Bio

Professional Education


  • Doctor of Philosophy, Duke University (2009)
  • Bachelor of Science, Mississippi State University, Biochemistry & Molecular Biology (2005)
  • Bachelor of Science, Mississippi State University, Computer Science (2005)

Stanford Advisors


Publications

Journal Articles


  • Extensive Variation in Chromatin States Across Humans SCIENCE Kasowski, M., Kyriazopoulou-Panagiotopoulou, S., Grubert, F., Zaugg, J. B., Kundaje, A., Liu, Y., Boyle, A. P., Zhang, Q. C., Zakharia, F., Spacek, D. V., Li, J., Xie, D., Olarerin-George, A., Steinmetz, L. M., Hogenesch, J. B., Kellis, M., Batzoglou, S., Snyder, M. 2013; 342 (6159): 750-752

    Abstract

    The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.

    View details for DOI 10.1126/science.1242510

    View details for Web of Science ID 000326647600047

    View details for PubMedID 24136358

  • An integrated encyclopedia of DNA elements in the human genome NATURE Dunham, I., Kundaje, A., Aldred, S. F., Collins, P. J., Davis, C., Doyle, F., Epstein, C. B., Frietze, S., Harrow, J., Kaul, R., Khatun, J., Lajoie, B. R., Landt, S. G., Lee, B., Pauli, F., Rosenbloom, K. R., Sabo, P., Safi, A., Sanyal, A., Shoresh, N., Simon, J. M., Song, L., Trinklein, N. D., Altshuler, R. C., Birney, E., Brown, J. B., Cheng, C., Djebali, S., Dong, X., Dunham, I., Ernst, J., Furey, T. S., Gerstein, M., Giardine, B., Greven, M., Hardison, R. C., Harris, R. S., Herrero, J., Hoffman, M. M., Iyer, S., Kellis, M., Khatun, J., Kheradpour, P., Kundaje, A., Lassmann, T., Li, Q., Lin, X., Marinov, G. K., Merkel, A., Mortazavi, A., Parker, S. C., Reddy, T. E., Rozowsky, J., Schlesinger, F., Thurman, R. E., Wang, J., Ward, L. D., Whitfield, T. W., Wilder, S. P., Wu, W., Xi, H. S., Yip, K. Y., Zhuang, J., Bernstein, B. E., Birney, E., Dunham, I., Green, E. D., Gunter, C., Snyder, M., Pazin, M. J., Lowdon, R. F., Dillon, L. A., Adams, L. B., Kelly, C. J., Zhang, J., Wexler, J. R., Green, E. D., Good, P. J., Feingold, E. A., Bernstein, B. E., Birney, E., Crawford, G. E., Dekker, J., Elnitski, L., Farnham, P. J., Gerstein, M., Giddings, M. C., Gingeras, T. R., Green, E. D., Guigo, R., Hardison, R. C., Hubbard, T. J., Kellis, M., Kent, W. J., Lieb, J. D., Margulies, E. H., Myers, R. M., Snyder, M., Stamatoyannopoulos, J. A., Tenenbaum, S. A., Weng, Z., White, K. P., Wold, B., Khatun, J., Yu, Y., Wrobel, J., Risk, B. A., Gunawardena, H. P., Kuiper, H. C., Maier, C. W., Xie, L., Chen, X., Giddings, M. C., Bernstein, B. E., Epstein, C. B., Shoresh, N., Ernst, J., Kheradpour, P., Mikkelsen, T. S., Gillespie, S., Goren, A., Ram, O., Zhang, X., Wang, L., Issner, R., Coyne, M. J., Durham, T., Ku, M., Truong, T., Ward, L. D., Altshuler, R. C., Eaton, M. L., Kellis, M., Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., Xue, C., Marinov, G. K., Khatun, J., Williams, B. A., Zaleski, C., Rozowsky, J., Roeder, M., Kokocinski, F., Abdelhamid, R. F., Alioto, T., Antoshechkin, I., Baer, M. T., Batut, P., Bell, I., Bell, K., Chakrabortty, S., Chen, X., Chrast, J., Curado, J., Derrien, T., Drenkow, J., Dumais, E., Dumais, J., Duttagupta, R., Fastuca, M., Fejes-Toth, K., Ferreira, P., Foissac, S., Fullwood, M. J., Gao, H., Gonzalez, D., Gordon, A., Gunawardena, H. P., Howald, C., Jha, S., Johnson, R., Kapranov, P., King, B., Kingswood, C., Li, G., Luo, O. J., Park, E., Preall, J. B., Presaud, K., Ribeca, P., Risk, B. A., Robyr, D., Ruan, X., Sammeth, M., Sandhu, K. S., Schaeffer, L., See, L., Shahab, A., Skancke, J., Suzuki, A. M., Takahashi, H., Tilgner, H., Trout, D., Walters, N., Wang, H., Wrobel, J., Yu, Y., Hayashizaki, Y., Harrow, J., Gerstein, M., Hubbard, T. J., Reymond, A., Antonarakis, S. E., Hannon, G. J., Giddings, M. C., Ruan, Y., Wold, B., Carninci, P., Guigo, R., Gingeras, T. R., Rosenbloom, K. R., Sloan, C. A., Learned, K., Malladi, V. S., Wong, M. C., Barber, G., Cline, M. S., Dreszer, T. R., Heitner, S. G., Karolchik, D., Kent, W. J., Kirkup, V. M., Meyer, L. R., Long, J. C., Maddren, M., Raney, B. J., Furey, T. S., Song, L., Grasfeder, L. L., Giresi, P. G., Lee, B., Battenhouse, A., Sheffield, N. C., Simon, J. M., Showers, K. A., Safi, A., London, D., Bhinge, A. A., Shestak, C., Schaner, M. R., Kim, S. K., Zhang, Z. Z., Mieczkowski, P. A., Mieczkowska, J. O., Liu, Z., McDaniell, R. M., Ni, Y., Rashid, N. U., Kim, M. J., Adar, S., Zhang, Z., Wang, T., Winter, D., Keefe, D., Birney, E., Iyer, V. R., Lieb, J. D., Crawford, G. E., Li, G., Sandhu, K. S., Zheng