The aims of this thesis were to investigate whether characteristics associated with animal welfare are genetically and genomically determined by using quantitative and molecular genetic approaches and to develop strategies indicating how these traits could be used in breeding programmes. Two traits that are closely related to animal welfare and associated with high socio-economic values are piglet survival at birth and aggressive behaviour in pigs. Piglet survival traits were analysed based on quantitative Bayesian approaches using phenotypic and pedigree information only, while aggressive behaviour was analysed based on molecular genetic approaches such as genome-wide association studies and genomic selection using additionally a dense panel of single nucleotide polymorphisms (SNP). The latter approach was validated using behavioural traits related to welfare characteristics in a welldocumented mouse data set. Selection for piglet survival at birth is expected to be effective, because all lines and breeds in this thesis showed considerable variation for this trait and relatively high heritabilities, particularly in lines with low average birth weight. Maternal heritabilities of individual birth weight were mostly at moderate magnitude and thus of great interest for selection. The genetic correlations between piglet survival and birth weight indicated that selection for either individual or average birth weight or variation of birth weight within litter would indirectly increase survival. The genetic associations of piglet survival with economically important (re)production traits are of great importance for breeding organisations. Undesirable genetic correlations between piglet survival and (re)production traits were generally of low magnitude, so that simultaneous improvement of all traits could be achieved. A comparison of five breeds and lines showed that differences in genetic parameters between breeds and lines can be substantial and no single selection strategy would be optimal for all. A unique study of a sire and a dam line originating from one breed but selected for more than 25 years with different breeding goals demonstrated how selection pressure can alter the genetic parameters over years. Breeding organisations should therefore consider selection strategies per breed or line individually to achieve maximum overall improvement. This study gives new insight into the use of genomic selection for traits associated with animal welfare. It is one of the first to present estimates for linkage disequilibrium in the pig using a new 60K SNP panel and the first to evaluate the efficiency of genomic selection against aggressive behaviour in pigs. Genomic selection showed a high predictive ability in comparison to traditional polygenic selection. It was especially advantageous for traits with lower heritabilities. In particular in situations where little family information was available, the performance of polygenic selection was low and genomic selection increased the performance considerably. Reducing the number of SNPs did not significantly change the performance of genomic selection. The consistently high performance across models indicates that low-density SNP panels may be sufficient to ensure a high efficiency of genomic selection, thus reducing the high costs associated with genotyping in pig breeding with its short generation interval. To summarize, this thesis has shown how to optimise quantitative and genomic approaches to improve animal welfare related characteristics efficiently in pig breeding programmes.

The first metazoan to be sequenced was a nematode (Caenorhabditis elegans), and understanding the genome of this model organism has led to many insights about all animals. Although eleven nematode genomes have been published so far and approximately twenty more are under way, the vast majority of the genomes of this incredibly diverse phylum remain unexplored. Next-generation sequencing has made it possible to generate large amounts of genome sequence data in a few days at a fraction of the cost of traditional Sanger-sequencing. However, assembling and annotating these data into genomic resources remains a challenge because of the short reads, the quality issues in these kinds of data, and the presence of contaminants and co-bionts in uncultured samples. In this thesis, I describe the process of creating high quality draft genomes and annotation resources for four nematode species representing three of the five major nematode clades: Caenorhabditis sp. 5, Meloidogyne floridensis, Dirofilaria immitis, and Litomosoides sigmodontis. I describe the new approaches I developed for visualising contamination and co-bionts, and I present the details of the robust workflow I devised to deal with the problems of generating low-cost genomic resources from Illumina short-read sequencing. Results: The draft genome assemblies created using the workflow described in this thesis are comparable to the draft nematode genomes created using Sanger sequencing. Armed with these genomes, I was able to answer two evolutionary genomics questions at very different scales. The first question was whether any non-coding elements were deeply conserved at the level of the whole phylum. Such elements had previously been hypothesised to be responsible for the phylum body plan in vertebrates, insects, and nematodes. I used twenty nematode genomes in several whole-genome alignments and concluded that no such elements were conserved across the whole phylum. The second question addressed the origins of the highly destructive plant-parasitic root-knot nematode Meloidogyne incognita. Comparisons with the newly sequenced Meloidogyne floridensis genome revealed the complex hybrid origins of both species, undermining previous assumptions about the rarity of hybrid speciation in animals. Conclusions: This thesis demonstrates the role of next-generation sequencing in democratising genome sequencing projects. Using the sequencing strategies, workflows, and tools described here, one can rapidly create genomic resources at a very low cost, even for unculturable metazoans. These genomes can be used to understand the evolutionary history of a genus or a phylum, as shown.

