SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping

<p>Abstract</p> <p>Background</p> <p>PCR-restriction fragment length polymorphism (RFLP) assay is a cost-effective method for SNP genotyping and mutation detection, but the manual mining for restriction enzyme sites is challenging and cumbersome. Three years after we constructed SNP-RFLPing, a freely accessible database and analysis tool for restriction enzyme mining of SNPs, significant improvements over the 2006 version have been made and incorporated into the latest version, SNP-RFLPing 2.</p> <p>Results</p> <p>The primary aim of SNP-RFLPing 2 is to provide comprehensive PCR-RFLP information with multiple functionality about SNPs, such as SNP retrieval to multiple species, different polymorphism types (bi-allelic, tri-allelic, tetra-allelic or indels), gene-centric searching, HapMap tagSNPs, gene ontology-based searching, miRNAs, and SNP500Cancer. The RFLP restriction enzymes and the corresponding PCR primers for the natural and mutagenic types of each SNP are simultaneously analyzed. All the RFLP restriction enzyme prices are also provided to aid selection. Furthermore, the previously encountered updating problems for most SNP related databases are resolved by an on-line retrieval system.</p> <p>Conclusions</p> <p>The user interfaces for functional SNP analyses have been substantially improved and integrated. SNP-RFLPing 2 offers a new and user-friendly interface for RFLP genotyping that can be used in association studies and is freely available at <url>http://bio.kuas.edu.tw/snp-rflping2</url>.</p

Bioinformatics tools for development of fast and cost effective simple sequence repeat (SSR), and single nucleotide polymorphisms (SNP) markers from expressed sequence tags (ESTs)

The development of current molecular biology techniques has led to the generation of huge amount of gene sequence information under the expressed sequence tag (EST) sequencing projects on a large number of plant species. This has opened a new era in crop molecular breeding with identification and/or development of a new class of useful DNA markers called genic molecular markers (GMMs). These markers represent the functional component of the genome in contrast to all other random DNA markers (RMMs). Many recent studies have demonstrated that GMMs may be superior to RMMs for use in the marker assisted selection, comparative mapping and exploration of functional genetic diversity in the germplasms adapted to different environment. Therefore, identification of DNA sequences which can be used as markers remains fundamental to the development of GMMs. Amongst others; bioinformatics approaches are very useful for development of molecular markers, making their development much faster and cheaper. Already, a number of computer programs have been implemented that aim at identifying molecular markers from sequence data. A revision of current bioinformatics tools for development of genic molecular markers is, therefore, crucial in this phase. This mini-review mainly provides an overview of different bioinformatics tools available and its use in marker development with particular reference to SNP and SSR markers.Keywords: Genic molecular marker, simple sequence repeat (SSR), and single nucleotide polymorphisms (SNP) markers from expressed sequence tags (ESTs).African Journal of Biotechnology Vol. 12(30), pp. 4713-472

LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs

<p>Abstract</p> <p>Background</p> <p>Linkage disequilibrium (LD) mapping is commonly used to evaluate markers for genome-wide association studies. Most types of LD software focus strictly on LD analysis and visualization, but lack supporting services for genotyping.</p> <p>Results</p> <p>We developed a freeware called LD₂SNPing, which provides a complete package of mining tools for genotyping and LD analysis environments. The software provides SNP ID- and gene-centric online retrievals for SNP information and tag SNP selection from dbSNP/NCBI and HapMap, respectively. Restriction fragment length polymorphism (RFLP) enzyme information for SNP genotype is available to all SNP IDs and tag SNPs. Single and multiple SNP inputs are possible in order to perform LD analysis by online retrieval from HapMap and NCBI. An LD statistics section provides <it>D</it>, <it>D'</it>, <it>r</it>², <it>δ</it>_<it>Q</it>, <it>ρ</it>, and the <it>P </it>values of the Hardy-Weinberg Equilibrium for each SNP marker, and Chi-square and likelihood-ratio tests for the pair-wise association of two SNPs in LD calculation. Finally, 2D and 3D plots, as well as plain-text output of the results, can be selected.</p> <p>Conclusion</p> <p>LD₂SNPing thus provides a novel visualization environment for multiple SNP input, which facilitates SNP association studies. The software, user manual, and tutorial are freely available at <url>http://bio.kuas.edu.tw/LD2NPing</url>.</p

Genetic epidemiology: Approaches to the genetic analysis of rheumatoid arthritis

The basis of susceptibility to rheumatoid arthritis (RA) is complex, comprising genetic and environmental susceptibility factors. We have reviewed the available approaches to the investigation of the genetic basis of complex diseases and how these are being applied to RA. Affected-sibling-pair methods for nonparametric linkage analysis, linkage-disequilibrium-based approaches, transmission disequilibrium testing, and disease-association studies are discussed. The pros, cons, and limitations of the approaches are considered and are illustrated by examples from the literature about rheumatoid arthritis

Genetic epidemiology: Systemic sclerosis

Systemic sclerosis (SSc) is a multisystem connective tissue disease characterised phenotypically by fibrosis and ischaemic atrophy. Its aetiology is most likely multifactorial. A genetic predisposition to the condition is suggested by reports of familial SSc (a positive family history is the strongest risk factor yet identified), by animal models, and by disease-association studies, in which researchers have examined a wide variety of genes including those involved in fibrosis, in vascular function and structure, and in autoimmunity – the relative rarity of SSc has precluded linkage studies, except in the Choctaw Indians. Recent advances in genetic methodologies should further our understanding of this complex disease process

Translation of the human genome into clinical allergy

ABSTRACTBy complete reading of the genome sequence, in the near future we will be able to determine the role of genomic DNA sequence variation among individuals, such a single nucleotide polymorphism (SNP), in the pathogenesis of diseases and responses to drugs. Comprehension of the genome will also accelerate understanding of the transcriptome, the whole transcripts present in a cell. Messages induced by a new therapy, such as an unexpected adverse effects, will not be missed by using such a comprehensive assay. Allergic diseases will be classified into subtypes depending on the impaired or affected molecule. Herein, I introduce our research strategy for genome-wide analysis of SNP related to asthma, granted by the Millennium Genome Project of the Japanese Government, and review the recent results of transcriptome analysis using microarray technology