, M., Wang, P., Luo, O. J., Shahab, A., Fullwood, M. J., Ruan, X., Ruan, Y., Myers, R. M., Pauli, F., Williams, B. A., Gertz, J., Marinov, G. K., Reddy, T. E., Vielmetter, J., Partridge, E. C., Trout, D., Varley, K. E., Gasper, C., Bansal, A., Pepke, S., Jain, P., Amrhein, H., Bowling, K. M., Anaya, M., Cross, M. K., King, B., Muratet, M. A., Antoshechkin, I., Newberry, K. M., McCue, K., Nesmith, A. S., Fisher-Aylor, K. I., Pusey, B., DeSalvo, G., Parker, S. L., Balasubramanian, S., Davis, N. S., Meadows, S. K., Eggleston, T., Gunter, C., Newberry, J. S., Levy, S. E., Absher, D. M., Mortazavi, A., Wong, W. H., Wold, B., Blow, M. J., Visel, A., Pennachio, L. A., Elnitski, L., Margulies, E. H., Parker, S. C., Petrykowska, H. M., Abyzov, A., Aken, B., Barrell, D., Barson, G., Berry, A., Bignell, A., Boychenko, V., Bussotti, G., Chrast, J., Davidson, C., Derrien, T., Despacio-Reyes, G., Diekhans, M., Ezkurdia, I., Frankish, A., Gilbert, J., Gonzalez, J. M., Griffiths, E., Harte, R., Hendrix, D. A., Howald, C., Hunt, T., Jungreis, I., Kay, M., Khurana, E., Kokocinski, F., Leng, J., Lin, M. F., Loveland, J., Lu, Z., Manthravadi, D., Mariotti, M., Mudge, J., Mukherjee, G., Notredame, C., Pei, B., Rodriguez, J. M., Saunders, G., Sboner, A., Searle, S., Sisu, C., Snow, C., Steward, C., Tanzer, A., Tapanari, E., Tress, M. L., van Baren, M. J., Walters, N., Washietl, S., Wilming, L., Zadissa, A., Zhang, Z., Brent, M., Haussler, D., Kellis, M., Valencia, A., Gerstein, M., Reymond, A., Guigo, R., Harrow, J., Hubbard, T. J., Landt, S. G., Frietze, S., Abyzov, A., Addleman, N., Alexander, R. P., Auerbach, R. K., Balasubramanian, S., Bettinger, K., Bhardwaj, N., Boyle, A. P., Cao, A. R., Cayting, P., Charos, A., Cheng, Y., Cheng, C., Eastman, C., Euskirchen, G., Fleming, J. D., Grubert, F., Habegger, L., Hariharan, M., Harmanci, A., Iyengar, S., Jin, V. X., Karczewski, K. J., Kasowski, M., Lacroute, P., Lam, H., Lamarre-Vincent, N., Leng, J., Lian, J., Lindahl-Allen, M., Min, R., Miotto, B., Monahan, H., Moqtaderi, Z., Mu, X. J., O'Geen, H., Ouyang, Z., Patacsil, D., Pei, B., Raha, D., Ramirez, L., Reed, B., Rozowsky, J., Sboner, A., Shi, M., Sisu, C., Slifer, T., Witt, H., Wu, L., Xu, X., Yan, K., Yang, X., Yip, K. Y., Zhang, Z., Struhl, K., Weissman, S. M., Gerstein, M., Farnham, P. J., Snyder, M., Tenenbaum, S. A., Penalva, L. O., Doyle, F., Karmakar, S., Landt, S. G., Bhanvadia, R. R., Choudhury, A., Domanus, M., Ma, L., Moran, J., Patacsil, D., Slifer, T., Victorsen, A., Yang, X., Snyder, M., White, K. P., Auer, T., Centanin, L., Eichenlaub, M., Gruhl, F., Heermann, S., Hoeckendorf, B., Inoue, D., Kellner, T., Kirchmaier, S., Mueller, C., Reinhardt, R., Schertel, L., Schneider, S., Sinn, R., Wittbrodt, B., Wittbrodt, J., Weng, Z., Whitfield, T. W., Wang, J., Collins, P. J., Aldred, S. F., Trinklein, N. D., Partridge, E. C., Myers, R. M., Dekker, J., Jain, G., Lajoie, B. R., Sanyal, A., Balasundaram, G., Bates, D. L., Byron, R., Canfield, T. K., Diegel, M. J., Dunn, D., Ebersol, A. K., Frum, T., Garg, K., Gist, E., Hansen, R. S., Boatman, L., Haugen, E., Humbert, R., Jain, G., Johnson, A. K., Johnson, E. M., Kutyavin, T. V., Lajoie, B. R., Lee, K., Lotakis, D., Maurano, M. T., Neph, S. J., Neri, F. V., Nguyen, E. D., Qu, H., Reynolds, A. P., Roach, V., Rynes, E., Sabo, P., Sanchez, M. E., Sandstrom, R. S., Sanyal, A., Shafer, A. O., Stergachis, A. B., Thomas, S., Thurman, R. E., Vernot, B., Vierstra, J., Vong, S., Wang, H., Weaver, M. A., Yan, Y., Zhang, M., Akey, J. M., Bender, M., Dorschner, M. O., Groudine, M., MacCoss, M. J., Navas, P., Stamatoyannopoulos, G., Kaul, R., Dekker, J., Stamatoyannopoulos, J. A., Dunham, I., Beal, K., Brazma, A., Flicek, P., Herrero, J., Johnson, N., Keefe, D., Lukk, M., Luscombe, N. M., Sobral, D., Vaquerizas, J. M., Wilder, S. P., Batzoglou, S., Sidow, A., Hussami, N., Kyriazopoulou-Panagiotopoulou, S., Libbrecht, M. W., Schaub, M. A., Kundaje, A., Hardison, R. C., Miller, W., Giardine, B., Harris, R. S., Wu, W., Bickel, P. J., Banfai, B., Boley, N. P., Brown, J. B., Huang, H., Li, Q., Li, J. J., Noble, W. S., Bilmes, J. A., Buske, O. J., Hoffman, M. M., Sahu, A. D., Kharchenko, P. V., Park, P. J., Baker, D., Taylor, J., Weng, Z., Iyer, S., Dong, X., Greven, M., Lin, X., Wang, J., Xi, H. S., Zhuang, J., Gerstein, M., Alexander, R. P., Balasubramanian, S., Cheng, C., Harmanci, A., Lochovsky, L., Min, R., Mu, X. J., Rozowsky, J., Yan, K., Yip, K. Y., Birney, E. 2012; 489 (7414): 57-74

