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openmit-licenseAug 2024View details →

Creating a 7,000 strains genotype-phenotype dataset of E. coli and antimicrobial resistance phenotypes

<h1>Description</h1> This Zenodo repository contains the data (except for the input fastq files available on SRA and intermediary files generated during the variant calling process) and code to recapitulate the study from <a href="https://doi.org/10.57844/arcadia-d2cf-ebe5">https://doi.org/10.57844/arcadia-d2cf-ebe5</a> and the associated GitHub repository, where the code, pipelines, and analysis are described in more detail.   <h1>Work summary</h1> In this work, we established a framework for compiling large genotype-phenotype datasets and produced a large-scale dataset of more than 7,000 E. coli strains and antimicrobial resistance phenotypes. We leveraged the genetic information and antimicrobial resistance (AMR) phenotype data available for the bacterium Escherichia coli to construct our dataset and took advantage of the existing knowledge about genetic variations and AMR phenotypes to validate our approach and dataset. We performed variant calling and compiled a genotype-phenotype dataset for more than 7,000 E. coli strains. Briefly, variant calling consists of identifying all genetic variations and their associated genotypes in a population compared to a reference genome. This is performed by aligning sequencing reads for each strain of the population against a reference genome, then identifying polymorphic regions in the population, and finally characterizing variants and their genotypes at each of these polymorphic regions. We have generated a dataset that successfully revealed significant genetic diversity and identified 2.4 million variants. By focusing on non-silent variants within genes associated with AMR, we confirmed the dataset's accuracy.  We hope this study is a foundational resource for conducting large-scale genotype-phenotype studies that will offer valuable insights for genetics investigations, informing the development of treatments and prevention strategies for AMR. This resource is invaluable for microbiologists and epidemiologists seeking to understand AMR mechanisms and improve genotype-phenotype predictions in pathogenic E. coli outbreaks. Additionally, it's of particular interest to geneticists and evolutionary biologists, providing a dataset to develop strategies for studying genetic interactions and broader applications in phenotype-phenotype predictions and phylogenetic research. <h1>Data organization</h1> Data are organized in the compressed folder. Briefly, they’re divided into two main folders. The first folder, dataset_generation, includes the code and information necessary to build the genotype dataset and perform the variant calling. It covers major steps like the generation of the reference pangenome used for variant calling, the variant calling pipeline applied to each of the 7,000 strains, the filtering of false positive variants, and the annotation of the variants.  The second section, dataset_analysis, includes the code and information used to process and analyze the dataset and generate figures for the Pub (https://doi.org/10.57844/arcadia-d2cf-ebe5). It includes the preliminary analysis of AMR phenotypes within the population and the analysis of variants regarding known AMR phenotypes.   <h1>Files description</h1> The following table provides a list and description of the different files and their locations. <table> <tbody> <tr> <td>File name</td> <td>Location</td> <td>Description</td> </tr> <tr> <td>variant_calling_pipeline</td> <td>dataset_generation/scripts/</td> <td>Snakefile: performs variant calling from raw paired-end sequencing files and generate one vcf.gz file per sample</td> </tr> <tr> <td>snakemake_ECOR72_annotation</td> <td>Snakefile: performs Prokka annotation on inputs whole genome fastq files</td> </tr> <tr> <td>ECOR72_and_DP_threshold_analysis.Rmd</td> <td>R markdown: analyses the coverage of known present and absebt loci in the ECOR population</td> </tr> <tr> <td>average_coverage_41.csv</td> <td>dataset_generation/data/dp_threshold/</td> <td>Pangenome loci read coverage information for 40 ECOR strains</td> </tr> <tr> <td>average_coverage_last32.csv</td> <td>Pangenome loci read coverage information for 32 ECOR strains</td> </tr> <tr> <td>whole_pan_ecor_presence_absence.csv</td> <td>Reformated pangenome loci presence-absence in ECOR strains</td> </tr> <tr> <td>pangenome_genomes_SRA_GCA.csv</td> <td>Correspondance table between ECOR72 strains genome names and raw sequencing files SRA accession number</td> </tr> <tr> <td>index_loci_pangenome_good.txt</td> <td>List of indexed positions in the pangenome</td> </tr> <tr> <td>list_ecor_txtfiles.txt</td> <td>List of txt files (containing the DP information per nucleotide) to use - This