FPC Web tools for rice, maize, and distribution

Many clone-based physical maps have been built with the FingerPrinted Contig (FPC) software, which is written in C and runs locally for fast and flexible analysis. If the maps were viewable only from FPC, they would not be as useful to the whole community since FPC must be installed on the user machine and the database downloaded. Hence, we have created a set of Web tools so users can easily view the FPC data and perform salient queries with standard browsers. This set includes the following four programs: WebFPC, a view of the contigs; WebChrom, the location of the contigs and genetic markers along the chromosome; WebBSS, locating user-supplied sequence on the map; and WebFCmp, comparing fingerprints. For additional FPC support, we have developed an FPC module for BioPerl and an FPC browser using the Generic Model Organism Project (GMOD) genome browser (GBrowse), where the FPC BioPerl module generates the data files for input into GBrowse. This provides an alternative to the WebChrom/WebFPC view. These tools are available to download along with documentation. The tools have been implemented for both the rice (Oryza sativa) and maize (Zea mays) FPC maps, which both contain the locations of clones, markers, genetic markers, and sequenced clone (along with links to sites that contain additional information).     

Genome-wide analysis of copy number variations reveals that aging processes influence body fat distribution in Korea Associated Resource (KARE) cohorts

Many anthropometric measures, including body mass index (BMI), waist-to-hip ratio (WHR), and subcutaneous fat thickness, are used as indicators of nutritional status, fertility and predictors of future health outcomes. While BMI is currently the best available estimate of body adiposity, WHR and skinfold thickness at various sites (biceps, triceps, suprailiac, and subscapular) are used as indices of body fat distribution. Copy number variation (CNV) is an attractive emerging approach to the study of associations with various diseases. In this study, we investigated the dosage effect of genes in the CNV genome widely associated with fat distribution phenotypes in large cohorts. We used the Affymetrix genome-wide human SNP Array 5.0 data of 8,842 healthy unrelated adults in KARE cohorts and identified CNVs associated with BMI and fat distribution-related traits including WHR and subcutaneous skinfold thickness at suprailiac (SUP) and subscapular (SUB) sites. CNV segmentation of each chromosome was performed using Golden Helix SVS 7.0, and single regression analysis was used to identify CNVs associated with each phenotype. We found one CNV for BMI, 287 for WHR, 2,157 for SUP, and 2,102 for SUB at the 5?% significance level after Holm–Bonferroni correction. Genes included in the CNV were used for the analysis of functional annotations using the Database for Annotation, Visualization and Integrated Discovery (DAVID v6.7b) tool. Functional gene classification analysis identified five significant gene clusters (metallothionein, ATP-binding proteins, ribosomal proteins, kinesin family members, and zinc finger proteins) for SUP, three (keratin-associated proteins, zinc finger proteins, keratins) for SUB, and one (protamines) for WHR. BMI was excluded from this analysis because the entire structure of no gene was identified in the CNV. Based on the analysis of genes enriched in the clusters, the fat distribution traits of KARE cohorts were related to the fat redistribution associated with the aging process. In addition to structural variation, dosage effect analysis of genes based on CNV is useful to gain an understanding of the comprehensive biological phenomena underlying particular phenotypes and/or diseases.     

Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance

Background

Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data.

Results

The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones.

Conclusions

Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-437) contains supplementary material, which is available to authorized users.     

TAMAL: an integrated approach to choosing SNPs for genetic studies of human complex traits

SUMMARY: Investigators conducting studies of the molecular genetics of complex traits in humans often need rationally to select a set of single nucleotide polymorphisms (SNPs) from the hundreds or thousands available for a candidate gene. Accomplishing this requires integration of genomic data from distributed databases and is both time-consuming and error-prone. We developed the TAMAL (Technology And Money Are Limiting) web site to help identify promising SNPs for further investigation. For a given list of genes, TAMAL identifies SNPs that meet user-specified criteria (e.g. haplotype tagging SNPs or SNP predicted to lead to amino acid changes) from current versions of online resources (i.e. HapMap, Perlegen, Affymetrix, dbSNP and the UCSC genome browser). AVAILABILITY: TAMAL is a platform independent web-based application available free of charge at http://neoref.ils.unc.edu/tamal. SUPPLEMENTARY INFORMATION: http://neoref.ils.unc.edu/tamal/.     