The present study aimed to gain better insights into the distribution of genomic variation, in the form of single nucleotide polymorphisms, within the human genome.  Using set theory, the average SNP density of the human genome was found to be 2.6 SNPs per kilobase.  This figure decreased with increasing evolutionary depth, i.e. conservation.  The conserved exonic, intronic subsets had a lower SNP density than the conserved intergenic subset, suggesting that the conserved exonic and intronic regions are under similar strengths of selective pressure while conserved intergenic regions are under a comparatively weaker selective pressure.  To better understand allelic differences on protein-DNA interactions, an algorithm was designed that scored the difference in binding site prediction for the alleles of an SNP.  The program created, RegSNP, was demonstrated to be more accurate than existing resources, and gives results that are relevant of SNP within binding sites in the literature. A further aim of the present study was to isolate potential regulatory regions of the GAL gene, that has been linked to diseases such as obesity and depression, and identify polymorphisms that may alter transcription factor binding.  One excellent candidate element was found by comparative genomics, Gal5.1, and confirmed by transgenic analysis as a transcriptional enhancer element.  Gal5.1, contained a single SNP that RegSNP predicted to interrupt a thyroid hormone receptor binding site.  However, using transgenic animal and cell biology techniques it was concluded that thyroid hormone receptor does not directly interact with the Gal5.1 element, suggesting that the Gal5.1 element must work in synergy with the GAL promoter to stimulate transcription.

Over the last decades, the formerly irrevocable believe that proteins are the only key-factors in the complex regulatory machinery of a cell was crushed by a plethora of findings in all major eukaryotic lineages. These suggested a rugged landscape in the eukaryotic genome consist- ing of sequential, overlapping, or even bi-directional transcripts and myriads of regulatory elements. The vast part of the genome is indeed transcribed into an RNA intermediate, but solely a small fraction is finally translated into functional proteins. The sweeping majority, however, is either degraded or functions as a non-protein coding RNA (ncRNA). Due to continuous developments in experimental and computational research, the variety of ncRNA classes grew larger and larger, ranging from key-processes in the cellular lifespan to regulatory processes that are driven and guided by ncRNAs. The bioinformatical part pri- marily concentrates on the prediction, annotation, and extraction of characteristic properties of novel ncRNAs. Due to conservation of sequence and/or structure, this task is often deter- mined by an homology-search that utilizes information about functional, and hence conserved regions, as an indicator. This thesis focuses mainly on a special class of ncRNAs, small nucleolar RNAs (snoRNAs). These abundant molecules are mainly responsible for the guidance of 2’-O-ribose-methylations and pseudouridylations in different types of RNAs, such as ribosomal and spliceosomal RNAs. Although the relevance of single modifications is still rather unclear, the elimination of a bunch of modifications is shown to cause severe effects, including lethality. Several de novo prediction programs have been published over the last years and a substantial amount of publicly available snoRNA databases has originated. Normally, these are restricted to a small amount of species and a collection of experimentally extracted snoRNA. The detection of snoRNAs by means of wet lab experiments and/or de novo prediction tools is generally time consuming (wet lab) and a quite tedious task (identification of snoRNA-specific characteristics). The snoRNA annotation pipeline snoStrip was developed with the intention to circumvent these obstacles. It therefore utilizes a homology-based search procedure to reliably predict snoRNA genes in genomic sequences. In a subsequent step, all candidates are filtered with respect to specific sequence motifs and secondary structures. In a functional analysis, poten- tial target sites are predicted in ribosomal and spliceosomal RNA sequences. In contrast to de novo prediction tools, snoStrip focuses on the extension of the known snoRNA world to uncharted organisms and the mapping and unification of the existing diversity of snoRNAs into functional, homologous families. The pipeline is properly suited to analyze a manifold set of organisms in search for their snoRNAome in short timescales. This offers the opportunity to generate large scale analyses over whole eukaryotic kingdoms to gain insights into the evolutionary history of these spe- cial ncRNA molecules. A set of experimentally validated snoRNA genes in Deuterostomia and Fungi were starting points for highly comprehensive surveys searching and analyzing the snoRNA repertoire in these two major eukaryotic clades. In both cases, the snoStrip pipeline proved itself as a fast and reliable tool and collected thousands of snoRNA genes in nearly 200 organisms. Additionally, the Interaction Conservation Index (ICI), which is am- plified to additionally work on single lineages, provides a convenient measure to analyze and evaluate the