    Abstract

    The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

    View details for DOI 10.1038/nature11247

    View details for Web of Science ID 000308347000039

    View details for PubMedID 22955616

  • Architecture of the human regulatory network derived from ENCODE data NATURE Gerstein, M. B., Kundaje, A., Hariharan, M., Landt, S. G., Yan, K., Cheng, C., Mu, X. J., Khurana, E., Rozowsky, J., Alexander, R., Min, R., Alves, P., Abyzov, A., Addleman, N., Bhardwaj, N., Boyle, A. P., Cayting, P., Charos, A., Chen, D. Z., Cheng, Y., Clarke, D., Eastman, C., Euskirchen, G., Frietze, S., Fu, Y., Gertz, J., Grubert, F., Harmanci, A., Jain, P., Kasowski, M., Lacroute, P., Leng, J., Lian, J., Monahan, H., O'Geen, H., Ouyang, Z., Partridge, E. C., Patacsil, D., Pauli, F., Raha, D., Ramirez, L., Reddy, T. E., Reed, B., Shi, M., Slifer, T., Wang, J., Wu, L., Yang, X., Yip, K. Y., Zilberman-Schapira, G., Batzoglou, S., Sidow, A., Farnham, P. J., Myers, R. M., Weissman, S. M., Snyder, M. 2012; 489 (7414): 91-100

    Abstract

    Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

    View details for DOI 10.1038/nature11245

    View details for Web of Science ID 000308347000042

    View details for PubMedID 22955619

  • Linking disease associations with regulatory information in the human genome GENOME RESEARCH Schaub, M. A., Boyle, A. P., Kundaje, A., Batzoglou, S., Snyder, M. 2012; 22 (9): 1748-1759

    Abstract

    Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify "functional SNPs" that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.

