Elucidating regulatory elements : studies in chronic lymphocytic leukemia and multiple myeloma

With next generation sequencing taking center stage in genetic and epigenetic research, its applications and challenges are many. This work revolves around the application of bioinformatics in different contexts: basic research in the understanding of diseases (biology), the effect of treatment on the target cells (clinics) and the assessment of a new wet-lab method (lab). Biology. Two studies fall under this topic, one on chronic lymphocytic leukemia, the other on multiple myeloma. Many coding mutations and chromosomal aberrations have long been identified in both diseases, yet they are only present in subsets of patients, and so it is puzzling that all this diversity results in a single diagnosis. We hypothesized that instead of a common genetic background, they might present with a common epigenetic background. For this we aimed to collect paired RNA-seq, histone ChIP-seq and ATAC-seq for patients and healthy controls, and had the following specific hypotheses: 1. Using H3K4me2 and H3K27Ac, we will be able to identify the regulatory elements altered between health and disease. 2. By looking at the interplay between those regulatory elemets, RNA-seq, ATAC-seq and database information, we will be able to describe the aberrant regulation in terms of transciption factors, regulatory elements and their target genes. Clinics Ibrutinib is a novel drug used in chronic lymphocytic leukemia treatment. Though it is shown to be beneficial to many patients, a lot of the early effects the treatment has on the malignant cells, especially in different parts of the body, are still unknown. We hypothesized that relevant changes in blood and lymph nodes would be visible soon after treatment, and collected RNA-seq data from both compartments, in additions to plasma values of inflammatory cytokines. We had to following specific hypotheses: 1. Early changes are visible, maybe even just hours after first treatment. 2. There will be differences in treatment effect between blood and lymph node compartments. Lab ChIP-seq is a very useful method to look at proteins bound to DNA, which, depending on the protein checked, can give a multitude of information. Yet, the amount of cells needed to perform these experiments is high, even in improved protocols like ChIPmentation. We hypothesized that the ChIPmentation protocol could be optimized, and that reducing time and steps would yield better data. For this we performed ChIP-seq with the original ChIPmentation protocol and with our adaptation, testing the following specific hypotheses: 1. Our version, high-throughput ChIPmentation, will perform equally well as the original method when high cell numbers are used, but be faster. 2. When low cell numbers are used, our method will give better results, as it involves less loss of material. My contribution lies in the development and execution of bioinformatics, pipelines, data handling etc, to test these hypotheses, which also includes discussions and planning of projects, samples and feasibility

miSTAR : miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure

In microRNA (miRNA) target prediction, typically two levels of information need to be modeled: the number of potential miRNA binding sites present in a target mRNA and the genomic context of each individual site. Single model structures insufficiently cope with this complex training data structure, consisting of feature vectors of unequal length as a consequence of the varying number of miRNA binding sites in different mRNAs. To circumvent this problem, we developed a two-layered, stacked model, in which the influence of binding site context is separately modeled. Using logistic regression and random forests, we applied the stacked model approach to a unique data set of 7990 probed miRNA-mRNA interactions, hereby including the largest number of miRNAs in model training to date. Compared to lower-complexity models, a particular stacked model, named miSTAR (miRNA stacked model target prediction; www.mi-star.org), displays a higher general performance and precision on top scoring predictions. More importantly, our model outperforms published and widely used miRNA target prediction algorithms. Finally, we highlight flaws in cross-validation schemes for evaluation of miRNA target prediction models and adopt a more fair and stringent approach

Comprehensive mapping of the effects of azacitidine on DNA methylation, repressive/permissive histone marks and gene expression in primary cells from patients with MDS and MDS-related disease

