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PubMed2006

Variations in two gene sequences of Citrus tristeza virus after host passage.

We estimated genetic variation in two groups of Citrus tristeza virus (CTV) isolates: one of them (isolates T385, T317, T318 and T305) derived from a Spanish source by successive host passages, and the other (isolates T388 and T390), obtained after aphid transmission of a Japanese source. The population structure of these isolates had been characterized by single-strand conformation polymorphism analysis of genes p18 and p20. The nucleotide sequences of representative haplotypes of each isolate and gene were used to estimate genetic diversity within and between isolates and to evaluate genetic differentiation between populations. Phylogenetic analysis of p18 and p20 sequence variants showed two main groups: one them included variants predominant in the severe isolates (T318, T305 and T388), and the other comprised variants present in both mild (T385, T317) and severe isolates. Most sequence variants of isolate T390 were not associated to these groups. In some isolates, within-isolate diversity was higher than diversity with other isolates because their population contained distantly related sequence variants, some of which were genetically close to variants predominant in the second isolate. Isolates T388 and T390 were genetically different for the two genes, as estimated by the F statistic. Furthermore, genetic differentiation between T385 and T317, T318 and T305 increased after each host passage. Our results suggest that aphid transmission and host passage may significantly alter the composition of CTV populations and thus be an important factor in their evolution.

Base Sequence↗
PubMed2003

Mitochondrial diversity evaluated by the single strand conformation polymorphism method in African and North American house flies (Musca domestica L.).

Single strand conformation polymorphisms (SSCPs) provide a convenient and inexpensive method of surveying mitochondrial genetic variation in large samples. We investigated how much variation should be incorporated into such surveys by scoring SSCP variation at eight mitochondrial loci in each of four sub-Saharan African and four North American house fly (Diptera: Muscidae.) populations. Hierarchical analysis of diversity was performed on haplotype frequencies at each locus and on haplotype frequencies formed by combining haplotypes from two, three, four, five and eight loci. Composite haplotypes at two loci were as informative about population structure as those composed of a greater number of loci. Increasing the number of loci increased diversity estimates within, but not between, populations. Mean composite haplotype diversities (16S2 and COII) were 0.49 +/- 0.09 among the African populations and 0.32 +/- 0.08 among the North American populations. Only two of 16 haplotypes were shared between continents. Nei's genetic differentiation statistic between populations in continents GPC was 0.30 +/- 0.06 and mean genetic differentiation between continents GCT was 0.39 +/- 0.06. We conclude that there has been little detectable gene flow between North America and sub-Saharan Africa.

Africa South of the Sahara↗
PubMed2001

Deciphering the genetic architecture of a multivariate phenotype.

A heritable multivariate quantitative phenotype comprises several correlated component phenotypes that are usually pleiotropically controlled by a set of major loci and environmental factors. One approach to decipher the genetic architecture of a multivariate phenotype, in particular to map the underlying loci, is to reduce the dimensionality of the data by means of a data reduction technique, such as principal component analysis. The extracted principal components are then analyzed in conjunction with marker data to map the underlying loci. We have examined the efficiency of this approach with and without taking into account the correlation structure of the multivariate phenotype when extracting principal components. We have assumed that genome-wide scan data on sibpairs are available for low-density (widely spaced) and high-density markers. Using extensive simulations, based on three models of the multivariate phenotype, we have shown that although ignoring the correlation structure of the multivariate phenotype does not have any serious impact on the efficiency of mapping the underlying trait loci in wide marker intervals, there is a significant adverse effect of this practice for fine-mapping. We, therefore, recommend that the correlation structure of the multivariate phenotype be carefully examined to decide on the strategy of extracting principal components for deciphering the genetic architecture of the multivariate phenotype.

Chromosome Mapping↗
PubMed2006

ssSNPer: identifying statistically similar SNPs to aid interpretation of genetic association studies.

UNLABELLED: ssSNPer is a novel user-friendly web interface that provides easy determination of the number and location of untested HapMap SNPs, in the region surrounding a tested HapMap SNP, which are statistically similar and would thus produce comparable and perhaps more significant association results. Identification of ssSNPs can have crucial implications for the interpretation of the initial association results and the design of follow-up studies. AVAILABILITY: http://fraser.qimr.edu.au/general/daleN/ssSNPer/

Chromosome Mapping↗
PubMed2001

Improved inference of mutation rates: II. Generalization of the Luria-Delbrück distribution for realistic cell-cycle time distributions.

