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arXiv2007

Combined Sum of Squares Penalties for Molecular Divergence Time Estimation

Estimates of molecular divergence times when rates of evolution vary require the assumption of a model of rate change. Brownian motion is one such model, and since rates cannot become negative, a log Brownian model seems appropriate. Divergence time estimates can then be made using weighted least squares penalties. As sequences become long, this approach effectively becomes equivalent to penalized likelihood or Bayesian approaches. Different forms of the least squares penalty are considered to take into account correlation due to shared ancestors. It is shown that a scale parameter is also needed since the sum of squares changes with the scale of time. Errors or uncertainty on fossil calibrations, may be folded in with errors due to the stochastic nature of Brownian motion and ancestral polymorphism, giving a total sum of squares to be minimized. Applying these methods to placental mammal data the estimated age of the root decreases from 125 to about 94 mybp. However, multiple fossil calibration points and relative molecular divergence times inflate the sum of squares more than expected. If fossil data are also bootstrapped, then the confidence interval for the root of placental mammals varies widely from ~70 to 130 mybp. Such a wide interval suggests that more and better fossil calibration data is needed and/or better models of rate evolution are needed and/or better molecular data are needed. Until these issues are thoroughly investigated, it is premature to declare either the old molecular dates frequently obtained (e.g. > 110 mybp) or the lack of identified placental fossils in the Cretaceous, more indicative of when crown-group placental mammals evolved.

q-bio.PE↗

arXiv2008

Global regulation of genome duplication in eukaryotes: an overview from the epifluorescence microscope

In eukaryotes, DNA replication is initiated along each chromosome at multiple sites called replication origins. Locally, each replication origin is "licensed", or specified, at the end of the M and the beginning of G1 phases of the cell cycle. During S phase when DNA synthesis takes place, origins are activated in stages corresponding to early and late replicating domains. The staged and progressive activation of replication origins reflects the need to maintain a strict balance between the number of active replication forks and the rate at which DNA synthesis procedes. This suggests that origin densities (frequency of intiation) and replication fork movement (rates of elongation) must be co-regulated in order to guarantee the efficient and complete duplication of each subchromosomal domain. Emerging evidence supports this proposal and suggests that the ATM/ATR intra-S phase checkpoint plays an important role in the co-regulation of initiation frequencies and rates of elongation. In the following, we review recent results concerning the mechanisms governing the global regulation of DNA replication and discuss the roles these mechanisms play in maintaining genome stability during both a normal and perturbed S phase.

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arXiv2007

Genomes: at the edge of chaos with maximum information capacity

We propose an order index, phi, which quantifies the notion of ``life at the edge of chaos'' when applied to genome sequences. It maps genomes to a number from 0 (random and of infinite length) to 1 (fully ordered) and applies regardless of sequence length. The 786 complete genomic sequences in GenBank were found to have phi values in a very narrow range, 0.037+/-0.027. We show this implies that genomes are halfway towards being completely random, namely, at the edge of chaos. We argue that this narrow range represents the neighborhood of a fixed-point in the space of sequences, and genomes are driven there by the dynamics of a robust, predominantly neutral evolution process.

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arXiv2007

Systems level circuit model of C. elegans undulatory locomotion: mathematical modeling and molecular genetics

To establish the relationship between locomotory behavior and dynamics of neural circuits in the nematode C. elegans we combined molecular and theoretical approaches. In particular, we quantitatively analyzed the motion of C. elegans with defective synaptic GABA and acetylcholine transmission, defective muscle calcium signaling, and defective muscles and cuticle structures, and compared the data with our systems level circuit model. The major experimental findings are: (i) anterior-to-posterior gradients of body bending flex for almost all strains both for forward and backward motion, and for neuronal mutants, also analogous weak gradients of undulatory frequency, (ii) existence of some form of neuromuscular (stretch receptor) feedback, (iii) invariance of neuromuscular wavelength, (iv) biphasic dependence of frequency on synaptic signaling, and (v) decrease of frequency with increase of the muscle time constant. Based on (i) we hypothesize that the Central Pattern Generator (CPG) is located in the head both for forward and backward motion. Points (i) and (ii) are the starting assumptions for our theoretical model, whose dynamical patterns are qualitatively insensitive to the details of the CPG design if stretch receptor feedback is sufficiently strong and slow. The model reveals that stretch receptor coupling in the body wall is critical for generation of the neuromuscular wave. Our model agrees with our behavioral data(iii), (iv), and (v), and with other pertinent published data, e.g., that frequency is an increasing function of muscle gap-junction coupling.