    View details for DOI 10.1101/gr.136127.111

    View details for Web of Science ID 000308272800016

    View details for PubMedID 22955986

  • Annotation of functional variation in personal genomes using RegulomeDB GENOME RESEARCH Boyle, A. P., Hong, E. L., Hariharan, M., Cheng, Y., Schaub, M. A., Kasowski, M., Karczewski, K. J., Park, J., Hitz, B. C., Weng, S., Cherry, J. M., Snyder, M. 2012; 22 (9): 1790-1797

    Abstract

    As the sequencing of healthy and disease genomes becomes more commonplace, detailed annotation provides interpretation for individual variation responsible for normal and disease phenotypes. Current approaches focus on direct changes in protein coding genes, particularly nonsynonymous mutations that directly affect the gene product. However, most individual variation occurs outside of genes and, indeed, most markers generated from genome-wide association studies (GWAS) identify variants outside of coding segments. Identification of potential regulatory changes that perturb these sites will lead to a better localization of truly functional variants and interpretation of their effects. We have developed a novel approach and database, RegulomeDB, which guides interpretation of regulatory variants in the human genome. RegulomeDB includes high-throughput, experimental data sets from ENCODE and other sources, as well as computational predictions and manual annotations to identify putative regulatory potential and identify functional variants. These data sources are combined into a powerful tool that scores variants to help separate functional variants from a large pool and provides a small set of putative sites with testable hypotheses as to their function. We demonstrate the applicability of this tool to the annotation of noncoding variants from 69 full sequenced genomes as well as that of a personal genome, where thousands of functionally associated variants were identified. Moreover, we demonstrate a GWAS where the database is able to quickly identify the known associated functional variant and provide a hypothesis as to its function. Overall, we expect this approach and resource to be valuable for the annotation of human genome sequences.

    View details for DOI 10.1101/gr.137323.112

    View details for Web of Science ID 000308272800019

    View details for PubMedID 22955989

  • Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes CELL Chen, R., Mias, G. I., Li-Pook-Than, J., Jiang, L., Lam, H. Y., Chen, R., Miriami, E., Karczewski, K. J., Hariharan, M., Dewey, F. E., Cheng, Y., Clark, M. J., Im, H., Habegger, L., Balasubramanian, S., O'Huallachain, M., Dudley, J. T., Hillenmeyer, S., Haraksingh, R., Sharon, D., Euskirchen, G., Lacroute, P., Bettinger, K., Boyle, A. P., Kasowski, M., Grubert, F., Seki, S., Garcia, M., Whirl-Carrillo, M., Gallardo, M., Blasco, M. A., Greenberg, P. L., Snyder, P., Klein, T. E., Altman, R. B., Butte, A. J., Ashley, E. A., Gerstein, M., Nadeau, K. C., Tang, H., Snyder, M. 2012; 148 (6): 1293-1307

    Abstract

    Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

    View details for DOI 10.1016/j.cell.2012.02.009

    View details for Web of Science ID 000301889500023

    View details for PubMedID 22424236

  • Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity GENOME RESEARCH Song, L., Zhang, Z., Grasfeder, L. L., Boyle, A. P., Giresi, P. G., Lee, B., Sheffield, N. C., Graef, S., Huss, M., Keefe, D., Liu, Z., London, D., McDaniell, R. M., Shibata, Y., Showers, K. A., Simon, J. M., Vales, T., Wang, T., Winter, D., Zhang, Z., Clarke, N. D., Birney, E., Iyer, V. R., Crawford, G. E., Lieb, J. D., Furey, T. S. 2011; 21 (10): 1757-1767

    Abstract

    The human body contains thousands of unique cell types, each with specialized functions. Cell identity is governed in large part by gene transcription programs, which are determined by regulatory elements encoded in DNA. To identify regulatory elements active in seven cell lines representative of diverse human cell types, we used DNase-seq and FAIRE-seq (Formaldehyde Assisted Isolation of Regulatory Elements) to map "open chromatin." Over 870,000 DNaseI or FAIRE sites, which correspond tightly to nucleosome-depleted regions, were identified across the seven cell lines, covering nearly 9% of the genome. The combination of DNaseI and FAIRE is more effective than either assay alone in identifying likely regulatory elements, as judged by coincidence with transcription factor binding locations determined in the same cells. Open chromatin common to all seven cell types tended to be at or near transcription start sites and to be coincident with CTCF binding sites, while open chromatin sites found in only one cell type were typically located away from transcription start sites and contained DNA motifs recognized by regulators of cell-type identity. We show that open chromatin regions bound by CTCF are potent insulators. We identified clusters of open regulatory elements (COREs) that were physically near each other and whose appearance was coordinated among one or more cell types. Gene expression and RNA Pol II binding data support the hypothesis that COREs control gene activity required for the maintenance of cell-type identity. This publicly available atlas of regulatory elements may prove valuable in identifying noncoding DNA sequence variants that are causally linked to human disease.

