Genomic methods for measuring DNA replication timing

 

We developed two related methods to measure replication timing across the entire genome: an experimental method and a predominantly computational method. Both of these methods rely on the principle that when DNA is replicated its copy number doubles, and the earlier a genomic region replicates, the higher its average copy number in a population of replicating cells. In the experimental method, replicating S phase cells are FACS-sorted, DNA is extracted and whole-genome sequenced, and fluctuations in DNA copy number along chromosomes are used to retrieve the cells' replication timing program. This method is highly accurate and applicable to a handful of samples at a time. In the computational method, whole-genome DNA sequences that were derived (knowingly or not) from cell cultures or tissues that were proliferating at the time of DNA extraction are used to analyze DNA copy number. Copy number fluctuations in these samples reflect DNA replication timing. This method enables studying replication timing in hundreds of samples. We are applying these methods to study replication timing in different people, cell types, and species, both in our lab and through various collaborations.

 

Massey et al., Genes 2019

Siefert et al., Genome Research 2017

Koren et al., Cell 2014

Koren et al., American Journal of Human Genetics 2012

Koren et al., Genome Research 2010

Koren et al., PLoS Genetics 2010

Replication timing quantitative trait loci (rtQTLs)

 

We found that replication timing is highly variable among people, with hundreds of genomic regions being replicated at different times in different people. By comparing people's genotypes to their replication profiles, we discovered specific SNPs that determine when a genomic locus replicates. We called these “replication timing quantitative trait loci” (rtQTLs). rtQTL mapping links DNA replication timing to other molecular and phenotypic traits. For instance, we showed that an rtQTL near the JAK2 gene links DNA replication timing with the susceptibility to blood neoplasms and leukemia. A major focus of our lab is to fine-map many more rtQTLs, in several cell types, and to use them to study the molecular causes and the cellular and phenotypic consequences of human DNA replication timing.

 

Koren et al., Cell 2014

DNA replication timing shapes the

mutational landscape of the genome

 

We found that in blood cells, late-replicating genomic regions have a 4-6-fold higher mutation rate compared to early-replicating regions. Structural mutations and recombination are also elevated in late-replicating DNA. By analyzing large-scale sequencing data of family trios, we found that there is a higher rate of de-novo germline mutations in late-replicating genomic regions. However, this was only seen in the offspring of younger fathers; there is an age-dependent decrease in the association of mutations with replication timing in males. As a result, mutations in older fathers are less biased to late-replicating genomic regions and are therefore more likely to influence genes and affect phenotype.

Replication timing is also a major factor affecting the distribution of mutations in cancer genomes. Before this was realized, many genes were thought to be cancer drivers because they were found to be recurrently mutated in cancer genomes; many of these genes turned out to be late-replicating genes that simply have a high background mutation rate. In addition, different cancer types have different mutational profiles which can be traced to differences in replication timing and other epigenetic variables in their cell type of origin. By analyzing mutation patterns in a cancer genome, it is therefore possible to identify the cell type of origin of the cancer. Furthermore, the distribution of replication origins in the genome has a major influence on mutational strand asymmetry in numerous tumors; in turn, patterns of mutational asymmetry can be used to illuminate mechanisms of DNA repair and mutagenesis during S phase in cancer cells.

Our lab is combining high-resolution measurements of DNA replication timing with various germline and cancer mutation datasets in order to better understand the links between DNA replication timing and mutations.

 

Hulke et al., Genome Biology and Evolution 2019

Haradhvala et al., Cell 2016

Francioli et al., Nature Genetics 2015

Polak et al., Nature 2015

Lawrence et al., Nature 2013

Michaelson et al., Cell 2012

Koren et al., American Journal of Human Genetics 2010

Our research is funded by: