Direct Inference of SNP Heterozygosity Rates and Resolution of LOH Detection

Single nucleotide polymorphisms (SNPs) have been increasingly utilized to investigate somatic genetic abnormalities in premalignancy and cancer. LOH is a common alteration observed during cancer development, and SNP assays have been used to identify LOH at specific chromosomal regions. The design of such studies requires consideration of the resolution for detecting LOH throughout the genome and identification of the number and location of SNPs required to detect genetic alterations in specific genomic regions. Our study evaluated SNP distribution patterns and used probability models, Monte Carlo simulation, and real human subject genotype data to investigate the relationships between the number of SNPs, SNP HET rates, and the sensitivity (resolution) for detecting LOH. We report that variances of SNP heterozygosity rate in dbSNP are high for a large proportion of SNPs. Two statistical methods proposed for directly inferring SNP heterozygosity rates require much smaller sample sizes (intermediate sizes) and are feasible for practical use in SNP selection or verification. Using HapMap data, we showed that a region of LOH greater than 200 kb can be reliably detected, with losses smaller than 50 kb having a substantially lower detection probability when using all SNPs currently in the HapMap database. Higher densities of SNPs may exist in certain local chromosomal regions that provide some opportunities for reliably detecting LOH of segment sizes smaller than 50 kb. These results suggest that the interpretation of the results from genome-wide scans for LOH using commercial arrays need to consider the relationships among inter-SNP distance, detection probability, and sample size for a specific study. New experimental designs for LOH studies would also benefit from considering the power of detection and sample sizes required to accomplish the proposed aims

Inferring Loss-of-Heterozygosity from Unpaired Tumors Using High-Density Oligonucleotide SNP Arrays

Loss of heterozygosity (LOH) of chromosomal regions bearing tumor suppressors is a key event in the evolution of epithelial and mesenchymal tumors. Identification of these regions usually relies on genotyping tumor and counterpart normal DNA and noting regions where heterozygous alleles in the normal DNA become homozygous in the tumor. However, paired normal samples for tumors and cell lines are often not available. With the advent of oligonucleotide arrays that simultaneously assay thousands of single-nucleotide polymorphism (SNP) markers, genotyping can now be done at high enough resolution to allow identification of LOH events by the absence of heterozygous loci, without comparison to normal controls. Here we describe a hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome. When we applied the method to data genotyped on 100 K arrays, we correctly identified 99% of SNP markers as either retention or loss. We also correctly identified 81% of the regions of LOH, including 98% of regions greater than 3 megabases. By integrating copy number analysis into the method, we were able to distinguish LOH from allelic imbalance. Application of this method to data from a set of prostate samples without paired normals identified known regions of prevalent LOH. We have developed a method for analyzing high-density oligonucleotide SNP array data to accurately identify of regions of LOH and retention in tumors without the need for paired normal samples

Accurate estimation of homologue-specific DNA concentration-ratios in cancer samples allows long-range haplotyping

Interpretation of allelic copy measurements at polymorphic markers in cancer samples presents distinctive challenges and opportunities. Due to frequent gross chromosomal alterations occurring in cancer (aneuploidy), many genomic regions are present at homologous-allele imbalance. Within such regions, the unequal contribution of alleles at heterozygous markers allows for direct phasing of the haplotype derived from each individual parent. In addition, genome-wide estimates of homologue specific copy- ratios (HSCRs) are important for interpretation of the cancer genome in terms of fixed integral copy-numbers. We describe HAPSEG, a probabilistic method to interpret bi- allelic marker data in cancer samples. HAPSEG operates by partitioning the genome into segments of distinct copy number and modeling the four distinct genotypes in each segment. We describe general methods for fitting these models to data which are suit- able for both SNP microarrays and massively parallel sequencing data. In addition, we demonstrate a specially tailored error-model for interpretation of systematic variations arising in microarray platforms. The ability to directly determine haplotypes from cancer samples represents an opportunity to expand reference panels of phased chromosomes, which may have general interest in various population genetic applications. In addition, this property may be exploited to interrogate the relationship between germline risk and cancer phenotype with greater sensitivity than is possible using unphased genotype. Finally, we exploit the statistical dependency of phased genotypes to enable the fitting of more elaborate sample-level error-model parameters, allowing more accurate estimation of HSCRs in cancer samples

Single nucleotide polymorphism-based genome-wide chromosome copy change, loss of heterozygosity, and aneuploidy in Barrett's esophagus neoplastic progression.