In the first paper of this series (Kepler and Oprea, Theor. Popul. Biol. 2001) we found a continuum approximation of the Luria-Delbrück distribution in terms of a scaled variable related to the proportion of mutants in the culture. Here we show that the Luria-Delbrück distribution is inaccurate when realistic division processes are being considered due to the non-Markovian character of the cell cycle. We derive the expectation of the proportion of mutants in the culture for arbitrary cell-cycle time distributions. We then introduce a two-parameter generalization of the continuum Luria-Delbrück distribution for two of the more commonly used cell-cycle time distributions: gamma and shifted exponential. We obtain the generalized distribution by defining a map from the actual parameters to "effective" parameters. The effective mutation rate is obtained analytically, while the effective population size is obtained by fitting simulation data. Our simulations show that the second parameter depend mostly on the coefficient of variation of the cell-cycle time distribution.

Algorithms↗
PubMed2003

A general statistical framework for mapping quantitative trait loci in nonmodel systems: issue for characterizing linkage phases.

Because of uncertainty about linkage phases of founders, linkage mapping in nonmodel, outcrossing systems using molecular markers presents one of the major statistical challenges in genetic research. In this article, we devise a statistical method for mapping QTL affecting a complex trait by incorporating all possible QTL-marker linkage phases within a mapping framework. The advantage of this model is the simultaneous estimation of linkage phases and QTL location and effect parameters. These estimates are obtained through maximum-likelihood methods implemented with the EM algorithm. Extensive simulation studies are performed to investigate the statistical properties of our model. In a case study from a forest tree, this model has successfully identified a significant QTL affecting wood density. Also, the probability of the linkage phase between this QTL and its flanking markers is estimated. The implications of our model and its extension to more general circumstances are discussed.

Chromosome Mapping↗
PubMed1998

[Man and the diversity of his genome. An extraordinary phase in the history of population genetics].

Population genetics is almost eighty years old, but benefited only very recently from the advantages of direct DNA analysis. Nevertheless, much knowledge had already accumulated and was completely confirmed by the study of DNA markers. Major benefits of the latter came with microsatellites. It allowed to discover an error made with classical markers but even more seriously with RFLPs, because of the practically involuntary sampling of individuals almost exclusively of European origin for the detection of polymorphisms. Among other evolutionary application of microsatellites, the most attractive is their very recent use for dating population separations during the recent migration out of Africa of modern humans. They confirm the theory that this expansion was quite recent. Single nucleotide substitutions are the major material of evolution, and so far markers of this kind were rare. A new method, DHPLC, is excellent for their detection and testing. In humans it has been applied almost exclusively to the Y chromosome, and in a year it has given a completely new picture of Y chromosome genetics. Some applications of statistical methods to genetic geography of classical markers and ADN markers will show the power of the geographical approach, and therefore the need of a wide collection of population samples, as will be made possible by the HGDP (Human Genome Diversity Project).

Africa↗
PubMed2001

Genetic linkage methods for quantitative traits.

We discuss methods for detecting genetic linkage for quantitative data. The usual LOD score method uses a pseudolikelihood formulation and has optimal power provided all parameters are correctly specified, but can lead to erroneous estimates of the location for the locus influencing a trait under misspecification of parameters describing the variance of the trait. Alternative methods, in which attention focuses upon modelling covariation among relatives as a function of genetic marker, similarity lead to unbiased estimates of the location and major gene heritability of the trait influencing locus. The Haseman-Elston approach uses a regression method to perform linkage analysis and its properties have been widely studied. This method is generally less powerful than variance components procedures, but the maximum likelihood-based variance components procedures require normality of the trait to ensure robustness of the genetic linkage tests (i.e. a correct false positive rate). When samples are non-randomly selected an ascertainment correction is generally required in order to obtain unbiased parameter estimates when applying variance components methods. For quantitative traits, ascertainment corrections usually condition either on the proband exceeding a threshold, or on the trait value of the proband. We summarize simulations that show that both approaches lead to similar efficiencies for estimating genetic effects. Finally, we discuss methods for analysing diseases that include time-to-onset information. A variety of methods are available for the linkage analysis of quantitative traits. Here, we have reviewed the most commonly used methods.