    View details for DOI 10.1101/gr.121541.111

    View details for Web of Science ID 000295407800019

    View details for PubMedID 21750106

  • A User's Guide to the Encyclopedia of DNA Elements (ENCODE) PLOS BIOLOGY Myers, R. M., Stamatoyannopoulos, J., Snyder, M., Dunham, I., Hardison, R. C., Bernstein, B. E., Gingeras, T. R., Kent, W. J., Birney, E., Wold, B., Crawford, G. E., Bernstein, B. E., Epstein, C. B., Shoresh, N., Ernst, J., Mikkelsen, T. S., Kheradpour, P., Zhang, X., Wang, L., Issner, R., Coyne, M. J., Durham, T., Ku, M., Thanh Truong, T., Ward, L. D., Altshuler, R. C., Lin, M. F., Kellis, M., Gingeras, T. R., Davis, C. A., Kapranov, P., Dobin, A., Zaleski, C., Schlesinger, F., Batut, P., Chakrabortty, S., Jha, S., Lin, W., Drenkow, J., Wang, H., Bell, K., Gao, H., Bell, I., Dumais, E., Dumais, J., Antonarakis, S. E., Ucla, C., Borel, C., Guigo, R., Djebali, S., Lagarde, J., Kingswood, C., Ribeca, P., Sammeth, M., Alioto, T., Merkel, A., Tilgner, H., Carninci, P., Hayashizaki, Y., Lassmann, T., Takahashi, H., Abdelhamid, R. F., Hannon, G., Fejes-Toth, K., Preall, J., Gordon, A., Sotirova, V., Reymond, A., Howald, C., Graison, E. A., Chrast, J., Ruan, Y., Ruan, X., Shahab, A., Poh, W. T., Wei, C., Crawford, G. E., Furey, T. S., Boyle, A. P., Sheffield, N. C., Song, L., Shibata, Y., Vales, T., Winter, D., Zhang, Z., London, D., Wang, T., Birney, E., Keefe, D., Iyer, V. R., Lee, B., McDaniell, R. M., Liu, Z., Battenhouse, A., Bhinge, A. A., Lieb, J. D., Grasfeder, L. L., Showers, K. A., Giresi, P. G., Kim, S. K., Shestak, C., Myers, R. M., Pauli, F., Reddy, T. E., Gertz, J., Partridge, E. C., Jain, P., Sprouse, R. O., Bansal, A., Pusey, B., Muratet, M. A., Varley, K. E., Bowling, K. M., Newberry, K. M., Nesmith, A. S., Dilocker, J. A., Parker, S. L., Waite, L. L., Thibeault, K., Roberts, K., Absher, D. M., Wold, B., Mortazavi, A., Williams, B., Marinov, G., Trout, D., Pepke, S., King, B., McCue, K., Kirilusha, A., DeSalvo, G., Fisher-Aylor, K., Amrhein, H., Vielmetter, J., Sherlock, G., Sidow, A., Batzoglou, S., Rauch, R., Kundaje, A., Libbrecht, M., Margulies, E. H., Parker, S. C., Elnitski, L., Green, E. D., Hubbard, T., Harrow, J., Searle, S., Kokocinski, F., Aken, B., Frankish, A., Hunt, T., Despacio-Reyes, G., Kay, M., Mukherjee, G., Bignell, A., Saunders, G., Boychenko, V., Brent, M., van Baren, M. J., Brown, R. H., Gerstein, M., Khurana, E., Balasubramanian, S., Zhang, Z., Lam, H., Cayting, P., Robilotto, R., Lu, Z., Guigo, R., Derrien, T., Tanzer, A., Knowles, D. G., Mariotti, M., Kent, W. J., Haussler, D., Harte, R., Diekhans, M., Kellis, M., Lin, M., Kheradpour, P., Ernst, J., Reymond, A., Howald, C., Graison, E. A., Chrast, J., Valencia, A., Tress, M., Manuel Rodriguez, J., Snyder, M., Landt, S. G., Raha, D., Shi, M., Euskirchen, G., Grubert, F., Kasowski, M., Lian, J., Cayting, P., Lacroute, P., Xu, Y., Monahan, H., Patacsil, D., Slifer, T., Yang, X., Charos, A., Reed, B., Wu, L., Auerbach, R. K., Habegger, L., Hariharan, M., Rozowsky, J., Abyzov, A., Weissman, S. M., Gerstein, M., Struhl, K., Lamarre-Vincent, N., Lindahl-Allen, M., Miotto, B., Moqtaderi, Z., Fleming, J. D., Newburger, P., Farnham, P. J., Frietze, S., O'Geen, H., Xu, X., Blahnik, K. R., Cao, A. R., Iyengar, S., Stamatoyannopoulos, J. A., Kaul, R., Thurman, R. E., Wang, H., Navas, P. A., Sandstrom, R., Sabo, P. J., Weaver, M., Canfield, T., Lee, K., Neph, S., Roach, V., Reynolds, A., Johnson, A., Rynes, E., Giste, E., Vong, S., Neri, J., Frum, T., Johnson, E. M., Nguyen, E. D., Ebersol, A. K., Sanchez, M. E., Sheffer, H. H., Lotakis, D., Haugen, E., Humbert, R., Kutyavin, T., Shafer, T., Dekker, J., Lajoie, B. R., Sanyal, A., Kent, W. J., Rosenbloom, K. R., Dreszer, T. R., Raney, B. J., Barber, G. P., Meyer, L. R., Sloan, C. A., Malladi, V. S., Cline, M. S., Learned, K., Swing, V. K., Zweig, A. S., Rhead, B., Fujita, P. A., Roskin, K., Karolchik, D., Kuhn, R. M., Haussler, D., Birney, E., Dunham, I., Wilder, S. P., Keefe, D., Sobral, D., Herrero, J., Beal, K., Lukk, M., Brazma, A., Vaquerizas, J. M., Luscombe, N. M., Bickel, P. J., Boley, N., Brown, J. B., Li, Q., Huang, H., Gerstein, M., Habegger, L., Sboner, A., Rozowsky, J., Auerbach, R. K., Yip, K. Y., Cheng, C., Yan, K., Bhardwaj, N., Wang, J., Lochovsky, L., Jee, J., Gibson, T., Leng, J., Du, J., Hardison, R. C., Harris, R. S., Song, G., Miller, W., Haussler, D., Roskin, K., Suh, B., Wang, T., Paten, B., Noble, W. S., Hoffman, M. M., Buske, O. J., Weng, Z., Dong, X., Wang, J., Xi, H., Tenenbaum, S. A., Doyle, F., Penalva, L. O., Chittur, S., Tullius, T. D., Parker, S. C., White, K. P., Karmakar, S., Victorsen, A., Jameel, N., Bild, N., Grossman, R. L., Snyder, M., Landt, S. G., Yang, X., Patacsil, D., Slifer, T., Dekker, J., Lajoie, B. R., Sanyal, A., Weng, Z., Whitfield, T. W., Wang, J., Collins, P. J., Trinklein, N. D., Partridge, E. C., Myers, R. M., Giddings, M. C., Chen, X., Khatun, J., Maier, C., Yu, Y., Gunawardena, H., Risk, B., Feingold, E. A., Lowdon, R. F., Dillon, L. A., Good, P. J. 2011; 9 (4)
  • High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells GENOME RESEARCH Boyle, A. P., Song, L., Lee, B., London, D., Keefe, D., Birney, E., Iyer, V. R., Crawford, G. E., Furey, T. S. 2011; 21 (3): 456-464