corresponds to the files for each 72 ECOR strains</td> </tr> <tr> <td>ECOR72_SRA_and_assembly_accessions.csv</td> <td>dataset_generation/data/</td> <td>List of Genome accession number and the SRA accession number of the associated sequencing files for the 72 ECOR strains</td> </tr> <tr> <td>sample_list_SRA.csv</td> <td>List of SRA accession numbers of the E. coli strains used for variant calling</td> </tr> <tr> <td>gene_presence_absence.csv</td> <td>dataset_generation/results/pangenome_cds/</td> <td>Roary output of presence-absence of the pangenome cds loci in the ECOR72 strains</td> </tr> <tr> <td>genes.gff</td> <td>Annotation file of the pangenome cds sequences (Prokka output)</td> </tr> <tr> <td>pangenome_cds.fa</td> <td>Roary output cds_pangenome sequencing file</td> </tr> <tr> <td>summary_statistics.txt</td> <td>Roary statistics output of creations of the cds pangenome</td> </tr> <tr> <td>roary_output</td> <td>Roary output folder</td> </tr> <tr> <td>IGR_presence_absence.csv</td> <td>dataset_generation/results/pangenome_igr/</td> <td>Piggy output of presence-absence of the pangenome igr loci in the ECOR72 strains</td> </tr> <tr> <td>pangenome_igr.fasta</td> <td>Piggy output igr_pangenome sequencing file</td> </tr> <tr> <td>piggy_output</td> <td>Piggy output folder</td> </tr> <tr> <td>whole_pangenome.fasta</td> <td>dataset_generation/results/pangenome_whole/</td> <td>whole pangenome sequences</td> </tr> <tr> <td>annot_summary_filtered.html</td> <td>dataset_generation/results/vcf/</td> <td>Summary of snpEff annotations</td> </tr> <tr> <td>annotated_output.vcf.gz</td> <td>snpEff annotated vcf file</td> </tr> <tr> <td>annotated_output.vcf.gz.csi</td> <td>indexed annotated vcf file</td> </tr> <tr> <td>filtered_output.vcf.gz</td> <td>filtered vcf file (removed low coveraged and low quality variants)</td> </tr> <tr> <td>filtered_output.vcf.gz.csi</td> <td>indexed filtered vcf files</td> </tr> <tr> <td>output.non_silent.vcf.gz</td> <td>vcf file containing only the nonsilent variants in the pangenome cds loci</td> </tr> <tr> <td>merged_output_listN.vcg.gz</td> <td>intermediary vcf files of 1000 merged strains vcf - these intermediary merged files are numbered from 1 to 7</td> </tr> <tr> <td>merged_output_all.vcf.gz</td> <td>final vcf.gz files of all merged vcf files in this study</td> </tr> <tr> <td>List_N_merging.txt</td> <td>dataset_generation/data/vcf_merging/</td> <td>List of the 1000 vcf.gz files to be merged together. There are 7 lists, numbered from 1 to 7</td> </tr> <tr> <td>ecor72_array.txt</td> <td>dataset_generation/results/ecor72_DP/</td> <td>Consolidate DP information per nucleotide for each ECOR strain</td> </tr> <tr> <td>variants_pos.tsv</td> <td>dataset_analysis/data/variant_analysis/</td> <td>List of all the variants found in the population and  identified by their locus and position within the locus</td> </tr> <tr> <td>allele_freqs.txt</td> <td>Variant frequency informations</td> </tr> <tr> <td>variants_non_silent_pos.tsv</td> <td>List of all the non-silent  variants found in the population and  identified by their locus and position within the locus</td> </tr> <tr> <td>allele_non_silent_freqs.txt</td> <td>Non-silent variant frequency informations</td> </tr> <tr> <td>cds_eggNog.tsv</td> <td>eggNog output file of the pangenome annotation</td> </tr> <tr> <td>COG_functional_categories.csv</td> <td>Correspondance between COG functional categories and higher-order annotation</td> </tr> <tr> <td>BVBRC_genome_May31.csv</td> <td>dataset_analysis/data/dataset_analysis</td> <td>List of E. coli with available genomes as reported in BCBRV database</td> </tr> <tr> <td>BVBRC_genome_amr_May31.csv</td> <td>E. coli antimicrobial resistance information available in BCBRV database</td> </tr> <tr> <td>antibiotic_class.csv</td> <td>Antibiotic name and Antibiotic class information</td> </tr> <tr> <td>resistance_output.non_silent.vcf.gz</td> <td>dataset_analysis/data/antimicrobial_resistance_analysis</td> <td>vcf.gz file of the loci expected to be associated with antimicrobial resistance</td> </tr> <tr> <td>antibiotic_resistance_freq.csv</td> <td>Frequency information for the non-silent variant in the selected antimicrobial genes</td> </tr> <tr> <td>SRA_to_genome_name.csv</td> <td>correspondence between strain SRA accession number and genome name (as reported in BVBRC)</td> </tr> <tr> <td>Dataset_metainfo_AMR_analysis.Rmd</td> <td>dataset_analysis/scripts</td> <td>R markdown: conducts the characterization of the population and analysis of the AMR phenotype distribution</td> </tr> <tr> <td>Variant_population_analysis.Rmd</td> <td>R markdown: conducts the analysis and investigation of identified variants in the population</td> </tr> <tr> <td>Antimicrobial_resistance_investigation.Rmd</td> <td>R markdown: conducts the antimicrobial resistance investigation </td> </tr> </tbody> </table>

