Multi-level convergence of complex traits and the evolution of bioluminescence

Evolutionary convergence provides natural opportunities to investigate how, when, and why novel traits evolve. Many convergent traits are complex, highlighting the importance of explicitly considering convergence at different levels of biological organization, or ‘multi-level convergent evolution’. To investigate multi-level convergent evolution, we propose a holistic and hierarchical framework that emphasizes breaking down traits into several functional modules. We begin by identifying long-standing questions on the origins of complexity and the diverse evolutionary processes underlying phenotypic convergence to discuss how they can be addressed by examining convergent systems. We argue that bioluminescence, a complex trait that evolved dozens of times through either novel mechanisms or conserved toolkits, is particularly well suited for these studies. We present an updated estimate of at least 94 independent origins of bioluminescence across the tree of life, which we calculated by reviewing and summarizing all estimates of independent origins. Then, we use our framework to review the biology, chemistry, and evolution of bioluminescence, and for each biological level identify questions that arise from our systematic review. We focus on luminous organisms that use the shared luciferin substrates coelenterazine or vargulin to produce light because these organisms convergently evolved bioluminescent proteins that use the same luciferins to produce bioluminescence. Evolutionary convergence does not necessarily extend across biological levels, as exemplified by cases of conservation and disparity in biological functions, organs, cells, and molecules associated with bioluminescence systems. Investigating differences across bioluminescent organisms will address fundamental questions on predictability and contingency in convergent evolution. Lastly, we highlight unexplored areas of bioluminescence research and advances in sequencing and chemical techniques useful for developing bioluminescence as a model system for studying multi-level convergent evolution.     

Single locus affects embryonic segment polarity and multiple aspects of an adult evolutionary novelty

Background  

The characterization of the molecular changes that underlie the origin and diversification of morphological novelties is a key challenge in evolutionary developmental biology. The evolution of such traits is thought to rely largely on co-option of a toolkit of conserved developmental genes that typically perform multiple functions. Mutations that affect both a universal developmental process and the formation of a novelty might shed light onto the genetics of traits not represented in model systems. Here we describe three pleiotropic mutations with large effects on a novel trait, butterfly eyespots, and on a conserved stage of embryogenesis, segment polarity.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

On mechanistic reasoning in unexpected places: the case of population genetics

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of mechanistic reasoning where it is not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences.     

Generalised Extreme Value Distributions Provide a Natural Hypothesis for the Shape of Seed Mass Distributions

Among co-occurring species, values for functionally important plant traits span orders of magnitude, are uni-modal, and generally positively skewed. Such data are usually log-transformed “for normality” but no convincing mechanistic explanation for a log-normal expectation exists. Here we propose a hypothesis for the distribution of seed masses based on generalised extreme value distributions (GEVs), a class of probability distributions used in climatology to characterise the impact of event magnitudes and frequencies; events that impose strong directional selection on biological traits. In tests involving datasets from 34 locations across the globe, GEVs described log10 seed mass distributions as well or better than conventional normalising statistics in 79% of cases, and revealed a systematic tendency for an overabundance of small seed sizes associated with low latitudes. GEVs characterise disturbance events experienced in a location to which individual species’ life histories could respond, providing a natural, biological explanation for trait expression that is lacking from all previous hypotheses attempting to describe trait distributions in multispecies assemblages. We suggest that GEVs could provide a mechanistic explanation for plant trait distributions and potentially link biology and climatology under a single paradigm.     

Assessing the Importance of Intraspecific Variability in Dung Beetle Functional Traits

Functional diversity indices are used to facilitate a mechanistic understanding of many theoretical and applied questions in current ecological research. The use of mean trait values in functional indices assumes that traits are robust, in that greater variability exists between than within species. While the assertion of robust traits has been explored in plants, there exists little information on the source and extent of variability in the functional traits of higher trophic level organisms. Here we investigated variability in two functionally relevant dung beetle traits, measured from individuals collected from three primary forest sites containing distinct beetle communities: body mass and back leg length. In doing so we too addressed the following questions: (i) what is the contribution of intra vs. interspecific differences in trait values; (ii) what sample size is needed to provide representative species mean trait values; and (iii) what impact does omission of intraspecific trait information have on the calculation of functional diversity (FD) indices from naturally assembled communities? At the population level, interspecific differences explained the majority of variability in measured traits (between 94% and 96%). In accordance with this, the error associated with calculating FD without inclusion of intraspecific variability was low, less than 20% in all cases. This suggests that complete sampling to capture intraspecific variance in traits is not necessary even when investigating the FD of small and/or naturally formed communities. To gain an accurate estimation of species mean trait values we encourage the measurement of 30–60 individuals and, where possible, these should be taken from specimens collected from the site of study.     

