Stochastic modelling chromosome replication
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Biology
Abstract
All cells contain a complete copy of the organism's DNA, the genetic blueprint of life, packaged into discrete units called chromosomes. Since new cells need a copy of the genetic material, the chromosomes must be completely and accurately replicated before the cell can divide. Eukaryotes, such as yeast and humans, have large genomes with millions of bases encoding the genetic information. To ensure complete replication of these genomes within the allowed time, the process of DNA replication starts at multiple sites along each chromosome, called replication origins. These replication origins are specialised DNA sequences that assemble the cellular machinery that then moves along the DNA reading and copying the genetic material. It is essential that the cell activates sufficient replication origins to ensure complete replication of the chromosomes. The importance of controlling replication origin activation is highlighted by the genome instability that may result from uncontrolled chromosome replication. Despite the importance of DNA replication origins we understand little about the DNA sequences that specify and control them. Failures in the processes of DNA replication lead to genetic instability and diseases such as cancer and congenital disorders. We hope that a better understanding of the basic biology that ensures genetic integrity will give new insights that will allow improved diagnosis and treatment of these diseases. We want to understand how the multiple replication origins on each chromosome are coordinated to ensure that the chromosome is successfully replicated. To study this 'system' we have developed a mathematical model that can be used to simulate the behaviour of all the replication origins on a chromosome. Now we will use our mathematical model to make predictions about chromosome replication that we can test experimentally in the lab. This will allow us to improve the model and include more complex scenarios. One such scenario is what happens when the DNA replication process encounters damage to the DNA. This is important, as damage to the DNA gives rise to genetic diseases such as cancer. Furthermore, many drugs that target cancer cells (chemotherapy) work by damaging the DNA, since cancer cells are more vulnerable to DNA damage than normal healthy cells. By combining mathematical modelling and experimental work we aim to identify the strengths and weaknesses of the chromosome replication process that may underlie genetic diseases such as cancer. In the long-term this work will help in our understanding of the biological basis of genetic diseases, including cancer, and may lead to new therapeutic strategies.
Technical Summary
Complete, accurate genome replication is essential for life. DNA replication is controlled by regulating the activation of replication origins - the sites of initiation of bi-directional replication forks. Eukaryotic genomes have an excess of potential replication origin sites, only a subset of which are utilised in any given cell cycle. The presence of more potential origins than are actually used may provide genome replication with robustness to ensure complete replication within S phase, particularly in the face of insults such as DNA damage. The purpose of this research is to develop and validate a predictive mathematical model of chromosome replication, and to use this model to understand how robustness to replication impediments is ensured to allow successful genome replication. Mathematical models of biological processes require the definition and measurement of the parameters that define the system. Budding yeast chromosome replication is particularly amenable to modelling, since the system is well characterised and amenable to whole genome methods for measuring the system parameters. Moreover, the genome structure can be genetically manipulated to test predictions. We have developed a preliminary mathematical model of chromosome replication. Next we will experimentally validate this model by testing its ability to predict the replication dynamics of perturbed replication systems. For example, we will use modified yeast strains in which individual replication origins have been deleted. Then we will extend the model to simulate the response of the replication system to insults, such as DNA damage, to uncover how genome replication retains robustness. In the long term, determining these mechanisms will be crucial for understanding the biological basis of genetic diseases, including cancer, and improving therapeutic strategies.
Publications
De Moura AP
(2010)
Mathematical modelling of whole chromosome replication.
in Nucleic acids research
Hawkins M
(2013)
Accelerated growth in the absence of DNA replication origins.
in Nature
Hawkins M
(2013)
High-resolution replication profiles define the stochastic nature of genome replication initiation and termination.
in Cell reports
Hoggard T
(2013)
A Link between ORC-origin binding mechanisms and origin activation time revealed in budding yeast.
in PLoS genetics
Karschau J
(2012)
Optimal Placement of Origins for DNA Replication
Karschau J
(2012)
Optimal placement of origins for DNA replication.
in Physical review letters
Liti G
(2013)
High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome.
in BMC genomics
Müller CA
(2012)
Conservation of replication timing reveals global and local regulation of replication origin activity.
in Genome research
Müller CA
(2014)
The dynamics of genome replication using deep sequencing.
