STAMS: STRING-assisted module search for genome wide association studies and application to autism.

MOTIVATION: Analyzing genome wide association data in the context of biological pathways helps us understand how genetic variation influences phenotype and increases power to find associations. However, the utility of pathway-based analysis tools is hampered by undercuration and reliance on a distribution of signal across all of the genes in a pathway. Methods that combine genome wide association results with genetic networks to infer the key phenotype-modulating subnetworks combat these issues, but have primarily been limited to network definitions with yes/no labels for gene-gene interactions. A recent method (EW_dmGWAS) incorporates a biological network with weighted edge probability by requiring a secondary phenotype-specific expression dataset. In this article, we combine an algorithm for weighted-edge module searching and a probabilistic interaction network in order to develop a method, STAMS, for recovering modules of genes with strong associations to the phenotype and probable biologic coherence. Our method builds on EW_dmGWAS but does not require a secondary expression dataset and performs better in six test cases. RESULTS: We show that our algorithm improves over EW_dmGWAS and standard gene-based analysis by measuring precision and recall of each method on separately identified associations. In the Wellcome Trust Rheumatoid Arthritis study, STAMS-identified modules were more enriched for separately identified associations than EW_dmGWAS (STAMS P-value 3.0 × 10-4; EW_dmGWAS- P-value = 0.8). We demonstrate that the area under the Precision-Recall curve is 5.9 times higher with STAMS than EW_dmGWAS run on the Wellcome Trust Type 1 Diabetes data. AVAILABILITY AND IMPLEMENTATION: STAMS is implemented as an R package and is freely available at https://simtk.org/projects/stams CONTACT: rbaltman@stanford.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Genetic variant in folate homeostasis is associated with lower warfarin dose in African Americans.

The anticoagulant warfarin has >30 million prescriptions per year in the United States. Doses can vary 20-fold between patients, and incorrect dosing can result in serious adverse events. Variation in warfarin pharmacokinetic and pharmacodynamic genes, such as CYP2C9 and VKORC1, do not fully explain the dose variability in African Americans. To identify additional genetic contributors to warfarin dose, we exome sequenced 103 African Americans on stable doses of warfarin at extremes (≤ 35 and ≥ 49 mg/week). We found an association between lower warfarin dose and a population-specific regulatory variant, rs7856096 (P = 1.82 × 10(-8), minor allele frequency = 20.4%), in the folate homeostasis gene folylpolyglutamate synthase (FPGS). We replicated this association in an independent cohort of 372 African American subjects whose stable warfarin doses represented the full dosing spectrum (P = .046). In a combined cohort, adding rs7856096 to the International Warfarin Pharmacogenetic Consortium pharmacogenetic dosing algorithm resulted in a 5.8 mg/week (P = 3.93 × 10(-5)) decrease in warfarin dose for each allele carried. The variant overlaps functional elements and was associated (P = .01) with FPGS gene expression in lymphoblastoid cell lines derived from combined HapMap African populations (N = 326). Our results provide the first evidence linking genetic variation in folate homeostasis to warfarin response.

Genomes of replicatively senescent cells undergo global epigenetic changes leading to gene silencing and activation of transposable elements.

Replicative cellular senescence is an important tumor suppression mechanism and also contributes to aging. Progression of both cancer and aging include significant epigenetic components, but the chromatin changes that take place during cellular senescence are not known. We used formaldehyde assisted isolation of regulatory elements (FAIRE) to map genome-wide chromatin conformations. In contrast to growing cells, whose genomes are rich with features of both open and closed chromatin, FAIRE profiles of senescent cells are significantly smoothened. This is due to FAIRE signal loss in promoters and enhancers of active genes, and FAIRE signal gain in heterochromatic gene-poor regions. Chromatin of major retrotransposon classes, Alu, SVA and L1, becomes relatively more open in senescent cells, affecting most strongly the evolutionarily recent elements, and leads to an increase in their transcription and ultimately transposition. Constitutive heterochromatin in centromeric and peri-centromeric regions also becomes relatively more open, and the transcription of satellite sequences increases. The peripheral heterochromatic compartment (PHC) becomes less prominent, and centromere structure becomes notably enlarged. These epigenetic changes progress slowly after the onset of senescence, with some, such as mobilization of retrotransposable elements becoming prominent only at late times. Many of these changes have also been noted in cancer cells.

Personal omics profiling reveals dynamic molecular and medical phenotypes.

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

T0901317 inhibits cisplatin-induced apoptosis in ovarian cancer cells [corrected].

OBJECTIVE: To determine the function of T0901317 in combination treatment with cisplatin in ovarian cancer cells. METHODS: We screened the effects of 3 nuclear hormone receptor ligands on cell viability in a panel of ovarian cancer cell lines. T0901317 regulation of apoptosis and cell cycle regulators was determined when applied as a single agent or in combination with cisplatin. RESULTS: Surprisingly, the liver X receptor agonist T0901317 had no significant effects on a panel of 7 ovarian cancer cell lines as a single agent. T0901317 does, however, significantly decrease cisplatin efficacy in at least 3 ovarian cancer cell lines. T0901317 reduces cisplatin-induced apoptosis and reverses cisplatin-induced expression of cell cycle regulators. T0901317 seems to work in a liver X receptor-, pregnane X receptor-, and farnesoid X receptor-independent manner, as agonists of these nuclear hormone receptors did not show similar effects. Interestingly, in the A2780-cp drug-resistant cell line, the effect of T0901317 is lost, suggesting that the pathways stimulated by T0901317 to reduce cisplatin efficacy could be inherently active features of the selected resistance. CONCLUSIONS: Together, these data suggest that T0901317 inhibits cisplatin in some ovarian cancer cells. These data provide an avenue to investigate when T0901317 may be acting to promote tumor survival and drug resistance through control of apoptosis and when it may be acting as an antitumor agent as has been previously reported.

