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PubMed1994

Statistical models for genetic susceptibility in toxicological and epidemiological investigations.

Models are presented for use in assessing genetic susceptibility to cancer (or other diseases) with animal or human data. Observations are assumed to be in the form of proportions, hence a binomial sampling distribution is considered. Generalized linear models are employed to model the response as a function of the genetic component; these include logistic and complementary log forms. Susceptibility is measured via odds ratios of response, relative to a background genetic group. Significance tests and confidence intervals for these odds ratios are based on maximum likelihood estimates of the regression parameters. Additional consideration is given to the problem of gene-environment interactions and to testing whether certain genetic identifiers/categories may be collapsed into a smaller set of categories. The collapsibility hypothesis provides an example of a mechanistic context wherein nonhierarchical models for the linear predictor can sometimes make sense.

Animals↗
PubMed1985

Genetic and phenotypic statistics of lactation cell counts in different lactations of Holstein cows.

Between February 1977 and February 1982, 680,246 monthly test-day observations of somatic cell count were taken for Holstein cows having completed 79,124 lactations in 941 herds on the Quebec Dairy Herd Analysis Service. Data were transformed to natural log scale, and analyses were separate within five parity groups. Two lactational measures of cell count, geometric mean, and weighted (by test-day milk yield) mean of the log of monthly cell counts were calculated for each lactation. Maximum likelihood, iterative Minimum Norm Quadratic Unbiased Estimation, and multivariate Restricted Maximum Likelihood procedures were used for estimation of genetic and phenotypic parameters. Repeatabilities of log test-day cell counts and log of test-day cell counts corrected for milk yield were the same at each parity, .36, .41, .42, .42, and .42 in first, second, third, fourth, and fifth and later parities. Repeatabilities of lactational measures of cell count were .33 between first and second parities, .40 between second and third parities, .13 between first and third parities, and .27 between first, second, and third parities. Heritabilities of measures of lactational cell count were small from .06 to .14 in the five parities. Genetic correlations between measures of lactational cell count in different parities were close to unity, .90 to .97.

Animals↗
PubMed2001

Statistical power when testing for genetic differentiation.

A variety of statistical procedures are commonly employed when testing for genetic differentiation. In a typical situation two or more samples of individuals have been genotyped at several gene loci by molecular or biochemical means, and in a first step a statistical test for allele frequency homogeneity is performed at each locus separately, using, e.g. the contingency chi-square test, Fisher's exact test, or some modification thereof. In a second step the results from the separate tests are combined for evaluation of the joint null hypothesis that there is no allele frequency difference at any locus, corresponding to the important case where the samples would be regarded as drawn from the same statistical and, hence, biological population. Presently, there are two conceptually different strategies in use for testing the joint null hypothesis of no difference at any locus. One approach is based on the summation of chi-square statistics over loci. Another method is employed by investigators applying the Bonferroni technique (adjusting the P-value required for rejection to account for the elevated alpha errors when performing multiple tests simultaneously) to test if the heterogeneity observed at any particular locus can be regarded significant when considered separately. Under this approach the joint null hypothesis is rejected if one or more of the component single locus tests is considered significant under the Bonferroni criterion. We used computer simulations to evaluate the statistical power and realized alpha errors of these strategies when evaluating the joint hypothesis after scoring multiple loci. We find that the 'extended' Bonferroni approach generally is associated with low statistical power and should not be applied in the current setting. Further, and contrary to what might be expected, we find that 'exact' tests typically behave poorly when combined in existing procedures for joint hypothesis testing. Thus, while exact tests are generally to be preferred over approximate ones when testing each particular locus, approximate tests such as the traditional chi-square seem preferable when addressing the joint hypothesis.

Animals↗
PubMedDate not supplied

Three autism candidate genes: a synthesis of human genetic analysis with other disciplines.

Autism is a particularly complex disorder when considered from virtually any methodological framework, including the perspective of human genetics. We first present a review of the genetic analysis principles relevant for discussing autism genetics research. From this body of work we highlight results from three candidate genes, REELIN (RELN), SEROTONIN TRANSPORTER (5HTT), and ENGRAILED 2 (EN2) and discuss the relevant neuroscience, molecular genetics, and statistical results that suggest involvement of these genes in autism susceptibility. As will be shown, the statistical results from genetic analysis, when considered alone, are in apparent conflict across research groups. We use these three candidate genes to illustrate different problems in synthesizing results from non-overlapping research groups examining the same problem. However, when basic genetic principles and results from other scientific disciplines are incorporated into a unified theoretical framework, at least some of the difficulties with interpreting results can be understood and potentially overcome as more data becomes available to the field of autism research. Integrating results from several scientific frameworks provides new hypotheses and alternative data collection strategies for future work.

Autistic Disorder↗
PubMed1982

Evidence for the horizontal acquisition of murine AKR virogenes by recent horizontal infection of the germ line.

