Academic literature on the topic 'Ecologically relevant loci'

ABSTRACTAcquisition of ecologically relevant genes is common among ocean bacteria, but whether it has a major impact on genome evolution in marine environments remains unknown. Here, we analyzed the core genomes of 16 phylogenetically diverse and ecologically relevant bacterioplankton lineages, each consisting of up to five genomes varying at the strain level. Statistical approaches identified from each lineage up to ∼50 loci showing anomalously high divergence at synonymous sites, which is best explained by recombination with distantly related organisms. The enriched gene categories in these outlier loci match well with the characteristics previously identified as the key phenotypes of these lineages. Examples are antibiotic synthesis and detoxification inPhaeobacter inhibens, exopolysaccharide production inAlteromonas macleodii, hydrocarbon degradation inMarinobacter hydrocarbonoclasticus, and cold adaptation inPseudoalteromonas haloplanktis. Intriguingly, the outlier loci feature polysaccharide catabolism inCellulophaga balticabut not inCellulophaga lytica, consistent with their primary habitat preferences in macroalgae and beach sands, respectively. Likewise, analysis ofProchlorococcusshowed that photosynthesis-related genes listed in the outlier loci are found only in the high-light-adapted ecotype and not in the low-light adapted ecotype. These observations strongly suggest that recombination with distant relatives is a key mechanism driving the ecological diversification among marine bacterial lineages.IMPORTANCEAcquisition of new metabolic genes has been known as an important mechanism driving bacterial evolution and adaptation in the ocean, but acquisition of novel alleles of existing genes and its potential ecological role have not been examined. Guided by population genetic theories, our genomic analysis showed that divergent allele acquisition is prevalent in phylogenetically diverse marine bacterial lineages and that the affected loci often encode metabolic functions that underlie the known ecological roles of the lineages under study.

AbstractMolecular biologists are rapidly characterizing the genetic basis of flowering in model species such as Arabidopsis thaliana. However, it is not clear how the developmental pathways identified in controlled environments contribute to variation in reproductive timing in natural ecological settings. Here we report the first study of quantitative trait loci (QTL) for date of bolting (the transition from vegetative to reproductive growth) in A. thaliana in natural seasonal field environments and compare the results with those obtained under typical growth-chamber conditions. Two QTL specific to long days in the chamber were expressed only in spring-germinating cohorts in the field, and two loci specific to short days in the chamber were expressed only in fall-germinating cohorts, suggesting differential involvement of the photoperiod pathway in different seasonal environments. However, several other photoperiod-specific QTL with large effects in controlled conditions were undetectable in natural environments, indicating that expression of allelic variation at these loci was overridden by environmental factors specific to the field. Moreover, a substantial number of QTL with major effects on bolting date in one or more field environments were undetectable under controlled environment conditions. These novel loci suggest the involvement of additional genes in the transition to flowering under ecologically relevant conditions.

Recent radiations are important to evolutionary biologists, because they provide an opportunity to study the mechanisms that link micro- and macroevolution. The role of ecological speciation during adaptive radiation has been intensively studied, but radiations can arise from a diversity of evolutionary processes; in particular, on large continental landmasses where allopatric speciation might frequently precede ecological differentiation. It is therefore important to establish a phylogenetic and ecological framework for recent continental-scale radiations that are species-rich and ecologically diverse. Here, we use a genomic (approx. 1 200 loci, exon capture) approach to fit branch lengths on a summary-coalescent species tree and generate a time-calibrated phylogeny for a recent and ecologically diverse radiation of Australian scincid lizards; the genus Cryptoblepharus . We then combine the phylogeny with a comprehensive phenotypic dataset for over 800 individuals across the 26 species, and use comparative methods to test whether habitat specialization can explain current patterns of phenotypic variation in ecologically relevant traits. We find significant differences in morphology between species that occur in distinct environments and convergence in ecomorphology with repeated habitat shifts across the continent. These results suggest that isolated analogous habitats have provided parallel ecological opportunity and have repeatedly promoted adaptive diversification. By contrast, speciation processes within the same habitat have resulted in distinct lineages with relatively limited morphological variation. Overall, our study illustrates how alternative diversification processes might have jointly stimulated species proliferation across the continent and generated a remarkably diverse group of Australian lizards.

Quantitative traits are often influenced by many loci with small effects. Identifying most of these loci and resolving them to specific genes or genetic variants is challenging. Yet, achieving such a detailed understanding of quantitative traits is important, as it can improve our knowledge of the genetic and molecular basis of heritable phenotypic variation. In this study, we use a genetic mapping strategy that involves recurrent backcrossing with phenotypic selection to obtain new insights into an ecologically, industrially, and medically relevant quantitative trait—tolerance of oxidative stress, as measured based on resistance to hydrogen peroxide. We examine the genetic basis of hydrogen peroxide resistance in three related yeast crosses and detect 64 distinct genomic loci that likely influence the trait. By precisely resolving or cloning a number of these loci, we demonstrate that a broad spectrum of cellular processes contribute to hydrogen peroxide resistance, including DNA repair, scavenging of reactive oxygen species, stress-induced MAPK signaling, translation, and water transport. Consistent with the complex genetic and molecular basis of hydrogen peroxide resistance, we show two examples where multiple distinct causal genetic variants underlie what appears to be a single locus. Our results improve understanding of the genetic and molecular basis of a highly complex, model quantitative trait.