conservation of snoRNA-targetRNA interactions across different species. The massive amount of data and the possibility to score the conservation of predicted interactions constitute the main pillars to gain an extraordinary insight into the evolutionary history of snoRNAs on both the sequence and the functional level. A substantial part of the snoR- NAome is traceable down to the root of both eukaryotic lineages and might indicate an even more ancient origin of these snoRNAs. However, a plenitude of lineage specific innovation and deletion events are also discernible. Due to its automated detection of homologous and functionally related snoRNA sequences, snoStrip identified extraordinary target switches in fungi. These unveiled a coupled evolutionary history of several snoRNA families that were previously thought to be independent. Although these findings are exceedingly interesting, the broad majority of snoRNA families is found to show remarkable conservation of the se- quence and the predicted target interactions. On two occasions, this thesis will shift its focus from a genuine snoRNA inspection to an analysis of introns. Both investigations, however, are still conducted under an evolutionary viewpoint. In case of the ubiquitously present U3 snoRNA, functional genes in a notable amount of fungi are found to be disrupted by U2-dependent introns. The set of previously known U3 genes is considerably enlarged by an adapted snoStrip-search procedure. Intron- disrupted genes are found in several fungal lineages, while their precise insertion points within the snoRNA-precursor are located in a small and homologous region. A potential targetRNA of snoRNA genes, U6 snRNA, is also found to contain intronic sequences. Within this work, U6 genes are detected and annotated in nearly all fungal organisms. Although a few U6 intron- carrying genes have been known before, the widespread of these findings and the diversity regarding the particular insertion points are surprising. Those U6 genes are commonly found to contain more than just one intron. In both cases of intron-disrupted non-coding RNA genes, the detected RNA molecules seem to be functional and the intronic sequences show remarkable sequence conservation for both their splice sites and the branch site. In summary, the snoStrip pipeline is shown to be a reliable and fast prediction tool that works on homology-based search principles. Large scale analyses on whole eukaryotic lineages become feasible on short notice. Furthermore, the automated detection of functionally related but not yet mapped snoRNA families adds a new layer of information. Based on surveys covering the evolutionary history of Fungi and Deuterostomia, profound insights into the evolutionary history of this ncRNA class are revealed suggesting ancient origin for a main part of the snoRNAome. Lineage specific innovation and deletion events are also found to occur at a large number of distinct timepoints.

Most animals contain chronic microbial infections that inflict no harm on their hosts. Recently, the gut microflora of humans and other animals have been characterized. However, little is known about the forces that shape the diversity of these bacterial communities. In this work, comparative genomics was used to investigate the evolutionary dynamics of host-adapted bacterial communities, using Wolbachia infecting arthropods and Lactobacteria infecting bees as the main model systems. Wolbachia are maternally inherited bacteria that cause reproductive disorders in arthropods, such as feminization, male killing and parthenogenesis. These bacteria are difficult to study because they cannot be cultivated outside their hosts. We have developed a novel protocol employing multiple displacement amplification to isolate and sequence their genomes. Taxonomically, Wolbachia is classified into different supergroups. We have sequenced the genomes of Wolbachia strain wHa and wNo that belong to supergroup A and B, respectively, and are present as a double-infection in the fruit-fly Drosophila simulans. Together with previously published genomes, a supergroup comparison of strains belonging to supergroups A and B indicated rampant homologous recombination between strains that belong to the same supergroup but were isolated from different hosts. In contrast, we observed little recombination between strains of different supergroups that infect the same host. Likewise, phylogenetically distinct members of Lactic acid bacteria co-exist in the gut of the honeybee, Apis mellifera, without transfer of genes between phylotypes. Nor did we find any evidence of co-diversification between symbionts and hosts, as inferred from a study of 13 genomes of Lactobacillus kunkeei isolated from diverse bee species and different geographic origins. Although Lactobacillus kunkeii is the most frequently isolated strain from the honey stomach, we hypothesize that the primary niche is the beebread where the bacteria are likely to contribute to the fermentation process. In the human gut, the microbial community has been shown to interact with the immune system, and likewise the microbial communities associated with insects are thought to affect the health of their host. Therefore, a better understanding of the role and evolution of endosymbiotic communities is important for developing strategies to control the health of their hosts.

