Network,degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system

Recently, the network paradigm, an application of graph theory to biology, has proven to be a powerful approach to gaining insights into biological complexity, and has catalyzed the advancement of systems biology. In this perspective and focusing on the immune system, we propose here a more comprehensive view to go beyond the concept of network. We start from the concept of degeneracy, one of the most prominent characteristic of biological complexity, defined as the ability of structurally different elements to perform the same function, and we show that degeneracy is highly intertwined with another recently-proposed organizational principle, i.e. 'bow tie architecture'. The simultaneous consideration of concepts such as degeneracy, bow tie architecture and network results in a powerful new interpretative tool that takes into account the constructive role of noise (stochastic fluctuations) and is able to grasp the major characteristics of biological complexity, i.e. the capacity to turn an apparently chaotic and highly dynamic set of signals into functional information.     

现代分子生物学技术在瘤胃微生态系统研究中的应用

瘤胃中栖息着大量的微生物,由于这些微生物组成复杂且有些细菌在体外无法培养,目前对这些微生物的了解仍然很少。现代分子生物学技术的发展为研究瘤胃微生物提供了有效的方法,利用核酸探针、基因序列分析、遗传指纹技术、全细胞杂交和实时定量PCR等技术可以对瘤胃微生物的分类及进化关系、区系结构图、重要酶的表达以及目的微生物的准确定量进行更为深入和透彻的研究。发展和利用这些技术不仅可以研究微生物之间的关系以及微生物与饲料颗粒之间时间与空间的关系,还能直接在细菌自然生长的环境中对其各种特征进行研究。     

Dissecting genetic networks underlying complex phenotypes: the theoretical framework

Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Both simulated and real data suggest that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many 'downstream' loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and "co-adapted" gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection, genotype by environment interaction, and the genetic basis of heterosis.     

A computational model of selection by consequences: log survivor plots

[McDowell, J.J, 2004. A computational model of selection by consequences. J. Exp. Anal. Behav. 81, 297-317] instantiated the principle of selection by consequences in a virtual organism with an evolving repertoire of possible behaviors undergoing selection, reproduction, and mutation over many generations. The process is based on the computational approach, which is non-deterministic and rules-based. The model proposes a causal account for operant behavior. McDowell found that the virtual organism consistently showed a hyperbolic relationship between response and reinforcement rates according to the quantitative law of effect. To continue validation of the computational model, the present study examined its behavior on the molecular level by comparing the virtual organism's IRT distributions in the form of log survivor plots to findings from live organisms. Log survivor plots did not show the "broken-stick" feature indicative of distinct bouts and pauses in responding, although the bend in slope of the plots became more defined at low reinforcement rates. The shape of the virtual organism's log survivor plots was more consistent with the data on reinforced responding in pigeons. These results suggest that log survivor plot patterns of the virtual organism were generally consistent with the findings from live organisms providing further support for the computational model of selection by consequences as a viable account of operant behavior.     

AFLP在分子生物学研究中的应用

扩增片段长度多态性（AFLP）可靠性强,多态检出率高,因而被认为是最有效的DNA指纹分析技术。AFLP已广泛应用于分类学、病理学、种群遗传学、DNA指纹分析的研究和建立数量性状基因图谱,成为最主要的遗传标记。介绍了AFLP的原理、影响因素及其在分子生物学研究中的应用。     

Accounting for variability in the use of permutation testing to detect quantitative trait loci

Locating quantitative trait loci (QTL), or genomic regions associated with known molecular markers, is of increasing interest in a wide variety of applications ranging from human genetics to agricultural genetics. The hope of locating QTL (or genes) affecting a quantitative trait is that it will lead to characterization and possible manipulations of these genes. However, the complexity of both statistical and genetic issues surrounding the location of these regions calls into question the asymptotic statistical results supplying the distribution of the test statistics employed. Coupled with the power of current-day computing, permutation theory was reintroduced for the purpose of estimating the distribution of any test statistic used to test for the location of QTL. Permutation techniques have offered an attractive alternative to significance measures based on asymptotic theory. The ideas of permutation testing are extended in this application to include confidence intervals for the thresholds and p-values estimated in permutation testing procedures. The confidence intervals developed account for the Monte Carlo error associated with practical applications of permutation testing and lead to an effective method of determining an efficient permutation sample size.     

