Comprehensive analysis of loss of heterozygosity events in glioblastoma using the 100K SNP mapping arrays and comparison with copy number abnormalities defined by BAC array comparative genomic hybridization.

We have undertaken an extensive high-resolution analysis of loss of heterozygosity (LOH) in 30 high grade gliomas using the Affymetrix 100K SNP mapping array. Only 70% of LOH events were accompanied by a copy number loss (CNA(loss)), and of the other 30%, the distal region of 17p preferentially showed copy number neutral (CNN)-associated LOH. Combined analysis of CNA(loss) and LOH using MergeLevels analysis software predicts whether the observed losses occurred on a diploid or tetraploid background. In a side-by-side comparison between SNP and bacterial artificial chromosome (BAC) arrays, the overall identification of CNAs was similar on both platforms. The resolution provided by the SNP arrays, however, allowed a considerably more accurate definition of breakpoints as well as defining small events within the cancer genomes, which could not be detected on BAC arrays. CNN LOH was only detected by the SNP arrays, as was ploidy prediction. From our analysis, therefore, it is clear that simultaneously defining CNAs and CNN-LOH using the SNP platform provides a higher resolution and more complete analysis of the genetic events that have occurred within tumor cells. Our extensive analysis of SNP array data has also allowed an objective assessment of threshold LOH scores that can accurately predict LOH. This capability has important implications for interpretation of LOH events since they have consistently been used to localize potential tumor suppressor genes within the cancer genome.

Genome-wide, high-resolution detection of copy number, loss of heterozygosity, and genotypes from formalin-fixed, paraffin-embedded tumor tissue using microarrays.

Formalin-fixed, paraffin-embedded (FFPE) material tends to yield degraded DNA and is thus suboptimal for use in many downstream applications. We describe an integrated analysis of genotype, loss of heterozygosity (LOH), and copy number for DNA derived from FFPE tissues using oligonucleotide microarrays containing over 500K single nucleotide polymorphisms. A prequalifying PCR test predicted the performance of FFPE DNA on the microarrays better than age of FFPE sample. Although genotyping efficiency and reliability were reduced for FFPE DNA when compared with fresh samples, closer examination revealed methods to improve performance at the expense of variable reduction in resolution. Important steps were also identified that enable equivalent copy number and LOH profiles from paired FFPE and fresh frozen tumor samples. In conclusion, we have shown that the Mapping 500K arrays can be used with FFPE-derived samples to produce genotype, copy number, and LOH predictions, and we provide guidelines and suggestions for application of these samples to this integrated system.

A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array.

BACKGROUND: DNA copy number aberration (CNA) is one of the key characteristics of cancer cells. Recent studies demonstrated the feasibility of utilizing high density single nucleotide polymorphism (SNP) genotyping arrays to detect CNA. Compared with the two-color array-based comparative genomic hybridization (array-CGH), the SNP arrays offer much higher probe density and lower signal-to-noise ratio at the single SNP level. To accurately identify small segments of CNA from SNP array data, segmentation methods that are sensitive to CNA while resistant to noise are required. RESULTS: We have developed a highly sensitive algorithm for the edge detection of copy number data which is especially suitable for the SNP array-based copy number data. The method consists of an over-sensitive edge-detection step and a test-based forward-backward edge selection step. CONCLUSION: Using simulations constructed from real experimental data, the method shows high sensitivity and specificity in detecting small copy number changes in focused regions. The method is implemented in an R package FASeg, which includes data processing and visualization utilities, as well as libraries for processing Affymetrix SNP array data.

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations.

MOTIVATION: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. METHODS: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed 'flipped SNPs'. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations. RESULTS: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study. AVAILABILITY: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.

A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays.

We have developed a robust algorithm for copy number analysis of the human genome using high-density oligonucleotide microarrays containing 116,204 single-nucleotide polymorphisms. The advantages of this algorithm include the improvement of signal-to-noise (S/N) ratios and the use of an optimized reference. The raw S/N ratios were improved by accounting for the length and GC content of the PCR products using quadratic regressions. The use of constitutional DNA, when available, gives the lowest SD values (0.16 +/- 0.03) and also enables allele-based copy number detection in cancer genomes, which can unmask otherwise concealed allelic imbalances. In the absence of constitutional DNA, optimized selection of multiple normal references with the highest S/N ratios, in combination with the data regressions, dramatically improves SD values from 0.67 +/- 0.12 to 0.18 +/- 0.03. These improvements allow for highly reliable comparison of data across different experimental conditions, detection of allele-based copy number changes, and more accurate estimations of the range and magnitude of copy number aberrations. This algorithm has been implemented in a software package called Copy Number Analyzer for Affymetrix GeneChip Mapping 100K arrays (CNAG). Overall, these enhancements make CNAG a useful tool for high-resolution detection of copy number alterations which can help in the understanding of the pathogenesis of cancers and other diseases as well as in exploring the complexities of the human genome.

