Identification of 96 single nucleotide polymorphisms in eight genes involved in iron metabolism: efficiency of bioinformatic extraction compared with a systematic sequencing approach

Abstract

Single nucleotide polymorphisms (SNPs) can significantly contribute to the characterization of the genes predisposing to iron overloads or deficiencies. We report an SNP survey of coding and non-coding regions of eight genes involved in iron metabolism, by two successive methods. First, we made use of the public domain sequence data, by using assembled expressed sequence tags, non-redundant sequences, and SNP database screening. We extracted 77 potential SNPs of which only 31 could be further validated by sequencing DNA from 44 unrelated multi-ethnic individuals. Our results indicate that a bioinformatic approach may be effective only in those cases where candidate SNPs are extracted from two different data sources or in cases of experimentally confirmed SNPs. Second, additional systematic sequencing of DNA from 24 unrelated Breton subjects increased the number of SNPs over a total length of 86 kb to 96. The average distance between the SNPs and minor allele frequencies were higher than reported by others authors; this discrepancy may reflect the nature of the genes studied and the ethnic homogeneity of our test population.Identification of 96 single nucleotide polymorphisms in eight genes involved in iron metabolism: efficiency of bioinformatic extraction compared with a systematic sequencing approach

Genome organization in coffee as revealed by EST PCRRFLP, SNPs and SSR analysis

“…In this case, the heterozygosity is due to single nucleotide polymorphism (SNP). The detection of SNPs is very important, as they can be used for a range of purposes including rapid identification of cultivars, construction of ultra, high-density genetic maps, and association studies related to gene functions (Cordeiro et al 2006;Douabin-Gicquel et al 2001). In general, SNPs are more prevalent in the non-coding regions of the genome.…”

Development and use of single nucleotide polymorphism markers for candidate resistance genes in wild peanuts (Arachis spp)

“…Candidate genes often present low levels of polymorphism, because they are often relatively conserved and because it is generally difficult to map these regions using markers based on size polymorphism. SNPs constitute the most abundant of molecular markers (Douabin-Gicquel et al, 2001). The high density and mutational stability of SNPs make them particularly useful DNA markers for population genetics and for mapping candidate genes for disease resistances and abiotic stress tolerance (Brookes, 1999).…”

“…Although candidate genes have high value, they often present low levels of polymorphism as they are relatively conserved. With this in mind, we targeted single nucleotide polymorphisms (SNPs), the most abundant of all marker types (Douabin-Gicquel et al, 2001). Although the development of SNP markers is in principle possible using a number of methods, this option tends to be labor intensive, expensive and difficult to apply efficiently to identify multiple markers.…”

Effect of SNPs on iron metabolism

“…Bioinformatics can be used to extract candidate SNPs from different data sources, but because the in silico approach has a low SNP prediction efficiency, the recommendation is to sequence selected genes systematically in an ethnically homogenous sample [7]. Frequent SNPs probably occurred a long time ago and are shared across ethnic groups whereas most rare SNPs have appeared more recently and are restricted to geographically defined populations, as is the case with the C282Y mutation.…”