Several recent reports (8, 10, 11, 13) have established the biological and molecular genetic similarity between the endogenous AKV virus of strain AKR, and an N-ecotropic endogenous virus found in the genome of feral Japanese mice, Mus musculus molossinus. The similarities are so striking as to suggest a common origin of these viruses, which are present in some, but not all, inbred mouse strains. The virogenes of AKR mice may have been acquired by either: (a) common descent of AKR (and other AKV(+) strains) from a common ancestor of AKR and molossinus animals, or (b) horizontal germ line infection of the AKR strains by molossinus virus at 1;he strain's inception followed by fixation through inbreeding. The sexual descent model carries with it a prediction of relative consanguinity of the AKR strain and molossinus, whereas the horizontal infection model does not. We have examined the polymorphic allozyme (allelic isozyme) genotype of 51 nonvirus-related loci in 17 strains of mice including AKR, C58, BALB/c, Swiss, and molossinus. By comparing the composite allozyme genotype of different inbred and outbred mouse strains, the "genetic distance" statistic was derived. Genetic distance measures the degree of allelic substitution between populations and increases proportionately with the amount of time the populations have been reproductively isolated. The genetic distance computed between molossinus and AKR is large, nearly 5-10 times the distance between known related populations and strains (e.g., C57L vs. C57BL/6). Molossinus had a similarly large distance from AKV negative strains (Swiss, C57L) as it did from AKV- positive strains. Cellular DNA sequences that flank the integrated AKV provirus were analyzed by restriction enzyme digestion of liver DNA from molossinus, AKR, and additional inbred strains that express ecotropic murine leukemia virus. The integration flanks of three AKR provirus sequences, Akv-1, Akv-2, and a third uncharacterized sequence, were not evident in molossinus cell DNA, which contained at least six different proviral integration fragments. These data effectively exclude the interpretation of consanguinity of AKR and molossinus and support the notion of acquisition of the endogenous virus in AKR by horizontal infection of the molossinus virus.

AKR murine leukemia virus↗
PubMed2005

Introductory guide to the statistics of molecular genetics.

BACKGROUND: This introductory guide presents the main two analytical approaches used by molecular geneticists: linkage and association. METHODS: Traditional linkage and association methods are described, along with more recent advances in methodologies such as those using a variance components approach. RESULTS: New methods are being developed all the time but the core principles of linkage and association remain the same. The basis of linkage is the transmission of a marker along with a disease within families, whereas association is based on the comparison of marker frequencies in case and control groups. CONCLUSIONS: It is becoming increasingly clear that effect sizes of individual markers on diseases and traits are likely to be very small. As such, much greater power is needed, and correspondingly greater sample sizes. Although non-replication is still a problem, molecular genetic studies in some areas such as attention deficit/hyperactivity disorder (ADHD) are starting to show greater convergence. Epidemiologists and other researchers with large well-characterized samples will be well placed to use these methods. Inter-disciplinary studies can then ask far more interesting questions such as those relating to developmental, multivariate and gene-environment interaction hypotheses.

Epidemiologic Methods↗
PubMed2006

A statistical framework for genetic association studies of power curves in bird flight.

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

Journal Article↗
PubMed1977

The use of the FST statistic of Wright for estimating the effects of genetic drift, selection and migration populations, with special reference to Ireland.

The Fst of Wright has been used to examine the available blood group, serum protein and enzyme data for the world, NW Europe and the counties of Ireland. These include the ABO, secretor, Lewis, MNSs, Rh, Kell, Duffy, Lutheran, Kidd, P, Diego, haptoglobin, Gc, Lp, Ag, adenosine deaminase, adenylate kinase, acid phosphatase, 6-phosphogluconate, phosphoglucomutase and transferrin systems. The highest value was found for the Fy gene. Much lower values than those calculated for world data were found for NW Europe and Ireland with the exception of the Lpa antigen which had high values in Ireland. sigma2p was used to estimate rates of genetic drift in an Irish population and it was estimated that a migration rate of 4% would counter genetic drift in Ireland.

Blood Group Antigens↗
PubMed2005

The impact of including tRNA content on the optimality of the genetic code.

Statistical and biochemical studies have revealed nonrandom patterns in codon assignments. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, since it is known that, when an amino acid is converted to another due to error, the biochemical properties of the resulted amino acid are usually very similar to those of the original one. In this study, we have taken into consideration both relative frequencies of amino acids and relative gene copy frequencies of tRNAs in genomic sequences in order to introduce a fitness function which models the mistranslational probabilities more accurately in modern organisms. The relative gene copy frequencies of tRNAs are used as estimates of the tRNA content. We also altered the rule previously used for the calculation of the probabilities of single base mutation occurrences. Our model signifies higher optimality of the genetic code towards load minimization and suggests the presence of a coevolution of tRNA frequency and the genetic code.

Amino Acids↗