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arXiv2008

Prediction of genomic properties and classification of life by protein length distributions

Much evolutionary information is stored in the fluctuations of protein length distributions. The genome size and non-coding DNA content can be calculated based only on the protein length distributions. So there is intrinsic relationship between the coding DNA size and non-coding DNA size. According to the correlations and quasi-periodicity of protein length distributions, we can classify life into three domains. Strong evidences are found to support the order in the structures of protein length distributions.

q-bio.GN↗
arXiv2008

A standalone version of IsoFinder for the computational prediction of isochores in genome sequences

Isochores are long genome segments relatively homogeneous in G+C. A heuristic algorithm based on entropic segmentation has been developed by our group, and a web server implementing all the required components is available. However, a researcher may want to perform batch processing of many sequences simultaneously in its local machine, instead of analyzing them on one by one basis through the web. To this end, standalone versions are required. We report here the implementation of two standalone programs, able to predict isochores at the sequence level: 1) a command-line version (IsoFinder) for Windows and Linux systems; and 2) a user-friendly version (IsoFinderWin) running under Windows.

q-bio.GN↗
arXiv2008

A fast and efficient gene-network reconstruction method from multiple over-expression experiments

Reverse engineering of gene regulatory networks presents one of the big challenges in systems biology. Gene regulatory networks are usually inferred from a set of single-gene over-expressions and/or knockout experiments. Functional relationships between genes are retrieved either from the steady state gene expressions or from respective time series. We present a novel algorithm for gene network reconstruction on the basis of steady-state gene-chip data from over-expression experiments. The algorithm is based on a straight forward solution of a linear gene-dynamics equation, where experimental data is fed in as a first predictor for the solution. We compare the algorithm's performance with the NIR algorithm, both on the well known E.Coli experimental data and on in-silico experiments. We show superiority of the proposed algorithm in the number of correctly reconstructed links and discuss computational time and robustness. The proposed algorithm is not limited by combinatorial explosion problems and can be used in principle for large networks of thousands of genes.

q-bio.MN↗
arXiv2008

Significance tests for comparing digital gene expression profiles

Most of the statistical tests currently used to detect differentially expressed genes are based on asymptotic results, and perform poorly for low expression tags. Another problem is the common use of a single canonical cutoff for the significance level (p-value) of all the tags, without taking into consideration the type II error and the highly variable character of the sample size of the tags. This work reports the development of two significance tests for the comparison of digital expression profiles, based on frequentist and Bayesian points of view, respectively. Both tests are exact, and do not use any asymptotic considerations, thus producing more correct results for low frequency tags than the chi-square test. The frequentist test uses a tag-customized critical level which minimizes a linear combination of type I and type II errors. A comparison of the Bayesian and the frequentist tests revealed that they are linked by a Beta distribution function. These tests can be used alone or in conjunction, and represent an improvement over the currently available methods for comparing digital profiles.

q-bio.GN↗
arXiv2008

Comment of Global dynamics of biological systems

In a recent study, (Grigorov, 2006) analyzed temporal gene expression profiles (Arbeitman et al., 2002) generated in a Drosophila experiment using SSA in conjunction with Monte-Carlo SSA. The author (Grigorov, 2006) makes three important claims in his article, namely: Claim1: A new method based on the theory of nonlinear time series analysis is used to capture the global dynamics of the fruit-fly cycle temporal gene expression profiles. Claim 2: Flattening of a significant part of the eigen-spectrum confirms the hypothesis about an underly-ing high-dimensional chaotic generating process. Claim 3: Monte-Carlo SSA can be used to establish whether a given time series is distinguishable from any well-defined process including deterministic chaos. In this report we present fundamental concerns with respect to the above claims (Grigorov, 2006) in a systematic manner with simple examples. The discussion provided especially discourages the choice of SSA for inferring nonlinear dynamical structure form time series obtained in any biological paradigm.

q-bio.GN↗
arXiv2008

From differential equations to Boolean networks: A Case Study in modeling regulatory networks

