ALBERT

Description: Understanding the diversity of human tissues is fundamental to disease and requires linking genetic information, which is identical in most of an individual's cells, with epigenetic mechanisms that could have tissue-specific roles. Surveys of DNA methylation in human tissues have established a complex landscape including both tissue-specific and invariant methylation patterns. Here we report high coverage methylomes that catalogue cytosine methylation in all contexts for the major human organ systems, integrated with matched transcriptomes and genomic sequence. By combining these diverse data types with each individuals' phased genome, we identified widespread tissue-specific differential CG methylation (mCG), partially methylated domains, allele-specific methylation and transcription, and the unexpected presence of non-CG methylation (mCH) in almost all human tissues. mCH correlated with tissue-specific functions, and using this mark, we made novel predictions of genes that escape X-chromosome inactivation in specific tissues. Overall, DNA methylation in several genomic contexts varies substantially among human tissues.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4499021/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4499021/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Schultz, Matthew D -- He, Yupeng -- Whitaker, John W -- Hariharan, Manoj -- Mukamel, Eran A -- Leung, Danny -- Rajagopal, Nisha -- Nery, Joseph R -- Urich, Mark A -- Chen, Huaming -- Lin, Shin -- Lin, Yiing -- Jung, Inkyung -- Schmitt, Anthony D -- Selvaraj, Siddarth -- Ren, Bing -- Sejnowski, Terrence J -- Wang, Wei -- Ecker, Joseph R -- F32 HL110473/HL/NHLBI NIH HHS/ -- F32HL110473/HL/NHLBI NIH HHS/ -- K99 HL119617/HL/NHLBI NIH HHS/ -- K99 NS080911/NS/NINDS NIH HHS/ -- K99HL119617/HL/NHLBI NIH HHS/ -- R00 NS080911/NS/NINDS NIH HHS/ -- R00NS080911/NS/NINDS NIH HHS/ -- R01 ES024984/ES/NIEHS NIH HHS/ -- T32 GM008666/GM/NIGMS NIH HHS/ -- U01 ES017166/ES/NIEHS NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2015 Jul 9;523(7559):212-6. doi: 10.1038/nature14465. Epub 2015 Jun 1.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Bioinformatics Program, University of California, San Diego, La Jolla, California 92093, USA [2] Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA. ; Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, USA. ; Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA. ; 1] Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA [2] Department of Cognitive Science, University of California, San Diego, La Jolla, California 92037, USA. ; Ludwig Institute for Cancer Research, La Jolla, California 92093, USA. ; Department of Genetics, Stanford University, 300 Pasteur Drive, M-344 Stanford, California 94305, USA. ; Department of Surgery, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8109, St Louis, Missouri 63110, USA. ; Bioinformatics Program, University of California, San Diego, La Jolla, California 92093, USA. ; 1] Ludwig Institute for Cancer Research, La Jolla, California 92093, USA [2] University of California, San Diego School of Medicine, Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, La Jolla, California 92093, USA. ; 1] Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA [2] Division of Biological Sciences, University of California at San Diego, La Jolla, California 92037, USA [3] Howard Hughes Medical Institute, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, California 92037, USA. ; 1] Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, USA [2] Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California 92093, USA. ; 1] Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA [2] Howard Hughes Medical Institute, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, California 92037, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26030523" target="_blank"〉PubMed〈/a〉

