Genetic Polymorphism Data Research Articles

A Nonparametric Test Reveals Selection for Rapid Flowering in the Arabidopsis Genome

The detection of footprints of natural selection in genetic polymorphism data is fundamental to understanding the genetic basis of adaptation, and has important implications for human health. The standard approach has been to reject neutrality in favor of selection if the pattern of variation at a candidate locus was significantly different from the predictions of the standard neutral model. The problem is that the standard neutral model assumes more than just neutrality, and it is almost always possible to explain the data using an alternative neutral model with more complex demography. Today's wealth of genomic polymorphism data, however, makes it possible to dispense with models altogether by simply comparing the pattern observed at a candidate locus to the genomic pattern, and rejecting neutrality if the pattern is extreme. Here, we utilize this approach on a truly genomic scale, comparing a candidate locus to thousands of alleles throughout the Arabidopsis thaliana genome. We demonstrate that selection has acted to increase the frequency of early-flowering alleles at the vernalization requirement locus FRIGIDA. Selection seems to have occurred during the last several thousand years, possibly in response to the spread of agriculture. We introduce a novel test statistic based on haplotype sharing that embraces the problem of population structure, and so should be widely applicable.

Molecular epidemiology of clonal diploids: A quick overview and a short DIY (do it yourself) notice

In this short review we report the basic notions needed for understanding the population genetics of clonal diploids. We focus on the consequences of clonality on the distribution of genetic diversity within individuals, between individuals and between populations. We then summarise how to detect clonality in mainly sexual populations, conversely, how to detect sexuality in mainly clonal populations and also how genetic differentiation between populations is affected by clonality in diploids. This information is then used for building recipes on how to analyse and interpret genetic polymorphism data in molecular epidemiology studies of clonal diploids.

Algorithms for association study design using a generalized model of haplotype conservation.

There is considerable interest in computational methods to assist in the use of genetic polymorphism data for locating disease-related genes. Haplotypes, contiguous sets of correlated variants, may provide a means of reducing the difficulty of the data analysis problems involved. The field to date has been dominated by methods based on the "haplotype block" hypothesis, which assumes discrete population-wide boundaries between conserved genetic segments, but there is strong reason to believe that haplotype blocks do not fully capture true haplotype conservation patterns. In this paper, we address the computational challenges of using a more flexible, block-free representation of haplotype structure called the "haplotype motif" model for downstream analysis problems. We develop algorithms for htSNP selection and missing data inference using this more generalized model of sequence conservation. Application to a dataset from the literature demonstrates the practical value of these block-free methods.

Developments of geriatric autopsy database and Internet-based database of Japanese single nucleotide polymorphisms for geriatric research (JG-SNP)

To facilitate geriatric research on the roles of genetic polymorphisms of candidate genes, two databases were developed based on data obtained from autopsy examinations of elderly subjects: the geriatric autopsy database (GEAD) and the Japanese single nucleotide polymorphisms (SNP) database for geriatric research (JG-SNP) which is accessible on the Internet ( http://www.tmgh.metro.tokyo.jp/jg-snp/english/E_top.html). The data for the GEAD were derived from 1074 consecutive autopsy cases (565 male and 509 female cases) with an average age of 80 years. The GEAD was installed on a stand-alone Windows 2000 server using Oracle 8i as the database application. The GEAD contains clinical diagnoses of 26 geriatric diseases, histories of smoking and alcohol consumption, pathological findings (720 items), severity of atherosclerosis, genetic polymorphism data, etc. On the JG-SNP website, case distribution corresponding to a specified SNP or disease can be searched or downloaded. Although there are several Internet-based SNP databases such as dbSNP, no databases are available at present on the web that contain both SNP data and phenotypic data. As autopsy studies can provide large amounts of accurate medical information, including the presence of undiagnosed diseases such as latent cancers, the GEAD is a unique and excellent database for research on genetic polymorphisms.

An approach for the quantitative consideration of genetic polymorphism data in chemical risk assessment: examples with warfarin and parathion.

In recent years, a great deal of research has been conducted to identify genetic polymorphisms. One focus has been to characterize variability in metabolic enzyme systems that could impact internal doses of pharmaceuticals or environmental pollutants. Methods are needed for using this metabolic information to estimate the resulting variability in tissue doses associated with chemical exposure. We demonstrate here the use of physiologically based pharmacokinetic (PBPK) modeling in combination with Monte Carlo analysis to incorporate information on polymorphisms into the analysis of toxicokinetic variability. Warfarin and parathion were used as case studies to demonstrate this approach. Our results suggest that polymorphisms in the PON1 gene, that give rise to allelic variants of paraoxonase, which is involved in the metabolism of paraoxon (a metabolite of parathion), make only a minor contribution to the overall variability in paraoxon tissue dose, while polymorphisms in the CYP2C9 gene, which gives rise to allelic variants of the major metabolic enzyme for warfarin, account for a significant portion of the overall variability in (S)-warfarin tissue dose. These analyses were used to estimate chemical-specific adjustment factors (CSAFs) for the human variability in toxicokinetics for both parathion and warfarin. Implications of alternatives in the calculation of CSAFs are explored. Key decision points for applying the PBPK-Monte Carlo approach to evaluate toxicokinetic variability for other chemicals are also discussed.

Artificial neural network predictive model for allergic disease using single nucleotide polymorphisms data

The purpose of this study was to develop a novel diagnostic prediction method for allergic diseases from the data of single nucleotide polymorphisms (SNPs) using an artificial neural network (ANN). We applied the prediction method to four allergic diseases, such as atopic dermatitis (AD), allergic conjunctivitis (AC), allergic rhinitis (AR) and bronchial asthma (BA), and verified its predictive ability. Almost all the learning data were precisely predicted. Regarding the evaluation data, the learned ANN model could correctly predict a diagnosis with more than 78% accuracy. We also analyzed the SNP data using multiple regression analysis (MRA). Using the MRA model, less than 10% of patients with the above allergic diseases were correctly diagnosed, while this figure was more than 75% for persons without allergic diseases. From these results, it was shown that the ANN model was superior to the MRA model with respect to predictive ability of allergic diseases. Moreover, we used two different methods to convert the genetic polymorphism data into numerical data. Using both methods, diagnostic predictions were quite precise and almost the same predictive abilities were observed. This is the first study showing the application and usefulness of an ANN for the prediction of allergic diseases based on SNP data.

Genomic Divergences between Humans and Other Hominoids and the Effective Population Size of the Common Ancestor of Humans and Chimpanzees

To study the genomic divergences among hominoids and to estimate the effective population size of the common ancestor of humans and chimpanzees, we selected 53 autosomal intergenic nonrepetitive DNA segments from the human genome and sequenced them in a human, a chimpanzee, a gorilla, and an orangutan. The average sequence divergence was only 1.24% +/- 0.07% for the human-chimpanzee pair, 1.62% +/- 0.08% for the human-gorilla pair, and 1.63% +/- 0.08% for the chimpanzee-gorilla pair. These estimates, which were confirmed by additional data from GenBank, are substantially lower than previous ones, which included repetitive sequences and might have been based on less-accurate sequence data. The average sequence divergences between orangutans and humans, chimpanzees, and gorillas were 3.08% +/- 0.11%, 3.12% +/- 0.11%, and 3.09% +/- 0.11%, respectively, which also are substantially lower than previous estimates. The sequence divergences in other regions between hominoids were estimated from extensive data in GenBank and the literature, and Alus showed the highest divergence, followed in order by Y-linked noncoding regions, pseudogenes, autosomal intergenic regions, X-linked noncoding regions, synonymous sites, introns, and nonsynonymous sites. The neighbor-joining tree derived from the concatenated sequence of the 53 segments--24,234 bp in length--supports the Homo-Pan clade with a 100% bootstrap value. However, when each segment is analyzed separately, 22 of the 53 segments (approximately 42%) give a tree that is incongruent with the species tree, suggesting a large effective population size (N(e)) of the common ancestor of Homo and Pan. Indeed, a parsimony analysis of the 53 segments and 37 protein-coding genes leads to an estimate of N(e) = 52,000 to 96,000. As this estimate is 5 to 9 times larger than the long-term effective population size of humans (approximately 10,000) estimated from various genetic polymorphism data, the human lineage apparently had experienced a large reduction in effective population size after its separation from the chimpanzee lineage. Our analysis assumes a molecular clock, which is in fact supported by the sequence data used. Taking the orangutan speciation date as 12 to 16 million years ago, we obtain an estimate of 4.6 to 6.2 million years for the Homo-Pan divergence and an estimate of 6.2 to 8.4 million years for the gorilla speciation date, suggesting that the gorilla lineage branched off 1.6 to 2.2 million years earlier than did the human-chimpanzee divergence.

Genetic variation observed at three tetrameric short tandem repeat loci HumTHO1, TPOX, and CSF1PO— in five ethnic population groups of northeastern India

This paper portrays the genetic variation observed at three tetrameric short tandem repeat (STR) loci HumTHO1, TPOX, and CSF1PO in five ethnic population groups from northeastern India. The study also specifies the suitability of use of these markers for forensic testing. The populations studied included three tribal groups (Kuki, Naga and Hmar), one Mongoloid caste group (Meitei), and a religious caste group (Manipuri Muslims). The loci were highly polymorphic in the populations, and all loci met Hardy–Weinberg expectations. No evidence for association of alleles among the loci was detected. The probability of match for the three loci of the most frequent genotype in the five population groups ranged between 2.6 × 10−4 and 6.6 × 10−5. The average heterozygosity among the population groups was approximately 70% with the overall extent of gene differentiation among the five groups being high (Gst = 0.046). Genetic affinity among the populations reveal very close association between the Kuki, Hmar, Naga, and Meitei. The Manipuri Muslims, despite being found in the same region, have had no admixture with these populations and maintain a substantial distance with the other groups. The genetic polymorphism data suggest that the studied systems can be used for human identity testing to estimate the frequency of a multiple locus STR DNA profile in population groups of northeastern India. Am. J. Hum. Biol. 13:23–29, 2001. © 2001 Wiley-Liss, Inc.

Huntington disease-linked locusD4S111 exposed as the ?-l-iduronidase gene

α-l-Iduronidase (IDUA) has been intensively studied due to its causative role in mucopolysaccharidosis type I (Hurler, Scheie and Hurler/Scheie syndromes). The recent cloning of a human IDUA cDNA has resulted in a reevaluation of the chromosomal location of this gene. Previously assigned to chromosome 22, IDUA now has been localized to 4p16.3, the region of chromosome 4 associated with Huntington's disease (HD). The existence of a battery of cloned DNA, physical map information, and genetic polymorphism data for this region has allowed the rapid fine mapping of IDUA within the terminal cytogenetic band of 4p. IDUA was found to be coincident with D4S111, an anonymous locus displaying a highly informative multiallele DNA polymorphism. This map location, 1.1×106 bp from the telomere, makes IDUA the most distal cloned gene assigned to 4p. However, it falls within a segment of 4p16.3 that has been eliminated from the HD candidate region, excluding a role for IDUA in this disorder.