SNPpy - Database Management for SNP Data from Genome Wide Association Studies

Background: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS). This system makes it possible to merge study data with HapMap data and merge across studies for meta-analyses, including data filtering based on the values of phenotype and Single-Nucleotide Polymorphism (SNP) data. SNPpy and its dependencies are open source software. Results: The current version of SNPpy offers utility functions to import genotype and annotation data from two commercial platforms. We use these to import data from two GWAS studies and the HapMap Project. We then export these individual datasets to standard data format files that can be imported into statistical software for downstream analyses. Conclusions: By leveraging the power of relational databases, SNPpy offers integrated management and manipulation of genotype and phenotype data from GWAS studies. The analysis of these studies requires merging across GWAS datasets as well as patient and marker selection. To this end, SNPpy enables the user to filter the data and output the results as standardized GWAS file formats. It does low level and flexible data validation, including validation of patient data. SNPpy is

Robust test method for time-course microarray experiments

<p>Abstract</p> <p>Background</p> <p>In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many of these experiments, the scientific aim is the identification of genes for which the trajectories depend on an experimental or phenotypic factor. There is an extensive recent body of literature on statistical methodology for addressing this analytical problem. Most of the existing methods are based on estimating the time-course trajectories using parametric or non-parametric mean regression methods. The sensitivity of these regression methods to outliers, an issue that is well documented in the statistical literature, should be of concern when analyzing microarray data.</p> <p>Results</p> <p>In this paper, we propose a robust testing method for identifying genes whose expression time profiles depend on a factor. Furthermore, we propose a multiple testing procedure to adjust for multiplicity.</p> <p>Conclusions</p> <p>Through an extensive simulation study, we will illustrate the performance of our method. Finally, we will report the results from applying our method to a case study and discussing potential extensions.</p

Thin minimal rim width at Bruch’s membrane opening is associated with glaucomatous paracentral visual field loss

Purpose To compare optic nerve head (ONH) measurements in glaucomatous eyes with paracentral visual field (VF) loss to eyes with peripheral VF loss and controls. Methods: Open-angle glaucoma (OAG) patients with early paracentral VF loss or isolated peripheral VF loss as well as control subjects underwent ONH imaging with swept-source optical coherence tomography (OCT) and retinal nerve fiber layer (RNFL) imaging with spectral-domain OCT. Minimum rim width at Bruch’s membrane opening (BMO-MRW), lamina cribrosa depth (LCD), and RNFL thickness were compared among the glaucoma and control groups with one-way analysis of variance, Kruskal–Wallis test, and multiple regression analysis. Results: Twenty-nine eyes from 29 OAG patients (15 early paracentral and 14 isolated peripheral VF loss) and 20 eyes of 20 control subjects were included. The early paracentral and isolated peripheral VF loss groups had similar VF mean deviation (MD) (−5.3±2.7 dB and −3.7±3.0 dB, p=0.15, respectively). Global BMO-MRW was lower in OAG eyes than in controls (193.8±40.0 vs 322.7±62.2 μm, p0.99). In contrast, the minimal BMO-MRW was lower in eyes with early paracentral loss (69.0±33.6 μm) than in eyes with isolated peripheral loss (107.7±40.2 μm; p=0.03) or control eyes (200.1±40.8 μm; p<0.001). Average and thinnest RNFL thickness did not differ between OAG groups (p=0.61 and 0.19, respectively). Horizontal and vertical LCD did not differ among the OAG groups and controls (p=0.80 and 0.82, respectively). Multivariable linear regression analysis among OAG cases confirmed the association between lower minimal BMO-MRW and early paracentral VF loss (β=−38.3 μm; 95% confidence interval, −69.8 to −6.8 μm; p=0.02) after adjusting for age, gender, MD, and disc size. Conclusion: Thin minimal BMO-MRW may represent a new structural biomarker associated with early glaucomatous paracentral VF loss

Small-Group Learning in an Upper-Level University Biology Class Enhances Academic Performance and Student Attitudes Toward Group Work

