BACKGROUND: Analysis of single nucleotide polymorphism (SNP) is becoming a key research in genomics fields. Many functional analyses of SNPs have been carried out for coding regions and splicing sites that can alter proteins and mRNA splicing. However, SNPs in non-coding regulatory regions can also influence important biological regulation. Presently, there are few databases for SNPs in non-coding regulatory regions. DESCRIPTION: We identified 488,452 human SNPs in the putative promoter regions that extended from the +5000 bp to -500 bp region of the transcription start sites. Some SNPs occurring in transcription factor (TF) binding sites were also predicted (47,832 SNP; 9.8%). The result is stored in a database: SNP@promoter. Users can search the SNP@Promoter database using three entries: 1) by SNP identifier (rs number from dbSNP), 2) by gene (gene name, gene symbol, refSeq ID), and 3) by disease term. The SNP@Promoter database provides extensive genetic information and graphical views of queried terms. CONCLUSION: We present the SNP@Promoter database. It was created in order to predict functional SNPs in putative promoter regions and predicted transcription factor binding sites. SNP@Promoter will help researchers to identify functional SNPs in non-coding regions.

BACKGROUND: In the study of adaptive evolution, it is important to detect the protein coding sites where natural selection is acting. In general, the ratio of the rate of non-synonymous substitutions (Ka) to the rate of synonymous substitutions (Ks) is used to estimate either negative or positive selection for an entire gene region of interest. However, since each amino acid in a region has a different function and structure, the type and strength of natural selection may be different for each amino acid. Specifically, domain sites on the protein are indicative of structurally and functionally important sites. Therefore, Window-sliding tools can be used to detect evolutionary forces acting on mutation sites. RESULTS: This paper reports the development of a web-based tool, WSPMaker (Window-sliding Selection pressure Plot Maker), for calculating selection pressures (estimated by Ka/Ks) in the sub-regions of two protein-coding DNA sequences (CDSs). The program uses a sliding window on DNA with a user-defined window length. This enables the investigation of adaptive protein evolution and shows selective constraints of the overall/specific region(s) of two orthologous gene-coding DNA sequences. The method accommodates various evolutionary models and options such as the sliding window size. WSPmaker uses domain information from Pfam HMM models to detect highly conserved residues within orthologous proteins. CONCLUSION: WSPMaker is a web tool for scanning and calculating selection pressures (estimated by Ka/Ks) in sub-regions of two protein-coding DNA sequences (CDSs).

MOTIVATION: Analysis of the functions of microorganisms and their dynamics in the environment is essential for understanding microbial ecology. For analysis of highly similar sequences of a functional gene family using microarrays, the previous long oligonucleotide probe design strategies have not been useful in generating probes. RESULTS: We developed a Hierarchical Probe Design (HPD) program that designs both sequence-specific probes and hierarchical cluster-specific probes from sequences of a conserved functional gene based on the clustering tree of the genes, specifically for analyses of functional gene diversity in environmental samples. HPD was tested on datasets for the nirS and pmoA genes. Our results showed that HPD generated more sequence-specific probes than several popular oligonucleotide design programs. With a combination of sequence-specific and cluster-specific probes, HPD generated a probe set covering all the sequences of each test set. AVAILABILITY: http://brcapp.kribb.re.kr/HPD/