Integrated genomics of ovarian xenograft tumor progression and chemotherapy response.

BACKGROUND: Ovarian cancer is the most deadly gynecological cancer with a very poor prognosis. Xenograft mouse models have proven to be one very useful tool in testing candidate therapeutic agents and gene function in vivo. In this study we identify genes and gene networks important for the efficacy of a pre-clinical anti-tumor therapeutic, MT19c. METHODS: In order to understand how ovarian xenograft tumors may be growing and responding to anti-tumor therapeutics, we used genome-wide mRNA expression and DNA copy number measurements to identify key genes and pathways that may be critical for SKOV-3 xenograft tumor progression. We compared SKOV-3 xenografts treated with the ergocalciferol derived, MT19c, to untreated tumors collected at multiple time points. Cell viability assays were used to test the function of the PPARγ agonist, Rosiglitazone, on SKOV-3 cell growth. RESULTS: These data indicate that a number of known survival and growth pathways including Notch signaling and general apoptosis factors are differentially expressed in treated vs. untreated xenografts. As tumors grow, cell cycle and DNA replication genes show increased expression, consistent with faster growth. The steroid nuclear receptor, PPARγ, was significantly up-regulated in MT19c treated xenografts. Surprisingly, stimulation of PPARγ with Rosiglitazone reduced the efficacy of MT19c and cisplatin suggesting that PPARγ is regulating a survival pathway in SKOV-3 cells. To identify which genes may be important for tumor growth and treatment response, we observed that MT19c down-regulates some high copy number genes and stimulates expression of some low copy number genes suggesting that these genes are particularly important for SKOV-3 xenograft growth and survival. CONCLUSIONS: We have characterized the time dependent responses of ovarian xenograft tumors to the vitamin D analog, MT19c. Our results suggest that PPARγ promotes survival for some ovarian tumor cells. We propose that a combination of regulated expression and copy number can identify genes that are likely important for chemotherapy response. Our findings suggest a new approach to identify candidate genes that are critical for anti-tumor therapy.

Chromatin remodeling in the aging genome of Drosophila.

Chromatin structure affects the accessibility of DNA to transcription, repair, and replication. Changes in chromatin structure occur during development, but less is known about changes during aging. We examined the state of chromatin structure and its effect on gene expression during aging in Drosophila at the whole genome and cellular level using whole-genome tiling microarrays of activation and repressive chromatin marks, whole-genome transcriptional microarrays and single-cell immunohistochemistry. We found dramatic reorganization of chromosomal regions with age. Mapping of H3K9me3 and HP1 signals to fly chromosomes reveals in young flies the expected high enrichment in the pericentric regions, the 4th chromosome, and islands of facultative heterochromatin dispersed throughout the genome. With age, there is a striking reduction in this enrichment resulting in a nearly equivalent level of H3K9me3 and HP1 in the pericentric regions, the 4th chromosome, facultative heterochromatin, and euchromatin. These extensive changes in repressive chromatin marks are associated with alterations in age-related gene expression. Large-scale changes in repressive marks with age are further substantiated by single-cell immunohistochemistry that shows changes in nuclear distribution of H3K9me3 and HP1 marks with age. Such epigenetic changes are expected to directly or indirectly impinge upon important cellular functions such as gene expression, DNA repair, and DNA replication. The combination of genome-wide approaches such as whole-genome chromatin immunoprecipitation and transcriptional studies in conjunction with single-cell immunohistochemistry as shown here provide a first step toward defining how changes in chromatin may contribute to the process of aging in metazoans.

Estrogen coordinates translation and transcription, revealing a role for NRSF in human breast cancer cells.

Posttranscriptional regulation may enhance or inhibit estrogen transcriptional control to promote proliferation of breast cancer cells. To understand how transcriptome and translational responses coordinate to drive proliferation, we determined estrogen's global and specific effects on translation regulation by comparing the genome-wide profiles of total mRNA, polysome-associated mRNA, and monosome-associated mRNAs in MCF-7 cells after stimulation by 1 h of 10 nm 17beta-estradiol (E2). We observe three significant, novel findings. 1) E2 regulates several transcripts and pathways at the translation level. 2) We find that polysome analysis has higher sensitivity than total RNA in detecting E2-regulated transcripts as exemplified by observing stronger E2-induced enrichment of E2 expression signatures in polysomes more than in total RNA. This increased sensitivity allowed the identification of the repression of neural restrictive silencing factor targets in polysome-associated RNA but not total RNA. NRSF activity was required for E2 stimulation of the cell cycle. 3) We observe that the initial translation state is already high for E2 up-regulated transcripts before E2 treatment and vice versa for E2 down-regulated transcripts. This suggests that the translation state anticipates potential E2-induced transcriptome levels. Together, these data suggest that E2 stimulates breast cancer cells by regulating translation using multiple mechanisms. In sum, we show that polysome profiling of E2 regulation of breast cancer cells provides novel insights into hormone action and can identify novel factors critical for breast cancer cell growth.