Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Abstract Background Correctly identifying genomic regions enriched with histone modifications and transcription factors is key to understanding their regulatory and developmental roles. Conceptually, these regions are divided into two categories, narrow peaks and broad domains, and different algorithms are used to identify each one. Datasets that span these two categories are often analyzed with a single program for peak calling combined with an ad hoc method for domains. Results We developed hiddenDomains, which identifies both peaks and domains, and compare it to the leading algorithms using H3K27me3, H3K36me3, GABP, ESR1 and FOXA ChIP-seq datasets. The output from the programs was compared to qPCR-validated enriched and depleted sites, predicted transcription factor binding sites, and highly-transcribed gene bodies. With every method, hiddenDomains, performed as well as, if not better than algorithms dedicated to a specific type of analysis. Conclusions hiddenDomains performs as well as the best domain and peak calling algorithms, making it ideal for analyzing ChIP-seq datasets, especially those that contain a mixture of peaks and domains

A Survey of Imprinted Gene Expression in Mouse Trophoblast Stem Cells

Several hundred mammalian genes are expressed preferentially from one parental allele as the result of a process called genomic imprinting. Genomic imprinting is prevalent in extra-embryonic tissue, where it plays an essential role during development. Here, we profiled imprinted gene expression via RNA-Seq in a panel of six mouse trophoblast stem lines, which are ex vivo derivatives of a progenitor population that gives rise to the placental tissue of the mouse. We found evidence of imprinted expression for 48 genes, 31 of which had been described previously as imprinted and 17 of which we suggest as candidate imprinted genes. An equal number of maternally and paternally biased genes were detected. On average, candidate imprinted genes were more lowly expressed and had weaker parent-of-origin biases than known imprinted genes. Several known and candidate imprinted genes showed variability in parent-of-origin expression bias between the six trophoblast stem cell lines. Sixteen of the 48 known and candidate imprinted genes were previously or newly annotated noncoding RNAs and six encoded for a total of 60 annotated microRNAs. Pyrosequencing across our panel of trophoblast stem cell lines returned levels of imprinted expression that were concordant with RNA-Seq measurements for all eight genes examined. Our results solidify trophoblast stem cells as a cell culture-based experimental model to study genomic imprinting, and provide a quantitative foundation upon which to delineate mechanisms by which the process is maintained in the mouse

Avoiding the high Bonferroni penalty in genome-wide association studies

A major challenge in genome-wide association studies (GWASs) is to derive the multiple testing threshold when hypothesis tests are conducted using a large number of single nucleotide polymorphisms. Permutation tests are considered the gold standard in multiple testing adjustment in genetic association studies. However, it is computationally intensive, especially for GWASs, and can be impractical if a large number of random shuffles are used to ensure accuracy. Many researchers have developed approximation algorithms to relieve the computing burden imposed by permutation. One particularly attractive alternative to permutation is to calculate the effective number of independent tests, Meff, which has been shown to be promising in genetic association studies. In this study, we compare recently developed Meff methods and validate them by the permutation test with 10,000 random shuffles using two real GWAS data sets: an Illumina 1M BeadChip and an Affymetrix GeneChip® Human Mapping 500K Array Set. Our results show that the simpleM method produces the best approximation of the permutation threshold, and it does so in the shortest amount of time. We also show that Meff is indeed valid on a genome-wide scale in these data sets based on statistical theory and significance tests. The significance thresholds derived can provide practical guidelines for other studies using similar population samples and genotyping platforms

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains

Abstract Background Correctly identifying genomic regions enriched with histone modifications and transcription factors is key to understanding their regulatory and developmental roles. Conceptually, these regions are divided into two categories, narrow peaks and broad domains, and different algorithms are used to identify each one. Datasets that span these two categories are often analyzed with a single program for peak calling combined with an ad hoc method for domains. Results We developed hiddenDomains, which identifies both peaks and domains, and compare it to the leading algorithms using H3K27me3, H3K36me3, GABP, ESR1 and FOXA ChIP-seq datasets. The output from the programs was compared to qPCR-validated enriched and depleted sites, predicted transcription factor binding sites, and highly-transcribed gene bodies. With every method, hiddenDomains, performed as well as, if not better than algorithms dedicated to a specific type of analysis. Conclusions hiddenDomains performs as well as the best domain and peak calling algorithms, making it ideal for analyzing ChIP-seq datasets, especially those that contain a mixture of peaks and domains

AWclust: point-and-click software for non-parametric population structure analysis

<p>Abstract</p> <p>Background</p> <p>Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation.</p> <p>Results</p> <p>We have developed point-and-click software for non-parametric population structure analysis distributed as an R package. The software takes advantage of the large number of SNPs available to categorize individuals into ethnically similar clusters and it does not require assumptions about population models. Nor does it estimate allele frequencies. Moreover, this software can also infer the optimal number of populations.</p> <p>Conclusion</p> <p>Our software tool employs non-parametric approaches to assign individuals to clusters using SNPs. It provides efficient computation and an intuitive way for researchers to explore ethnic relationships among individuals. It can be complementary to parametric approaches in population structure analysis.</p

