Biomedical subjects

Elizabeth A Housworth

Publications and source records attributed to Elizabeth A Housworth.

7 recordsLinked to original sources

PubMed2006

Genetic map-based analysis of genome structure in the homosporous fern Ceratopteris richardii.

Homosporous ferns have extremely high chromosome numbers relative to flowering plants, but the species with the lowest chromosome numbers show gene expression patterns typical of diploid organisms, suggesting that they may be diploidized ancient polyploids. To investigate the role of polyploidy in fern genome evolution, and to provide permanent genetic resources for this neglected group, we constructed a high-resolution genetic linkage map of the homosporous fern model species, Ceratopteris richardii (n = 39). Linkage map construction employed 488 doubled haploid lines (DHLs) that were genotyped for 368 RFLP, 358 AFLP, and 3 isozyme markers. Forty-one linkage groups were recovered, with average spacing between markers of 3.18 cM. Most loci (approximately 76%) are duplicated and most duplicates occur on different linkage groups, indicating that as in other eukaryotic genomes, gene duplication plays a prominent role in shaping the architecture of fern genomes. Although past polyploidization is a potential mechanism for the observed abundance of gene duplicates, a wide range in the number of gene duplicates as well as the absence of large syntenic regions consisting of duplicated gene copies implies that small-scale duplications may be the primary mode of gene duplication in C. richardii. Alternatively, evidence of past polyploidization(s) may be masked by extensive chromosomal rearrangements as well as smaller-scale duplications and deletions following polyploidization(s).

Chromosome Mapping↗

PubMed2005

InterferenceAnalyzer: tools for the analysis and simulation of multi-locus genetic data.

BACKGROUND: Good statistical models for analyzing and simulating multilocus recombination data exist but are not accessible to many biologists because their use requires reasonably sophisticated mathematical and computational implementation. While some labs have direct access to statisticians or programmers competent to carry out such analyses, many labs do not. We have created a platform independent application with an easy-to-use graphical user interface that will carry out such analyses including the simulations needed to bootstrap confidence intervals for the parameters of interest. This software should make multi-locus techniques accessible to labs that previously relied on less powerful and potentially statistically confounded single interval or double interval techniques. RESULTS: We introduce InterferenceAnalyzer, an implementation with a user-friendly graphical interface incorporating previously developed algorithms for the analysis and simulation of multilocus recombination data. We demonstrate the use and features of the program with an example of multilocus tetrad data from the mustard plant, Arabidopsis thaliana, and the yeast, Saccharomyces cerevisiae. CONCLUSION: InterferenceAnalyzer provides easy access to the powerful and appropriate statistical tools for the multi-locus analysis of genetic data.

Algorithms↗

PubMed2005

Crossover interference on nucleolus organizing region-bearing chromosomes in Arabidopsis.

In most eukaryotes, crossovers are not independently distributed along the length of a chromosome. Instead, they appear to avoid close proximity to one another--a phenomenon known as crossover interference. Previously, for three of the five Arabidopsis chromosomes, we measured the strength of interference and suggested a model wherein some crossovers experience interference while others do not. Here we show, using the same model, that the fraction of interference-insensitive crossovers is significantly smaller on the remaining two chromosomes. Since these two chromosomes bear the Arabidopsis NOR domains, the possibility that these chromosomal regions influence interference is discussed.

Arabidopsis↗

PubMed2004

The phylogenetic mixed model.

The phylogenetic mixed model is an application of the quantitative-genetic mixed model to interspecific data. Although this statistical framework provides a potentially unifying approach to quantitative-genetic and phylogenetic analysis, the model has been applied infrequently because of technical difficulties with parameter estimation. We recommend a reparameterization of the model that eliminates some of these difficulties, and we develop a new estimation algorithm for both the original maximum likelihood and new restricted maximum likelihood estimators. The phylogenetic mixed model is particularly rich in terms of the evolutionary insight that might be drawn from model parameters, so we also illustrate and discuss the interpretation of the model parameters in a specific comparative analysis.

