The spatial organization of chromatin fiber at the level of several nucleosomes–the mesoscale–is an area of active study. Recent results have shown that it differs between functional states, affects higher orders of chromosome organization, and is likely involved in transcriptional control. However, the heterogeneity of nucleosome positioning and histone variant composition in cells as well as the high density of chromatin in situ make the mesoscale difficult to study. Recent methodological advances have made it possible to derive nucleosome-resolution three-dimensional contact information directly from cells. We therefore sought to develop a structural inference tool for inferring mesoscale chromatin structures consistent with such contact data sets. We have built a Bayesian inference framework that combines a simplified worm-like chain model of DNA and steric interactions between nucleosomes with a pseudopotential that represents the structure's fit to experimental data. We show how this framework can be used to fit oligonucleosome structures to high-coverage Region Capture Micro-C data at several-kilobase regions of interest, evaluate the goodness-of-fit, and discuss how the framework's modularity could lead to promising future work with other types of experimental data. Additionally, we show preliminary data from radiation simulations that will be used to develop models for Radiation-Induced Correlated Cleavage experiments, which will also be incorporated into the structural inference model in future work.
","abstract_html":"<p>The spatial organization of chromatin fiber at the level of several nucleosomes–the mesoscale–is an area of active study. Recent results have shown that it differs between functional states, affects higher orders of chromosome organization, and is likely involved in transcriptional control. However, the heterogeneity of nucleosome positioning and histone variant composition in cells as well as the high density of chromatin <em>in situ</em> make the mesoscale difficult to study. Recent methodological advances have made it possible to derive nucleosome-resolution three-dimensional contact information directly from cells. We therefore sought to develop a structural inference tool for inferring mesoscale chromatin structures consistent with such contact data sets. We have built a Bayesian inference framework that combines a simplified worm-like chain model of DNA and steric interactions between nucleosomes with a pseudopotential that represents the structure's fit to experimental data. We show how this framework can be used to fit oligonucleosome structures to high-coverage Region Capture Micro-C data at several-kilobase regions of interest, evaluate the goodness-of-fit, and discuss how the framework's modularity could lead to promising future work with other types of experimental data. Additionally, we show preliminary data from radiation simulations that will be used to develop models for Radiation-Induced Correlated Cleavage experiments, which will also be incorporated into the structural inference model in future work.</p>","abstract_has_math":false,"creators":["West, Devany Walsh"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Viviana I. Risca"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T04:10:53Z","subjects":["chromatin","nucleosomes","mesoscale","structure inference","Micro Capture-C (MCC)","Bayesian modeling","Life Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/830","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Viviana I. Risca"]},{"key":"dc:creator","label":"Author","values":["West, Devany Walsh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["chromatin","nucleosomes","mesoscale","structure inference","Micro Capture-C (MCC)","Bayesian modeling","Life Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/830"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The spatial organization of chromatin fiber at the level of several nucleosomes–the mesoscale–is an area of active study. Recent results have shown that it differs between functional states, affects higher orders of chromosome organization, and is likely involved in transcriptional control. However, the heterogeneity of nucleosome positioning and histone variant composition in cells as well as the high density of chromatin in situ make the mesoscale difficult to study. Recent methodological advances have made it possible to derive nucleosome-resolution three-dimensional contact information directly from cells. We therefore sought to develop a structural inference tool for inferring mesoscale chromatin structures consistent with such contact data sets. We have built a Bayesian inference framework that combines a simplified worm-like chain model of DNA and steric interactions between nucleosomes with a pseudopotential that represents the structure's fit to experimental data. We show how this framework can be used to fit oligonucleosome structures to high-coverage Region Capture Micro-C data at several-kilobase regions of interest, evaluate the goodness-of-fit, and discuss how the framework's modularity could lead to promising future work with other types of experimental data. Additionally, we show preliminary data from radiation simulations that will be used to develop models for Radiation-Induced Correlated Cleavage experiments, which will also be incorporated into the structural inference model in future work.
"]},{"key":"dc:title","label":"Title","values":["Towards Models Mesoscale Chromatin Structure and Radiative DNA Damage via Computational Simulation"]}]}],"canonical_facts":{"dc:contributor":["Viviana I. Risca"],"dc:creator":["West, Devany Walsh"],"dc:description.abstract":["The spatial organization of chromatin fiber at the level of several nucleosomes–the mesoscale–is an area of active study. Recent results have shown that it differs between functional states, affects higher orders of chromosome organization, and is likely involved in transcriptional control. However, the heterogeneity of nucleosome positioning and histone variant composition in cells as well as the high density of chromatin in situ make the mesoscale difficult to study. Recent methodological advances have made it possible to derive nucleosome-resolution three-dimensional contact information directly from cells. We therefore sought to develop a structural inference tool for inferring mesoscale chromatin structures consistent with such contact data sets. We have built a Bayesian inference framework that combines a simplified worm-like chain model of DNA and steric interactions between nucleosomes with a pseudopotential that represents the structure's fit to experimental data. We show how this framework can be used to fit oligonucleosome structures to high-coverage Region Capture Micro-C data at several-kilobase regions of interest, evaluate the goodness-of-fit, and discuss how the framework's modularity could lead to promising future work with other types of experimental data. Additionally, we show preliminary data from radiation simulations that will be used to develop models for Radiation-Induced Correlated Cleavage experiments, which will also be incorporated into the structural inference model in future work.
"],"dc:identifier":["https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/830"],"dc:subject":["chromatin","nucleosomes","mesoscale","structure inference","Micro Capture-C (MCC)","Bayesian modeling","Life Sciences"],"dc:title":["Towards Models Mesoscale Chromatin Structure and Radiative DNA Damage via Computational Simulation"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:10:53Z"}