Methods of modeling cellular regulatory networks as diverse as differential equations and Boolean networks co-exist, however, without any closer correspondence to each other. With the example system of the fission yeast cell cycle control network, we here set the two approaches in relation to each other. We find that the Boolean network can be formulated as a specific coarse-grained limit of the more detailed differential network model for this system. This lays the mathematical foundation on which Boolean networks can be applied to biological regulatory networks in a controlled way.

q-bio.MN↗
arXiv2008

Number of natively unfolded proteins scales with genome size

Natively unfolded proteins exist as an ensemble of flexible conformations lacking a well defined tertiary structure along a large portion of their polypeptide chain. Despite the absence of a stable configuration, they are involved in important cellular processes. In this work we used from three indicators of folding status, derived from the analysis of mean packing and mean contact energy of a protein sequence as well as from VSL2, a disorder predictor, and we combined them into a consensus score to identify natively unfolded proteins in several genomes from Archaea, Bacteria and Eukarya. We found a high correlation among the number of predicted natively unfolded proteins and the number of proteins in the genomes. More specifically, the number of natively unfolded proteins scaled with the number of proteins in the genomes, with exponent 1.81 +- 0.10. This scaling law may be important to understand the relation between the number of natively unfolded proteins and their roles in cellular processes.

q-bio.GN↗
arXiv2008

Universal Features in the Genome-level Evolution of Protein Domains

Protein domains are found on genomes with notable statistical distributions, which bear a high degree of similarity. Previous work has shown how these distributions can be accounted for by simple models, where the main ingredients are probabilities of duplication, innovation, and loss of domains. However, no one so far has addressed the issue that these distributions follow definite trends depending on protein-coding genome size only. We present a stochastic duplication/innovation model, falling in the class of so-called Chinese Restaurant Processes, able to explain this feature of the data. Using only two universal parameters, related to a minimal number of domains and to the relative weight of innovation to duplication, the model reproduces two important aspects: (a) the populations of domain classes (the sets, related to homology classes, containing realizations of the same domain in different proteins) follow common power-laws whose cutoff is dictated by genome size, and (b) the number of domain families is universal and markedly sublinear in genome size. An important ingredient of the model is that the innovation probability decreases with genome size. We propose the possibility to interpret this as a global constraint given by the cost of expanding an increasingly complex interactome.

q-bio.GN↗
arXiv2008

Towards a core genome: pairwise similarity searches on interspecific genomic data

The phenomenon of gene conservation is an interesting evolutionary problem related to speciation and adaptation. Conserved genes are acted upon in evolution in a way that preserves their function despite other structural and functional changes going on around them. The recent availability of whole-genomic data from closely related species allows us to test the hypothesis that a core genome present in a hypothetical common ancestor is inherited by all sister taxa. Furthermore, this core genome should serve essential functions such as genetic regulation and cellular repair. Whole-genome sequences from three strains of bacteria (Shewanella sp.) were used in this analysis. The open reading frames (ORFs) for each identified and putative gene were used for each genome. Reciprocal Blast searches were conducted on all three genomes, which distilled a list of thousands of genes to 68 genes that were identical across taxa. Based on functional annotation, these genes were identified as housekeeping genes, which confirmed the original hypothesis. This method could be used in eukaryotes as well, in particular the relationship between humans, chimps, and macaques.

q-bio.GN↗
arXiv2008

Origin and evolution of the genetic code: The universal enigma

The genetic code is nearly universal, and the arrangement of the codons in the standard codon table is highly non-random. The three main concepts on origin and evolution of the code are the stereochemical theory; the coevolution theory; and the error minimization theory. These theories are not mutually exclusive and are also compatible with the frozen accident hypothesis. Mathematical analysis of the structure and possible evolutionary trajectories of the code shows that it is highly robust to translational error but there is a huge number of more robust codes, so that the standard code potentially could evolve from a random code via a short sequence of codon series reassignments. Thus, much of the evolution that led to the standard code can be interpreted as a combination of frozen accident with selection for translational error minimization although contributions from coevolution of the code with metabolic pathways and/or weak affinities between amino acids and nucleotide triplets cannot be ruled out. However, such scenarios for the code evolution are based on formal schemes whose relevance to the actual primordial evolution is uncertain, so much caution in interpretation is necessary. A real understanding of the code's origin and evolution is likely to be attainable only in conjunction with a credible scenario for the evolution of the coding principle itself and the translation system.