Invertebrate traits for the biomonitoring of large European rivers: an assessment of specific types of human impact

1. The power of selected biological invertebrate traits for discriminating different types of human impact (heavy metal pollution and cargo‐ship traffic) were tested using ecological reasoning and linear Discriminant Function Analysis (DFA). 2. Frequency distributions of individual traits and categories of traits from 68 least impacted river reaches (LIRRs) and 304 impacted river reaches were used to define simple assessment rules based on ecological reasoning for specific impairments in large European rivers. In calibration, a maximum of three variables with a priori predictions and two different impairment threshold levels were used. Similarly, DFA was performed on the same variables included in the ecological reasoning approach, but also on all available traits or trait categories. 3. Validation with an independent data set (40 LIRRs, 291 variously impacted river reaches) and using the ecological reasoning approach showed that 75–78% of the reaches were correctly assign with rules on all impact types, 35–57% with rules on heavy metal pollution and 78–93% with rules on cargo‐ship traffic. By comparison, validation showed that DFA performed globally poorer than the ecological reasoning approach. In addition, the performance of the rules based on ecological reasoning remained stable, whereas DFA performance changed between calibration and validation. 4. Although not defined for this purpose, our study provided alarming evidence regarding the impact of cargo‐ship traffic on invertebrate communities in river reaches. Reaches with cargo‐ship traffic were found to have more genera with long life cycles that reproduce repeatedly by ovoviviparity and have a sessile life. 5. The performance of our trait‐based approach to correctly assign reaches to either least impacted or impacted conditions should promote further research on the topic across larger geographic areas (without regionalization) and across smaller stream types to provide a powerful biomonitoring tool that fulfils current European Union directives.     

Trade-offs in thermal adaptation: the need for a molecular to ecological integration

Through functional analyses, integrative physiology is able to link molecular biology with ecology as well as evolutionary biology and is thereby expected to provide access to the evolution of molecular, cellular, and organismic functions; the genetic basis of adaptability; and the shaping of ecological patterns. This paper compiles several exemplary studies of thermal physiology and ecology, carried out at various levels of biological organization from single genes (proteins) to ecosystems. In each of those examples, trade-offs and constraints in thermal adaptation are addressed; these trade-offs and constraints may limit species' distribution and define their level of fitness. For a more comprehensive understanding, the paper sets out to elaborate the functional and conceptual connections among these independent studies and the various organizational levels addressed. This effort illustrates the need for an overarching concept of thermal adaptation that encompasses molecular, organellar, cellular, and whole-organism information as well as the mechanistic links between fitness, ecological success, and organismal physiology. For this data, the hypothesis of oxygen- and capacity-limited thermal tolerance in animals provides such a conceptual framework and allows interpreting the mechanisms of thermal limitation of animals as relevant at the ecological level. While, ideally, evolutionary studies over multiple generations, illustrated by an example study in bacteria, are necessary to test the validity of such complex concepts and underlying hypotheses, animal physiology frequently is constrained to functional studies within one generation. Comparisons of populations in a latitudinal cline, closely related species from different climates, and ontogenetic stages from riverine clines illustrate how evolutionary information can still be gained. An understanding of temperature-dependent shifts in energy turnover, associated with adjustments in aerobic scope and performance, will result. This understanding builds on a mechanistic analysis of the width and location of thermal windows on the temperature scale and also on study of the functional properties of relevant proteins and associated gene expression mechanisms.     

Using evolutionary genomics,transcriptomics, and systems biology to reveal gene networks underlying fungal development

Fungal model species have contributed to many aspects of modern biology, from biochemistry and cell biology to molecular genetics. Nevertheless, only a few genes associated with morphological development in fungi have been functionally characterized in terms of their genetic or molecular interactions. Evolutionary developmental biology in fungi faces challenges from a lack of fossil records and unresolved species phylogeny, to homoplasy associated with simple morphology. Traditionally, reductive approaches use genetic screens to reveal phenotypes from a large number of mutants; the efficiency of these approaches relies on profound prior knowledge of the genetics and biology of the designated development trait—knowledge which is often not available for even well-studied fungal model species. Reductive approaches become less efficient for the study of developmental traits that are regulated quantitatively by more than one gene via networks. Recent advances in genome-wide analysis performed in representative multicellular fungal models and non-models have greatly improved upon the traditional reductive approaches in fungal evo-devo research by providing clues for focused knockout strategies. In particular, genome-wide gene expression data across developmental processes of interest in multiple species can expedite the advancement of integrative synthetic and systems biology strategies to reveal regulatory networks underlying fungal development.     

Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population

While rhizome formation is intimately associated with perennialism and the derived benefit of sustainability, the introduction of this trait into temperate-zone adapted Sorghum cultivars requires precise knowledge of the genetics conditioning this trait in order to minimize the risk of weediness (e.g., Johnsongrass, S. halepense) while maximizing the productivity of perennial sorghum. As an incremental step towards dissecting the genetics of perennialism, a segregating F4 heterogeneous inbred family derived from a cross between S. bicolor and S. propinquum was phenotyped in both field and greenhouse environments for traits related to over-wintering and rhizome formation. An unseasonably cold winter in 2011 provided high selection pressure, and hence 74.8 % of the population did not survive. This severe selection pressure for cold tolerance allowed the resolution of two previously unidentified over-wintering quantitative trait locus (QTL) and more powerful correlation models than previously reported. Conflicting with previous reports, a maximum of 33 % of over-wintering variation could be explained by above-ground shoot formation from rhizomes; however, every over-wintering plant exhibited rhizome growth. Thus, while rhizome formation is required for over-wintering, other factors also determine survival in this interspecific population. The fine mapping of a previously reported rhizome QTL on sorghum chromosome SBI-01 was conducted by targeting this genomic region with additional simple sequence repeat markers. Fine mapping reduced the 2-LOD rhizome QTL interval from ~59 to ~14.5 Mb, which represents a 75 % reduction in physical distance and a 53 % reduction in the number of putative genes in the locus.     

The range implications of lizard traits in changing environments

Aim Most predictions of species ranges are based on correlating current species localities to environmental conditions. These correlative models do not explicitly include a species' biology. In contrast, some mechanistic models link traits to energetics and population dynamics to predict species distributions. These models enable one to ask whether considering a species' biology is important for predicting its range. I implement mechanistic models to investigate how a species' morphology, physiology and life history influence its range. Location North America. Methods I compare the mechanistic model predictions with those of correlative models for eight species of North American lizards in both current environments and following a uniform 3 °C temperature warming. I then examine the implications of superimposing habitat and elevation requirements on constraints associated with environmental tolerances. Results In the mechanistic model, species with a narrower thermal range for activity are both predicted and observed to have more restricted distributions. Incorporating constraints on habitat and elevation further restricts species distributions beyond areas that are thermally suitable. While correlative models generally outperform mechanistic models at predicting current distributions, the performance of mechanistic models improves when incorporating additional factors. In response to a 3 °C temperature warming, the northward range shifts predicted by the mechanistic model vary between species according to trait differences and are of a greater extent than those predicted by correlative models. Main conclusions These findings highlight the importance of species traits for understanding the dynamics of species ranges in changing environments. The analysis demonstrates that mechanistic models may provide an important complement to correlative models for predicting range dynamics, which may underpredict climate‐induced range shifts.     

Effect prediction of identified SNPs linked to fruit quality and chilling injury in peach [<Emphasis Type="Italic">Prunus persica</Emphasis> (L.) Batsch]