FIG. 5 in Patterns of Phenotypic Variation in the Mouth Size of Lanternfishes (Teleostei: Myctophiformes)

FIG. 5. Time-calibrated phylogeny of lanternfishes from Davis et al. (2014) based on nuclear and mitochondrial data. Maximum likelihood and parsimony ancestral character-state reconstructions shown at nodes. Where reconstructions differ, parsimony is above the node and likelihood is below the node.

FIG. 4 in Patterns of Phenotypic Variation in the Mouth Size of Lanternfishes (Teleostei: Myctophiformes)

FIG. 4. Relative warp analysis of mouth size in: (A) Lampanyctinae; (B) lampanyctine genera with high morphospace variation; (C–E) examples of lampanyctine genera with separation in morphospace.

FIG. 6 in Patterns of Phenotypic Variation in the Mouth Size of Lanternfishes (Teleostei: Myctophiformes)

FIG. 6. Relative warp analysis of upper-jaw length among species of Diaphus. The two main trends of mouth size are represented by text color and outlines on the circles representing specimens; black text and outlines indicate longer upper jaws and orange text with white outlines indicate shorter upper jaws. The presence of short and long upper jaws are indicated on a summary phylogeny of species within Diaphus (Denton, 2014), with species included in this study indicated by a circle and species coded from an external source indicated by a square (Froese and Pauly, 2015). Circles and squares colored black indicate longer upper jaws, whereas orange indicates shorter upper jaws.

FIG. 3 in Patterns of Phenotypic Variation in the Mouth Size of Lanternfishes (Teleostei: Myctophiformes)

FIG. 3. Relative warp analysis of mouth size in: (A) Myctophinae; (B) myctophine genera with high morphospace variation; (C–E) examples of myctophine genera with separation in morphospace.

FIG. 1 in Patterns of Phenotypic Variation in the Mouth Size of Lanternfishes (Teleostei: Myctophiformes)

FIG. 1. Examples of variation in upper-jaw morphology among lanternfishes. Scale bars represent 5 mm. (A) Myctophum obtusirostre (MCZ 51389); (B) Hygophum macrochir (MCZ 115225); (C) Stenobrachius leucopsarus (FMNH 71832); (D) Nannobrachium cuprarium (MCZ 112776); (E) Neoscopelus macrolepidotus (FMNH 112581); (F) Scopelengys tristis (USNM 201152); (G) Landmark placement sites on lanternfish specimens. Gonichthys tenuiculus (FMNH 71685).

opencc-by-4.0Sep 2024View details →

Simulation and empirical data for "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations"

Simulation data and empirical data used to generate figures from "Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations". Can be used with code provided on the associated github to regenerate the figures.

opencc-by-4.0Sep 2024View details →

BRESOV WP5 Common Bean, phenotypic data

Partners P6-FiBL, P11-VRDS, P16-SERIDA, P18-ITAKA, P21-SECL conducted 2 years of trials except P11-VRDS who conducted 3 years, the first two of them in two locations each. The file BRESOV_BEAN_DATA_descriptors.xlsx contains the list of all the cultivars/lines tested per partner and year, as well as all the descriptors used in the data files. For each trait the average value of the repetitions is reported. P6-FiBL:  Trials were conducted in spring/summer 2020 and 2021 at an organic farming cooperative in Dietikon, Switzerland.  Plots are randomly distributed per block. Blocks are four seed beds. In 2020, the trial was sown on the 3rd of July (direct sowing), almost 2 months later than normal in this location due to the late availability of seeds from the seed multiplication. The 8 varieties were cultivated in 4 plots per variety for an outcome of approx. 25 Plants/m2 outcome, 9.375m2 per plot, half of each plot was harvested green (the data in this dataset) and the rest was left to be harvested as dry beans (dry beans data not included).  In 2021, seed were sown on 10.05.2021 in rows spaced 0.5m, at a density of 25-35 plant/m2, in 17.6m2 per variety plot and 4 repetitions per variety. No fertilizer was applied. The harvest of green beans was carried 3 times a week from 07 July to 09 August 2021.  P11-VRDS VRDS conducted trials in two location in 2020 and 2021, and for an additional year in one location in 2022. The two locations are a Romanian organic Farm (RO FARM) and P11-VRDS experimental farm on-station. Four plots (7.5 m2 and 80 plants/plot) per variety, were randomized on a field of 300m2, at each of the 2 locations and for each of the three trials years. every year of trial. P16-SERIDA The trials of snap bean cultivars were carried out on the field of an organic farmer in Asturias, Spain under the supervision of SERIDA staff during the years 2020 and 2021. The field trial included 12 cultivars (in 2020) and three replicates per cultivar with 20-25 plants distributed in plots of 4.5 m2. P18-ITAKA ITAKA conducted 3 bean trials, two under greenhouse in 2020 and 2021 (September to December) and a third trial in open field in 2021.  The trials were conducted with 4 replicates per variety on an area of 245 m2 (18m x 13,5m greenhouse) in the greenhouse trials and open field trial.  Variety plots were randomly distributed within blocks. Each block consisted of one repetition of all varieties in the trial. P21-SECL SECL conducted their bean variety trial on their organic experimental farm in open field from July to September 2020 and June to September 2021. A complete random block design with varieties and four replicates per variety were used. In 2020, each experimental unit consisted of 88 plants sown into two plots of 1.5m wide and 4m length (12m², 7.4 plants/m²). In 2021, each experimental plot was 5m in length and 1.5m in width and beans were sown at 13 plants/m².

opencc-by-4.0Nov 2024View details →

Natural selection at PRKAA1 variant in Andeans is associated with improved ventilation and sleep phenotypes in highlanders and lowlanders

<h2>Overview</h2> This repository contains data files and scripts related to the study titled "Natural selection at PRKAA1 variant in Andeans is associated with improved ventilation and sleep phenotypes in highlanders and lowlanders." This study explores genetic selection on the PRKAA1 gene in Andean populations and investigates how it impacts physiological responses to high altitude. The data includes genotype-phenotype associations, whole-genome sequences, and selection scans that contribute to understanding how PRKAA1 variants support adaptation to high-altitude environments. <h2>Repository Structure</h2> <h3>Main Directory</h3> <ul> <li> README.md: This document. </li> </ul> <h3>Subdirectories and Files</h3> <ol> <li> SNP Genotyping <ul> <li> prkaa1 association results.xlsx: Contains statistical results for associations between PRKAA1 SNPs and respiratory and sleep-related phenotypes. </li> <li> prkaa1 genotype and cdp phenotype.csv: Dataset with PRKAA1 genotypes linked to phenotypic data, particularly ventilation and sleep metrics, in Cerro de Pasco, Peru. </li> <li> summary table.xlsx: Summary statistics for SNP association tests, including sample sizes and effect sizes for each phenotype. </li> </ul> </li> <li> Large Genome Summary Statistics <ul> <li> FHS : Data from the Framingham Heart Study (FHS), a cohort of European descent. <ul> <li> dbgap variables.xlsx: Description of phenotype and covariate variables in FHS. </li> <li> fhs stats.xlsx: Summary statistics for PRKAA1 SNPs in FHS, including sleep-related phenotypes. </li> <li> prkaa1 variant.csv: Genotype data for PRKAA1 SNPs in FHS participants. </li> </ul> </li> <li> HCHS : Data from the Hispanic Community Health Study/Study of Latinos (HCHS), focusing on the Latino population. <ul> <li> HCHS top results annotated.xlsx: Annotated top results from association tests with PRKAA1 variants. </li> <li> HCHS variable explained.xlsx: Explanation of phenotype variables in the HCHS dataset. </li> <li> prkaa1 variant.csv: Genotype data for PRKAA1 SNPs in HCHS participants. </li> </ul> </li> </ul> </li> <li> Luciferase <ul> <li> prkaa1 luciferase.csv: Contains results from luciferase assays assessing transcriptional activity related to PRKAA1 variants. These assays were conducted in HEK293T cells to determine the regulatory effect of the rs10035235 variant. </li> </ul> </li> <li> Selection Scan <ul> <li> selection scan results part1.csv.gz & selection scan results part2.csv.gz: Compressed CSV files with selection scan results for PRKAA1 across the Andean genome. These files contain scores and metrics derived from the Composite of Multiple Signals (CMS) test to identify regions under selection. </li> </ul> </li> <li> Whole Genome Sequencing <ul> <li> andean_prkaa1_region.vcf: A VCF file of high-coverage whole-genome sequences from Andean individuals, focused on the PRKAA1 region. Used in selection scans to assess allele frequencies and LD (linkage disequilibrium) patterns. </li> </ul> </li> </ol> <h2>Data Use and Citation</h2> Please cite the original manuscript when using this data for publications, presentations, or analyses. Data access is intended for research purposes only and requires proper attribution. For further information or questions about the data, please contact the repository authors: Wanjun Gu (<a href="mailto:wanjun.gu@ucsf.edu">wanjun.gu@ucsf.edu</a>) and Elijah Lawrence (<a href="mailto:elijah.lawrence@duke.edu">elijah.lawrence@duke.edu</a>) or the corresponding author Dr. Tatum Simonson (<a href="mailto:tsimonson@ucsd.edu">tsimonson@ucsd.edu</a>).

