Biomedical subjects

George Casella

Publications and source records attributed to George Casella.

30 records · Page 2Linked to original sources

PubMed2002

A statistical model for the genetic origin of allometric scaling laws in biology.

Many biological processes, from cellular metabolism to population dynamics, are characterized by particular allometric scaling (power-law) relationships between size and rate. Although such allometric relationships may be under genetic determination, their precise genetic mechanisms have not been clearly understood due to a lack of a statistical analytical method. In this paper, we present a basic statistical framework for mapping quantitative genes (or quantitative trait loci, QTL) responsible for universal quarter-power scaling laws of organic structure and function with the entire body size. Our model framework allows the testing of whether a single QTL affects the allometric relationship of two traits or whether more than one linked QTL is segregating. Like traditional multi-trait mapping, this new model can increase the power to detect the underlying QTL and the precision of its localization on the genome. Beyond the traditional method, this model is integrated with pervasive scaling laws to take advantage of the mechanistic relationships of biological structures and processes. Simulation studies indicate that the estimation precision of the QTL position and effect can be improved when the scaling relationship of the two traits is considered. The application of our model in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship of third-year stem height with third-year stem biomass. The model proposed here has implications for genetic, evolutionary, biomedicinal and breeding research.

Animals↗

PubMed2002

An improved genetic model generates high-resolution mapping of QTL for protein quality in maize endosperm.

The genetic mapping of polymorphic markers in a cross between two inbred plant lines has proven to be a powerful method for detecting quantitative trait loci (QTL) underlying complex traits. However, existing methods of QTL mapping were developed for disomic inheritance of both marker and QTL loci in a diploid population. To map QTL influencing traits expressed in the endosperm, a triploid embryo-nourishing tissue resulting from double fertilization, existing QTL mapping models require modification to consider the trisomic inheritance of the endosperm and the generation difference between the mapping population and the endosperm. Such a model requires simultaneous use of two successive generations, which theoretically can lead to an increase in resolution for QTL mapping compared with the use of a single backcross or F(2) generation. Using a newly developed model based on these considerations, we demonstrate the improved resolution of QTL, influencing protein quality traits in maize endosperm. The increased resolution made possible with this approach makes identified QTL accessible to positional cloning.

Chromosome Mapping↗

PubMed2002

A hierarchical statistical model for estimating population properties of quantitative genes.

BACKGROUND: Earlier methods for detecting major genes responsible for a quantitative trait rely critically upon a well-structured pedigree in which the segregation pattern of genes exactly follow Mendelian inheritance laws. However, for many outcrossing species, such pedigrees are not available and genes also display population properties. RESULTS: In this paper, a hierarchical statistical model is proposed to monitor the existence of a major gene based on its segregation and transmission across two successive generations. The model is implemented with an EM algorithm to provide maximum likelihood estimates for genetic parameters of the major locus. This new method is successfully applied to identify an additive gene having a large effect on stem height growth of aspen trees. The estimates of population genetic parameters for this major gene can be generalized to the original breeding population from which the parents were sampled. A simulation study is presented to evaluate finite sample properties of the model. CONCLUSIONS: A hierarchical model was derived for detecting major genes affecting a quantitative trait based on progeny tests of outcrossing species. The new model takes into account the population genetic properties of genes and is expected to enhance the accuracy, precision and power of gene detection.

Algorithms↗

PubMed2002

A bivalent polyploid model for linkage analysis in outcrossing tetraploids.