Single nucleotide polymorphisms (SNPs) are a fundamental source of genomic variation. Large SNP panels have been developed for Prunus species. Fruit quality traits are essential peach breeding program objectives since they determine consumer acceptance, fruit consumption, industry trends and cultivar adoption. For many cultivars, these traits are negatively impacted by cold storage, used to extend fruit market life. The major symptoms of chilling injury are lack of flavor, off flavor, mealiness, flesh browning, and flesh bleeding. A set of 1,109 SNPs was mapped previously and 67 were linked with these complex traits. The prediction of the effects associated with these SNPs on downstream products from the ‘peach v1.0’ genome sequence was carried out. A total of 2,163 effects were detected, 282 effects (non-synonymous, synonymous or stop codon gained) were located in exonic regions (13.04 %) and 294 placed in intronic regions (13.59 %). An extended list of genes and proteins that could be related to these traits was developed. Two SNP markers that explain a high percentage of the observed phenotypic variance, UCD_SNP_1084 and UCD_SNP_46, are associated with zinc finger (C3HC4-type RING finger) family protein and AOX1A (alternative oxidase 1a) protein groups, respectively. In addition, phenotypic variation suggests that the observed polymorphism for SNP UCD_SNP_1084 [A/G] mutation could be a candidate quantitative trait nucleotide affecting quantitative trait loci for mealiness. The interaction and expression of affected proteins could explain the variation observed in each individual and facilitate understanding of gene regulatory networks for fruit quality traits in peach.     

Covariation of larval gene expression and adult body size in natural populations of Drosophila melanogaster

Understanding adaptive phenotypic variation is one of the most fundamental problems in evolutionary biology. Genes involved in adaptation are most likely those that affect traits most intimately connected to fitness: life-history traits. The genetics of quantitative trait variation (including life histories) is still poorly understood, but several studies suggest that (1) quantitative variation might be the result of variation in gene expression, rather than protein evolution, and (2) natural variation in gene expression underlies adaptation. The next step in studying the genetics of adaptive phenotypic variation is therefore an analysis of naturally occuring covariation of global gene expression and a life-history trait. Here, we report a microarray study addressing the covariation in larval gene expression and adult body weight, a life-history trait involved in adaptation. Natural populations of Drosophila melanogaster show adaptive geographic variation in adult body size, with larger animals at higher latitudes. Conditions during larval development also affect adult size with larger flies emerging at lower temperatures. We found statistically significant differences in normalized larval gene expression between geographic populations at one temperature (genetic variation) and within geographic populations between temperatures (developmental plasticity). Moreover, larval gene expression correlated highly with adult weight, explaining 81% of its natural variation. Of the genes that show a correlation of gene expression with adult weight, most are involved in cell growth or cell maintenance or are associated with growth pathways.     

Identification and characterization of a repertoire of genes differentially expressed in developing top ear shoots between a superior hybrid and its parental inbreds in Zea mays L.

Heterosis has been widely used in crop breeding and production; however, little is known about the genes controlling trait heterosis. The shortage of genes known to function in heterosis significantly limits our understanding of the molecular basis underlying heterosis. Here, we report 748 genes differentially expressed (DG) in the developing top ear shoots between a maize heterotic F₁ hybrid (Mo17 × B73) and its parental inbreds identified using maize microarrays containing 28,608 unigene features. Of the 748 DG, over 600 were new for the inbred and hybrid combination. The DG were enriched for 35 of the total 213 maize gene ontology (GO) terms, including those describing photosynthesis, respiration, DNA replication, metabolism, and hormone biosynthesis. From the DG, we identified six genes involved in glycolysis, three genes in the citrate cycle, and four genes in the C4-dicarboxylic acid cycle. We mapped 533 of the 748 DG to the maize B73 genome, 298 (55.9 %) of which mapped to the QTL intervals of 11 maize ear traits. Moreover, we compared the repertoire of the DG with that of 14-day seedlings of the same inbred and hybrid combination. Only approximately 5 % of the DG was shared between the two organs and developmental stages. Furthermore, we mapped 417 (55.7 %) of the 748 maize DG to the QTL intervals of 26 rice yield-related traits. Therefore, this study provides a repertoire of genes useful for identification of genes involved in maize ear trait heterosis and information for a better understanding of the molecular basis underlying heterosis in maize.     

Disentangling Coordination among Functional Traits Using an Individual-Centred Model: Impact on Plant Performance at Intra- and Inter-Specific Levels

Background

Plant functional traits co-vary along strategy spectra, thereby defining trade-offs for resource acquisition and utilization amongst other processes. A main objective of plant ecology is to quantify the correlations among traits and ask why some of them are sufficiently closely coordinated to form a single axis of functional specialization. However, due to trait co-variations in nature, it is difficult to propose a mechanistic and causal explanation for the origin of trade-offs among traits observed at both intra- and inter-specific level.