SNP mining porcine ESTs with MAVIANT, a novel tool for SNP evaluation and annotation

MOTIVATION: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators. RESULTS: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies. AVAILABILITY: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Association between Expression Quantitative Trait Loci and Metabolic Traits in Two Korean Populations

Most genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant for those studies. However, the significance of the associations between SNPs and candidate genes has not been fully determined. An alternative approach that used SNPs in expression quantitative trait loci (eQTL) was reported previously for Crohn’s disease; it was shown that eQTL-based preselection for follow-up studies was a useful approach for identifying risk loci from the results of moderately sized GWAS. In this study, we propose an approach that uses eQTL SNPs to support the functional relationships between an SNP and a candidate gene in a genome-wide association study. The genome-wide SNP genotypes and 10 biochemical measures (fasting glucose levels, BUN, serum albumin levels, AST, ALT, gamma GTP, total cholesterol, HDL cholesterol, triglycerides, and LDL cholesterol) were obtained from the Korean Association Resource (KARE) consortium. The eQTL SNPs were isolated from the SNP dataset based on the RegulomeDB eQTL-SNP data from the ENCODE projects and two recent eQTL reports. A total of 25,658 eQTL SNPs were tested for their association with the 10 metabolic traits in 2 Korean populations (Ansung and Ansan). The proportion of phenotypic variance explained by eQTL and non-eQTL SNPs showed that eQTL SNPs were more likely to be associated with the metabolic traits genetically compared with non-eQTL SNPs. Finally, via a meta-analysis of the two Korean populations, we identified 14 eQTL SNPs that were significantly associated with metabolic traits. These results suggest that our approach can be expanded to other genome-wide association studies.     

UCSC genome browser tutorial

The University of California Santa Cruz (UCSC) Genome Bioinformatics website consists of a suite of free, open-source, on-line tools that can be used to browse, analyze, and query genomic data. These tools are available to anyone who has an Internet browser and an interest in genomics. The website provides a quick and easy-to-use visual display of genomic data. It places annotation tracks beneath genome coordinate positions, allowing rapid visual correlation of different types of information. Many of the annotation tracks are submitted by scientists worldwide; the others are computed by the UCSC Genome Bioinformatics group from publicly available sequence data. It also allows users to upload and display their own experimental results or annotation sets by creating a custom track. The suite of tools, downloadable data files, and links to documentation and other information can be found at http://genome.ucsc.edu/.     

Analysis of gene-derived SNP marker polymorphism in US wheat (Triticum aestivum L.) cultivars

In this study, we developed 359 detection primers for single nucleotide polymorphisms (SNPs) previously discovered within intron sequences of wheat genes and used them to evaluate SNP polymorphism in common wheat (Triticum aestivum L.). These SNPs showed an average polymorphism information content (PIC) of 0.18 among 20 US elite wheat cultivars, representing seven market classes. This value increased to 0.23 when SNPs were pre-selected for polymorphisms among a diverse set of 13 hexaploid wheat accessions (excluding synthetic wheats) used in the wheat SNP discovery project (). PIC values for SNP markers in the D genome were approximately half of those for the A and B genomes. D genome SNPs also showed a larger PIC reduction relative to the other genomes (P < 0.05) when US cultivars were compared with the more diverse set of 13 wheat accessions. Within those accessions, D genome SNPs show a higher proportion of alleles with low minor allele frequencies (<0.125) than found in the other two genomes. These data suggest that the reduction of PIC values in the D genome was caused by differential loss of low frequency alleles during the population size bottleneck that accompanied the development of modern commercial cultivars. Additional SNP discovery efforts targeted to the D genome in elite wheat germplasm will likely be required to offset the lower diversity of this genome. With increasing SNP discovery projects and the development of high-throughput SNP assay technologies, it is anticipated that SNP markers will play an increasingly important role in wheat genetics and breeding applications. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genotype patterns and characteristics of PRNP in the Korean population

