Doctor of Philosophy, University of Washington (2019)
Bachelor of Arts, Harvard University (2013)
Joanna Wysocka, Postdoctoral Faculty Sponsor
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
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
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
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 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
View details for Web of Science ID 000424396600007
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
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 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
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