Running title: Regulatory genomics of GWAS SNPsAbbreviations: GWAS -genome-wide association study; eQTL -expression quantitative trait loci; ASE -allele-specific expression; TF -transcription factor; LDlinkage disequilibrium; FPKM -fragments per kilobase of transcript per million mapped reads; LCASE -local chromosome allele-specific expression; DHS -DNase I hypersensitive sites; PWM -position weight matrix; TCGA -The Cancer Genome Atlas; ER+ -estrogen receptor positive; TAD -topologically associated domain; MAF -minor allele frequency; RPKM -reads per kilobase of transcript per million mapped reads; SNP -single nucleotide polymorphism; MAPQ -mapping quality;ChIP-seq -chromatin immunoprecipitation sequencing; ASB -allele-specific binding;ncRNA -non-coding RNA; TSS -transcription start site; DNase-seq -DNase I Major FindingsResearch. Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on January 19, 2018; DOI: 10.1158/0008-5472.CAN-17-3486 Cancer Research Mathematical Oncology 4We developed a computational framework for integrating GWAS results with heterogeneous cancer genomic data and tissue-specific epigenetic data to facilitate the discovery of causative variants functioning through long-distance gene regulation.Applied to a breast cancer susceptibility region in 5p12, our method provides strong support for a putative causative SNP that is predicted to modulate GATA3 binding and regulate the expression of MRPS30 and nearby lncRNAs. Quick Guide to Equations and AssumptionsSince the majority of GWAS variants lie in non-coding regions of the human genome where a direct link to gene function is not obvious, we searched for (causative SNP, TF, target gene) triplets under the model of gene regulation by enhancers, in which the SNP interferes with the binding affinity of a key transcription factor (TF). With this assumption, we built a regulation model for a breast cancer susceptibility locus harboring three GWAS SNPs in the 5p12 region. To infer candidate target genes, we first performed expression quantitative trait loci (eQTL) analysis by regressing gene expression levels against two co-variates: genotype status at a given GWAS SNP and copy number of the gene. For each pair of ∈ {GWAS SNPs in 5p12} and ∈ {genes in 5p12 TAD}, the eQTL model can be expressed as: DOI: 10.1158/0008-5472.CAN-17-3486 Cancer Research Mathematical Oncology 5 hypothesis testing was further applied using ≤ , where is the total number of genes tested in the TAD ( = 22, thus = 0.0023).Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on JanuaryTo identify cis-regulated target genes, we tested local chromosome allele-specific expression (LCASE) using exonic SNPs that were properly phased with the GWAS SNP . For each exonic SNP , we obtained a subset of patients who had heterozygous genotypes at both the GWAS SNP and the exonic SNP . For each patient ( ∈ {1, ...

The influence of randomness on wave propagation in one-dimensional chains of spherical granular media is investigated. The interaction between the elastic spheres is modeled using the classical Hertzian contact law. Randomness is introduced in the discrete model using random distributions of particle mass, Young's modulus, or radius. Of particular interest in this study is the quantification of the attenuation in the amplitude of the impulse associated with various levels of randomness: two distinct regimes of decay are observed, characterized by an exponential or a power law, respectively. The responses are normalized to represent a vast array of material parameters and impact conditions. The virial theorem is applied to investigate the transfer from potential to kinetic energy components in the system for different levels of randomness. The level of attenuation in the two decay regimes is compared for the three different sources of randomness and it is found that randomness in radius leads to the maximum rate of decay in the exponential regime of wave propagation.

Genome-wide association studies (GWAS) have hitherto identified several germline variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of noncoding GWAS SNPs using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast-cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor-infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3’ end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant could regulate a gene not only in the cell of cancer origin but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.

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Background Large-scale genome-wide association studies (GWAS) have implicated thousands of germline genetic variants in modulating individuals’ risk to various diseases, including cancer. At least 25 risk loci have been identified for low-grade gliomas (LGGs), but their molecular functions remain largely unknown. Methods We hypothesized that GWAS loci contain causal single nucleotide polymorphisms (SNPs) that reside in accessible open chromatin regions and modulate the expression of target genes by perturbing the binding affinity of transcription factors (TFs). We performed an integrative analysis of genomic and epigenomic data from The Cancer Genome Atlas and other public repositories to identify candidate causal SNPs within linkage disequilibrium blocks of LGG GWAS loci. We assessed their potential regulatory role via in-silico TF binding sequence perturbations, convolutional neural network trained on TF binding data, and simulated-annealing-based interpretation methods. Results We built an interactive website (http://education.knoweng.org/alg3/) summarizing the functional footprinting of 280 variants in 25 LGG GWAS regions, providing rich information for further computational and experimental scrutiny. As case studies, we identified PHLDB1 and SLC25A26 as candidate target genes of rs12803321 and rs11706832, respectively, and also predicted the GWAS variant rs648044 to be the causal SNP modulating ZBTB16, a known tumor suppressor in multiple cancers. We showed that rs648044 likely perturbed the binding affinity of the TF MAFF, as supported by RNA interference and in-vitro MAFF binding experiments. Conclusions The identified candidate (causal SNP, target gene, TF) triplets and the accompanying resource will help accelerate our understanding of the molecular mechanisms underlying genetic risk factors for gliomas.