Genome-wide analysis of DNA replication timing in single cells : Yes! We're all individuals

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Whole-genome analysis of animal A- and B-type cyclins.

BACKGROUND: Multiple A- and B-type cyclins have been identified in animals, but their study is complicated by varying degrees of functional redundancy. A non-essential phenotype may reflect redundancy with a known or as yet unknown gene. Complete sequencing of several animal genomes has allowed us to determine the size of the mitotic cyclin gene family and therefore to start to address this issue. RESULTS: We analyzed the Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens genomes to identify known and novel A- and B-type cyclin genes and distinguish them from related pseudogenes. We find only a single functional A-type cyclin gene in invertebrates but two in vertebrates. In addition to the single functional cyclin A gene, the C. elegans genome contains numerous cyclin A pseudogenes. In contrast, the number and relationship of B-type cyclins varies considerably between organisms but all contain at least one cyclin B1-like gene and a cyclin B3 gene. CONCLUSIONS: There are three conserved families of mitotic cyclins in animals: A-, B3- and B-type. The precise number of genes within the A- and B-type families varies in different organisms, possibly as an adaptation to their distinct developmental strategies.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Whole-genome analysis of animal A- and B-type cyclins

BACKGROUND: Multiple A- and B-type cyclins have been identified in animals, but their study is complicated by varying degrees of functional redundancy. A non-essential phenotype may reflect redundancy with a known or as yet unknown gene. Complete sequencing of several animal genomes has allowed us to determine the size of the mitotic cyclin gene family and therefore to start to address this issue. RESULTS: We analyzed the Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens genomes to identify known and novel A- and B-type cyclin genes and distinguish them from related pseudogenes. We find only a single functional A-type cyclin gene in invertebrates but two in vertebrates. In addition to the single functional cyclin A gene, the C. elegans genome contains numerous cyclin A pseudogenes. In contrast, the number and relationship of B-type cyclins varies considerably between organisms but all contain at least one cyclin B1-like gene and a cyclin B3 gene. CONCLUSIONS: There are three conserved families of mitotic cyclins in animals: A-, B3- and B-type. The precise number of genes within the A- and B-type families varies in different organisms, possibly as an adaptation to their distinct developmental strategies

The Beacon Calculus: A formal method for the flexible and concise modelling of biological systems.

Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This paper introduces the Beacon Calculus, a process algebra designed to simplify the task of modelling interacting biological components. Its breadth is demonstrated by creating models of DNA replication dynamics, the gene expression dynamics in response to DNA methylation damage, and a multisite phosphorylation switch. The flexibility of these models is shown by adapting the DNA replication model to further include two topics of interest from the literature: cooperative origin firing and replication fork barriers. The Beacon Calculus is supported with the open-source simulator bcs (https://github.com/MBoemo/bcs.git) to allow users to develop and simulate their own models

Mathematical modeling of genome replication

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Chromosome replication: from ORC to fork

A report on the 2001 Eukaryotic DNA Replication meeting, Cold Spring Harbor Laboratory, New York, 5-9 September 2001

High-Resolution Replication Profiles Define the Stochastic Nature of Genome Replication Initiation and Termination

Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.Peer reviewedPublisher PD

A global profile of replicative polymerase usage

Three eukaryotic DNA polymerases are essential for genome replication. Polymerase (Pol) α–primase initiates each synthesis event and is rapidly replaced by processive DNA polymerases: Polɛ replicates the leading strand, whereas Polδ performs lagging-strand synthesis. However, it is not known whether this division of labor is maintained across the whole genome or how uniform it is within single replicons. Using Schizosaccharomyces pombe, we have developed a polymerase usage sequencing (Pu-seq) strategy to map polymerase usage genome wide. Pu-seq provides direct replication-origin location and efficiency data and indirect estimates of replication timing. We confirm that the division of labor is broadly maintained across an entire genome. However, our data suggest a subtle variability in the usage of the two polymerases within individual replicons. We propose that this results from occasional leading-strand initiation by Polδ followed by exchange for Polɛ

Dynamics of DNA replication in yeast

We present a mathematical model for the spatial dynamics of DNA replication. Using this model we determine the probability distribution for the time at which each chromosomal position is replicated. From this we show, contrary to previous reports, that mean replication time curves cannot be used to directly determine origin parameters. We demonstrate that the stochastic nature of replication dynamics leaves a clear signature in experimentally measured population average data, and we show that the width of the activation time probability distribution can be inferred from this data. Our results compare favorably with experimental measurements in Saccharomyces cerevisae

Effectiveness of glass beads for plating cell cultures

Cell plating, the spreading out of a liquid suspension of cells on a surface followed by colony growth, is a common laboratory procedure in microbiology. Despite this, the exact impact of its parameters on colony growth has not been extensively studied. A common protocol involves the shaking of glass beads within a Petri dish containing solid growth media. We investigated the effects of multiple parameters in this protocol: the number of beads, the shape of movement, and the number of movements. Standard suspensions of Escherichia coli were spread while varying these parameters to assess their impact on colony growth. Results were assessed by a variety of metrics: the number of colonies, the mean distance between closest colonies, and the variability and uniformity of their spatial distribution. Finally, we devised a mathematical model of shifting billiard to explain the heterogeneities in the observed spatial patterns. Exploring the parameters that affect the most fundamental techniques in microbiology allows us to better understand their function, giving us the ability to precisely control their outputs for our exact needs