GM haplotype diversity of 82 populations over the world suggests a centrifugal model of human migrations

This study investigates the GM genetic relationships of 82 human populations, among which 10 represent original data, within and among the main broad geographic areas of the world. Different approaches are used: multidimensional scaling analysis and test for isolation by distance, to assess the correlation between genetic variation and spatial distributions; analysis of variance, to investigate the genetic structure at different hierarchical levels of population subdivision; genetic similarity map (geographic map distorted by available genetic information), to identify regions of high and low genetic variation; and minimal spanning network, to point out possible migration routes across continental areas. The results show that the GM polymorphism is characterized by one of the highest amounts of genetic variation observed so far among populations of different continents (Fct=0.3915, P < 0.0001). GM diversity can be explained by a model of isolation by distance (IBD) at most continental levels, with a particularly significant fit to IBD for the Middle East and Europe. Five peripheral regions of the world (Europe, west and south sub-Saharan Africa, Southeast Asia, and America) exhibit a low level of genetic diversity both within and among populations. By contrast, East and North African, Southwest Asian, and Northeast Asian populations are highly diverse and interconnected genetically by large genetic distances. Therefore, the observed GM variation can be explained by a "centrifugal model" of modern humans peopling history, involving ancient dispersals across a large intercontinental area spanning from East Africa to Northeast Asia, followed by recent migrations in peripheral geographic regions.     

"Immunetworks", intersecting circuits and dynamics

This paper proposes a study of biological regulation networks based on a multi-level strategy. Given a network, the first structural level of this strategy consists in analysing the architecture of the network interactions in order to describe it. The second dynamical level consists in relating the patterns found in the architecture to the possible dynamical behaviours of the network. It is known that circuits are the patterns that play the most important part in the dynamics of a network in the sense that they are responsible for the diversity of its asymptotic behaviours. Here, we pursue further this idea and argue that beyond the influence of underlying circuits, intersections of circuits also impact significantly on the dynamics of a network and thus need to be payed special attention to. For some genetic regulation networks involved in the control of the immune system (“immunetworks”), we show that the small number of attractors can be explained by the presence, in the underlying structures of these networks, of intersecting circuits that “inter-lock”.     

Haplotyping for disease association: a combinatorial approach

We consider a combinatorial problem derived from haplotyping a population with respect to a genetic disease, either recessive or dominant. Given a set of individuals, partitioned into healthy and diseased, and the corresponding sets of genotypes, we want to infer "bad' and "good' haplotypes to account for these genotypes and for the disease. Assume e.g. the disease is recessive. Then, the resolving haplotypes must consist of bad and good haplotypes, so that (i) each genotype belonging to a diseased individual is explained by a pair of bad haplotypes and (ii) each genotype belonging to a healthy individual is explained by a pair of haplotypes of which at least one is good. We prove that the associated decision problem is NP-complete. However, we also prove that there is a simple solution, provided the data satisfy a very weak requirement.     

Dissecting the loci underlying maturation timing in Atlantic salmon using haplotype and multi-SNP based association methods

Characterizing the role of different mutational effect sizes in the evolution of fitness-related traits has been a major goal in evolutionary biology for a century. Such characterization in a diversity of systems, both model and non-model, will help to understand the genetic processes underlying fitness variation. However, well-characterized genetic architectures of such traits in wild populations remain uncommon. In this study, we used haplotype-based and multi-SNP Bayesian association methods with sequencing data for 313 individuals from wild populations to test the mutational composition of known candidate regions for sea age at maturation in Atlantic salmon (Salmo salar). We detected an association at five loci out of 116 candidates previously identified in an aquaculture strain with maturation timing in wild Atlantic salmon. We found that at four of these five loci, variation explained by the locus was predominantly driven by a single SNP suggesting the genetic architecture of this trait includes multiple loci with simple, non-clustered alleles and a locus with potentially more complex alleles. This highlights the diversity of genetic architectures that can exist for fitness-related traits. Furthermore, this study provides a useful multi-SNP framework for future work using sequencing data to characterize genetic variation underlying phenotypes in wild populations.Subject terms: Evolutionary genetics, Genetic association study     