opencc-zeroDec 2012View details →

Data from: Endocrine phenotype, reproductive success and survival in the great tit, Parus major

A central goal in evolutionary ecology is to characterize and identify selection patterns on the optimal phenotype in different environments. Physiological traits, such as hormonal responses, provide important mechanisms by which individuals can adapt to fluctuating environmental conditions. It is therefore expected that selection shapes hormonal traits, but the strength and the direction of selection on plastic hormonal signals are still under investigation. Here, we determined whether, and in which way, selection is acting on the hormones corticosterone and prolactin by characterizing endocrine phenotypes and their relationship with fitness in free-living great tits, Parus major. We quantified variation in circulating concentrations of baseline and stress-induced corticosterone and in prolactin during the prebreeding (March) and the breeding season (May) for two consecutive years, and correlated these with reproductive success (yearly fledgling number) and overwinter survival in female and male individuals. In both years, individuals with high baseline corticosterone concentrations in March had the highest yearly fledgling numbers; while in May, individuals with low baseline corticosterone had the highest yearly reproductive success. Likewise, individuals that displayed strong seasonal plasticity in baseline corticosterone concentrations (high in March and low in May) had the highest reproductive success in each year. Prolactin concentrations were not related to reproductive success, but were positively correlated to the proximity to lay. Between-year plasticity in stress-induced corticosterone concentrations of males was related to yearly variation in food abundance, but not to overall reproductive success. These findings suggest that seasonally alternating directional selection is operating on baseline corticosterone concentrations in both sexes. The observed between-year consistency in selection patterns indicates that a one-time hormone sample in a given season can allow the prediction of individual fitness.

Data from: Phenotypic plasticity through transcriptional regulation of the evolutionary hotspot gene tan in Drosophila melanogaster

Phenotypic plasticity is the ability of a given genotype to produce different phenotypes in response to distinct environmental conditions. Phenotypic plasticity can be adaptive. Furthermore, it is thought to facilitate evolution. Although phenotypic plasticity is a widespread phenomenon, its molecular mechanisms are only beginning to be unravelled. Environmental conditions can affect gene expression through modification of chromatin structure, mainly via histone modifications, nucleosome remodelling or DNA methylation, suggesting that phenotypic plasticity might partly be due to chromatin plasticity. As a model of phenotypic plasticity, we study abdominal pigmentation of Drosophila melanogaster females, which is temperature sensitive. Abdominal pigmentation is indeed darker in females grown at 18°C than at 29°C. This phenomenon is thought to be adaptive as the dark pigmentation produced at lower temperature increases body temperature. We show here that temperature modulates the expression of tan (t), a pigmentation gene involved in melanin production. t is expressed 7 times more at 18°C than at 29°C in female abdominal epidermis. Genetic experiments show that modulation of t expression by temperature is essential for female abdominal pigmentation plasticity. Temperature modulates the activity of an enhancer of t without modifying compaction of its chromatin or level of the active histone mark H3K27ac. By contrast, the active mark H3K4me3 on the t promoter is strongly modulated by temperature. The H3K4 methyl-transferase involved in this process is likely Trithorax, as we show that it regulates t expression and the H3K4me3 level on the t promoter and also participates in female pigmentation and its plasticity. Interestingly, t was previously shown to be involved in inter-individual variation of female abdominal pigmentation in Drosophila melanogaster, and in abdominal pigmentation divergence between Drosophila species. Sensitivity of t expression to environmental conditions might therefore give more substrate for selection, explaining why this gene has frequently been involved in evolution of pigmentation.

