Bio

Academic Appointments


Professional Education


  • PhD, MIT, Harvard-MIT Division of Health Sciences and Technology (2016)
  • MS, Stanford University, Bioengineering (2010)
  • BS, Stanford University, Biomedical Computation (2010)

Teaching

2020-21 Courses


Stanford Advisees


  • Doctoral Dissertation Reader (AC)
    Jeffrey Granja, Rosa Ma
  • Postdoctoral Faculty Sponsor
    Gabriella Martyn

Publications

All Publications


  • Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature Bick, A. G., Weinstock, J. S., Nandakumar, S. K., Fulco, C. P., Bao, E. L., Zekavat, S. M., Szeto, M. D., Liao, X., Leventhal, M. J., Nasser, J., Chang, K., Laurie, C., Burugula, B. B., Gibson, C. J., Lin, A. E., Taub, M. A., Aguet, F., Ardlie, K., Mitchell, B. D., Barnes, K. C., Moscati, A., Fornage, M., Redline, S., Psaty, B. M., Silverman, E. K., Weiss, S. T., Palmer, N. D., Vasan, R. S., Burchard, E. G., Kardia, S. L., He, J., Kaplan, R. C., Smith, N. L., Arnett, D. K., Schwartz, D. A., Correa, A., de Andrade, M., Guo, X., Konkle, B. A., Custer, B., Peralta, J. M., Gui, H., Meyers, D. A., McGarvey, S. T., Chen, I. Y., Shoemaker, M. B., Peyser, P. A., Broome, J. G., Gogarten, S. M., Wang, F. F., Wong, Q., Montasser, M. E., Daya, M., Kenny, E. E., North, K. E., Launer, L. J., Cade, B. E., Bis, J. C., Cho, M. H., Lasky-Su, J., Bowden, D. W., Cupples, L. A., Mak, A. C., Becker, L. C., Smith, J. A., Kelly, T. N., Aslibekyan, S., Heckbert, S. R., Tiwari, H. K., Yang, I. V., Heit, J. A., Lubitz, S. A., Johnsen, J. M., Curran, J. E., Wenzel, S. E., Weeks, D. E., Rao, D. C., Darbar, D., Moon, J., Tracy, R. P., Buth, E. J., Rafaels, N., Loos, R. J., Durda, P., Liu, Y., Hou, L., Lee, J., Kachroo, P., Freedman, B. I., Levy, D., Bielak, L. F., Hixson, J. E., Floyd, J. S., Whitsel, E. A., Ellinor, P. T., Irvin, M. R., Fingerlin, T. E., Raffield, L. M., Armasu, S. M., Wheeler, M. M., Sabino, E. C., Blangero, J., Williams, L. K., Levy, B. D., Sheu, W. H., Roden, D. M., Boerwinkle, E., Manson, J. E., Mathias, R. A., Desai, P., Taylor, K. D., Johnson, A. D., NHLBI Trans-Omics for Precision Medicine Consortium, Auer, P. L., Kooperberg, C., Laurie, C. C., Blackwell, T. W., Smith, A. V., Zhao, H., Lange, E., Lange, L., Rich, S. S., Rotter, J. I., Wilson, J. G., Scheet, P., Kitzman, J. O., Lander, E. S., Engreitz, J. M., Ebert, B. L., Reiner, A. P., Jaiswal, S., Abecasis, G., Sankaran, V. G., Kathiresan, S., Natarajan, P., Abe, N., Albert, C., Almasy, L., Alonso, A., Ament, S., Anderson, P., Anugu, P., Applebaum-Bowden, D., Arking, D., Ashley-Koch, A., Aslibekyan, S., Assimes, T., Avramopoulos, D., Barnard, J., Barr, R. G., Barron-Casella, E., Barwick, L., Beaty, T., Beck, G., Becker, D., Beer, R., Beitelshees, A., Benjamin, E., Benos, P., Bezerra, M., Bielak, L., Bowler, R., Brody, J., Broeckel, U., Bunting, K., Bustamante, C., Cardwell, J., Carey, V., Carty, C., Casaburi, R., Casella, J., Castaldi, P., Chaffin, M., Chang, C., Chang, Y., Chasman, D., Chavan, S., Chen, B., Chen, W., Choi, S. H., Chuang, L., Chung, M., Chung, R., Clish, C., Comhair, S., Cornell, E., Crandall, C., Crapo, J., Curtis, J., Damcott, C., Das, S., David, S., Davis, C., DeBaun, M., Deka, R., DeMeo, D., Devine, S., Duan, Q., Duggirala, R., Dutcher, S., Eaton, C., Ekunwe, L., Boueiz, A. E., Emery, L., Erzurum, S., Farber, C., Flickinger, M., Franceschini, N., Frazar, C., Fu, M., Fullerton, S. M., Fulton, L., Gabriel, S., Gan, W., Gao, S., Gao, Y., Gass, M., Gelb, B., Priscilla Geng, X., Geraci, M., Germer, S., Gerszten, R., Ghosh, A., Gibbs, R., Gignoux, C., Gladwin, M., Glahn, D., Gong, D., Goring, H., Graw, S., Grine, D., Gu, C. C., Guan, Y., Gupta, N., Haessler, J., Hall, M., Harris, D., Hawley, N. L., Heavner, B., Hernandez, R., Herrington, D., Hersh, C., Hidalgo, B., Hobbs, B., Hokanson, J., Hong, E., Hoth, K., Agnes Hsiung, C., Hung, Y., Huston, H., Hwu, C. M., Jackson, R., Jain, D., Jaquish, C., Jhun, M. A., Johnson, C., Johnston, R., Jones, K., Kang, H. M., Kelly, S., Kessler, M., Khan, A., Kim, W., Kinney, G., Kramer, H., Lange, C., LeBoff, M., Lee, S. S., Lee, W., LeFaive, J., Levine, D., Lewis, J., Li, X., Li, Y., Lin, H., Lin, H., Lin, K. H., Lin, X., Liu, S., Liu, Y., Lunetta, K., Luo, J., Mahaney, M., Make, B., Manichaikul, A., Margolin, L., Martin, L., Mathai, S., May, S., McArdle, P., McDonald, M., McFarland, S., McGoldrick, D., McHugh, C., Mei, H., Mestroni, L., Mikulla, J., Min, N., Minear, M., Minster, R. L., Moll, M., Montgomery, C., Musani, S., Mwasongwe, S., Mychaleckyj, J. C., Nadkarni, G., Naik, R., Naseri, T., Nekhai, S., Nelson, S. C., Neltner, B., Nickerson, D., O'Connell, J., O'Connor, T., Ochs-Balcom, H., Paik, D., Pankow, J., Papanicolaou, G., Parsa, A., Perez, M., Perry, J., Peters, U., Peyser, P., Phillips, L. S., Pollin, T., Post, W., Becker, J. P., Boorgula, M. P., Preuss, M., Qasba, P., Qiao, D., Qin, Z., Rasmussen-Torvik, L., Ratan, A., Reed, R., Regan, E., Sefuiva Reupena, M., Rice, K., Roselli, C., Ruczinski, I., Russell, P., Ruuska, S., Ryan, K., Saleheen, D., Salimi, S., Salzberg, S., Sandow, K., Scheller, C., Schmidt, E., Schwander, K., Sciurba, F., Seidman, C., Seidman, J., Sheehan, V., Sherman, S. L., Shetty, A., Shetty, A., Silver, B., Smith, J., Smith, T., Smoller, S., Snively, B., Snyder, M., Sofer, T., Sotoodehnia, N., Stilp, A. M., Storm, G., Streeten, E., Su, J. L., Sung, Y. J., Sylvia, J., Szpiro, A., Sztalryd, C., Taliun, D., Tang, H., Taylor, M., Taylor, S., Telen, M., Thornton, T. A., Threlkeld, M., Tinker, L., Tirschwell, D., Tishkoff, S., Tiwari, H., Tong, C., Tsai, M., Vaidya, D., Berg, D. V., VandeHaar, P., Vrieze, S., Walker, T., Wallace, R., Walts, A., Wang, H., Watson, K., Weir, B., Weng, L., Wessel, J., Willer, C., Williams, K., Wilson, C., Wu, J., Xu, H., Yanek, L., Yang, R., Zaghloul, N., Zhang, Y., Zhao, S. X., Zhao, W., Zhi, D., Zhou, X., Zhu, X., Zody, M., Zoellner, S. 2020

    Abstract

    Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon istermed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIPdriver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

    View details for DOI 10.1038/s41586-020-2819-2

    View details for PubMedID 33057201

  • Publisher Correction: Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries. Nature communications Zekavat, S. M., Ruotsalainen, S., Handsaker, R. E., Alver, M., Bloom, J., Poterba, T., Seed, C., Ernst, J., Chaffin, M., Engreitz, J., Peloso, G. M., Manichaikul, A., Yang, C., Ryan, K. A., Fu, M., Johnson, W. C., Tsai, M., Budoff, M., Vasan, R. S., Cupples, L. A., Rotter, J. I., Rich, S. S., Post, W., Mitchell, B. D., Correa, A., Metspalu, A., Wilson, J. G., Salomaa, V., Kellis, M., Daly, M. J., Neale, B. M., McCarroll, S., Surakka, I., Esko, T., Ganna, A., Ripatti, S., Kathiresan, S., Natarajan, P., NHLBI TOPMed Lipids Working Group, Abe, N., Abecasis, G., Albert, C., Allred, N. N., Almasy, L., Alonso, A., Ament, S., Anderson, P., Anugu, P., Applebaum-Bowden, D., Arking, D., Arnett, D. K., Ashley-Koch, A., Aslibekyan, S., Assimes, T., Auer, P., Avramopoulos, D., Barnard, J., Barnes, K., Barr, R. G., Barron-Casella, E., Beaty, T., Becker, D., Becker, L., Beer, R., Begum, F., Beitelshees, A., Benjamin, E., Bezerra, M., Bielak, L., Bis, J., Blackwell, T., Blangero, J., Boerwinkle, E., Borecki, I., Bowler, R., Brody, J., Broeckel, U., Broome, J., Bunting, K., Burchard, E., Cardwell, J., Carty, C., Casaburi, R., Casella, J., Chang, C., Chasman, D., Chavan, S., Chen, B., Chen, W., Chen, Y. I., Cho, M., Choi, S. H., Chuang, L., Chung, M., Cornell, E., Crandall, C., Crapo, J., Curran, J., Curtis, J., Custer, B., Damcott, C., Darbar, D., Das, S., David, S., Davis, C., Daya, M., Andrade, M. d., DeBaun, M., Deka, R., DeMeo, D., Devine, S., Do, R., Duan, Q., Duggirala, R., Durda, P., Dutcher, S., Eaton, C., Ekunwe, L., Ellinor, P., Emery, L., Farber, C., Farnam, L., Fingerlin, T., Flickinger, M., Fornage, M., Franceschini, N., Fullerton, S. M., Fulton, L., Gabriel, S., Gan, W., Gao, Y., Gass, M., Gelb, B., Geng, X. P., Germer, S., Gignoux, C., Gladwin, M., Glahn, D., Gogarten, S., Gong, D., Goring, H., Gu, C. C., Guan, Y., Guo, X., Haessler, J., Hall, M., Harris, D., Hawley, N., He, J., Heavner, B., Heckbert, S., Hernandez, R., Herrington, D., Hersh, C., Hidalgo, B., Hixson, J., Hokanson, J., Hong, E., Hoth, K., Hsiung, C. A., Huston, H., Hwu, C. M., Irvin, M. R., Jackson, R., Jain, D., Jaquish, C., Jhun, M. A., Johnsen, J., Johnson, A., Johnston, R., Jones, K., Kang, H. M., Kaplan, R., Kardia, S., Kaufman, L., Kelly, S., Kenny, E., Kessler, M., Khan, A., Kinney, G., Konkle, B., Kooperberg, C., Kramer, H., Krauter, S., Lange, C., Lange, E., Lange, L., Laurie, C., Laurie, C., LeBoff, M., Lee, S. S., Lee, W., LeFaive, J., Levine, D., Levy, D., Lewis, J., Li, Y., Lin, H., Lin, K. H., Liu, S., Liu, Y., Loos, R., Lubitz, S., Lunetta, K., Luo, J., Mahaney, M., Make, B., Manson, J., Margolin, L., Martin, L., Mathai, S., Mathias, R., McArdle, P., McDonald, M., McFarland, S., McGarvey, S., Mei, H., Meyers, D. A., Mikulla, J., Min, N., Minear, M., Minster, R. L., Montasser, M. E., Musani, S., Mwasongwe, S., Mychaleckyj, J. C., Nadkarni, G., Naik, R., Nekhai, S., Nickerson, D., North, K., O'Connell, J., O'Connor, T., Ochs-Balcom, H., Pankow, J., Papanicolaou, G., Parker, M., Parsa, A., Penchev, S., Peralta, J. M., Perez, M., Perry, J., Peters, U., Peyser, P., Phillips, L., Phillips, S., Pollin, T., Becker, J. P., Boorgula, M. P., Preuss, M., Prokopenko, D., Psaty, B., Qasba, P., Qiao, D., Qin, Z., Rafaels, N., Raffield, L., Rao, D. C., Rasmussen-Torvik, L., Ratan, A., Redline, S., Reed, R., Regan, E., Reiner, A., Rice, K., Roden, D., Roselli, C., Ruczinski, I., Russell, P., Ruuska, S., Sakornsakolpat, P., Salimi, S., Salzberg, S., Sandow, K., Sankaran, V., Scheller, C., Schmidt, E., Schwander, K., Schwartz, D., Sciurba, F., Seidman, C., Sheehan, V., Shetty, A., Shetty, A., Sheu, W. H., Shoemaker, M. B., Silver, B., Silverman, E., Smith, J., Smith, J., Smith, N., Smith, T., Smoller, S., Snively, B., Sofer, T., Sotoodehnia, N., Stilp, A., Streeten, E., Sung, Y. J., Sylvia, J., Szpiro, A., Sztalryd, C., Taliun, D., Tang, H., Taub, M., Taylor, K., Taylor, S., Telen, M., Thornton, T. A., Tinker, L., Tirschwell, D., Tiwari, H., Tracy, R., Vaidya, D., VandeHaar, P., Vrieze, S., Walker, T., Wallace, R., Walts, A., Wan, E., Wang, F. F., Watson, K., Weeks, D. E., Weir, B., Weiss, S., Weng, L., Willer, C., Williams, K., Williams, L. K., Wilson, C., Wong, Q., Xu, H., Yanek, L., Yang, I., Yang, R., Zaghloul, N., Zhang, Y., Zhao, S. X., Zhao, W., Zheng, X., Zhi, D., Zhou, X., Zody, M., Zoellner, S. 2020; 11 (1): 1715

    Abstract

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

    View details for DOI 10.1038/s41467-020-15236-6

    View details for PubMedID 32238811

  • Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features NATURE COMMUNICATIONS Ray, J. P., de Boer, C. G., Fulco, C. P., Lareau, C. A., Kanai, M., Ulirsch, J. C., Tewhey, R., Ludwig, L. S., Reilly, S. K., Bergman, D. T., Engreitz, J. M., Issner, R., Finucane, H. K., Lander, E. S., Regev, A., Hacohen, N. 2020; 11 (1): 1237

    Abstract

    Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants.