Reinventing Molecular Weismannism: Information in Evolution

Molecular Weismannism is the claim that: In the development of an individual, DNA causes the production both of DNA (genetic material) and of protein (somatic material). The reverse process never occurs. Protein is never a cause of DNA. This principle underpins both the idea that genes are the objects upon which natural selection operates and the idea that traits can be divided into those that are genetic and those that are not. Recent work in developmental biology and in philosophy of biology argues that an acceptance of Molecular Weismannism requires the tacit assumption that genetic causes are different in kind from other developmental causes. They argue that if this assumption proves to be unwarranted then we should abandon, not just gene selectionism and gene centred functional solutions to the units of selection problem, but also the very notion that there is any such thing as a genetic trait. A group of possible causal distinctions (proximity, ultimacy and specificity) are explored and found wanting. It is argued that an extended version of information theory, while not strong enough to support Molecular Weismannism, will support both the claim that traits can be divided into those that are genetic and those that are not as well as the claim that there is good reason to privilege genetic causes within evolutionary and developmental explanations. The outcome of this for the units of selection debate is explored.     

Are attractors 'strange', or is life more complicated than the simple laws of physics?

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.     

The August Krogh principle applies to plants

The Krogh principle refers to the use of a large number of animals to study the large number of physiological problems, rather than limiting study to a particular organism for all problems. There may be organisms that are more suited to study of a particular problem than others. This same principle applies to plants. The authors are concerned with the recent trend in plant biology of using Arabidopsis thaliana as the "organism of choice." Arabidopsis is an excellent organism for molecular genetic research, but other plants are superior models for other research areas of plant biology. The authors present examples of the successful use of the Krogh principle in plant cell biology research, emphasizing the particular characteristics of the selected research organisms that make them the appropriate choice.     

Reaction networks as systems for resource allocation: a variational principle for their non-equilibrium steady states

Within a fully microscopic setting, we derive a variational principle for the non-equilibrium steady states of chemical reaction networks, valid for time-scales over which chemical potentials can be taken to be slowly varying: at stationarity the system minimizes a global function of the reaction fluxes with the form of a Hopfield Hamiltonian with hebbian couplings, that is explicitly seen to correspond to the rate of decay of entropy production over time. Guided by this analogy, we show that reaction networks can be formally re-cast as systems of interacting reactions that optimize the use of the available compounds by competing for substrates, akin to agents competing for a limited resource in an optimal allocation problem. As an illustration, we analyze the scenario that emerges in two simple cases: that of toy (random) reaction networks and that of a metabolic network model of the human red blood cell.     

Genetic structure of <Emphasis Type="Italic">Parnassius mnemosyne</Emphasis> (Lepidoptera: Papilionidae) populations in the Carpathian Basin

The pattern of genetic variation in a butterfly species depends on the past history of the given species and also on recent evolutionary processes affecting its populations. The aim of the present study was (i) to analyse the enzyme polymorphism in the Clouded Apollo populations of the Carpathian Basin to reveal the contemporary pattern of their genetic differentiation and (ii) to compare it with an expanded mitochondrial DNA (mtDNA) haplotype network of the SE European populations. Allozyme polymorphism was analysed in 22 populations of four geographic regions: Transdanubian (TM) and North Hungarian Mountains (NM), Körös (KÖR) and Bereg–Apuseni–East Carpathian regions (BEAC). The results of the Bayesian clustering analyses based on allozymes supported the presence of three main genetic lineages in the Carpathian Basin: One was typical for TM, another was characteristic for NM and the third cluster was predominant in KÖR. The populations of BEAC harboured a mixture of two clusters. The mtDNA haplotype network suggested a fairly similar distribution: The peri-Alpine clade together with the West Balkan clade was detected in TM, while the East Balkan clade occurred in NM, partly in TR and in the two eastern regions of the Basin (KÖR and BAEC). The incongruities between the results of the mtDNA and allozyme studies can be explained by the different timescales represented by the two markers. The mtDNA haplotype network provided strong evidence concerning the existence of two Balkan lineages, which probably formed a ‘zone of admixture’ in the Transdanubian and North Hungarian Mountains. The possibility of Last Glacial survival of Parnassius mnemosyne in the Carpathian Basin and the conservation implications of these results are discussed.     