Topoisomerases facilitate transcription of long genes linked to autism

Topoisomerases are expressed throughout the developing and adult brain and are mutated in some individuals with autism spectrum disorder (ASD). However, how topoisomerases are mechanistically connected to ASD is unknown. Here we found that topotecan, a Topoisomerase 1 (TOP1) inhibitor, dose-dependently reduced the expression of extremely long genes in mouse and human neurons, including nearly all genes >200 kb. Expression of long genes was also reduced following knockdown of Top1 or Top2b in neurons, highlighting that each enzyme was required for full expression of long genes. By mapping RNA polymerase II density genome-wide in neurons, we found that this length-dependent effect on gene expression was due to impaired transcription elongation. Interestingly, many high confidence ASD candidate genes are exceptionally long and were reduced in expression following TOP1 inhibition. Our findings suggest that chemicals and genetic mutations that impair topoisomerases could commonly contribute to ASD and other neurodevelopmental disorders

Coexistent ARID1A–PIK3CA mutations promote ovarian clear-cell tumorigenesis through pro-tumorigenic inflammatory cytokine signalling

Ovarian clear-cell carcinoma (OCCC) is an aggressive form of ovarian cancer with high ARID1A mutation rates. Here we present a mutant mouse model of OCCC. We find that ARID1A inactivation is not sufficient for tumor formation, but requires concurrent activation of the phosphoinositide 3-kinase catalytic subunit, PIK3CA. Remarkably, the mice develop highly penetrant tumors with OCCC-like histopathology, culminating in hemorrhagic ascites and a median survival period of 7.5 weeks. Therapeutic treatment with the pan-PI3K inhibitor, BKM120, prolongs mouse survival by inhibiting tumor cell growth. Cross-species gene expression comparisons support a role for IL-6 inflammatory cytokine signaling in OCCC pathogenesis. We further show that ARID1A and PIK3CA mutations cooperate to promote tumor growth through sustained IL-6 overproduction. Our findings establish an epistatic relationship between SWI/SNF chromatin remodeling and PI3K pathway mutations in OCCC and demonstrate that these pathways converge on pro-tumorigenic cytokine signaling. We propose that ARID1A protects against inflammation-driven tumorigenesis

T Follicular Helper Cell-Dependent Clearance of a Persistent Virus Infection Requires T Cell Expression of the Histone Demethylase UTX

Epigenetic changes, including histone methylation, control T cell differentiation and memory formation, though the enzymes that mediate these processes are not clear. We show that UTX, a histone H3 lysine 27 (H3K27) demethylase, supports T follicular helper (Tfh) cell responses that are essential for B cell antibody generation and the resolution of chronic viral infections. Mice with a T cell-specific UTX deletion had fewer Tfh cells, reduced germinal center responses, lacked virus-specific immunoglobulin G (IgG), and were unable to resolve chronic lymphocytic choriomeningitis virus infections. UTX-deficient T cells showed decreased expression of interleukin-6 receptor-α and other Tfh cell-related genes that were associated with increased H3K27 methylation. Additionally, Turner Syndrome subjects, who are predisposed to chronic ear infections, had reduced UTX expression in immune cells and decreased circulating CD4(+) CXCR5(+) T cell frequency. Thus, we identify a critical link between UTX in T cells and immunity to infection

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

A Survey of Imprinted Gene Expression in Mouse Trophoblast Stem Cells

Several hundred mammalian genes are expressed preferentially from one parental allele as the result of a process called genomic imprinting. Genomic imprinting is prevalent in extra-embryonic tissue, where it plays an essential role during development. Here, we profiled imprinted gene expression via RNA-Seq in a panel of six mouse trophoblast stem lines, which are ex vivo derivatives of a progenitor population that gives rise to the placental tissue of the mouse. We found evidence of imprinted expression for 48 genes, 31 of which had been described previously as imprinted and 17 of which we suggest as candidate imprinted genes. An equal number of maternally and paternally biased genes were detected. On average, candidate imprinted genes were more lowly expressed and had weaker parent-of-origin biases than known imprinted genes. Several known and candidate imprinted genes showed variability in parent-of-origin expression bias between the six trophoblast stem cell lines. Sixteen of the 48 known and candidate imprinted genes were previously or newly annotated noncoding RNAs and six encoded for a total of 60 annotated microRNAs. Pyrosequencing across our panel of trophoblast stem cell lines returned levels of imprinted expression that were concordant with RNA-Seq measurements for all eight genes examined. Our results solidify trophoblast stem cells as a cell culture-based experimental model to study genomic imprinting, and provide a quantitative foundation upon which to delineate mechanisms by which the process is maintained in the mouse