    View details for DOI 10.1038/s41467-020-15022-4

    View details for Web of Science ID 000549162600014

    View details for PubMedID 32144282

    View details for PubMedCentralID PMC7060350

  • Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations NATURE GENETICS Fulco, C. P., Nasser, J., Jones, T. R., Munson, G., Bergman, D. T., Subramanian, V., Grossman, S. R., Anyoha, R., Doughty, B. R., Patwardhan, T. A., Nguyen, T. H., Kane, M., Perez, E. M., Durand, N. C., Lareau, C. A., Stamenova, E. K., Aiden, E., Lander, E. S., Engreitz, J. M. 2019; 51 (12): 1664-+

    Abstract

    Enhancer elements in the human genome control how genes are expressed in specific cell types and harbor thousands of genetic variants that influence risk for common diseases1-4. Yet, we still do not know how enhancers regulate specific genes, and we lack general rules to predict enhancer-gene connections across cell types5,6. We developed an experimental approach, CRISPRi-FlowFISH, to perturb enhancers in the genome, and we applied it to test?>3,500?potential enhancer-gene connections for 30?genes. We found that a simple activity-by-contact model substantially outperformed previous methods at predicting the complex connections in our CRISPR dataset. This activity-by-contact model allows us to construct genome-wide maps of enhancer-gene connections in a given cell type, on the basis of chromatin state measurements. Together, CRISPRi-FlowFISH and the activity-by-contact model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

    View details for DOI 10.1038/s41588-019-0538-0

    View details for Web of Science ID 000499696700003

    View details for PubMedID 31784727

    View details for PubMedCentralID PMC6886585

  • Functional disease architectures reveal unique biological role of transposable elements NATURE COMMUNICATIONS Hormozdiari, F., van de Geijn, B., Nasser, J., Weissbrod, O., Gazal, S., Ju, C., O'Connor, L., Hujoel, M. A., Engreitz, J., Hormozdiari, F., Price, A. L. 2019; 10: 4054

    Abstract

    Transposable elements (TE) comprise roughly half of the human genome. Though initially derided as junk DNA, they have been widely hypothesized to contribute to the evolution of gene regulation. However, the contribution of TE to the genetic architecture of diseases remains unknown. Here, we analyze data from 41 independent diseases and complex traits to draw three conclusions. First, TE are uniquely informative for disease heritability. Despite overall depletion for heritability (54% of SNPs, 39?±?2% of heritability), TE explain substantially more heritability than expected based on their depletion for known functional annotations. This implies that TE acquire function in ways that differ from known functional annotations. Second, older TE contribute more to disease heritability, consistent with acquiring biological function. Third, Short Interspersed Nuclear Elements (SINE) are far more enriched for blood traits than for other traits. Our results can help elucidate the biological roles that TE play in the genetic architecture of diseases.

    View details for DOI 10.1038/s41467-019-11957-5

    View details for Web of Science ID 000484599900004

    View details for PubMedID 31492842

    View details for PubMedCentralID PMC6731302

  • CRISPR Tools for Systematic Studies of RNA Regulation COLD SPRING HARBOR PERSPECTIVES IN BIOLOGY Engreitz, J., Abudayyeh, O., Gootenberg, J., Zhang, F. 2019; 11 (8)

    Abstract

    RNA molecules perform diverse functions in mammalian cells, including transferring genetic information from DNA to protein and playing diverse regulatory roles through interactions with other cellular components. Here, we discuss how clustered regularly interspaced short palindromic repeat (CRISPR)-based technologies for directed perturbations of DNA and RNA are revealing new insights into RNA regulation. First, we review the fundamentals of CRISPR-Cas enzymes and functional genomics tools that leverage these systems. Second, we explore how these new perturbation technologies are transforming the study of regulation of and by RNA, focusing on the functions of DNA regulatory elements and long noncoding RNAs (lncRNAs). Third, we highlight an emerging class of RNA-targeting CRISPR-Cas enzymes that have the potential to catalyze studies of RNA biology by providing tools to directly perturb or measure RNA modifications and functions. Together, these tools enable systematic studies of RNA function and regulation in mammalian cells.

    View details for DOI 10.1101/cshperspect.a035386

    View details for Web of Science ID 000482756900008

    View details for PubMedID 31371352

    View details for PubMedCentralID PMC6671937

  • Discovering metabolic disease gene interactions by correlated effects on cellular morphology MOLECULAR METABOLISM Jiao, Y., Ahmed, U., Sim, M., Bejar, A., Zhang, X., Talukder, M., Rice, R., Flannick, J., Podgornaia, A., Reilly, D. F., Engreitz, J. M., Kost-Alimova, M., Hartland, K., Mercader, J., Georges, S., Wagh, V., Tadin-Strapps, M., Doench, J. G., Edwardson, J., Rochford, J. J., Rosen, E. D., Majithia, A. R. 2019; 24: 108?19

    Abstract

    Impaired expansion of peripheral fat contributes to the pathogenesis of insulin resistance and Type 2 Diabetes (T2D). We aimed to identify novel disease-gene interactions during adipocyte differentiation.Genes in disease-associated loci for T2D, adiposity and insulin resistance were ranked according to expression in human adipocytes. The top 125 genes were ablated in human pre-adipocytes via CRISPR/CAS9 and the resulting cellular phenotypes quantified during adipocyte differentiation with high-content microscopy and automated image analysis. Morphometric measurements were extracted from all images and used to construct morphologic profiles for each gene.Over 107 morphometric measurements were obtained. Clustering of the morphologic profiles accross all genes revealed a group of 14 genes characterized by decreased lipid accumulation, and enriched for known lipodystrophy genes. For two lipodystrophy genes, BSCL2 and AGPAT2, sub-clusters with PLIN1 and CEBPA identifed by morphological similarity were validated by independent experiments as novel protein-protein and gene regulatory interactions.A morphometric approach in adipocytes can resolve multiple cellular mechanisms for metabolic disease loci; this approach enables mechanistic interrogation of the hundreds of metabolic disease loci whose function still remains unknown.

    View details for DOI 10.1016/j.molmet.2019.03.001

    View details for Web of Science ID 000468472300008

    View details for PubMedID 30940487

    View details for PubMedCentralID PMC6531784

  • Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis ELIFE Nandakumar, S. K., McFarland, S. K., Mateyka, L. M., Lareau, C. A., Ulirsch, J. C., Ludwig, L. S., Agarwal, G., Engreitz, J. M., Przychodzen, B., McConkey, M., Cowley, G. S., Doench, J. G., Maciejewski, J. P., Ebert, B. L., Root, D. E., Sankaran, V. G. 2019; 8

    Abstract

    Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding regions of the genome and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1-2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in specific and relevant biological pathways, allowing regulators of human erythropoiesis and modifiers of blood diseases to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.

    View details for DOI 10.7554/eLife.44080

    View details for Web of Science ID 000468967900001

    View details for PubMedID 31070582

    View details for PubMedCentralID PMC6534380

  • CRISPR-SURF: discovering regulatory elements by deconvolution of CRISPR tiling screen data NATURE METHODS Hsu, J. Y., Fulco, C. P., Cole, M. A., Canver, M. C., Pellin, D., Sher, F., Farouni, R., Clement, K., Guo, J. A., Biasco, L., Orkin, S. H., Engreitz, J. M., Lander, E. S., Joung, J., Bauer, D. E., Pinello, L. 2018; 15 (12): 992-+

    View details for DOI 10.1038/s41592-018-0225-6

    View details for Web of Science ID 000451826200006

    View details for PubMedID 30504875

    View details for PubMedCentralID PMC6620603

  • The NORAD lncRNA assembles a topoisomerase complex critical for genome stability (vol 561, pg 132, 2018) NATURE Munschauer, M., Nguyen, C. T., Sirokman, K., Hartigan, C. R., Hogstrom, L., Engreitz, J. M., Ulirsch, J. C., Fulco, C. P., Subramanian, V., Chen, J., Schenone, M., Guttman, M., Carr, S. A., Lander, E. S. 2018; 563 (7733): E32

    Abstract

    A typo in the 'Reviewer information' section of this Letter was corrected online.

