Sickle cell disease is a monogenic blood disorder in which the clinical course and disease severity vary widely among patients. In order for physicians to make more informed decisions regarding the treatment and management of disease, it would be useful to be able to predict disease severity. We focus on two primary modulators of disease severity in sickle cell patients, hemolysis and fetal hemoglobin (HbF). This dissertation evaluates methodology to identify genetic variants associated with severity of sickle cell disease and develops new methodology of genetic risk prediction to predict disease severity in sickle cell patients based on levels of HbF. Hemolysis is a trait that is influenced by multiple correlated phenotypes (lactate dehydrogenase, reticulocytes, bilirubin and aspartate transaminase). There are several approaches to statistical analyses of multiple correlated phenotypes. The first part of this dissertation evaluates the use of principal component analysis (PCA) and compares it to the alternative approach of examining the results of multiple univariate phenotypes individually. We will focus on the question of if and under what conditions we gain more power using a summarized phenotype from PCA in a genome wide association study (GWAS) rather than conducting multiple individual GWAS. We find that the there is more power gained from the PCA approach when there is a strong intercorrelation between the phenotypes. The second part of this dissertation proposes a novel method of genetic risk prediction for continuous traits using an ensemble of genetic models. We aim to show through a simulation and prediction of HbF that the proposed method is more robust to the inclusion of false positives and yields more stable predictions than computing a GRS and 10 fold cross validation. The third part of this dissertation introduces a Bayesian-based clustering approach to produce clusters of sickle cell anemia patients based on their "predicted genetic profiles" of HbF. We then examine the genetic profiles of individuals in the extreme clusters to determine which genes contribute more prominently to the genetic profile so that we may potentially identify genes that are highly influential in the regulation of extremely high and low values of HbF.

One of the principle factors that limits the areas to which seeded bermudagrass can be adapted is low temperature. Therefore, increasing the winter tolerance of seeded bermudagrass cultivars has been a goal of turfgrass breeders for many years. Design of an efficient breeding method for developing cultivars with increased tolerance to cool and freezing temperatures could be enhanced by having heritability estimates for cold tolerance traits. Additionally, the identification of correlated traits can be useful in improvement of cultivar development. Heritability estimates for winter tolerance can be obtained from cold treatments imposed artificially or from observations made in the field. Parental clones and their respective polycross half-sib families were established in a randomized complete block design with four replications in 2004 in Lexington, KY. Differences in spring green up and fall dormancy measured in 2006 were detected between genotypes within the progeny and parental groups. These same lines were subjected to 15 replications of a freezing treatment in a freeze chamber. Differences in spring green up and fall dormancy were detected between genotypes within the progeny and parental groups. Differences in freeze response were also detected using the artificial freeze treatment. Broad-sense heritabilities were estimated to be 0.895 and 0.573 for spring green-up and fall dormancy respectively. Narrow-sense heritability estimates were found to be 0.885 and 0.265 for these same traits. These results indicate that this population could be improved for cold tolerance using phenotypic recurrent selection. Freeze response was found to be positively correlated to winter hardiness and seed yield in the parent group.

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Individuelle Verhaltensunterschiede (sog. „Animal personality“) werden oft als konsistent über die Zeit und situationsunabhängig angenommen. Vielfach werden solche Persönlichkeitsunterschiede zwischen Tieren einer Art durch individuelle Unterschiede im Energiehaushalt sowie Lebenszyklusvariablen (sog. ‚state variables‘, dt. Zustandsgrößen) erklärt. Dies ist in der „pace-of-life“ Hypothese zusammengefasst. In neueren Arbeiten wurde jedoch die Konsistenz von Persönlichkeitsmerkmalen über den Lebensverlauf und deren strikte Abhängigkeit von Zustandsgrößen in Frage gestellt. Die vorliegende Dissertation soll neue Einblicke in die Mechanismen, die zur Entstehung von Persönlichkeitsunterschieden im Verlauf des Lebens von Fischen, deren Situationsabhängigkeit sowie ihre Verbindung zu individuellen Unterschieden in Zustandsgrößen liefern. In einer Abfolge von fünf unabhängigen Studien untersuchte ich die genannten Annahmen und fand, dass (1) Persönlichkeitsunterschiede sich im Laufe des Lebens von Tieren vergrößern; (2) Persönlichkeitsabschätzungen bei jungen Tieren oft stärker vom experimentellen Aufbau beeinflusst werden als bei Erwachsenen; (3) der Energiehaushalt und Lebenszyklusvariablen Persönlichkeitsunterschiede sowohl unter Laborbedingungen als auch im Freiland nicht hinreichend erklären können; (4) Beziehungen zwischen Persönlichkeitsunterschieden und Unterschieden im Energiehaushalt und in Lebenszyklusvariablen fanden sich nur bei Fischen einer Population mit langsamer Lebenszyklusstrategie nicht jedoch in einer Population mit schnellem Lebenszyklus. Die vorliegende Arbeit suggeriert daher, dass sich erst im Verlauf des Lebens eines Tieres Persönlichkeitsunterschiede unvermeidbar entwickeln. Dies stellt Persönlichkeitsmessungen bei juvenilen Tieren grundsätzlich in Frage. Weiterhin scheinen Persönlichkeitsunterschiede und Zustandsgrößen unter bestimmten Umweltbedingungen und evolutiven Szenarien voneinander unabhängig zu sein. / Among-individual differences in behavior (i.e., animal personality) are assumed to be consistent over time and contexts. In theory, they are often explained by individual variations in energy costs of self-maintenance as well as life history among animals (i.e., state variables), commonly expressed as the pace-of-life syndrome hypothesis. Yet, recent theories have disputed the consistency of personality types over lifetime and their rigid state-dependency. This thesis aims to offer novel insights on the mechanisms behind the emergence and development of personality over lifetime of fishes, its context dependency, and its link to individual variation in state variables. In a sequence of five independent yet interconnected studies, I tested the assumptions above and observed that (1) personality differences increased during lifetime as a function of consistent declines in the behavioral plasticity with increasing age of animals; (2) personality estimates in young animals were weaker and thus more vulnerable to experimental biases compared to adults; (3) personality variation did not depend upon individual differences in energy costs of self-maintenance and life-history traits among individuals, under both laboratory and natural settings; and (4) the relationship between behavioral, metabolic, and life-history traits was manifested only in fish populations with slow rather than fast life-history strategies. This thesis suggests that personality variation in animals might be the inevitable outcome of development, raising questions about the reliability of personality estimates in juvenile individuals. Furthermore, individual variation in personality and “states” may act independently (i.e., phenotypes are uncorrelated) under environmental conditions and evolutionary contexts that mask or select against their trade-offs.