Global patterns of DNA polymorphism in noncoding regions in human populations

DNA sequence variation is currently a major source of data for studying human origins, evolution, and demographic history, and for detecting linkage association of complex diseases. In this dissertation, I investigated DNA variation in worldwide populations from two ∼10 kb autosomal regions on 22q11.2 (noncoding) and 1q24 (introns). A total of 75 variant sites were found among 128 human sequences in the 22q11.2 region, yielding an estimate of 0.088% for nucleotide diversity (π), and a total of 52 variant sites were found among 122 human sequences in the 1q24 region with an estimated π value of 0.057%. The data from these two regions and a 10 kb noncoding region on Xq13.3 all show a strong excess of low-frequency variants in comparison to that expected from an equilibrium population, indicating a relatively recent population expansion. The effective population sizes estimated from the three regions were 11,000, 12,700, and 8,600, respectively, which are close to the commonly used value of 10,000. In each of the two autosomal regions, the age of the most recent common ancestor (MRCA) was estimated to be older than 1 million years among all the sequences and ∼600,000 years among non-African sequences, providing first evidence from autosomal noncoding or intronic regions for a genetic history of humans much more ancient than the emergence of modern humans. The ancient genetic history of humans indicates no severe bottleneck during the evolution of humans in the last half million years; otherwise, much of the ancient genetic history would have been lost during a severe bottleneck. This study strongly suggests that both the “out of Africa” and the multiregional models are too simple for explaining the evolution of modern humans. A compilation of genome-wide data revealed that nucleotide diversity is highest in autosomal regions, intermediate in X-linked regions, and lowest in Y-linked regions. The data suggest the existence of background selection or selective sweep on Y-linked loci. In general, the nucleotide diversity in humans is low compared to that in chimpanzee and Drosophila populations. ^

Theoretical and experimental studies of linkage disequilibrium in human populations

Linkage disequilibrium (LD) is defined as the nonrandom association of alleles at two or more loci in a population and may be a useful tool in a diverse array of applications including disease gene mapping, elucidating the demographic history of populations, and testing hypotheses of human evolution. However, the successful application of LD-based approaches to pertinent genetic questions is hampered by a lack of understanding about the forces that mediate the genome-wide distribution of LD within and between human populations. Delineating the genomic patterns of LD is a complex task that will require interdisciplinary research that transcends traditional scientific boundaries. The research presented in this dissertation is predicated upon the need for interdisciplinary studies and both theoretical and experimental projects were pursued. In the theoretical studies, I have investigated the effect of genotyping errors and SNP identification strategies on estimates of LD. The primary importance of these two chapters is that they provide important insights and guidance for the design of future empirical LD studies. Furthermore, I analyzed the allele frequency distribution of 26,530 single nucleotide polymorphisms (SNPs) in three populations and generated the first-generation natural selection map of the human genome, which will be an important resource for explaining and understanding genomic patterns of LD. Finally, in the experimental study, I describe a novel and simple, low-cost, and high-throughput SNP genotyping method. The theoretical analyses and experimental tools developed in this dissertation will facilitate a more complete understanding of patterns of LD in human populations. ^

Detecting the signature of natural selection with microsatellites

Natural selection is one of the major factors in the evolution of all organisms. Detecting the signature of natural selection has been a central theme in evolutionary genetics. With the availability of microsatellite data, it is of interest to study how natural selection can be detected with microsatellites. ^ The overall aim of this research is to detect signatures of natural selection with data on genetic variation at microsatellite loci. The null hypothesis to be tested is the neutral mutation theory of molecular evolution, which states that different alleles at a locus have equivalent effects on fitness. Currently used tests of this hypothesis based on data on genetic polymorphism in natural populations presume that mutations at the loci follow the infinite allele/site models (IAM, ISM), in the sense that at each site at most only one mutation event is recorded, and each mutation leads to an allele not seen before in the population. Microsatellite loci, which are abundant in the genome, do not obey these mutation models, since the new alleles at such loci can be created either by contraction or expansion of tandem repeat sizes of core motifs. Since the current genome map is mainly composed of microsatellite loci and this class of loci is still most commonly studied in the context of human genome diversity, this research explores how the current test procedures for testing the neutral mutation hypothesis should be modified to take into account a generalized model of forward-backward stepwise mutations. In addition, recent literature also suggested that past demographic history of populations, presence of population substructure, and varying rates of mutations across loci all have confounding effects for detecting signatures of natural selection. ^ The effects of the stepwise mutation model and other confounding factors on detecting signature of natural selection are the main results of the research. ^