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arXiv2007

Detection of an ancient principle and an elegant solution to the protein classification problem

This work is concerned with the development of a well-founded, theoretically justified, and least complicated metric for the classification of proteins with reference to enzymes. As the signature of an enzyme family, a catalytic domain is easily fingerprinted. Given that the classification problem has so far seemed intractable, a classification schema derived from the catalytic domain would be satisfying. Here I show that there exists a natural ab initio if nonobvious basis to theorize that the catalytic domain of an enzyme is uniquely informative about its regulation. This annotates its function. Based on this hypothesis, a method that correctly classifies potassium ion channels into their respective subfamilies is described. To put the principle on firmer ground, extra validation was sought and obtained through co-evolutionary analyses. The co-evolutionary analyses reveal a departure from the notion that potassium ion channel proteins are functionally modular. This finding is discussed in light of the prevailing notion of domain. These studies establish that significant co-evolution of the catalytic domain of a gene with its conjoint domain is a specialized, necessary process following fusion and swapping events in evolution. Instances of this discovery are likely to be found pervasive in protein science.

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arXiv2007

CompostBin: A DNA composition-based algorithm for binning environmental shotgun reads

A major hindrance to studies of microbial diversity has been that the vast majority of microbes cannot be cultured in the laboratory and thus are not amenable to traditional methods of characterization. Environmental shotgun sequencing (ESS) overcomes this hurdle by sequencing the DNA from the organisms present in a microbial community. The interpretation of this metagenomic data can be greatly facilitated by associating every sequence read with its source organism. We report the development of CompostBin, a DNA composition-based algorithm for analyzing metagenomic sequence reads and distributing them into taxon-specific bins. Unlike previous methods that seek to bin assembled contigs and often require training on known reference genomes, CompostBin has the ability to accurately bin raw sequence reads without need for assembly or training. It applies principal component analysis to project the data into an informative lower-dimensional space, and then uses the normalized cut clustering algorithm on this filtered data set to classify sequences into taxon-specific bins. We demonstrate the algorithm's accuracy on a variety of simulated data sets and on one metagenomic data set with known species assignments. CompostBin is a work in progress, with several refinements of the algorithm planned for the future.

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arXiv2007

Power-law Signatures and Patchiness in Genechip Oligonucleotide Microarrays

. Genechip oligonucleotide microarrays have been used widely for transcriptional profiling of a large number of genes in a given paradigm. Gene expression estimation precedes biological inference and is given as a complex combination of atomic entities on the array called probes. These probe intensities are further classified into perfect-match (PM) and mis-match (MM) probes. While former is a measure of specific binding, the lat-ter is a measure of non-specific binding. The behavior of the MM probes has especially proven to be elusive. The present study investigates qualita-tive similarities in the distributional signatures and local correlation struc-tures/patchiness between the PM and MM probe intensities. These qualita-tive similarities are established on publicly available microarrays generated across laboratories investigating the same paradigm. Persistence of these similarities across raw as well as background subtracted probe intensities is also investigated. The results presented raise fundamental concerns in inter-preting Genechip oligonucleotide microarray data.

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arXiv2008

Units of genetic transfer in prokaryotes

The transfer of genetic materials across species (lateral genetic transfer, LGT) contributes to genomic and physiological innovation in prokaryotes. The extent of LGT in prokaryotes has been examined in a number of studies, but the unit of transfer has not been studied in a rigorous manner. Using a rigorous phylogenetic approach, we analysed the units of LGT within families of single-copy genes obtained from 144 fully sequenced prokaryote genomes. A total of 30.3% of these gene families show evidence of LGT. We found that the transfer of gene fragments has been more frequent than the transfer of entire genes, suggesting the extent of LGT has been underestimated. We found little functional bias between within-gene (fragmentary) and whole-gene (non-fragmentary) genetic transfer, but non-fragmentary transfer has been more frequent into pathogens than into non-pathogens. As gene families that contain probable paralogs were excluded from the current study, our results may still underestimate the extent of LGT; nonetheless this is the most-comprehensive study to date of the unit of LGT among prokaryote genomes.

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arXiv2008

Protein domains as units of genetic transfer

Genomes evolve as modules. In prokaryotes (and some eukaryotes), genetic material can be transferred between species and integrated into the genome via homologous or illegitimate recombination. There is little reason to imagine that the units of transfer correspond to entire genes; however, such units have not been rigorously characterized. We examined fragmentary genetic transfers in single-copy gene families from 144 prokaryotic genomes and found that breakpoints are located significantly closer to the boundaries of genomic regions that encode annotated structural domains of proteins than expected by chance, particularly when recombining sequences are more divergent. This correlation results from recombination events themselves and not from differential nucleotide substitution. We report the first systematic study relating genetic recombination to structural features at the protein level.

