Richard Park
Harvard University
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Publication
Featured researches published by Richard Park.
Nature | 2011
Peter V. Kharchenko; Artyom A. Alekseyenko; Yuri B. Schwartz; Aki Minoda; Nicole C. Riddle; Jason Ernst; Peter J. Sabo; Erica Larschan; Andrey A. Gorchakov; Tingting Gu; Daniela Linder-Basso; Annette Plachetka; Gregory Shanower; Michael Y. Tolstorukov; Lovelace J. Luquette; Ruibin Xi; Youngsook L. Jung; Richard Park; Eric P. Bishop; Theresa P. Canfield; Richard Sandstrom; Robert E. Thurman; David M. MacAlpine; John A. Stamatoyannopoulos; Manolis Kellis; Sarah C. R. Elgin; Mitzi I. Kuroda; Vincenzo Pirrotta; Gary H. Karpen; Peter J. Park
Chromatin is composed of DNA and a variety of modified histones and non-histone proteins, which have an impact on cell differentiation, gene regulation and other key cellular processes. Here we present a genome-wide chromatin landscape for Drosophila melanogaster based on eighteen histone modifications, summarized by nine prevalent combinatorial patterns. Integrative analysis with other data (non-histone chromatin proteins, DNase I hypersensitivity, GRO-Seq reads produced by engaged polymerase, short/long RNA products) reveals discrete characteristics of chromosomes, genes, regulatory elements and other functional domains. We find that active genes display distinct chromatin signatures that are correlated with disparate gene lengths, exon patterns, regulatory functions and genomic contexts. We also demonstrate a diversity of signatures among Polycomb targets that include a subset with paused polymerase. This systematic profiling and integrative analysis of chromatin signatures provides insights into how genomic elements are regulated, and will serve as a resource for future experimental investigations of genome structure and function.
Nature | 2014
Joshua W. K. Ho; Youngsook L. Jung; Tao Liu; Burak H. Alver; Soohyun Lee; Kohta Ikegami; Kyung Ah Sohn; Aki Minoda; Michael Y. Tolstorukov; Alex Appert; Stephen C. J. Parker; Tingting Gu; Anshul Kundaje; Nicole C. Riddle; Eric P. Bishop; Thea A. Egelhofer; Sheng'En Shawn Hu; Artyom A. Alekseyenko; Andreas Rechtsteiner; Dalal Asker; Jason A. Belsky; Sarah K. Bowman; Q. Brent Chen; Ron Chen; Daniel S. Day; Yan Dong; Andréa C. Dosé; Xikun Duan; Charles B. Epstein; Sevinc Ercan
Genome function is dynamically regulated in part by chromatin, which consists of the histones, non-histone proteins and RNA molecules that package DNA. Studies in Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular mechanisms of genome function in humans, and have revealed conservation of chromatin components and mechanisms. Nevertheless, the three organisms have markedly different genome sizes, chromosome architecture and gene organization. On human and fly chromosomes, for example, pericentric heterochromatin flanks single centromeres, whereas worm chromosomes have dispersed heterochromatin-like regions enriched in the distal chromosomal ‘arms’, and centromeres distributed along their lengths. To systematically investigate chromatin organization and associated gene regulation across species, we generated and analysed a large collection of genome-wide chromatin data sets from cell lines and developmental stages in worm, fly and human. Here we present over 800 new data sets from our ENCODE and modENCODE consortia, bringing the total to over 1,400. Comparison of combinatorial patterns of histone modifications, nuclear lamina-associated domains, organization of large-scale topological domains, chromatin environment at promoters and enhancers, nucleosome positioning, and DNA replication patterns reveals many conserved features of chromatin organization among the three organisms. We also find notable differences in the composition and locations of repressive chromatin. These data sets and analyses provide a rich resource for comparative and species-specific investigations of chromatin composition, organization and function.