Methodology/Principal Findings

Using the Gemini individual-centered model which coordinates physiological and morphological processes, we investigated with 12 grass species the consequences of deliberately decoupling variation of leaf traits (specific leaf area, leaf lifespan) and plant stature (height and tiller number) on plant growth and phenotypic variability. For all species under both high and low N supplies, simulated trait values maximizing plant growth in monocultures matched observed trait values. Moreover, at the intraspecific level, plastic trait responses to N addition predicted by the model were in close agreement with observed trait responses. In a 4D trait space, our modeling approach highlighted that the unique trait combination maximizing plant growth under a given environmental condition was determined by a coordination of leaf, root and whole plant processes that tended to co-limit the acquisition and use of carbon and of nitrogen.

Conclusion/Significance

Our study provides a mechanistic explanation for the origin of trade-offs between plant functional traits and further predicts plasticity in plant traits in response to environmental changes. In a multidimensional trait space, regions occupied by current plant species can therefore be viewed as adaptive corridors where trait combinations minimize allometric and physiological constraints from the organ to the whole plant levels. The regions outside this corridor are empty because of inferior plant performance.     

The Mathematical Basis of Mendelian Genetics

In a climate where increasing numbers of students are encouraged to pursue post-secondary education, the level of preparedness students have for college-level coursework is not far from the minds of all educators, especially high school teachers. Specifically within the biological sciences, introductory biology classes often serve as the gatekeeper or a pre-requisite for subsequent coursework in those fields and pre-professional programmes (eg pre-medicine or pre-veterinarian). Thus, how helpful high school science and mathematics experiences are in preparing students for their introductory biology classes is important and relevant for teachers, science educators and policy makers alike. This quantitative study looked at the association between students' high school science and mathematics experiences with introductory college biology performance. Using a nationally representative sample of US students (n?=?2667) enrolled in 33 introductory college biology courses, a multi-level statistical model was developed to analyse the association between high school educational experiences and the final course grade in introductory biology courses. Advanced high school science and mathematics coursework, an emphasis on a deep conceptual understanding of biology concepts and a prior knowledge of concepts addressed in well-structured laboratory investigations are all positively associated with students' achievement in introductory college biology.     

Individual differences in chronotypes associated with academic performance among Chilean University students

A chronotype is an individual trait that determines circadian rhythm (dark/light cycle) characteristics, associated with bedtime, waking, and other daily activities. A chronotype is classified as morning, intermediate, and evening. The objective is to associate chronotypes with academic performance in university students. A cross-sectional study was performed to evaluate the chronotype of university students (n = 703) by Horne-Ostberg questionnaire and associated with academic performance. The group with higher GPAs had higher chronotype scores (p = 0.002). Morning and intermediate chronotypes exhibited better academic performance; however, more studies are necessary to determine the underlying causes, which could influence cognitive aspects.     

Heritability and identification of QTLs and underlying candidate genes associated with the architecture of the grapevine cluster (Vitis vinifera L.)

Key message

We have identified 19 QTLs for rachis architecture, a key and complex trait for grapevine production. Fifty out of 1,173 genes underlying these QTLs are candidates to be further explored.

Abstract

In the table grape industry, the rachis architecture has economic and management implications. Therefore, understanding the genetics of this trait is key for its breeding. The aim of this work was to identify genetic determinants of traits associated with the cluster architecture. Characterisations of eight traits was performed on a ‘Ruby Seedless’ × ‘Sultanina’ crossing (F₁: n = 137) during three seasons, with and without gibberellic acid (GA₃) applications. The genotypic effects and the genotype × GA₃ interactions were significant for several traits. Rachis length (rl), lateral shoulder length and node number along the central axis were the most prominent traits. On average, the heritability of these traits was ~71 %, with heritability of rl being 76 % as estimated under different seasons. Quantitative trait loci (QTLs) analyses showed that linkage group 5 (LG₅) and LG₁₈ harboured the largest number of QTLs for these traits. According to the variance explained, the main QTL (corresponding to rl) was found on LG₉. These QTLs were supported mainly by a paternal additive effect and revealed possible pleiotropic effects. Based on the grapevine reference genome, we identified 1,173 genes located under these QTL confidence intervals. Fifty of the 891 annotated genes of this list were selected for their further characterisation because of their possible participation in the rachis architecture. In conclusion, the QTLs detected indicate that these traits and their GA₃ responsiveness have a clear genetic basis. Due to the percentage of the total variance explained, they are good candidates to participate in the genetic determination of the cluster architecture.