Illumina Infinium Array Research Articles

PATH-45. INTRAEPIGLIOM - RAPID SEQUENCING-BASED DIAGNOSIS OF BRAIN TUMORS

Abstract The intraoperative diagnosis of brain tumors remains a clinical challenge despite recent technological advances. The current clinical practice differentiates non-surgical brain tumors from those preferably treated with cytoreductive surgery employing intraoperative frozen section diagnostics. A detailed molecular diagnosis required for this classification task within the timeframe of a routine neurosurgical procedure is currently unavailable. We have analyzed a clinical cohort of several brain tumor entities using Nanopore long-read sequencing on two Oxford Nanopore Technologies sequencing platforms (MinION, PromethION). Since currently available molecular cancer classifiers such as the DKFZ methylation profiling classifier cannot be readily adapted to real-time sequencing analysis, we implemented a novel algorithm (MethyLYZR) to predict the underlying cancer type. Publicly available Illumina Infinium array data were used to train the classifier to distinguish 91 brain tumor classes. For validation of classification accuracy, we conducted a comprehensive validation strategy. Both nanopore platforms could sequence more than 5,000 pre-selected CpG within less than 20 minutes for most of our samples. When combining an optimized library preparation protocol with the time used for sequencing the minimal number of CpGs needed for classification, we saw sample-to-answer times of less than 1 hour – in many cases within 45 minutes - from receiving a fresh biopsy to a robust cancer type prediction. Comparing actual and predicted diagnoses resulted in a favorable error rate, indicating potentially highly clinical validity. Our real-time based molecular diagnostic algorithm enables, in most cases, a reliable diagnostic call within the timeframe of a typical neuro-oncological surgery. MethyLYZR as a predictive tool may allow us to adjust the surgical strategy and deliver the prognosis to our patients right after surgery, thus allowing for as-of-yet unexplored opportunities for the intraoperative application of individualized therapeutic modalities.

Aclust2.0: a revamped unsupervised R tool for Infinium methylation beadchips data analyses.

A wide range of computational packages has been developed for regional DNA methylation analyses of Illumina's Infinium array data. Aclust, one of the first unsupervised algorithms, was originally designed to analyze regional methylation of Infinium's 27K and 450K arrays by clustering neighboring methylation sites prior to downstream analyses. However, Aclust relied on outdated packages that rendered it largely non-operational especially with the newer Infinium EPIC and mouse arrays. We have created Aclust2.0, a streamlined pipeline that involves five steps for the analyses of human (450K and EPIC) and mouse array data. Aclust2.0 provides a user-friendly pipeline and versatile for regional DNA methylation analyses for molecular epidemiological and mouse studies. Aclust2.0 is freely available on Github (https://github.com/OluwayioseOA/Alcust2.0.git).

Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations.

Genome-wide association studies (GWAS) in crops requires genotyping platforms that are capable of producing accurate high density genotyping data on hundreds of plants in a cost-effective manner. Currently there are multiple commercial platforms available that are being effectively used across crops. These platforms include genotyping arrays such as the Illumina Infinium arrays and the Applied Biosystems Axiom Arrays along with a variety of resequencing methods. These methods are being used to genotype tens of thousands of markers up to millions of markers on GWAS panels. They are being used on crops with simple genomes to crops with very complex, large, polyploid genomes. Depending on the crop and the goal of the GWAS, there are several options and practical considerations to take into account when selecting a genotyping technology to ensure that the right coverage, accuracy, and cost for the study is achieved.

Genetic mapping of host resistance to the Pyrenophora teres f. maculata isolate 13IM8.3.