Description: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530010/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4530010/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Roadmap Epigenomics Consortium -- Kundaje, Anshul -- Meuleman, Wouter -- Ernst, Jason -- Bilenky, Misha -- Yen, Angela -- Heravi-Moussavi, Alireza -- Kheradpour, Pouya -- Zhang, Zhizhuo -- Wang, Jianrong -- Ziller, Michael J -- Amin, Viren -- Whitaker, John W -- Schultz, Matthew D -- Ward, Lucas D -- Sarkar, Abhishek -- Quon, Gerald -- Sandstrom, Richard S -- Eaton, Matthew L -- Wu, Yi-Chieh -- Pfenning, Andreas R -- Wang, Xinchen -- Claussnitzer, Melina -- Liu, Yaping -- Coarfa, Cristian -- Harris, R Alan -- Shoresh, Noam -- Epstein, Charles B -- Gjoneska, Elizabeta -- Leung, Danny -- Xie, Wei -- Hawkins, R David -- Lister, Ryan -- Hong, Chibo -- Gascard, Philippe -- Mungall, Andrew J -- Moore, Richard -- Chuah, Eric -- Tam, Angela -- Canfield, Theresa K -- Hansen, R Scott -- Kaul, Rajinder -- Sabo, Peter J -- Bansal, Mukul S -- Carles, Annaick -- Dixon, Jesse R -- Farh, Kai-How -- Feizi, Soheil -- Karlic, Rosa -- Kim, Ah-Ram -- Kulkarni, Ashwinikumar -- Li, Daofeng -- Lowdon, Rebecca -- Elliott, GiNell -- Mercer, Tim R -- Neph, Shane J -- Onuchic, Vitor -- Polak, Paz -- Rajagopal, Nisha -- Ray, Pradipta -- Sallari, Richard C -- Siebenthall, Kyle T -- Sinnott-Armstrong, Nicholas A -- Stevens, Michael -- Thurman, Robert E -- Wu, Jie -- Zhang, Bo -- Zhou, Xin -- Beaudet, Arthur E -- Boyer, Laurie A -- De Jager, Philip L -- Farnham, Peggy J -- Fisher, Susan J -- Haussler, David -- Jones, Steven J M -- Li, Wei -- Marra, Marco A -- McManus, Michael T -- Sunyaev, Shamil -- Thomson, James A -- Tlsty, Thea D -- Tsai, Li-Huei -- Wang, Wei -- Waterland, Robert A -- Zhang, Michael Q -- Chadwick, Lisa H -- Bernstein, Bradley E -- Costello, Joseph F -- Ecker, Joseph R -- Hirst, Martin -- Meissner, Alexander -- Milosavljevic, Aleksandar -- Ren, Bing -- Stamatoyannopoulos, John A -- Wang, Ting -- Kellis, Manolis -- 5R24HD000836/HD/NICHD NIH HHS/ -- ES017166/ES/NIEHS NIH HHS/ -- F32 HL110473/HL/NHLBI NIH HHS/ -- F32HL110473/HL/NHLBI NIH HHS/ -- K99 HL119617/HL/NHLBI NIH HHS/ -- K99HL119617/HL/NHLBI NIH HHS/ -- P01 DA008227/DA/NIDA NIH HHS/ -- P30AG10161/AG/NIA NIH HHS/ -- P50 MH096890/MH/NIMH NIH HHS/ -- R01 AG015819/AG/NIA NIH HHS/ -- R01 AG017917/AG/NIA NIH HHS/ -- R01 ES024984/ES/NIEHS NIH HHS/ -- R01 ES024992/ES/NIEHS NIH HHS/ -- R01 HG004037/HG/NHGRI NIH HHS/ -- R01 HG007175/HG/NHGRI NIH HHS/ -- R01 HG007354/HG/NHGRI NIH HHS/ -- R01AG15819/AG/NIA NIH HHS/ -- R01AG17917/AG/NIA NIH HHS/ -- R01HG004037/HG/NHGRI NIH HHS/ -- R01HG004037-S1/HG/NHGRI NIH HHS/ -- R01NS078839/NS/NINDS NIH HHS/ -- RC1HG005334/HG/NHGRI NIH HHS/ -- RF1 AG015819/AG/NIA NIH HHS/ -- T32 ES007032/ES/NIEHS NIH HHS/ -- T32 GM007198/GM/NIGMS NIH HHS/ -- T32 GM007266/GM/NIGMS NIH HHS/ -- T32 GM081739/GM/NIGMS NIH HHS/ -- U01 ES017154/ES/NIEHS NIH HHS/ -- U01AG46152/AG/NIA NIH HHS/ -- U01DA025956/DA/NIDA NIH HHS/ -- U01ES017154/ES/NIEHS NIH HHS/ -- U01ES017155/ES/NIEHS NIH HHS/ -- U01ES017156/ES/NIEHS NIH HHS/ -- U01ES017166/ES/NIEHS NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2015 Feb 19;518(7539):317-30. doi: 10.1038/nature14248.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Genetics, Department of Computer Science, 300 Pasteur Dr., Lane Building, L301, Stanford, California 94305-5120, USA. ; 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. ; 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Biological Chemistry, University of California, Los Angeles, 615 Charles E Young Dr South, Los Angeles, California 90095, USA. ; Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. ; 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Department of Stem Cell and Regenerative Biology, 7 Divinity Ave, Cambridge, Massachusetts 02138, USA. ; Epigenome Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA. ; Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. ; Genomic Analysis Laboratory, Howard Hughes Medical Institute &The Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, California 92037, USA. ; Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, Washington 98195, USA. ; 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA. ; The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. ; 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, Massachusetts 02139, USA. ; 1] Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. [2] Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA. ; Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 1450 3rd Street, San Francisco, California 94158, USA. ; Department of Pathology, University of California San Francisco, 513 Parnassus Avenue, San Francisco, California 94143-0511, USA. ; Department of Medicine, Division of Medical Genetics, University of Washington, 2211 Elliot Avenue, Seattle, Washington 98121, USA. ; 1] Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, 32 Vassar St, Cambridge, Massachusetts 02139, USA. [2] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [3] Department of Computer Science &Engineering, University of Connecticut, 371 Fairfield Way, Storrs, Connecticut 06269, USA. ; Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada. ; Bioinformatics Group, Department of Molecular Biology, Division of Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia. ; Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA. ; Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA. ; Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland 4072, Australia. ; 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. ; 1] Department of Genetics, Center for Genome Sciences and Systems Biology, Washington University in St Louis, 4444 Forest Park Ave, St Louis, Missouri 63108, USA. [2] Department of Computer Science and Engineeering, Washington University in St. Louis, St. Louis, Missouri 63130, USA. ; 1] Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794-3600, USA. [2] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA. ; Molecular and Human Genetics Department, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA. ; Biology Department, Massachusetts Institute of Technology, 31 Ames St, Cambridge, Massachusetts 02142, USA. ; 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Brigham &Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA. [3] Harvard Medical School, 25 Shattuck St, Boston, Massachusetts 02115, USA. ; Department of Biochemistry, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, California 90089-9601, USA. ; ObGyn, Reproductive Sciences, University of California San Francisco, 35 Medical Center Way, San Francisco, California 94143, USA. ; Center for Biomolecular Sciences and Engineering, University of Santa Cruz, 1156 High Street, Santa Cruz, California 95064, USA. ; 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada. [3] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4. ; Dan L. Duncan Cancer Center, Baylor College of Medicine, One Baylor Plaza, Houston, Texas 77030, USA. ; 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Medical Genetics, University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, V6T 1Z4. ; Department of Microbiology and Immunology, Diabetes Center, University of California, San Francisco, 513 Parnassus Ave, San Francisco, California 94143-0534, USA. ; 1] University of Wisconsin, Madison, Wisconsin 53715, USA. [2] Morgridge Institute for Research, 330 N. Orchard Street, Madison, Wisconsin 53707, USA. ; USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, Texas 77030, USA. ; 1] Department of Molecular and Cell Biology, Center for Systems Biology, The University of Texas, Dallas, NSERL, RL10, 800 W Campbell Road, Richardson, Texas 75080, USA. [2] Bioinformatics Division, Center for Synthetic and Systems Biology, TNLIST, Tsinghua University, Beijing 100084, China. ; National Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Research Triangle Park, North Carolina 27709, USA. ; 1] The Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, Massachusetts 02142, USA. [2] Massachusetts General Hospital, 55 Fruit St, Boston, Massachusetts 02114, USA. [3] Howard Hughes Medical Institute, 4000 Jones Bridge Road, Chevy Chase, Maryland 20815-6789, USA. ; 1] Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, British Columbia V5Z 1L3, Canada. [2] Department of Microbiology and Immunology and Centre for High-Throughput Biology, University of British Columbia, 2125 East Mall, Vancouver, British Columbia V6T 1Z4, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25693563" target="_blank"〉PubMed〈/a〉

Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Schultz, Matthew D -- He, Yupeng -- Whitaker, John W -- Hariharan, Manoj -- Mukamel, Eran A -- Leung, Danny -- Rajagopal, Nisha -- Nery, Joseph R -- Urich, Mark A -- Chen, Huaming -- Lin, Shin -- Lin, Yiing -- Jung, Inkyung -- Schmitt, Anthony D -- Selvaraj, Siddarth -- Ren, Bing -- Sejnowski, Terrence J -- Wang, Wei -- Ecker, Joseph R -- England -- Nature. 2016 Feb 11;530(7589):242. doi: 10.1038/nature16179. Epub 2015 Nov 25.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26605523" target="_blank"〉PubMed〈/a〉

