A new method based on entropy theory for genomic sequence analysis

We have refined entropy theory to explore the meaning of the increasing sequence data on nucleic acids and proteins more conveniently. The concept of selection constraint was not introduced, only the analyzed sequences themselves were considered. The refined theory serves as a basis for deriving a method to analyze non-coding regions (NCRs) as well as coding regions. Positions with maximal entropy might play the most important role in genome functions as opposed to positions with minimal entropy. This method was tested in the well-characterized coding regions of 12 strains of Classical Swine Fever Virus (CSFV) and non-coding regions of 20 strains of CSFV. It is suitable to analyze nucleic acid sequences of a complete genome and to detect sensitive positions for mutagenesis. As such, the method serves to formulate the basis for elucidating the functional mechanism.     

Comparing strategies for association mapping in samples with related individuals

In this paper, different strategies to test for association in samples with related individuals designed for linkage studies are compared. Because no independent controls are available, a family-based association test and case-control tests corrected for the presence of related individuals in which unaffected relatives are used as controls were tested. When unrelated controls are available, additional strategies including selection of a single case per family considering either all families or a subset of linked families, are also considered. Analyses are performed on the simulated dataset, blind to the answers. The case-control test corrected for the presence of related individuals is the most powerful strategy to detect three loci associated with the disease under study. Using a correction factor for the case-control test performed conditional on the marker information rather than unconditional does not impact the power significantly.     

Generalized genomic distance-based regression methodology for multilocus association analysis

Large-scale, multilocus genetic association studies require powerful and appropriate statistical-analysis tools that are designed to relate genotype and haplotype information to phenotypes of interest. Many analysis approaches consider relating allelic, haplotypic, or genotypic information to a trait through use of extensions of traditional analysis techniques, such as contingency-table analysis, regression methods, and analysis-of-variance techniques. In this work, we consider a complementary approach that involves the characterization and measurement of the similarity and dissimilarity of the allelic composition of a set of individuals' diploid genomes at multiple loci in the regions of interest. We describe a regression method that can be used to relate variation in the measure of genomic dissimilarity (or "distance") among a set of individuals to variation in their trait values. Weighting factors associated with functional or evolutionary conservation information of the loci can be used in the assessment of similarity. The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates. In addition, the proposed method actually encompasses both single-locus and haplotype-phylogeny analysis methods, which are two of the most widely used approaches in genetic association analysis. We showcase the method with data described in the literature. Ultimately, our method is appropriate for high-dimensional genomic data and anticipates an era when cost-effective exhaustive DNA sequence data can be obtained for a large number of individuals, over and above genotype information focused on a few well-chosen loci.     

A comparative genomic analysis of plant hormone related genes in different species

Plant hormones are small molecules that play important roles throughout the life span of a plant,known as auxin,gibberellin,cyto-kinin,abscisic acid,ethylene,jasmonic acid,salicylic acid,and brassinosteroid.Genetic and molecular studies in the model organism Arabidopsis thaliana have revealed the individual pathways of various plant hormone responses.In this study,we selected 479 genes that were convincingly associated with various hormone actions based on genetic evidence.By using these 479 genes as querie...     

A comparative genomic analysis of plant hormone related genes in different species

Plant hormones are small molecules that play important roles throughout the life span of a plant,known as auxin,gibberellin,cytokinin,abscisic acid,ethylene,jasmonic acid,salicylic acid,and brassinosteroid.Genetic and molecular studies in the model organism Arabidopsis thaliana have revealed the individual pathways of various plant hormone responses.In this study,we selected 479 genes that were convincingly associated with various hormone actions based on genetic evidence.By using these 479 genes as queries,a genome-wide search for their orthoiogues in several species(microorganisms,plants and animals) was performed.Meanwhile,a comparative analysis was conducted to evaluate their evolutionary relationship.Our analysis revealed that the metabolisms and functions of plant hormones are generally more sophisticated and diversified in higher plant species.In particular,we found that several phytohormone receptors and key signaling components were not present in lower plants or animals.Meanwhile,as the genome complexity increases,the orthologne genes tend to have more copies and probably gain more diverse functions.Our study attempts to introduce the classification and phylogenic analysis of phytohormone related genes,from metabolism enzymes to receptors and signaling components,in different species.     

