Cost and power analysis of linkage disequilibrium methods for locating genes influencing quantitative traits in humans

Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

Expression cloning of a candidate prostate cancer oncogene

Genetic analysis, both karyotyping and comparative genomic hybridization, of prostate cancer cell lines and specimens have revealed multiple areas of concordant increases in DNA content. An increase of DNA in specific regions of the genome in cancer is often associated with the amplification of oncogenes. Based on these observations we have hypothesized that oncogenes are involved in the initiation or progression of prostate cancer. An expression cloning approach was utilized to identify candidate oncogenes in prostate cancer. ^ A full-length, unidirectional cDNA expression library was constructed from DU145 prostate cancer cells. The cDNA library was screened using CP12, a rat prostate epithelial cell line. In soft agarose assays, CP12 (parental or vector transfected) do not form colonies. However, upon the introduction of a number of known oncogenes CP12 becomes anchorage independent in soft agarose. Based on this in-vitro phenotypic shift, a DU145 cDNA library was stably transfected into CP12, and selected for anchorage independence. Two hundred fifty nine anchorage independent clones were isolated. Some colonies contained more than one insert, bringing the candidate oncogene pool to approximately 400. Seven inserts were sequenced at random. Using the sequences obtained, GenBank was screened, and matches were found with p53, PARG1, a mitochondrial ATPase, RNF6, and three unknown genes that mapped to Unigene clusters. As the pool of cDNA inserts appeared promising, overexpressed genes were further selected. From 259 clones, 17 clones were overexpressed more than 6-fold in DU145 compared to Normal Prostate. From the 17 clones, 12 cDNA inserts were strongly expressed in DU145 and were isolated for sequencing. ^ Two of the sequences, 1G6 and 3E9, were identical. Expression of 1G6/2G9/3E9 was tested by RT-PCR. 1G6/2G9/3E9 was not expressed in normal prostate, but was expressed in all prostate cancer cell lines tested as well as six prostate cancer samples. When retransfected into CP12, 1G6/2G9/3E9 induced the formation of foci and anchorage independent colonies. Thus, functional and expression data suggest that 1G6/2G9/3E9 may be a prostate cancer oncogene. ^

Positional candidate cloning of the RP10 form of retinitis pigmentosa

Retinitis pigmentosa (RP) is a genetically heterogeneous group of retinal degenerations that affects over one million people worldwide. To date, 11 autosomal dominant, 13 autosomal recessive, and 5 X-linked forms of retinitis pigmentosa have been identified through linkage analysis, but the disease-causing genes and mutations have been found for only half of these loci. My research uses a positional candidate cloning approach to identify the gene and mutations responsible for one type of autosomal dominant retinitis pigmentosa, RP10. The premise is that identifying the genes and mutations responsible for disease will provide insight into disease mechanisms and provide treatment options. Previous research mapped the RP10 locus to a 5cM region on chromosome 7q31 between markers D7S686 and D7S530. Linkage and fine-point haplotype analysis was used to reduce and refine the RP10 disease interval to a 4cM region located between D7S2471 and a new marker located 45,000bp telomeric of D7S461. In order to identify genes located in the RP10 interval, an extensive EST map was created of this region. Five EST clusters from this map were analyzed to determine if mutations in these genes cause the RP10 form of retinitis pigmentosa. The genomic structure of a known metabotrophic glutamate receptor, GRMS8, was determined first. DNA sequencing of GRM8 in RP10 family members did not identify any disease-causing mutations. Four other EST clusters (A170, A173, A189, and A258) were characterized and determined to be part of the same gene, UBNL1 (ubinuclein-like 1). The full-length mRNA sequence and genomic structure of UBNL1 was determined and then screened in patients. No disease-causing mutations were identified in any of the RP10 family members tested. Recent data made available with the release of the public and Celera genome assemblies indicates that UBNL1 is outside of the RP10 disease region. Despite this complication, characterization of UBNL1 is still important in the understanding of normal visual processes and it is possible that mutations in UBNL1 could cause other forms of retinopathy. The EST map and list of RP10 candidates will continue to aid others in the search for the RP10 gene and mutations. ^

