Single feature polymorphism discovery using the wheat Affymetrix Gene Chip

PURPOSE: To determine how often medical students are not allowed to perform gynecological examinations during their obstetrics-gynecology clerkship, identify the barriers to participation related to physicians and patients, explore the role of the supervisory physician in not allowing medical student involvement, and explore differences between male and female students' experiences. METHOD: All medical students entering their obstetrics-gynecology clerkship at a medical school in the Netherlands between May and October 2011 were invited to participate in this study's questionnaire, which asked them to report the number of gynecological examinations they were allowed and not allowed to perform during their clerkship. Eighteen questionnaire respondents participated in three focus groups. RESULTS: Of the 139 medical students invited, 76 (55%) completed the questionnaire. Students reported a total of 2,196 instances in which they were not allowed to participate in the examination; 89% (n = 1,956) were related to the supervisory physician. Qualitative data from the focus group interviews showed that female supervisory physicians prioritized patients' autonomy above students' learning needs. Furthermore, female students were less assertive than male students in asking the supervisory physician for permission to participate. CONCLUSIONS: The physician's role in not allowing student involvement is substantial and results in fewer opportunities for students to perform gynecological examinations. For students to develop the necessary gynecological exam skills during their clerkship, medical educators need to improve the learning environment

K-ATP channel gene expression is induced by urocortin and mediates its cardioprotective effect

Background-Urocortin is a novel cardioprotective agent that can protect cardiac myocytes from the damaging effects of ischemia/reperfusion both in culture and in the intact heart and is effective when given at reperfusion.Methods and Results-We have analyzed global changes in gone expression in cardiac myocytes after urocortin treatment using gene chip technology. We report that urocortin specifically induces enhanced expression of the Kir 6.1 cardiac potassium channel subunit. On the basis of this finding, we showed that the cardioprotective effect of urocortin both in isolated cardiac cells and in the intact heart is specifically blocked by both generalized and mitochondrial-specific K-ATP channel blockers, whereas the cardioprotective effect of cardiotrophin-1 is unaffected. Conversely, inhibiting the Kir 6.1 channel subunit greatly enhances cardiac cell death after ischemia.Conclusions-This is, to our knowledge, the first report of the altered expression of a K-ATP. channel subunit induced by a cardioprotective agent and demonstrates that K-ATP, channel opening is essential for the effect of this novel cardioprotective agent

Probabilistic estimation of microarray data reliability and underlying gene expression

Background: The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. Results: Our approach yields a quantitative measure of two important parameter classes: First, the probability $P(\sigma | S)$ that a gene is in the biological state $\sigma$ in a certain variety, given its observed expression $S$ in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a $t$-test is used as reference. On a set of known genes it performs better than the $t$-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. Conclusions: The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques.Comment: 11 pages, 4 figure

Evaluation of Affymetrix Gene Chip sensitivity in rat hippocampal tissue using SAGE analysis *

DNA microarrays are a powerful tool for monitoring thousands of transcript levels simultaneously. However, the use of DNA microarrays in studying the central nervous system faces several challenges. These include the detection of low-abundance transcripts in highly complex tissue as well as estimating relatively low-magnitude changes in transcript levels in response to experimental manipulation. Many transcripts important to brain function have low expression levels or are expressed in relatively few cells, making them difficult to detect in the complex background of brain tissue. The aim of the present study is to evaluate the sensitivity of Gene Chip detection of transcripts in brain by using results from serial analysis of gene expression (SAGE) studies. The results of this comparison indicate that Affymetrix Gene Chips, like SAGE, only reliably detect medium- to high-abundance transcripts and that detection of low-abundance transcripts, many of which have great relevance to biological function in brain, is inconsistent. Specifically, we estimate that Gene Chips reliably detect no more than 30% of the hippocampal transcriptome when using a gross hippocampal dissection as the source tissue. This report provides the first broad evaluation of Affymetrix Gene Chip sensitivity relevant to studying the brain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75717/1/j.1460-9568.2002.02097.x.pd

Genetic Correlates of Brain Aging on MRI and Cognitive Test Measures: A Genome-Wide Association and Linkage Analysis in the Framingham Study

BACKGROUND: Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample. METHODS: A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999–2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency ≥ 0.10, genotypic call rate ≥ 0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores. RESULTS: The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 × 10-6) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 × 10-8) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1). CONCLUSION: Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.National Institutes of Health National Center for Research Resources Shared Instrumentation grant (ISI0RR163736-01A1); National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC-25195); National Institute of Aging (5R01-AG08122, 5R01-AG16495); National Institute of Neurological Disorders and Stroke (5R01-NS17950

Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

BACKGROUND: Comparison of data produced on different microarray platforms often shows surprising discordance. It is not clear whether this discrepancy is caused by noisy data or by improper probe matching between platforms. We investigated whether the significant level of inconsistency between results produced by alternative gene expression microarray platforms could be reduced by stringent sequence matching of microarray probes. We mapped the short oligo probes of the Affymetrix platform onto cDNA clones of the Stanford microarray platform. Affymetrix probes were reassigned to redefined probe sets if they mapped to the same cDNA clone sequence, regardless of the original manufacturer-defined grouping. The NCI-60 gene expression profiles produced by Affymetrix HuFL platform were recalculated using these redefined probe sets and compared to previously published cDNA measurements of the same panel of RNA samples. RESULTS: The redefined probe sets displayed a substantially higher level of cross-platform consistency at the level of gene correlation, cell line correlation and unsupervised hierarchical clustering. The same strategy allowed an almost complete correspondence of breast cancer subtype classification between Affymetrix gene chip and cDNA microarray derived gene expression data, and gave an increased level of similarity between normal lung derived gene expression profiles using the two technologies. In total, two Affymetrix gene-chip platforms were remapped to three cDNA platforms in the various cross-platform analyses, resulting in improved concordance in each case. CONCLUSION: We have shown that probes which target overlapping transcript sequence regions on cDNA microarrays and Affymetrix gene-chips exhibit a greater level of concordance than the corresponding Unigene or sequence matched features. This method will be useful for the integrated analysis of gene expression data generated by multiple disparate measurement platforms

Strange Bedfellows: Quantum Mechanics and Data Mining

Last year, in 2008, I gave a talk titled {\it Quantum Calisthenics}. This year I am going to tell you about how the work I described then has spun off into a most unlikely direction. What I am going to talk about is how one maps the problem of finding clusters in a given data set into a problem in quantum mechanics. I will then use the tricks I described to let quantum evolution lets the clusters come together on their own.Comment: 11 pages, 7 figures, Invited Talk at Light Cone 200

PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity