{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/354191"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/354191","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Evolution of the genome in myeloproliferative neoplasms and the methylome in blood","abstract":"The increased accessibility of next generation sequencing (NGS) has unlocked the genomics of normal and diseased haematopoiesis, providing remarkable insights into the rates that mutations are acquired throughout life, mutations that drive disease and the growth rates of clones that acquire driver mutations. Such metrics for DNA methylation, another heritable marker, are less well understood. In this thesis, I use two NGS approaches to answer questions pertaining to genomic evolution in myeloproliferative neoplasms (MPNs) and identify changes in the methylome of blood with age and in the context of driver mutations. In the first study, serial sequencing of bulk samples from 30 patients with MPN coupled with clinical data show that clonal evolution is associated with disease transformation. Moreover, by robustly identifying all SNV mutations in major clones, we can ascribe estimates of timing over which the driver mutations may have occurred. Our timing estimates are in line with recent work by our group using single cell derived haematopoietic colonies (scHCs) and generating phylogenetic trees to time mutation acquisition. In addition, analysis of mutational signatures highlights mutagenic signals associated with therapy. In the second and more substantial body of work, a novel method to interrogate genome- wide methylation is developed and optimised and I show the steps taken to achieve this. I used this method to sequence > 700 scHCs from individuals with normal, aged and MPN haematopoiesis that had already undergone whole genome sequencing. This unique dataset provides fascinating insights into the mechanisms behind epigenetic clocks and how driver mutations may impact upon this. I also demonstrate how we discovered unexpected heritable signals from early life that are retained in scHCs of individuals up to 77 years of age. I conclude by highlighting the additional work we are undergoing to explore such insights further.","abstract_html":"The increased accessibility of next generation sequencing (NGS) has unlocked the genomics of normal and diseased haematopoiesis, providing remarkable insights into the rates that mutations are acquired throughout life, mutations that drive disease and the growth rates of clones that acquire driver mutations. Such metrics for DNA methylation, another heritable marker, are less well understood. In this thesis, I use two NGS approaches to answer questions pertaining to genomic evolution in myeloproliferative neoplasms (MPNs) and identify changes in the methylome of blood with age and in the context of driver mutations. In the first study, serial sequencing of bulk samples from 30 patients with MPN coupled with clinical data show that clonal evolution is associated with disease transformation. Moreover, by robustly identifying all SNV mutations in major clones, we can ascribe estimates of timing over which the driver mutations may have occurred. Our timing estimates are in line with recent work by our group using single cell derived haematopoietic colonies (scHCs) and generating phylogenetic trees to time mutation acquisition. In addition, analysis of mutational signatures highlights mutagenic signals associated with therapy. In the second and more substantial body of work, a novel method to interrogate genome- wide methylation is developed and optimised and I show the steps taken to achieve this. I used this method to sequence > 700 scHCs from individuals with normal, aged and MPN haematopoiesis that had already undergone whole genome sequencing. This unique dataset provides fascinating insights into the mechanisms behind epigenetic clocks and how driver mutations may impact upon this. I also demonstrate how we discovered unexpected heritable signals from early life that are retained in scHCs of individuals up to 77 years of age. I conclude by highlighting the additional work we are undergoing to explore such insights further.","abstract_has_math":false,"creators":["Lee, Joe"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Nangalia, Jyoti","Green, Anthony"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-30","date_published":"2023-01-30","updated_at":"2026-07-22T22:24:23Z","subjects":["Methylation","Methylation clocks","Myeloproliferative neoplasms","Single cell derived haematopoietic colonies","Whole genome sequencing"],"languages":["eng"],"rights":[],"rights_urls":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/457d201f-ba58-4ef1-9927-aaa8321092e8/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.100088","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Nangalia, Jyoti","Green, Anthony"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Wellcome Trust"]},{"key":"dc:creator","label":"Author","values":["Lee, Joe"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2023-01-30"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/354191"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Methylation","Methylation clocks","Myeloproliferative neoplasms","Single cell derived haematopoietic colonies","Whole genome