    Abstract

    Regulation of gene transcription in diverse cell types is determined largely by varied sets of cis-elements where transcription factors bind. Here we demonstrate that data from a single high-throughput DNase I hypersensitivity assay can delineate hundreds of thousands of base-pair resolution in vivo footprints in human cells that precisely mark individual transcription factor-DNA interactions. These annotations provide a unique resource for the investigation of cis-regulatory elements. We find that footprints for specific transcription factors correlate with ChIP-seq enrichment and can accurately identify functional versus nonfunctional transcription factor motifs. We also find that footprints reveal a unique evolutionary conservation pattern that differentiates functional footprinted bases from surrounding DNA. Finally, detailed analysis of CTCF footprints suggests multiple modes of binding and a novel DNA binding motif upstream of the primary binding site.

    View details for DOI 10.1101/gr.112656.110

    View details for Web of Science ID 000287841100011

    View details for PubMedID 21106903

  • Global Epigenomic Analysis of Primary Human Pancreatic Islets Provides Insights into Type 2 Diabetes Susceptibility Loci CELL METABOLISM Stitzel, M. L., Sethupathy, P., Pearson, D. S., Chines, P. S., Song, L., Erdos, M. R., Welch, R., Parker, S. C., Boyle, A. P., Scott, L. J., Margulies, E. H., Boehnke, M., Furey, T. S., Crawford, G. E., Collins, F. S. 2010; 12 (5): 443-455

