Here, I investigate chromatin organization on the scale of a few nucleosomes (~1kb). I developed an experimentally-validated coarse-grained polymer model and applied it 1) to show how chromatin fiber parameters, such as nucleosome spacing and breathing, impact chromatin organization on this scale–the mesoscale 2) to interpret mesoscale sequencing assay data and 3) to demonstrate that spatially-correlated cleavage, not protein protection, primarily drives the shape of the distribution of DNA fragment lengths resulting from ionizing-radiation damage. Pair-wise DNA-DNA contact data from DNA sequencing-based assays have the potential to provide locus-specific information about the relationships between chromatin structure and function. Radiation-induced correlated cleavage of chromatin (RICC-seq) is one such assay that reports on characteristic DNA self-contact lengths by sequencing the single-stranded DNA fragments released from cells exposed to large-dose ionizing radiation. Structural inference is necessary to interpret RICC-seq data in terms of chromatin structures. Here, we develop a mesoscale chromatin modeling framework (meso-wlc) to enable the interpretation of RICC-seq data in terms of oligonucleosome structure ensembles. We find that our model reproduces previously observed patterns of fiber compaction as a function of linker DNA length. Using an exponential model of spatially correlated cleavage by ionizing radiation, we predict RICC-seq fragment length distributions from simulated chromatin structure ensembles to determine the correspondence between chromatin structure parameters and the observed RICC-seq signal. Our results show that RICC-seq signal is sensitive to nucleosome repeat length, the extent of nucleosome breathing and the relative strength of inter-nucleosome interactions. Using a 1D convolutional neural net trained on predicted RICC-seq signal, we show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data. Our framework thus provides a suite of analysis tools that add an important layer of quantitative structural interpretability to RICC-seq experiments. I use meso-wlc structure ensembles and another mesoscale chromatin model to investigate the effects of linker histone on mesoscale chromatin compaction. These models provide insights into nucleosome spacing and DNA wrapping changes in linker histone-depleted cells. Lastly, I examine whether the RICC-seq fragment length distribution signal is primarily driven by spatially-correlated cleavage or by protein-conferred protection of DNA from radiation. Simulations indicate that the shape of the RICC-seq fragment length distributions is primarily attributable to spatially-correlated cleavage. Overall, I use coarse-grained mesoscale chromatin simulations to learn more about chromatin organization on the mesoscale.
","abstract_html":"<p>Here, I investigate chromatin organization on the scale of a few nucleosomes (~1kb). I developed an experimentally-validated coarse-grained polymer model and applied it 1) to show how chromatin fiber parameters, such as nucleosome spacing and breathing, impact chromatin organization on this scale–the mesoscale 2) to interpret mesoscale sequencing assay data and 3) to demonstrate that spatially-correlated cleavage, not protein protection, primarily drives the shape of the distribution of DNA fragment lengths resulting from ionizing-radiation damage. Pair-wise DNA-DNA contact data from DNA sequencing-based assays have the potential to provide locus-specific information about the relationships between chromatin structure and function. Radiation-induced correlated cleavage of chromatin (RICC-seq) is one such assay that reports on characteristic DNA self-contact lengths by sequencing the single-stranded DNA fragments released from cells exposed to large-dose ionizing radiation. Structural inference is necessary to interpret RICC-seq data in terms of chromatin structures. Here, we develop a mesoscale chromatin modeling framework (meso-wlc) to enable the interpretation of RICC-seq data in terms of oligonucleosome structure ensembles. We find that our model reproduces previously observed patterns of fiber compaction as a function of linker DNA length. Using an exponential model of spatially correlated cleavage by ionizing radiation, we predict RICC-seq fragment length distributions from simulated chromatin structure ensembles to determine the correspondence between chromatin structure parameters and the observed RICC-seq signal. Our results show that RICC-seq signal is sensitive to nucleosome repeat length, the extent of nucleosome breathing and the relative strength of inter-nucleosome interactions. Using a 1D convolutional neural net trained on predicted RICC-seq signal, we show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data. Our framework thus provides a suite of analysis tools that add an important layer of quantitative structural interpretability to RICC-seq experiments. I use meso-wlc structure ensembles and another mesoscale chromatin model to investigate the effects of linker histone on mesoscale chromatin compaction. These models provide insights into nucleosome spacing and DNA wrapping changes in linker histone-depleted cells. Lastly, I examine whether the RICC-seq fragment length distribution signal is primarily driven by spatially-correlated cleavage or by protein-conferred protection of DNA from radiation. Simulations indicate that the shape of the RICC-seq fragment length distributions is primarily attributable to spatially-correlated cleavage. Overall, I use coarse-grained mesoscale chromatin simulations to learn more about chromatin organization on the mesoscale.