Cancer Research | 2011
Tae-Min Kim; Wei Huang; Richard Park; Peter J. Park; Mark D. Johnson
mRNA expression profiling has suggested the existence of multiple glioblastoma subclasses, but their number and characteristics vary among studies and the etiology underlying their development is unclear. In this study, we analyzed 261 microRNA expression profiles from The Cancer Genome Atlas (TCGA), identifying five clinically and genetically distinct subclasses of glioblastoma that each related to a different neural precursor cell type. These microRNA-based glioblastoma subclasses displayed microRNA and mRNA expression signatures resembling those of radial glia, oligoneuronal precursors, neuronal precursors, neuroepithelial/neural crest precursors, or astrocyte precursors. Each subclass was determined to be genetically distinct, based on the significant differences they displayed in terms of patient race, age, treatment response, and survival. We also identified several microRNAs as potent regulators of subclass-specific gene expression networks in glioblastoma. Foremost among these is miR-9, which suppresses mesenchymal differentiation in glioblastoma by downregulating expression of JAK kinases and inhibiting activation of STAT3. Our findings suggest that microRNAs are important determinants of glioblastoma subclasses through their ability to regulate developmental growth and differentiation programs in several transformed neural precursor cell types. Taken together, our results define developmental microRNA expression signatures that both characterize and contribute to the phenotypic diversity of glioblastoma subclasses, thereby providing an expanded framework for understanding the pathogenesis of glioblastoma in a human neurodevelopmental context.
Molecular Cancer | 2015
Richard Park; Tae-Min Kim; Simon Kasif; Peter J. Park
BackgroundCopy number variations (CNVs) are increasingly recognized as significant disease susceptibility markers in many complex disorders including cancer. The availability of a large number of chromosomal copy number profiles in both malignant and normal tissues in cancer patients presents an opportunity to characterize not only somatic alterations but also germline CNVs, which may confer increased risk for cancer.ResultsWe explored the germline CNVs in five cancer cohorts from the Cancer Genome Atlas (TCGA) consisting of 351 brain, 336 breast, 342 colorectal, 370 renal, and 314 ovarian cancers, genotyped on Affymetrix SNP6.0 arrays. Comparing these to ~3000 normal controls from another study, our case–control association study revealed 39 genomic loci (9 brain, 3 breast, 4 colorectal, 11 renal, and 12 ovarian cancers) as potential candidates of tumor susceptibility loci. Many of these loci are new and in some cases are associated with a substantial increase in disease risk. The majority of the observed loci do not overlap with coding sequences; however, several observed genomic loci overlap with known cancer genes including RET in brain cancers, ERBB2 in renal cell carcinomas, and DCC in ovarian cancers, all of which have not been previously associated with germline changes in cancer.ConclusionsThis large-scale genome-wide association study for CNVs across multiple cancer types identified several novel rare germline CNVs as cancer predisposing genomic loci. These loci can potentially serve as clinically useful markers conferring increased cancer risk.
Genome Research | 2013
Tae-Min Kim; Ruibin Xi; Lovelace J. Luquette; Richard Park; Mark D. Johnson; Peter J. Park
Neoplasia | 2012
Hong Wei Yang; Tae-Min Kim; Sydney S. Song; Nihal Shrinath; Richard Park; Michel Kalamarides; Peter J. Park; Peter McL. Black; Rona S. Carroll; Mark D. Johnson
Archive | 2014
W. K. Ho; Youngsook L. Jung; Tao Liu; Burak H. Alver; Soohyun Lee; Kohta Ikegami; Kyung-Ah Sohn; Aki Minoda; Michael Y. Tolstorukov; Alex Appert; Stephen C. J. Parker; Tingting Gu; Nicole C. Riddle; Eric P. Bishop; Thea A. Egelhofer; Artyom A. Alekseyenko; Andreas Rechtsteiner; Dalal Asker; Jason A. Belsky; Sarah K. Bowman; Q. Brent Chen; Daniel S. Day; Yan Dong; Andréa C. Dosé; Charles B. Epstein; Sevinc Ercan; Elise A. Feingold; Francesco Ferrari; Jacob M. Garrigues; Nils Gehlenborg
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science | 2013
Shannan J. Ho Sui; Emily Merrill; Nils Gehlenborg; Psalm Haseley; Ilya Sytchev; Richard Park; Philippe Rocca-Serra; Stéphane Corlosquet; Alejandra Gonzalez-Beltran; Eamonn Maguire; Oliver Hofmann; Peter J. Park; Sudeshna Das; Susanna-Assunta Sansone; Winston Hide
F1000Research | 2016
Nils Gehlenborg; Shannan J. Ho Sui; Ilya Sytchev; Stefan Luger; Fritz Lekschas; Richard Park; Jennifer Marx; Scott Ouellette; David R Jones; Anton Xue; Psalm Haseley; Marc Streit; Winston Hide; Peter J. Park