Stanford Advisors

All Publications

  • Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage. bioRxiv : the preprint server for biology Naqvi, S., Kim, S., Tabatabaee, S., Pampari, A., Kundaje, A., Pritchard, J. K., Wysocka, J. 2024


    Deep learning approaches have made significant advances in predicting cell type-specific chromatin patterns from the identity and arrangement of transcription factor (TF) binding motifs. However, most models have been applied in unperturbed contexts, precluding a predictive understanding of how chromatin state responds to TF perturbation. Here, we used transfer learning to train and interpret deep learning models that use DNA sequence to predict, with accuracy approaching experimental reproducibility, how the concentration of two dosage-sensitive TFs (TWIST1, SOX9) affects regulatory element (RE) chromatin accessibility in facial progenitor cells. High-affinity motifs that allow for heterotypic TF co-binding and are concentrated at the center of REs buffer against quantitative changes in TF dosage and strongly predict unperturbed accessibility. In contrast, motifs with low-affinity or homotypic binding distributed throughout REs lead to sensitive responses with minimal contributions to unperturbed accessibility. Both buffering and sensitizing features show signatures of purifying selection. We validated these predictive sequence features using reporter assays and showed that a biophysical model of TF-nucleosome competition can explain the sensitizing effect of low-affinity motifs. Our approach of combining transfer learning and quantitative measurements of the chromatin response to TF dosage therefore represents a powerful method to reveal additional layers of the cis-regulatory code.

    View details for DOI 10.1101/2024.05.28.596078

    View details for PubMedID 38853998

  • DNA-guided transcription factor cooperativity shapes face and limb mesenchyme. Cell Kim, S., Morgunova, E., Naqvi, S., Goovaerts, S., Bader, M., Koska, M., Popov, A., Luong, C., Pogson, A., Swigut, T., Claes, P., Taipale, J., Wysocka, J. 2024


    Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest that it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how "Coordinator," a long DNA motif composed of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines the regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, whereas HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in the shared regulation of genes involved in cell-type and positional identities and ultimately shapes facial morphology and evolution.

    View details for DOI 10.1016/j.cell.2023.12.032

    View details for PubMedID 38262408

  • DNA-guided transcription factor cooperativity shapes face and limb mesenchyme. bioRxiv : the preprint server for biology Kim, S., Morgunova, E., Naqvi, S., Bader, M., Koska, M., Popov, A., Luong, C., Pogson, A., Claes, P., Taipale, J., Wysocka, J. 2023


    Transcription factors (TFs) can define distinct cellular identities despite nearly identical DNA-binding specificities. One mechanism for achieving regulatory specificity is DNA-guided TF cooperativity. Although in vitro studies suggest it may be common, examples of such cooperativity remain scarce in cellular contexts. Here, we demonstrate how 'Coordinator', a long DNA motif comprised of common motifs bound by many basic helix-loop-helix (bHLH) and homeodomain (HD) TFs, uniquely defines regulatory regions of embryonic face and limb mesenchyme. Coordinator guides cooperative and selective binding between the bHLH family mesenchymal regulator TWIST1 and a collective of HD factors associated with regional identities in the face and limb. TWIST1 is required for HD binding and open chromatin at Coordinator sites, while HD factors stabilize TWIST1 occupancy at Coordinator and titrate it away from HD-independent sites. This cooperativity results in shared regulation of genes involved in cell-type and positional identities, and ultimately shapes facial morphology and evolution.

    View details for DOI 10.1101/2023.05.29.541540

    View details for PubMedID 37398193

    View details for PubMedCentralID PMC10312427

  • Precise modulation of transcription factor levels identifies features underlying dosage sensitivity. Nature genetics Naqvi, S., Kim, S., Hoskens, H., Matthews, H. S., Spritz, R. A., Klein, O. D., Hallgrimsson, B., Swigut, T., Claes, P., Pritchard, J. K., Wysocka, J. 2023


    Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.

    View details for DOI 10.1038/s41588-023-01366-2

    View details for PubMedID 37024583

  • Deciphering the multi-scale, quantitative cis-regulatory code. Molecular cell Kim, S., Wysocka, J. 2023


    Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.

    View details for DOI 10.1016/j.molcel.2022.12.032

    View details for PubMedID 36693380

  • Mechanisms of Interplay between Transcription Factors and the 3D Genome. Molecular cell Kim, S., Shendure, J. 2019


    Transcription factors (TFs) bind DNA in a sequence-specific manner and thereby serve as the protein anchors and determinants of 3D genome organization. Conversely, chromatin conformation shapes TF activity, for example, by looping TF-bound enhancers to distally located target genes. Despite considerable effort, our understanding of the mechanistic relation between TFs and 3D genome organization remains limited, in large part due to this interdependency. In this review, we summarize the evidence for the diverse mechanisms by which TFs and their activity shape the 3D genome and vice versa. We further highlight outstanding questions and potential approaches for untangling the complex relation between TF activity and the 3D genome.

    View details for DOI 10.1016/j.molcel.2019.08.010

    View details for PubMedID 31521504

  • A combination of transcription factors mediates inducible interchromosomal contacts ELIFE Kim, S., Dunham, M. J., Shendure, J. 2019; 8


    The genome forms specific three-dimensional contacts in response to cellular or environmental conditions. However, it remains largely unknown which proteins specify and mediate such contacts. Here we describe an assay, MAP-C (Mutation Analysis in Pools by Chromosome conformation capture), that simultaneously characterizes the effects of hundreds of cis or trans-acting mutations on a chromosomal contact. Using MAP-C, we show that inducible interchromosomal pairing between HAS1pr-TDA1pr alleles in saturated cultures of Saccharomyces yeast is mediated by three transcription factors, Leu3, Sdd4 (Ypr022c), and Rgt1. The coincident, combined binding of all three factors is strongest at the HAS1pr-TDA1pr locus and is also specific to saturated conditions. We applied MAP-C to further explore the biochemical mechanism of these contacts, and find they require the structured regulatory domain of Rgt1, but no known interaction partners of Rgt1. Altogether, our results demonstrate MAP-C as a powerful method for dissecting the mechanistic basis of chromosome conformation.

    View details for DOI 10.7554/eLife.42499

    View details for Web of Science ID 000470717700001

    View details for PubMedID 31081754

    View details for PubMedCentralID PMC6548505

  • Condensin-Dependent Chromatin Compaction Represses Transcription Globally during Quiescence MOLECULAR CELL Swygert, S. G., Kim, S., Wu, X., Fu, T., Hsieh, T., Rando, O. J., Eisenman, R. N., Shendure, J., McKnight, J. N., Tsukiyama, T. 2019; 73 (3): 533-+


    Quiescence is a stress-resistant state in which cells reversibly exit the cell cycle and suspend most processes. Quiescence is essential for stem cell maintenance, and its misregulation is implicated in tumor formation. One of the hallmarks of quiescent cells is highly condensed chromatin. Because condensed chromatin often correlates with transcriptional silencing, it has been hypothesized that chromatin compaction represses transcription during quiescence. However, the technology to test this model by determining chromatin structure within cells at gene resolution has not previously been available. Here, we use Micro-C XL to map chromatin contacts at single-nucleosome resolution genome-wide in quiescent Saccharomyces cerevisiae cells. We describe chromatin domains on the order of 10-60 kilobases that, only in quiescent cells, are formed by condensin-mediated loops. Condensin depletion prevents the compaction of chromatin within domains and leads to widespread transcriptional de-repression. Finally, we demonstrate that condensin-dependent chromatin compaction is conserved in quiescent human fibroblasts.

    View details for DOI 10.1016/j.molcel.2018.11.020

    View details for Web of Science ID 000458015200013

    View details for PubMedID 30595435

    View details for PubMedCentralID PMC6368455

  • A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens CELL Gasperini, M., Hill, A. J., McFaline-Figueroa, J. L., Martin, B., Kim, S., Zhang, M. D., Jackson, D., Leith, A., Schreiber, J., Noble, W. S., Trapnell, C., Ahituv, N., Shendure, J. 2019; 176 (1-2): 377-+


    Over one million candidate regulatory elements have been identified across the human genome, but nearly all are unvalidated and their target genes uncertain. Approaches based on human genetics are limited in scope to common variants and in resolution by linkage disequilibrium. We present a multiplex, expression quantitative trait locus (eQTL)-inspired framework for mapping enhancer-gene pairs by introducing random combinations of CRISPR/Cas9-mediated perturbations to each of many cells, followed by single-cell RNA sequencing (RNA-seq). Across two experiments, we used dCas9-KRAB to perturb 5,920 candidate enhancers with no strong a priori hypothesis as to their target gene(s), measuring effects by profiling 254,974 single-cell transcriptomes. We identified 664 (470 high-confidence) cis enhancer-gene pairs, which were enriched for specific transcription factors, non-housekeeping status, and genomic and 3D conformational proximity to their target genes. This framework will facilitate the large-scale mapping of enhancer-gene regulatory interactions, a critical yet largely uncharted component of the cis-regulatory landscape of the human genome.

