How well do HapMap SNPs capture the untyped SNPs?

BACKGROUND: The recent advancement in human genome sequencing and genotyping has revealed millions of single nucleotide polymorphisms (SNP) which determine the variation among human beings. One of the particular important projects is The International HapMap Project which provides the catalogue of human genetic variation for disease association studies. In this paper, we analyzed the genotype data in HapMap project by using National Institute of Environmental Health Sciences Environmental Genome Project (NIEHS EGP) SNPs. We first determine whether the HapMap data are transferable to the NIEHS data. Then, we study how well the HapMap SNPs capture the untyped SNPs in the region. Finally, we provide general guidelines for determining whether the SNPs chosen from HapMap may be able to capture most of the untyped SNPs. RESULTS: Our analysis shows that HapMap data are not robust enough to capture the untyped variants for most of the human genes. The performance of SNPs for European and Asian samples are marginal in capturing the untyped variants, i.e. approximately 55%. Expectedly, the SNPs from HapMap YRI panel can only capture approximately 30% of the variants. Although the overall performance is low, however, the SNPs for some genes perform very well and are able to capture most of the variants along the gene. This is observed in the European and Asian panel, but not in African panel. Through observation, we concluded that in order to have a well covered SNPs reference panel, the SNPs density and the association among reference SNPs are important to estimate the robustness of the chosen SNPs. CONCLUSION: We have analyzed the coverage of HapMap SNPs using NIEHS EGP data. The results show that HapMap SNPs are transferable to the NIEHS SNPs. However, HapMap SNPs cannot capture some of the untyped SNPs and therefore resequencing may be needed to uncover more SNPs in the missing region

iHAP – integrated haplotype analysis pipeline for characterizing the haplotype structure of genes

BACKGROUND: The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations. RESULTS: To facilitate analysis of HapMap data for characterizing the haplotype structure of genes or any chromosomal regions, we have developed an integrated web-based resource, iHAP. In addition to incorporating genotype and haplotype data from the International HapMap Project and gene information from the UCSC Genome Browser Database, iHAP also provides capabilities for inferring haplotype blocks and selecting tag SNPs that are representative of haplotype patterns. These include block partitioning algorithms, block definitions, tag SNP definitions, as well as SNPs to be "force included" as tags. Based on the parameters defined at the input stage, iHAP performs on-the-fly analysis and displays the result graphically as a webpage. To facilitate analysis, intermediate and final result files can be downloaded. CONCLUSION: The iHAP resource, available at , provides a convenient yet flexible approach for the user community to analyze HapMap data and identify candidate targets for genotyping studies

Evaluating the coverage and potential of imputing the exome microarray with next-generation imputation using the 1000 genomes project

10.1371/journal.pone.0106681PLoS ONE991-

SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis

<p>Abstract</p> <p>Background</p> <p>We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis.</p> <p>Methods</p> <p>We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform.</p> <p>Results</p> <p>Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r²from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the ≥ 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays.</p> <p>Conclusion</p> <p>A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.</p

Diagnostic Accuracy of the Electrocardiogram for Heart Failure With Reduced or Preserved Ejection Fraction

Current heart failure (HF) guidelines recommend electrocardiography (ECG) as an essential initial investigation in a patient's workup. 1 However, these recommendations were based on studies primarily including patients with HF with reduced ejection fraction (HFrEF). 1 , 2 , 3 Guidelines do not distinguish HFrEF from HF with preserved and mid-range ejection fraction (HFpEF and HFmrEF) in their ECG recommendations. We hypothesized that a normal ECG does not exclude HFpEF and has a considerably lower sensitivity for diagnosing HFpEF than HFrEF

ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins

<p>Abstract</p> <p>Background</p> <p>The expansion of raw protein sequence databases in the post genomic era and availability of fresh annotated sequences for major localizations particularly motivated us to introduce a new improved version of our previously forged eukaryotic subcellular localizations prediction method namely "ESLpred". Since, subcellular localization of a protein offers essential clues about its functioning, hence, availability of localization predictor would definitely aid and expedite the protein deciphering studies. However, robustness of a predictor is highly dependent on the superiority of dataset and extracted protein attributes; hence, it becomes imperative to improve the performance of presently available method using latest dataset and crucial input features.</p> <p>Results</p> <p>Here, we describe augmentation in the prediction performance obtained for our most popular ESLpred method using new crucial features as an input to Support Vector Machine (SVM). In addition, recently available, highly non-redundant dataset encompassing three kingdoms specific protein sequence sets; 1198 fungi sequences, 2597 from animal and 491 plant sequences were also included in the present study. First, using the evolutionary information in the form of profile composition along with whole and N-terminal sequence composition as an input feature vector of 440 dimensions, overall accuracies of 72.7, 75.8 and 74.5% were achieved respectively after five-fold cross-validation. Further, enhancement in performance was observed when similarity search based results were coupled with whole and N-terminal sequence composition along with profile composition by yielding overall accuracies of 75.9, 80.8, 76.6% respectively; best accuracies reported till date on the same datasets.</p> <p>Conclusion</p> <p>These results provide confidence about the reliability and accurate prediction of SVM modules generated in the present study using sequence and profile compositions along with similarity search based results. The presently developed modules are implemented as web server "ESLpred2" available at <url>http://www.imtech.res.in/raghava/eslpred2/</url>.</p

Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset

Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get reliable summarization of gene expression intensities. Among various factors that could affect expression profiling using a microarray platform, single nucleotide polymorphisms (SNPs) in target mRNA may lead to reduced signal intensity measurements and result in spurious results. The recently released 1000 Genomes Project dataset provides an opportunity to evaluate the distribution of both known and novel SNPs in the International HapMap Project lymphoblastoid cell lines (LCLs). We mapped the 1000 Genomes Project genotypic data to the Affymetrix GeneChip Human Exon 1.0ST array (exon array), which had been used in our previous studies and for which gene expression data had been made publicly available. We also evaluated the potential impact of these SNPs on the differentially spliced probesets we had identified previously. Though the 1000 Genomes Project data allowed a comprehensive survey of the SNPs in this particular array, the same approach can certainly be applied to other microarray platforms. Furthermore, we present a detailed catalogue of SNP-containing probesets (exon-level) and transcript clusters (gene-level), which can be considered in evaluating findings using the exon array as well as benefit the design of follow-up experiments and data re-analysis

Gene-Centric Characteristics of Genome-Wide Association Studies

BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions

Genomewide association study of leprosy.

BACKGROUND: The narrow host range of Mycobacterium leprae and the fact that it is refractory to growth in culture has limited research on and the biologic understanding of leprosy. Host genetic factors are thought to influence susceptibility to infection as well as disease progression. METHODS: We performed a two-stage genomewide association study by genotyping 706 patients and 1225 controls using the Human610-Quad BeadChip (Illumina). We then tested three independent replication sets for an association between the presence of leprosy and 93 single-nucleotide polymorphisms (SNPs) that were most strongly associated with the disease in the genomewide association study. Together, these replication sets comprised 3254 patients and 5955 controls. We also carried out tests of heterogeneity of the associations (or lack thereof) between these 93 SNPs and disease, stratified according to clinical subtype (multibacillary vs. paucibacillary). RESULTS: We observed a significant association (P<1.00x10(-10)) between SNPs in the genes CCDC122, C13orf31, NOD2, TNFSF15, HLA-DR, and RIPK2 and a trend toward an association (P=5.10x10(-5)) with a SNP in LRRK2. The associations between the SNPs in C13orf31, LRRK2, NOD2, and RIPK2 and multibacillary leprosy were stronger than the associations between these SNPs and paucibacillary leprosy. CONCLUSIONS: Variants of genes in the NOD2-mediated signaling pathway (which regulates the innate immune response) are associated with susceptibility to infection with M. leprae

ANALISIS USAHA BUDIDAYA PEMBESARAN IKAN LELE (Clarias sp) DI KECAMATAN LEBAKSIU, KABUPATEN TEGAL

Ikan lele merupakan komoditas perikanan yang banyak diminati masyarakat terutama pada kalangan menengah ke bawah, selain harganya yang terjangkau ikan lele juga mudah untuk dibudidayakan. Penelitian ini dilakukan pada bulan januari 2022. Tujuan penelitian ini untuk mengetahui seberapa besar keuntungan dari usaha budidaya pembesaran ikan lele di Kecamatan Lebaksiu, Kabupaten Tegal. Metode yang digunakan dalam penelitian ini menggunakan metode deskritif kuantitatif dengan teknik survey wawancara dan kuesioner. Sampel yang digunakan sebanyak 7 responden. Hasil penelitian menunjukan sebagai berikut: keuntungan berkisar 12.683.334 - 53.133.334 rupiah per tahun, Payback Period 1,24 - 3,17 tahun, Break Event Point berkisar 2.699.999 - 9.666.665 rupiah, Net Present Value berkisar 29.471.019 - 177.574.442 rupiah dan Internal Rate of Return berkisar 25% - 70%. Kesimpulan dari hasil penelitian ini yaitu bahwa usaha budidaya pembesaran ikan lele di Kecamatan Lebaksiu, Kabupaten Tegal layak untuk dilanjutkan. Kata kunci: Analisis usaha, budidaya ikan lele, Tega