An Sp1/Sp3 site polymorphism associated with hypermethylation of the candidate tumor suppressor gene RIL in cancer

Gene silencing due to promoter methylation is an alternative to mutations and deletions, which inactivate tumor suppressor genes (TSG) in cancer. We identified RIL by Methylated CpG Island Amplification technique as a novel aberrantly methylated gene. RIL is expressed in normal tissues and maps to the 5q31 region, frequently deleted in leukemias. We found methylation of RIL in 55/80 (69%) cancer cell lines, with highest methylation in leukemia and colon. We also observed methylation in 46/80 (58%) primary tumors, whereas normal tissues showed substantially lower degrees of methylation. RIL expression was lost in 13/16 cancer cell lines and was restored by demethylating agent. Screening of 38 cell lines and 13 primary cancers by SSCP revealed no mutations in RIL, suggesting that methylation and LOH are the primary inactivation mechanisms. Stable transfection of RIL into colorectal cancer cells resulted in reduction in cell growth, clonogenicity, and increased apoptosis upon UVC treatment, suggesting that RIL is a good candidate TSG. ^ In searching for a cause of RIL hypermethylation, we identified a 12-bp polymorphic sequence around the transcription start site of the gene that creates a long allele containing 3CTC repeat. Evolutionary studies suggested that the long allele appeared late in evolution due to insertion. Using bisulfite sequencing, in cancers heterozygous for RIL, we found that the short allele is 4.4-fold more methylated than the long allele (P = 0.003). EMSA results suggested binding of factor(s) to the inserted region of the long allele, but not to the short. EMSA mutagenesis and competition studies, as well as supershifts using nuclear extracts or recombinant Sp1 strongly indicated that those DNA binding proteins are Sp1 and Sp3. Transient transfections of RIL allele-specific expression constructs showed less than 2-fold differences in luciferase activity, suggesting no major effects of the additional Sp1 site on transcription. However, stable transfection resulted in 3-fold lower levels of transcription from the short allele 60 days post-transfection, consistent with the concept that the polymorphic Sp1 site protects against time-dependent silencing. Thus, an insertional polymorphism in the RIL promoter creates an additional Sp1/Sp3 site, which appears to protect it from silencing and methylation in cancer. ^

Identification of germ cell tumor modifier genes from the 129.MOLF-Chr19 consomic mouse strain

Naturally occurring genetic variants confer susceptibility to disease in the human population, including in testicular germ cell tumor development. Disease susceptibility loci for testicular germ cell tumors have been identified by genetic mapping in humans and mice. However, the identity of many of the susceptibility genes remains unclear. My study utilized a chromosome substitution strain, the 129.MOLF-Chr 19 (or M19 strain), to identify candidate testicular germ cell tumor susceptibility genes. Males of this strain have a high incidence of germ cell tumors in the testes. By forward genetic approaches, five susceptibility loci were fine-mapped and the genetic interactions were dissected. In addition, I identified three protein-coding genes and one micro-RNA as testicular tumor susceptibility genes by genomic screening. Using reverse genetic approaches, I verified one of the candidates, Splicing factor 1, as a modifier of testicular tumor. Deficiency of SF1 significantly reduces the incidence of testicular tumors in mice. This study highlights the advantage of the 129.MOLF-Chr 19 consomic strain in disease gene identification and validation. It also sets the stage to elucidate the molecular mechanisms of tumorigenesis in the testis. ^

Identification and characterization of mutations in SMC contractile genes involved in thoracic aortic aneurysms and dissections