    View details for DOI 10.1016/j.cell.2018.11.029

    View details for Web of Science ID 000455410800031

    View details for PubMedID 30612741

    View details for PubMedCentralID PMC6690346

  • The 4D nucleome project NATURE Dekker, J., Belmont, A. S., Guttman, M., Leshyk, V. O., Lis, J. T., Lomvardas, S., Mirny, L. A., O'Shea, C. C., Park, P. J., Ren, B., Politz, J., Shendure, J., Zhong, S., van den Berg, A., Heckert, A., Bertero, A., Bortnick, A., Kukalev, A., Moore, A., Pombo, A., Hansen, A., Chiariello, A., Sali, A., Belmont, A., Stephens, A., Nand, A., Valton, A., Goloborodko, A., He, A., van Steensel, B., Webb, B., Roscoe, B., Li, B., Ren, B., Chait, B., Blau, C., Annunziatella, C., Ware, C., Wei, C., Leemans, C., Disteche, C., Jarjour, C., Thieme, C., Murry, C., Barcia, C., Trapnell, C., Murre, C., Peric-Hupkes, D., Simon, D., Bartlett, D., Gao, D., Plewczynski, D., Gilbert, D., Gorkin, D., McSwiggen, D., Lin, D., Aghamirzaie, D., Banigan, E., Finn, E., Sontheimer, E., Cadete, F., Alber, F., Mast, F., Filippova, G., Yardimci, G., Fudenberg, G., Loof, G., Bonora, G., Pegoraro, G., Caglio, G., Polles, G., Ozadam, H., Shin, H., Pliner, H., Reinecke, H., Li, H., Tjong, H., Fang, H., Marie-Nelly, H., Belaghzal, H., Brandao, H., Zhao, H., Cisse, I., Jung, I., Tasan, I., Juric, I., Andrews, J., Schreiber, J., Spille, J., Zimmerman, J., Shendure, J., Dixon, J., Ma, J., Xu, J., Sima, J., Dekker, J., Gibcus, J., Nuebler, J., Aitchison, J., Marko, J., Lam, J., Mendieta, J., Rivera Mulia, J., Cayford, J., Cook, K., Mitzelfelt, K., Parsi, K., Klein, K., Brueckner, L., Mirny, L., Zhang, L., Pabon, L., Chen, L., Carpp, L., Yang, L., Pei, L., Sander, M., Imakaev, M., Nicodemi, M., Schueler, M., Falk, M., Denholtz, M., Libbrecht, M., Bolukbasi, M., Zhen, M., Yu, M., Rout, M., Hu, M., Mir, M., Armani, N., Hua, N., Kubo, N., Abdennur, N., Krietenstein, N., Khanna, N., Dudko, O., Rando, O., Luo, O., Chaturvedi, P., Blainey, P., Fields, P., Wang, P., Li, Q., Casellas, R., Gudla, R., Maeh, R., Kempfer, R., Beagrie, R., Biggs, R., Fang, R., Qiu, R., Jude Genga, R., Srivatsan, S., Kumar, S., Wolfe, S., Shaffer, S., Kim, S., Shachar, S., Bianco, S., Jain, S., Sasaki, T., Isoda, T., Misteli, T., van Schaik, T., Liu, T., Hsieh, T., Ramani, V., Agarwal, V., Dileep, V., Chandra, V., Winick-Ng, W., Li, W., Noble, W., Darzacq, X., Zhou, X., Deng, X., Xiong, X., Yang, X., Yang, Y., Zhang, Y., Kou, Y., Zhou, Y., Ruan, Y., Chen, Y., Wang, Y., Qiu, Y., Duan, Z., Tang, Z., Ozer, A., Cote, A., Tanay, A., Chow, A., Omer, A. D., Hwang, A., Dudley, C., Bartman, C., Danko, C., Varnai, C., Aiden, E., Blobel, G