一种快速提取基因组DNA的方法

采采用氧化硅超顺磁性纳米磁珠和自己设计的试剂体系及提取流程,建立了一种基因组DNA的快速提取方法,该方法以氧化硅磁珠为固相吸附载体,盐酸胍、 -巯基乙醇和SDS为主要裂解吸附试剂。以全血或培养细胞为实验材料进行基因组DNA的提取结果显示用本文建立的方法提取100 L小鼠抗凝血,可得2～3 g基因组DNA, OD260/OD280为1.8 ± 0.05,其纯度可满足后续的酶切和PCR生物操作要求。该方法整个提取过程只需12分钟,不需特殊实验条件同时可省略蛋白酶K的消化过程和离心操作,适用于一般实验室的需求,是一种操作简便、快速高效的提取方法。     

Robust genomic control for association studies

Population-based case-control studies are a useful method to test for a genetic association between a trait and a marker. However, the analysis of the resulting data can be affected by population stratification or cryptic relatedness, which may inflate the variance of the usual statistics, resulting in a higher-than-nominal rate of false-positive results. One approach to preserving the nominal type I error is to apply genomic control, which adjusts the variance of the Cochran-Armitage trend test by calculating the statistic on data from null loci. This enables one to estimate any additional variance in the null distribution of statistics. When the underlying genetic model (e.g., recessive, additive, or dominant) is known, genomic control can be applied to the corresponding optimal trend tests. In practice, however, the mode of inheritance is unknown. The genotype-based chi (2) test for a general association between the trait and the marker does not depend on the underlying genetic model. Since this general association test has 2 degrees of freedom (df), the existing formulas for estimating the variance factor by use of genomic control are not directly applicable. By expressing the general association test in terms of two Cochran-Armitage trend tests, one can apply genomic control to each of the two trend tests separately, thereby adjusting the chi (2) statistic. The properties of this robust genomic control test with 2 df are examined by simulation. This genomic control-adjusted 2-df test has control of type I error and achieves reasonable power, relative to the optimal tests for each model.     

A robust method for testing association in genome-wide association studies

In genetic association studies, due to the varying underlying genetic models, no single statistical test can be the most powerful test under all situations. Current studies show that if the underlying genetic models are known, trend-based tests, which outperform the classical Pearson χ2 test, can be constructed. However, when the underlying genetic models are unknown, the χ2 test is usually more robust than trend-based tests. In this paper, we propose a new association test based on a generalized genetic model, namely the generalized order-restricted relative risks model. Through a Monte Carlo simulation study, we show that the proposed association test is generally more powerful than the χ2 test, and more robust than those trend-based tests. The proposed methodologies are also illustrated by some real SNP datasets.     

A system architecture for genomic data analysis

MOTIVATION: Most of diseases are caused by a set of gene defects, which occur in a complex association. The association scheme of expressed genes can be modelled by genetic networks. Genetic networks are efficiently facilities to understand the dynamic of pathogenic processes by modelling molecular reality of cell conditions. In this sense a genetic network consists of first, a set of genes of specified cells, tissues or species and second, causal relations between these genes determining the functional condition of the biological system, i. e. under disease. A relation between two genes will exist if they both are directly or indirectly associated with disease [8]. Our goal is to characterize diseases (especially autoimmune diseases like chronic pancreatitis CP, multiple sclerosis MS, rheumatoid arthritis RA) by genetic networks generated by a computer system. We want to introduce this practice as a bioinformatic approach for finding targets.     