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arXiv2008

Genetic transfer in Staphylococcus: a case study of 13 genomes

The widespread presence of antibiotic resistance and virulence among Staphylococcus isolates has been attributed to lateral genetic transfer (LGT) between different strains or species. However, there has been very little study of the extent of LGT in Staphylococcus species using a phylogenetic approach, particularly of the units of such genetic transfer. Here we report the first systematic study of the units of genetic transfer in 13 Staphylococcus genomes, using a rigorous phylogenetic approach. We found clear evidence of LGT in 26.1% of the 1354 homologous gene families examined, and possibly more in another 17.9% of the total families. Within-gene and whole-gene transfer contribute almost equally to the discordance of these gene families against a reference phylogeny. Comparing genetic transfer in single-copy and in multi-copy gene families, we found little functional bias in cases of within-gene (fragmentary) genetic transfer but substantial functional bias in cases of whole-gene (non-fragmentary) genetic transfer, and we observed a higher frequency of LGT in multi-copy gene families. Our results demonstrate that LGT and gene duplication play an important part among the factors that contribute to functional innovation in staphylococcal genomes.

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arXiv2007

Pseudo-Random Fluctuations, Stochastic Cooperativity and Burstiness in Dynamically Unstable High-Dimensional Biochemical Networks

The goal of this paper is to outline a scenario of emerging stochasticity in high-dimensional highly nonlinear systems, such as genetic regulatory networks (GRN). We focus attention on the fact that in such systems confluence of all the factors necessary for gene expression is a comparatively rare event, and only massive redundancy makes such events sufficiently frequent. An immediate consequence of this rareness is burstiness in mRNA and protein copy numbers, a well known experimentally observed effect. We introduce the concept of stochastic cooperativity and show that this phenomenon is a natural consequence of high dimensionality coupled with highly nonlinearity of a dynamical system. In mathematical terms, burstiness is associated with heavy-tailed probability distributions of stochastic processes describing the dynamics of the system. The sequence of stochastic cooperativity events allows for transition from continuous deterministic dynamics expressed in terms of ordinary differential equations (ODE) to discrete stochastic dynamics expressed in terms of Langevin and Fokker-Plank equations. We demonstrate also that high-dimensional nonlinear systems, even in the absence of explicit mechanisms for suppressing inherent instability, may nevertheless reside in a state of stationary pseudo-random fluctuations which for all practical purposes may be regarded as stochastic process. This type of stochastic behavior is an inherent property of such systems and requires neither an external random force, nor highly specialized conditions of bistability.

q-bio.MN↗

arXiv2007

Two distinct logical types of network control in gene expression profiles

In unicellular organisms such as bacteria the same acquired mutations beneficial in one environment can be restrictive in another. However, evolving Escherichia coli populations demonstrate remarkable flexibility in adaptation. The mechanisms sustaining genetic flexibility remain unclear. In E. coli the transcriptional regulation of gene expression involves both dedicated regulators binding specific DNA sites with high affinity and also global regulators - abundant DNA architectural proteins of the bacterial chromoid binding multiple low affinity sites and thus modulating the superhelical density of DNA. The first form of transcriptional regulation is dominantly pairwise and specific, representing digitial control, while the second form is (in strength and distribution) continuous, representing analog control. Here we look at the properties of effective networks derived from significant gene expression changes under variation of the two forms of control and find that upon limitations of one type of control (caused e.g. by mutation of a global DNA architectural factor) the other type can compensate for compromised regulation. Mutations of global regulators significantly enhance the digital control; in the presence of global DNA architectural proteins regulation is mostly of the analog type, coupling spatially neighboring genomic loci; together our data suggest that two logically distinct types of control are balancing each other. By revealing two distinct logical types of control, our approach provides basic insights into both the organizational principles of transcriptional regulation and the mechanisms buffering genetic flexibility. We anticipate that the general concept of distinguishing logical types of control will apply to many complex biological networks.