    Abstract

    Identifying cis-regulatory elements is important to understanding how human pancreatic islets modulate gene expression in physiologic or pathophysiologic (e.g., diabetic) conditions. We conducted genome-wide analysis of DNase I hypersensitive sites, histone H3 lysine methylation modifications (K4me1, K4me3, K79me2), and CCCTC factor (CTCF) binding in human islets. This identified ?18,000 putative promoters (several hundred unannotated and islet-active). Surprisingly, active promoter modifications were absent at genes encoding islet-specific hormones, suggesting a distinct regulatory mechanism. Of 34,039 distal (nonpromoter) regulatory elements, 47% are islet unique and 22% are CTCF bound. In the 18 type 2 diabetes (T2D)-associated loci, we identified 118 putative regulatory elements and confirmed enhancer activity for 12 of 33 tested. Among six regulatory elements harboring T2D-associated variants, two exhibit significant allele-specific differences in activity. These findings present a global snapshot of the human islet epigenome and should provide functional context for noncoding variants emerging from genetic studies of T2D and other islet disorders.

    View details for DOI 10.1016/j.cmet.2010.09.012

    View details for Web of Science ID 000283952300008

    View details for PubMedID 21035756

  • Heritable Individual-Specific and Allele-Specific Chromatin Signatures in Humans SCIENCE McDaniell, R., Lee, B., Song, L., Liu, Z., Boyle, A. P., Erdos, M. R., Scott, L. J., Morken, M. A., Kucera, K. S., Battenhouse, A., Keefe, D., Collins, F. S., Willard, H. F., Lieb, J. D., Furey, T. S., Crawford, G. E., Iyer, V. R., Birney, E. 2010; 328 (5975): 235-239

    Abstract

    The extent to which variation in chromatin structure and transcription factor binding may influence gene expression, and thus underlie or contribute to variation in phenotype, is unknown. To address this question, we cataloged both individual-to-individual variation and differences between homologous chromosomes within the same individual (allele-specific variation) in chromatin structure and transcription factor binding in lymphoblastoid cells derived from individuals of geographically diverse ancestry. Ten percent of active chromatin sites were individual-specific; a similar proportion were allele-specific. Both individual-specific and allele-specific sites were commonly transmitted from parent to child, which suggests that they are heritable features of the human genome. Our study shows that heritable chromatin status and transcription factor binding differ as a result of genetic variation and may underlie phenotypic variation in humans.

    View details for DOI 10.1126/science.1184655

    View details for Web of Science ID 000276459600044

    View details for PubMedID 20299549

  • Evidence-ranked motif identification GENOME BIOLOGY Georgiev, S., Boyle, A. P., Jayasurya, K., Ding, X., Mukherjee, S., Ohler, U. 2010; 11 (2)

    Abstract

    cERMIT is a computationally efficient motif discovery tool based on analyzing genome-wide quantitative regulatory evidence. Instead of pre-selecting promising candidate sequences, it utilizes information across all sequence regions to search for high-scoring motifs. We apply cERMIT on a range of direct binding and overexpression datasets; it substantially outperforms state-of-the-art approaches on curated ChIP-chip datasets, and easily scales to current mammalian ChIP-seq experiments with data on thousands of non-coding regions.

    View details for DOI 10.1186/gb-2010-11-2-r19

    View details for Web of Science ID 000276434300016

    View details for PubMedID 20156354

  • Both Noncoding and Protein-Coding RNAs Contribute to Gene Expression Evolution in the Primate Brain GENOME BIOLOGY AND EVOLUTION Babbitt, C. C., Fedrigo, O., Pfefferle, A. D., Boyle, A. P., Horvath, J. E., Furey, T. S., Wray, G. A. 2010; 2: 67-79

    Abstract

    Despite striking differences in cognition and behavior between humans and our closest primate relatives, several studies have found little evidence for adaptive change in protein-coding regions of genes expressed primarily in the brain. Instead, changes in gene expression may underlie many cognitive and behavioral differences. Here, we used digital gene expression: tag profiling (here called Tag-Seq, also called DGE:tag profiling) to assess changes in global transcript abundance in the frontal cortex of the brains of 3 humans, 3 chimpanzees, and 3 rhesus macaques. A substantial fraction of transcripts we identified as differentially transcribed among species were not assayed in previous studies based on microarrays. Differentially expressed tags within coding regions are enriched for gene functions involved in synaptic transmission, transport, oxidative phosphorylation, and lipid metabolism. Importantly, because Tag-Seq technology provides strand-specific information about all polyadenlyated transcripts, we were able to assay expression in noncoding intragenic regions, including both sense and antisense noncoding transcripts (relative to nearby genes). We find that many noncoding transcripts are conserved in both location and expression level between species, suggesting a possible functional role. Lastly, we examined the overlap between differential gene expression and signatures of positive selection within putative promoter regions, a sign that these differences represent adaptations during human evolution. Comparative approaches may provide important insights into genes responsible for differences in cognitive functions between humans and nonhuman primates, as well as highlighting new candidate genes for studies investigating neurological disorders.