<p>Lymphomas are a heterogeneous group of hematological malignancies composed of diseases with diverse molecular origins and clinical outcomes. Derived from immune cells of lymphoid origin, lymphoma can arise from lymphoid cells present anywhere in the body, from the spleen and lymph nodes to peripheral sites like the liver and intestines. Current strategies for lymphoma diagnosis involve primarily histopathological examinations of the tumor biopsy, including cytogenetics and immunophenotyping. As more data becomes available, diagnoses may increasingly depend on genomic features that define each disease. Classification of lymphoid neoplasms is generally based on the cell of origin, or the lineage of the normal cell that the cancer is thought to arise from. Lymphomas can be classified into dozens of distinct diagnostic entities, though any two patients with the same diagnosis may have very different outcomes and molecular underpinnings, so we need to understand both the commonalities of patients with the same disease and the unique features that may require personalized treatment strategies. Patient prognosis in lymphoma depends greatly on the type of lymphoma, ranging from nearly curable diseases with over 90% five-year survival rates, to most patients dying in the first year in the worse entities. Greater clarity is needed in the role of the underlying genomics that contribute to these variable treatment responses and clinical outcomes. </p><p>Next-generation sequencing approaches allow us to delve into the molecular underpinnings of lymphomas, in order to gain insight about the origin and evolution of these diseases. High-throughput sequencing protocols allow us to examine the whole genome, exome, epigenome, or transcriptome of cancer cells in tens to hundreds of patients for each disease. As cost of sequencing is reduced, and the ability to generate more data increases, we face increasing computational challenges to both process and interpret the wealth of data available in cancer genomics. Developing efficient and effective bioinformatics tools is necessary to transform billions of sequencing reads into actionable hypotheses on the role of certain genes or biological pathways in a specific cancer type or patient. </p><p>In this dissertation, I present several strategies and applications of integrative computational genomics in lymphoma, with contributions throughout the research process, from development of initial assays and quality control strategies for the sequencing data, to joint analysis of clinical and genomic data, and finally through follow-up experimental models for lymphoma. </p><p>First, I focus on two rare T cell lymphomas, hepatosplenic T cell lymphoma (HSTL) and enteropathy associated T cell lymphoma (EATL), which are both diseases with very poor clinical outcomes and a previous dearth of knowledge on the genetic basis of the diseases. We define the somatic mutation landscape of HSTL, through application of exome sequencing and find SETD2 to be the most highly mutated gene. We further utilize the exome sequencing data to investigate copy number alterations and show a significant survival difference between cases with and without certain arm-level copy number alterations. Knockdown of SETD2 in an HSTL cell line, followed by RNA sequencing, demonstrates the role of SETD2 loss in proliferation and cell cycle changes, linking the SETD2 mutations to a potential oncogenic mechanism. Furthermore, we investigate the potentially targetable mutations in the JAK-STAT pathway and demonstrate oncogenic downstream molecular phenotypes and potential druggability of these mutations. In the enteropathy associated T cell lymphoma study, we apply exome and RNA sequencing to a large EATL cohort. Our findings show a significant role for loss of function mutations in chromatin modifiers and JAK-STAT signaling genes. EATL can be separated into two subtypes, Type I and Type II, which we show to have convergent genomic features, in the face of divergent gene expression. RNA sequencing data defines a distinct separation between the two subtypes. Delving further into the role of SETD2 in these T cell lymphomas, we generate a mouse model with a conditional knockout of SETD2 in T cells and demonstrate a role for SETD2 in altering the lineage development of T cells. </p><p>To understand more about why certain genetic abnormalities are recurrent in some disease entities and not others, we turn to the cell of origin for clues. We pair two different lymphomas, Burkitt lymphoma and mantle cell lymphoma, with their associated cells of origin, germinal center B cells and naive B cells. These closely related cell types have much in common as B cells, but from studies of their transcriptomes, we know that there are many molecular differences that distinguish the two. In this work, after looking more closely at mantle cell lymphoma genomics, we look at the underlying chromatin markers that define the epigenomes of these B cells. We test the association between chromatin markers and mutation rates of genes between these two cell types and lymphomas, and find that genes with more open chromatin may have a higher mutation rate, when comparing closely related cells and lymphomas. Finally, I present my work on developing an RNA sequencing based strategy for defining the complete transcriptome of diffuse large B cell lymphoma (DLBCL). Gene expression profiling with microarray has shown the existence of two subtypes in DLBCL, activated B cell like (ABC) and germinal center B cell like (GCB). However, the role for non-coding RNAs, alternative splicing, and mutations, in these two subtypes and the larger group is previously not well understood. We develop a strand-specific RNA sequencing strategy that will allow the investigation of the total RNA transcriptome in DLBCL, including microRNAs, lncRNAs, and other important non-coding RNAs. Furthermore, we show that RNA sequencing can be used to distinguish the two subtypes, including through RNA sequencing based mutation calls, as well as through differentially expressed lncRNAs that we define for the first time in DLBCL.</p><p>Broadly, this dissertation contributes novel findings in the field of lymphoma genomics, as well as presenting a framework for computational integrative genomics that can guide future studies. The heterogeneity of lymphoma across cases requires us to dive deep into individual diseases, even rare ones, as well as appreciate the similarities and differences across lymphomas. To improve diagnoses, prognoses, and treatment options, we need to understand the molecular origins of lymphoma. Using a range of molecular and computational approaches, we can move closer to true personalized medicine at the genomic level.</p> / Dissertation

