Hidden Markov models for the analysis of next-generation-sequencing data

Onderzoekers in de hedendaagse biologie zijn steeds meer afhankelijk van de productie en analyse van grote hoeveelheden digitale data. Deze data wordt geproduceerd met behulp van nieuwe experimentele technieken die grotere inzichten verschaffen over de manier waarop onze cellen werken. Eén van deze technieken is next-generation sequencing (NGS). Deze techniek werd ontwikkeld in het begin van de 21e eeuw, en wordt nu op brede wijze toegepast om alles omtrent de basepaarvolgorde (sequentie) van het DNA te bestuderen. Dit proefschrift beschrijft vier nieuwe algoritmes voor de analyse van NGS-data, welke zijn ontwikkeld voor verschillende NGS-experimenten die elk een uniek inzicht leveren in de cel. Hoofdstuk 1 dient als introductie voor NGS en legt in detail uit hoe dezelfde technologie gebruikt kan worden om verschillende soorten fenomenen gerelateerd aan de DNA-sequentie te onderzoeken. Hoofdstuk 2 behandelt een model voor de analyse van kopienummerveranderingen in individuele cellen aan de hand van NGS-data, en deze methode is toegepast om de rol van aneuploïdie in de ziekte van Alzheimer te bestuderen en de rol van kleine kopienummerveranderingen in kankercellen. In hoofdstuk 3 wordt uitgeweid over een uitbreiding van het in hoofdstuk 2 beschreven model. Hoofdstukken 4 en 5 beschrijven modellen voor de analyse van epigenetische wijzigingen van het DNA, en deze modellen kunnen helpen om onze kennis te vergroten over hoe totipotente stamcellen differentiëren in gespecialiseerde celtypen, en hoe de omgeving de expressie van genen kan beïnvloeden

breakpointR:an R/Bioconductor package to localize strand state changes in Strand-seq data

MOTIVATION: Strand-seq is a specialized single-cell DNA sequencing technique centered around the directionality of single-stranded DNA. Computational tools for Strand-seq analyses must capture the strand-specific information embedded in these data. RESULTS: Here we introduce breakpointR, an R/Bioconductor package specifically tailored to process and interpret single-cell strand-specific sequencing data obtained from Strand-seq. We developed breakpointR to detect local changes in strand directionality of aligned Strand-seq data, to enable fine-mapping of sister chromatid exchanges, germline inversion and to support global haplotype assembly. Given the broad spectrum of Strand-seq applications we expect breakpointR to be an important addition to currently available tools and extend the accessibility of this novel sequencing technique. AVAILABILITY: R/Bioconductor package https://bioconductor.org/packages/breakpointR

Histone methylation changes are required for life cycle progression in the human parasite Schistosoma mansoni

Epigenetic mechanisms and chromatin structure play an important role in development. Their impact is therefore expected to be strong in parasites with complex life cycles and multiple, strikingly different, developmental stages, i.e. developmental plasticity. Some studies have already described how the chromatin structure, through histone modifications, varies from a developmental stage to another in a few unicellular parasites. However, this, to our knowledge, has never been done before in multicellular metazoan parasites. We used chromatin immunoprecipitation followed by massively parallel sequencing (ChIPSeq) to characterize the profile of two histone post-translational modifications (trimethylation on lysine 4 of histone H3, H3K4me3, and trimethylation on lysine 27 of histone H3 H3K27me3) over five developmental stages (miracidium, primary sporocyst, cercaria, schistosomulum, adult) of the human blood fluke Schistosoma mansoni. While H3K4me3 profiles remain relatively constant, H3K27 trimethylation and bivalent methylation show strong variation. Inhibitors (A366 and GSK343) of H3K27 histone methyltransferase activity in S. mansoni efficiently blocked miracidium to sporocyst transition indicating that H3K27 trimethylation is required for life cycle progression. As S. mansoni is a multicellular parasite that significantly affects both the health and economy of endemic areas, a better understanding of fluke developmental processes within the definitive host will likely highlight novel disease control strategies. Towards this goal, we also studied H4K20me1 in female cercariae and adults. In particular, we found that bivalent trimethylation of H3K4 and H3K27 at the transcription start site of genes is a landmark of the cercarial stage. In cercariae, H3K27me3 presence and strong enrichment in H4K20me1 over long regions (10?100 kb) is associated with development related genes. Here, we provide a broad overview of the chromatin structure of a metazoan parasite throughout its most important lifecycle stages. The five developmental stages studied here present distinct chromatin structures, indicating that histone methylation plays an important role during development. Hence, components of the histone methylation (and demethylation) machinery may provide suitable Schistosomiasis control targets.publishersversionPeer reviewe

histoneHMM:Differential analysis of histone modifications with broad genomic footprints

BACKGROUND: ChIP-seq has become a routine method for interrogating the genome-wide distribution of various histone modifications. An important experimental goal is to compare the ChIP-seq profiles between an experimental sample and a reference sample, and to identify regions that show differential enrichment. However, comparative analysis of samples remains challenging for histone modifications with broad domains, such as heterochromatin-associated H3K27me3, as most ChIP-seq algorithms are designed to detect well defined peak-like features. RESULTS: To address this limitation we introduce histoneHMM, a powerful bivariate Hidden Markov Model for the differential analysis of histone modifications with broad genomic footprints. histoneHMM aggregates short-reads over larger regions and takes the resulting bivariate read counts as inputs for an unsupervised classification procedure, requiring no further tuning parameters. histoneHMM outputs probabilistic classifications of genomic regions as being either modified in both samples, unmodified in both samples or differentially modified between samples. We extensively tested histoneHMM in the context of two broad repressive marks, H3K27me3 and H3K9me3, and evaluated region calls with follow up qPCR as well as RNA-seq data. Our results show that histoneHMM outperforms competing methods in detecting functionally relevant differentially modified regions. CONCLUSION: histoneHMM is a fast algorithm written in C++ and compiled as an R package. It runs in the popular R computing environment and thus seamlessly integrates with the extensive bioinformatic tool sets available through Bioconductor. This makeshistoneHMM an attractive choice for the differential analysis of ChIP-seq data. Software is available from http://histonehmm.molgen.mpg.de

プレゼンテーション演習

平成26年8月5日にお茶の水女子大学で行われた「三大学連携 機関リポジトリ研修会」におけるプレゼンテーション資