Azacitidine (Aza) is first-line treatment for patients with high-risk myelodysplastic syndromes (MDS), although its precise mechanism of action is unknown. We performed the first study to globally evaluate the epigenetic effects of Aza on MDS bone marrow progenitor cells assessing gene expression (RNA seq), DNA methylation (Illumina 450k) and the histone modifications H3K18ac and H3K9me3 (ChIP seq). Aza induced a general increase in gene expression with 924 significantly upregulated genes but this increase showed no correlation with changes in DNA methylation or H3K18ac, and only a weak association with changes in H3K9me3. Interestingly, we observed activation of transcripts containing 15 endogenous retroviruses (ERVs) confirming previous cell line studies. DNA methylation decreased moderately in 99% of all genes, with a median beta-value reduction of 0.018; the most pronounced effects seen in heterochromatin. Aza-induced hypomethylation correlated significantly with change in H3K9me3. The pattern of H3K18ac and H3K9me3 displayed large differences between patients and healthy controls without any consistent pattern induced by Aza. We conclude that the marked induction of gene expression only partly could be explained by epigenetic changes, and propose that activation of ERVs may contribute to the clinical effects of Aza in MDS.Peer reviewe

High-throughput ChIPmentation: freely scalable, single day ChIPseq data generation from very low cell-numbers

BackgroundChromatin immunoprecipitation coupled to sequencing (ChIP-seq) is widely used to map histone modifications and transcription factor binding on a genome-wide level.ResultsWe present high-throughput ChIPmentation (HT-ChIPmentation) that eliminates the need for DNA purification prior to library amplification and reduces reverse-crosslinking time from hours to minutes.ConclusionsThe resulting workflow is easily established, extremely rapid, and compatible with requirements for very low numbers of FACS sorted cells, high-throughput applications and single day data generation

SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post-enrichment. Here, we present a new methodology based on classical population genetic theory, i.e. the Hardy-Weinberg theorem, that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation was done using both 14 whole-genome bisulfite sequencing data sets and 16 mRNA-seq data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, like the ChIP-seq-based identification of monoallelic histone modifications

Ebf1 heterozygosity results in increased DNA damage in pro-B cells and their synergistic transformation by Pax5 haploinsufficiency.

Ebf1 is a transcription factor with documented dose dependent functions in normal and malignant B-lymphocyte development. To understand more about the roles of Ebf1 in malignant transformation, we investigated the impact of reduced functional Ebf1 dosage on mouse B-cell progenitors. Gene expression analysis suggested that Ebf1 was involved in the regulation of genes important for DNA repair as well as cell survival. Investigation of the DNA damage in steady state as well as after induction of DNA damage by UV light, confirmed that pro-B cells lacking one functional allele of Ebf1 display signs of increased DNA damage. This correlated to reduced expression of DNA repair genes including Rad51 and chromatin immunoprecipitation data suggested that Rad51 is a direct target for Ebf1. Although reduced dosage of Ebf1 did not significantly increase tumor formation in mice, a dramatic increase in the frequency of pro-B cell leukemia was observed in mice with combined heterozygous mutations in the Ebf1 and Pax5 genes revealing a synergistic effect of combined dose reduction of these proteins. Our data suggest that Ebf1 controls DNA repair in a dose dependent manner providing a possible explanation to the frequent involvement of EBF1 gene loss in human leukemia

The Concerted Action of E2-2 and HEB Is Critical for Early Lymphoid Specification

The apparition of adaptive immunity in Gnathostomata correlates with the expansion of the E-protein family to encompass E2-2, HEB, and E2A. Within the family, E2-2 and HEB are more closely evolutionarily related but their concerted action in hematopoiesis remains to be explored. Here we show that the combined disruption of E2-2 and HEB results in failure to express the early lymphoid program in Common lymphoid precursors (CLPs) and a near complete block in B-cell development. In the thymus, Early T-cell progenitors (ETPs) were reduced and T-cell development perturbed, resulting in reduced CD4 T- and increased γδ T-cell numbers. In contrast, hematopoietic stem cells (HSCs), erythro-myeloid progenitors, and innate immune cells were unaffected showing that E2-2 and HEB are dispensable for the ancestral hematopoietic lineages. Taken together, this E-protein dependence suggests that the appearance of the full Gnathostomata E-protein repertoire was critical to reinforce the gene regulatory circuits that drove the emergence and expansion of the lineages constituting humoral immunity

SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post-enrichment. Here, we present a new methodology based on classical population genetic theory, i.e. the Hardy-Weinberg theorem, that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation was done using both 14 whole-genome bisulfite sequencing data sets and 16 mRNA-seq data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, like the ChIP-seq-based identification of monoallelic histone modifications