    View details for DOI 10.1038/s41586-018-0584-2

    View details for Web of Science ID 000451599900011

    View details for PubMedID 30279576

  • The NORAD lncRNA assembles a topoisomerase complex critical for genome stability NATURE Munschauer, M., Nguyen, C. T., Sirokman, K., Hartigan, C. R., Hogstrom, L., Engreitz, J. M., Ulirsch, J. C., Fulco, C. P., Subramanian, V., Chen, J., Schenone, M., Guttman, M., Carr, S. A., Lander, E. S. 2018; 561 (7721): 132-+

    Abstract

    The human genome contains thousands of long non-coding RNAs1, but specific biological functions and biochemical mechanisms have been discovered for only about a dozen2-7. A specific long non-coding RNA-non-coding RNA activated by DNA damage (NORAD)-has recently been shown to be required for maintaining genomic stability8, but its molecular mechanism is unknown. Here we combine RNA antisense purification and quantitative mass spectrometry to identify proteins that directly interact with NORAD in living cells. We show that NORAD interacts with proteins involved in DNA replication and repair in steady-state cells and localizes to the nucleus upon stimulation with replication stress or DNA damage. In particular, NORAD interacts with RBMX, a component of the DNA-damage response, and contains the strongest RBMX-binding site in the transcriptome. We demonstrate that NORAD controls the ability of RBMX to assemble a ribonucleoprotein complex-which we term NORAD-activated ribonucleoprotein complex 1 (NARC1)-that contains the known suppressors of genomic instability topoisomerase I (TOP1), ALYREF and the PRPF19-CDC5L complex. Cells depleted for NORAD or RBMX display an increased frequency of chromosome segregation defects, reduced replication-fork velocity and altered cell-cycle progression-which represent phenotypes that are mechanistically linked to TOP1 and PRPF19-CDC5L function. Expression of NORAD in trans can rescue defects caused by NORAD depletion, but rescue is significantly impaired when the RBMX-binding site in NORAD is deleted. Our results demonstrate that the interaction between NORAD and RBMX is important for NORAD function, and that NORAD is required for the assembly of the previously unknown topoisomerase complex NARC1, which contributes to maintaining genomic stability. In addition, we uncover a previously unknown function for long non-coding RNAs in modulating the ability of an RNA-binding protein to assemble a higher-order ribonucleoprotein complex.

    View details for DOI 10.1038/s41586-018-0453-z

    View details for Web of Science ID 000443755200046

    View details for PubMedID 30150775

  • Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries (vol 9, 2606, 2018) NATURE COMMUNICATIONS Zekavat, S. M., Ruotsalainen, S., Handsaker, R. E., Alver, M., Bloom, J., Poterba, T., Seed, C., Ernst, J., Chaffin, M., Engreitz, J., Peloso, G. M., Manichaikul, A., Yang, C., Ryan, K. A., Fu, M., Johnson, W., Tsai, M., Budoff, M., Vasan, R. S., Cupples, L., Rotter, J. I., Rich, S. S., Post, W., Mitchell, B. D., Correa, A., Metspalu, A., Wilson, J. G., Salomaa, V., Kellis, M., Daly, M. J., Neale, B. M., McCarroll, S., Surakka, I., Esko, T., Ganna, A., Ripatti, S., Kathiresan, S., Natarajan, P., NHLBI TOPMed Lipids Working Grp 2018; 9: 3493

    Abstract

    The original version of this article contained an error in the name of the author Ramachandran S. Vasan, which was incorrectly given as Vasan S. Ramachandran. This has now been corrected in both the PDF and HTML versions of the article.

    View details for DOI 10.1038/s41467-018-05975-y

    View details for Web of Science ID 000442522400001

    View details for PubMedID 30140049

    View details for PubMedCentralID PMC6107495

  • Positional specificity of different transcription factor classes within enhancers PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Grossman, S. R., Engreitz, J., Ray, J. P., Nguyen, T. H., Hacohen, N., Lander, E. S. 2018; 115 (30): E7222?E7230

    Abstract

    Gene expression is controlled by sequence-specific transcription factors (TFs), which bind to regulatory sequences in DNA. TF binding occurs in nucleosome-depleted regions of DNA (NDRs), which generally encompass regions with lengths similar to those protected by nucleosomes. However, less is known about where within these regions specific TFs tend to be found. Here, we characterize the positional bias of inferred binding sites for 103 TFs within ?500,000 NDRs across 47 cell types. We find that distinct classes of TFs display different binding preferences: Some tend to have binding sites toward the edges, some toward the center, and some at other positions within the NDR. These patterns are highly consistent across cell types, suggesting that they may reflect TF-specific intrinsic structural or functional characteristics. In particular, TF classes with binding sites at NDR edges are enriched for those known to interact with histones and chromatin remodelers, whereas TFs with central enrichment interact with other TFs and cofactors such as p300. Our results suggest distinct regiospecific binding patterns and functions of TF classes within enhancers.

    View details for DOI 10.1073/pnas.1804663115

    View details for Web of Science ID 000439574700030

    View details for PubMedID 29987030

    View details for PubMedCentralID PMC6065035

  • Ribosome Levels Selectively Regulate Translation and Lineage Commitment in Human Hematopoiesis CELL Khajuria, R. K., Munschauer, M., Ulirsch, J. C., Fiorini, C., Ludwig, L. S., McFarland, S. K., Abdulhay, N. J., Specht, H., Keshishian, H., Mani, D. R., Jovanovic, M., Ellis, S. R., Fulco, C. P., Engreitz, J. M., Schutz, S., Lian, J., Gripp, K. W., Weinberg, O. K., Pinkus, G. S., Gehrke, L., Regev, A., Lander, E. S., Gazda, H. T., Lee, W. Y., Panse, V. G., Carr, S. A., Sankaran, V. G. 2018; 173 (1): 90-+

    Abstract

    Blood cell formation is classically thought to occur through a hierarchical differentiation process, although recent studies have shown that lineage commitment may occur earlier in hematopoietic stem and progenitor cells (HSPCs). The relevance to human blood diseases and the underlying regulation of these refined models remain poorly understood. By studying a genetic blood disorder, Diamond-Blackfan anemia (DBA), where the majority of mutations affect ribosomal proteins and the erythroid lineage is selectively perturbed, we are able to gain mechanistic insight into how lineage commitment is programmed normally and disrupted in disease. We show that in DBA, the pool of available ribosomes is limited, while ribosome composition remains constant. Surprisingly, this global reduction in ribosome levels more profoundly alters translation of a select subset of transcripts. We show how the reduced translation of select transcripts in HSPCs can impair erythroid lineage commitment, illuminating a regulatory role for ribosome levels in cellular differentiation.

    View details for DOI 10.1016/j.cell.2018.02.036

    View details for Web of Science ID 000428234200010

    View details for PubMedID 29551269

    View details for PubMedCentralID PMC5866246

  • Deep coverage whole genome sequences and plasma lipoprotein(a) in individuals of European and African ancestries. Nature communications Zekavat, S. M., Ruotsalainen, S., Handsaker, R. E., Alver, M., Bloom, J., Poterba, T., Seed, C., Ernst, J., Chaffin, M., Engreitz, J., Peloso, G. M., Manichaikul, A., Yang, C., Ryan, K. A., Fu, M., Johnson, W. C., Tsai, M., Budoff, M., Ramachandran, V. S., Cupples, L. A., Rotter, J. I., Rich, S. S., Post, W., Mitchell, B. D., Correa, A., Metspalu, A., Wilson, J. G., Salomaa, V., Kellis, M., Daly, M. J., Neale, B. M., McCarroll, S., Surakka, I., Esko, T., Ganna, A., Ripatti, S., Kathiresan, S., Natarajan, P. 2018; 9 (1): 2606

    Abstract

    Lipoprotein(a), Lp(a), is a modified low-density lipoprotein particle that contains apolipoprotein(a), encoded by LPA, and is a highly heritable, causal risk factor for cardiovascular diseases that varies in concentrations across ancestries. Here, we use deep-coverage whole genome sequencing in 8392 individuals of European and African ancestry to discover and interpret both single-nucleotide variants and copy number (CN) variation associated with Lp(a). We observe that genetic determinants between Europeans and Africans have several unique determinants. The common variant rs12740374 associated with Lp(a) cholesterol is an eQTL for SORT1 and independent of LDL cholesterol. Observed associations of aggregates of rare non-coding variants are largely explained by LPA structural variation, namely the LPA kringle IV 2 (KIV2)-CN. Finally, we find that LPA risk genotypes confer greater relative risk for incident atherosclerotic cardiovascular diseases compared to directly measured Lp(a), and are significantly associated with measures of subclinical atherosclerosis in African Americans.