Chromosome copy gain, loss, and loss of heterozygosity (LOH) involving most chromosomes have been reported in many cancers; however, less is known about chromosome instability in premalignant conditions. 17p LOH and DNA content abnormalities have been previously reported to predict progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA). Here, we evaluated genome-wide chromosomal instability in multiple stages of BE and EA in whole biopsies. Forty-two patients were selected to represent different stages of progression from BE to EA. Whole BE or EA biopsies were minced, and aliquots were processed for flow cytometry and genotyped with a paired constitutive control for each patient using 33,423 single nucleotide polymorphisms (SNP). Copy gains, losses, and LOH increased in frequency and size between early- and late-stage BE (P 30% in early and late stages, respectively. A set of statistically significant events was unique to either early or late, or both, stages, including previously reported and novel abnormalities. The total number of SNP alterations was highly correlated with DNA content aneuploidy and was sensitive and specific to identify patients with concurrent EA (empirical receiver operating characteristic area under the curve = 0.91). With the exception of 9p LOH, most copy gains, losses, and LOH detected in early stages of BE were smaller than those detected in later stages, and few chromosomal events were common in all stages of progression. Measures of chromosomal instability can be quantified in whole biopsies using SNP-based genotyping and have potential to be an integrated platform for cancer risk stratification in BE

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan

BACKGROUND: A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging. RESULTS: We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'Étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA. CONCLUSION: SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website

Analysis of the relationship between genomic instability, heterozygosity levels and phenotype in Saccharomyces cerevisiae

2018 Fall.Includes bibliographical references.Understanding the forces that mediate genome evolution is a central problem in genetics, with implications for diverse processes that range from speciation, to biotechnological applications, to human disease. The central theme of my dissertation was the characterization of two forces, genomic instability and natural selection, that significantly impact genome structure by influencing the levels of genomic heterozygosity. While genomic instability processes can act to erode heterozygosity from the genome, natural selection may favor the maintenance of heterozygous alleles in cases where there is a positive correlation between heterozygosity and higher fitness. In Chapter I, I reviewed different types of mitotic mutations that can result in the appearance of tracts of homozygosity in genomes and recent discoveries about the temporal accumulation of such events. I also introduce the concept of heterosis, a phenomenon characterized by a positive correlation between genomic heterozygosity and phenotype in many species, and its potential role in contributing to the long-term maintenance of genomic heterozygosity. In Chapter II, I describe the characterization of a mechanism of systemic genomic instability in yeast that challenges the conventional model of gradual and independent accumulation of mutations. We showed that a subset of mitotic cells within a population experience bursts of genomic instability, which results in multiple independent events of loss-of-heterozygosity (LOH) accumulating over one or a few generations of mitotic cell division. We named this outcome "systemic genomic instability". The occurrence of this phenomenon was initially identified in the heterozygous yeast strain JAY270, and then validated in a conventional laboratory strain background, whose genome is almost fully homozygous. Elevated rates of coincident LOH was also observed in mutant strains incapable of entering meiosis, indicating cryptic initiation of meiotic recombination followed by return-to-growth in a few cells in the population was not responsible for the higher than expected rates of coincident LOH. This finding brings to light a novel and intriguing mechanism of genomic instability in yeast that has relevant parallels to bursts of accumulation of copy number alterations in the human genome, providing a powerful experimental model system to dissect the fundamental mechanisms responsible for the generation of rapid changes in chromosome structure. In Chapter III, we explored the role that genomic heterozygosity plays on the superior industrial traits of the JAY270 strain. In the previous Chapter we showed that mitotic recombination leading to LOH occurs at a high frequency during JAY270's clonal propagation. These LOH events act against the long-term maintenance of genomic heterozygosity, yet about 60% of JAY270's genome has remained heterozygous over time. We hypothesized that specific heterozygous alleles may have a positive impact on the traits of this strain and therefore were maintained through selection. We generated a collection of inbred strains derived from JAY270, and assessed them phenotypically under different growth conditions. Our results demonstrated that genomic heterozygosity indeed has a substantial impact on two important industrial traits of this strain – heat stress tolerance and growth kinetics. We identified several genomic regions potentially associated with those traits and conducted experiments to investigate the bulk contributions of heterozygosity blocks in three specific chromosomes. This study revealed candidate regions containing loci that potentially underlie important industrial traits of JAY270 and details on the extent to which heterozygosity may impact JAY270's genome evolution and phenotype. The combined results of these research projects provide important insights about the role of genomic instability mechanisms and their phenotypic outcomes in determining genome evolution, contributing discoveries that may have important practical implications for diverse fields, including biotechnology, cancer development and evolution, as well as genome sciences