Spot form net blotch (SFNB), caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata (Ptm), is a foliar disease of barley that results in significant yield losses in major growing regions worldwide. Understanding the host-parasite interactions between pathogen virulence/avirulence genes and the corresponding host susceptibility/resistance genes is important for the deployment of genetic resistance against SFNB. Two recombinant inbred mapping populations were developed to characterize genetic resistance/susceptibility to the Ptm isolate 13IM8.3, which was collected from Idaho (ID). An Illumina Infinium array was used to produce a genome-wide marker set. Quantitative trait loci (QTL) analysis identified ten significant resistance/susceptibility loci, with two of the QTL being common to both populations. One of the QTL on 5H appears to be novel, while the remaining loci have been reported previously. Single nucleotide polymorphisms (SNPs) closely linked to or delimiting the significant QTL have been converted to user-friendly markers. Loci and associated molecular markers identified in this study will be useful in genetic mapping and deployment of the genetic resistance to SFNB in barley.

The Rlm13 Gene, a New Player of Brassica napus-Leptosphaeria maculans Interaction Maps on Chromosome C03 in Canola.

Canola exhibits an extensive genetic variation for resistance to blackleg disease, caused by the fungal pathogen Leptosphaeria maculans. Despite the identification of several Avr effectors and R (race-specific) genes, specific interactions between Avr-R genes are not yet fully understood in the Brassica napus–L. maculans pathosystem. In this study, we investigated the genetic basis of resistance in an F2:3 population derived from Australian canola varieties CB-Telfer (Rlm4)/ATR-Cobbler (Rlm4) using a single-spore isolate of L. maculans, PHW1223. A genetic linkage map of the CB-Telfer/ATR-Cobbler population was constructed using 7,932 genotyping-by-sequencing-based DArTseq markers and subsequently utilized for linkage and haplotype analyses. Genetic linkage between DArTseq markers and resistance to PHW1223 isolate was also validated using the B. napus 60K Illumina Infinium array. Our results revealed that a major locus for resistance, designated as Rlm13, maps on chromosome C03. To date, no R gene for resistance to blackleg has been reported on the C subgenome in B. napus. Twenty-four candidate R genes were predicted to reside within the quantitative trait locus (QTL) region. We further resequenced both the parental lines of the mapping population (CB-Telfer and ATR-Cobbler, > 80 × coverage) and identified several structural sequence variants in the form of single-nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and presence/absence variations (PAVs) near Rlm13. Comparative mapping revealed that Rlm13 is located within the homoeologous A03/C03 region in ancestral karyotype block “R” of Brassicaceae. Our results provide a “target” for further understanding the Avr–Rlm13 gene interaction as well as a valuable tool for increasing resistance to blackleg in canola germplasm.

Meta-Analysis of Genome-Wide Association Studies of Acute Myeloid Leukemia (AML) Patients Identifies Variants Associated with Risk of 11q23/KMT2A-Translocated and Core-Binding Factor (CBF) AML and Suggests a Role for Transcription Elongation in Leukemogenesis

Meta-Analysis of Genome-Wide Association Studies of Acute Myeloid Leukemia (AML) Patients Identifies Variants Associated with Risk of 11q23/KMT2A-Translocated and Core-Binding Factor (CBF) AML and Suggests a Role for Transcription Elongation in Leukemogenesis

Abstract A31: Genome-wide association study (GWAS) of host DNA sequence variation and the gut microbiome in the Multiethnic Cohort

