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Bouchard-Cannon P.,University of Toronto | Mendoza-Viveros L.,University of Toronto | Yuen A.,University of Toronto | Kaern M.,Ottawa Institute of Systems Biology | Cheng H.-Y.M.,University of Toronto
Cell Reports | Year: 2013

The subgranular zone (SGZ) of the adult hippocampus contains a pool of quiescent neural progenitor cells (QNPs) that are capable of entering the cell cycle and producing newborn neurons. The mechanisms that control the timing and extent of adult neurogenesis are not well understood. Here, we show that QNPs of the adult SGZ express molecular-clock components and proliferate in a rhythmic fashion. The clock proteins PERIOD2 and BMAL1 are critical for proper control of neurogenesis. The absence of PERIOD2 abolishes the gating of cell-cycle entrance of QNPs, whereas genetic ablation of bmal1 results in constitutively high levels of proliferation and delayed cell-cycle exit. We use mathematical model simulations to show that these observations may arise from clock-driven expression of a cell-cycle inhibitor that targets the cyclin D/Cdk4-6 complex. Our findings may have broad implications for the circadian clock in timing cell-cycle events of other stem cell populations throughout the body.

Dilworth F.J.,Ottawa Hospital Research Institute | Dilworth F.J.,University of Ottawa | Blais A.,Ottawa Institute of Systems Biology | Blais A.,University of Ottawa
Stem Cell Research and Therapy | Year: 2011

Satellite cells are a population of adult muscle stem cells that play a key role in mediating muscle regeneration. Activation of these quiescent stem cells in response to muscle injury involves modulating expression of multiple developmentally regulated genes, including mediators of the muscle-specific transcription program: Pax7, Myf5, MyoD and myogenin. Here we present evidence suggesting an essential role for the antagonistic Polycomb group and Trithorax group proteins in the epigenetic marking of muscle-specific genes to ensure proper temporal and spatial expression during muscle regeneration. The importance of Polycomb group and Trithorax group proteins in establishing chromatin structure at muscle-specific genes suggests that therapeutic modulation of their activity in satellite cells could represent a viable approach for repairing damaged muscle in muscular dystrophy. © 2011 BioMed Central Ltd.

Phenix H.,University of Ottawa | Perkins T.,Ottawa Hospital Research Institute | Perkins T.,University of Ottawa | Kaern M.,Ottawa Institute of Systems Biology
Chaos | Year: 2013

The accuracy of genetic network inference is limited by the assumptions used to determine if one hypothetical model is better than another in explaining experimental observations. Most previous work on epistasis analysis-in which one attempts to infer pathway relationships by determining equivalences among traits following mutations-has been based on Boolean or linear models. Here, we delineate the ultimate limits of epistasis-based inference by systematically surveying all two-gene network motifs and use symbolic algebra with arbitrary regulation functions to examine trait equivalences. Our analysis divides the motifs into equivalence classes, where different genetic perturbations result in indistinguishable experimental outcomes. We demonstrate that this partitioning can reveal important information about network architecture, and show, using simulated data, that it greatly improves the accuracy of genetic network inference methods. Because of the minimal assumptions involved, equivalence partitioning has broad applicability for gene network inference. © 2013.

Julian L.M.,Ottawa Hospital Research Institute | Blais A.,Ottawa Institute of Systems Biology | Blais A.,University of Ottawa
Frontiers in Genetics | Year: 2015

E2F transcription factors and their regulatory partners, the pocket proteins (PPs), have emerged as essential regulators of stem cell fate control in a number of lineages. In mammals, this role extends from both pluripotent stem cells to those encompassing all embryonic germ layers, as well as extra-embryonic lineages. E2F/PP-mediated regulation of stem cell decisions is highly evolutionarily conserved, and is likely a pivotal biological mechanism underlying stem cell homeostasis. This has immense implications for organismal development, tissue maintenance, and regeneration. In this article, we discuss the roles of E2F factors and PPs in stem cell populations, focusing on mammalian systems. We discuss emerging findings that position the E2F and PP families as widespread and dynamic epigenetic regulators of cell fate decisions. Additionally, we focus on the ever expanding landscape of E2F/PP target genes, and explore the possibility that E2Fs are not simply regulators of general 'multi-purpose' cell fate genes but can execute tissue- and cell type-specific gene regulatory programs. © 2015 Julian and Blais.