Creutzfeldt-Jakob disease (CJD), included in the human transmissible spongiform encephalopathies (TSE), is widely known to be caused by an abnormal accumulation of misfolding prion protein in the brain. Human prion protein gene (PRNP) is mapped in chromosome 20p13 and many single nucleotide polymorphisms (SNPs) in PRNP have been discovered. However, the functionality of SNPs in PRNP is yet unclear, though several SNPs have been known as important mutation related with susceptibility human prion diseases. Our aim is to identify specific genotype patterns and characteristics in the PRNP genomic region and to understand susceptibility among Korean discriminated prion disease patients, suspected CJD patients and the KARE data group. Here, we have researched genotypes and SNPs allele frequencies in PRNP in discriminated prion disease patients group (n = 22), suspected prion diseases patients group (n = 163) and the Korea Association REsource (KARE) data group (n = 296) in Korea. The sequencing regions were promoter region, exon1 and exon2 with their junction parts among 481 samples. A total of 25 SNPs were shown in this study. Nucleotide frequencies of all SNPs are exceedingly tended to bias toward dominant homozygote types except in rs2756271. Genotype frequencies at codon 129 and 219 coding region were similar with previous studies in Korea and Japan. Pathogenic mutations such as 102P/L, 200E/K and 203V/I were observed in discriminated CJD patients group, and 180V/I and 232M/R were shown in suspected prion disease patients group and the KARE data group. A total of 10 SNPs were newly identified, six in the promoter region, one in exon 2 and three in the 3′ UTR. The strong and unique linkage disequilibrium (D' = 0.94, r² = 0.89) was observed between rs57633656 and rs1800014 which is located in codon 219 coding region. We expect that these data can be provided to determine specific susceptibility and a protective factor of prion diseases not only in Koreans but also in East Asians.     

GStream: Improving SNP and CNV Coverage on Genome-Wide Association Studies

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.     

Genome-wide polymorphism and comparative analyses in the white-tailed deer (Odocoileus virginianus): a model for conservation genomics

The white-tailed deer (Odocoileus virginianus) represents one of the most successful and widely distributed large mammal species within North America, yet very little nucleotide sequence information is available. We utilized massively parallel pyrosequencing of a reduced representation library (RRL) and a random shotgun library (RSL) to generate a complete mitochondrial genome sequence and identify a large number of putative single nucleotide polymorphisms (SNPs) distributed throughout the white-tailed deer nuclear and mitochondrial genomes. A SNP validation study designed to test specific classes of putative SNPs provides evidence for as many as 10,476 genome-wide SNPs in the current dataset. Based on cytogenetic evidence for homology between cow (Bos taurus) and white-tailed deer chromosomes, we demonstrate that a divergent genome may be used for estimating the relative distribution and density of de novo sequence contigs as well as putative SNPs for species without draft genome assemblies. Our approach demonstrates that bioinformatic tools developed for model or agriculturally important species may be leveraged to support next-generation research programs for species of biological, ecological and evolutionary importance. We also provide a functional annotation analysis for the de novo sequence contigs assembled from white-tailed deer pyrosequencing reads, a mitochondrial phylogeny involving 13,722 nucleotide positions for 10 unique species of Cervidae, and a median joining haplotype network as a putative representation of mitochondrial evolution in O. virginianus. The results of this study are expected to provide a detailed template enabling genome-wide sequence-based studies of threatened, endangered or conservationally important non-model organisms.     

Large-scale genome-wide association study of Asian population reveals genetic factors in FRMD4A and other loci influencing smoking initiation and nicotine dependence

Diseases related to smoking are the second leading cause of death in the world. Cigarette smoking is a risk factor for several diseases such as cancer and cardiovascular and respiratory disorders. Despite increasing evidence of genetic determination, the susceptibility genes and loci underlying various aspects of smoking behavior are largely unknown. Moreover, almost all reported genome-wide association studies (GWASs) have been performed on samples of European origin, limiting the applicability of the results to other ethnic populations. In this first GWAS on smoking behavior in an Asian population, after analyzing 8,842 DNA samples from the Korea Association Resource project with 352,228 single nucleotide polymorphisms (SNPs) genotyped for each sample, we identified 8 SNPs significantly associated with smoking initiation (SI) and 4 with nicotine dependence (ND). Because of the current unavailability of an independent Asian smoking sample, we replicated the discoveries in independent samples of European-American and African-American origin. Of the 12 SNPs examined in the replicated samples, we identified two SNPs, in the regulator of G-protein signaling 17 gene (rs7747583, p value(meta)?=?6.40?×?10(-6); rs2349433, p value(meta)?=?5.57?×?10(-6)), associated with SI. Also, we found two SNPs significantly associated with ND; one in the FERM domain containing 4A (rs4424567, p value(meta)?=?2.30?×?10(-6)) and the other at 7q31.1 (rs848353, p value(meta)?=?9.16?×?10(-8)). These SNPs represent novel targets for examination of smoking behavior and warrant further investigation using independent samples.     