    View details for DOI 10.1038/s41467-018-04668-w

    View details for PubMedID 29973585

    View details for PubMedCentralID PMC6031652

  • Deep-coverage whole genome sequences and blood lipids among 16,324 individuals. Nature communications Natarajan, P., Peloso, G. M., Zekavat, S. M., Montasser, M., Ganna, A., Chaffin, M., Khera, A. V., Zhou, W., Bloom, J. M., Engreitz, J. M., Ernst, J., O'Connell, J. R., Ruotsalainen, S. E., Alver, M., Manichaikul, A., Johnson, W. C., Perry, J. A., Poterba, T., Seed, C., Surakka, I. L., Esko, T., Ripatti, S., Salomaa, V., Correa, A., Vasan, R. S., Kellis, M., Neale, B. M., Lander, E. S., Abecasis, G., Mitchell, B., Rich, S. S., Wilson, J. G., Cupples, L. A., Rotter, J. I., Willer, C. J., Kathiresan, S. 2018; 9 (1): 3391

    Abstract

    Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30?mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia.

    View details for DOI 10.1038/s41467-018-05747-8

    View details for PubMedID 30140000

  • Genome-scale activation screen identifies a lncRNA locus regulating a gene neighbourhood NATURE Joung, J., Engreitz, J. M., Konermann, S., Abudayyeh, O. O., Verdine, V. K., Aguet, F., Gootenberg, J. S., Sanjana, N. E., Wright, J. B., Fulco, C. P., Tseng, Y., Yoon, C. H., Boehm, J. S., Lander, E. S., Zhang, F. 2017; 548 (7667): 343-+

    Abstract

    Mammalian genomes contain thousands of loci that transcribe long noncoding RNAs (lncRNAs), some of which are known to carry out critical roles in diverse cellular processes through a variety of mechanisms. Although some lncRNA loci encode RNAs that act non-locally (in trans), there is emerging evidence that many lncRNA loci act locally (in cis) to regulate the expression of nearby genes-for example, through functions of the lncRNA promoter, transcription, or transcript itself. Despite their potentially important roles, it remains challenging to identify functional lncRNA loci and distinguish among these and other mechanisms. Here, to address these challenges, we developed a genome-scale CRISPR-Cas9 activation screen that targets more than 10,000 lncRNA transcriptional start sites to identify noncoding loci that influence a phenotype of interest. We found 11 lncRNA loci that, upon recruitment of an activator, mediate resistance to BRAF inhibitors in human melanoma cells. Most candidate loci appear to regulate nearby genes. Detailed analysis of one candidate, termed EMICERI, revealed that its transcriptional activation resulted in dosage-dependent activation of four neighbouring protein-coding genes, one of which confers the resistance phenotype. Our screening and characterization approach provides a CRISPR toolkit with which to systematically discover the functions of noncoding loci and elucidate their diverse roles in gene regulation and cellular function.

    View details for DOI 10.1038/nature23451

    View details for Web of Science ID 000407748400035

    View details for PubMedID 28792927

    View details for PubMedCentralID PMC5706657

  • A Genetic Variant Associated with Five Vascular Diseases Is a Distal Regulator of Endothelin-1 Gene Expression CELL Gupta, R. M., Hadaya, J., Trehan, A., Zekavat, S. M., Roselli, C., Klarin, D., Emdin, C. A., Hilvering, C. E., Bianchi, V., Mueller, C., Khera, A. V., Ryan, R. H., Engreitz, J. M., Issner, R., Shoresh, N., Epstein, C. B., De laat, W., Brown, J. D., Schnabel, R. B., Bernstein, B. E., Kathiresan, S. 2017; 170 (3): 522-+

    Abstract

    Genome-wide association studies (GWASs) implicate the PHACTR1 locus (6p24) in risk for five vascular diseases, including coronary artery disease, migraine headache, cervical artery dissection, fibromuscular dysplasia, and hypertension. Through genetic fine mapping, we prioritized rs9349379, a common SNP in the third intron of the PHACTR1 gene, as the putative causal variant. Epigenomic data from human tissue revealed an enhancer signature at rs9349379 exclusively in aorta, suggesting a regulatory function for this SNP in the vasculature. CRISPR-edited stem cell-derived endothelial cells demonstrate rs9349379 regulates expression of endothelin 1 (EDN1), a gene located 600 kb upstream of PHACTR1. The known physiologic effects of EDN1 on the vasculature may explain the pattern of risk for the five associated diseases. Overall, these data illustrate the integration of genetic, phenotypic, and epigenetic analysis to identify the biologic mechanism by which a common, non-coding variant can distally regulate a gene and contribute to the pathogenesis of multiple vascular diseases.

    View details for DOI 10.1016/j.cell.2017.06.049

    View details for Web of Science ID 000406462400011

    View details for PubMedID 28753427

    View details for PubMedCentralID PMC5785707

  • Recurrent and functional regulatory mutations in breast cancer NATURE Rheinbay, E., Parasuraman, P., Grimsby, J., Tiao, G., Engreitz, J. M., Kim, J., Lawrence, M. S., Taylor-Weiner, A., Rodriguez-Cuevas, S., Rosenberg, M., Hess, J., Stewart, C., Maruvka, Y. E., Stojanov, P., Cortes, M. L., Seepo, S., Cibulskis, C., Tracy, A., Pugh, T. J., Lee, J., Zheng, Z., Ellisen, L. W., Iafrate, A., Boehm, J. S., Gabriel, S. B., Meyerson, M., Golub, T. R., Baselga, J., Hidalgo-Miranda, A., Shioda, T., Bernards, A., Lander, E. S., Getz, G. 2017; 547 (7661): 55-+

    Abstract

    Genomic analysis of tumours has led to the identification of hundreds of cancer genes on the basis of the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here we perform deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters. Clear signals are found in the promoters of three genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbours a mutational hotspot in its promoter leading to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that affect protein binding to their promoters and alter expression levels. Our study shows that promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions. Power analyses indicate that more such regions remain to be discovered through deep sequencing of adequately sized cohorts of patients.

    View details for DOI 10.1038/nature22992

    View details for Web of Science ID 000404839900030

    View details for PubMedID 28658208

    View details for PubMedCentralID PMC5563978

  • Systematic dissection of genomic features determining transcription factor binding and enhancer function PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Grossman, S. R., Zhang, X., Wang, L., Engreitz, J., Melnikov, A., Rogov, P., Tewhey, R., Isakova, A., Deplancke, B., Bernstein, B. E., Mikkelsen, T. S., Lander, E. S. 2017; 114 (7): E1291?E1300

    Abstract

    Enhancers regulate gene expression through the binding of sequence-specific transcription factors (TFs) to cognate motifs. Various features influence TF binding and enhancer function-including the chromatin state of the genomic locus, the affinities of the binding site, the activity of the bound TFs, and interactions among TFs. However, the precise nature and relative contributions of these features remain unclear. Here, we used massively parallel reporter assays (MPRAs) involving 32,115 natural and synthetic enhancers, together with high-throughput in vivo binding assays, to systematically dissect the contribution of each of these features to the binding and activity of genomic regulatory elements that contain motifs for PPAR?, a TF that serves as a key regulator of adipogenesis. We show that distinct sets of features govern PPAR? binding vs. enhancer activity. PPAR? binding is largely governed by the affinity of the specific motif site and higher-order features of the larger genomic locus, such as chromatin accessibility. In contrast, the enhancer activity of PPAR? binding sites depends on varying contributions from dozens of TFs in the immediate vicinity, including interactions between combinations of these TFs. Different pairs of motifs follow different interaction rules, including subadditive, additive, and superadditive interactions among specific classes of TFs, with both spatially constrained and flexible grammars. Our results provide a paradigm for the systematic characterization of the genomic features underlying regulatory elements, applicable to the design of synthetic regulatory elements or the interpretation of human genetic variation.