Aortic aneurysms and dissections are the 15th most common cause of death in the United States. Genetic factors contribute to the pathogenesis of thoracic aortic aneurysms and dissections (TAAD). Currently, six loci and four genes have been identified for familial TAAD. Notably, mutations in smooth muscle cell (SMC) contractile genes, ACTA2 and MYH11, are responsible for 15% of familial TAAD, suggesting that proper SMC contraction is important for normal aorta function. Therefore, we hypothesize that mutations in other genes encoding SMC contractile proteins also cause familial TAAD. ^ To test this hypothesis, we used a candidate gene approach to identify causative mutations in SMC contractile genes for familial TAAD. Sequencing DNA in 80 TAAD patients from unrelated families, we identified putative mutations in eight contractile genes. We chose myosin light chain kinase (MLCK ) S1759P for further study for the following reasons: (1) Serine 1759 is conserved between vertebrates and invertebrates. (2) S1759P is predicted to be functionally deleterious by bioinformatics. (3) Low blood pressure is observed in SMC-selective MLCK-deficient mice. ^ In the presence of Ca2+/Calmodulin (CaM), MLCK containing CaM binding and kinase domains are activated to phosphorylate myosin light chain, thereby initiate SMC contraction. The CaM binding sequence of MLCK forms an α-helix structure required for CaM binding. MLCK Serine 1759 is located within the CaM binding domain. S1759P is predicted to decrease the α-helix composition in the CaM binding domain. Hence, we hypothesize that MLCK mutations cause TAAD through disturbing CaM binding and MLCK activity. ^ We further sequenced MLCK in DNA samples from additional 86 probands with familial TAAD. Two more mutations, MLCK A1754T and R1480Stop, were identified, supporting that MLCK mutations cause familial TAAD. ^ To define whether MLCK mutations disrupted CaM binding and MLCK activity, we performed co-immunoprecipitation and kinase assays. Decreased CaM binding and kinase activity was detected in A1754T and S1759P. Moreover, R1480Stop is predicted to truncate kinase and CaM binding domains. We conclude that MLCK mutations disrupt CaM binding and MLCK activity. ^ Collectively, our study is first to show mutations in genes regulating SMC contraction cause TAAD. This finding further highlights the importance of SMC contraction in maintaining aorta function. ^

Identification and characterization of cellular genes differentially expressed in a subset of tumors with non -functional WT1

Wilms tumor (WT) or nephroblastoma is a genetically heterogeneous pediatric renal tumor that accounts for 6–7% of all childhood cancers in the U.S. WT1, located at 11p13, is the sole WT gene cloned to date. Additional genomic regions containing genes that play a role in the development of Wilms tumor include 11p15, 7p, 16q, 1p, 17q and 19q. This heterogeneity has made it extremely difficult to develop an understanding of the pathways involved in the development of WT, even in the 5–20% of tumors that show mutations at the WT1 locus. My research addresses this gap in our current comprehension of the development of WT. ^ I have used two complementary approaches to extend the current understanding of molecular changes involved in the development of WT. In order to minimize complexities due to genetic heterogeneity, I confined my analysis to the WT1 pathway by assessing those genetically defined tumors that carry WT1 mutations. WT1 encodes a zinc finger transcription factor, and in vitro studies have identified many genes that are potentially regulated in vivo by WT1. However, there is very little in vivo data that suggests that they are transcriptionally regulated endogenously by WT1. In one approach I assessed the role of WT1 in the in vivo regulation of PDGFA and IGF2, two genes that are strong contenders for endogenous regulation by WT1. Using primary tissue samples, I found no correlation between the level of RNA expression of WT1 with either PDGFA or IGF2, suggesting that WT1 does not play a critical role in their expression in either normal kidney or WT. ^ In a parallel strategy, using differential display analysis I compared global gene expression in a subset of tumors with known homozygous inactivating WT1 mutations (WT1-tumors) to the gene expression in a panel of appropriate control tissues (fetal kidney, normal kidney, rhabdoid tumor and pediatric renal cell carcinoma). Transcripts that are aberrantly expressed in this subset of Wilms tumors are candidates for endogenous transcriptional regulation by WT1 as well as for potentially functioning in the development of WT. By this approach I identified several differentially expressed transcripts. I further characterized two of these transcripts, identifying a candidate WT gene in the process. I then performed a detailed analysis of this WT candidate gene, which maps to 7p. Future studies will shed more light on the role of these differentially expressed genes in WT. ^