Person:

Ho, Joshua Wing Kei

The Drosophila MSL complex mediates dosage compensation by increasing transcription of the single X chromosome in males approximately two-fold. This is accomplished through recognition of the X chromosome and subsequent acetylation of histone H4K16 on X-linked genes. Initial binding to the X is thought to occur at “entry sites” that contain a consensus sequence motif (“MSL recognition element” or MRE). However, this motif is only (\sim)2 fold enriched on X, and only a fraction of the motifs on X are initially targeted. Here we ask whether chromatin context could distinguish between utilized and non-utilized copies of the motif, by comparing their relative enrichment for histone modifications and chromosomal proteins mapped in the modENCODE project. Through a comparative analysis of the chromatin features in male S2 cells (which contain MSL complex) and female Kc cells (which lack the complex), we find that the presence of active chromatin modifications, together with an elevated local GC content in the surrounding sequences, has strong predictive value for functional MSL entry sites, independent of MSL binding. We tested these sites for function in Kc cells by RNAi knockdown of Sxl, resulting in induction of MSL complex. We show that ectopic MSL expression in Kc cells leads to H4K16 acetylation around these sites and a relative increase in X chromosome transcription. Collectively, our results support a model in which a pre-existing active chromatin environment, coincident with H3K36me3, contributes to MSL entry site selection. The consequences of MSL targeting of the male X chromosome include increase in nucleosome lability, enrichment for H4K16 acetylation and JIL-1 kinase, and depletion of linker histone H1 on active X-linked genes. Our analysis can serve as a model for identifying chromatin and local sequence features that may contribute to selection of functional protein binding sites in the genome.

The diagnosis of Systemic Lupus Erythematosus (SLE) is challenging due to its heterogeneous clinical presentation and the lack of robust biomarkers to distinguish it from other autoimmune diseases. Further, currently used laboratory tests do not readily distinguish active and inactive disease. Several groups have attempted to apply emerging high throughput profiling technologies to diagnose and monitor SLE. Despite showing promise, many are expensive and technically challenging for routine clinical use. The goal of this work is to develop a better diagnostic and monitoring tool for SLE. We report a highly customisable antibody microarray that consists of a duplicate arrangement of 82 antibodies directed against surface antigens on peripheral blood mononuclear cells (PMBCs). This high-throughput array was used to profile SLE patients (n = 60) with varying disease activity, compared to healthy controls (n = 24), patients with rheumatoid arthritis (n = 25), and other autoimmune diseases (n = 28). We used a computational algorithm to calculate a score from the entire microarray profile and correlated it with SLE disease activity. Our results demonstrate that leukocyte-capture microarray profiles can readily distinguish active SLE patients from healthy controls (AUROC = 0.84). When combined with the standard laboratory tests (serum anti-dsDNA, complements C3 and C4), the microarrays provide significantly increased discrimination. The antibody microarrays can be enhanced by the addition of other markers for potential application to the diagnosis and stratification of SLE, paving the way for the customised and accurate diagnosis and monitoring of SLE.

To elucidate the transcriptional regulation of Bmp4 expression during organogenesis, we used phylogenetic footprinting and transgenic reporter analyses to identify Bmp4 cis-regulatory modules (CRMs). These analyses identified a regulatory region located (\sim)46 kb upstream of the mouse Bmp4 transcription start site that had previously been shown to direct expression in lateral plate mesoderm. We refined this regulatory region to a 396-bp minimal enhancer, and show that it recapitulates features of endogenous Bmp4 expression in developing mandibular arch ectoderm and incisor epithelium during the initiation-stage of tooth development. In addition, this enhancer directs expression in the apical ectodermal ridge (AER) of the developing limb and in anterior and posterior limb mesenchyme. Transcript profiling of E11.5 mouse incisor dental lamina, together with protein binding microarray (PBM) analyses, allowed identification of a conserved DNA binding motif in the Bmp4 enhancer for Pitx homeoproteins, which are also expressed in the developing mandibular and incisor epithelium. In vitro electrophoretic mobility shift assays (EMSA) and in vivo transgenic reporter mutational analyses revealed that this site supports Pitx binding and that the site is necessary to recapitulate aspects of endogenous Bmp4 expression in developing craniofacial and limb tissues. Finally, Pitx2 chromatin immunoprecipitation (ChIP) demonstrated direct binding of Pitx2 to this Bmp4 enhancer site in a dental epithelial cell line. These results establish a direct molecular regulatory link between Pitx family members and Bmp4 gene expression in developing incisor epithelium.

Background: Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of Drosophila melanogaster. Results: Both technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis. Conclusions: Our findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis.