Haplo2Ped: a tool using haplotypes as markers for linkage analysis

<p>Abstract</p> <p>Background</p> <p>Generally, SNPs are abundant in the genome; however, they display low power in linkage analysis because of their limited heterozygosity. Haplotype markers, on the other hand, which are composed of many SNPs, greatly increase heterozygosity and have superiority in linkage statistics.</p> <p>Results</p> <p>Here we developed Haplo2Ped to automatically transform SNP data into haplotype markers and then to compute the logarithm (base 10) of odds (LOD) scores of regional haplotypes that are homozygous within the disease co-segregation haploid group. The results are reported as a hypertext file and a 3D figure to help users to obtain the candidate linkage regions. The hypertext file contains parameters of the disease linked regions, candidate genes, and their links to public databases. The 3D figure clearly displays the linkage signals in each chromosome. We tested Haplo2Ped in a simulated SNP dataset and also applied it to data from a real study. It successfully and accurately located the causative genomic regions. Comparison of Haplo2Ped with other existing software for linkage analysis further indicated the high effectiveness of this software.</p> <p>Conclusions</p> <p>Haplo2Ped uses haplotype fragments as mapping markers in whole genome linkage analysis. The advantages of Haplo2Ped over other existing software include straightforward output files, increased accuracy and superior ability to deal with pedigrees showing incomplete penetrance. Haplo2Ped is freely available at: <url>http://bighapmap.big.ac.cn/software.html</url>.</p

SNP@Evolution: a hierarchical database of positive selection on the human genome

<p>Abstract</p> <p>Background</p> <p>Positive selection is a driving force that has shaped the modern human. Recent developments in high throughput technologies and corresponding statistics tools have made it possible to conduct whole genome surveys at a population scale, and a variety of measurements, such as heterozygosity (HET), <it>F</it>_<it>ST</it>, and Tajima's D, have been applied to multiple datasets to identify signals of positive selection. However, great effort has been required to combine various types of data from individual sources, and incompatibility among datasets has been a common problem. SNP@Evolution, a new database which integrates multiple datasets, will greatly assist future work in this area.</p> <p>Description</p> <p>As part of our research scanning for evolutionary signals in HapMap Phase II and Phase III datasets, we built SNP@Evolution as a multi-aspect database focused on positive selection. Among its many features, SNP@Evolution provides computed <it>F</it>_{<it>ST </it>}and HET of all HapMap SNPs, 5+ HapMap SNPs per qualified gene, and all autosome regions detected from whole genome window scanning. In an attempt to capture multiple selection signals across the genome, selection-signal enrichment strength (E_S) values of HET, <it>F</it>_<it>ST</it>, and <it>P</it>-values of iHS of most annotated genes have been calculated and integrated within one frame for users to search for outliers. Genes with significant E_Sor <it>P</it>-values (with thresholds of 0.95 and 0.05, respectively) have been highlighted in color. Low diversity chromosome regions have been detected by sliding a 100 kb window in a 10 kb step. To allow this information to be easily disseminated, a graphical user interface (GBrowser) was constructed with the Generic Model Organism Database toolkit.</p> <p>Conclusion</p> <p>Available at <url>http://bighapmap.big.ac.cn</url>, SNP@Evolution is a hierarchical database focused on positive selection of the human genome. Based on HapMap Phase II and III data, SNP@Evolution includes 3,619,226/1,389,498 SNPs with their computed HET and <it>F</it>_<it>ST</it>, as well as qualified genes of 21,859/21,099 with E_Svalues of HET and <it>F</it>_<it>ST</it>. In at least one HapMap population group, window scanning for selection signals has resulted in 1,606/10,138 large low HET regions. Among Phase II and III geographical groups, 660 and 464 regions show strong differentiation.</p

Universal primers for HBV genome DNA amplification across subtypes: a case study for designing more effective viral primers

<p>Abstract</p> <p>Background</p> <p>The highly heterogenic characteristic of viruses is the major obstacle to efficient DNA amplification. Taking advantage of the large number of virus DNA sequences in public databases to select conserved sites for primer design is an optimal way to tackle the difficulties in virus genome amplification.</p> <p>Results</p> <p>Here we use hepatitis B virus as an example to introduce a simple and efficient way for virus primer design. Based on the alignment of HBV sequences in public databases and a program BxB in Perl script, our method selected several optimal sites for HBV primer design. Polymerase chain reaction showed that compared with the success rate of the most popular primers for whole genome amplification of HBV, one set of primers for full length genome amplification and four sets of walking primers showed significant improvement. These newly designed primers are suitable for most subtypes of HBV.</p> <p>Conclusion</p> <p>Researchers can extend the method described here to design universal or subtype specific primers for various types of viruses. The BxB program based on multiple sequence alignment not only can be used as a separate tool but also can be integrated in any open source primer design software to select conserved regions for primer design.</p

CBM Injection/Falling Off Well-Test Parameters' Optimization and Study in the Middle of Qinshui Basin, China

As one effective mean of obtaining CBM parameters, injection/falling off well-test also has abnormal results. This paper studies process parameters’ optimization such as injecting pressure, injecting volume, shut-in time and reservoir closure pressure, which will insure test procedure and results’ reliability. In order to avoid ambiguity of well-test results it studies fluid and reservoir parameters’ impacts on well-test interpretation results, and determines the range of parameters’ value such as compression co-efficient, fluid viscosity and so on. The results prove that injection parameters’ design affects field test success, determines whether test data truly reflect reservoir information or not, and its values may affect the accuracy of well-test interpretation. This paper’s study will play an important role on solving injection/falling off well-test abnormal problems

Genome-wide compound heterozygote analysis highlights alleles associated with adult height in Europeans

Adult height is the most widely genetically studied common trait in humans; however, the trait variance explainable by currently known height-associated single nucleotide polymorphisms (SNPs) identified from the previous genome-wide association studies (GWAS) is yet far from complete given the high heritability of this complex trait. To exam if compound heterozygotes (CH) may explain extra height variance, we conducted a genome-wide analysis to screen for CH in association with adult height in 10,631 Dutch Europeans enriched with extremely tall people, using our recently developed method implemented in the software package CollapsABEL. The analysis identified six regions (3q23, 5q35.1, 6p21.31, 6p21.33, 7q21.2, and 9p24.3), where multiple pairs of SNPs as CH showed genome-wide significant association with height (P < 1.67 × 10−10). Of those, 9p24.3 represents a novel region influencing adult height, whereas the others have been highlighted in the previous GWAS on height based on analysis of individual SNPs. A replication analysis in 4080 Australians of European ancestry confirmed the significant CH-like association at 9p24.3 (P < 0.05). Together, the collapsed genotypes at these six loci explained 2.51% of the height variance (after adjusting for sex and age), compared with 3.23% explained by the 14 top-associated SNPs at 14 loci identified by traditional GWAS in the same data set (P < 5 × 10−8). Overall, our study empirically demonstrates that CH plays an important role in adult height and may explain a proportion of its “missing heritability”. Moreover, our findings raise promising expectations for other highly polygenic complex traits to explain missing heritability identifiable through CH-like associations