Publications by Year: 2007

Larschan E, Alekseyenko AA, Gortchakov AA, Peng S, Li B, Yang P, Workman JL, Park PJ, Kuroda MI. MSL complex is attracted to genes marked by H3K36 trimethylation using a sequence-independent mechanism. Mol Cell 2007;28(1):121-33.Abstract

In Drosophila, X chromosome dosage compensation requires the male-specific lethal (MSL) complex, which associates with actively transcribed genes on the single male X chromosome to upregulate transcription approximately 2-fold. We found that on the male X chromosome, or when MSL complex is ectopically localized to an autosome, histone H3K36 trimethylation (H3K36me3) is a strong predictor of MSL binding. We isolated mutants lacking Set2, the H3K36me3 methyltransferase, and found that Set2 is an essential gene in both sexes of Drosophila. In set2 mutant males, MSL complex maintains X specificity but exhibits reduced binding to target genes. Furthermore, recombinant MSL3 protein preferentially binds nucleosomes marked by H3K36me3 in vitro. Our results support a model in which MSL complex uses high-affinity sites to initially recognize the X chromosome and then associates with many of its targets through sequence-independent features of transcribed genes.

Liu M, Liberzon A, Kong SW, Lai WR, Park PJ, Kohane IS, Kasif S. Network-based analysis of affected biological processes in type 2 diabetes models. PLoS Genet 2007;3(6):e96.Abstract

Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies present an unprecedented opportunity to study type 2 diabetes mellitus at a genome-wide scale and across different models. To date, a key challenge has been to identify the biological processes or signaling pathways that play significant roles in the disorder. Here, using a network-based analysis methodology, we identified two sets of genes, associated with insulin signaling and a network of nuclear receptors, which are recurrent in a statistically significant number of diabetes and insulin resistance models and transcriptionally altered across diverse tissue types. We additionally identified a network of protein-protein interactions between members from the two gene sets that may facilitate signaling between them. Taken together, the results illustrate the benefits of integrating high-throughput microarray studies, together with protein-protein interaction networks, in elucidating the underlying biological processes associated with a complex disorder.

Peng S, Alekseyenko AA, Larschan E, Kuroda MI, Park PJ. Normalization and experimental design for ChIP-chip data. BMC Bioinformatics 2007;8:219.Abstract

BACKGROUND: Chromatin immunoprecipitation on tiling arrays (ChIP-chip) has been widely used to investigate the DNA binding sites for a variety of proteins on a genome-wide scale. However, several issues in the processing and analysis of ChIP-chip data have not been resolved fully, including the effect of background (mock control) subtraction and normalization within and across arrays. RESULTS: The binding profiles of Drosophila male-specific lethal (MSL) complex on a tiling array provide a unique opportunity for investigating these topics, as it is known to bind on the X chromosome but not on the autosomes. These large bound and control regions on the same array allow clear evaluation of analytical methods.We introduce a novel normalization scheme specifically designed for ChIP-chip data from dual-channel arrays and demonstrate that this step is critical for correcting systematic dye-bias that may exist in the data. Subtraction of the mock (non-specific antibody or no antibody) control data is generally needed to eliminate the bias, but appropriate normalization obviates the need for mock experiments and increases the correlation among replicates. The idea underlying the normalization can be used subsequently to estimate the background noise level in each array for normalization across arrays. We demonstrate the effectiveness of the methods with the MSL complex binding data and other publicly available data. CONCLUSION: Proper normalization is essential for ChIP-chip experiments. The proposed normalization technique can correct systematic errors and compensate for the lack of mock control data, thus reducing the experimental cost and producing more accurate results.