A dynamic model for functional mapping of biological rhythms

Functional mapping is a statistical method for mapping quantitative trait loci (QTLs) that regulate the dynamic pattern of a biological trait. This method integrates mathematical aspects of biological complexity into a mixture model for genetic mapping and tests the genetic effects of QTLs by comparing genotype-specific curve parameters. As a way of quantitatively specifying the dynamic behavior of a system, differential equations have proven to be powerful for modeling and unraveling the biochemical, molecular, and cellular mechanisms of a biological process, such as biological rhythms. The equipment of functional mapping with biologically meaningful differential equations provides new insights into the genetic control of any dynamic processes. We formulate a new functional mapping framework for a dynamic biological rhythm by incorporating a group of ordinary differential equations (ODE). The Runge-Kutta fourth order algorithm was implemented to estimate the parameters that define the system of ODE. The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms.     

Applying Quantitative Genetic Methods to Primate Social Behavior

Increasingly, behavioral ecologists have applied quantitative genetic methods to investigate the evolution of behaviors in wild animal populations. The promise of quantitative genetics in unmanaged populations opens the door for simultaneous analysis of inheritance, phenotypic plasticity, and patterns of selection on behavioral phenotypes all within the same study. In this article, we describe how quantitative genetic techniques provide studies of the evolution of behavior with information that is unique and valuable. We outline technical obstacles for applying quantitative genetic techniques that are of particular relevance to studies of behavior in primates, especially those living in noncaptive populations, e.g., the need for pedigree information, non-Gaussian phenotypes, and demonstrate how many of these barriers are now surmountable. We illustrate this by applying recent quantitative genetic methods to spatial proximity data, a simple and widely collected primate social behavior, from adult rhesus macaques on Cayo Santiago. Our analysis shows that proximity measures are consistent across repeated measurements on individuals (repeatable) and that kin have similar mean measurements (heritable). Quantitative genetics may hold lessons of considerable importance for studies of primate behavior, even those without a specific genetic focus.     

A bird's-eye view on the modern genetics workflow and its potential applicability to the locust problem

Genetics is an immense science and the current developments in its methods and techniques as well as the fast emerging tools make it one of the most powerful biological sciences. Indeed, from taxonomy and ecology to physiology and molecular biology, every biological science makes use of genetics techniques and methods at one time or another. In fact, development in genetics is such that it is now possible to characterize and analyze the expression of the whole set of genes of virtually every living organism, even if it is a non-model one. Locusts are notorious for the damage they cause to the ecosystems and economies of the areas affected by their recurrent population outbreaks. To prevent and deal with these outbreaks, we now count on both biological as well as chemical agents that are proving to be successful in reducing the damage that otherwise locust population outbreaks might cause. However, a better, efficient and environmentally friendly solution is still a hoped-for target. In my opinion, the ideal future pesticide should be both environmentally friendly, risk free and species-specific. To reach the knowledge needed for the development of such species-specific anti-locust agent, deep and accurate knowledge of the locusts’ genetics and molecular biology is a must. Since genes and their expression levels lie at the bottom of every biological phenomenon, any species-specific solution to the locust problem requires a good knowledge of these organisms’ genes as well as the quantitative and spatio-temporal dynamics of their expression. To reach such knowledge, collaborative work is needed as well as a clear workflow that, given the fast development in the genetics tools, is not always clear to all research groups. For this reason, here I describe a genetics workflow that should allow taking advantage of the most recent genetics tools and techniques to answer question relating to locust biology. My hope is that the adoption of this and other work strategies by different research groups, especially when the work is a collaborative one, would provide precious information on the biology and the biological phenomena that these economically important organisms exhibit.     

How Important is Genetics for an Understanding of Evolution?

SYNOPSIS. The contributions of modern genetics to the understandingof evolution have been threefold. First, it has documented theextent of genetic variation that exists in populations as abasis for future evolution. In particular it has shown thatnatural selection has not destroyed all variation, as mightbe predicted, so that there must be mechanisms for the maintenanceandorigin of new selectable variation that balance the homogenizingforces of selection. Second, it has begun to provide a mechanismof the origin of genetic novelties which must be at the basisof the major features of the history of life. In doing so, ithas shown how selection fornew features is at all times historicallycontingent and that evolution is at all times at riskof fallinginto genetic dead-ends. Third, modern genetics has greatly enrichedthe diversity ofmechanisms known to cause evolutionary change.All of these mechanisms involve the conversion of variationbetween individuals into variation between populations in timeand space, but many are non-selective or even counter-selective.Natural selection is not the only mechanism of evolution.     