Abstract Patterns of microbiome diversity vary across human populations, and although variation is largely driven by diet and lifestyle, genetically encoded differences between hosts may be important in shaping the microbiome and health outcomes, including cancer. We report preliminary results from a GWAS of the gut microbiome in 6,217 individuals from the Multiethnic Cohort Study, including African Americans, Japanese Americans, Native Hawaiians, Latinos, and Whites. Genome-wide SNP data was based on existing data from a variety of Illumina Infinium arrays (500,000 to 2.5 million single nucleotide polymorphisms (SNPs); n=4,363) as well as genotyping 1,853 individuals using the Illumina MEGA EX array. SNP imputation was conducted using a cosmopolitan reference panel of all 1000 Genomes samples. The stool microbiome was assessed by paired-end sequencing (Illumina MiSeq) of the16S rRNA gene (V1-3). SNP-genera association tests were conducted using linear regression of covariate-adjusted bacterial genera abundance quintiles on SNP genotype. The chi-square statistics were adjusted by the genomic inflation factor. A threshold of p=5 × 10−8 was used to determine genome-wide statistical significance. The covariate-adjusted genera values were computed as the residuals of a logistic ordinal regression of genera abundance quintiles on variables expected to affect the microbiome (i.e., age, sex, genetic ancestry proportions, sample month, and sequencing batch). Initial results yielded 22 genome-wide significant associations across SNPs in 15 different human chromosomes and 11 bacterial genera. Notably, Fusobacteria was significantly associated with star-related lipid transfer domain (STARD3, chromosome 13q13; p=2.8 × 10−8), voltage-dependent calcium channel gamma 3 subunit (CACNG3, chromosome 16p12; p=3.1 × 10−8), organic anion transporter polypeptide (OATP, SCLO2B1, chromosome 11q13; p=2.8 × 10−8), and E-cadherin (CDHR3, chromosome 7q22, p=1.6 × 10−8). Some Fusobacterial species have been associated with increased risk of colon tumors. Coprobacillus was significantly associated with ubiquitin modifier activating enzyme 2 (UBA2, chromosome 19q13, p=4.1 × 10−9). The pathogen Slackia was significantly associated with variants in the zinc finger 850 gene (ZNF850, chromosome 19p13; p=4.3 × 10−8). These results suggest that host gene variants may be important in shaping the microbiome and may influence bacterial pathogen-associated cancer outcomes. Citation Format: Meredith A. Hullar, Johanna W. Lampe, Timothy Randolph, Keith R. Curtis, Unhee Lim, Lynne R. Wilkens, Loic Le Marchand, Bruce S. Kristal, Kris R. Monroe, Kechen Zhao, Daniel Stram, Iona Cheng. Genome-wide association study (GWAS) of host DNA sequence variation and the gut microbiome in the Multiethnic Cohort [abstract]. In: Proceedings of the AACR Special Conference on the Microbiome, Viruses, and Cancer; 2020 Feb 21-24; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2020;80(8 Suppl):Abstract nr A31.

Changes of DNA methylation are associated with changes in lung function during adolescence

BackgroundAdolescence is a significant period for the gender-dependent development of lung function. Prior studies have shown that DNA methylation (DNA-M) is associated with lung function and DNA-M at some cytosine-phosphate-guanine dinucleotide sites (CpGs) changes over time. This study examined whether changes of DNA-M at lung-function-related CpGs are associated with changes in lung function during adolescence for each gender, and if so, the biological significance of the detected CpGs.MethodsGenome-scale DNA-M was measured in peripheral blood samples at ages 10 (n = 330) and 18 years (n = 476) from the Isle of Wight (IOW) birth cohort in United Kingdom, using Illumina Infinium arrays (450 K and EPIC). Spirometry was conducted at both ages. A training and testing method was used to screen 402,714 CpGs for their potential associations with lung function. Linear regressions were applied to assess the association of changes in lung function with changes of DNA-M at those CpGs potentially related to lung function. Adolescence-related and personal and family-related confounders were included in the model. The analyses were stratified by gender. Multiple testing was adjusted by controlling false discovery rate of 0.05. Findings were further examined in two independent birth cohorts, the Avon Longitudinal Study of Children and Parents (ALSPAC) and the Children, Allergy, Milieu, Stockholm, Epidemiology (BAMSE) cohort. Pathway analyses were performed on genes to which the identified CpGs were mapped.ResultsFor females, 42 CpGs showed statistically significant associations with change in FEV1/FVC, but none for change in FEV1 or FVC. No CpGs were identified for males. In replication analyses, 16 and 21 of the 42 CpGs showed the same direction of associations among the females in the ALSPAC and BAMSE cohorts, respectively, with 11 CpGs overlapping across all the three cohorts. Through pathway analyses, significant biological processes were identified that have previously been related to lung function development.ConclusionsThe detected 11 CpGs in all three cohorts have the potential to serve as the candidate epigenetic markers for changes in lung function during adolescence in females.

