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

Sox4 Promotes Atoh1-Independent Intestinal Secretory Differentiation Toward Tuft and Enteroendocrine Fates

BACKGROUND & AIMS: The intestinal epithelium is maintained by intestinal stem cells (ISCs), which produce postmitotic absorptive and secretory epithelial cells. Initial fate specification toward enteroendocrine, goblet, and Paneth cell lineages requires the transcription factor Atoh1, which regulates differentiation of the secretory cell lineage. However, less is known about the origin of tuft cells, which participate in type II immune responses to parasite infections and appear to differentiate independently of Atoh1. We investigated the role of Sox4 in ISC differentiation. METHODS: We performed experiments in mice with intestinal epithelial-specific disruption of Sox4 (Sox4fl/fl:vilCre; SOX4 conditional knockout [cKO]) and mice without disruption of Sox4 (control mice). Crypt- and single-cell-derived organoids were used in assays to measure proliferation and ISC potency. Lineage allocation and gene expression changes were studied by immunofluorescence, real-time quantitative polymerase chain reaction, and RNA-seq analyses. Intestinal organoids were incubated with the type 2 cytokine interleukin 13 and gene expression was analyzed. Mice were infected with the helminth Nippostrongylus brasiliensis and intestinal tissues were collected 7 days later for analysis. Intestinal tissues collected from mice that express green fluorescent protein regulated by the Atoh1 promoter (Atoh1GFP mice) and single-cell RNA-seq analysis were used to identify cells that coexpress Sox4 and Atoh1. We generated SOX4-inducible intestinal organoids derived from Atoh1fl/fl:vilCreER (ATOH1 inducible knockout) mice and assessed differentiation. RESULTS: Sox4cKO mice had impaired ISC function and secretory differentiation, resulting in decreased numbers of tuft and enteroendocrine cells. In control mice, numbers of SOX4+ cells increased significantly after helminth infection, coincident with tuft cell hyperplasia. Sox4 was activated by interleukin 13 in control organoids; SOX4cKO mice had impaired tuft cell hyperplasia and parasite clearance after infection with helminths. In single-cell RNA-seq analysis, Sox4+/Atoh1- cells were enriched for ISC, progenitor, and tuft cell genes; 12.5% of Sox4-expressing cells coexpressed Atoh1 and were enriched for enteroendocrine genes. In organoids, overexpression of Sox4 was sufficient to induce differentiation of tuft and enteroendocrine cells-even in the absence of Atoh1. CONCLUSIONS: We found Sox4 promoted tuft and enteroendocrine cell lineage allocation independently of Atoh1. These results challenge the longstanding model in which Atoh1 is the sole regulator of secretory differentiation in the intestine and are relevant for understanding epithelial responses to parasitic infection

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

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

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

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

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

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