An Algorithm of Step-by-step Pedigree Drawing

An algorithm for drawing large, complex pedigrees containing inbred loops and multiple-mate families is presented. The algorithm is based on a step-by-step approach to imaging, when the researcher determines the direction of further extension of the scheme. The algorithm is implemented as the PedigreeQuery software package written in Java. The software has a convenient graphical interface. The software package permits constructing not only whole pedigrees, but also their fragments that are particularly interesting for research. It also allows for adding new information on the phenotypes and genotypes of pedigree members. PedigreeQuery is distributed free of charge; it is available at http://mga.bionet.msc.ru/PedigreeQuery/PedigreeQuery.html and ftp://mga.bionet.nsc.ru/PedigreeQuery/.     

Breaking loops in large complex pedigrees

For pedigrees with multiple loops, exact likelihoods could not be computed in an acceptable time frame and thus, approximate methods are used. Some of these methods are based on breaking loops and approximations of complex pedigree likelihoods using the exact likelihood of the corresponding zero-loop pedigree. Due to ignoring loops, this method results in a loss of genetic information and a decrease in the power to detect linkage. To minimize this loss, an optimal set of loop breakers has to be selected. In this paper, we present a graph theory based algorithm for automatic selection of an optimal set of loop breakers. We propose using a total relationship between measured pedigree members as a proxy to power. To minimize the loss of genetic information, we suggest selection of such breakers whose duplication in a pedigree would be accompanied by a minimal loss of total relationship between measured pedigree members. We show that our algorithm compares favorably with other existing loop-breaker selection algorithms in terms of conservation of genetic information, statistical power and CPU time of subsequent linkage analysis. We implemented our method in a software package LOOP_EDGE, which is available at http://mga.bionet.nsc.ru/nlru/.     

Estimation of allele frequencies in ethnically heterogeneous populations

A method for reconstructing allele frequencies characteristic of an original ethnically homogeneous population before the start of migration processes is described. Information on both the ethnic group studied and offspring of interethnic marriages is used to estimate the allele frequencies. This makes it possible to increase the informativeness of the sample, which, in the case of ethnic heterogeneity, depends not only on allele frequencies and the total sample size, but also on the ethnic structure of the sample. The problem of estimating allele frequency in an ethnically heterogeneous sample has been solved analytically for diallelic loci. It has been demonstrated that, if offspring of interethnic marriages with the same degree of outbreeding is added to a sample of the ethnic group studied, the sample informativeness does not change. To utilize the information contained in the phenotypes of the offspring of interethnic marriages, representatives of the population from which migration occurs should be included into the sample. The size of the sample ensuring the preassigned accuracy of estimation is minimized at a certain ratio between the numbers of the offspring of interethnic marriages and the "immigrants." To analyze polyallelic loci, a software package has been developed that allows estimating allele frequencies, determining the errors of these estimates, and planning the sample ensuring the preassigned accuracy of estimation. The package is available free at http://mga.bionet.bionet.nsc.ru/PopMixed/PopMixed.html.     

Prediction of eukaryotic mRNA translational properties.

MOTIVATION: It is well known that eukaryotic mRNAs are translated at different levels depending on their sequence characteristics. Evaluation of mRNA translatability is of importance in prediction of the gene expression pattern by computer methods and to improve the recognition of mRNAs within cloned nucleotide sequences. It may also be used in biotechnological experiments to optimize the expression of foreign genes in transgenic organisms. RESULTS: The sets of 5' untranslated region characteristics, significantly different between mRNAs encoding abundant and scarce polypeptides, were determined for mammals, dicot plants and monocot plants, and collected in the LEADER_RNA database. Computer tools for the prediction of mRNA translatability are presented. AVAILABILITY: Programs for mRNA translatability prediction are available at http://wwwmgs.bionet.nsc. ru/programs/acts2/mo_mRNA.htm (for monocots), http://wwwmgs.bionet. nsc.ru/programs/acts2/di_mRNA.htm (for dicots) and http://wwwmgs. bionet.nsc.ru/programs/acts2/ma_mRNA.htm (for mammals). The LEADER_RNA database may be accessed at: http://wwwmgs.bionet.nsc. ru/systems/LeaderRNA/.     