Changes in DNA methylation from pre- to post-adolescence are associated with pubertal exposures

BackgroundAdolescence is a period characterized by major biological development, which may be associated with changes in DNA methylation (DNA-M). However, it is unknown to what extent DNA-M varies from pre- to post-adolescence, whether the pattern of changes is different between females and males, and how adolescence-related factors are associated with changes in DNA-M.MethodsGenome-scale DNA-M at ages 10 and 18 years in whole blood of 325 subjects (n = 140 females) in the Isle of Wight (IOW) birth cohort was analyzed using Illumina Infinium arrays (450K and EPIC). Linear mixed models were used to examine DNA-M changes between pre- and post-adolescence and whether the changes were gender-specific. Adolescence-related factors and environmental exposure factors were assessed on their association with DNA-M changes. Replication of findings was attempted in the comparable Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.ResultsIn the IOW cohort, after controlling for technical variation and cell compositions at both pre- and post-adolescence, 15,532 cytosine–phosphate–guanine (CpG) sites (of 400,825 CpGs, 3.88%) showed statistically significant DNA-M changes from pre-adolescence to post-adolescence invariant to gender (false discovery rate (FDR) = 0.05). Of these 15,532 CpGs, 10,212 CpGs (66%) were replicated in the ALSPAC cohort. Pathway analysis using Ingenuity Pathway Analysis (IPA) identified significant biological pathways related to growth and development of the reproductive system, emphasizing the importance of this period of transition on epigenetic state of genes. In addition, in IOW, we identified 1179 CpGs with gender-specific DNA-M changes. In the IOW cohort, body mass index (BMI) at age 10 years, age of growth spurt, nonsteroidal drugs use, and current smoking status showed statistically significant associations with DNA-M changes at 15 CpGs on 14 genes such as the AHRR gene. For BMI at age 10 years, the association was gender-specific. Findings on current smoking status were replicated in the ALSPAC cohort.ConclusionAdolescent transition is associated with changes in DNA-M at more than 15K CpGs. Identified pathways emphasize the importance of this period of transition on epigenetic state of genes relevant to cell growth and immune system development.

Genome mapping and molecular markers identification for yield, yield component and fibre quality traits in tetraploid cotton

AbstractThe identification of quantitative trait loci (QTL) across different environments is a prerequisite for marker‐assisted selection (MAS) in crop improvement programmes. CottonSNP63k Illumina infinium array was used for genotyping 178 inter‐specific recombinant inbred lines and the parents, and identified 1,667 homozygous polymorphic markers between the parents. Of these, 1,430 markers were used for the construction of linkage map after removing 237 redundant markers. The genetic map spans a total genetic length of 3,149.8 cM with an average marker interval size of 2.2 cM. The phenotypic data from five environments were analysed separately using inclusive composite interval mapping which identified a total of 56 QTL explaining phenotypic variances (PVE) in the range of 8.18%–28.91%. There were 11 and 24 major QTL found for fibre quality and yield components, respectively. A total of 64 QTL were identified through Multi‐Environment Trials analysis, of which 34 recorded QTL × Environment interactions.

Molecular and comparative mapping for heading date and plant height in oat

Selection of oat genotypes combining earliness and short plant height could stimulate oat cultivation worldwide. However, the mechanisms involved with the genetic control of heading date and plant height traits are not fully understood to date. This study aimed to identify genomic regions controlling heading date and plant height in two hulled by naked oat populations and to compare these genomic regions with that of other grass species. Recombinant inbred lines of each population and their parents were genotyped by a 6 K BeadChip Illumina Infinium array and assessed for heading date and plant height in two sowing dates. The quantitative trait loci (QTL) affecting these traits were detected by simple interval mapping. The two oat populations showed different genetic mechanisms controlling heading date. A major QTL was identified in one of the populations, mapped into the ‘Mrg33’ consensus linkage group from the current oat map. Two other QTL were detected into the ‘Mrg02’ and ‘Mrg24’ groups, in the second population. On the other hand, both populations presented the same genomic region controlling plant height. Six SNP markers, mapping on the same linkage group within each population, were associated with the trait, regardless the sowing date, explaining more than 20% of the phenotypic variation. Five of these six markers were mapped into three different linkage groups on the oat consensus map. Genomic regions associated with heading date and plant height in oat seem to be conserved in Oryza sativa L. and Brachypodium distachyon. Our results provide valuable information for marker-assisted selection in oats, allowing selection for earliness and plant height on early segregating generations.