Natural history study of arthrogryposis multiplex congenita, amyoplasia type

Arthrogryposis or Arthrogrypsosis Multiplex Congenita (AMC) are terms used to describe the clinical finding of multiple congenital contractures. There are more than 300 distinct disorders associated with arthrogryposis. Amyoplasia is the most common type of arthrogryposis and is often referred to as the “classic” type. There is no known cause of amyoplasia and no risk factors have been identified. Moreover, there is no established diagnostic criteria, which has led to inconsistency and confusion in the medical literature. The purpose of this study was to describe the natural history of amyoplasia, to determine if there are any identifiable risk factors and develop a list of diagnostic criteria. A retrospective chart review of 59 children with arthrogryposis ascertained at the Shriners Hospitals for Children in Houston, Texas was performed and included the following information: prenatal, birth, and family histories, and phenotypic descriptions. Forty-four children were identified with amyoplasia and 15 children with other multiple congenital contractures and other anomalies (MCC) were used as a comparison group. With the exception of abnormal amniotic fluid levels during pregnancy, there were no significant demographic or prenatal risk factors identified. However, we found common features that discriminate amyoplasia from other types of arthrogryposis and developed a diagnostic checklist. This checklist can be used as diagnostic criteria for discriminating amyoplasia from isolated and multiple contracture conditions.

Prediction of cardiovascular disease risk factors in Mexican-American children from parental risk factors, and social and demographic characteristics in the HHANES

Objectives. Cardiovascular disease (CVD) including CVD secondary to diabetes type II, a significant health problem among Mexican American populations, originates in early childhood. This study seeks to determine risk factors available to the health practitioner that can identify the child at potential risk of developing CVD, thereby enabling early intervention. ^ Design. This is a secondary analysis of cross-sectional data of matched Mexican American parents and children selected from the HHANES, 1982–1984. ^ Methods. Parents at high risk for CVD were identified based on medical history, and clinical and physical findings. Factor analysis was performed on children's skinfold thicknesses, height, weight, and systolic and diastolic blood pressures, in order to produce a limited number of uncorrelated child CVD risk factors. Multiple regression analyses were then performed to determine other CVD markers associated with these Factors, independently for mothers and fathers. ^ Results. Factor analysis of children's measurements revealed three uncorrelated latent variables summarizing the children's CVD risk: Factor1: ‘Fatness’, Factor2: ‘Size and Maturity’, and Factor3: ‘Blood Pressure’, together accounting for the bulk of variation in children's measurements (86–89%). Univariate analyses showed that children from high CVD risk families did not differ from children of low risk families in occurrence of high blood pressure, overweight, biological maturity, acculturation score, or social and economic indicators. However, multiple regression using the factor scores (from factor analysis) as dependent variables, revealed that higher CVD risk in parents, was significantly associated with increased fatness and increased blood pressure in the children. Father's CVD risk status was associated with higher levels of body fat in his children and higher levels of blood pressure in sons. Mother's CVD risk status was associated with higher blood pressure levels in children, and occurrence of obesity in the mother associated with higher fatness levels in her children. ^ Conclusion. Occurrence of cardiovascular disease and its risk factors in parents of Mexican American children, may be used to identify children at potentially higher risk for developing CV disease in the future. Obesity in mothers appears to be an important marker for the development of higher levels of body fatness in children. ^