Using mathematical models to understand metabolism,genes, and disease

Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene–environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene–environment interactions, and genotype–phenotype mapping, and how they can be used in precision and personalized medicine.     

Selective imitation for a private sign system

A distinctive feature of all human languages is the diverse and arbitrary nature of the sign (signifier). This can be interpreted as stating that the mapping between signals and referents is established by convention rather than by functional constraints. This property of the sign provides for a great deal of linguistic flexibility and is a key component of symbolic communication. Game theoretic models to describe signal imitation are investigated with a view to understanding how non-arbitrary (indexical) animal-style signals might 'evolve' culturally into diverse, arbitrary signs. I explore the evolutionary hypothesis that private, arbitrary signs emerge as a result of selective imitation within a socially structured population. Once arbitrary signs have emerged, they contribute towards greater assortative interactions among individuals using a shared sign system. In natural populations, the models for imitation will very often be close kin. Hence, kinship provides one mechanism for the creation of true symbols. An imitation-structured population can support many more sign systems than an equivalent non-structured population and is one in which symbols become the dominant force in assortative interactions.     

Genome radiation hybrid mapping: summary and future directions

Genome mapping by means of radiation-induced interspecific cell hybrids is a direct way to localize both high- and low-polymorphic nucleotide sequences, including gene sequences, on animal chromosomes. Using radiation hybrid panels either individual chromosomes and loci or entire genome can be mapped. This efficient approach makes it possible to reach high resolution of markers (up to 100 bp) as well as unify the mapping language. Due to electronic means of communication, the same experimental material can be used in numerous laboratories to provide high-resolution extended genomic maps saturated with markers. Radiation hybrid mapping is a powerful tool for analysis of complex genome structure. Using radiation hybrid maps permitted verification of regions of chromosome homeology in various species and detection of regions with conserved sequence and conserved gene order. Identification of these regions is extremely important for understanding evolution of species karyotypes and for making use of positional cloning to isolate genes responsible for commercial traits as well as genes involved in hereditary human diseases.     

Genome Radiation Hybrid Mapping: Summary and Future Direction

Genome mapping by means of radiation-induced interspecific cell hybrids is a direct means for localizing both high- and low-polymorphic nucleotide sequences, including gene sequences, on animal chromosomes. Using radiation hybrid panels either individual chromosomes and loci or the entire genome can be mapped. This is a novel efficient approach that allows one to reach high resolution of markers (up to 100 bp) and unify the mapping language. Due to electronic means of communication, the same experimental material can be used in numerous laboratories to provide high-resolution extended genomic maps saturated with markers. Radiation hybrid mapping is a powerful tool for the analysis of the complex genome structure. Using radiation hybrid maps permitted to verify regions of chromosome homeology in various species and to detect regions not only with conserved sequences but also with conserved gene order. Identification of these regions is extremely important for understanding evolution of species karyotypes. It permits the use of positional cloning to isolate genes controlling commercially valuable traits and those involved in the development of hereditary human diseases.     

Rapid SNP discovery and genetic mapping using sequenced RAD markers

Single nucleotide polymorphism (SNP) discovery and genotyping are essential to genetic mapping. There remains a need for a simple, inexpensive platform that allows high-density SNP discovery and genotyping in large populations. Here we describe the sequencing of restriction-site associated DNA (RAD) tags, which identified more than 13,000 SNPs, and mapped three traits in two model organisms, using less than half the capacity of one Illumina sequencing run. We demonstrated that different marker densities can be attained by choice of restriction enzyme. Furthermore, we developed a barcoding system for sample multiplexing and fine mapped the genetic basis of lateral plate armor loss in threespine stickleback by identifying recombinant breakpoints in F(2) individuals. Barcoding also facilitated mapping of a second trait, a reduction of pelvic structure, by in silico re-sorting of individuals. To further demonstrate the ease of the RAD sequencing approach we identified polymorphic markers and mapped an induced mutation in Neurospora crassa. Sequencing of RAD markers is an integrated platform for SNP discovery and genotyping. This approach should be widely applicable to genetic mapping in a variety of organisms.     

Physical and genetic characterization of the genome of Lactobacillus lactis bacteriophage LL-H.

Bacteriophage LL-H is a virulent phage of Lactobacillus lactis LL23. A restriction map of the phage genome was constructed with various restriction endonucleases. This chromosome has a 34-kilobase size and seems to be circularly permuted. We used a bank of LL-H restriction fragments to study the expression of five of the seven main phage particle proteins. Immunoblotting experiments permitted the mapping on the chromosome of several genes coding for phage particle proteins. We also show that the gene of the main capsid protein is expressed from its own promoter in an Escherichia coli strain.     