Parkinson\u2019s disease is associated with DNA methylation levels in human blood and saliva

BackgroundSeveral articles suggest that DNA methylation levels in blood relate to Parkinson’s disease (PD) but there is a need for a large-scale study that involves suitable population based controls. The purposes of the study were: (1) to study whether PD status is associated with DNA methylation levels in blood/saliva; (2) to study whether observed associations relate to blood cell types; and (3) to characterize genome-wide significant markers (“CpGs”) and clusters of CpGs (co-methylation modules) in terms of biological pathways.MethodsIn a population-based case control study of PD, we studied blood samples from 335 PD cases and 237 controls and saliva samples from another 128 cases and 131 controls. DNA methylation data were generated from over 486,000 CpGs using the Illumina Infinium array. We identified modules of CpGs (clusters) using weighted correlation network analysis (WGCNA).ResultsOur cross-sectional analysis of blood identified 82 genome-wide significant CpGs (including cg02489202 in LARS2 p = 8.3 × 10–11 and cg04772575 in ABCB9 p = 4.3 × 10–10). Three out of six PD related co-methylation modules in blood were significantly enriched with immune system related genes. Our analysis of saliva identified five significant CpGs. PD-related CpGs are located near genes that relate to mitochondrial function, neuronal projection, cytoskeleton organization, systemic immune response, and iron handling.ConclusionsThis study demonstrates that: (1) PD status has a profound association with DNA methylation levels in blood and saliva; and (2) the most significant PD-related changes reflect changes in blood cell composition. Overall, this study highlights the role of the immune system in PD etiology but future research will need to address the causal structure of these relationships.

Effects of DNA Methylation on Progression to Interstitial Fibrosis and Tubular Atrophy in Renal Allograft Biopsies: A Multi-Omics Approach.

Progressive fibrosis of the interstitium is the dominant final pathway in renal destruction in native and transplanted kidneys. Over time, the continuum of molecular events following immunological and nonimmunological insults lead to interstitial fibrosis and tubular atrophy and culminate in kidney failure. We hypothesize that these insults trigger changes in DNA methylation (DNAm) patterns, which in turn could exacerbate injury and slow down the regeneration processes, leading to fibrosis development and graft dysfunction. Herein, we analyzed biopsy samples from kidney allografts collected 24 months posttransplantation and used an integrative multi-omics approach to understand the underlying molecular mechanisms. The role of DNAm and microRNAs on the graft gene expression was evaluated. Enrichment analyses of differentially methylated CpG sites were performed using GenomeRunner. CpGs were strongly enriched in regions that were variably methylated among tissues, implying high tissue specificity in their regulatory impact. Corresponding to this methylation pattern, gene expression data were related to immune response (activated state) and nephrogenesis (inhibited state). Preimplantation biopsies showed similar DNAm patterns to normal allograft biopsies at 2 years posttransplantation. Our findings demonstrate for the first time a relationship among epigenetic modifications and development of interstitial fibrosis, graft function, and inter-individual variation on long-term outcomes.

Genome- and CD4+ T-cell methylome-wide association study of circulating trimethylamine-N-oxide in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)