Genotype patterns and characteristics of PRNP in the Korean population

Creutzfeldt-Jakob disease (CJD), included in the human transmissible spongiform encephalopathies (TSE), is widely known to be caused by an abnormal accumulation of misfolding prion protein in the brain. Human prion protein gene (PRNP) is mapped in chromosome 20p13 and many single nucleotide polymorphisms (SNPs) in PRNP have been discovered. However, the functionality of SNPs in PRNP is yet unclear, though several SNPs have been known as important mutation related with susceptibility human prion diseases. Our aim is to identify specific genotype patterns and characteristics in the PRNP genomic region and to understand susceptibility among Korean discriminated prion disease patients, suspected CJD patients and the KARE data group. Here, we have researched genotypes and SNPs allele frequencies in PRNP in discriminated prion disease patients group (n = 22), suspected prion diseases patients group (n = 163) and the Korea Association REsource (KARE) data group (n = 296) in Korea. The sequencing regions were promoter region, exon1 and exon2 with their junction parts among 481 samples. A total of 25 SNPs were shown in this study. Nucleotide frequencies of all SNPs are exceedingly tended to bias toward dominant homozygote types except in rs2756271. Genotype frequencies at codon 129 and 219 coding region were similar with previous studies in Korea and Japan. Pathogenic mutations such as 102P/L, 200E/K and 203V/I were observed in discriminated CJD patients group, and 180V/I and 232M/R were shown in suspected prion disease patients group and the KARE data group. A total of 10 SNPs were newly identified, six in the promoter region, one in exon 2 and three in the 3′ UTR. The strong and unique linkage disequilibrium (D' = 0.94, r² = 0.89) was observed between rs57633656 and rs1800014 which is located in codon 219 coding region. We expect that these data can be provided to determine specific susceptibility and a protective factor of prion diseases not only in Koreans but also in East Asians.     

Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays

MOTIVATION: A high density of single nucleotide polymorphism (SNP) coverage on the genome is desirable and often an essential requirement for population genetics studies. Region-specific or chromosome-specific linkage studies also benefit from the availability of as many high quality SNPs as possible. The availability of millions of SNPs from both Perlegen and the public domain and the development of an efficient microarray-based assay for genotyping SNPs has brought up some interesting analytical challenges. Effective methods for the selection of optimal subsets of SNPs spanning the genome and methods for accurately calling genotypes from probe hybridization patterns have enabled the development of a new microarray-based system for robustly genotyping over 100,000 SNPs per sample. RESULTS: We introduce a new dynamic model-based algorithm (DM) for screening over 3 million SNPs and genotyping over 100,000 SNPs. The model is based on four possible underlying states: Null, A, AB and B for each probe quartet. We calculate a probe-level log likelihood for each model and then select between the four competing models with an SNP-level statistical aggregation across multiple probe quartets to provide a high-quality genotype call along with a quality measure of the call. We assess performance with HapMap reference genotypes, informative Mendelian inheritance relationship in families, and consistency between DM and another genotype classification method. At a call rate of 95.91% the concordance with reference genotypes from the HapMap Project is 99.81% based on over 1.5 million genotypes, the Mendelian error rate is 0.018% based on 10 trios, and the consistency between DM and MPAM is 99.90% at a comparable rate of 97.18%. We also develop methods for SNP selection and optimal probe selection. AVAILABILITY: The DM algorithm is available in Affymetrix's Genotyping Tools software package and in Affymetrix's GDAS software package. See http://www.affymetrix.com for further information. 10 K and 100 K mapping array data are available on the Affymetrix website.