opencc-zeroDec 2014View details →

Data from: Integrating molecular, phenotypic and environmental data to elucidate patterns of crocodile hybridization in Belize

The genus Crocodylus comprises 12 currently recognized species, many of which can be difficult to differentiate phenotypically. Interspecific hybridization among crocodiles is known to occur in captivity and has been documented between some species in the wild. The identification of hybrid individuals is of importance for management and monitoring of crocodilians, many of which are Convention on International Trade in Endangered Species (CITES) listed. In this study, both mitochondrial and nuclear DNA markers were evaluated for their use in confirming a suspected hybrid zone between American crocodile (Crocodylus acutus) and Morelet's crocodile (Crocodylus moreletii) populations in southern Belize where individuals and nests exhibiting atypical phenotypic features had previously been observed. Patterns observed in both phenotypic and molecular data indicate possible behavioural and ecological characteristics associated with hybridization events. The results of the combined analyses found that the majority of suspected hybrid samples represent crosses between female C. acutus and male C. moreletii. Phenotypic data could statistically identify hybrids, although morphological overlap between hybrids and C. moreletii reduced reliability of identification based solely on field characters. Ecologically, C. acutus was exclusively found in saline waters, whereas hybrids and C. moreletii were largely absent in these conditions. A hypothesized correlation between unidirectional hybridization and destruction of C. acutus breeding habitats warrants additional research.

opencc-zeroDec 2014View details →

Data from: Phenotypic variation in overwinter environmental transmission of a baculovirus and the cost of virulence

A pathogen's ability to persist in the environment is an ecologically important trait, and variation in this trait may promote coexistence of different pathogen strains. We asked whether naturally occurring isolates of the baculovirus that infects gypsy moth larvae varied in their overwinter environmental transmission, and whether this variation was consistent with a tradeoff or an upper limit to virulence that might promote pathogen diversity. We used experimental manipulations to replicate the natural overwinter infection process using 16 field-collected isolates. Virus isolates varied substantially in the fraction of larvae infected, leading to differences in overwinter transmission rates. Furthermore, isolates that killed more larvae also had higher rates of early larval death in which no infectious particles were produced, consistent with a cost of high virulence. Our results thus support the existence of a cost that could impose an upper limit to virulence even in a highly virulent pathogen.

Data from: Investigating genomic and phenotypic parallelism between piscivorous and planktivorous lake trout (Salvelinus namaycush) ecotypes by means of RADseq and morphometrics analyses

Repeated adaptive ecological diversification has commonly been reported in fish and has often been associated with trophic niche diversity. The main goal of this study was to investigate the extent of parallelism in the genomic and phenotypic divergence between piscivorous and planktivorous lake trout ecotypes from Laurentian Shield lakes, Canada. This was achieved by documenting the extent of morphological differentiation using geometric morphometrics and linear measurements as well as the pattern of genomic divergence by means of RADseq genotyping (3925 filtered SNPs) in 12 lakes. Our results indicate that the two ecotypes evolved distinct body shape and several linear measurements in parallel. Neutral genetic differentiation was pronounced between all isolated populations (Mean FST = 0.433), indicating no or very limited migration and pronounced genetic drift. Significant genetic differentiation also suggested partial reproductive isolation between ecotypes in the two lakes where they are found in sympatry. Combining different outlier detection methods, we identified 48 SNPs putatively under divergent selection between ecotypes, among which 10 could be annotated and related to functions such as developmental processes and ionic regulation. Finally, our results indicate that parallel morphological divergence is accompanied by both parallel and nonparallel genomic divergence, which is associated with the use of different trophic niches between ecotypes. The results are also discussed in the context of management and conservation of this highly exploited species throughout northern North America.