BackgroundTrimethylamine-N-oxide (TMAO), an atherogenic metabolite species, has emerged as a possible new risk factor for cardiovascular disease. Animal studies have shown that circulating TMAO levels are regulated by genetic and environmental factors. However, large-scale human studies have failed to replicate the observed genetic associations, and epigenetic factors such as DNA methylation have never been examined in relation to TMAO levels. Methods and resultsWe used data from the family-based Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) to investigate the heritable determinants of plasma TMAO in humans. TMAO was not associated with other plasma markers of cardiovascular disease, e.g. lipids or inflammatory cytokines. We first estimated TMAO heritability at 27%, indicating a moderate genetic influence. We used 1000 Genomes imputed data (n = 626) to estimate genome-wide associations with TMAO levels, adjusting for age, sex, family relationships, and study site. The genome-wide study yielded one significant hit at the genome-wide level, located in an intergenic region on chromosome 4. We subsequently quantified epigenome-wide DNA methylation using the Illumina Infinium array on CD4+ T-cells. We tested for association of methylation loci with circulating TMAO (n = 847), adjusting for age, sex, family relationships, and study site as the genome-wide study plus principal components capturing CD4+ T-cell purity. Upon adjusting for multiple testing, none of the epigenetic findings were statistically significant. ConclusionsOur findings contribute to the growing body of evidence suggesting that neither genetic nor epigenetic factors play a critical role in establishing circulating TMAO levels in humans.

Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk.

We have developed a genome-wide association study analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g., SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from well-established statistical tools such as bootstrapping, penalized regression, and decision trees. Unlike marginal regression, which considers each SNP individually, the key idea behind DEPTH is to rank groups of SNPs in terms of their joint strength of association with the outcome. Our aim was to compare the performance of DEPTH with that of standard logistic regression analysis. We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array. From the DEPTH analysis, we identified 14 regions associated with prostate cancer risk that had been reported previously, five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions. DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs. This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation. Cancer Epidemiol Biomarkers Prev; 25(12); 1619-24. ©2016 AACR.

Abstract 2030: The role of genetic variation in calcium-activated potassium channels in breast cancer patients treated with tamoxifen

Abstract Potassium channels control membrane voltage and are essential for cell proliferation. Abnormal regulation and/or expression of these channels have been reported in cancer and result in dysregulated cell cycle progression, cell proliferation and migration. In breast cancer, clinical correlations of potassium channels have been associated with brain metastases, high stage, high grade, high proliferation, nodal status and poor prognosis. Interestingly, they have been associated with increased estrogen receptor (ER) expression. The selective ER modulator, tamoxifen, blocks estrogen from binding to the ER and is commonly used to treat patients with ER-positive breast cancer. However, up to 33% of patients treated with tamoxifen relapse or dies at 15 years of follow up. Both estrogen and tamoxifen have been demonstrated to activate potassium channels which then cause an increase in cell proliferation. In preliminary animal in vivo studies, we observed a better breast cancer prognosis in those with a knockout in potassium channel genes. Therefore, any alterations in the potassium channels may help to explain why patients treated with tamoxifen fail therapy. We hypothesized that genetic variation in potassium channels may affect breast cancer risk as well as tamoxifen treatment outcome. Genotyping was conducted on 45,290 breast cancer patients and 41,880 controls of European ancestry from 41 studies with the custom Illumina Infinium array (iCOGS). More than 200,000 SNPs were genotyped with over 11 million SNPs estimated using genotype imputation with SHAPEIT and IMPUTEv2 and the 1000 Genomes Project March 2012 release as the reference panel (Michailidou et al. Nature Genetics 2015). Variants from 13 potassium channels including KCNMA1, KCNMB1-4, KCNN1-4, LRRC26, LRRC38, LRRC52 and LRRC55 were analyzed. Of these, 3 imputed SNPs from KCNN4 have shown decreased breast cancer risk with GWAS significance (rs12463319, rs12609846, rs1685191; OR 0.94, P < 1.0E-08). In particular, these SNPs were significant in ER-positive breast cancer (OR 0.93, P < 1.0E-09), but was not observed in ER-negative patients (P > 0.05). These findings encouraged us to now further investigate the outcomes of patients with ER-positive breast cancer treated with tamoxifen. Survival data for 49,751 patients with a median follow-up of 8 years has been completed and released in November 2015. Of these, 32,571 were ER-positive and 10,383 have been treated with tamoxifen. Current efforts are underway in order to determine the effects of genetic variations in potassium channels on the survival of patients treated with tamoxifen. Our work will provide a better understanding of the potential clinical relevance of potassium channels in tamoxifen treatment in breast cancer. Citation Format: Wing-Yee Lo, Corinna Mohr, Friederike Steudel, Marjanka Schmidt, Douglas Easton, Reiner Hoppe, Werner Schroth, Peter Ruth, Robert Lukowski, Hiltrud Brauch, in collaboration with the Breast Cancer Association Consortium. The role of genetic variation in calcium-activated potassium channels in breast cancer patients treated with tamoxifen. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2030.

