, 9 and 10. Sorting Intolerant from Tolerant (SIFT) results showed that a candidate [C/A] SNP (ID: OryzaSNP2) in exon 6 (coordinate 2494) is the most important non-synonymous SNP with the highest phenotypic impact on waxy protein. This SNP can alter a tyrosine to serine residue at position 224 of waxy protein. Computational simulation of GBSSI protein with the Geno3D suggested that this mutant SNP creates a bigger loop on the surface of waxy protein and results in a shape different from that of native GBSSI. Here, we suggest a potential transcriptional binding factor site (TBF8) which has one [C/T] SNP [rs53176842] at coordinate 2777 in boundary site of intron 7/exon 8, according to Transcriptional Factor (TF) search analysis. This SNP might potentially have a major effect on regulation and function of GBSSI. <p id="x-x-x-">Combining SNP mining data and <em>in silico</em> structural analysis of waxy protein led us to prepare an efficient computational pathway which can be applied for other plant genes.</p>
Details
- Title
- An efficient computational method for screening functional SNPs in plants
- Creators
- Ardashir Kharabian - Southern Cross University
- Publication Details
- Journal of Theoretical Biology, Vol.265(1), pp.55-62
- Identifiers
- 1178; 991012820409002368
- Academic Unit
- Southern Cross Plant Science
- Resource Type
- Journal article