Population Biology of the First Replicators: On the Origin of the Genotype, Phenotype and Organism

Prebiotic synthesis of short length macromolecules from precursormolecules results in a dynamic of spontaneous creation, whichallows for growth from zero density. At this prereplicator stagein the evolution of life there is no life history, since thebirth and death processes are intimately coupled through thephysical chemistry of a single reaction. With the emergenceof nonenzymatic, template-directed replication, the birth anddeath processes could diverge for the first time, since selectioncould act differently on the birth and death rates of the replicatingmolecule. Thus, with replication, natural selection and life-historyevolution began. The genotype, or nucleotide sequence, of thereplicating molecule gave rise to several phenotypic properties,the most important of which was its three-dimensional structurewhich in turn affected the birth and death processes. However,at this stage of nonenzymatic template replication, the phenotypewas the physical structure of the genotype, nothing more: Forthe divergence of the phenotype from the genotype it was necessaryfor the replicator to produce a protein. It is shown here thatthe evolution of enzyme production is facilitated by the existenceof population structure in the distribution of the macromoleculesassociated with replication. Initially, this structure was createdpassively by the localization of the macromolecules in rockcrevices, suspended water droplets, etc. Ultimately, the replicatoralong with its proteins were localized in a protocellular structureand this became the first organism. Thus, initially, the organismwas one extreme of the population structure of the macromoleculesassociated with life. The organism was the culmination of theencapsulation phase of evolution which proceeded through initialphases of passive localization.     

Obstructive Sleep Apnea Syndrome: From Phenotype to Genetic Basis

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity.Key Words: Obstructive sleep apnea, genetic, hypopnea, AHI, snoring, risk factors, phenotype, multifactorial disease.     

From Desert to Rainforest: Phenotypic Variation in Functionally Important Traits of Bushy-Tailed Woodrats (Neotoma cinerea) Across Two Climatic Extremes

Changes in body size inversely related to ambient temperatures have been described in woodrats (Neotoma) over time scales ranging from decades to millennia. However, climate-mediated variation in other traits has not been evaluated, and the effects of precipitation have been overlooked. We assessed variation in skull morphology among bushy-tailed woodrats (Neotoma cinerea) over two sampling transects spanning coastal rainforest and interior desert environments to determine whether skull morphology varied with climate. We also tested whether previously described size-temperature relationships could be generalized to our study populations. In both transects, linear measurements of functionally significant traits differed between coastal and interior populations. Geometric morphometric analyses of shape confirmed some of those differences and revealed additional patterns of skull variation. Variation in some linear measurements, including body size, was predicted by climate. However, body and skull size, as well as measurements of skull components, displayed varying responses. Although longitudinal patterns of body size variation supported Bergmann’s rule, skull size variation was only weakly associated with climate. The strongest phenotypic responses to climate were those of auditory, dental, and palatal skull traits. Altogether, our findings suggest that geographic variation in temperature and precipitation mediated selective heterogeneity and plasticity in skull traits associated with food processing and sensory organs in N. cinerea. This was consistent with our expectation of resource-dependent phenotypic variation among populations in environments with highly contrasting climatic regimes.     

数量性状由表型变异到基因发现的研究进展

分子生物学的快速发展为研究数量性状的遗传基础提供了更为有效的途径。我们可以沿着由表型变异去发现基因之路, 更准确地剖析数量性状的遗传基础; 尤其是对作物的许多重要的数量性状进行的QTL研究越来越受到重视。文章对数量遗传发展, QTL作图群体和方法的发展, QTL定位和QTG(quantitative traits genes)的鉴别方面的现状进行了综述。     

基于植物功能性状的生态学研究进展:从个体水平到全球尺度

植物功能性状是指能够反映植物碳获取、水分传递、养分循环等的重要生命活动的属性,包括植物生理、形态和物候等方面的特征。通过植物功能性状探讨物种分布格局、生长策略和存活机制及其对全球变化的响应与适应,是近年来生态学研究的热点之一。然而,不同尺度下植物功能性状与环境因子的关系存在差异,并且性状之间的关系也不尽相同。从物种、种群、群落、植被区系到全球尺度,围绕植物功能性状之间的相互关系及其对气候环境变化响应的热点问题进行了综述,梳理了近年来植物功能性状研究领域的进展,并讨论了目前植物功能性状研究的局限性和该领域未来的发展趋势。     

A Probabilistic Model to Predict Clinical Phenotypic Traits from Genome Sequencing

Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina''s Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves'' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.     