Novel epigenetic changes in CDKN2A are associated with progression of cervical intraepithelial neoplasia

ObjectiveTo conduct a comprehensive mapping of the genomic DNA methylation in CDKN2A, which codes for the p16INK4A and p14ARF proteins, and 14 of the most promising DNA methylation marker candidates previously reported to be associated with progression of low-grade cervical intraepithelial neoplasia (CIN1) to cervical cancer. MethodsWe analyzed DNA methylation in 68 HIV-seropositive and negative women with incident CIN1, CIN2, CIN3 and invasive cervical cancer, assaying 120 CpG dinucleotide sites spanning APC, CDH1, CDH13, CDKN2A, CDKN2B, DAPK1, FHIT, GSTP1, HIC1, MGMT, MLH1, RARB, RASSF1, TERT and TIMP3 using the Illumina Infinium array. Validation was performed using high resolution mapping of the target genes with HELP-tagging for 286 CpGs, followed by fine mapping of candidate genes with targeted bisulfite sequencing. We assessed for statistical differences in DNA methylation levels for each CpG loci assayed using univariate and multivariate methods correcting for multiple comparisons. ResultsIn our discovery sample set, we identified dose dependent differences in DNA methylation with grade of disease in CDKN2A, APC, MGMT, MLH1 and HIC1, whereas single CpG locus differences between CIN2/3 and cancer groups were seen for CDH13, DAPK1 and TERT. Only those CpGs in the gene body of CDKN2A showed a monotonic increase in methylation between persistent CIN1, CIN2, CIN3 and cancers. ConclusionOur data suggests a novel link between early cervical disease progression and DNA methylation in a region downstream of the CDKN2A transcription start site that may lead to increased p16INK4A/p14ARF expression prior to development of malignant disease.

A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of single-locus markers in the allotetraploid genome.

Key messageTheBrassica napusIllumina array provides genome-wide markers linked to the available genome sequence, a significant tool for genetic analyses of the allotetraploidB. napusand its progenitor diploid genomes.A high-density single nucleotide polymorphism (SNP) Illumina Infinium array, containing 52,157 markers, was developed for the allotetraploid Brassica napus. A stringent selection process employing the short probe sequence for each SNP assay was used to limit the majority of the selected markers to those represented a minimum number of times across the highly replicated genome. As a result approximately 60 % of the SNP assays display genome-specificity, resolving as three clearly separated clusters (AA, AB, and BB) when tested with a diverse range of B. napus material. This genome specificity was supported by the analysis of the diploid ancestors of B. napus, whereby 26,504 and 29,720 markers were scorable in B. oleracea and B. rapa, respectively. Forty-four percent of the assayed loci on the array were genetically mapped in a single doubled-haploid B. napus population allowing alignment of their physical and genetic coordinates. Although strong conservation of the two positions was shown, at least 3 % of the loci were genetically mapped to a homoeologous position compared to their presumed physical position in the respective genome, underlying the importance of genetic corroboration of locus identity. In addition, the alignments identified multiple rearrangements between the diploid and tetraploid Brassica genomes. Although mostly attributed to genome assembly errors, some are likely evidence of rearrangements that occurred since the hybridisation of the progenitor genomes in the B. napus nucleus. Based on estimates for linkage disequilibrium decay, the array is a valuable tool for genetic fine mapping and genome-wide association studies in B. napus and its progenitor genomes.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-016-2746-7) contains supplementary material, which is available to authorized users.

ASSIsT: an automatic SNP scoring tool for in- and outbreeding species.

ASSIsT (Automatic SNP ScorIng Tool) is a user-friendly customized pipeline for efficient calling and filtering of SNPs from Illumina Infinium arrays, specifically devised for custom genotyping arrays. Illumina has developed an integrated software for SNP data visualization and inspection called GenomeStudio® (GS). ASSIsT builds on GS-derived data and identifies those markers that follow a bi-allelic genetic model and show reliable genotype calls. Moreover, ASSIsT re-edits SNP calls with null alleles or additional SNPs in the probe annealing site. ASSIsT can be employed in the analysis of different population types such as full-sib families and mating schemes used in the plant kingdom (backcross, F1, F2), and unrelated individuals. The final result can be directly exported in the format required by the most common software for genetic mapping and marker–trait association analysis. ASSIsT is developed in Python and runs in Windows and Linux.Availability and implementation: The software, example data sets and tutorials are freely available at http://compbiotoolbox.fmach.it/assist/.Contact: eric.vandeweg@wur.nl

Abstract 5483: CYP19A1 genetic variation is a potential predictor of outcome in ER-positive postmenopausal early breast cancer patients treated with tamoxifen

Abstract Tamoxifen is a selective estrogen receptor modulator which blocks estrogen from binding to the estrogen receptor (ER). Although estrogens are natural hormones vital for development, they are also critical growth factors responsible for cell proliferation and DNA synthesis, thus enhancing the growth of estrogen-responsive breast tumors. With breast cancer being the most frequent cancer in women, the carcinogenic effects of estrogen are mediated by ER which is expressed in approximately 75% of all tumors. Hence tamoxifen is commonly used to treat patients with ER-positive breast cancer. Our group has a long standing interest in the investigation of potential tamoxifen outcome predictors as up to 33% of treated patients relapse or dies at 15 years of follow up. Therefore it is crucial to determine which patient will benefit from tamoxifen or not. In a pilot study of 915 patients, we previously identified a single nucleotide polymorphism (SNP) at the aromatase gene (CYP19A1) which could potentially predict the outcome of postmenopausal patients treated with tamoxifen. Aromatase is a key enzyme in the estrogen biosynthesis pathway and in postmenopausal women, estrogen levels are low with the aromatase being responsible for estrogen synthesis from adipose tissue following the cessation of ovarian function. Therefore any alterations in aromatase function may affect the inhibitory capacity of tamoxifen for estrogen at the ER, resulting in variation of outcome in patients treated with tamoxifen. We hypothesized that genetic variation in CYP19A1 may influence aromatase expression and function, thus affecting the outcome of ER-positive postmenopausal early breast cancer patients treated with tamoxifen. Genotyping was conducted on 55,540 breast cancer patients from 50 studies with the custom Illumina Infinium array (iCOGS) by the Breast Cancer Association Consortium. More than 200,000 SNPs were genotyped of which 89 SNPs are located in the CYP19A1 genomic region. We included patients that are female with European ancestry, available follow up and vital status, invasive breast tumor, ascertained for their first tumor, stage I-III disease, postmenopausal, ER-positive, right truncation at 15 years of follow up, left censoring for study entry and those treated with tamoxifen. Furthermore, studies with less than 10 events for relapse or death were excluded leaving a total of 1313 patients for outcome analyses with distant metastasis-free survival as the endpoint. We identified rs7172156 being associated with poor outcome of which carriers of the minor A allele had a higher risk of distant metastasis or death (P = 0.007). Multivariate Cox regression stratified by study and adjusted for age, node status, tumor size and grade confirmed this observation (HR = 1.30, 95% CI 1.00-1.68, P = 0.049). Our data suggest that rs7172156 could be clinically relevant as a tamoxifen outcome predictor in early breast cancer. Citation Format: Wing-Yee Lo, Werner Schroth, Reiner Hoppe, Marjanka Schmidt, Montserrat Garcia-Closas, Paul Pharaoh, Per Hall, Douglas Easton, Peter Fasching, Hiltrud Brauch, in collaboration with the Breast Cancer Association Consortium. CYP19A1 genetic variation is a potential predictor of outcome in ER-positive postmenopausal early breast cancer patients treated with tamoxifen. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5483. doi:10.1158/1538-7445.AM2015-5483