Overlay tool for aCGHViewer: an analysis module built for aCGHViewer used to perform comparisons of data derived from different microarray platforms.

The Overlay Tool has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.

Oligonucleotide microarray analysis of genomic imbalance in children with mental retardation.

The cause of mental retardation in one-third to one-half of all affected individuals is unknown. Microscopically detectable chromosomal abnormalities are the most frequently recognized cause, but gain or loss of chromosomal segments that are too small to be seen by conventional cytogenetic analysis has been found to be another important cause. Array-based methods offer a practical means of performing a high-resolution survey of the entire genome for submicroscopic copy-number variants. We studied 100 children with idiopathic mental retardation and normal results of standard chromosomal analysis, by use of whole-genome sampling analysis with Affymetrix GeneChip Human Mapping 100K arrays. We found de novo deletions as small as 178 kb in eight cases, de novo duplications as small as 1.1 Mb in two cases, and unsuspected mosaic trisomy 9 in another case. This technology can detect at least twice as many potentially pathogenic de novo copy-number variants as conventional cytogenetic analysis can in people with mental retardation.

High-resolution identification of chromosomal abnormalities using oligonucleotide arrays containing 116,204 SNPs.

Mutation of the human genome ranges from single base-pair changes to whole-chromosome aneuploidy. Karyotyping, fluorescence in situ hybridization, and comparative genome hybridization are currently used to detect chromosome abnormalities of clinical significance. These methods, although powerful, suffer from limitations in speed, ease of use, and resolution, and they do not detect copy-neutral chromosomal aberrations--for example, uniparental disomy (UPD). We have developed a high-throughput approach for assessment of DNA copy-number changes, through use of high-density synthetic oligonucleotide arrays containing 116,204 single-nucleotide polymorphisms, spaced at an average distance of 23.6 kb across the genome. Using this approach, we analyzed samples that failed conventional karyotypic analysis, and we detected amplifications and deletions across a wide range of sizes (1.3-145.9 Mb), identified chromosomes containing anonymous chromatin, and used genotype data to determine the molecular origin of two cases of UPD. Furthermore, our data provided independent confirmation for a case that had been misinterpreted by karyotype analysis. The high resolution of our approach provides more-precise breakpoint mapping, which allows subtle phenotypic heterogeneity to be distinguished at a molecular level. The accurate genotype information provided on these arrays enables the identification of copy-neutral loss-of-heterozygosity events, and the minimal requirement of DNA (250 ng per array) allows rapid analysis of samples without the need for cell culture. This technology overcomes many limitations currently encountered in routine clinical diagnostic laboratories tasked with accurate and rapid diagnosis of chromosomal abnormalities.

Genomic maps and comparative analysis of histone modifications in human and mouse.

We mapped histone H3 lysine 4 di- and trimethylation and lysine 9/14 acetylation across the nonrepetitive portions of human chromosomes 21 and 22 and compared patterns of lysine 4 dimethylation for several orthologous human and mouse loci. Both chromosomes show punctate sites enriched for modified histones. Sites showing trimethylation correlate with transcription starts, while those showing mainly dimethylation occur elsewhere in the vicinity of active genes. Punctate methylation patterns are also evident at the cytokine and IL-4 receptor loci. The Hox clusters present a strikingly different picture, with broad lysine 4-methylated regions that overlay multiple active genes. We suggest these regions represent active chromatin domains required for the maintenance of Hox gene expression. Methylation patterns at orthologous loci are strongly conserved between human and mouse even though many methylated sites do not show sequence conservation notably higher than background. This suggests that the DNA elements that direct the methylation represent only a small fraction of the region or lie at some distance from the site.

Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution.

Sites of transcription of polyadenylated and nonpolyadenylated RNAs for 10 human chromosomes were mapped at 5-base pair resolution in eight cell lines. Unannotated, nonpolyadenylated transcripts comprise the major proportion of the transcriptional output of the human genome. Of all transcribed sequences, 19.4, 43.7, and 36.9% were observed to be polyadenylated, nonpolyadenylated, and bimorphic, respectively. Half of all transcribed sequences are found only in the nucleus and for the most part are unannotated. Overall, the transcribed portions of the human genome are predominantly composed of interlaced networks of both poly A+ and poly A- annotated transcripts and unannotated transcripts of unknown function. This organization has important implications for interpreting genotype-phenotype associations, regulation of gene expression, and the definition of a gene.