Polyploids can be classified as either allopolyploids or autopolyploids based on their presumed origins. From a perspective of linkage analysis, however, the nature of polyploids can be better described as bivalent polyploids, in which two chromosomes pair at meiosis, multivalent polyploids, in which more than two chromosomes pair, and general polyploids, in which bivalent and multivalent formations occur simultaneously. In this paper, we develop a statistical method for linkage analysis of polymorphic markers in bivalent polyploids. This method takes into account a unique cytological pairing mechanism for the formation of diploid gametes in tetraploids-preferential bivalent pairings at meiosis during which two homologous chromosomes pair with a higher probability than two homoeologous chromosomes. The higher frequency of homologous over homoeologous pairing, defined as the preferential pairing factor, affects the segregation patterns and linkage analysis of different genes on the same chromosome. A maximum likelihood method implemented with the EM algorithm is proposed to simultaneously estimate linkage and parental linkage phases over a pair of markers from any possible marker cross type between two outbred bivalent tetraploid parents demonstrating preferential bivalent pairings. Simulation studies display that the method can be well used to estimate the recombination fraction between different marker types and the preferential pairing factor typical of bivalent tetraploids. The implications of this method for current genome projects in polyploid species are discussed.

Algorithms↗

PubMed2002

Needle core length in sextant biopsy influences prostate cancer detection rate.

OBJECTIVES: Prostate cancer detection in biopsies increases with the number of sites and total tissue sampled. Its dependence on needle core fragment length is uncertain. METHODS: We surveyed two consecutive series of sextant needle biopsies from two practices in 1998 to 2000: 251 patients from Pennsylvania (group P) and 1596 from Virginia (group V). We tabulated the gross needle core lengths per sextant site and classified the diagnoses as benign or into four nonbenign categories: high-grade prostatic intraepithelial neoplasia; atypical small acinar proliferation, suspicious; atypical small acinar proliferation, suspicious plus high-grade prostatic intraepithelial neoplasia; and cancer. Logistic regression analysis was used to correlate cancer or a nonbenign diagnosis with the total length (sum of six sites) and, after excluding the sites with more than one core, with the length per single core, and the anatomic site of origin (apex, mid-gland, base). RESULTS: The mean total tissue length sampled was 108 +/- 27 mm (range 30 to 275) in group P and 81 +/- 22 mm (range 30 to 228) in group V. Sextant sites with a single core contained a mean of 12.8 +/- 3.5 mm tissue, with a 3.6-fold variation among the middle 95%. Group V core lengths at the apex averaged 11.8 mm, shorter (P = 0.0001) than mid (13.3 mm) or base (12.7 mm). A predictive value of longer length for a nonbenign diagnosis was noted in four of six sextants (P <0.04), with trend strongest at the apex, for which detection was influenced by abnormal digital rectal examination (P = 0.02) or ultrasound (P = 0.04) findings. CONCLUSIONS: The length of single cores sampled by sextant biopsy can vary more than 3.6-fold and represents a quality assurance consideration. The effect of length on cancer or nonbenign detection was maximal at the prostatic apex where the cores were shortest.

Biopsy, Needle↗

PubMed2002

A logistic mixture model for characterizing genetic determinants causing differentiation in growth trajectories.

The logistic or S-shaped curve of growth is one of the few universal laws in biology. It is certain that there exist specific genes affecting growth curves, but, due to a lack of statistical models, it is unclear how these genes cause phenotypic differentiation in growth and developmental trajectories. In this paper we present a statistical model for detecting major genes responsible for growth trajectories. This model is incorporated with pervasive logistic growth curves under the maximum likelihood framework and, thus, is expected to improve over previous models in both parameter estimation and inference. The power of this model is demonstrated by an example using forest tree data, in which evidence of major genes affecting stem growth processes is successfully detected. The implications for this model and its extensions are discussed.

Crosses, Genetic↗

PubMed2002

Joint linkage and linkage disequilibrium mapping of quantitative trait loci in natural populations.