Abstract Phenotypic plasticity and genotype-environment interactions (GEI) play a prominent role in plant morphological diversity and in the potential functional capacities of plant life-history traits. The genetic basis of plasticity and GEI, however, is poorly understood in most organisms. In this report, inflorescence development patterns in Arabidopsis thaliana were examined under different, ecologically relevant photoperiod environments for two recombinant inbred mapping populations (Ler × Col and Cvi × Ler) using a combination of quantitative genetics and quantitative trait locus (QTL) mapping. Plasticity and GEI were regularly observed for the majority of 13 inflorescence traits. These observations can be attributable (at least partly) to variable effects of specific QTL. Pooled across traits, 12/44 (27.3%) and 32/62 (51.6%) of QTL exhibited significant QTL × environment interactions in the Ler × Col and Cvi × Ler lines, respectively. These interactions were attributable to changes in magnitude of effect of QTL more often than to changes in rank order (sign) of effect. Multiple QTL × environment interactions (in Cvi × Ler) clustered in two genomic regions on chromosomes 1 and 5, indicating a disproportionate contribution of these regions to the phenotypic patterns observed. High-resolution mapping will be necessary to distinguish between the alternative explanations of pleiotropy and tight linkage among multiple genes.

Phenotypic novelties are an important but poorly understood category of morphological diversity. They can provide insights into the origins of phenotypic variation, but we know relatively little about their genetic origins. Cichlid fishes display remarkable diversity in craniofacial anatomy, including several novelties. One aspect of this variation is a conspicuous, exaggerated snout that has evolved in a single Malawi cichlid lineage and is associated with foraging specialization and increased ecological success. We examined the developmental and genetic origins for this phenotype and found that the snout is composed of two hypertrophied tissues: the intermaxillary ligament (IML), which connects the right and left sides of the upper jaw, and the overlying loose connective tissue. The IML is present in all cichlids, but in its exaggerated form it interdigitates with the more superficial connective tissue and anchors to the epithelium, forming a unique ligament–epithelial complex. We examined the Transforming growth factor β (Tgfβ) → Scleraxis (Scx) candidate pathway and confirmed a role for these factors in snout development. We demonstrate further that experimental up-regulation of Tgfβ is sufficient to produce an expansion of scx expression and concomitant changes in snout morphology. Genetic and genomic mapping show that core members of canonical Tgfβ signaling segregate with quantitative trait loci (QTL) for snout variation. These data also implicate a candidate for ligament development, adam12, which we confirm using the zebrafish model. Collectively, these data provide insights into ligament morphogenesis, as well as how an ecologically relevant novelty can arise at the molecular level.

Genome scans have become a common approach to identify genomic signatures of natural selection and reproductive isolation, as well as the genomic bases of ecologically relevant phenotypes, based on patterns of polymorphism and differentiation among populations or species. Here, we review the results of studies taking genome scan approaches in plants, consider the patterns of genomic differentiation documented and their possible causes, discuss the results in light of recent models of genomic differentiation during divergent adaptation and speciation, and consider assumptions and caveats in their interpretation. We find that genomic regions of high divergence generally appear quite small in comparisons of both closely and more distantly related populations, and for the most part, these differentiated regions are spread throughout the genome rather than strongly clustered. Thus, the genome scan approach appears well-suited for identifying genomic regions or even candidate genes that underlie adaptive divergence and/or reproductive barriers. We consider other methodologies that may be used in conjunction with genome scan approaches, and suggest further developments that would be valuable. These include broader use of sequence-based markers of known genomic location, greater attention to sampling strategies to make use of parallel environmental or phenotypic transitions, more integration with approaches such as quantitative trait loci mapping and measures of gene flow across the genome, and additional theoretical and simulation work on processes related to divergent adaptation and speciation.

Under standard guidance for conducting Ecological Risk Assessments (ERAs), the risks of chemical exposure to diverse organisms are most often based on deterministic point estimates evaluated against safety-factor-based levels of concern (LOCs). While the science and guidance for mechanistic effect models (e.g., demographic, population, and agent-based) have long been demonstrated to provide more ecologically relevant effect endpoints upon which risk can be evaluated, their application in ERAs has been limited, particularly in the US. This special issue highlights the state of the science in effect modeling for ERAs through demonstrated application of the recently published Population modeling Guidance, Use, Interpretation, and Development for ERA (Pop-GUIDE). We introduce this issue with a perspective on why it is critical to move past the current application of deterministic endpoints and LOCs. We demonstrate how the current, widely used approaches contain extensive uncertainty that could be reduced considerably by applying models that account for species life histories and other important endogenous and exogenous factors critical to species sustainability. We emphasize that it is long past time to incorporate better, more robust, and ecologically relevant effect models into ERAs, particularly for chronic risk determination. The papers in this special issue demonstrate how mechanistic models that follow Pop-GUIDE better inform ERAs compared to the current standard practice.