Yang Z.,Ottawa Institute of Systems Biology | Li Z.,Shenyang Pharmaceutical University | Bickel D.R.,Ottawa Institute of Systems Biology
BMC Bioinformatics | Year: 2013

Background: In investigating differentially expressed genes or other selected features, researchers conduct hypothesis tests to determine which biological categories, such as those of the Gene Ontology (GO), are enriched for the selected features. Multiple comparison procedures (MCPs) are commonly used to prevent excessive false positive rates. Traditional MCPs, e.g., the Bonferroni method, go to the opposite extreme: strictly controlling a family-wise error rate, resulting in excessive false negative rates. Researchers generally prefer the more balanced approach of instead controlling the false discovery rate (FDR). However, the q-values that methods of FDR control assign to biological categories tend to be too low to reliably estimate the probability that a biological category is not enriched for the preselected features. Thus, we study an application of the other estimators of that probability, which is called the local FDR (LFDR).Results: We considered five LFDR estimators for detecting enriched GO terms: a binomial-based estimator (BBE), a maximum likelihood estimator (MLE), a normalized MLE (NMLE), a histogram-based estimator assuming a theoretical null hypothesis (HBE), and a histogram-based estimator assuming an empirical null hypothesis (HBE-EN). Since NMLE depends not only on the data but also on the specified value of Π0, the proportion of non-enriched GO terms, it is only advantageous when either Π0 is already known with sufficient accuracy or there are data for only 1 GO term. By contrast, the other estimators work without specifying Π0 but require data for at least 2 GO terms. Our simulation studies yielded the following summaries of the relative performance of each of those four estimators. HBE and HBE-EN produced larger biases for 2, 4, 8, 32, and 100 GO terms than BBE and MLE. BBE has the lowest bias if Π0 is 1 and if the number of GO terms is between 2 and 32. The bias of MLE is no worse than that of BBE for 100 GO terms even when the ideal number of components in its underlying mixture model is unknown, but has high bias when the number of GO terms is small compared to the number of estimated parameters. For unknown values of Π0, BBE has the lowest bias for a small number of GO terms (2-32 GO terms), and MLE has the lowest bias for a medium number of GO terms (100 GO terms).Conclusions: For enrichment detection, we recommend estimating the LFDR by MLE given at least a medium number of GO terms, by BBE given a small number of GO terms, and by NMLE given either only 1 GO term or precise knowledge of Π0. © 2013 Yang et al.; licensee BioMed Central Ltd.

Chithambaram S.,University of Ottawa | Prabhakaran R.,University of Ottawa | Xia X.,University of Ottawa | Xia X.,Ottawa Institute of Systems Biology
Genetics | Year: 2014

Studying phage codon adaptation is important not only for understanding the process of translation elongation, but also for reengineering phages for medical and industrial purposes. To evaluate the effect of mutation and selection on phage codon usage, we developed an index to measure selection imposed by host translation machinery, based on the difference in codon usage between all host genes and highly expressed host genes. We developed linear and nonlinear models to estimate the C/T mutation bias in different phage lineages and to evaluate the relative effect of mutation and host selection on phage codon usage. C/T-biased mutations occur more frequently in single-stranded DNA (ssDNA) phages than in double-stranded DNA (dsDNA) phages and affect not only synonymous codon usage, but also nonsynonymous substitutions at second codon positions, especially in ssDNA phages. The host translation machinery affects codon adaptation in both dsDNA and ssDNA phages, with a stronger effect on dsDNA phages than on ssDNA phages. Strand asymmetry with the associated local variation in mutation bias can significantly interfere with codon adaptation in both dsDNA and ssDNA phages. © 2014 by the Genetics Society of America.

Xia X.,University of Ottawa | Xia X.,Ottawa Institute of Systems Biology
Molecular Phylogenetics and Evolution | Year: 2016

While pairwise sequence alignment (PSA) by dynamic programming is guaranteed to generate one of the optimal alignments, multiple sequence alignment (MSA) of highly divergent sequences often results in poorly aligned sequences, plaguing all subsequent phylogenetic analysis. One way to avoid this problem is to use only PSA to reconstruct phylogenetic trees, which can only be done with distance-based methods. I compared the accuracy of this new computational approach (named PhyPA for phylogenetics by pairwise alignment) against the maximum likelihood method using MSA (the ML + MSA approach), based on nucleotide, amino acid and codon sequences simulated with different topologies and tree lengths. I present a surprising discovery that the fast PhyPA method consistently outperforms the slow ML + MSA approach for highly diverged sequences even when all optimization options were turned on for the ML + MSA approach. Only when sequences are not highly diverged (i.e., when a reliable MSA can be obtained) does the ML + MSA approach outperforms PhyPA. The true topologies are always recovered by ML with the true alignment from the simulation. However, with MSA derived from alignment programs such as MAFFT or MUSCLE, the recovered topology consistently has higher likelihood than that for the true topology. Thus, the failure to recover the true topology by the ML + MSA is not because of insufficient search of tree space, but by the distortion of phylogenetic signal by MSA methods. I have implemented in DAMBE PhyPA and two approaches making use of multi-gene data sets to derive phylogenetic support for subtrees equivalent to resampling techniques such as bootstrapping and jackknifing. © 2016 The Author

