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arXiv2007

From DNA sequence analysis to modeling replication in the human genome

We explore the large-scale behavior of nucleotide compositional strand asymmetries along human chromosomes. As we observe for 7 of 9 origins of replication experimentally identified so far, the (TA+GC) skew displays rather sharp upward jumps, with a linear decreasing profile in between two successive jumps. We present a model of replication with well positioned replication origins and random terminations that accounts for the observed characteristic serrated skew profiles. We succeed in identifying 287 pairs of putative adjacent replication origins with an origin spacing approximately 1-2 Mbp that are likely to correspond to replication foci observed in interphase nuclei and recognized as stable structures that persist throughout subsequent cell generations.

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arXiv2007

Thermodynamic and structural consensus principle predicts mature miRNA location and structure, categorizes conserved interspecies miRNA subgroups, and hints new possible mechanisms of miRNA maturization

Although conservation of thermodynamics is much less studied than of sequences and structures, thermodynamic details are biophysical features different from but as important as structural features. As a succession of previous research which revealed the important relationships between thermodynamic features and miRNA maturization, this article applies interspecies conservation of miRNA thermodynamics and structures to study miRNA maturization. According to a thermodynamic and structural consensus principle, miRBase is categorized by conservation subgroups, which imply various functions. These subgroups are divided without the introduction of functional information. This suggests the consistency between the two processes of miRNA maturization and functioning. Different from prevailing methods which predict extended miRNA precursors, a learning-based algorithm is proposed to predict ~22bp mature parts of 2780 test miRNA genes in 44 species with a rate of 79.4%. This is the first attempt of a general interspecies prediction of mature miRNAs. Suboptimal structures that most fit the consensus thermodynamic and structural profiles are chosen to improve structure prediction. Distribution of miRNA locations on corresponding pri-miRNA stem-loop structures is then studied. Existing research on Drosha cleavage site is not generally true across species. Instead, the distance between mature miRNA and center loop normalized by stem length is a more conserved structural feature in animals, and the normalized distance between mature miRNA and ss-RNA tail is the counterpart in plants. This suggests two possibly-updating mechanisms of miRNA maturization in animals and plants. All in all, conservations of thermodynamics together with other features are shown closely related to miRNA maturization.

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arXiv2007

Thermodynamics of DNA loops with long-range correlated structural disorder

We study the influence of a structural disorder on the thermodynamical properties of 2D-elastic chains submitted to mechanical/topological constraint as loops. The disorder is introduced via a spontaneous curvature whose distribution along the chain presents either no correlation or long-range correlations (LRC). The equilibrium properties of the one-loop system are derived numerically and analytically for weak disorder. LRC are shown to favor the formation of small loop, larger the LRC, smaller the loop size. We use the mean first passage time formalism to show that the typical short time loop dynamics is superdiffusive in the presence of LRC. Potential biological implications on nucleosome positioning and dynamics in eukaryotic chromatin are discussed.

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arXiv2007

Identifying statistical dependence in genomic sequences via mutual information estimates

Questions of understanding and quantifying the representation and amount of information in organisms have become a central part of biological research, as they potentially hold the key to fundamental advances. In this paper, we demonstrate the use of information-theoretic tools for the task of identifying segments of biomolecules (DNA or RNA) that are statistically correlated. We develop a precise and reliable methodology, based on the notion of mutual information, for finding and extracting statistical as well as structural dependencies. A simple threshold function is defined, and its use in quantifying the level of significance of dependencies between biological segments is explored. These tools are used in two specific applications. First, for the identification of correlations between different parts of the maize zmSRp32 gene. There, we find significant dependencies between the 5' untranslated region in zmSRp32 and its alternatively spliced exons. This observation may indicate the presence of as-yet unknown alternative splicing mechanisms or structural scaffolds. Second, using data from the FBI's Combined DNA Index System (CODIS), we demonstrate that our approach is particularly well suited for the problem of discovering short tandem repeats, an application of importance in genetic profiling.