., Lin, H., Phillips-Cremins, J., Lis, J., Wang, J., Ray, J., Dunagin, M., Arrastia, M., Lai, M., Curtis, M., Kushner, M., Pham, M., Wang, M., Yang, M., Guttman, M., Durand, N. C., Ollikainen, N., Munn, P., Fraser, P., Ismagilov, R., Hsu, S., Bhardwaj, S., Quinodoz, S., Nagano, T., Amarante, T., Zipfel, W., Baran, Y., Lubling, Y., Wang, Z., Palla, A., Muimbey-Wahula, A., Vertii, A., Moradian, A., Larabell, C., Brangwynne, C., Lindsay, C., Sanders, D., Scalzo, D., Cannavo, E., McDermott, G., Ozadam, H., Ma, H., Moresco, J., Ritland, J., Dekker, J., Rinn, J., Yates, J., Zhu, J., Roth, K., Gerace, L., Tait, L., Brown, L., Zhu, L., Kordon, M., Groudine, M., Le Gros, M., Escamilla, M., Sweredoski, M., Guttman, M., Kaufman, P., Maas, P., Barutcu, R., Amin, R., Baboo, S., Debartolome, S., Hess, S., Lomvardas, S., Pederson, T., Szempruch, T., Walkup, W., Sun, X., Shin, Y., Senecal, A., Hansen, A., Barentine, A., Spakowitz, A., Gustavsson, A., Tangara, A., Rieger, B., Nijmeijer, B., Lim, B., English, B., Barton, C., Kenworthy, C., Carroll, C., O'Shea, C., Boassa, D., Baddeley, D., Grunwald, D., Birney, E., Chuang, F., Castillon, G., Wang, H., Grabmayr, H., Chen, H., Ou, H., Ellenberg, J., Liphardt, J., Soroczynski, J., Biswas, J., Yao, J., Yin, J., Bewersdorf, J., Ries, J., Bardales, J., Roberti, J., Zaret, K., Chung, K., Lam, K., Qi, L. S., Schmitt, L., Barinov, L., Tu, L., Yang, L., Tian, L., Cai, L., Ellisman, M., Mackey, M., Haberl, M., Huisman, M., Clark, M., Levo, M., Levine, M., Mir, M., Walther, N., Oedegaard, O., Guo, P., Zheng, Q., Cheng, R., Ghosh, R., Ramachandra, R., Coleman, R., Singer, R., Liu, R., Walden, R., Phan, S., Ramachandra, S., Coleman, R., Singer, R., Liu, R., Walden, R., Phan, S., Quanming, S., Ganguly, S., Alexander, S., Peltier, S., Fukaya, T., Deerinck, T., Gregor, T., Fitzgerald, T., Moerner, W., Darzacq, X., Zhang, Y., Li, Y., Takei, Y., Izumiya, Y., Lin, Y., Frankenstein, Z., Ren, B., Kling, C., Rivera, C., Zheng, H., Rivera, K., Hebert, L., Rivas-Astroza, M., Wu, Q., Calandrelli, R., Subramaniam, S., Zhong, S., Chien, S., Leshyk, V., Chen, W., Cao, X., Yan, Z., Balashov, A., Schroeder, A., Goloborodko, A., Alver, B., Vitzthum, C., Nam, C., Li, D., Purushotham, D., Pehrsson, E. C., Yue, F., Lekschas, F., Pfister, H., Strobelt, H., Brandao, H., Jang, H., Luber, J., Hwang, J., Walsh, J., Johnson, J., Nubler, J., Kirli, K., Mirny, L., Falk, M., Imakaev, M., Choudhary, M. K., Abdennur, N., Gehlenborg, N., Kerpedjiev, P., Park, P., Kharchenko, P. V., Sears, R. L., Lee, S., Wang, S., Yang, T., Hu, T., Wang, T., Hou, Y., 4D Nucleome Network 2017; 549 (7671): 219–26