A New Method to Infer Causal Phenotype Networks Using QTL and Phenotypic Information

In the context of genetics and breeding research on multiple phenotypic traits, reconstructing the directional or causal structure between phenotypic traits is a prerequisite for quantifying the effects of genetic interventions on the traits. Current approaches mainly exploit the genetic effects at quantitative trait loci (QTLs) to learn about causal relationships among phenotypic traits. A requirement for using these approaches is that at least one unique QTL has been identified for each trait studied. However, in practice, especially for molecular phenotypes such as metabolites, this prerequisite is often not met due to limited sample sizes, high noise levels and small QTL effects. Here, we present a novel heuristic search algorithm called the QTL+phenotype supervised orientation (QPSO) algorithm to infer causal directions for edges in undirected phenotype networks. The two main advantages of this algorithm are: first, it does not require QTLs for each and every trait; second, it takes into account associated phenotypic interactions in addition to detected QTLs when orienting undirected edges between traits. We evaluate and compare the performance of QPSO with another state-of-the-art approach, the QTL-directed dependency graph (QDG) algorithm. Simulation results show that our method has broader applicability and leads to more accurate overall orientations. We also illustrate our method with a real-life example involving 24 metabolites and a few major QTLs measured on an association panel of 93 tomato cultivars. Matlab source code implementing the proposed algorithm is freely available upon request.     

作物种质资源表型性状鉴定评价:现状与趋势

表型是作物基因型与环境互作后呈现出来的性状,包括形态学、生育期、产量、品质、抗性等性状。作物种质资源具有丰富的遗传多样性,并经过数千年在世界不同区域驯化利用中的人工选择,形成了表型性状的多样性,构成育种家选育作物新品种的物质基础。认识和发现作物种质资源表型的多样性需要通过系统、科学的鉴定,特别是培育适应全球气候变化下环境的品种,更需在大量种质资源中发掘和利用抗旱、耐热、抗病虫、水肥高效利用等特性的材料。作物种质资源各类表型性状的鉴定需要对环境进行有效的控制,而多年多点的鉴定可以准确观察鉴定性状的变异水平或表达稳定性,是育种家准确选择和利用性状的重要依据。作物种质资源表型性状的鉴定主要采用田间鉴定、设施鉴定、仪器分析、感官鉴定的方式。近年来,作物种质资源表型性状鉴定已从单一环境、低通量、粗放型鉴定转变为多年多环境、重点性状、高通量精准型鉴定。随着组学技术、智能与信息技术的快速发展,作物种质资源的表型性状鉴定已进入一个新阶段,形成作物育种中重要性状准确快速发掘与应用的坚实基础。     

基于表型性状的叶用莴苣资源多样性分析

对从国内外引进的153份叶用莴苣种质资源的15个表型性状进行了系统鉴定,主要包括叶片性状、植株性状、抽薹开花时间等。结果表明:15个表型性状的平均变异系数为28.98%,其中叶缘变异系数最大(49.85%),开花期的最小(7.05%)。15个表型性状的平均遗传多样性指数为1.08,抽薹期(1.41)、叶形(1.56)、株高(1.39)的遗传多样性指数均较大,叶裂刻的遗传多样性指数最小(0.3)。通过SAS对这些材料进行聚类分析,将153份材料分为4组群,结果表明第l I和IV组群包含资源60和65份,其余组群包含材料较少。总体来讲叶用莴苣资源型性状的变异程度和遗传多样性指数较高,具有丰富的变异程度和多样性。     

The Effect of Isogenization on the Phenotypic Manifestation of Quantitative Traits in Drosophila melanogaster

A comparative analysis of the phenotypic values of the proximal and distal fragments of the radial wing vein was carried out in heterogeneous lines of Drosophila melanogaster and in isogenic lines derived from them with the help of a balancer line. The mean values of the traits in the isogenic lines were shown to significantly differ from the corresponding values in the parental heterogeneous lines. Apparently, the change in the trait values was caused by a double recombination exchange between the inverted and the normal chromosomes, which suggests partial crossing over suppression in the balancer lines.     

Measuring Evolutionary Constraints Through the Dimensionality of the Phenotype: Adjusted Bootstrap Method to Estimate Rank of Phenotypic Covariance Matrices

The potential and direction of phenotypic evolution is constrained by the distribution of genetic variation for the traits as described by the phenotypic (P) and genetic covariance matrices (G). The rank of the covariance matrix reflects the number of independent variational dimensions of the phenotype. Covariance matrices with less than full rank indicate lack of variation in some directions of the phenotype space and thus are an indication of absolute evolutionary constraints. Because selection acts upon phenotypic variation, the rank of P represents the upper limit of the dimensionality in G, relevant for selection response. The limitations of current methods to estimate matrix rank motivated us to analyze and adjust a bootstrap method and evaluate its performance by simulation. The results show that the modified bootstrap method (ABRE) gives reliable and rather conservative rank estimates when the sample size is sufficient for the number of variables studied (the sample size is at least five-fold the number of variables). Applying the method to various datasets suggests high phenotypic dimensionality in all cases. The analysis thus provides no evidence for absolute evolutionary constraints. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

