Projects:
Phenotypes in Heterozygous Carriers of Autosomal Recessive Disease
Ataxia Telangiectasia (AT) is an autosomal recessive trait that results from mutations in the Ataxia Telangiectasia Mutated (ATM) gene on human chromosome 11q21-22. AT is characterized by cerebellar ataxia, telangiectatic lesions, immune deficiency and predisposition to malignancies. At the cellular level, AT is characterized by chromosomal instability, hypersensitivity to ionizing radiation and insufficient cell-cycle checkpoint activation.
Our study focuses on heterozygous carriers of the ATM mutations. Although AT is an autosomal recessive disease, studies have shown as a group AT carriers have increased risk of breast cancer. Using gene expression microarrays, we found that the expression levels of some genes differ at baseline and in response to ionizing radiation among AT carriers and non carriers (Watts et. al 2002). This suggests that there is an expression phenotype in AT carriers. This is important for carrier identification and also in studies to determine if AT carriers have an increased risk of cancer. Although AT is a rare disease, carrier frequency is not rare, it is about 1 per 100 in the population. Studying AT carriers is important in its own right, but extension of the project to carriers of other diseases is as instructive since disease carriers are much more common than patients. We are also carrying out comparative analysis of gene expression phenotype of noncarriers, AT carriers and AT patients to uncover ATM-dependent transcriptional regulatory pathways.
Response of Cells to Ionizing Radiation (IR)
Humans are exposed to radiation through the environment and in medical settings. The use of IR as treatment of cancer is increasing. About 50 percent of the treatment regimen includes the use of radiation, either alone or in conjunction with chemotherapy and/or surgery. Because individual responses to radiation vary, this complicates the use of IR as therapy and in handling accidental exposure to IR. In this project, our goal is to study cellular responses to radiation (Jen & Cheung, 2003; Jen & Cheung, 2005) and determine the genetic basis of variation in radiosensitivity (Correa & Cheung, 2004).
Genetics of Human Gene Expression
Most studies of genome variation have focused on the variability of DNA at the sequence level. In this study, we are measuring the extent of variation at the mRNA level and identifying the determinants of this variation. We used microarrays to measure the expression levels of genes (expression phenotypes) in lymphoblastoid cells from normal individuals. We found extensive differences in expression levels of many genes among these individuals and a genetic component to this variation (Cheung et al, 2003). To identify the genetic determinants of this variation, we are performing linkage and association analyses (Morley et al, 2004; Cheung et al, 2005). Data from these studies identified candidate cis- and trans-regulators. Most regulators act in trans. Also, many gene expression phenotypes are regulated by several genetic determinants. In addition, we found hotspots of regulation that influence the expression of many genes (Morley et al, 2004). Results from this study will allow us to characterize genome variation at the mRNA level and identify elements that regulate gene expression in human cells. By using a genetic approach, we can screen the genome for regulators without any prior knowledge of the regulatory mechanisms. This study will further our understanding of the genes and the networks involved in control of gene expression.
Genetic analysis requires genotyping of polymorphic markers, which is a labor-intensive and costly procedure. We have developed a computational method to infer genotypes. Our method combines sparse marker data from a typical linkage scan and high-resolution SNP genotypes for several individuals to infer genotypes for related individuals with high accuracy. The approach reduces the number of traditional genotyping reactions and increases the power of genome-wide association studies. This inference method can be generalized to different family structures to obtain high-density genotypes computationally for gene mapping studies.
To download our Genotype Inference Program, please click here.
To download the inferred genotypes for children in the HapMap CEPH families, please click here.
Meiotic recombination is a key mechanism for generating genetic diversity. In meiosis, crossovers result in genetic exchanges which provide daughter cells with new combinations of parental alleles. Because of its fundamental role, there is intense interest in identifying and characterizing the sites and the frequencies of crossovers during meiosis. Using genotypes of three-generation CEPH pedigrees, we have inferred the sites of meiotic recombination. We found extensive inter-individual variability in the number of meiotic crossovers in males and females. We also identified genomic regions, recombination “jungles”, with significantly more recombination events than other regions in the genome, and showed that there are polymorphic differences among individuals in activity of these recombination “jungles.” We are now extending this study to other pedigrees and to identify the genetic basis of variation in human meiotic recombination.