    The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

    View details for DOI 10.1038/nature23884

    View details for Web of Science ID 000410555900035

    View details for PubMedID 28905911

    View details for PubMedCentralID PMC5617335

  • Somatic Homolog Pairing in Yeast CELL SYSTEMS Kim, S., Shendure, J., Dunham, M. J. 2017; 5 (1): 4
  • The dynamic three-dimensional organization of the diploid yeast genome ELIFE Kim, S., Liachko, I., Brickner, D. G., Cook, K., Noble, W. S., Brickner, J. H., Shendure, J., Dunham, M. J. 2017; 6


    The budding yeast Saccharomyces cerevisiae is a long-standing model for the three-dimensional organization of eukaryotic genomes. However, even in this well-studied model, it is unclear how homolog pairing in diploids or environmental conditions influence overall genome organization. Here, we performed high-throughput chromosome conformation capture on diverged Saccharomyces hybrid diploids to obtain the first global view of chromosome conformation in diploid yeasts. After controlling for the Rabl-like orientation using a polymer model, we observe significant homolog proximity that increases in saturated culture conditions. Surprisingly, we observe a localized increase in homologous interactions between the HAS1-TDA1 alleles specifically under galactose induction and saturated growth. This pairing is accompanied by relocalization to the nuclear periphery and requires Nup2, suggesting a role for nuclear pore complexes. Together, these results reveal that the diploid yeast genome has a dynamic and complex 3D organization.

    View details for DOI 10.7554/eLife.23623

    View details for Web of Science ID 000403555900001

    View details for PubMedID 28537556

    View details for PubMedCentralID PMC5476426

  • Delayed commitment to evolutionary fate in antibiotic resistance fitness landscapes NATURE COMMUNICATIONS Palmer, A. C., Toprak, E., Baym, M., Kim, S., Veres, A., Bershtein, S., Kishony, R. 2015; 6: 7385


    Predicting evolutionary paths to antibiotic resistance is key for understanding and controlling drug resistance. When considering a single final resistant genotype, epistatic contingencies among mutations restrict evolution to a small number of adaptive paths. Less attention has been given to multi-peak landscapes, and while specific peaks can be favoured, it is unknown whether and how early a commitment to final fate is made. Here we characterize a multi-peaked adaptive landscape for trimethoprim resistance by constructing all combinatorial alleles of seven resistance-conferring mutations in dihydrofolate reductase. We observe that epistatic interactions increase rather than decrease the accessibility of each peak; while they restrict the number of direct paths, they generate more indirect paths, where mutations are adaptively gained and later adaptively lost or changed. This enhanced accessibility allows evolution to proceed through many adaptive steps while delaying commitment to genotypic fate, hindering our ability to predict or control evolutionary outcomes.

    View details for DOI 10.1038/ncomms8385

    View details for Web of Science ID 000357175300018

    View details for PubMedID 26060115

    View details for PubMedCentralID PMC4548896

  • Alternating antibiotic treatments constrain evolutionary paths to multidrug resistance PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Kim, S., Lieberman, T. D., Kishony, R. 2014; 111 (40): 14494–99


    Alternating antibiotic therapy, in which pairs of drugs are cycled during treatment, has been suggested as a means to inhibit the evolution of de novo resistance while avoiding the toxicity associated with more traditional combination therapy. However, it remains unclear under which conditions and by what means such alternating treatments impede the evolution of resistance. Here, we tracked multistep evolution of resistance in replicate populations of Staphylococcus aureus during 22 d of continuously increasing single-, mixed-, and alternating-drug treatment. In all three tested drug pairs, the alternating treatment reduced the overall rate of resistance by slowing the acquisition of resistance to one of the two component drugs, sometimes as effectively as mixed treatment. This slower rate of evolution is reflected in the genome-wide mutational profiles; under alternating treatments, bacteria acquire mutations in different genes than under corresponding single-drug treatments. To test whether this observed constraint on adaptive paths reflects trade-offs in which resistance to one drug is accompanied by sensitivity to a second drug, we profiled many single-step mutants for cross-resistance. Indeed, the average cross-resistance of single-step mutants can help predict whether or not evolution was slower in alternating drugs. Together, these results show that despite the complex evolutionary landscape of multidrug resistance, alternating-drug therapy can slow evolution by constraining the mutational paths toward resistance.

    View details for DOI 10.1073/pnas.1409800111

    View details for Web of Science ID 000342633900052

    View details for PubMedID 25246554

    View details for PubMedCentralID PMC4210010