q-bio.GN↗
arXiv2008

Digital PCR provides sensitive and absolute calibration for high throughput sequencing

Several of the next generation sequencers are limited in their sample preparation process by the need to make an absolute measurement of the number of template molecules in the library to be sequenced. As currently practiced, the practical effects of this requirement compromise sequencing performance, both by requiring large amounts of sample DNA and by requiring extra sequencing runs to be performed. We used digital PCR to quantitate sequencing libraries, and demonstrated its sensitivity and robustness by preparing and sequencing libraries from subnanogram amounts of bacterial and human DNA on the 454 and Solexa sequencing platforms. This assay allows absolute quantitation and eliminates uncertainties associated with the construction and application of standard curves. The digital PCR platform consumes subfemptogram amounts of the sequencing library and gives highly accurate results, allowing the optimal DNA concentration to be used in setting up sequencing runs without costly and time-consuming titration techniques. This approach also reduces the input sample requirement more than 1000-fold: from micrograms of DNA to less than a nanogram.

q-bio.QM↗
arXiv2008

Computation of Maximal Resolution of Copy Number Variation on a Nanofluidic Device using Digital PCR

Copy Number Variations (CNVs) of regions of the human genome are important in disease association studies.The digital array is a nanofluidic biochip which utilizes integrated channels and valves that partition mixtures of sample and reagents into 765 nanovolume reaction chambers. It was recently shown how one can perform statistical analysis of CNV in a DNA sample the digital array. In particular, it was shown how one can accurately estimate the true concentration of the molecules in the DNA sample and then determine the ratios of different sequences along with statistical confidence intervals on these estimations. In this paper we perform computation of maximum number of copies which can be distinguished using the digital array which gives its resolution in terms of its ability to determine CNV. Then, we demonstrate the usefulness of the mathematical analysis to solve an important real-world problem of determination of the copy number of X chromosome as our example application.

q-bio.GN↗
arXiv2008

Matrix genetics, part 4: cyclic changes of the genetic 8-dimensional Yin-Yang-algebras and the algebraic models of physiological cycles

The article continues an analysis of the genetic 8-dimensional Yin-Yang-algebra. This algebra was revealed in a course of matrix researches of structures of the genetic code and it was described in the author's articles arXiv:0803.3330 and arXiv:0805.4692. The article presents data about many kinds of cyclic permutations of elements of the genetic code in the genetic (8x8)-matrix [C A; U G](3) of 64 triplets, where C, A, U, G are letters of the genetic alphabet. These cyclic permutations lead to such reorganizations of the matrix form of presentation of the initial genetic Yin-Yang-algebra that arisen matrices serve as matrix forms of presentations of new Yin-Yang-algebras as well. They are connected algorithmically with Hadamard matrices. The discovered existence of a hierarchy of the cyclic changes of types of genetic Yin-Yang-algebras allows thinking about new algebraic-genetic models of cyclic processes in inherited biological systems including models of cyclic metamorphoses of animals. These cycles of changes of the genetic 8-dimensional algebras and of their 8-dimensional numeric systems have many analogies with famous facts and doctrines of modern and ancient physiology, medicine, etc. This viewpoint proposes that the famous idea by Pythagoras (about organization of natural systems in accordance with harmony of numerical systems) should be combined with the idea of cyclic changes of Yin-Yang-numeric systems in considered cases. This second idea reminds of the ancient idea of cyclic changes in nature. From such algebraic-genetic viewpoint, the notion of biological time can be considered as a factor of coordinating these hierarchical ensembles of cyclic changes of types of the genetic multi-dimensional algebras.