sequencing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/457d201f-ba58-4ef1-9927-aaa8321092e8/download","https://www.rioxx.net/licenses/all-rights-reserved/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.100088"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/873c95dc-7dd1-4daf-a328-89d70ae3b6b3/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The increased accessibility of next generation sequencing (NGS) has unlocked the genomics of normal and diseased haematopoiesis, providing remarkable insights into the rates that mutations are acquired throughout life, mutations that drive disease and the growth rates of clones that acquire driver mutations. Such metrics for DNA methylation, another heritable marker, are less well understood. In this thesis, I use two NGS approaches to answer questions pertaining to genomic evolution in myeloproliferative neoplasms (MPNs) and identify changes in the methylome of blood with age and in the context of driver mutations. In the first study, serial sequencing of bulk samples from 30 patients with MPN coupled with clinical data show that clonal evolution is associated with disease transformation. Moreover, by robustly identifying all SNV mutations in major clones, we can ascribe estimates of timing over which the driver mutations may have occurred. Our timing estimates are in line with recent work by our group using single cell derived haematopoietic colonies (scHCs) and generating phylogenetic trees to time mutation acquisition. In addition, analysis of mutational signatures highlights mutagenic signals associated with therapy. In the second and more substantial body of work, a novel method to interrogate genome- wide methylation is developed and optimised and I show the steps taken to achieve this. I used this method to sequence > 700 scHCs from individuals with normal, aged and MPN haematopoiesis that had already undergone whole genome sequencing. This unique dataset provides fascinating insights into the mechanisms behind epigenetic clocks and how driver mutations may impact upon this. I also demonstrate how we discovered unexpected heritable signals from early life that are retained in scHCs of individuals up to 77 years of age. I conclude by highlighting the additional work we are undergoing to explore such insights further."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["873af636940159823013b917e2b0a671","87eda9de84448d1f82354d60eee3eb5f"]},{"key":"dc:title","label":"Title","values":["Evolution of the genome in myeloproliferative neoplasms and the methylome in blood"]}]}],"canonical_facts":{"dc:contributor.advisor":["Nangalia, Jyoti","Green, Anthony"],"dc:contributor.sponsor":["Wellcome Trust"],"dc:creator":["Lee, Joe"],"dc:date.issued":["2023-01-30"],"dc:description.abstract":["The increased accessibility of next generation sequencing (NGS) has unlocked the genomics of normal and diseased haematopoiesis, providing remarkable insights into the rates that mutations are acquired throughout life, mutations that drive disease and the growth rates of clones that acquire driver mutations. Such metrics for DNA methylation, another heritable marker, are less well understood. In this thesis, I use two NGS approaches to answer questions pertaining to genomic evolution in myeloproliferative neoplasms (MPNs) and identify changes in the methylome of blood with age and in the context of driver mutations. In the first study, serial sequencing of bulk samples from 30 patients with MPN coupled with clinical data show that clonal evolution is associated with disease transformation. Moreover, by robustly identifying all SNV mutations in major clones, we can ascribe estimates of timing over which the driver mutations may have occurred. Our timing estimates are in line with recent work by our group using single cell derived haematopoietic colonies (scHCs) and generating phylogenetic trees to time mutation acquisition. In addition, analysis of mutational signatures highlights mutagenic signals associated with therapy. In the second and more substantial body of work, a novel method to interrogate genome- wide methylation is developed and optimised and I show the steps taken to achieve this. I used this method to sequence > 700 scHCs from individuals with normal, aged and MPN haematopoiesis that had already undergone whole genome sequencing. This unique dataset provides fascinating insights into the mechanisms behind epigenetic clocks and how driver mutations may impact upon this. I also demonstrate how we discovered unexpected heritable signals from early life that are retained in scHCs of individuals up to 77 years of age. I conclude by highlighting the additional work we are undergoing to explore such insights further."],"dc:format.checksum.md5":["873af636940159823013b917e2b0a671","87eda9de84448d1f82354d60eee3eb5f"],"dc:identifier.doi":["https://doi.org/10.17863/CAM.100088"],"dc:identifier.uri":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/873c95dc-7dd1-4daf-a328-89d70ae3b6b3/download"],"dc:language":["eng"],"dc:publisher.institution":["University of Cambridge"],"dc:relation.isreferencedby.uri":["https://www.repository.cam.ac.uk/handle/1810/354191"],"dc:rights":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/457d201f-ba58-4ef1-9927-aaa8321092e8/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"dc:subject":["Methylation","Methylation clocks","Myeloproliferative neoplasms","Single cell derived haematopoietic colonies","Whole genome sequencing"],"dc:title":["Evolution of the genome in myeloproliferative neoplasms and the methylome in blood"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-22T22:24:23Z"}