From Engineering Economics to Extended Exergy Accounting: A Possible Path from Monetary to Resource-Based Costing

The article describes the extended exergy accounting technique (EEA), a novel method for computing the cost of a commodity based on its resource-base equivalent value (as opposed to its monetary cost) that enables the analyst to perform more complete and meaningful assessments of a complex system. The claim made here is that the novelty, as well as the decisive advantage, of EEA consists in its being entirely and uniformly resource based, thanks to the inclusion in the system balance of exergetic fluxes equivalent to labor, capital, and environmental remediation costs. In this respect, EEA owes some of its structural formalism to Sraffa's network representation of the economic production of commodities by means of other commodities, which it extends by accounting for the unavoidable energy dissipation in the productive chain (whose economic implications were first discussed by Georgescu-Roegen), to Daly's pioneering work in resource-oriented economics, and to Szargut's cumulative exergy consumption method.
The representation of a process by means of its extended exergy flow diagram is discussed in this article, and it is argued that some of the issues that are difficult to address with a purely monetary approach can be properly resolved by EEA. The main shortcomings of EEA are its intrinsic locality in time and space: They are demonstrated to be necessary and not casual consequences of its very definition and of the nonuniformity of societal conditions. In the conclusions, some indications are given as to the possibility of using this new technique to complement (and extend) other current tools, such as life-cycle assessment or environmental footprint analysis.     

Focus Issue on Roots: Natural Variation of Root Traits: From Development to Nutrient Uptake

The root system has a crucial role for plant growth and productivity. Due to the challenges of heterogeneous soil environments, diverse environmental signals are integrated into root developmental decisions. While root growth and growth responses are genetically determined, there is substantial natural variation for these traits. Studying the genetic basis of the natural variation of root growth traits can not only shed light on their evolution and ecological relevance but also can be used to map the genes and their alleles responsible for the regulation of these traits. Analysis of root phenotypes has revealed growth strategies and root growth responses to a variety of environmental stimuli, as well as the extent of natural variation of a variety of root traits including ion content, cellular properties, and root system architectures. Linkage and association mapping approaches have uncovered causal genes underlying the variation of these traits.Since their advent more than 400 million years ago, vascular plants have drastically transformed the land surface of our planet and facilitated the dense colonization of its land masses (Algeo and Scheckler, 1998; Gibling and Davies, 2012). Key to this was the evolution of root systems that enable plants to forage their environment for nutrients and water and anchor themselves tightly in the soil substrate. Soils are very heterogeneous environments, and because of the constant need to optimize root distribution in the soil according to sometimes conflicting parameters, root growth and development are some of the most plastic traits in plants. This plasticity is guided by environmental information that is integrated into decisions regarding how fast and in which direction to grow and where and when to place new lateral roots (LRs; Malamy and Ryan, 2001; Malamy, 2005). The distribution and function of roots are of crucial importance for plants. In fact, they are considered the most limiting factors for plant growth in almost all natural ecosystems (Den Herder et al., 2010). Not surprisingly, the plant root system plays a major role in yield and overall plant productivity (Lynch, 1995; Den Herder et al., 2010).The extent of plasticity is determined by genetic components (Pigliucci, 2005). For instance, one ecotype of a plant species may be able to increase root growth rate on a certain stimulus, whereas another ecotype lacks this characteristic (Gifford et al., 2013). The genetic components that govern traits in different ecotypes represent the outcome of adaptation arising from the selection of those traits that allow better adapted populations to reproduce more successfully (higher fitness) than less well-adapted populations (Trontin et al., 2011; Savolainen, 2013). Although local adaptation is common in plants and animals, its genetic basis is still poorly understood (Savolainen et al., 2013). Traits that drive local adaptation are often quantitative traits shaped by multiple genes. Therefore, phenotypic differences are often caused by allelic variation at several loci, each of them making small contributions to the trait (Weigel and Nordborg, 2005; Rockman, 2012). Studying the genetic basis of the natural variation of traits cannot only shed light on the evolution of these traits and their ecological relevance but also, can be used to map the genes responsible for the regulation of these traits.Most efforts to study intraspecies genetic variation to find trait-governing genes or identify useful traits have been conducted in crop species and the model plant Arabidopsis (Arabidopsis thaliana). Whereas in crop species, traits that are used have been subjected to human-directed selection during domestication, often with the aim of increasing productivity, in Arabidopsis, it is mostly natural selection that is examined. Arabidopsis is widely distributed around the world, inhabiting diverse environments that include beaches, rocky slopes, riverbanks, roadsides, and areas surrounding agriculture fields (Horton et al., 2012). A large number of accessions has been collected over the past decades from locations all over the world and made available to the scientific community. Importantly, these accessions of Arabidopsis exhibit a striking diversity of phenotypic variation of morphology and physiology (Koornneef et al., 2004) and can be used to understand the genetic and molecular bases of traits using quantitative genetics. Variations of traits are measured in a panel of genetically distinct plant strains and then correlated with the occurrence of genetic markers in these plants. Linked or associated genome regions can eventually be identified, and additional analysis can be conducted to find the causal genes. Self-fertilizing species, such as Arabidopsis, are particularly suited for such approaches, because they can be maintained as inbred lines and therefore, need to be genotyped only one time, after which they can be phenotyped multiple times. In the past, natural variation has been used to map causal genes mainly by using recombinant inbred lines (RILs) approaches; these are very powerful but lack a high mapping resolution, and they can only capture a very small subset of the allelic diversity (Korte and Farlow, 2013). However, the advent of new and cheap large-scale genotyping and sequencing technologies has enabled large-scale, high-resolution genotyping (Horton et al., 2012) and even the complete sequencing of a large number of plant strains (http://1001genomes.org; 3,000 Rice Genomes Project, 2014). With these data, genome-wide association studies (GWASs) for identification of alleles responsible for many different quantitative traits have become feasible (Weigel, 2012). In these studies, traits of a large number of accessions are measured and subsequently associated with genotyped markers, most frequently single-nucleotide polymorphism. Although GWASs are a very powerful tool and in principle, allow for a high mapping accuracy, a notable disadvantage is that the complexity of the population structure can confound these studies. However, there has been remarkable progress addressing this issue (Atwell et al., 2010; Segura et al., 2012).In this review, we highlight recent progress in understanding the genetic bases of natural variation of growth, development, and physiology of the root system. After briefly explaining how root growth and development give rise to the root system architecture (RSA), we highlight natural variation and what has been learned from it for fundamental processes in root growth and development, root growth responses to nutrient availability, and ion uptake and homeostasis.     

