Teresa Webster

Integrated detection and population-genetic analysis of SNPs and copy number variation

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.

Ancient Admixture in Human History

Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.”

Genotyping over 100,000 SNPs on a pair of oligonucleotide arrays

We present a genotyping method for simultaneously scoring 116,204 SNPs using oligonucleotide arrays. At call rates >99%, reproducibility is >99.97% and accuracy, as measured by inheritance in trios and concordance with the HapMap Project, is >99.7%. Average intermarker distance is 23.6 kb, and 92% of the genome is within 100 kb of a SNP marker. Average heterozygosity is 0.30, with 105,511 SNPs having minor allele frequencies >5%.

Probe selection for high-density oligonucleotide arrays

High-density oligonucleotide microarrays enable simultaneous monitoring of expression levels of tens of thousands of transcripts. For accurate detection and quantitation of transcripts in the presence of cellular mRNA, it is essential to design microarrays whose oligonucleotide probes produce hybridization intensities that accurately reflect the concentration of original mRNA. We present a model-based approach that predicts optimal probes by using sequence and empirical information. We constructed a thermodynamic model for hybridization behavior and determined the influence of empirical factors on the effective fitting parameters. We designed Affymetrix GeneChip probe arrays that contained all 25-mer probes for hundreds of human and yeast transcripts and collected data over a 4,000-fold concentration range. Multiple linear regression models were built to predict hybridization intensities of each probe at given target concentrations, and each intensity profile is summarized by a probe response metric. We selected probe sets to represent each transcript that were optimized with respect to responsiveness, independence (degree to which probe sequences are nonoverlapping), and uniqueness (lack of similarity to sequences in the expressed genomic background). We show that this approach is capable of selecting probes with high sensitivity and specificity for high-density oligonucleotide arrays.

Next generation genome-wide association tool: Design and coverage of a high-throughput European-optimized SNP array

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm.

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.

High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool.

Summary In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheats secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra‐high‐density Axiom® genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site.

Genotyping Informatics and Quality Control for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California—San Francisco, undertook genome-wide genotyping of >100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated >70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1–95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

Characterisation of a Wheat Breeders’ Array suitable for high throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivium)

Summary Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism‐based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high‐density Affymetrix Axiom® genotyping array (the Wheat Breeders’ Array), in a high‐throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders’ Array is also suitable for generating high‐density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site ‘CerealsDB’.

Rank-based algorithms for anlaysis of microarrays

Analysis of microarray data often involves extracting information from raw intensities of spots of cells and making certain calls. Rank-based algorithms are powerful tools to provide probability values of hypothesis tests, especially when the distribution of the intensities is unknown. For our current gene expression arrays, a gene is detected by a set of probe pairs consisting of perfect match and mismatch cells. The one-sided upper-tail Wilcoxons signed rank test is used in our algorithms for absolute calls (whether a gene is detected or not), as well as comparative calls (whether a gene is increasing or decreasing or no significant change in a sample compared with another sample). We also test the possibility to use only perfect match cells to make calls. This paper focuses on absolute calls. We have developed error analysis methods and software tools that allow us to compare the accuracy of the calls in the presence or absence of mismatch cells at different target concentrations. The usage of nonparametric rank-based tests is not limited to absolute and comparative calls of gene expression chips. They can also be applied to other oligonucleotide microarrays for genotyping and mutation detection, as well as spotted arrays.