Algorithms↗

PubMed2004

Gene conversion and crossing over along the 405-kb left arm of Saccharomyces cerevisiae chromosome VII.

Gene conversions and crossing over were analyzed along 10 intervals in a 405-kb region comprising nearly all of the left arm of chromosome VII in Saccharomyces cerevisiae. Crossover interference was detected in all intervals as measured by a reduced number of nonparental ditypes. We have evaluated interference between crossovers in adjacent intervals by methods that retain the information contained in tetrads as opposed to single segregants. Interference was seen between intervals when the distance in the region adjacent to a crossover was < approximately 35 cM (90 kb). At the met13 locus, which exhibits approximately 9% gene conversions, those gene conversions accompanied by crossing over exerted interference in exchanges in an adjacent interval, whereas met13 gene conversions without an accompanying exchange did not show interference. The pattern of exchanges along this chromosome arm can be represented by a counting model in which there are three nonexchange events between adjacent exchanges; however, maximum-likelihood analysis suggests that approximately 8-12% of the crossovers on chromosome VII arise by a separate, noninterfering mechanism.

Chromosome Mapping↗

PubMed2002

Phylogeny shape and the phylogenetic comparative method.

We explored the impact of phylogeny shape on the results of interspecific statistical analyses incorporating phylogenetic information. In most phylogenetic comparative methods (PCMs), the phylogeny can be represented as a relationship matrix, and the hierarchical nature of interspecific phylogenies translates into a distinctive blocklike matrix that can be described by its eigenvectors (topology) and eigenvalues (branch lengths). Thus, differences in the eigenvectors and eigenvalues of different relationship matrices can be used to gauge the impact of possible phylogeny errors by comparing the actual phylogeny used in a PCM analysis with a second phylogenetic hypothesis that may be more accurate. For example, we can use the sum of inverse eigenvalues as a rough index to compare the impact of phylogenies with different branch lengths. Topological differences are better described by the eigenvectors. In general, phylogeny errors that involve deep splits in the phylogeny (e.g., moving a taxon across the base of the phylogeny) are likely to have much greater impact than will those involving small perturbations in the fine structure near the tips. Small perturbations, however, may have more of an impact if the phylogeny structure is highly dependent (with many recent splits near the tips of the tree). Unfortunately, the impact of any phylogeny difference on the results of a PCM depends on the details of the data being considered. Recommendations regarding the choice, design, and statistical power of interspecific analyses are also made.

Biological Evolution↗

PubMed2002

Adaptive constraints and the phylogenetic comparative method: a computer simulation test.

Recently, the utility of modern phylogenetic comparative methods (PCMs) has been questioned because of the seemingly restrictive assumptions required by these methods. Although most comparative analyses involve traits thought to be undergoing natural or sexual selection, most PCMs require an assumption that the traits be evolving by less directed random processes, such as Brownian motion (BM). In this study, we use computer simulation to generate data under more realistic evolutionary scenarios and consider the statistical abilities of a variety of PCMs to estimate correlation coefficients from these data. We found that correlations estimated without taking phylogeny into account were often quite poor and never substantially better than those produced by the other tested methods. In contrast, most PCMs performed quite well even when their assumptions were violated. Felsenstein's independent contrasts (FIC) method gave the best performance in many cases, even when weak constraints had been acting throughout phenotypic evolution. When strong constraints acted in opposition to variance-generating (i.e., BM) forces, however, FIC correlation coefficients were biased in the direction of those BM forces. In most cases, all other PCMs tested (phylogenetic generalized least squares, phylogenetic mixed model, spatial autoregression, and phylogenetic eigenvector regression) yielded good statistical performance, regardless of the details of the evolutionary model used to generate the data. Actual parameter estimates given by different PCMs for each dataset, however, were occasionally very different from one another, suggesting that the choice among them should depend on the types of traits and evolutionary processes being considered.

Adaptation, Physiological↗