The Progress on Genetic Analysis of Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a rare malignancy in most parts of the world, but is one of the most common cancers in Southeast Asia. Both genetic and environmental factors contribute to the tumorigenesis of NPC, most notably the consumption of certain salted food items and Epstein-Barr virus infection. This review will focus on the current progress of the genetic analysis of NPC (genetic susceptibilities and somatic alterations). We will review the current advances in genomic technologies and their shaping of the future direction of NPC research

Refphase: Multi-sample phasing reveals haplotype-specific copy number heterogeneity

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient’s disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample phasing. We demonstrate Refphase’s ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours

TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays

<p>Abstract</p> <p>Background</p> <p>High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, including total copy number and loss of heterozygosity (LOH) analyses. Even after state of the art preprocessing methods, allelic signal estimates from genotyping arrays still suffer from systematic effects that make them difficult to use effectively for such downstream analyses.</p> <p>Results</p> <p>We propose a method, TumorBoost, for normalizing allelic estimates of one tumor sample based on estimates from a single matched normal. The method applies to any paired tumor-normal estimates from any microarray-based technology, combined with any preprocessing method. We demonstrate that it increases the signal-to-noise ratio of allelic signals, making it significantly easier to detect allelic imbalances.</p> <p>Conclusions</p> <p>TumorBoost increases the power to detect somatic copy-number events (including copy-neutral LOH) in the tumor from allelic signals of Affymetrix or Illumina origin. We also conclude that high-precision allelic estimates can be obtained from a single pair of tumor-normal hybridizations, if TumorBoost is combined with single-array preprocessing methods such as (allele-specific) CRMA v2 for Affymetrix or BeadStudio's (proprietary) XY-normalization method for Illumina. A bounded-memory implementation is available in the open-source and cross-platform R package <it>aroma.cn</it>, which is part of the Aroma Project (<url>http://www.aroma-project.org/</url>).</p

Host-induced aneuploidy and phenotypic diversification in the Sudden Oak Death pathogen Phytophthora ramorum

BackgroundAneuploidy can result in significant phenotypic changes, which can sometimes be selectively advantageous. For example, aneuploidy confers resistance to antifungal drugs in human pathogenic fungi. Aneuploidy has also been observed in invasive fungal and oomycete plant pathogens in the field. Environments conducive to the generation of aneuploids, the underlying genetic mechanisms, and the contribution of aneuploidy to invasiveness are underexplored. We studied phenotypic diversification and associated genome changes in Phytophthora ramorum, a highly destructive oomycete pathogen with a wide host-range that causes Sudden Oak Death in western North America and Sudden Larch Death in the UK. Introduced populations of the pathogen are exclusively clonal. In California, oak (Quercus spp.) isolates obtained from trunk cankers frequently exhibit host-dependent, atypical phenotypes called non-wild type (nwt), apparently without any host-associated population differentiation. Based on a large survey of genotypes from different hosts, we previously hypothesized that the environment in oak cankers may be responsible for the observed phenotypic diversification in P. ramorum.ResultsWe show that both normal wild type (wt) and nwt phenotypes were obtained when wt P. ramorum isolates from the foliar host California bay (Umbellularia californica) were re-isolated from cankers of artificially-inoculated canyon live oak (Q. chrysolepis). We also found comparable nwt phenotypes in P. ramorum isolates from a bark canker of Lawson cypress (Chamaecyparis lawsoniana) in the UK; previously nwt was not known to occur in this pathogen population. High-throughput sequencing-based analyses identified major genomic alterations including partial aneuploidy and copy-neutral loss of heterozygosity predominantly in nwt isolates. Chromosomal breakpoints were located at or near transposons.ConclusionThis work demonstrates that major genome alterations of a pathogen can be induced by its host species. This is an undocumented type of plant-microbe interaction, and its contribution to pathogen evolution is yet to be investigated, but one of the potential collateral effects of nwt phenotypes may be host survival