Linkage analysis and allelic association (also referred to as linkage disequilibrium) studies are two major approaches for mapping genes that control simple or complex traits in plants, animals, and humans. But these two approaches have limited utility when used alone, because they use only part of the information that is available for a mapping population. More recently, a new mapping strategy has been designed to integrate the advantages of linkage analysis and linkage disequilibrium analysis for genome mapping in outcrossing populations. The new strategy makes use of a random sample from a panmictic population and the open-pollinated progeny of the sample. In this article, we extend the new strategy to map quantitative trait loci (QTL), using molecular markers within the EM-implemented maximum-likelihood framework. The most significant advantage of this extension is that both linkage and linkage disequilibrium between a marker and QTL can be estimated simultaneously, thus increasing the efficiency and effectiveness of genome mapping for recalcitrant outcrossing species. Simulation studies are performed to test the statistical properties of the MLEs of genetic and genomic parameters including QTL allele frequency, QTL effects, QTL position, and the linkage disequilibrium of the QTL and a marker. The potential utility of our mapping strategy is discussed.

Algorithms↗

PubMed2002

Functional mapping of quantitative trait loci underlying the character process: a theoretical framework.

Unlike a character measured at a finite set of landmark points, function-valued traits are those that change as a function of some independent and continuous variable. These traits, also called infinite-dimensional characters, can be described as the character process and include a number of biologically, economically, or biomedically important features, such as growth trajectories, allometric scalings, and norms of reaction. Here we present a new statistical infrastructure for mapping quantitative trait loci (QTL) underlying the character process. This strategy, termed functional mapping, integrates mathematical relationships of different traits or variables within the genetic mapping framework. Logistic mapping proposed in this article can be viewed as an example of functional mapping. Logistic mapping is based on a universal biological law that for each and every living organism growth over time follows an exponential growth curve (e.g., logistic or S-shaped). A maximum-likelihood approach based on a logistic-mixture model, implemented with the EM algorithm, is developed to provide the estimates of QTL positions, QTL effects, and other model parameters responsible for growth trajectories. Logistic mapping displays a tremendous potential to increase the power of QTL detection, the precision of parameter estimation, and the resolution of QTL localization due to the small number of parameters to be estimated, the pleiotropic effect of a QTL on growth, and/or residual correlations of growth at different ages. More importantly, logistic mapping allows for testing numerous biologically important hypotheses concerning the genetic basis of quantitative variation, thus gaining an insight into the critical role of development in shaping plant and animal evolution and domestication. The power of logistic mapping is demonstrated by an example of a forest tree, in which one QTL affecting stem growth processes is detected on a linkage group using our method, whereas it cannot be detected using current methods. The advantages of functional mapping are also discussed.

Chromosome Mapping↗

PubMed2002

Statistical methods for dissecting triploid endosperm traits using molecular markers. An autogamous model.

The endosperm, a result of double fertilization in flowering plants, is a triploid tissue whose genetic composition is more complex than diploid tissue. We present a new maximum-likelihood-based statistical method for mapping quantitative trait loci (QTL) underlying endosperm traits in an autogamous plant. Genetic mapping of quantitative endosperm traits is qualitatively different from traits for other plant organs because the endosperm displays complicated trisomic inheritance and represents a younger generation than its mother plant. Our endosperm mapping method is based on two different experimental designs: (1) a one-stage design in which marker information is derived from the maternal genome and (2) a two-stage hierarchical design in which marker information is derived from both the maternal and offspring genomes (embryos). Under the one-stage design, the position and additive effect of a putative QTL can be well estimated, but the estimates of the dominant and epistatic effects are upward biased and imprecise. The two-stage hierarchical design, which extracts more genetic information from the material, typically improves the accuracy and precision of the dominant and epistatic effects for an endosperm trait. We discuss the effects on the estimation of QTL parameters of different sampling strategies under the two-stage hierarchical design. Our method will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.

Chromosome Mapping↗

PubMed2002

A unified framework for mapping quantitative trait loci in bivalent tetraploids using single-dose restriction fragments: a case study from alfalfa.