    View details for DOI 10.1073/pnas.1621150114

    View details for Web of Science ID 000393989300030

    View details for PubMedID 28137873

    View details for PubMedCentralID PMC5321001

  • Cohesin Loss Eliminates All Loop Domains. Cell Rao, S. S., Huang, S. C., Glenn St Hilaire, B., Engreitz, J. M., Perez, E. M., Kieffer-Kwon, K. R., Sanborn, A. L., Johnstone, S. E., Bascom, G. D., Bochkov, I. D., Huang, X., Shamim, M. S., Shin, J., Turner, D., Ye, Z., Omer, A. D., Robinson, J. T., Schlick, T., Bernstein, B. E., Casellas, R., Lander, E. S., Aiden, E. L. 2017; 171 (2): 305?20.e24

    Abstract

    The human genome folds to create thousands of intervals, called "contact domains," that exhibit enhanced contact frequency within themselves. "Loop domains" form because of tethering between two loci-almost always bound by CTCF and cohesin-lying on the same chromosome. "Compartment domains" form when genomic intervals with similar histone marks co-segregate. Here, we explore the effects of degrading cohesin. All loop domains are eliminated, but neither compartment domains nor histone marks are affected. Loss of loop domains does not lead to widespread ectopic gene activation but does affect a significant minority of active genes. In particular, cohesin loss causes superenhancers to co-localize, forming hundreds of links within and across chromosomes and affecting the regulation of nearby genes. We then restore cohesin and monitor the re-formation of each loop. Although re-formation rates vary greatly, many megabase-sized loops recovered in under an hour, consistent with a model where loop extrusion is rapid.

    View details for PubMedID 28985562

    View details for PubMedCentralID PMC5846482

  • Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression NATURE REVIEWS MOLECULAR CELL BIOLOGY Engreitz, J. M., Ollikainen, N., Guttman, M. 2016; 17 (12): 756?70

    Abstract

    Over the past decade, it has become clear that mammalian genomes encode thousands of long non-coding RNAs (lncRNAs), many of which are now implicated in diverse biological processes. Recent work studying the molecular mechanisms of several key examples - including Xist, which orchestrates X chromosome inactivation - has provided new insights into how lncRNAs can control cellular functions by acting in the nucleus. Here we discuss emerging mechanistic insights into how lncRNAs can regulate gene expression by coordinating regulatory proteins, localizing to target loci and shaping three-dimensional (3D) nuclear organization. We explore these principles to highlight biological challenges in gene regulation, in which lncRNAs are well-suited to perform roles that cannot be carried out by DNA elements or protein regulators alone, such as acting as spatial amplifiers of regulatory signals in the nucleus.

    View details for DOI 10.1038/nrm.2016.126

    View details for Web of Science ID 000388967900010

    View details for PubMedID 27780979

  • Local regulation of gene expression by lncRNA promoters, transcription and splicing NATURE Engreitz, J. M., Haines, J. E., Perez, E. M., Munson, G., Chen, J., Kane, M., McDonel, P. E., Guttman, M., Lander, E. S. 2016; 539 (7629): 452?55

    Abstract

    Mammalian genomes are pervasively transcribed to produce thousands of long non-coding RNAs (lncRNAs). A few of these lncRNAs have been shown to recruit regulatory complexes through RNA-protein interactions to influence the expression of nearby genes, and it has been suggested that many other lncRNAs can also act as local regulators. Such local functions could explain the observation that lncRNA expression is often correlated with the expression of nearby genes. However, these correlations have been challenging to dissect and could alternatively result from processes that are not mediated by the lncRNA transcripts themselves. For example, some gene promoters have been proposed to have dual functions as enhancers, and the process of transcription itself may contribute to gene regulation by recruiting activating factors or remodelling nucleosomes. Here we use genetic manipulation in mouse cell lines to dissect 12 genomic loci that produce lncRNAs and find that 5 of these loci influence the expression of a neighbouring gene in cis. Notably, none of these effects requires the specific lncRNA transcripts themselves and instead involves general processes associated with their production, including enhancer-like activity of gene promoters, the process of transcription, and the splicing of the transcript. Furthermore, such effects are not limited to lncRNA loci: we find that four out of six protein-coding loci also influence the expression of a neighbour. These results demonstrate that cross-talk among neighbouring genes is a prevalent phenomenon that can involve multiple mechanisms and cis-regulatory signals, including a role for RNA splice sites. These mechanisms may explain the function and evolution of some genomic loci that produce lncRNAs and broadly contribute to the regulation of both coding and non-coding genes.

    View details for DOI 10.1038/nature20149

    View details for Web of Science ID 000388161700059

    View details for PubMedID 27783602

    View details for PubMedCentralID PMC6853796

  • Systematic mapping of functional enhancer-promoter connections with CRISPR interference SCIENCE Fulco, C. P., Munschauer, M., Anyoha, R., Munson, G., Grossman, S. R., Perez, E. M., Kane, M., Cleary, B., Lander, E. S., Engreitz, J. M. 2016; 354 (6313): 769?73

    Abstract

    Gene expression in mammals is regulated by noncoding elements that can affect physiology and disease, yet the functions and target genes of most noncoding elements remain unknown. We present a high-throughput approach that uses clustered regularly interspaced short palindromic repeats (CRISPR) interference (CRISPRi) to discover regulatory elements and identify their target genes. We assess >1 megabase of sequence in the vicinity of two essential transcription factors, MYC and GATA1, and identify nine distal enhancers that control gene expression and cellular proliferation. Quantitative features of chromatin state and chromosome conformation distinguish the seven enhancers that regulate MYC from other elements that do not, suggesting a strategy for predicting enhancer-promoter connectivity. This CRISPRi-based approach can be applied to dissect transcriptional networks and interpret the contributions of noncoding genetic variation to human disease.

    View details for DOI 10.1126/science.aag2445

    View details for Web of Science ID 000387326300042

    View details for PubMedID 27708057

    View details for PubMedCentralID PMC5438575

  • Principles of Systems Biology-No. 10 CELL SYSTEMS Sanjana, N., Zhang, F., Fulco, C., Lander, E., Engreitz, J., Costanzo, M., Myers, C. L., Andrews, B., Boone, C., Kwiecien, N., Coon, J., Stefely, J., Pagliarini, D., Lewitus, E., Morlon, H., Zhang, R., Heyde, K. C., Scott, F. Y., Paek, S., Ruder, W. C., Liang, K., Doonan, C., Falcaro, P. 2016; 3 (4): 318?20

    Abstract

    CRISPR analysis of gene regulatory elements, a near-complete yeast genetic interaction map, and multi-omics mass spectrometry are milestones covered in this month's Cell Systems Call (Cell Systems 1, 307).

    View details for Web of Science ID 000395781400002

    View details for PubMedID 27788354

  • Eradication of large established tumors in mice by combination immunotherapy that engages innate and adaptive immune responses. Nature medicine Moynihan, K. D., Opel, C. F., Szeto, G. L., Tzeng, A., Zhu, E. F., Engreitz, J. M., Williams, R. T., Rakhra, K., Zhang, M. H., Rothschilds, A. M., Kumari, S., Kelly, R. L., Kwan, B. H., Abraham, W., Hu, K., Mehta, N. K., Kauke, M. J., Suh, H., Cochran, J. R., Lauffenburger, D. A., Wittrup, K. D., Irvine, D. J. 2016

    Abstract

    Checkpoint blockade with antibodies specific for cytotoxic T lymphocyte-associated protein (CTLA)-4 or programmed cell death 1 (PDCD1; also known as PD-1) elicits durable tumor regression in metastatic cancer, but these dramatic responses are confined to a minority of patients. This suboptimal outcome is probably due in part to the complex network of immunosuppressive pathways present in advanced tumors, which are unlikely to be overcome by intervention at a single signaling checkpoint. Here we describe a combination immunotherapy that recruits a variety of innate and adaptive immune cells to eliminate large tumor burdens in syngeneic tumor models and a genetically engineered mouse model of melanoma; to our knowledge tumors of this size have not previously been curable by treatments relying on endogenous immunity. Maximal antitumor efficacy required four components: a tumor-antigen-targeting antibody, a recombinant interleukin-2 with an extended half-life, anti-PD-1 and a powerful T cell vaccine. Depletion experiments revealed that CD8(+) T cells, cross-presenting dendritic cells and several other innate immune cell subsets were required for tumor regression. Effective treatment induced infiltration of immune cells and production of inflammatory cytokines in the tumor, enhanced antibody-mediated tumor antigen uptake and promoted antigen spreading. These results demonstrate the capacity of an elicited endogenous immune response to destroy large, established tumors and elucidate essential characteristics of combination immunotherapies that are capable of curing a majority of tumors in experimental settings typically viewed as intractable.