Cultural transmission of fitness: genes take the fast lane

Classical population genetics describes how the fate of an allele is driven by four forces: mutation, migration, selection and drift. However, these are sometimes insufficient to explain how the observed allele frequency changes and, therefore, another factor must be invoked: cultural transmission of fitness (CTF). CTF is the non-genetic transmission of any kind of behaviour that affects reproductive success. There are several clearly documented examples of CTF, and theoretical studies have shown that it affects effective population size, linkage disequilibrium and coalescent times. It is therefore a factor that must be taken into account to explain the structure of genetic diversity. In this article, we will present documented cases of how CTF affects the genetic diversity of populations and yields dramatic changes in allele frequencies.     

The expansion of information in ecological systems: Emergence as a quantifiable state

Although the term ‘emergence’ has received wide attention in the literature, most of this attention has been focused on epistemological discussions about the nature of what might be considered emergent behavior in self-organizing systems. For the concept of emergence to have any great utility for biologists, it must (1) be perceptible as a physical, quantitative property rather than just a philosophical one; (2) have a quantitative definition applicable to all levels of biological organization; and (3) be an essential component of biological system performance or evolution. Using an independent, cellular population model (running in the StarLogo system), we have developed a mutual information calculation to measure the information expansion when considering the interactions between a population of herbivores and an environment in comparison to the interactions between the individual herbivores and that environment. In self-organizing biological systems, the collective action of massively parallel units generates a greater potential complexity in the information processing capacity of the ‘whole’ system relative to the ‘individual’ parts, and as such, there is a demonstrable increase in mutual information content. From this perspective, we consider emergence to exist as a simple information expansion that is a default behavior of any system with multiple, component parts governed by a simple, probabilistic rule set. It is not a first principle of self-organizing biological systems, but rather a collective behavior that can be quantitatively described in practical terms for experimental biologists. With a quantitative formulation, the concept of emergence may become a useful information statistic in assessing the structure of biological systems.     

Going the distance: human population genetics in a clinal world

Global human genetic variation is greatly influenced by geography, with genetic differentiation between populations increasing with geographic distance and within-population diversity decreasing with distance from Africa. In fact, these 'clines' can explain most of the variation in human populations. Despite this, population genetics inferences often rely on models that do not take geography into account, which could result in misleading conclusions when working at global geographic scales. Geographically explicit approaches have great potential for the study of human population genetics. Here, we discuss the most promising avenues of research in the context of human settlement history and the detection of genomic elements under natural selection. We also review recent technical advances and address the challenges of integrating geography and genetics.     

Statistical Genetics of an Annual Plant, Impatiens Capensis. I. Genetic Basis of Quantitative Variation

Analysis of quantitative genetics in natural populations has been hindered by computational and methodological problems in statistical analysis. We developed and validated a jackknife procedure to test for existence of broad sense heritabilities and dominance or maternal effects influencing quantitative characters in Impatiens capensis. Early life cycle characters showed evidence of dominance and/or maternal effects, while later characters exhibited predominantly environmental variation. Monte Carlo simulations demonstrate that these jackknife tests of variance components are extremely robust to heterogeneous error variances. Statistical methods from human genetics provide evidence for either a major locus influencing germination date, or genes that affect phenotypic variability per se. We urge explicit consideration of statistical behavior of estimation and testing procedures for proper biological interpretation of statistical results.     

Divergent natural selection with gene flow along major environmental gradients in Amazonia: insights from genome scans, population genetics and phylogeography of the characin fish Triportheus albus

The unparalleled diversity of tropical ecosystems like the Amazon Basin has been traditionally explained using spatial models within the context of climatic and geological history. Yet, it is adaptive genetic diversity that defines how species evolve and interact within an ecosystem. Here, we combine genome scans, population genetics and sequence-based phylogeographic analyses to examine spatial and ecological arrangements of selected and neutrally evolving regions of the genome of an Amazonian fish, Triportheus albus. Using a sampling design encompassing five major Amazonian rivers, three hydrochemical settings, 352 nuclear markers and two mitochondrial DNA genes, we assess the influence of environmental gradients as biodiversity drivers in Amazonia. We identify strong divergent natural selection with gene flow and isolation by environment across craton (black and clear colour)- and Andean (white colour)-derived water types. Furthermore, we find that heightened selection and population genetic structure present at the interface of these water types appears more powerful in generating diversity than the spatial arrangement of river systems and vicariant biogeographic history. The results from our study challenge assumptions about the origin and distribution of adaptive and neutral genetic diversity in tropical ecosystems. In addition, they have important implications for measures of biodiversity and evolutionary potential in one of the world's most diverse and iconic ecosystems.     