q-bio.GN↗
arXiv2008

The transmission sense of information

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory as developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon's theory addresses. First, philosophers have suggested that Shannon theory is only useful for developing a shallow notion of correlation, the so-called "causal sense" of information. Second they typically argue that in genetics and evolutionary biology, information language is used in a "semantic sense," whereas semantics are deliberately omitted from Shannon theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon's theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence.

q-bio.PE↗
arXiv2008

Sequence alignment and mutual information

Background: Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. All existing alignment algorithms rely on heuristic scoring schemes based on biological expertise. Therefore, these algorithms do not provide model independent and objective measures for how similar two (or more) sequences actually are. Although information theory provides such a similarity measure -- the mutual information (MI) -- previous attempts to connect sequence alignment and information theory have not produced realistic estimates for the MI from a given alignment. Results: Here we describe a simple and flexible approach to get robust estimates of MI from {\it global} alignments. For mammalian mitochondrial DNA, our approach gives pairwise MI estimates for commonly used global alignment algorithms that are strikingly close to estimates obtained by an entirely unrelated approach -- concatenating and zipping the sequences. Conclusions: This remarkable consistency may help establish MI as a reliable tool for evaluating the quality of global alignments, judging the relative merits of different alignment algorithms, and estimating the significance of specific alignments. We expect that our approach can be extended to establish further connections between information theory and sequence alignment, including applications to local and multiple alignment procedures.

q-bio.GN↗
arXiv2008

A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network

Many complex disease syndromes such as asthma consist of a large number of highly related, rather than independent, clinical phenotypes, raising a new technical challenge in identifying genetic variations associated simultaneously with correlated traits. In this study, we propose a new statistical framework called graph-guided fused lasso (GFlasso) to address this issue in a principled way. Our approach explicitly represents the dependency structure among the quantitative traits as a network, and leverages this trait network to encode structured regularizations in a multivariate regression model over the genotypes and traits, so that the genetic markers that jointly influence subgroups of highly correlated traits can be detected with high sensitivity and specificity. While most of the traditional methods examined each phenotype independently and combined the results afterwards, our approach analyzes all of the traits jointly in a single statistical method, and borrow information across correlated phenotypes to discover the genetic markers that perturbe a subset of correlated triats jointly rather than a single trait. Using simulated datasets based on the HapMap consortium data and an asthma dataset, we compare the performance of our method with the single-marker analysis, and other sparse regression methods such as the ridge regression and the lasso that do not use any structural information in the traits. Our results show that there is a significant advantage in detecting the true causal SNPs when we incorporate the correlation pattern in traits using our proposed methods.

stat.ML↗
arXiv2008

Identity and divergence of protein domain architectures after the Yeast Whole Genome Duplication event

Analyzing the properties of duplicate genes during evolution is useful to understand the development of new cell functions. The yeast S. cerevisiae is a useful testing ground for this problem, because its duplicated genes with different evolutionary birth and destiny are well distinguishable. In particular, there is a clear detection for the occurrence of a Whole Genome Duplication (WGD) event in S. cerevisiae, and the genes derived from this event (WGD paralogs) are known. We studied WGD and non-WGD duplicates by two parallel analysis based on structural protein domains and on Gene Ontology annotation scheme respectively. The results show that while a large number of ``duplicable'' structural domains is shared in local and global duplications, WGD and non-WGD paralogs tend to have different functions. The reason for this is the existence of WGD and non-WGD specific domains with largely different functions. In agreement with the recent findings of Wapinski and collaborators (Nature 449, 2007), WGD paralogs often perform ``core'' cell functions, such as translation and DNA replication, while local duplications associate with ``peripheral'' functions such as response to stress. Our results also support the fact that domain architectures are a reliable tool to detect homology, as the domains of duplicates are largely invariant with date and nature of the duplication, while their sequences and also their functions might migrate.

q-bio.GN↗