SNP HiTLink: a high-throughput linkage analysis system employing dense SNP data

Background  

During this recent decade, microarray-based single nucleotide polymorphism (SNP) data are becoming more widely used as markers for linkage analysis in the identification of loci for disease-associated genes. Although microarray-based SNP analyses have markedly reduced genotyping time and cost compared with microsatellite-based analyses, applying these enormous data to linkage analysis programs is a time-consuming step, thus, necessitating a high-throughput platform.     

SNPP: automating large-scale SNP genotype data management

To manage high-throughput single nucleotide polymorphism (SNP) genotyping data efficiently, we developed a dynamic general database management system-SNPP (SNP Processor). It provides several functions, including data importing with comparison, Mendelian inheritance check within pedigrees, data compiling and exporting. Furthermore, SNPP may generate files for repeat genotyping and transform them into files that can be executed by a liquid handling system. AVAILABILITY: http://orclinux.creighton.edu/snpp/ CONTACT: lanjuanzhao@creighton.edu     

SEAN: SNP prediction and display program utilizing EST sequence clusters

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.     

The PI3K inhibitor arsenal: choose your weapon!

Owing to its widespread activation in inflammation and cancer, a growing appreciation of the therapeutic potential of inhibitors of the phosphoinositide 3-kinase (PI3K) pathway has stimulated intense interest in compounds with suitable pharmacological profiles. These are primarily directed toward PI3K itself. However, as class I PI3Ks are also essential for a range of normal physiological processes, broad spectrum PI3K inhibition could be poorly tolerated. In recent years, patents describing a new generation of PI3K inhibitors have started to appear, with a particular focus on the development of compounds with enhanced isoform selectivity for use as anti-cancer and anti-inflammatory therapies. However, challenges remain for the efforts to pharmacologically target this enzyme family in a successful manner.     

SNPchip: R classes and methods for SNP array data

High-density single nucleotide polymorphism microarrays (SNP chips) provide information on a subject's genome, such as copy number and genotype (heterozygosity/homozygosity) at a SNP. While fluorescence in situ hybridization and karyotyping reveal many abnormalities, SNP chips provide a higher resolution map of the human genome that can be used to detect, e.g., aneuploidies, microdeletions, microduplications and loss of heterozygosity (LOH). As a variety of diseases are linked to such chromosomal abnormalities, SNP chips promise new insights for these diseases by aiding in the discovery of such regions, and may suggest targets for intervention. The R package SNPchip contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality. AVAILABILITY: The package is available from the Bioconductor web page at www.bioconductor.org. SUPPLEMENTARY INFORMATION: The supplementary material as described in this article (case studies, installation guidelines and R code) is available from http://biostat.jhsph.edu/~iruczins/publications/sm/     

Poised polymerases: on your mark...get set...go!

Recent global analyses have determined that many Drosophila and human genes have engaged polymerase molecules trapped immediately downstream of promoters. These results strongly implicate RNA polymerase II elongation control as a major regulator of differentiation and development.     

Bis-SNP: Combined DNA methylation and SNP calling for Bisulfite-seq data

ABSTRACT: Bisulfite treatment of DNA followed by high-throughput sequencing (Bisulfite-seq) is an important method for studying DNA methylation and epigenetic gene regulation, yet current software tools do not adequately address single nucleotide polymorphisms (SNPs). Identifying SNPs is important for accurate quantification of methylation levels and for identification of allele-specific epigenetic events such as imprinting. We have developed a model-based bisulfite SNP caller, Bis-SNP, that results in substantially better SNP calls than existing methods, thereby improving methylation estimates. At an average 30× genomic coverage, Bis-SNP correctly identified 96% of SNPs using the default high-stringency settings. The open-source package is available at http://epigenome.usc.edu/publicationdata/bissnp2011.     

Genomic prediction of breeding values using previously estimated SNP variances

Background

Genomic prediction requires estimation of variances of effects of single nucleotide polymorphisms (SNPs), which is computationally demanding, and uses these variances for prediction. We have developed models with separate estimation of SNP variances, which can be applied infrequently, and genomic prediction, which can be applied routinely.

Methods

SNP variances were estimated with Bayes Stochastic Search Variable Selection (BSSVS) and BayesC. Genome-enhanced breeding values (GEBV) were estimated with RR-BLUP (ridge regression best linear unbiased prediction), using either variances obtained from BSSVS (BLUP-SSVS) or BayesC (BLUP-C), or assuming equal variances for each SNP. Datasets used to estimate SNP variances comprised (1) all animals, (2) 50% random animals (RAN50), (3) 50% best animals (TOP50), or (4) 50% worst animals (BOT50). Traits analysed were protein yield, udder depth, somatic cell score, interval between first and last insemination, direct longevity, and longevity including information from predictors.

Results

BLUP-SSVS and BLUP-C yielded similar GEBV as the equivalent Bayesian models that simultaneously estimated SNP variances. Reliabilities of these GEBV were consistently higher than from RR-BLUP, although only significantly for direct longevity. Across scenarios that used data subsets to estimate GEBV, observed reliabilities were generally higher for TOP50 than for RAN50, and much higher than for BOT50. Reliabilities of TOP50 were higher because the training data contained more ancestors of selection candidates. Using estimated SNP variances based on random or non-random subsets of the data, while using all data to estimate GEBV, did not affect reliabilities of the BLUP models. A convergence criterion of 10⁻⁸ instead of 10⁻¹⁰ for BLUP models yielded similar GEBV, while the required number of iterations decreased by 71 to 90%. Including a separate polygenic effect consistently improved reliabilities of the GEBV, but also substantially increased the required number of iterations to reach convergence with RR-BLUP. SNP variances converged faster for BayesC than for BSSVS.

Conclusions

Combining Bayesian variable selection models to re-estimate SNP variances and BLUP models that use those SNP variances, yields GEBV that are similar to those from full Bayesian models. Moreover, these combined models yield predictions with higher reliability and less bias than the commonly used RR-BLUP model.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0052-x) contains supplementary material, which is available to authorized users.     

Submit your manuscript today!Journal of Integrative Plant Biology

<正>Published on behalf of the Institute of Botany,the Chinese Academy of Sciences and the Botanical Society of China.Journal of Integrative Plant Biology(JIPB,formerly A eta Botanica Sinica)is an international journal of plant sciences that publishes peer-reviewed papers in six categories:commentaries,invited expert reviews,letters to the editor,minireviews,new technologies,and research articles.The aim of the journal is to report novel and significant information related to any aspect of     

Submit your manuscript today!Journal of Integrative Plant Biology

正Published on behalf of the Institute of Botany,the Chinese Academy of Sciences and the Botanical Society of China.Journal of Integrative Plant Biology(JIPB,formerly Acta Botanica Sinica)is an international journal of plant sciences that publishes peer-reviewed papers in six categories:commentaries,invited expert reviews,letters to the editor,new resources,new technologies,and research articles.The aim of the journal is to report novel and significant information related to any aspect of     

Submit your manuscript today! Journal of Integrative Plant Biology

<正>Published on behalf of the Institute of Botany,the Chinese Academy of Sciences and the Botanical Society of China.Journal of Integrative Plant Biology(JIPB,formerly Acta Botanica Sinica)is an international journal of plant sciences that publishes peer-reviewed papers in five categories:commenlaries.invited expert reviews,letters to the editor,new technologies,and research articles The aim of the journal is to report novel and significant information related to any aspect of