Faculty Bibliography

In Israel, as in several countries of the Mediterranean basin, beta-thalassemia is frequent among Arabs, and many different mutations in the beta globin gene have been identified. In a single Arab village, three different thalassemia mutations, as well as the sickle-cell mutation, were characterized. Using genealogical data as well as the results of screening in the village population, we were able to demonstrate/speculate on how mutations were introduced into the village and how they later expanded. The sickle-cell mutation became particularly prevalent in the village as the result of a founder effect due to a preference for consanguineous marriages.

The ability to discriminate between deleterious and neutral amino acid substitutions in the genes of patients remains a significant challenge in human genetics. The increasing availability of genomic sequence data from multiple vertebrate species allows inclusion of sequence conservation and physicochemical properties of residues to be used for functional prediction. In this study, the RET receptor tyrosine kinase serves as a model disease gene in which a broad spectrum (> or = 116) of disease-associated mutations has been identified among patients with Hirschsprung disease and multiple endocrine neoplasia type 2. We report the alignment of the human RET protein sequence with the orthologous sequences of 12 non-human vertebrates (eight mammalian, one avian, and three teleost species), their comparative analysis, the evolutionary topology of the RET protein, and predicted tolerance for all published missense mutations. We show that, although evolutionary conservation alone provides significant information to predict the effect of a RET mutation, a model that combines comparative sequence data with analysis of physiochemical properties in a quantitative framework provides far greater accuracy. Although the ability to discern the impact of a mutation is imperfect, our analyses permit substantial discrimination between predicted functional classes of RET mutations and disease severity even for a multigenic disease such as Hirschsprung disease.

The identification of common variants that contribute to the genesis of human inherited disorders remains a significant challenge. Hirschsprung disease (HSCR) is a multifactorial, non-mendelian disorder in which rare high-penetrance coding sequence mutations in the receptor tyrosine kinase RET contribute to risk in combination with mutations at other genes. We have used family-based association studies to identify a disease interval, and integrated this with comparative and functional genomic analysis to prioritize conserved and functional elements within which mutations can be sought. We now show that a common non-coding RET variant within a conserved enhancer-like sequence in intron 1 is significantly associated with HSCR susceptibility and makes a 20-fold greater contribution to risk than rare alleles do. This mutation reduces in vitro enhancer activity markedly, has low penetrance, has different genetic effects in males and females, and explains several features of the complex inheritance pattern of HSCR. Thus, common low-penetrance variants, identified by association studies, can underlie both common and rare diseases.

When a novel variant is found in a patient and not in a group of controls, it becomes a candidate for the disease-causing mutation in that patient. At present, no sampling theory exists for assessing the probability that the novel SNP might actually be a neutral variant. We have developed a population genetics-based method for calculating a P-value for a mutation-detection effort. Our method can be applied to a heterozygous patient, a homozygous patient, with or without inbreeding, or to a patient who is a compound heterozygote. Additionally, the method can be used to calculate the probability of finding a neutral variant at frequencies that differ between a group of patients and a group of controls, given some length of sequence examined. This method accounts for the multiple testing that is inherent in identification of variants through sequencing, to be used in subsequent case-control analyses. We show, for example, that for complete resequencing of 10 kb, the probability of finding a neutral variant in a patient and not in 50 controls is about 15%. Thus, discovery of a variant in a patient and not in a group of controls is, on its own, very weak evidence of involvement with disease

Genome-wide disease-association mapping has been heralded as the study design of the next generation, but the lack of analytical methods to use genotype data fully is a large stumbling block. Here we describe an algorithm and statistical method that efficiently and exhaustively exploits haplotype information by subjecting alleles (a marker or contiguous sets of markers) from sliding windows of all sizes to transmission disequilibrium tests. By applying our method to simulated data and to Hirschsprung disease, we show that it can detect both common and rare disease variants of small effect. These results show that the theoretical benefits of genome-wide association studies are at last realizable.

Determining linkage phase from population samples with statistical methods is accurate only within regions of high linkage disequilibrium (LD). Yet, affected individuals in a genetic mapping study, including those involving cases and controls, may share sequences identical-by-descent stretching on the order of 10s to 100s of kilobases, quite possibly over regions of low LD in the population. At the same time, inferring phase from nuclear families may be hampered by missing family members, missing genotypes, and the noninformativity of certain genotype patterns. In this study, we reformulate our previous haplotype reconstruction algorithm, and its associated computer program, to phase parents with information derived from population samples as well as from their offspring. In applications of our algorithm to 100-kb stretches, simulated in accordance to a Wright-Fisher model with typical levels of LD in humans, we find that phase reconstruction for 160 trios with 10% missing data is highly accurate (>90%) over the entire length. Furthermore, our algorithm can estimate allelic status for missing data at high accuracy (>95%). Finally, the input capacity of the program is vast, easily handling thousands of segregating sites in > or = 1000 chromosomes.

Somatic mitochondrial mutations are common in human cancers, and can be used as a tool for early detection of cancer. We have developed a mitochondrial Custom Reseq microarray as an array-based sequencing platform for rapid and high-throughput analysis of mitochondrial DNA. The MitoChip contains oligonucleotide probes synthesized using standard photolithography and solid-phase synthesis, and is able to sequence >29 kb of double-stranded DNA in a single assay. Both strands of the entire human mitochondrial coding sequence (15,451 bp) are arrayed on the MitoChip; both strands of an additional 12,935 bp (84% of coding DNA) are arrayed in duplicate. We used 300 ng of genomic DNA to amplify the mitochondrial coding sequence in three overlapping long PCR fragments. We then sequenced >2 million base pairs of mitochondrial DNA, and successfully assigned base calls at 96.0% of nucleotide positions. Replicate experiments demonstrated >99.99% reproducibility. In matched fluid samples (urine and pancreatic juice, respectively) obtained from five patients with bladder cancer and four with pancreatic cancer, the MitoChip detected at least one cancer-associated mitochondrial mutation in six (66%) of nine samples. The MitoChip is a high-throughput sequencing tool for the reliable identification of mitochondrial DNA mutations from primary tumors in clinical samples.