Background Large carnivores maintain the stability and functioning of ecosystems. Currently, many carnivore species face declining population sizes due to natural and anthropogenic pressures. The leopard, Panthera pardus, is probably the most widely distributed and highly adaptable large felid globally, still persisting in most of its historic range. However, we lack subspecies-level data on country or regional scale on population trends, as ecological monitoring approaches are difficult to apply on such wide-ranging species. We used genetic data from leopards sampled across the Indian subcontinent to investigate population structure and patterns of demographic decline. Methods We collected faecal samples from the Terai-Arc landscape of northern India and identified 56 unique individuals using a panel of 13 microsatellite markers. We merged this data with already available 143 leopard individuals and assessed genetic structure at country scale. Subsequently, we investigated the demographic history of each identified subpopulations and compared genetic decline analyses with countrywide local extinction probabilities. Results Our genetic analyses revealed four distinct subpopulations corresponding to Western Ghats, Deccan Plateau-Semi Arid, Shivalik and Terai region of the north Indian landscape, each with high genetic variation. Coalescent simulations with microsatellite loci revealed a possibly human-induced 75–90% population decline between ∼120–200 years ago across India. Population-specific estimates of genetic decline are in concordance with ecological estimates of local extinction probabilities in these subpopulations obtained from occupancy modeling of the historic and current distribution of leopards in India. Conclusions Our results confirm the population decline of a widely distributed, adaptable large carnivore. We re-iterate the relevance of indirect genetic methods for such species in conjunction with occupancy assessment and recommend that detailed, landscape-level ecological studies on leopard populations are critical to future conservation efforts. Our approaches and inference are relevant to other widely distributed, seemingly unaffected carnivores such as the leopard.

Comprendre les bases moléculaires de l'adaptation est un enjeu majeur en biologie évolutive. L'adaptation locale est le patron de distribution de génotypes résultant de l'action de la sélection qui tend à différencier certaines populations vivant dans des environnements différents. Au niveau génétique, l'adaptation locale se traduit par des fréquences alléliques variant le long des gradients de sélection. L'objectif de ce travail de doctorat est d'étudier l'apport des modèles de distributions d'allèles dans l'étude de l'adaptation locale à travers le cas de la plante alpine Arabis alpina (Brassicaceae) en milieu naturel. Premièrement, un criblage génomique de 825 marqueurs AFLPs sur 678 plantes provenant de 198 sites des Alpes françaises et suisses a été réalisé. Il a nécessité le développement d'une méthode de sélection des marqueurs semi-automatique. Les conséquences de cette sélection des marqueurs sur l'estimation des structure et variabilité génétiques ont été explorées. Deuxièmement, des loci d'intérêt écologique ont été identifiés comme potentiellement sous sélection. Leurs distributions alléliques sont significativement corrélées à des variables environnementales climatiques et topographiques. Les effets confondants (admixture et isolement par la distance) ont été évalués et écartés dans notre cas d'étude. Troisièmement, certains loci d'intérêt écologique ont été séquencés afin d'identifier des gènes candidats et régions génomiques potentiellement sélectionnées, en recourant à la synténie entre les génomes d'A. Alpina et de l'espèce modèle, Arabidopsis thaliana. Finalement, l'approche corrélative de détection de la sélection a été comparée avec les approches plus classiques de génomique des populations permettant de la valider. L'ensemble de ces travaux suggère que les modèles de distribution d'allèles sont une première étape pertinente avant des études d'écologie fonctionnelle visant à mieux comprendre l'adaptation à différentes conditions environnementales
Understanding the molecular basis of adaptation is a major task in evolutionary biology. Local adaptation is the pattern of genotype distributions driven by the natural selection that tends to differentiate populations living in different environments. Genetically, local adaptation results in allele frequencies varying along selection gradients. Our objective is to infer the contribution of allele distribution models in the study of local adaptation through the case of the alpine plant Arabis alpina (Brassicaceae) in the wild. First, a genome scan of 825 AFLP markers genotyped on 678 plants from 198 sites in French and Swiss Alps has been completed and has required the development of a semi-automatic method to select the markers. The effects of this selection on the estimation of genetic structure and variability have been explored. Second, ecologically relevant loci were identified as potentially submitted to selection. Their allele distributions are significantly correlated with environmental variables and topographical conditions. The confounding effects (admixture and isolation by distance) were assessed and discarded in our study case. Some ecologically relevant loci have been sequenced to identify candidate genes and genomic regions potentially selected using the synteny between the genomes of A. Alpina and the model species Arabidopsis thaliana. Finally, the correlative approach to detect selection was compared with more traditional approaches of population genomic. These results suggest that the allele distribution models are a first step before the relevant functional ecology studies to better understand the adaptation to different environmental conditions