A regression-based approach to selection mapping

Selection mapping applies the population genetics theory of hitchhiking to the localization of genomic regions containing genes under selection. This approach predicts that neutral loci linked to genes under positive selection will have reduced diversity due to their shared history with a selected locus, and thus, genome scans of diversity levels can be used to identify regions containing selected loci. Most previous approaches to this problem ignore the spatial genomic pattern of diversity expected under selection. The regression-based approach advocated in this paper takes into account the expected pattern of decreasing genetic diversity with increased proximity to a selected locus. Simulated data are used to examine the patterns of diversity under different scenarios, in order to assess the power of a regression-based approach to the identification of regions under selection. Application of this method to both simulated and empirical data demonstrates its potential to detect selection. In contrast to some other methods, the regression approach described in this paper can be applied to any marker type. Results also suggest that this approach may give more precise estimates of the location of the selected locus than alternative methods, although the power is slightly lower in some cases.     

Multigene families and the evolution of complexity

Summary Higher organisms are complex, and their developmental processes are controlled by the sequential expression of genes that often form multigene families. Facts are surveyed on how functional diversity of genes is related to duplication of genes or segments of genes, by emphasizing that diversity is often enhanced by alternate splicing and proteolytic cleavage involving duplicated genes or gene segments. Analyses of a population genetics model for the origin of gene families suggest that positive Darwinian selection is needed for acquiring gene families with desirable functions. Based on these considerations, examples that show acceleration of amino acid substitution relative to synonymous change during evolutionary processes are surveyed. Some of such examples strongly suggest that positive selection has worked. In other cases it is difficult to judge whether or not acceleration is caused by positive Darwinian selection. As a general pattern, acceleration of amino acid substitution is often found to be related to gene duplication. It is thought that complexity and diversity of gene function have been advantageous in the long evolutionary course of higher organisms.     

Use of invertebrate traits for the biomonitoring of European large rivers: the effects of sampling effort on genus richness and functional diversity

1. Studies on biodiversity and ecosystem function require considering metrics for accurately describing the functional diversity of communities. The number of taxa (richness) is commonly used to characterise biological diversity. The disadvantage of richness as a measure of biological diversity is that all taxa are taken into account on an equal basis regardless of their abundance, their biological characteristics or their function in the ecosystem. 2. To circumvent this problem, we applied a recently described measure of biological diversity that incorporates dissimilarities among taxa. Dissimilarities were defined from biological traits (e.g. life history, morphology, physiology and behaviour) of stream invertebrate taxa and the resulting biological diversity index was considered as a surrogate for functional diversity. 3. As sampling effort is known to affect the number of taxa collected within a reach, we investigated how change in functional diversity is affected by sampling effort. We used stream invertebrate community data from three large European rivers to model accumulation curves and to assess the number of samples required to estimate (i.e. closeness to the maximal value) functional diversity and genera richness. We further evaluated the precision of estimates (i.e. similarity of temporal or spatial replicates) of the total functional diversity. 4. As expected, richness estimates were strongly dependent on sampling effort, and 10 replicate samples were found to underestimate actual richness. Moreover, richness estimates showed much variation with season and location. In contrast, functional diversity had greater accuracy with less sampling effort and the precision of the estimates was higher than richness both across sampling occasions and sampling reaches. These results are further arguments towards conducting research on the design of a biomonitoring tool based on biological traits.     

Population genetics strategies to characterize long-distance dispersal of insects

Population genetics strategies offer an alternative and powerful approach for obtaining information about long-distance movement, and have been widely used for examining patterns and magnitude of insect dispersal over geographic and temporal scales. Such strategies are based on the principle that genetic divergence between local populations reflects the interplay between genetic drift and gene flow, and thus can function as an indicator of dispersal capacity. Relatively new approaches for inferring population history are widely applicable for documenting introduction routes of invasive or quarantine species. These approaches are based on genetic variability calculated from changes in gene frequency of subpopulations, measured using molecular genetic markers. Inferences from population genetics can supplement and corroborate conventional observational approaches for characterizing insect dispersal and have provided important clues to many questions raised in the field of behavior and ecology of insects. Here, we summarize our work on the boll weevil as a case study to illustrate the kinds of information on dispersal capacity and dispersal patterns that can be obtained from population genetics techniques that would be difficult or impossible to acquire in other ways. Then we provide examples of how the molecular markers and population genetics tools have been applied to answer immediate questions of relevance to eradication program managers. Though the latter are idiosyncratic to this particular pest, they demonstrate the kinds and range of problems that can be addressed in other systems through application of population genetics strategies.