in Nucleic acids research
Natsume T
(2013)
Kinetochores Coordinate Pericentromeric Cohesion and Early DNA Replication by Cdc7-Dbf4 Kinase Recruitment
in Molecular Cell
Newman TJ
(2013)
Replisome stall events have shaped the distribution of replication origins in the genomes of yeasts.
in Nucleic acids research
Nieduszynski CA
(2011)
From sequence to function: Insights from natural variation in budding yeasts.
in Biochimica et biophysica acta
Prusokas A
(2018)
The effectiveness of glass beads for plating cell cultures
Retkute R
(2011)
Dynamics of DNA replication in yeast.
in Physical review letters
Retkute R
(2012)
Mathematical modeling of genome replication.
in Physical review. E, Statistical, nonlinear, and soft matter physics
Saner N
(2013)
Stochastic association of neighboring replicons creates replication factories in budding yeast.
in The Journal of cell biology
Shor E
(2009)
The origin recognition complex interacts with a subset of metabolic genes tightly linked to origins of replication.
in PLoS genetics
Siow C
(2011)
OriDB, the DNA replication origin database updated and extended
in Nucleic Acids Research
Description | During this project new methodologies and analytical tools (including software) were developed. We developed deep sequencing technologies to study the dynamics of genome replication. This required custom software to process the wealth of sequence data. In addition we developed mathematical models and software to allow the maximum amount of information to be derived from these data. |
Exploitation Route | Our mathematical models will form the basis for more sophisticated models of chromosome and cell biology. |
Sectors | Other |
Description | Wellcome Trust Investigator Award |
Amount | £1,279,523 (GBP) |
Funding ID | 110064/Z/15/Z |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 05/2016 |
End | 05/2021 |
Title | Sort-seq |
Description | This methodology allows genome-wide measurement of the dynamics of DNA replication. |
Type Of Material | Technology assay or reagent |
Year Produced | 2011 |
Provided To Others? | Yes |
Impact | The methodology has allowed multiple mechanisms that regulate DNA replication and directly contribute to genome stability to be elucidated. Including in the following collaborative publications: Rudolph, C.J., Upton, A.L., Stockum, A., Nieduszynski, C.A. and Lloyd, R.G., 2013. Avoiding chromosome pathology when replication forks collide. Nature, 500(7464), pp.608-611. Natsume, T., Müller, C.A., Katou, Y., Retkute, R., Gierlinski, M., Araki, H., Blow, J.J., Shirahige, K., Nieduszynski, C.A. and Tanaka, T.U., 2013. Kinetochores coordinate pericentromeric cohesion and early DNA replication by Cdc7-Dbf4 kinase recruitment. Molecular cell, 50(5), pp.661-674. Hawkins, M., Malla, S., Blythe, M.J., Nieduszynski, C.A. and Allers, T., 2013. Accelerated growth in the absence of DNA replication origins. Nature, 503(7477), pp.544-547. Daigaku, Y., Keszthelyi, A., Müller, C.A., Miyabe, I., Brooks, T., Retkute, R., Hubank, M., Nieduszynski, C.A. and Carr, A.M., 2015. A global profile of replicative polymerase usage. Nature structural & molecular biology, 22(3), pp.192-198. |
URL | https://nar.oxfordjournals.org/content/42/1/e3.full |
Description | Article for 'The Conversation' |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | This was an online article for the general public to accompany our paper: Hawkins, M., Malla, S., Blythe, M.J., Nieduszynski, C.A. and Allers, T., 2013. Accelerated growth in the absence of DNA replication origins. Nature, 503(7477), pp.544-547. The article had high visibility with many shares via social media. |
Year(s) Of Engagement Activity | 2013 |
URL | http://theconversation.com/selfish-gene-solves-dna-replication-puzzle-20166 |
Description | Schools Outreach (Nottingham) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | School-based science activities at local schools (to year 12 and 13 pupils) to demonstrate the power of genetic analysis. The activities generated lively discussions and many questions. We had positive feedback from the schools, who emphasised the value to pupils deciding on university-level courses. |
Year(s) Of Engagement Activity | 2010,2011,2012 |
Description | Schools outreach |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Presentation about 'Genome Science' to science pupils at Tunbridge School. The presentation included an opportunity for pupils to test there own response to a taste test and then understand the pattern of inheritance. This generated lively discussions and many questions. I had positive feedback from the schools, who emphasised the value to pupils deciding on university-level courses. |
Year(s) Of Engagement Activity | 2013,2014 |