Description: Human embryonic stem cells (hESCs) hold great promise for regenerative medicine because they can undergo unlimited self-renewal and retain the capability to differentiate into all cell types in the body. Although numerous genes/proteins such as Oct4 and Gata6 have been identified to play critical regulatory roles in self-renewal and differentiation of hESC, the majority of the regulators in these cellular processes and more importantly how these regulators co-operate with each other and/or with epigenetic modifications are still largely unknown. We propose here a systematic approach to integrate genomic and epigenomic data for identification of direct regulatory interactions. This approach allows reconstruction of cell-type-specific transcription networks in embryonic stem cells (ESCs) and fibroblasts at an unprecedented scale. Many links in the reconstructed networks coincide with known regulatory interactions or literature evidence. Systems-level analyses of these networks not only uncover novel regulators for pluripotency and differentiation, but also reveal extensive interplays between transcription factor binding and epigenetic modifications. Especially, we observed poised enhancers characterized by both active (H3K4me1) and repressive (H3K27me3) histone marks that contain enriched Oct4- and Suz12-binding sites. The success of such a systems biology approach is further supported by experimental validation of the predicted interactions.

Description: Enhancers play a pivotal role in regulating the transcription of distal genes. Although certain chromatin features, such as the histone acetyltransferase P300 and the histone modification H3K4me1, indicate the presence of enhancers, only a fraction of enhancers are functionally active. Individual chromatin marks, such as H3K27ac and H3K27me3, have been identified to distinguish active from inactive enhancers. However, the systematic identification of the most informative single modification, or combination thereof, is still lacking. Furthermore, the discovery of enhancer RNAs (eRNAs) provides an alternative approach to directly predicting enhancer activity. However, it remains challenging to link chromatin modifications to eRNA transcription. Herein, we develop a logistic regression model to unravel the relationship between chromatin modifications and eRNA synthesis. We perform a systematic assessment of 24 chromatin modifications in fetal lung fibroblast and demonstrate that a combination of four modifications is sufficient to accurately predict eRNA transcription. Furthermore, we compare the ability of eRNAs and H3K27ac to discriminate enhancer activity. We demonstrate that eRNA is more indicative of enhancer activity. Finally, we apply our fibroblast trained model to six other cell-types and successfully predict eRNA synthesis. Thus, we demonstrate the learned relationships are general and independent of cell-type. We provided a powerful tool to identify active enhancers and reveal the relationship between chromatin modifications, eRNA production and enhancer activity.

Description: Motivation: Easily visualization of complex data features is a necessary step to conduct studies on next-generation sequencing (NGS) data. We developed STAR, an integrated web application that enables online management, visualization and track-based analysis of NGS data. Results: STAR is a multilayer web service system. On the client side, STAR leverages JavaScript, HTML5 Canvas and asynchronous communications to deliver a smoothly scrolling desktop-like graphical user interface with a suite of in-browser analysis tools that range from providing simple track configuration controls to sophisticated feature detection within datasets. On the server side, STAR supports private session state retention via an account management system and provides data management modules that enable collection, visualization and analysis of third-party sequencing data from the public domain with over thousands of tracks hosted to date. Overall, STAR represents a next-generation data exploration solution to match the requirements of NGS data, enabling both intuitive visualization and dynamic analysis of data. Availability and implementation: STAR browser system is freely available on the web at http://wanglab.ucsd.edu/star/browser and https://github.com/angell1117/STAR-genome-browser . Contact: wei-wang@ucsd.edu