Patterns of genetic structuring in a brown trout (<Emphasis Type="Italic">Salmo trutta</Emphasis> L.) metapopulation

One main challenge in conservation biology is to preserve genetic variability and adaptive variation within and among populations. However, constant anthropogenic habitat modifications have severe effects on the evolutionary dynamics shaping wild populations and pose a serious threat to the natural evolution of biodiversity. The aim of the present study was to unravel the genetic structuring of brown trout (Salmo trutta) populations in the largest freshwater catchment in Ireland, whose habitats have experienced major human-mediated changes over at least two centuries. A total of 419 juvenile fish were sampled from nine main rivers in the Corrib catchment and were genotyped using 12 microsatellites. Both Bayesian clustering and F _ST-based analyses of genetic variance sorted these populations into five main genetically distinct groups, characterized by different extent of genetic differentiation among populations. These groups were also characterized by some degree of admixture, which can be partly explained by recent gene flow. Overall, the study suggests that the Corrib trout may conform to a metapopulation model with local populations that show different degrees of isolation and are interconnected by various level of gene flow. Results add further insights into metapopulation evolutionary dynamics and provide a useful basis to implement appropriate conservation strategies.     

LsrR quorum sensing "switch" is revealed by a bottom-up approach

Quorum sensing (QS) enables bacterial multicellularity and selective advantage for communicating populations. While genetic "switching" phenomena are a common feature, their mechanistic underpinnings have remained elusive. The interplay between circuit components and their regulation are intertwined and embedded. Observable phenotypes are complex and context dependent. We employed a combination of experimental work and mathematical models to decipher network connectivity and signal transduction in the autoinducer-2 (AI-2) quorum sensing system of E. coli. Negative and positive feedback mechanisms were examined by separating the network architecture into sub-networks. A new unreported negative feedback interaction was hypothesized and tested via a simple mathematical model. Also, the importance of the LsrR regulator and its determinant role in the E. coli QS "switch", normally masked by interfering regulatory loops, were revealed. Our simple model allowed mechanistic understanding of the interplay among regulatory sub-structures and their contributions to the overall native functioning network. This "bottom up" approach in understanding gene regulation will serve to unravel complex QS network architectures and lead to the directed coordination of emergent behaviors.     

On finite-horizon control of genetic regulatory networks with multiple hard-constraints

Background

Probabilistic Boolean Networks (PBNs) provide a convenient tool for studying genetic regulatory networks. There are three major approaches to develop intervention strategies: (1) resetting the state of the PBN to a desirable initial state and letting the network evolve from there, (2) changing the steady-state behavior of the genetic network by minimally altering the rule-based structure and (3) manipulating external control variables which alter the transition probabilities of the network and therefore desirably affects the dynamic evolution. Many literatures study various types of external control problems, with a common drawback of ignoring the number of times that external control(s) can be applied.

Results

This paper studies the intervention problem by manipulating multiple external controls in a finite time interval in a PBN. The maximum numbers of times that each control method can be applied are given. We treat the problem as an optimization problem with multi-constraints. Here we introduce an algorithm, the "Reserving Place Algorithm'', to find all optimal intervention strategies. Given a fixed number of times that a certain control method is applied, the algorithm can provide all the sub-optimal control policies. Theoretical analysis for the upper bound of the computational cost is also given. We also develop a heuristic algorithm based on Genetic Algorithm, to find the possible optimal intervention strategy for networks of large size.

Conclusions

Studying the finite-horizon control problem with multiple hard-constraints is meaningful. The problem proposed is NP-hard. The Reserving Place Algorithm can provide more than one optimal intervention strategies if there are. Moreover, the algorithm can find all the sub-optimal control strategies corresponding to the number of times that certain control method is conducted. To speed up the computational time, a heuristic algorithm based on Genetic Algorithm is proposed for genetic networks of large size.

     

Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.

Due to the recent progress of the DNA microarray technology, a large number of gene expression profile data are being produced. How to analyze gene expression data is an important topic in computational molecular biology. Several studies have been done using the Boolean network as a model of a genetic network. This paper proposes efficient algorithms for identifying Boolean networks of bounded indegree and related biological networks, where identification of a Boolean network can be formalized as a problem of identifying many Boolean functions simultaneously. For the identification of a Boolean network, an O(mnD+1) time naive algorithm and a simple O (mnD) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and D denotes the maximum in degree. This paper presents an improved O(momega-2nD + mnD+omega-3) time Monte-Carlo type randomized algorithm, where omega is the exponent of matrix multiplication (currently, omega < 2.376). The algorithm is obtained by combining fast matrix multiplication with the randomized fingerprint function for string matching. Although the algorithm and its analysis are simple, the result is nontrivial and the technique can be applied to several related problems.     

Genetic variability of wildlife-derived <Emphasis Type="Italic">Sarcoptes scabiei</Emphasis> determined by the ribosomal ITS-2 and mitochondrial 16S genes

Infestation by the ectoparasitic mite Sarcoptes scabiei (Acari: Sarcoptidae) has important implications for global wildlife conservation and both animal and human health. Ribosomal and mitochondrial DNA sequences of parasites are useful to determine genetic diversity and to describe their likely dynamic evolution. In this study, we described the genetic diversity of S. scabiei individuals collected from wild animals in China by sequencing the ribosomal ITS-2 and mitochondrial 16S rRNA genes. A total of 13 Sarcoptes isolates of wildlife, coupled with one of rabbit origin, were subjected to genetic characteristics. After cloning and sequencing, 14 ITS-2 sequences and 12 16S rRNA sequences were obtained and analyzed. Further analysis of haplotype network and population genetic structure revealed that there were 79 haplotypes in ITS-2 (main haplotype H2) and 31 haplotypes in 16S rRNA (main haplotype C10). The phylogenetic trees showed some partial clustering by location and host, and the analysis of gene polymorphism may prompt that all isolates of S. scabiei have a similar origin. We speculate that the genetic evolution of S. scabiei may be related with that of the hosts, but more research is necessary to better understand the host-parasite co-evolutionary relationship in S. scabiei. These results provide new insights into understanding the population genetics and evolutionary biology of S. scabiei and therefore a better understanding of controlling its infestation pathways worldwide.     

Disentangling the effects of isolation-by-distance and isolation-by-environment on genetic differentiation among <Emphasis Type="Italic">Rhododendron</Emphasis> lineages in the subgenus <Emphasis Type="Italic">Tsutsusi</Emphasis>

Ecological speciation has long been noted as a central topic in the field of evolutionary biology, and investigation into the relative importance of ecological and geographical factors is becoming increasingly emphasized. We surveyed genetic variation of 277 samples from 25 populations of nine Rhododendron species within Tsutsusi subgenus in Taiwan using simple sequence repeats of expressed sequence tags. Bayesian clustering revealed four genetic lineages: (1) the Rhododendron simsii, Rhododendron kanehirai, and Rhododendron nakaharae lineage (lineage 1); (2) the Rhododendron longiperulatum, Rhododendron breviperulatum, and Rhododendron noriakianum lineage (lineage 2); (3) the Rhododendron rubropilosum lineage (lineage 3); and (4) the Rhododendron oldhamii lineage (lineage 4). Asymmetric introgressions were found from lineage 3 into lineages 1 and 2 (introgressed lineages). Genetic admixture of non-R. oldhamii species was also revealed by a neighbor-joining tree. Variation partitioning showed that environment explained much larger portions of genetic variation than geography between non-introgressed lineages (i.e., between R. oldhamii and other lineages). However, the Mantel and partial Mantel tests and the multiple matrix regression with randomization found that isolation-by-distance played a more important role than isolation-by-environment (IBE) in contributing to genetic variation in most between lineage comparisons. Nevertheless, strong IBE was found when compared between non-introgressed lineages of R. oldhamii and R. rubropilosum, suggesting post-speciation ecological divergence. Several environmental variables, including annual mean temperature, aspect, isothermality, seasonal precipitation, slope, and soil pH, could be important ecological drivers involved in reproductive isolation between R. oldhamii and non-R. oldhamii species within the Tsutsusi subgenus.     

Combination of quantification and observation methods for study of "Side Population" cells in their "in vitro" microenvironment.