    View details for DOI 10.1093/gbe/evq002

    View details for Web of Science ID 000280480000008

    View details for PubMedID 20333225

  • High-resolution mapping studies of chromatin and gene regulatory elements EPIGENOMICS Boyle, A. P., Furey, T. S. 2009; 1 (2): 319-329

    View details for DOI 10.2217/EP1.09.29

    View details for Web of Science ID 000278298900013

  • DNaseI hypersensitivity at gene-poor, FSH dystrophy-linked 4q35.2 NUCLEIC ACIDS RESEARCH Xu, X., Tsumagari, K., Sowden, J., Tawil, R., Boyle, A. P., Song, L., Furey, T. S., Crawford, G. E., Ehrlich, M. 2009; 37 (22): 7381-7393

    Abstract

    A subtelomeric region, 4q35.2, is implicated in facioscapulohumeral muscular dystrophy (FSHD), a dominant disease thought to involve local pathogenic changes in chromatin. FSHD patients have too few copies of a tandem 3.3-kb repeat (D4Z4) at 4q35.2. No phenotype is associated with having few copies of an almost identical repeat at 10q26.3. Standard expression analyses have not given definitive answers as to the genes involved. To investigate the pathogenic effects of short D4Z4 arrays on gene expression in the very gene-poor 4q35.2 and to find chromatin landmarks there for transcription control, unannotated genes and chromatin structure, we mapped DNaseI-hypersensitive (DH) sites in FSHD and control myoblasts. Using custom tiling arrays (DNase-chip), we found unexpectedly many DH sites in the two large gene deserts in this 4-Mb region. One site was seen preferentially in FSHD myoblasts. Several others were mapped >0.7 Mb from genes known to be active in the muscle lineage and were also observed in cultured fibroblasts, but not in lymphoid, myeloid or hepatic cells. Their selective occurrence in cells derived from mesoderm suggests functionality. Our findings indicate that the gene desert regions of 4q35.2 may have functional significance, possibly also to FSHD, despite their paucity of known genes.

    View details for DOI 10.1093/nar/gkp833

    View details for Web of Science ID 000272935000012

    View details for PubMedID 19820107

  • High-resolution mapping studies of chromatin and gene regulatory elements. Epigenomics Boyle, A. P., Furey, T. S. 2009; 1 (2): 319-329

    Abstract

    Microarray and high-throughput sequencing technologies have enabled the development of comprehensive assays to identify locations of particular chromatin structures and regulatory elements. It is now possible to create genome-wide maps of DNA methylation, trans-factor binding sites, histone variants and histone tail modifications, nucleosome positions, regions of open chromatin, and chromosome locations and interactions. This review provides a summary of these new assays that are changing the way in which molecular biology research is being performed. While the generation of large amounts of data from these experiments is becoming increasingly easier, the development of corresponding analysis methods has progressed more slowly. It will likely be years before the full extent of the information contained in these data is fully appreciated.

    View details for PubMedID 20514362

  • F-Seq: a feature density estimator for high-throughput sequence tags BIOINFORMATICS Boyle, A. P., Guinney, J., Crawford, G. E., Furey, T. S. 2008; 24 (21): 2537-2538

    Abstract

    Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features, such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an accurate and interpretable signal, we developed F-Seq, a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser.The software is written in the Java language and is available on all major computing platforms for download at http://www.genome.duke.edu/labs/furey/software/fseq.

    View details for DOI 10.1093/bioinformatics/btn480

    View details for Web of Science ID 000260381200018

    View details for PubMedID 18784119

  • High-resolution mapping and characterization of open chromatin across the genome CELL Boyle, A. P., Davis, S., Shulha, H. P., Meltzer, P., Margulies, E. H., Weng, Z., Furey, T. S., Crawford, G. E. 2008; 132 (2): 311-322

    Abstract

    Mapping DNase I hypersensitive (HS) sites is an accurate method of identifying the location of genetic regulatory elements, including promoters, enhancers, silencers, insulators, and locus control regions. We employed high-throughput sequencing and whole-genome tiled array strategies to identify DNase I HS sites within human primary CD4+ T cells. Combining these two technologies, we have created a comprehensive and accurate genome-wide open chromatin map. Surprisingly, only 16%-21% of the identified 94,925 DNase I HS sites are found in promoters or first exons of known genes, but nearly half of the most open sites are in these regions. In conjunction with expression, motif, and chromatin immunoprecipitation data, we find evidence of cell-type-specific characteristics, including the ability to identify transcription start sites and locations of different chromatin marks utilized in these cells. In addition, and unexpectedly, our analyses have uncovered detailed features of nucleosome structure.

    View details for DOI 10.1016/j.cell.2007.12.014

    View details for Web of Science ID 000253427700016

    View details for PubMedID 18243105

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