Ciliopathies are a group of disorders that arise from ciliary dysfunction. Meckelin (MKS3 or TMEM67) is a conserved transmembrane protein found at the transition zone of ciliated cells. In humans MKS3 is one of 3 genes linked to the ciliopathy Meckel Syndrome. This disease is characterized by occipital meningioencephalocoele, polycystic kidneys, fibrotic changes to the liver, postnatal polydactyly and situs inversus. Paramecium tetraurelia is a single celled ciliated eukaryote. Its surface is organized of a meshwork of cortical units that run the length of the cell. At the center of the cortical units are either one or two basal bodies. In two basal body units only the posterior basal body is ciliated. From the ciliated basal body, three rootlets project in stereotypical orientations: the post-ciliary rootlet projects posteriorly, the transverse microtubule projects toward the adjacent basal body row and the striated rootlet projects anteriorly. Both the post-ciliary rootlet and transverse microtubule are microtubule-based structures. The striated rootlet is composed of multiple subunits that are predicted to have conserved segmented coiled coil domains known as SF-Assemblin domains. In Picariello at al., 2014, we showed that MKS3 is present in the transition zone of Paramecium tetraurelia and that RNAi for MKS3 leads to global ciliary loss. Additionally, RNAi for MKS3 results in the disorganization of the basal body rows. Within the areas of disorganization, the basal bodies along with their striated rootlets, post-ciliary rootlets and transverse microtubules are rotated away from their expected orientation. Interestingly, the post-ciliary rootlet and transverse microtubule are still attached at the expected angles relative to each other within the areas of disorganization. Initial GST pull-down experiments using the coiled coil domain of MKS3 suggest a potential interaction between MKS3 and the striated rootlet family members KdC1 and KdB2. To test potential interactions between MKS3 and the striated rootlet we identified 27 potential striated rootlet family members in Paramecium. Full-length sequences for 13 of these genes were marked at their N-terminus with a 3x FLAG sequence. Components with a conserved SF-Assemblin domain were distributed uniformly within the striated rootlet. Components lacking the SF-Assemblin domain were found in various cellular locations, but not within the striated rootlet. GST pull-down experiments utilizing the MKS3 C-terminus as bait were performed using cells expressing the FLAG-tagged striated rootlet family members. Unfortunately a clear interaction between MKS3 and the striated rootlet remains elusive. The organized nature of the surface of Paramecium has allowed us to identify a previously unrealized function for MKS3. Our immunofluorescence data suggest that MKS3 functions outside the transition zone to maintain basal body row organization by potentially contributing to a link between the basal body and the striated rootlet. Without the link, the migrating basal bodies are free to rotate and project their rootlets in the wrong directions. Although the nature of the link remains elusive, the identification of disorganized basal body rows upon MKS3 reduction suggests that, in addition to ciliary dysfunction, basal body polarity defects may contribute to the development of MKS.

Alcohol use disorders (AUDs) are major health issues with few known genetic explanations. This project used the fruit fly (Drosophila melanogaster) model to identify genes and gene networks that influence alcohol intoxication, a phenotype related to alcohol abuse in humans. We used bioinformatic tools to build gene networks based on 24 published Drosophila ethanol-responsive genes with human orthologs. We then assessed the role of these networks in ethanol sedation by testing two of the networks seeded on IP3K2, a gene that regulates calcium signaling, and CG14630, a gene involved in carnitine biosynthesis. We knocked down several genes in each of the networks using RNAi and tested the knockdown flies in a behavioral assay for ethanol sedation. Nervous system RNAi expression against 7 of 20 genes in the IP3K2 network and 4 of 30 genes in the CG14630 network significantly affected the sensitivity of flies to ethanol. To determine whether the hit rates in these two networks were greater than would be expected by random chance alone, we also assessed the effects of nervous system RNAi targeting a random set of fly genes. Unexpectedly, the fraction of randomly selected genes that affected ethanol sensitivity in a primary screen was comparable to or even larger than that from bioinformatically-derived gene networks. Our data are consistent with two possibilities that are not mutually exclusive. One possibility is that there are a very large number of genes that impact ethanol sedation and our bioinformatic analyses did not substantially enrich for these genes. A second possibility is that expression of RNAi could influence ethanol sedation independent of target gene knock-down. These two possibilities will be examined in future experiments.