    View details for DOI 10.1038/nm.4200

    View details for PubMedID 27775706

    View details for PubMedCentralID PMC5209798

  • RNA Antisense Purification (RAP) for Mapping RNA Interactions with Chromatin NUCLEAR BODIES AND NONCODING RNAS: METHODS AND PROTOCOLS Engreitz, J., Lander, E. S., Guttman, M., Nakagawa, S., Hirose, T. 2015; 1262: 183?97

    Abstract

    RNA-centric biochemical purification is a general approach for studying the functions and mechanisms of noncoding RNAs. Here, we describe the experimental procedures for RNA antisense purification (RAP), a method for selective purification of endogenous RNA complexes from cell extracts that enables mapping of RNA interactions with chromatin. In RAP, the user cross-links cells to fix endogenous RNA complexes and purifies these complexes through hybrid capture with biotinylated antisense oligos. DNA loci that interact with the target RNA are identified using high-throughput DNA sequencing.

    View details for DOI 10.1007/978-1-4939-2253-6_11

    View details for Web of Science ID 000357692500012

    View details for PubMedID 25555582

  • RNA-RNA Interactions Enable Specific Targeting of Noncoding RNAs to Nascent Pre-mRNAs and Chromatin Sites CELL Engreitz, J. M., Sirokman, K., McDonel, P., Shishkin, A. A., Surka, C., Russell, P., Grossman, S. R., Chow, A. Y., Guttman, M., Lander, E. S. 2014; 159 (1): 188?99

    Abstract

    Intermolecular RNA-RNA interactions are used by many noncoding RNAs (ncRNAs) to achieve their diverse functions. To identify these contacts, we developed a method based on RNA antisense purification to systematically map RNA-RNA interactions (RAP-RNA) and applied it to investigate two ncRNAs implicated in RNA processing: U1 small nuclear RNA, a component of the spliceosome, and Malat1, a large ncRNA that localizes to nuclear speckles. U1 and Malat1 interact with nascent transcripts through distinct targeting mechanisms. Using differential crosslinking, we confirmed that U1 directly hybridizes to 5' splice sites and 5' splice site motifs throughout introns and found that Malat1 interacts with pre-mRNAs indirectly through protein intermediates. Interactions with nascent pre-mRNAs cause U1 and Malat1 to localize proximally to chromatin at active genes, demonstrating that ncRNAs can use RNA-RNA interactions to target specific pre-mRNAs and genomic sites. RAP-RNA is sensitive to lower abundance RNAs as well, making it generally applicable for investigating ncRNAs.

    View details for DOI 10.1016/j.cell.2014.08.018

    View details for Web of Science ID 000343095000019

    View details for PubMedID 25259926

    View details for PubMedCentralID PMC4177037

  • Transcriptome-wide Mapping Reveals Widespread Dynamic-Regulated Pseudouridylation of ncRNA and mRNA CELL Schwartz, S., Bernstein, D. A., Mumbach, M. R., Jovanovic, M., Herbst, R. H., Leon-Ricardo, B. X., Engreitz, J. M., Guttman, M., Satija, R., Lander, E. S., Fink, G., Regev, A. 2014; 159 (1): 148?62

    Abstract

    Pseudouridine is the most abundant RNA modification, yet except for a few well-studied cases, little is known about the modified positions and their function(s). Here, we develop ?-seq for transcriptome-wide quantitative mapping of pseudouridine. We validate ?-seq with spike-ins and de novo identification of previously reported positions and discover hundreds of unique sites in human and yeast mRNAs and snoRNAs. Perturbing pseudouridine synthases (PUS) uncovers which pseudouridine synthase modifies each site and their target sequence features. mRNA pseudouridinylation depends on both site-specific and snoRNA-guided pseudouridine synthases. Upon heat shock in yeast, Pus7p-mediated pseudouridylation is induced at >200 sites, and PUS7 deletion decreases the levels of otherwise pseudouridylated mRNA, suggesting a role in enhancing transcript stability. rRNA pseudouridine stoichiometries are conserved but reduced in cells from dyskeratosis congenita patients, where the PUS DKC1 is mutated. Our work identifies an enhanced, transcriptome-wide scope for pseudouridine and methods to dissect its underlying mechanisms and function.

    View details for DOI 10.1016/j.cell.2014.08.028

    View details for Web of Science ID 000343095000016

    View details for PubMedID 25219674

    View details for PubMedCentralID PMC4180118

  • Topological organization of multichromosomal regions by the long intergenic noncoding RNA Firre NATURE STRUCTURAL & MOLECULAR BIOLOGY Hacisuleyman, E., Goff, L. A., Trapnell, C., Williams, A., Henao-Mejia, J., Sun, L., McClanahan, P., Hendrickson, D. G., Sauvageau, M., Kelley, D. R., Morse, M., Engreitz, J., Lander, E. S., Guttman, M., Lodish, H. F., Flavell, R., Raj, A., Rinn, J. L. 2014; 21 (2): 198-+

    Abstract

    RNA, including long noncoding RNA (lncRNA), is known to be an abundant and important structural component of the nuclear matrix. However, the molecular identities, functional roles and localization dynamics of lncRNAs that influence nuclear architecture remain poorly understood. Here, we describe one lncRNA, Firre, that interacts with the nuclear-matrix factor hnRNPU through a 156-bp repeating sequence and localizes across an ~5-Mb domain on the X chromosome. We further observed Firre localization across five distinct trans-chromosomal loci, which reside in spatial proximity to the Firre genomic locus on the X chromosome. Both genetic deletion of the Firre locus and knockdown of hnRNPU resulted in loss of colocalization of these trans-chromosomal interacting loci. Thus, our data suggest a model in which lncRNAs such as Firre can interface with and modulate nuclear architecture across chromosomes.

    View details for DOI 10.1038/nsmb.2764

    View details for Web of Science ID 000331093600013

    View details for PubMedID 24463464

    View details for PubMedCentralID PMC3950333

  • Neuregulin Autocrine Signaling Promotes Self-Renewal of Breast Tumor-Initiating Cells by Triggering HER2/HER3 Activation CANCER RESEARCH Lee, C. Y., Lin, Y., Bratman, S. V., Feng, W., Kuo, A. H., Scheeren, F. A., Engreitz, J. M., Varma, S., West, R. B., Diehn, M. 2014; 74 (1): 341-352

    Abstract

    Currently, only patients with HER2-positive tumors are candidates for HER2-targeted therapies. However, recent clinical observations suggest that the survival of patients with HER2-low breast cancers, who lack HER2 amplification, may benefit from adjuvant therapy that targets HER2. In this study, we explored a mechanism through which these benefits may be obtained. Prompted by the hypothesis that HER2/HER3 signaling in breast tumor-initiating cells (TIC) promotes self-renewal and survival, we obtained evidence that neuregulin 1 (NRG1) produced by TICs promotes their proliferation and self-renewal in HER2-low tumors, including in triple-negative breast tumors. Pharmacologic inhibition of EGFR, HER2, or both receptors reduced breast TIC survival and self-renewal in vitro and in vivo and increased TIC sensitivity to ionizing radiation. Through a tissue microarray analysis, we found that NRG1 expression and associated HER2 activation occurred in a subset of HER2-low breast cancers. Our results offer an explanation for why HER2 inhibition blocks the growth of HER2-low breast tumors. Moreover, they argue that dual inhibition of EGFR and HER2 may offer a useful therapeutic strategy to target TICs in these tumors. In generating a mechanistic rationale to apply HER2-targeting therapies in patients with HER2-low tumors, this work shows why these therapies could benefit a considerably larger number of patients with breast cancer than they currently reach.