To improve science learning, science educators' teaching tools need to address two major criteria: teaching practice should mirror our current understanding of the learning process; and science teaching should reflect scientific practice. We designed a small-group learning (SGL) model for a fourth year university neurobiology course using these criteria and studied student achievement and attitude in five course sections encompassing the transition from individual work-based to SGL course design. All students completed daily quizzes/assignments involving analysis of scientific data and the development of scientific models. Students in individual work-based (Individualistic) sections usually worked independently on these assignments, whereas SGL students completed assignments in permanent groups of six. SGL students had significantly higher final exam grades than Individualistic students. The transition to the SGL model was marked by a notable increase in 10th percentile exam grade (Individualistic: 47.5%; Initial SGL: 60%; Refined SGL: 65%), suggesting SGL enhanced achievement among the least prepared students. We also studied student achievement on paired quizzes: quizzes were first completed individually and submitted, and then completed as a group and submitted. The group quiz grade was higher than the individual quiz grade of the highest achiever in each group over the term. All students – even term high achievers –could benefit from the SGL environment. Additionally, entrance and exit surveys demonstrated student attitudes toward SGL were more positive at the end of the Refined SGL course. We assert that SGL is uniquely-positioned to promote effective learning in the science classroom

Reduced-Intensity Conditioning Allogeneic Hematopoietic Cell Transplantation for Patients with Hematologic Malignancies Who Relapse following Autologous Transplantation: A Multi-institutional Prospective Study from the Cancer and Leukemia Group B (CALGB trial 100002)

We prospectively treated 80 patients with relapse of malignancy or secondary myelodysplasia after autologous hematopoietic cell transplantation (AHCT) with allogeneic hematopoietic cell transplantation (allo-HCT) using a reduced-intensity conditioning (RIC) regimen of fludarabine 150 mg/m2 plus intravenous busulfan 6.4 mg/kg. Both sibling (MSD) and unrelated donors (MUD) were allowed. Patients transplanted from MUD donors received more intensive graft-versus-host disease (GVHD) prophylaxis, including rabbit anti-thymocyte globulin 10 mg/kg, mycophenolate mofetil, and an extended schedule of tacrolimus. With a median follow-up of 3.1 years (0.9 to 5.8), TRM at 6 months and 2 years was 8% and 23% respectively. Neither TRM nor the rates of acute GVHD were different in those with sibling or MUD donors. Donor CD3 cell chimerism > 90% at day +30 was achieved more often in patients with MUD than with MSD donors, 70% versus 23% (p<0.0001). Median EFS was higher in patients who achieved early full donor chimerism (14.2 versus 8 mo, p = 0.0395). Allo-HCT using this RIC regimen can be performed with low TRM in patients who have received a prior AHCT. Efforts to improve early donor CD3 chimerism may improve EFS

The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

BACKGROUND: The number of gene expression studies in the public domain is rapidly increasing, representing a highly valuable resource. However, dataset-specific bias precludes meta-analysis at the raw transcript level, even when the RNA is from comparable sources and has been processed on the same microarray platform using similar protocols. Here, we demonstrate, using Affymetrix data, that much of this bias can be removed, allowing multiple datasets to be legitimately combined for meaningful meta-analyses. RESULTS: A series of validation datasets comparing breast cancer and normal breast cell lines (MCF7 and MCF10A) were generated to examine the variability between datasets generated using different amounts of starting RNA, alternative protocols, different generations of Affymetrix GeneChip or scanning hardware. We demonstrate that systematic, multiplicative biases are introduced at the RNA, hybridization and image-capture stages of a microarray experiment. Simple batch mean-centering was found to significantly reduce the level of inter-experimental variation, allowing raw transcript levels to be compared across datasets with confidence. By accounting for dataset-specific bias, we were able to assemble the largest gene expression dataset of primary breast tumours to-date (1107), from six previously published studies. Using this meta-dataset, we demonstrate that combining greater numbers of datasets or tumours leads to a greater overlap in differentially expressed genes and more accurate prognostic predictions. However, this is highly dependent upon the composition of the datasets and patient characteristics. CONCLUSION: Multiplicative, systematic biases are introduced at many stages of microarray experiments. When these are reconciled, raw data can be directly integrated from different gene expression datasets leading to new biological findings with increased statistical power