</p>","abstract_has_math":false,"creators":["Clerkin, Ariana Brenner"],"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":"2026-07-24T04:11:21Z","subjects":["chromatin organization","mesoscale modeling","nucleosome spacing","RICC-seq","coarse-grained simulation","DNA cleavage","Life Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/797","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":["Clerkin, Ariana Brenner"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2026-10-24T07:00:00Z"]},{"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 organization","mesoscale modeling","nucleosome spacing","RICC-seq","coarse-grained simulation","DNA cleavage","Life Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/797"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Here, I investigate chromatin organization on the scale of a few nucleosomes (~1kb). I developed an experimentally-validated coarse-grained polymer model and applied it 1) to show how chromatin fiber parameters, such as nucleosome spacing and breathing, impact chromatin organization on this scale–the mesoscale 2) to interpret mesoscale sequencing assay data and 3) to demonstrate that spatially-correlated cleavage, not protein protection, primarily drives the shape of the distribution of DNA fragment lengths resulting from ionizing-radiation damage. Pair-wise DNA-DNA contact data from DNA sequencing-based assays have the potential to provide locus-specific information about the relationships between chromatin structure and function. Radiation-induced correlated cleavage of chromatin (RICC-seq) is one such assay that reports on characteristic DNA self-contact lengths by sequencing the single-stranded DNA fragments released from cells exposed to large-dose ionizing radiation. Structural inference is necessary to interpret RICC-seq data in terms of chromatin structures. Here, we develop a mesoscale chromatin modeling framework (meso-wlc) to enable the interpretation of RICC-seq data in terms of oligonucleosome structure ensembles. We find that our model reproduces previously observed patterns of fiber compaction as a function of linker DNA length. Using an exponential model of spatially correlated cleavage by ionizing radiation, we predict RICC-seq fragment length distributions from simulated chromatin structure ensembles to determine the correspondence between chromatin structure parameters and the observed RICC-seq signal. Our results show that RICC-seq signal is sensitive to nucleosome repeat length, the extent of nucleosome breathing and the relative strength of inter-nucleosome interactions. Using a 1D convolutional neural net trained on predicted RICC-seq signal, we show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data. Our framework thus provides a suite of analysis tools that add an important layer of quantitative structural interpretability to RICC-seq experiments. I use meso-wlc structure ensembles and another mesoscale chromatin model to investigate the effects of linker histone on mesoscale chromatin compaction. These models provide insights into nucleosome spacing and DNA wrapping changes in linker histone-depleted cells. Lastly, I examine whether the RICC-seq fragment length distribution signal is primarily driven by spatially-correlated cleavage or by protein-conferred protection of DNA from radiation. Simulations indicate that the shape of the RICC-seq fragment length distributions is primarily attributable to spatially-correlated cleavage. Overall, I use coarse-grained mesoscale chromatin simulations to learn more about chromatin organization on the mesoscale.
"]},{"key":"dc:title","label":"Title","values":["Deriving Structural Insights About Mesoscale Chromatin Folding Using Coarse-Grained Oligonucleosome Modeling"]}]}],"canonical_facts":{"dc:contributor":["Viviana I. Risca"],"dc:creator":["Clerkin, Ariana Brenner"],"dc:date.available":["2026-10-24T07:00:00Z"],"dc:description.abstract":["Here, I investigate chromatin organization on the scale of a few nucleosomes (~1kb). I developed an experimentally-validated coarse-grained polymer model and applied it 1) to show how chromatin fiber parameters, such as nucleosome spacing and breathing, impact chromatin organization on this scale–the mesoscale 2) to interpret mesoscale sequencing assay data and 3) to demonstrate that spatially-correlated cleavage, not protein protection, primarily drives the shape of the distribution of DNA fragment lengths resulting from ionizing-radiation damage. Pair-wise DNA-DNA contact data from DNA sequencing-based assays have the potential to provide locus-specific information about the relationships between chromatin structure and function. Radiation-induced correlated cleavage of chromatin (RICC-seq) is one such assay that reports on characteristic DNA self-contact lengths by sequencing the single-stranded DNA fragments released from cells exposed to large-dose ionizing radiation. Structural inference is necessary to interpret RICC-seq data in terms of chromatin structures. Here, we develop a mesoscale chromatin modeling framework (meso-wlc) to enable the interpretation of RICC-seq data in terms of oligonucleosome structure ensembles. We find that our model reproduces previously observed patterns of fiber compaction as a function of linker DNA length. Using an exponential model of spatially correlated cleavage by ionizing radiation, we predict RICC-seq fragment length distributions from simulated chromatin structure ensembles to determine the correspondence between chromatin structure parameters and the observed RICC-seq signal. Our results show that RICC-seq signal is sensitive to nucleosome repeat length, the extent of nucleosome breathing and the relative strength of inter-nucleosome interactions. Using a 1D convolutional neural net trained on predicted RICC-seq signal, we show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data. Our framework thus provides a suite of analysis tools that add an important layer of quantitative structural interpretability to RICC-seq experiments. I use meso-wlc structure ensembles and another mesoscale chromatin model to investigate the effects of linker histone on mesoscale chromatin compaction. These models provide insights into nucleosome spacing and DNA wrapping changes in linker histone-depleted cells. Lastly, I examine whether the RICC-seq fragment length distribution signal is primarily driven by spatially-correlated cleavage or by protein-conferred protection of DNA from radiation. Simulations indicate that the shape of the RICC-seq fragment length distributions is primarily attributable to spatially-correlated cleavage. Overall, I use coarse-grained mesoscale chromatin simulations to learn more about chromatin organization on the mesoscale.
"],"dc:identifier":["https://digitalcommons.rockefeller.edu/student_theses_and_dissertations/797"],"dc:subject":["chromatin organization","mesoscale modeling","nucleosome spacing","RICC-seq","coarse-grained simulation","DNA cleavage","Life Sciences"],"dc:title":["Deriving Structural Insights About Mesoscale Chromatin Folding Using Coarse-Grained Oligonucleosome Modeling"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T04:11:21Z"}