The development of statistical methodologies for quantitative trait locus (QTL) mapping in polyploids is complicated by complex polysomic inheritance. In this article, we propose a statistical method for mapping QTL in tetraploids undergoing bivalent formation at meiosis by using single-dose restriction fragments. Our method is based on a unified framework, one that uses chromosome bivalent pairing configuration and gametic recombination to discern different mechanisms of gamete formation. Our bivalent polyploid model can not only provide a simultaneous estimation of the linkage and chromosome pairing configuration-a cytological parameter of evolutionary and systematic interest-but also enhances the precision of estimating QTL effects and position by correctly characterizing gene segregation during polyploid meiosis. By using our method and a linkage map constructed in a previous study, we successfully identify several QTL affecting winter hardiness in bivalent tetraploid alfalfa. Moreover, our results reveal significant preferential chromosome pairing at meiosis in an F1 hybrid population, which indicates the importance of reassessing the traditional view of random chromosome segregation in alfalfa.

Chromosome Pairing↗

PubMed2002

Mapping epigenetic quantitative trait loci (QTL) altering a developmental trajectory.

Genetic variation in a quantitative trait that changes with age is important to both evolutionary biologists and breeders. A traditional analysis of the dynamics of genetic variation is based on the genetic variance-covariance matrix among different ages estimated from a quantitative genetic model. Such an analysis, however, cannot reveal the mechanistic basis of the genetic variation for a growth trait during ontogeny. Age-specific genetic variance at time t conditional on the causal genetic effect at time t - 1 implies the generation of episodes of new genetic variation arising during the interval t - 1 to t. In the present paper, the conditional genetic variance estimated from Zhu's (1995) conditional model was partitioned into its underlying individual quantitative trait loci (QTL) using molecular markers in an F2 progeny of poplars (Populus trichocarpa and Populus deltoides). These QTL, defined as epigenetic QTL, govern the alterations of growth trajectory in a population. Three epigenetic QTL were detected to contribute significantly to variation in growth trajectory during the period from the establishment year to the subsequent year in the field. It is suggested that the activation and expression of epigenetic QTL are influenced by the developmental status of trees and the environment in which they are grown.

Analysis of Variance↗

PubMed2002

Quantitative genetics of traits associated with hip dysplasia in a canine pedigree constructed by mating dysplastic Labrador Retrievers with unaffected Greyhounds.

OBJECTIVE: To determine the genetic influence on expression of traits associated with canine hip dysplasia. ANIMALS: 193 dogs from an experimental canine pedigree. PROCEDURE: An experimental canine pedigree was developed for linkage analysis of hip dysplasia by mating dysplastic Labrador Retrievers with nondysplastic Greyhounds. A statistical model was designed to test the effects of Labrador Retriever and Greyhound alleles on age at detection of femoral capital epiphyseal ossification, 8-month distraction index, and 8-month dorsolateral subluxation score. RESULTS: The additive effect was significant for age at detection of femoral capital epiphyseal ossification. Restricted maximum likelihood estimates (+/-SD) for this trait were 6.4+/-1.95, 10.2+/-2.0, 10.8+/-3.1, 11.4+/-2.1, and 13.6+/-4.6 days of age for Greyhounds, Greyhound backcross dogs, F1 dogs, Labrador Retriever backcross dogs, and Labrador Retrievers, respectively. The additive effect was also significant for the distraction index. Estimates for this trait were 0.21+/-0.07, 0.29+/-0.15, 0.44+/-0.12, 0.52+/-0.18, and 0.6+/-0.17 for the same groups, respectively. For the dorsolateral subluxation score, additive and dominance effects were significant. Estimates for this trait were 73.5+/-4.1, 71.3+/-6.5, 69.1+/-6.0, 50.6+/-12.9, and 48.4+/-7.7%, respectively, for the same groups. CONCLUSIONS: In this canine pedigree, traits associated with canine hip dysplasia are heritable. Phenotypic differences exist among founder dogs of each breed and their crosses. This pedigree should be useful for identification of quantitative trait loci underlying the dysplastic phenotype.

Animals↗