Epigenetic Regulation of Cell Type–Specific Expression Patterns in the Human Mammary Epithelium

Differentiation is an epigenetic program that involves the gradual loss of pluripotency and acquisition of cell type–specific features. Understanding these processes requires genome-wide analysis of epigenetic and gene expression profiles, which have been challenging in primary tissue samples due to limited numbers of cells available. Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, as well as gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type–specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation

The Met oncogene and basal-like breast cancer: another culprit to watch out for?

Recent findings suggest the involvement of the MET oncogene, encoding the tyrosine kinase receptor for hepatocyte growth factor, in the onset and progression of basal-like breast carcinoma. The expression profiles of basal-like tumors - but not those of other breast cancer subtypes - are enriched for gene sets that are coordinately over-represented in transcriptional signatures regulated by Met. Consistently, tissue microarray analyses have revealed that Met immunoreactivity is much higher in basal-like cases of human breast cancer than in other tumor types. Finally, mouse models expressing mutationally activated forms of Met develop a high incidence of mammary tumors, some of which exhibit basal characteristics. The present review summarizes current knowledge on the role and activity of Met in basal-like breast cancer, with a special emphasis on the correlation between this tumor subtype and the cellular hierarchy of the normal mammary gland

FOXA1 repression is associated with loss of BRCA1 and increased promoter methylation and chromatin silencing in breast cancer

FOXA1 expression correlates with the breast cancer luminal subtype and patient survival. RNA and protein analysis of a panel of breast cancer cell lines revealed that BRCA1 deficiency is associated with the downregulation of FOXA1 expression. Knockdown of BRCA1 resulted in the downregulation of FOXA1 expression and enhancement of FOXA1 promoter methylation in MCF-7 breast cancer cells, whereas the reconstitution of BRCA1 in Brca1-deficent mouse mammary epithelial cells (MMECs) promoted Foxa1 expression and methylation. These data suggest that BRCA1 suppresses FOXA1 hypermethylation and silencing. Consistently, the treatment of MMECs with the DNA methylation inhibitor 5-aza-2'-deoxycitydine induced Foxa1 mRNA expression. Furthermore, treatment with GSK126, an inhibitor of EZH2 methyltransferase activity, induced FOXA1 expression in BRCA1-deficient but not in BRCA1-reconstituted MMECs. Likewise, the depletion of EZH2 by small interfering RNA enhanced FOXA1 mRNA expression. Chromatin immunoprecipitation (ChIP) analysis demonstrated that BRCA1, EZH2, DNA methyltransferases (DNMT)1/3a/3b and H3K27me3 are recruited to the endogenous FOXA1 promoter, further supporting the hypothesis that these proteins interact to modulate FOXA1 methylation and repression. Further co-immunoprecipitation and ChIP analysis showed that both BRCA1 and DNMT3b form complexes with EZH2 but not with each other, consistent with the notion that BRCA1 binds to EZH2 and negatively regulates its methyltransferase activity. We also found that EZH2 promotes and BRCA1 impairs the deposit of the gene silencing histone mark H3K27me3 on the FOXA1 promoter. These associations were validated in a familial breast cancer patient cohort. Integrated analysis of the global gene methylation and expression profiles of a set of 33 familial breast tumours revealed that FOXA1 promoter methylation is inversely correlated with the transcriptional expression of FOXA1 and that BRCA1 mutation breast cancer is significantly associated with FOXA1 methylation and downregulation of FOXA1 expression, providing physiological evidence to our findings that FOXA1 expression is regulated by methylation and chromatin silencing and that BRCA1 maintains FOXA1 expression through suppressing FOXA1 gene methylation in breast cancer.Oncogene advance online publication, 22 December 2014; doi:10.1038/onc.2014.421.published_or_final_versio