BACKGROUND: Qualitative and quantitative analyses of the rare phenotypic variants in in vitro culture systems is necessary for the understanding of cell differentiation in cell culture of primary cells or cell lines. Slide-based cytometry combines image acquisition and data treatment, and associates the power of flow cytometry (FCM) and the resolution of the microscopic studies making it suitable for the analysis of cells with rare phenotype. In this paper we develop a method that applies these principles to a particularly hot problem in cell biology, the study of stem cell like cells in cultures of primary cells, cancer cells, and various cell lines. METHODS: The adherent cells were labeled by the fluorescent dye Hoechst 33342. The images of cell populations were collected by a two-photon microscope and processed by a software developed by us. The software allows the automated segmentation of the nuclei in a very dense cell environment, the measurement of the fluorescence intensity of each nucleus and the recording of their position in the plate. The cells with a given fluorescence intensity can then be located easily on the recorded image of the culture plate for further analysis. RESULTS: The potential of our method is illustrated by the identification and localization of SP cells in the cultures of the C2C12 cell line. Although these cells represent only about 1% of the total population as calculated by flow cytometry, they can be identified in the culture plate with high precision by microscopy. CONCLUSION: Cells with the rare stem-cell like phenotype can be efficiently identified in the undisturbed cultures. Since the fluorescence intensity of rare events and the position of thousands of surrounding cells are recorded at the same time, the method associates the advantage of the FCM analysis and the microscopic observation.     

Variability of nuclear microsatellite loci in the populations of Siberian dwarf pine (<Emphasis Type="Italic">Pinus pumila</Emphasis> (Pallas) Regel) from the Russian part of the range

Variability of nuclear microsatellite loci was examined in Siberian dwarf pine. Six microsatellite loci (RPS2, RPS6, RPS12, RPS124, RPS127, Pc18) demonstrated different polymorphism levels in ten populations of Siberian dwarf pine. The average number of alleles per locus was 4.88, the average observed heterozygosity was 0.465, and the average expected heterozygosity was 0.510. About 13% of total genetic variability was explained by the genetic differences between the populations (F _ST = 0.129). Genetic distances between the examined populations of Pinus pumila inferred from the data on the SSR marker frequencies statistically significantly correlated with the geographical distances between the population samples. The level of genetic variability of the populations from Kamchatka Peninsula was lower than that demonstrated by continental and island populations. The genetic differentiation of the Kamchatka–Magadan and other populations of Siberian dwarf pine observed in our study can be explained in terms of their formation from different Pleistocene refugial centers.     

Habitat quality limits gene flow between populations of <Emphasis Type="Italic">Bombus ruderatus</Emphasis> in the South Island,New Zealand

One of the primary reasons for the decline of some bumblebee species has been habitat loss and fragmentation through land use change. Habitat fragmentation can limit connectivity between populations and gene flow between bumblebee populations can be limited by open water and human altered landscapes, however the influence of landscape features on gene flow has only been examined in non-declining species. The ruderal bumblebee, Bombus ruderatus, was successfully introduced to and is now relatively common in New Zealand, providing an opportunity to examine the biology of a species that is now rare in its native range in the UK. In this study, we examine the genetic structuring of B. ruderatus populations in the South Island of New Zealand and we demonstrate that a relatively simple classification of the landscape, into either good or poor foraging habitat at coarse resolution (800 m²), can predict levels of gene flow. We found populations of B. ruderatus as far apart as 160 km showing no significant genetic differentiation. However, this level of gene flow appears to be reliant upon continuous suitable habitat, as other populations <100 km apart were found to be significantly differentiated. These results suggest that corridors of continuous habitat are required to facilitate gene flow over large distances for this species.     

A transformational-grammar approach to the study of the regulation of gene expression

An important problem in biology is the lack of a set of common principles unifying biological knowledge. We propose generative grammar for constructing an integrative paradigm for the understanding of genome organization and the regulation of gene expression. Linguistic terms in molecular biology are defined. A genetic syntactic structure is defined as being equivalent to a sentence. The hypotheses for the grammar of genome structure are: (i) the "grammaticality" of the linguistic approach studies the "regulability" of genome structures; (ii) the "regulability" of genetic structures is independent from their specific biochemical meaning and (iii) the dynamics of regulation is implicit in the genome structure. A general structure is presented for the grammar; the application of phase-structure rules is justified by the existence of lexical categories. Transformational rules are utilized to represent loops of regulation. Negative inducible, positive repressible, positive inducible and negative repressible alternative mechanisms of regulation are represented, by four transformational rules, and the application of these rules is established by two principles. Finally, this approach is compared to other linguistic applications in molecular biology.