    View details for DOI 10.1158/0008-5472.CAN-13-1055

    View details for Web of Science ID 000329297600033

    View details for PubMedID 24177178

    View details for PubMedCentralID PMC3917843

  • The Xist lncRNA Exploits Three-Dimensional Genome Architecture to Spread Across the X Chromosome SCIENCE Engreitz, J. M., Pandya-Jones, A., McDonel, P., Shishkin, A., Sirokman, K., Surka, C., Kadri, S., Xing, J., Goren, A., Lander, E. S., Plath, K., Guttman, M. 2013; 341 (6147): 767-+

    Abstract

    Many large noncoding RNAs (lncRNAs) regulate chromatin, but the mechanisms by which they localize to genomic targets remain unexplored. We investigated the localization mechanisms of the Xist lncRNA during X-chromosome inactivation (XCI), a paradigm of lncRNA-mediated chromatin regulation. During the maintenance of XCI, Xist binds broadly across the X chromosome. During initiation of XCI, Xist initially transfers to distal regions across the X chromosome that are not defined by specific sequences. Instead, Xist identifies these regions by exploiting the three-dimensional conformation of the X chromosome. Xist requires its silencing domain to spread across actively transcribed regions and thereby access the entire chromosome. These findings suggest a model in which Xist coats the X chromosome by searching in three dimensions, modifying chromosome structure, and spreading to newly accessible locations.

    View details for DOI 10.1126/science.1237973

    View details for Web of Science ID 000323122200041

    View details for PubMedID 23828888

    View details for PubMedCentralID PMC3778663

  • Three-Dimensional Genome Architecture Influences Partner Selection for Chromosomal Translocations in Human Disease PLOS ONE Engreitz, J. M., Agarwala, V., Mirny, L. A. 2012; 7 (9): e44196

    Abstract

    Chromosomal translocations are frequent features of cancer genomes that contribute to disease progression. These rearrangements result from formation and illegitimate repair of DNA double-strand breaks (DSBs), a process that requires spatial colocalization of chromosomal breakpoints. The "contact first" hypothesis suggests that translocation partners colocalize in the nuclei of normal cells, prior to rearrangement. It is unclear, however, the extent to which spatial interactions based on three-dimensional genome architecture contribute to chromosomal rearrangements in human disease. Here we intersect Hi-C maps of three-dimensional chromosome conformation with collections of 1,533 chromosomal translocations from cancer and germline genomes. We show that many translocation-prone pairs of regions genome-wide, including the cancer translocation partners BCR-ABL and MYC-IGH, display elevated Hi-C contact frequencies in normal human cells. Considering tissue specificity, we find that translocation breakpoints reported in human hematologic malignancies have higher Hi-C contact frequencies in lymphoid cells than those reported in sarcomas and epithelial tumors. However, translocations from multiple tissue types show significant correlation with Hi-C contact frequencies, suggesting that both tissue-specific and universal features of chromatin structure contribute to chromosomal alterations. Our results demonstrate that three-dimensional genome architecture shapes the landscape of rearrangements directly observed in human disease and establish Hi-C as a key method for dissecting these effects.

    View details for DOI 10.1371/journal.pone.0044196

    View details for Web of Science ID 000309973900005

    View details for PubMedID 23028501

    View details for PubMedCentralID PMC3460994

  • ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression BIOINFORMATICS Engreitz, J. M., Chen, R., Morgan, A. A., Dudley, J. T., Mallelwar, R., Butte, A. J. 2011; 27 (23): 3317-3318

    Abstract

    We introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.http://profilechaser.stanford.eduabutte@stanford.eduSupplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btr548

    View details for Web of Science ID 000297352100015

    View details for PubMedID 21967760

    View details for PubMedCentralID PMC3223361

  • The Lin28/let-7 Axis Regulates Glucose Metabolism CELL Zhu, H., Shyh-Chang, N., Segre, A. V., Shinoda, G., Shah, S. P., Einhorn, W. S., Takeuchi, A., Engreitz, J. M., Hagan, J. P., Kharas, M. G., Urbach, A., Thornton, J. E., Triboulet, R., Gregory, R. I., Altshuler, D., Daley, G. Q., DIAGRAM Consortium, MAGIC Investigators 2011; 147 (1): 81?94

    Abstract

    The let-7 tumor suppressor microRNAs are known for their regulation of oncogenes, while the RNA-binding proteins Lin28a/b promote malignancy by inhibiting let-7 biogenesis. We have uncovered unexpected roles for the Lin28/let-7 pathway in regulating metabolism. When overexpressed in mice, both Lin28a and LIN28B promote an insulin-sensitized state that resists high-fat-diet induced diabetes. Conversely, muscle-specific loss of Lin28a or overexpression of let-7 results in insulin resistance and impaired glucose tolerance. These phenomena occur, in part, through the let-7-mediated repression of multiple components of the insulin-PI3K-mTOR pathway, including IGF1R, INSR, and IRS2. In addition, the mTOR inhibitor, rapamycin, abrogates Lin28a-mediated insulin sensitivity and enhanced glucose uptake. Moreover, let-7 targets are enriched for genes containing SNPs associated with type 2 diabetes and control of fasting glucose in human genome-wide association studies. These data establish the Lin28/let-7 pathway as a central regulator of mammalian glucose metabolism.

    View details for DOI 10.1016/j.cell.2011.08.033

    View details for Web of Science ID 000295396700017

    View details for PubMedID 21962509

    View details for PubMedCentralID PMC3353524

  • Content-based microarray search using differential expression profiles BMC BIOINFORMATICS Engreitz, J. M., Morgan, A. A., Dudley, J. T., Chen, R., Thathoo, R., Altman, R. B., Butte, A. J. 2010; 11

    Abstract

    With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these repositories based on gene expression content, rather than textual annotations, may enable more effective experiment retrieval as well as the discovery of novel associations between drugs, diseases, and other perturbations.We develop methods to retrieve gene expression experiments that differentially express the same transcriptional programs as a query experiment. Avoiding thresholds, we generate differential expression profiles that include a score for each gene measured in an experiment. We use existing and novel dimension reduction and correlation measures to rank relevant experiments in an entirely data-driven manner, allowing emergent features of the data to drive the results. A combination of matrix decomposition and p-weighted Pearson correlation proves the most suitable for comparing differential expression profiles. We apply this method to index all GEO DataSets, and demonstrate the utility of our approach by identifying pathways and conditions relevant to transcription factors Nanog and FoxO3.Content-based gene expression search generates relevant hypotheses for biological inquiry. Experiments across platforms, tissue types, and protocols inform the analysis of new datasets.

    View details for DOI 10.1186/1471-2105-11-603

    View details for Web of Science ID 000286192100001

    View details for PubMedID 21172034

    View details for PubMedCentralID PMC3022631

  • Independent component analysis: Mining microarray data for fundamental human gene expression modules JOURNAL OF BIOMEDICAL INFORMATICS Engreitz, J. M., Daigle, B. J., Marshall, J. J., Altman, R. B. 2010; 43 (6): 932-944

    Abstract

    As public microarray repositories rapidly accumulate gene expression data, these resources contain increasingly valuable information about cellular processes in human biology. This presents a unique opportunity for intelligent data mining methods to extract information about the transcriptional modules underlying these biological processes. Modeling cellular gene expression as a combination of functional modules, we use independent component analysis (ICA) to derive 423 fundamental components of human biology from a 9395-array compendium of heterogeneous expression data. Annotation using the Gene Ontology (GO) suggests that while some of these components represent known biological modules, others may describe biology not well characterized by existing manually-curated ontologies. In order to understand the biological functions represented by these modules, we investigate the mechanism of the preclinical anti-cancer drug parthenolide (PTL) by analyzing the differential expression of our fundamental components. Our method correctly identifies known pathways and predicts that N-glycan biosynthesis and T-cell receptor signaling may contribute to PTL response. The fundamental gene modules we describe have the potential to provide pathway-level insight into new gene expression datasets.

    View details for DOI 10.1016/j.jbi.2010.07.001

    View details for Web of Science ID 000285036700009

    View details for PubMedID 20619355

    View details for PubMedCentralID PMC2991480

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