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arXiv2007

Inferring Diversity: Life After Shannon

The diversity of a community that cannot be fully counted must be inferred. The two preeminent inference methods are the MaxEnt method, which uses information in the form of constraints and Bayes' rule which uses information in the form of data. It has been shown that these two methods are special cases of the method of Maximum (relative) Entropy (ME). We demonstrate how this method can be used as a measure of diversity that not only reproduces the features of Shannon's index but exceeds them by allowing more types of information to be included in the inference. A specific example is solved in detail. Additionally, the entropy that is found is the same form as the thermodynamic entropy.

stat.ME↗

arXiv2007

Copy Number Variants and Segmental Duplications Show Different Formation Signatures

In addition to variation in terms of single nucleotide polymorphisms (SNPs), whole regions ranging from several kilobases up to a megabase in length differ in copy number among individuals. These differences are referred to as Copy Number Variants (CNVs) and extensive mapping of these is underway. Recent studies have highlighted their great prevalence in the human genome. Segmental Duplications (SDs) are long (>1kb) stretches of duplicated DNA with high sequence identity. First, we analyzed the co-localization of SDs and find that SDs are significantly co-localized with each other, resulting in a power-law distribution, which suggests a preferential attachment mechanism, i.e. existing SDs are likely to be involved in creating new ones nearby. Second, we look at the relationship of CNVs/SDs with various types of repeats. We we find that the previously recognized association of SDs with Alu elements is significantly stronger for older SDs and is sharply decreasing for younger ones. While it might be expected that the patterns should be similar for SDs and CNVs, we find, surprisingly, no association of CNVs with Alu elements. This trend is consistent with the decreasing correlation between Alu elements and younger SDs, the activity of Alu elements has been decreasing and by now it they seem no longer active. Furthermore, we find a striking association of SDs with processed pseudogenes suggesting that they may also have mediated SD formation. Moreover, find strong association with microsatellites for both SDs and CNVs that suggests a role for satellites in the formation of both.

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arXiv2007

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision tree-based machine learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering essential genes in Escherichia coli and then assessed its performance.

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arXiv2007

DrosOCB: a high resolution map of conserved non coding sequences in Drosophila

Comparative genomics methods are widely used to aid the functional annotation of non coding DNA regions. However, aligning non coding sequences requires new algorithms and strategies, in order to take into account extensive rearrangements and turnover during evolution. Here we present a novel large scale alignment strategy which aims at drawing a precise map of conserved non coding regions between genomes, even when these regions have undergone small scale rearrangments events and a certain degree of sequence variability. We applied our alignment approach to obtain a genome-wide catalogue of conserved non coding blocks (CNBs) between Drosophila melanogaster and 11 other Drosophila species. Interestingly, we observe numerous small scale rearrangement events, such as local inversions, duplications and translocations, which are not observable in the whole genome alignments currently available. The high rate of observed low scale reshuffling show that this database of CNBs can constitute the starting point for several investigations, related to the evolution of regulatory DNA in Drosophila and the in silico identification of unannotated functional elements.

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arXiv2007

Electric Transport Properties of the p53 Gene and the Effects of Point Mutations

In this work, charge transport (CT) properties of the p53 gene are numerically studied by the transfer matrix method, and using either single or double strand effective tight-binding models. A statistical analysis of the consequences of known p53 point mutations on CT features is performed. It is found that in contrast to other kind of mutation defects, cancerous mutations result in much weaker changes of CT efficiency. Given the envisioned role played by CT in the DNA-repairing mechanism, our theoretical results suggest an underlying physical explanation at the origin of carcinogenesis.

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arXiv2007

Understanding Transcriptional Regulation Using De-novo Sequence Motif Discovery, Network Inference and Interactome Data

Gene regulation is a complex process involving the role of several genomic elements which work in concert to drive spatio-temporal expression. The experimental characterization of gene regulatory elements is a very complex and resource-intensive process. One of the major goals in computational biology is the \textit{in-silico} annotation of previously uncharacterized elements using results from the subset of known, previously annotated, regulatory elements. The recent results of the ENCODE project (\emph{http://encode.nih.gov}) presented in-depth analysis of such functional (regulatory) non-coding elements for 1% of the human genome. It is hoped that the results obtained on this subset can be scaled to the rest of the genome. This is an extremely important effort which will enable faster dissection of other functional elements in key biological processes such as disease progression and organ development (\cite{Kleinjan2005},\cite{Lieb2006}. The computational annotation of these hitherto uncharacterized regions would require an identification of features that have good predictive value. In this work, we study transcriptional regulation as a problem in heterogeneous data integration, across sequence, expression and interactome level attributes. Using the example of the \textit{Gata2} gene and its recently discovered urogenital enhancers \cite{Khandekar2004} as a case study, we examine the predictive value of various high throughput functional genomic assays (from projects like ENCODE and SymAtlas) in characterizing these enhancers and their regulatory role. Observing results from the application of modern statistical learning methodologies for each of these data modalities, we propose a set of features that are most discriminatory to find these enhancers.

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