Biometry↗
PubMed2006

Extension of the Haseman-Elston regression model to longitudinal data.

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well.

Algorithms↗
PubMed2004

Disentangling multidimensional femtosecond spectra of excitons by pulse shaping with coherent control.

Sequences of carefully timed and shaped optical pulses provide femtosecond snapshots of molecular structure as well as electronic and vibrational dynamical processes, in analogy with multidimensional NMR. We apply a genetic learning algorithm towards the design of pulse sequences which simplify the multidimensional signals by controlling the relative intensities of various peaks. Numerical simulations demonstrate how poorly resolved weak features may be amplified and observed by using optimized optical pulses, specifically shaped to achieve a desired spectroscopic target.

Algorithms↗
PubMed2000

g and the one-many problem: is one enough?

No one believes that g is the only construct needed to describe individual differences in intelligence. Many believe that g is a dispensable construct. Others object to what they construe as its hegemonic position in the domain of intelligence. In this paper I defend the hegemonic status of g by a brief consideration of diverse criticisms of the g construct. I argue that g is a heritable component of intelligence that accounts for approximately 50% of the covariance among diverse measures of intelligence. It derives from a core information processing ability and it influences a diverse set of social outcomes. The covariances between g and information processing ability and social outcomes are, in large measure, attributable to common genetic influences.

Creativity↗
PubMed2001

Genetic and environmental influences on the relationship among combat exposure, posttraumatic stress disorder symptoms, and alcohol use.

The role of genetic and environmental influences on the relationship between combat exposure, posttraumatic stress disorder (PTSD) symptoms, and alcohol use were examined in 4072 male-male twin pairs who served in the United States military during the Vietnam era (1965-1975). Results indicate that the relationship between combat and alcohol use and between PTSD symptom factors and alcohol use were both substantially influenced by genetic factors. Findings are most consistent with a shared vulnerability model for the etiology of the association between PTSD symptoms and alcohol use. Specific unique environmental factors were more important than genetic factors for PTSD symptoms, and both factors were equally important for alcohol use. Further support is also found for the role of the unique environment in PTSD symptoms.

Alcoholism↗
PubMed1997

The cult of culling.

It is difficult to understand why culling (reduction of litter size) has become such a widely used procedure in reproductive toxicity studies since there appear to have been no prior investigations to ascertain that it would improve the efficiency of studies with respect to detecting adverse effects. Perhaps the only provable advantage of culling is with respect to economics and convenience. Post hoc rationalizations for culling lack conviction because many of the claims made for culling are erroneous, inconsistent, vague, and contradictory. Mostly, they are based on part truths derived from minimal studies, conducted for totally different purposes. That experimental animals have to be killed sooner or later is unquestioned, but for ethical and scientific reasons, it is imperative that the maximum amount of information is obtained from them. Currently, the most common practice is to cull litters to four per sex (total eight) on Day 4 postpartum. This is totally divorced from natural values for most rat strains and involves elimination, usually without adequate examination, of between 30 and 45% of offspring. Without culling most of these would survive, unless there was a treatment effect. Intuitively, it would seem that removal of such a proportion of offspring would severely limit the possibility of detecting the postnatal equivalent of fetal malformations. Culling totally nullifies litter size as an indicator of toxicity. Indirectly, it also nullifies the value of mean pup weight as an indicator of toxicity because it greatly increases the variation in mean pup weight. This is quite contrary to the claim that culling reduces variance. Further, the increased growth of offspring in culled litters can have long-term consequences of a shorter overall and reproductive life span.

Animals↗
PubMed2006

Reconstructing human origins in the genomic era.

Analyses of recently acquired genomic sequence data are leading to important insights into the early evolution of anatomically modern humans, as well as into the more recent demographic processes that accompanied the global radiation of Homo sapiens. Some of the new results contradict early, but still influential, conclusions that were based on analyses of gene trees from mitochondrial DNA and Y-chromosome sequences. In this review, we discuss the different genetic and statistical methods that are available for studying human population history, and identify the most plausible models of human evolution that can accommodate the contrasting patterns observed at different loci throughout the genome.

Africa↗