Estimation of Allele Frequencies in Ethnically Heterogeneous Populations

A method for reconstructing allele frequencies characteristic of an original ethnically homogeneous population before the start of migration processes is described. Information on both the ethnic group studied and offspring of interethnic marriages is used to estimate the allele frequencies. This makes it possible to increase the informativeness of the sample, which, in the case of ethnic heterogeneity, depends not only on allele frequencies and the total sample size, but also on the ethnic structure of the sample. The problem of estimating allele frequency in an ethnically heterogeneous sample has been solved analytically for diallelic loci. It has been demonstrated that, if offspring of interethnic marriages with the same degree of outbreeding is added to a sample of the ethnic group studied, the sample informativeness does not change. To utilize the information contained in the phenotypes of the offspring of interethnic marriages, representatives of the population from which migration occurs should be included into the sample. The size of the sample ensuring the preassigned accuracy of estimation is minimized at a certain ratio between the numbers of the offspring of interethnic marriages and the “immigrants.” To analyze polyallelic loci, a software package has been developed that allows estimating allele frequencies, determining the errors of these estimates, and planning the sample ensuring the preassigned accuracy of estimation. The package is available free at http://mga.bionet.nsc.ru/PopMixed/PopMixed.html.__________Translated from Genetika, Vol. 41, No. 7, 2005, pp. 990–996.Original Russian Text Copyright © 2005 by Axenovich, Kirichenko.     

Haploid evolutionary constructor: new features and further challenges

In this paper we consider the recent advances in methodology for modeling of prokaryotic communities evolution and new features of the software package "Haploid evolutionary constructor" (http://evol-constructor.bionet.nsc.ru). We show the principles of building complex computer models in our software tool. These models describe several levels of biological organization: genetic, metabolic, population, ecological. New features of the haploid evolutionary constructor include the modeling of gene networks and phage infections.     

Analysis and recognition of promoters for erythroid-specific genes based on degenerative oligonucleotide motifs]

We developed a method to search for degenerate oligonucleotide motifs specific for certain regions in eukaryotic gene promoters. A procedure of promoter recognition based on these motifs is presented. The methods are integrated within program package ARGO available for the Internet users (http://wwwmgs.bionet.nsc.ru/mgs/programs/argo). This method was applied to study erythroid-specific gene promoters. High efficiency of their recognition is demonstrated.     

Analysis and Recognition of Erythroid-Specific Gene Promoters Basing on Degenerate Oligonucleotide Motifs

We developed a method to search for degenerate oligonucleotide motifs specific for certain regions in eukaryotic gene promoters. A procedure of promoter recognition based on these motifs is presented. The methods are integrated within the program package ARGO available for Internet users (http://wwwmgs.bionet.nsc.ru/mgs/programs/argo). This method was applied to study erythroid-specific gene promoters. High efficiency of their recognition is demonstrated.     

Functional linear models for region-based association analysis

Regional association analysis is one of the most powerful tools for gene mapping because instead analysis of individual variants it simultaneously considers all variants in the region. Recent development of the models for regional association analysis involves functional data analysis approach. In the framework of this approach, genotypes of variants within region as well as their effects are described by continuous functions. Such approach allows us to use information about both linkage and linkage disequilibrium and reduce the influence of noise and/or observation errors. Here we define a functional linear mixed model to test association on independent and structured samples. We demonstrate how to test fixed and random effects of a set of genetic variants in the region on quantitative trait. Estimation of statistical properties of new methods shows that type I errors are in accordance with declared values and power is high especially for models with fixed effects of genotypes. We suppose that new functional regression linear models facilitate identification of rare genetic variants controlling complex human and animal traits. New methods are implemented in computer software FREGAT which is available for free download at http://mga.bionet.nsc.ru/soft/FREGAT/.     

Gene Network and Database for Genes of Wheat’s Resistance to Pathogenic Fungi

An overview describing a gene network that controls the formation of plant responses to diseases caused by pathogenic fungi (http://wwwmgs.bionet.nsc.ru/mgs/gnw/genenet//viewer/Plant%20fungus%20pathogen.html) is presented. The gene network represents the coordinated interactions of genes, proteins, and regulatory molecules, including integrated defense mechanisms that prevent the development of infection, localize the lesion, and minimize damage. The gene network was reconstructed on the basis of literature data, and the elements of the gene network were associated with the records of the PGR database (Pathogenesis-Related Genes, http://srs6.bionet.nsc.ru/srs6bin/cgi-bin/wgetz?-page+top+-newId), where information on plant genes resistant to pathogenic fungi is accumulated. Reconstruction of the gene network allows us to formalize, visualize, and systematize possible mechanisms for the response of plant cells to fungal infection, which may be useful for the planning of experiments and interpretation of experimental data in this field of science.     