Mapping quantitative trait loci with dominant and missing markers in various crosses from two inbred lines

Dominant phenotype of a genetic marker provides incomplete information about the marker genotype of an individual. A consequence of using this incomplete information for mapping quantitative trait loci (QTL) is that the inference of the genotype of a putative QTL flanked by a marker with dominant phenotype will depend on the genotype or phenotype of the next marker. This dependence can be extended further until a marker genotype is fully observed. A general algorithm is derived to calculate the probability distribution of the genotype of a putative QTL at a given genomic position, conditional on all observed marker phenotypes in the region with dominant and missing marker information for an individual. The algorithm is implemented for various populations stemming from two inbred lines in the context of mapping QTL. Simulation results show that if only a proportion of markers contain missing or dominant phenotypes, QTL mapping can be almost as efficient as if there were no missing information in the data. The efficiency of the analysis, however, may decrease substantially when a very large proportion of markers contain missing or dominant phenotypes and a genetic map has to be reconstructed first on the same data as well. So it is important to combine dominant markers with codominant markers in a QTL mapping study. This revised version was published online in July 2006 with corrections to the Cover Date.     

MPSS: an integrated database system for surveying a set of proteins

SUMMARY: We design and implement an integrated database system called 'multi-protein survey system' (MPSS), which provides a platform to retrieve information about many proteins at a time. This system integrates several important and widely used databases including SwissProt, TrEMBL, PDB and InterPro, plus useful references such as GO and KEGG to other databases. Users may submit a group of protein IDs, entry names, SwissProt/TrEMBL accession numbers or GenBank GIs through MPSS' web interface, and obtain protein annotation information from public databases and pre-computed molecular properties speedily. MPSS can also supply comprehensive information about query proteins, including 3D structures, domains, pathway, gene ontology and visual presentation of mapping to the GO tree and KEGG pathway, to provide an up-to-date view of available knowledge with regard to the structures and molecular functions of proteins under study. AVAILABILITY: MPSS is freely accessible at http://www.scbit.org/mpss/     

SeqMap: mapping massive amount of oligonucleotides to the genome

SeqMap is a tool for mapping large amount of short sequences to the genome. It is designed for finding all the places in a reference genome where each sequence may come from. This task is essential to the analysis of data from ultra high-throughput sequencing machines. With a carefully designed index-filtering algorithm and an efficient implementation, SeqMap can map tens of millions of short sequences to a genome of several billions of nucleotides. Multiple substitutions and insertions/deletions of the nucleotide bases in the sequences can be tolerated and therefore detected. SeqMap supports FASTA input format and various output formats, and provides command line options for tuning almost every aspect of the mapping process. A typical mapping can be done in a few hours on a desktop PC. Parallel use of SeqMap on a cluster is also very straightforward.     

Ordering of Mutant Sites in the Isoleucine-Valine Genes of Escherichia coli by Use of Merogenotes Derived from F14: a New Procedure for Fine-Structure Mapping

F-merogenotes derived from F(14) by transductional shortening have previously been found to consist of the sex factor plus one or more of the ilv genes. It is shown here that they carry one or more ilv genes and a variable portion of the adjacent proximal ilv gene. This observation was used to develop a method, analogous to deletion mapping, for ordering mutant sites within the ilv genes. This method requires the use of a series of merogenotes each carrying an increasingly longer segment of the gene being mapped. A simplified method of fine-structure mapping is also described which requires only one or two F' donor strains to map any one gene. This method is based on the large differences observed in recombination frequencies for mutant sites at various distances from the origin of the incomplete merogenote gene. The sequence of 25 mutant sites within three of the ilv genes was determined by use of the simplified procedure.     

Multi-agent-based bio-network for systems biology: protein–protein interaction network as an example

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.     

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

ABSTRACT: BACKGROUND: The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. RESULTS: Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. CONCLUSIONS: Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at.     

Optical mapping of DNA: single-molecule-based methods for mapping genomes

The technologies associated with DNA sequencing are rapidly evolving. Indeed, single-molecule DNA sequencing strategies are cheaper and faster than ever before. Despite this progress, every sequencing platform to date relies on reading the genome in small, abstract fragments, typically of less than 1000 bases in length. The overarching aim of the optical map is to complement the information derived from DNA sequencing by providing long-range context on which these short sequence reads can be built. This is typically done using an enzyme to target and modify at short DNA sequences of, say, six bases in length throughout the genome. By accurately placing these short pieces of sequence on long genomic DNA fragments, up to several millions of bases in length, a scaffold for sequence assembly can be obtained. This review focuses on three enzymatic approaches to optical mapping. Optical mapping was first developed using restriction enzymes to sequence-specifically cleave DNA that is immobilized on a surface. More recently, nicking enzymes have found application in the sequence-specific fluorescent labeling of DNA for optical mapping. Such covalent modification allows the DNA to be imaged in solution, and this, in combination with developing nanofluidic technologies, is enabling new high-throughput approaches to mapping. And, finally, this review will discuss the recent development of mapping with subdiffraction-limit precision using methyltransferase enzymes to label the DNA with an ultrahigh density.