The boylston street fishweir: Revisited

Excavations for the Boston subway system early in this century and later for building sites revealed the presence of waterlogged wood in the peat and silt deep beneath the present surface. Beginning more than 50 yr ago, the investigation of geological and biological materials recovered from these sites, especially the wood remains, believed to have been set in place by prehistoric Native Americans, became a benchmark for the multidisciplinary application of scientific methods in archaeology and environmental reconstruction. Recent excavations for building foundations in Boston have exposed additional wooden materials. We have analyzed 216 specimens recently recovered from an excavation at 500 Boylston Street where older office buildings were demolished to make way for a new commercial structure. Although some of our findings differ from those of the previous investigators we find support for the earlier supposition that the remains represent an ancient Native American fishweir, a fencelike barrier and trap for fish on an ancient shoreline.     

Alternative Phenotypic States in Genomically Identical Cells: Interstock Genetics of a Trichocyst Phenotype in PARAMECIUM TETRAURELIA

The trichocysts of most wild stocks of Paramecium tetraurelia discharge en masse in response to picric acid. In most nonresponding wild stocks, the defective phenotype is simply determined by a single recessive gene difference from the standard wild type, stock 51. However, two wild stocks, 146 and 148, which are completely homozygous at all loci, express either a nondischarge, ND, or discharge, DI, phenotype. In stock 146, both ND and DI sublines generally reproduce true to type, but observed changes are highly biased. Changes from ND to DI occur more than ten times as often as changes from DI to ND. After conjugation between ND and DI cells, genomically identical exconjugant lines from the ND parent may be either ND or DI, while those from the DI parent invariably remain DI.—Interstock crosses between stocks 146 and 51 indicate that stock 146 possesses a recessive gene, nd146, which, when homozygous in stock 51 background, produces a distinct nondischarge phenotype, KO. Crosses between stock 146 and KO phenotype nd146 homozygotes in stock 51 background demonstrate that stock 146 possesses a dominant gene, M-nd146, which modifies the defect of nd146 homozygotes, resulting in either the ND or DI phenotype. The two loci, M-nd146 and nd146, are linked and estimated to be 5.3 centiMorgans apart. Stock 148 has the same alleles as stock 146 at these loci.—Presumably M-nd146 is involved in the dual phenotypic states in stock 146, but M-nd146 nd146 homozygotes backcrossed into stock 51 are invariably discharging. The possibility that the original ND state is independent of these genes is discussed and is regarded as unlikely. The phenotypic and genetic relationship discovered in these stocks should remind population biologists that phenotypic and genotypic variability do not always have a simple relationship. The nature and frequency of epistasis in the highly inbreeding P. tetraurelia are reviewed.