A simple method of genomic DNA extraction suitable for analysis of bulk fungal strains

Aims: A simple and rapid method (designated thermolysis) for extracting genomic DNA from bulk fungal strains was described. Methods and Results: In the thermolysis method, a few mycelia or yeast cells were first rinsed with pure water to remove potential PCR inhibitors and then incubated in a lysis buffer at 85°C to break down cell walls and membranes. This method was used to extract genomic DNA from large numbers of fungal strains (more than 92 species, 35 genera of three phyla) isolated from different sections of natural Ophiocordyceps sinensis specimens. Regions of interest from high as well as single‐copy number genes were successfully amplified from the extracted DNA samples. The DNA samples obtained by this method can be stored at ?20°C for over 1 year. Conclusions: The method was effective, easy and fast and allowed batch DNA extraction from multiple fungal isolates. Significance and Impact of Study: Use of the thermolysis method will allow researchers to obtain DNA from fungi quickly for use in molecular assays. This method requires only minute quantities of starting material and is suitable for diverse fungal species.     

Identifying disease related sub-pathways for analysis of genome-wide association studies

Most methods for genome-wide association studies (GWAS) focus on discovering a single genetic variant, but the pathogenesis of complex diseases is thought to arise from the joint effect of multiple genetic variants. Information about pathway structure, such as the interactions and distances between gene products within pathways, can help us learn more about the functions and joint effect of genes associated with disease risk. We developed a novel sub-pathway based approach to study the joint effect of multiple genetic variants that are modestly associated with disease. The approach prioritized sub-pathways based on the significance values of single nucleotide polymorphisms (SNPs) and the interactions and distances between gene products within pathways. We applied the method to seven complex diseases. The result showed that our method can efficiently identify statistically significant sub-pathways associated with the pathogenesis of complex diseases. The approach identified sub-pathways that may inform the interpretation of GWAS data.     

A method for extraction and analysis of high quality genomic DNA from ixodid ticks

Currently, no published methods describe the extraction of high molecular weight genomic DNA from ixodid ticks (Acari: Ixodidae) and commonly used methods of extraction are not well adapted for use with members of this family. A method for extraction of minimally degraded genomic DNA from ixodid ticks that can be completed in one or two days is described. The method produces DNA which is of sufficient size (>24 kb) for use in Southern analysis and which is readily digestible by restriction endonucleases. Southern analysis using a cytochrome P450 gene probe, demonstrates the success of our method with genomic DNA extracted from two species of Ixodidae, the lone star tick, Amblyomma americanum (Linnaeus) and the cattle fever tick, Boophilus microplus (Canestrini).     

Application of random amplified polymorphic DNA PCR for genomic analysis of HIV-1-infected individuals

Random amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) is a DNA fingerprinting technique used to detect genomic polymorphisms. We employed sixteen different RAPD-PCR 10-mer primers to amplify DNA from the peripheral blood mononuclear cells (PBMC) of 80 HIV-1-infected individuals. These individuals were previously identified as either heterozygotes (+/Δ32) and homozygotes (+/+) for the CCR5 locus by PCR with gene specific primers. Four of the sixteen randomly selected RAPD primers produced distinguishable banding profiles between CCR5 (+/Δ32) heterozygotes and CCR5 (+/+) homozygotes. Direct sequencing of some RAPD-PCR products obtained with one of the four RAPD primers that were tested yielded clearly readable, but limited sequences, which were similar to portions of the previously published sequences for (+/+) homozygotes (98% similarity) and (+/Δ32) heterozygotes (87% similarity) of the CCR5 alleles. Thus, the RAPD-PCR technique may be useful for the identification of human molecular markers that may correlate with susceptibility to HIV-1-infection, or differences in disease progression among HIV-1-infected individuals.     

Case-control association testing with related individuals: a more powerful quasi-likelihood score test

We consider the problem of genomewide association testing of a binary trait when some sampled individuals are related, with known relationships. This commonly arises when families sampled for a linkage study are included in an association study. Furthermore, power to detect association with complex traits can be increased when affected individuals with affected relatives are sampled, because they are more likely to carry disease alleles than are randomly sampled affected individuals. With related individuals, correlations among relatives must be taken into account, to ensure validity of the test, and consideration of these correlations can also improve power. We provide new insight into the use of pedigree-based weights to improve power, and we propose a novel test, the MQLS test, which, as we demonstrate, represents an overall, and in many cases, substantial, improvement in power over previous tests, while retaining a computational simplicity that makes it useful in genomewide association studies in arbitrary pedigrees. Other features of the MQLS are as follows: (1) it is applicable to completely general combinations of family and case-control designs, (2) it can incorporate both unaffected controls and controls of unknown phenotype into the same analysis, and (3) it can incorporate phenotype data about relatives with missing genotype data. The methods are applied to data from the Genetic Analysis Workshop 14 Collaborative Study of the Genetics of Alcoholism, where the MQLS detects genomewide significant association (after Bonferroni correction) with an alcoholism-related phenotype for four different single-nucleotide polymorphisms: tsc1177811 (P=5.9x10(-7)), tsc1750530 (P=4.0x10(-7)), tsc0046696 (P=4.7x10(-7)), and tsc0057290 (P=5.2x10(-7)) on chromosomes 1, 16, 18, and 18, respectively. Three of these four significant associations were not detected in previous studies analyzing these data.     

A multi-sample based method for identifying common CNVs in normal human genomic structure using high-resolution aCGH data

Background

It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample.

Methodology and Principal Findings

We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR).

Conclusions and Significance

We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php.     

A genomic walking method for screening sequence length polymorphism

We adapted a recently developed nonrestrictional, nonligational genome walking method, Universal Fast Walking (UFW), for detection of length polymorphism in the proximal promoter region of genes. We demonstrate its efficacy at discovering naturally occurring transposition into heat‐shock genes of wild Drosophila and show that it surmounts limitations of simple polymerase chain reaction (PCR) approaches. We further present modifications to the standard UFW protocol and provide some guidelines to improve specificity. Although the resultant banding pattern of a standard UFW can be regarded as a DNA fingerprint, many amplicons result from false priming and not real polymorphisms. We describe ways to distinguish between UFW amplicons and false priming products in a high‐throughput assay.     

一种粗糙脉孢霉基因组DNA的快速制备方法

粗糙脉孢霉基因组ＤＮＡ的制备方法一般很费工费时。ＷｅｎｄｌａｎｄＪＡ等人发展了一种丝状真菌的ＤＮＡ提取方法 ,应用在裂褶菌取得了良好的效果[1] 。本文基于该方法制备粗糙脉孢霉基因组ＤＮＡ也取得了成功 ,应用ＰＣＲ从基因组扩增出了一个与无机焦磷酸酶有同源性的基因。1　材料与方法1 1　菌种 :粗糙脉孢霉 (Ｎｅｕｒｏｓｐｏｒａｃｒａｓｓａ)菌种 490 7ｐｒｄ - 4 ,ｂｄＡ ,来自ＦｕｎｇａｌＧｅｎｅｔｉｃｓｓｔｏｃｋｃｅｎｔｅｒ,ＵｎｉｖｅｒｓｉｔｙｏｆＫａｎｓａｓＭｅｄｉｃａｌＣｅｎｔｅｒ,Ｋａｎｓａｓ ,ＵＳＡ。1 2…     

A simple method for extraction of fungal genomic DNA

We have developed a new, simple and effective method for extraction of fungal genomic DNA. The initial steps involved suspension of freeze-dried mycelium in buffer containing sodium dodecyl sulphate, detachment of DNA from polysaccharides by mild shearing, NaCl precipitation of polysaccharides and protein, chloroform extraction and ethanol precipitation. The ethanol precipitate was then subjected to a second round of mild shearing, NaCl precipitation, chloroform extraction and ethanol precipitation. The procedure required approximately 1 h to perform. The method yielded 8-32 microg of high molecular weight DNA per 30 mg of freeze-dried mycelium when tested on six fungal species: Aspergillus niger, A. flavus, Fusarium graminarum, Neotyphodium lolii, Penicillium citrinum and Rhizopus nigricanes. The DNA was digestible with EcoRI, HindIII, SalI and BamHI. For the slow-growing N. lolii, a modification of the method was developed that removed the agar residue from colonies grown on agar plates by centrifugation at 13 000 rev min(-1) in the presence of CsCl. The modified method yielded 1.5-2 microg of high molecular weight DNA per colony.