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arXiv2007

A simple computational method for the identification of disease-associated loci in complex, incomplete pedigrees

We present an approach, called the "Shadow Method," for the identification of disease loci from dense genetic marker maps in complex, potentially incomplete pedigrees. "Shadow" is a simple method based on an analysis of the patterns of obligate meiotic recombination events in genotypic data. This method can be applied to any high density marker map and was specifically designed to exploit the fact that extremely dense marker maps are becoming more readily available. We also describe how to interpret and associate meaningful P-Values to the results. Shadow has significant advantages over traditional parametric linkage analysis methods in that it can be readily applied even in cases in which the topology of a pedigree or pedigrees can only be partially determined. In addition, Shadow is robust to variability in a range of parameters and in particular does not require prior knowledge of mode of inheritance, penetrance or clinical misdiagnosis rate. Shadow can be used for any SNP data, but is especially effective when applied to dense samplings. Our primary example uses data from Affymetrix 100k SNPChip samples in which we illustrate our approach by analyzing simulated data as well as genome-wide SNP data from two pedigrees with inherited forms of kidney failure, one of which is compared with a typical LOD score analysis.

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arXiv2007

Mixed membership analysis of genome-wide expression data

Learning latent expression themes that best express complex patterns in a sample is a central problem in data mining and scientific research. For example, in computational biology we seek a set of salient gene expression themes that explain a biological process, extracting them from a large pool of gene expression profiles. In this paper, we introduce probabilistic models to learn such latent themes in an unsupervised fashion. Our models capture contagion, i.e., dependence among multiple occurrences of the same feature, using a hierarchical Bayesian scheme. Contagion is a convenient analytical formalism to characterize semantic themes underlying observed feature patterns, such as biological context. We present model variants tailored to different properties of biological data, and we outline a general variational inference scheme for approximate posterior inference. We validate our methods on both simulated data and realistic high-throughput gene expression profiles via SAGE. Our results show improved predictions of gene functions over existing methods based on stronger independence assumptions, and demonstrate feasibility of a promising hierarchical Bayesian formalism for soft clustering and latent aspects analysis.

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arXiv2011

Molecular Labor Division: Its Cause and Consequence

Both external environmental selection and internal lower-level evolution are essential for an integral picture of evolution. This paper proposes that the division of internal evolution into DNA/RNA pattern formation (genotype) and protein functional action (phenotype) resolves a universal conflict between fitness and evolvability. Specifically, this paper explains how this universal conflict drove the emergence of genotype-phenotype division, why this labor division is responsible for the extraordinary complexity of life, and how the specific ways of genotype-phenotype mapping in the labor division determine the paths and forms of evolution and development.

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arXiv2007

Computational analysis of folding and mutation properties of C5 domain from Myosin binding protein C

Thermal folding Molecular Dynamics simulations of the domain C5 from Myosin Binding Protein C were performed using a native-centric model to study the role of three mutations related to Familial Hypertrophic Cardiomyopathy. Mutation of Asn755 causes the largest shift of the folding temperature, and the residue is located in the CFGA' beta-sheet featuring the highest Phi-values. The mutation thus appears to reduce the thermodynamic stability in agreement with experimental data. The mutations on Arg654 and Arg668, conversely, cause a little change in the folding temperature and they reside in the low Phi-value BDE beta-sheet, so that their pathologic role cannot be related to impairment of the folding process but possibly to the binding with target molecules. As the typical signature of Domain C5 is the presence of a longer and destabilizing CD-loop with respect to the other Ig-like domains we completed the work with a bioinformatic analysis of this loop showing a high density of negative charge and low hydrophobicity. This indicates the CD-loop as a natively unfolded sequence with a likely coupling between folding and ligand binding.

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arXiv2007

A mechanistic model for +1 frameshifts in eubacteria

This work applies the methods of signal processing and the concepts of control system design to model the maintenance and modulation of reading frame in the process of protein synthesis. The model shows how translational speed can modulate translational accuracy to accomplish programmed +1 frameshifts and could have implications for the regulation of translational efficiency. A series of free energy estimates were calculated from the ribosome's interaction with mRNA sequences during the process of translation elongation in eubacteria. A sinusoidal pattern of roughly constant phase was detected in these free energy signals. Signal phase was identified as a useful parameter for locating programmed +1 frameshifts encoded in bacterial genes for release factor 2. A displacement model was developed that captures the mechanism of frameshift based on the information content of the signal parameters and the relative abundance of tRNA in the bacterial cell. Results are presented using experimentally verified frameshift genes across eubacteria.

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arXiv2009

An Illustrated Introduction to the Basic Biological Principles

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arXiv2007

A comparison of sexual and asexual replication strategies in a simplified model based on the yeast life cycle

This paper develops simplified mathematical models describing the mutation-selection balance for the asexual and sexual replication pathways in {\it Saccharomyces cerevisiae}. We assume diploid genomes consisting of two chromosomes, and we assume that each chromosome is functional if and only if its base sequence is identical to some master sequence. The growth and replication of the yeast cells is modeled as a first-order process, with first-order growth rate constants that are determined by whether a given genome consists of zero, one, or two functional chromosomes. In the asexual pathway, we assume that a given diploid cell divides into two diploids. In the sexual pathway, we assume that a given diploid cell divides into two diploids, each of which then divide into two haploids. The resulting four haploids enter a haploid pool, where they grow and replicate until they meet another haploid with which to fuse. When the cost for sex is low, we find that the selective mating strategy leads to the highest mean fitness of the population, when compared to all of the other strategies. We also show that, at low to intermediate replication fidelities, sexual replication with random mating has a higher mean fitness than asexual replication, as long as the cost for sex is low. This is consistent with previous work suggesting that sexual replication is advantageous at high population densities, low replication rates, and intermediate replication fidelities. The results of this paper also suggest that {\it S. cerevisiae} switches from asexual to sexual replication when stressed, because stressful growth conditions provide an opportunity for the yeast to clear out deleterious mutations from their genomes.

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arXiv2007

MicroRNA Systems Biology

Recently, microRNAs (miRNAs) have emerged as central posttranscriptional regulators of gene expression. miRNAs regulate many key biological processes, including cell growth, death, development and differentiation. This discovery is challenging the central dogma of molecular biology. Genes are working together by forming cellular networks. It has become an emerging concept that miRNAs could intertwine with cellular networks to exert their function. Thus, it is essential to understand how miRNAs take part in cellular processes at a systems-level. In this review, I will first introduce basic knowledge of miRNAs and their relations to heart disaeses and cancer, highlight recently dicovered functions such as filtering out gene expression noise by miRNAs. I will aslo introduce basic concepts of cellular networks and interpret their biological meaning in such a way that the network concepts are digested in a biological context and are understandable for biologists. Finally, I will summarize the most recent progress in understanding of miRNA biology at a systems-level: the principles of miRNA regulation of the major cellular networks including signaling, metabolic, protein interaction and gene regulatory networks. A common miRNA regulatory principle is emerging: miRNAs preferentially regulated the genes that have high regulation complexity. In addition, miRNAs preferentially regulate positive regulatory motifs, highly connected scaffolds and the most network downstream components of cellular signaling networks, while miRNAs selectively regulate the genes which have specific network structural features on metabolic networks.

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arXiv2007

Cancer systems biology: exploring cancer-associated genes on cellular networks

Genomic alterations lead to cancer complexity and form a major hurdle for a comprehensive understanding of the molecular mechanisms underlying oncogenesis. In this review, we describe the recent advances in studying cancer-associated genes from a systems biological point of view. The integration of known cancer genes onto protein and signaling networks reveals the characteristics of cancer genes within networks. This approach shows that cancer genes often function as network hub proteins which are involved in many cellular processes and form focal nodes in the information exchange between many signaling pathways. Literature mining allows constructing gene-gene networks, in which new cancer genes can be identified. The gene expression profiles of cancer cells are used for reconstructing gene regulatory networks. By doing so, the genes, which are involved in the regulation of cancer progression, can be picked up from these networks after which their functions can be further confirmed in the laboratory.

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arXiv2007

Comparing a Menagerie of Models for Estimating Molecular Divergence Times

Estimation of molecular evolutionary divergence times requires models of rate change. These vary with regard to the assumption of what quantity is penalized. The possibilities considered are the rate of evolution, the log of the rate of evolution and the inverse of the rate of evolution. These models also vary with regard to how time affects the expected variance of rate change. Here the alternatives are not at all, linearly with time and as the product of rate and time. This results in a set of nine models, both random walks and Brownian motion. A priori any of these models could be correct, yet different researchers may well prefer, or simply use, one rather than the others. Another variable is whether to use a scaling factor to take account of the variance of the process of rate change being unknown and therefore avoid minimizing the penalty function with unrealistically large times. Here the difference these models and assumptions make on a tree of mammals, with the root fixed and with a single internal node fixed, is measured. The similarity of models is measured as the correlation of their time estimates and visualized with a least squares tree. The fit of model to data is measured and Q-Q plots are shown. Comparing model estimates with each other, the age of clades within Laurasiatheria are seen to vary far more across models than those within Supraprimates (informally called Euarchontoglires). Especially problematic are the often-used fossil calibrated nodes of horse/rhino and whale/hippo clashing with times within Supraprimates and in particular no fossil rodent teeth older than ~60 mybp. A scaling factor in addition to penalizing rate change is seen to yield consistent relative time estimates irrespective of exactly where the calibration point is placed.

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arXiv2007

Simulating Genomes and Populations in the Mutation Space: An example with the evolution of HIV drug resistance

When simulating biological populations under different evolutionary genetic models, backward or forward strategies can be followed. Backward simulations, also called coalescent-based simulations, are computationally very efficient. However, this framework imposes several limitations that forward simulation does not. In this work, a new simple and efficient model to perform forward simulation of populations and/or genomes is proposed. The basic idea considers an individual as the differences (mutations) between this individual and a reference or consensus genotype. Thus, this individual is no longer represented by its complete sequence or genotype. An example of the efficiency of the new model with respect to a more classical forward one is demonstrated. This example models the evolution of HIV resistance using the B_FR.HXB2 reference sequence to study the emergence of known resistance mutants to Zidovudine and Didanosine drugs

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arXiv2008

Nemo: a computational tool for analyzing nematode locomotion

The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement. In this paper, we introduce Nemo (nematode movement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification. Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.

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arXiv2008

Classification of arrayCGH data using a fused SVM

Motivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profiles are characterized by a large number of variables usually measured on a limited number of samples. However, arrayCGH profiles have a particular structure of correlations between variables, due to the spatial organization of BACs along the genome. This suggests that classical classification methods, often based on the selection of a small number of discriminative features, may not be the most accurate methods and may not produce easily interpretable prediction rules. Results: We propose a new method for supervised classification of arrayCGH data. The method is a variant of support vector machine (SVM) that incorporates the biological specificities of DNA copy number variations along the genome as prior knowledge. The resulting classifier is a sparse linear classifier based on a limited number of regions automatically selected on the chromosomes, leading to easy interpretation and identification of discriminative regions of the genome. We test this method on three classification problems for bladder and uveal cancer, involving both diagnosis and prognosis. We demonstrate that the introduction of the new prior on the classifier leads not only to more accurate predictions, but also to the identification of known and new regions of interest in the genome. Availability: All data and algorithms are publicly available.

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arXiv2008

QPS -- quadratic programming sampler, a motif finder using biophysical modeling

We present a Markov chain Monte Carlo algorithm for local alignments of nucleotide sequences aiming to infer putative transcription factor binding sites, referred to as the quadratic programming sampler. The new motif finder incorporates detailed biophysical modeling of the transcription factor binding site recognition which arises an intrinsic threshold discriminating putative binding sites from other/background sequences. We validate the principal functioning of the algorithm on a sample of four promoter regions from Escherichia coli. The resulting description of the motif can be readily evaluated on the whole genome to identify new putative binding sites.

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