ABSTRACT
Genomic analysis can be a valuable tool to assistmanagement of non-native invasive species, through determining source and number of introductions as well as clarifying phylogenetic relationships. Here, we used whole chloroplast sequencing to investigate the introduction history of Passiflora foetida sensu lato in Australia and clarify its relationship with other Passiflora species present. Phylogenetic analysis of chloroplast genome data identified three separate genetic lineages of P. foetida s. l. present in Australia, indicating multiple introductions. These lineages had affinities to samples from three separate areas within the native range in Central and South America that represented phylogenetically distinct lineages. These results provide a basis for a targeted search of the native range of P. foetida s. l. for candidate biological control agents that have co-evolved with this species and are thus better adapted to the lineages that are present in Australia. Results also indicated that the Passiflora species native to Australia are in a separate clade to that of P. foetida s. l. and other introduced Passiflora species cultivated in Australia. This knowledge is important to assess the likelihood of finding biological control agents for P. foetida s. l. that will be sufficiently host-specific for introduction in Australia. As P. foetida s. l. is a widespread non-native invasive species across many regions of the world, outcomes from this work highlight the importance of first evaluating the specific entities present in a country before the initiation of a biological control program.
ABSTRACT
Genotype-environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to best filter genotype-by-sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the results, negatively affecting management strategies. Here, we investigate the effects of filtering on GEA results and the potential implications for assessment of adaptation to environment. We use empirical and simulated data sets derived from two widespread tree species to assess the effects of filtering on GEA outputs. Critically, we find that the level of filtering of missing data and minor allele frequency affect the identification of true positives. Even slight adjustments to these thresholds can change the rate of true positive detection. Using conservative thresholds for missing data and minor allele frequency substantially reduces the size of the data set, lessening the power to detect adaptive variants (i.e., simulated true positives) with strong and weak strengths of selection. Regardless, strength of selection was a good predictor for GEA detection, but even some SNPs under strong selection went undetected. False positive rates varied depending on the species and GEA method, and filtering significantly impacted the predictions of adaptive capacity in downstream analyses. We make several recommendations regarding filtering for GEA methods. Ultimately, there is no filtering panacea, but some choices are better than others, depending on the study system, availability of genomic resources, and desired objectives.
Subject(s)
Gene-Environment Interaction , Genomics , Genotype , Gene Frequency , Genome , Polymorphism, Single NucleotideABSTRACT
Many species occur across environmental gradients and it is expected that these species will exhibit some signals of adaptation as heterogeneous environments and localized gene flow may facilitate local adaptation. While riparian zones can cross climate gradients, many of which are being impacted by climate change, they also create microclimates for the vegetation, reducing environmental heterogeneity. Species with differing distributions in these environments provide an opportunity to investigate the importance of genetic connectivity in influencing signals of adaptation over relatively short geographical distance. Association analysis with genomic data was used to compare signals of selection to climate variables in two species that have differing distributions along a river traversing a climate gradient. Results demonstrate links between connectivity, standing genetic variation, and the development of signals of selection. In the restricted species, the combination of high gene flow in the middle and lower catchment and occurrence in a microclimate created along riverbanks likely mitigated the development of selection to most climatic variables. In contrast the more widely distributed species with low gene flow showed a stronger signal of selection. Together these results strengthen our knowledge of the drivers and scale of adaptation and reinforce the importance of connectivity across a landscape to maintain adaptive potential of plant species.
Subject(s)
Ecosystem , Gene Flow , Myrtaceae/genetics , Polymorphism, Genetic , Selection, Genetic , Climate , RiversABSTRACT
Plant taxa can be broadly divided based on the mechanisms enabling persistence through whole-crown disturbances, specifically whether individuals resprout, populations reseed, or both or neither of these mechanisms are employed. At scales from species through to communities, the balance of disturbance-response types has major ramifications for ecological function and biodiversity conservation. In some lineages, morphologically identical populations except for differences in a disturbance-response trait (e.g.⯱â¯lignotuber) occur, offering the opportunity to apply genetic analyses to test whether trait state is representative of broader genetic distinctiveness, or alternatively, variation in response to local environmental conditions. In eucalypts, a globally-significant plant group, we apply dense taxon sampling and high-density, genome-wide markers to test monophyly and genetic divergence among pairs of essentially morphologically-identical taxa excepting lignotuber state. Taxa differing in lignotuber state formed discrete phylogenetic lineages. Obligate-seeders were monophyletic and strongly differentiated from each other and lignotuber-resprouters, but this was not the case for all lignotuber-resprouter taxa. One lignotuber state transition within our sample clade was supported, implying convergence of some non-lignotuber morphology characters. Greater evolutionary rate associated with the obligate-seeder disturbance-response strategy offers a plausible explanation for these genetic patterns. Lignotuber state is an important taxonomic character in eucalypts, with transitions in lignotuber state having contributed to the evolution of the exceptional diversity of eucalypts in south-western Australia. Differences in lignotuber state have evolved directionally with respect to environmental conditions.
Subject(s)
Eucalyptus/classification , Eucalyptus/genetics , Genomics , Phylogeny , Wood/genetics , Biodiversity , Geography , Phenotype , Principal Component Analysis , Quantitative Trait, Heritable , Rain , South Australia , Temperature , Western AustraliaABSTRACT
Spatial genetic patterns can be influenced by a broad range of factors across a landscape. The hypothesis that heterogeneous vegetation and habitat fragmentation rather than water flow influence genetic patterns in two riparian plant species with different niches was tested. Genotyping by sequencing was used to assess the genetic diversity and structure of each species at 12 sites across a river catchment. Generalized dissimilarity modelling examined the relative influence that vegetation type and habitat fragmentation had on patterns of genetic differentiation across the landscape. Restricted gene flow in the widespread species, Callistachys lanceolata, resulted in lower genetic differentiation than that exhibited by Astartea leptophylla, a restricted riparian species with high gene flow. Geographic distance and vegetation type explained the patterns of genetic differentiation in the widespread species, whereas habitat fragmentation and, to a lesser extent, vegetation type explained patterns in the restricted species. Water flow was not found to have significant impacts on patterns of genetic diversity in riparian plant species with restricted and widespread distribution. Impacts of vegetation type on genetic differentiation were most likely due to change in canopy density and associated pollinator communities in the vegetation types across the catchment. Reduced connectivity caused by habitat fragmentation was evident in the restricted riparian species, while reduced connectivity in the widespread species was related to the change of vegetation type between sites. Natural causes of reduced connectivity as well as anthropogenic causes need to be considered in future work to predict persistence and resilience under a changing climate.
Subject(s)
Ecosystem , Gene Flow , Climate , RiversABSTRACT
Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species, and several software packages exist for elucidating paternity in diploids; however, these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce polypatex, an r package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers and a set of candidate fathers, polypatex uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring-mother pair. polypatex can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) - for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. polypatex is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.