Prediction of contact numbers of amino acid residues using a neural network regression algorithm

The profile of contact numbers of amino acid residues in proteins contains important information about the protein structure and is connected with the accessibility of residues to solvent. Here we propose a method for predicting the profile of contact numbers of residues in protein from its amino acid sequence. The method is based on regression using a neural network algorithm. The algorithm predicts two types of profiles, namely, the total number of contacts and the number of close contacts with the neighbors in the chain. The Pearson coefficient of correlation between the actual and predicted values of total contact numbers amounted to 0.526–0.703. As for the number of close contacts, this coefficient was higher (0.662–0.743) for all the considered threshold contact distances (6, 8, 10, and 12 Å). The program for prediction of contact numbers CONNP is available at http://wwwmgs2.bionet.nsc.ru/reloaded.

     

Region-Based Association Test for Familial Data under Functional Linear Models

Region-based association analysis is a more powerful tool for gene mapping than testing of individual genetic variants, particularly for rare genetic variants. The most powerful methods for regional mapping are based on the functional data analysis approach, which assumes that the regional genome of an individual may be considered as a continuous stochastic function that contains information about both linkage and linkage disequilibrium. Here, we extend this powerful approach, earlier applied only to independent samples, to the samples of related individuals. To this end, we additionally include a random polygene effects in functional linear model used for testing association between quantitative traits and multiple genetic variants in the region. We compare the statistical power of different methods using Genetic Analysis Workshop 17 mini-exome family data and a wide range of simulation scenarios. Our method increases the power of regional association analysis of quantitative traits compared with burden-based and kernel-based methods for the majority of the scenarios. In addition, we estimate the statistical power of our method using regions with small number of genetic variants, and show that our method retains its advantage over burden-based and kernel-based methods in this case as well. The new method is implemented as the R-function ‘famFLM’ using two types of basis functions: the B-spline and Fourier bases. We compare the properties of the new method using models that differ from each other in the type of their function basis. The models based on the Fourier basis functions have an advantage in terms of speed and power over the models that use the B-spline basis functions and those that combine B-spline and Fourier basis functions. The ‘famFLM’ function is distributed under GPLv3 license and is freely available at http://mga.bionet.nsc.ru/soft/famFLM/.     

Construction of stochastic context trees for genetic texts

A method has been developed for constructing a tree source model for genetic text generation. Model visualisation in the form of suffix (context) trees provides a new way of context analysis of symbol sequences. Estimation of the stochastic complexity of the data in the frame of the model serves as a criterion for the model's ascertainment. The model and complexity values are used for analysis of genetic texts. The software realisation of this algorithm enables to reveal statistical properties of genetic sequences based on an information measure. The program developed is available via Internet at http://wwwmgs.bionet.nsc.ru/mgs/programs/complexity/.     

Interstitial telomeric repeats as markers of evolutionary changes in the mammalian karyotype: Human chromosome 2

The presence of conserved telomeric repeats represented by the hexamer (TTAGGG)_n at the chromosomal termini is necessary for the correct functioning and stability of chromosomes. A number of the genomes of mammals, including human, are known to contain interstitial telomeric sequences located far from the chromosomal termini. It is assumed that these repeats mark the regions of fusions or other rear-rangements of ancestral chromosomes. Exact localization of all interstitial telomeric sequences in the genome could significantly advance the understanding of the mechanisms of karyotype evolution and speciation. In this context, software was developed to search for degenerate interstitial telomeric repeats in complete sequences of mammalian chromosomes. The evolutionary significance of such repeats was demonstrated by the example of human chromosome 2. The results are available at http://www.bionet.nsc.ru/labs/theorylabmain/orlov/telomere/.     

Prediction of contact numbers of amino acid residues using a neural network regression algorithm

The profile of contact numbers of amino acid residues in proteins contains important information about the protein structure and is connected with the accessibility of residues to solvent. Here we propose a method for predicting the profile of contact numbers of residues in protein from its amino acid sequence. The method is based on regression using a neural network algorithm. The algorithm predicts two types of profiles, namely, the total number of contacts and the number of close contacts with the neighbors in the chain. The Pearson coefficient of correlation between the actual and predicted values of total contact numbers amounted to 0.526–0.703. As for the number of close contacts, this coefficient was higher (0.662–0.743) for all the considered threshold contact distances (6, 8, 10, and 12 Å). The program for prediction of contact numbers CONNP is available at http://wwwmgs2.bionet.nsc.ru/reloaded.