Alcoholism is a complex neurological disorder characterized by loss of control in limiting intake, compulsion to seek and imbibe ethanol, and chronic craving and relapse. It is suggested that the characteristic behaviors associated with the escalation of drug use are caused by long-term molecular adaptations precipitated by the drug’s continual administration. These lasting activity-dependent changes that underlie addiction-associated behavior are thought, in part, to depend on new protein synthesis and remodeling at the synapses. It is well established that mRNA can be transported to neuronal distal processes, where it can undergo localized translation that is regulated in a spatially restricted manner in response to stimulation. Through two avenues of investigation, the research herein demonstrates that behavioral responses to ethanol result, at least in part, from alterations in the synaptic transcriptome which contribute to synaptic remodeling and plasticity. The synaptoneurosome preparation was utilized to enrich for RNAs trafficked to the synapse. Two complementary methods of genomic profiling, microarrays and RNA-Seq, were used to survey the synaptic transcriptome of DBA/2J mice subjected to ethanol-induced behavioral sensitization. A habituating expression profile, characteristic of glucocorticoid-responsive genes, was observed for a portion of synaptically targeted genes determined to be sensitive to repeated ethanol exposure. Other ethanol-responsive genes significantly enriched for at the synapse were related to biological functions such as protein folding and extra-cellular matrix components, suggesting a role for local regulation of synaptic functioning by ethanol. In a separate series of experiments, it was shown that altered trafficking of Bdnf, an ethanol-responsive gene, resulted in aberrant ethanol behavioral phenotypes. In particular, mice lacking dendritically targeted Bdnf mRNA exhibited enhanced sensitivity to low, activating doses and high, sedating doses of ethanol. Together these experiments suggest that ethanol has local regulatory effects at the synapse and lays the foundation for further investigations into the role of the synaptic transcriptome in ethanol-responsive behaviors. Supported by NIAA grants R01AA014717, U01 AA016667 and P20AA017828 to MFM, F31AA021035 to MAO, and NIDA T32DA007027 to WLD.

The nucleosome remodeling factor (NURF) is an evolutionary conserved ATP-dependent chromatin remodeling factor. It was first isolated from Drosophila as a complex with enzymatic activity that once recruited to nucleosome, it slides the nucleosome to provide accessibility for transcription factors. Since then, numerous works from animal models and cell lines show the role of NURF as a regulator of gene expression. NURF interacts with H3K4me3 and sequence specific transcription factors that recruit the complex to promoter regions. Whether this is the only mechanism by which NURF regulates gene expression is not known. However, other ATP-dependent chromatin remodeling complexes are known to regulate gene expression independent from transcription initiation. In order to explore the role of NURF in regulating gene expression, we utilized two genome wide approaches to map NURF binding and NURF dependent changes in chromatin structure using ChIP-Seq and FAIRE-Seq, respectively. From these analyses, we discovered that NURF broadly localizes in the genome with preferences to gene bodies and 3’ends of genes. Also, we found that NURF maintains open chromatin regions at upstream, intron and downstream of genes. These novel findings shed light on new roles for NURF complex within genes, in addition to its classical role at promoter regions. Furthermore, we discovered the function of a previously uncharacterized domain in the NURF specific subunit BPTF. We show that the N-terminal the plant homeodomain (PHD) of BPTF directly interacts with THOC4, a protein associated with RNA-pol 2. Also, we show using ChIP analyses that this interaction recruits BPTF to gene bodies. Next, we investigated functional consequences for NURF recruitment to gene bodies using Cyclin D1 (Ccnd1) gene as a model. These analyses revealed that NURF is required for normal mRNA processing and loss of NURF induces intron retention, which results in unstable transcripts. Finally, we show that the defect in mRNA processing is not specific to the Ccnd1 gene, as we observe similar defects in four other BPTF dependent genes. Together, our work uncovered new role of mammalian NURF complex in regulating gene expression through mRNA processing.