Xia X.,University of Ottawa | Xia X.,Ottawa Institute of Systems Biology | Yang Q.,Chinese Academy of Sciences
Molecular Phylogenetics and Evolution | Year: 2011

Distance-based phylogenetic methods are widely used in biomedical research. However, there has been little development of rigorous statistical methods and software for dating speciation and gene duplication events by using evolutionary distances. Here we present a simple, fast and accurate dating method based on the least-squares (LS) method that has already been widely used in molecular phylogenetic reconstruction. Dating methods with a global clock or two different local clocks are presented. Single or multiple fossil calibration points can be used, and multiple data sets can be integrated in a combined analysis. Variation of the estimated divergence time is estimated by resampling methods such as bootstrapping or jackknifing. Application of the method to dating the divergence time among seven ape species or among 35 mammalian species including major mammalian orders shows that the estimated divergence time with the LS criterion is nearly identical to those obtained by the likelihood method or Bayesian inference. © 2011 Elsevier Inc.

Montazeri Z.,Ottawa Institute of Systems Biology | Yanofsky C.M.,Ottawa Institute of Systems Biology | Bickel D.R.,Ottawa Institute of Systems Biology
Statistical Applications in Genetics and Molecular Biology | Year: 2010

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a hard-threshold estimator of the expression ratio that is not known to perform well in terms of mean-squared error, the sum of estimator variance and squared estimator bias. On the basis of two distinct simulation studies and data from different microarray studies, we systematically compared the performance of several estimators representing both current practice and shrinkage. We find that the threshold-based estimators usually perform worse than the maximum-likelihood estimator (MLE) and they often perform far worse as quantified by estimated mean-squared risk. By contrast, the shrinkage estimators tend to perform as well as or better than the MLE and never much worse than the MLE, as expected from what is known about shrinkage. However, a Bayesian measure of performance based on the prior information that few genes are differentially expressed indicates that hard-threshold estimators perform about as well as the local false discovery rate (FDR), the best of the shrinkage estimators studied. Based on the ability of the latter to leverage information across genes, we conclude that the use of the local-FDR estimator of the fold change instead of informal or threshold-based combinations of statistical tests and non-shrinkage estimators can be expected to substantially improve the reliability of gene prioritization at very little risk of doing so less reliably. Since the proposed replacement of post-selection estimates with shrunken estimates applies as well to other types of high-dimensional data, it could also improve the analysis of SNP data from genome-wide association studies. Copyright © 2010 The Berkeley Electronic Press. All rights reserved.

Xia X.,University of Ottawa | Xia X.,Ottawa Institute of Systems Biology
Current Genomics | Year: 2012

Different patterns of strand asymmetry have been documented in a variety of prokaryotic genomes as well as mitochondrial genomes. Because different replication mechanisms often lead to different patterns of strand asymmetry, much can be learned of replication mechanisms by examining strand asymmetry. Here I summarize the diverse patterns of strand asymmetry among different taxonomic groups to suggest that (1) the single-origin replication may not be universal among bacterial species as the endosymbionts Wigglesworthia glossinidia, Wolbachia species, cyanobacterium Synechocystis 6803 and Mycoplasma pulmonis genomes all exhibit strand asymmetry patterns consistent with the multiple origins of replication, (2) different replication origins in some archaeal genomes leave quite different patterns of strand asymmetry, suggesting that different replication origins in the same genome may be differentially used, (3) mitochondrial genomes from representative vertebrate species share one strand asymmetry pattern consistent with the stranddisplacement replication documented in mammalian mtDNA, suggesting that the mtDNA replication mechanism in mammals may be shared among all vertebrate species, and (4) mitochondrial genomes from primitive forms of metazoans such as the sponge and hydra (representing Porifera and Cnidaria, respectively), as well as those from plants, have strand asymmetry patterns similar to single-origin or multi-origin replications observed in prokaryotes and are drastically different from mitochondrial genomes from other metazoans. This may explain why sponge and hydra mitochondrial genomes, as well as plant mitochondrial genomes, evolves much slower than those from other metazoans. © 2012 Bentham Science Publishers.

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