Summary statistics of neutral mutations in longitudinal DNA samples

Longitudinal samples of DNA sequences are the DNA sequences sampled from the same population at different time points. For fast evolving organisms, e.g. RNA virus, these kind of samples have increasingly been used to study the evolutionary process in action. Longitudinal samples provide some interesting new summary statistics of genetic variation, such as the frequency of mutation of size i in one sample and size j in another, the average number of mutations accumulated since the common ancestor of two sequences each from a different sample, and number of private, shared and fixed mutations within samples. To make the results more applicable, we used in this study a general two-sample model, which assumes two longitudinal samples were taken from the same measurably evolving population. Inspired by the HIV study, we also studied a two-sample-two-stage model, which is a special case of two-sample model and assumes a treatment after the first sampling instantaneously changes the population size. We derived the formulas for calculating statistical properties, e.g. expectations, variances and covariances, of these new summary statistics under the two models. Potential applications of these results were discussed.     

The application of the entropy-based statistic for genomic association study of QTL

An entropy-based statistic TPE has been proposed for genomic association study for disease-susceptibility locus.The statistic TPE may be directly adopted and/or extended to quantitative-trait locus (QTL)mapping for quantitative traits.In this article,the statistic TPE was extended and applied to quantitative trait for association analysis of QTL by means of selective genotyping.The statistical properties (the type I error rate and the power) were examined under a range of parameters and population-sampling strategies (e.g.,various genetic models,various heritabilities,and various sample-selection threshold values) by simulation studies.The results indicated that the statistic Tee is robust and powerful for genomic association study of QTL.A simulation study based on the haplotype frequencies of 10 single nucleotide polymorphisms (SNPs) of angiotensin-I converting enzyme genes was conducted to evaluate the performance of the statistic TPE for genetic association study.     

A mixture model approach to the mapping of QTL controlling endosperm traits with bulked samples

Endosperm traits are of triploid inheritance and have become a focus of breeding effort for their close relations with the grain quality. Current methods for mapping quantitative trait loci (QTL) underlying endosperm traits are restricted to the use of the phenotypes of single grain samples as input data set, which are often not available in practice due to the small size of the cereal seeds. This paper proposed a statistical model for one specially tailored mapping strategy, where the marker genotypes are obtained from the maternal plants in the segregation population and the phenotypic responses are replaced by the trait means of composite endosperm samples pooled from each plant. It should therefore be more practical and have wide applicability in mapping endosperm traits. The method was implemented by fitting the phenotypic means of endosperms into a Gaussian mixture model. Both the exact and approximate Expectation-Maximization algorithms were proposed to estimate the model parameters. The presence of the QTL was determined by likelihood ratio test statistics. Statistical power and other properties of the new method were investigated and compared to the current single-seed method under a variety of scenarios through simulation studies. The simulations suggest a reasonable sample size should be used to ensure reliable results. The proposed method was also applied to a simulated genome data for further evaluation. As an illustration, a real data of maize was analyzed to find the loci responsible for the popping expansion volume.     

Colorimetric determination of urinary adenosine using aptamer-modified gold nanoparticles

This paper describes a colorimetric sensing approach for the determination of adenosine triphosphate (ATP) using aptamer-modified gold nanoparticles (Apt-Au NPs). In the absence of the analytes, the color of the Apt-Au NPs solution changed from wine-red to purple as a result of salt-induced aggregation. Binding of the analytes to the Apt-Au NPs induced folding of the aptamers on the Au NP surfaces into four-stranded tetraplex structures (G-quartet) and/or an increase in charge density. As a result, the Apt-Au NPs solution was wine-red in color in the presence of the analytes under high salt conditions. For mixtures of ATP (20.0–100.0 nM), Apt-Au NPs (3.0 nM), 10.0% poly(ethylene glycol), 0.2 μM TOTO-3, 150.0 mM NaCl, 15.0 mM KCl, and 16.0 mM Tris–HCl (pH 7.4), a linear correlation (R² = 0.99) existed between the ratio of the extinctions of the Apt-Au NPs at 650 and 520 nm (Ex_650/520) and the concentration of ATP. The limit of detection for ATP was 10.0 nM. The practicality of this simple, sensitive, specific, and cost-effective approach was demonstrated through the determination of the concentration of adenosine in urine samples.     

Statistical power for detecting epistasis QTL effects under the F-2 design

Epistasis refers to gene interaction effect involving two or more genes. Statistical methods for mapping quantitative trait loci (QTL) with epistasis effects have become available recently. However, little is known about the statistical power and sample size requirements for mapping epistatic QTL using genetic markers. In this study, we developed analytical formulae to calculate the statistical power and sample requirement for detecting each epistasis effect under the F-2 design based on crossing inbred lines. Assuming two unlinked interactive QTL and the same absolute value for all epistasis effects, the heritability of additive × additive (a × a) effect is twice as large as that of additive × dominance (a × d) or dominance × additive (d × a) effect, and is four times as large as that of dominance × dominance (d × d) effect. Consequently, among the four types of epistasis effects involving two loci, ''a × a'' effect is the easiest to detect whereas ''d × d'' effect is the most difficult to detect. The statistical power for detecting ''a × a'' effect is similar to that for detecting dominance effect of a single QTL. The sample size requirements for detecting ''a × d'', ''d × a'' and ''d × d'' are highly sensitive to increased distance between the markers and the interacting QTLs. Therefore, using dense marker coverage is critical to detecting those effects.     

土壤样品中DNA提取方法的比较

对土壤样品中提取DNA方法的有效性进行了比较研究。如果以细胞有效裂解和DNA产率为标准,用冻融进行预处理再结合SDS和溶菌酶的化学裂解方法,是效果最佳的DNA抽提方法,细胞裂解率为82%,DNA产率达20.8μg/g。为了去除PCR抑制物,将DNA样品进一步用柱纯化,回收率为80%。纯化后的DNA样品可用于16SrDNA扩增及其他分子操作。     

Counting Alleles with Rarefaction: Private Alleles and Hierarchical Sampling Designs

The number of alleles (allelic richness) in a population is a fundamental measure of genetic variation, and a useful statistic for identifying populations for conservation. Estimating allelic richness is complicated by the effects of sample size: large samples are expected to have more alleles. Rarefaction solves this problem. This communication extends the rarefaction procedure to count private alleles and to accommodate hierarchical sampling designs.     

陈旧皮张中DNA提取的新方法

对传统的馆藏陈旧皮张标本DNA提取方法进行了改进,所提DNA分子量可达1kb,而且具有样品用量少（约0.01g),消化时间短（约14h)和操作步骤简单等优点,利用所提DNA,对小熊猫等珍稀动物线粒体DNA的细胞色素b和控制区序列的部分片段进行了PCR扩增,序列测定和比较分析,证实所提DNA合格而无污染,完全可以用于珍稀动物保护遗传学研究。     

A Note on Testing Equality of Means when Sample Sizes are Random with Application

The problem of testing the equality of means of two normal populations is considered when independent random samples of random sizes are given with the total number of observations from both populations being a fixed number. An application in forestry is discussed.