opencc-zeroDec 2010View details →

Data from: Convergence and non-convergence in ecological, phenotypic, and genetic divergence across replicate population pairs of lake and stream stickleback

Convergent (or parallel) evolution provides strong evidence for a deterministic role of natural selection: similar phenotypes evolve when independent populations colonize similar environments. In reality, however, independent populations in similar environments always show some differences: some non-convergent evolution is present. It is therefore important to explicitly quantify the convergent and non-convergent aspects of trait variation, and to investigate the ecological and genetic explanations for each. We performed such an analysis for threespine stickleback (Gasterosteus aculeatus) populations inhabiting lake and stream habitats in independent watersheds. Morphological traits differed in the degree to which lake-stream divergence was convergent across watersheds. Some aspects of this variation were correlated with ecological variables related to diet, presumably reflecting the strength and specifics of divergent selection. Furthermore, a genetic scan revealed some markers that diverged between lakes and streams in many of the watersheds and some that diverged in only a few watersheds. Moreover, some of the lake-stream divergence in genetic markers was associated within some of the lake-stream divergence in morphological traits. Our results suggest that convergent evolution, and deviations from it, are primarily the result of natural selection, which corresponds in only some respect to the dichotomous habitat classifications frequently used in such studies.

opencc-zeroDec 2017View details →

Data from: Niche theory and its relation to morphology and phenotype in geographic space: a case study in woodpeckers (Picidae)

Ecogeographic analyses have recovered common environmental trends with respect to morphology; however discrepancies among trends exist. Hypothesized reasons for these divergences vary, but most relate a taxon's morphology to its ecological niche. Morphology is known to diverge when species co-occur with competitors or predators and when species occur across different habitats and environments. A less understood divergence from ecogeographic trends is niche fixation, wherein species become locked into particular niches due to their community interactions or foraging ecology. A form of niche fixation has been hypothesized in the theory of Interspecies Social Dominance Mimicry (ISDM), in which mimics maintain relatively constant size ratios with models to perpetuate their mimicry. If true, mimics should display variation and trends in tandem with their models. Here, I use mass as a proxy for body size and examine ecogeographic trends in two sets of woodpeckers (Picidae): a Nearctic group which has been reported to interact via ISDM, and a Neotropical group which, based on similar appearances and overlapping distributions, is a potential ISDM system. I found ecogeographic trends suggestive of differential evolutionary responses, and I found evidence against niche fixation in the Nearctic clade. The Neotropic clade showed limited evidence for tandem size evolution between models and mimics, but inconsistencies in the size ratios between mimic and model populations. Here, I discuss the implications of observing divergent ecogeographic trends within mimicry systems, with specific emphasis on how environment, ecology, and community interactions guide evolution.

opencc-zeroDec 2011View details →

Data from: Niche specialization influences adaptive phenotypic plasticity in threespine stickleback

Phenotypic plasticity may be favored in generalist populations if it increases niche width, even in temporally constant environments. Phenotypic plasticity can increase the frequency of extreme phenotypes in a population and thus allow it to make use of a wide resource spectrum. Here we test the prediction that generalist populations should be more plastic than specialists. In a common-garden experiment, we show that solitary, generalist populations of threespine sticklebacks inhabiting small coastal lakes of British Columbia have a higher degree of morphological plasticity than the more specialized sympatric limnetic and benthic species. The ancestral marine stickleback showed low levels of plasticity similar to those of sympatric sticklebacks, implying that the greater plasticity of the generalist population has evolved recently. Measurements of wild populations show that those with mean trait values intermediate between the benthic and limnetic values indeed have higher morphological variation. Our data indicate that plasticity can evolve rapidly after colonization of a new environment in response to changing niche use.

Data from: Parapatric genetic introgression and phenotypic assimilation: testing conditions for introgression between Hercules beetles (Dynastes, Dynastinae)

The prevalence and consequences of genetic introgression between species have been intensively debated. I used Hercules beetles as examples to test for conditions that may be associated with the occurrence of introgression. RADseq data were used to reconstruct the species tree and history of introgression between Hercules beetles. Image data from museum specimens were used to investigate the phenotypic similarity of two adaptive traits between species from two distinct climatic realms (Nearctic vs. Neotropical). Genetic introgression was identified between Hercules beetles living in geographic proximity (parapatric). Phylogenetic relatedness and phenotypic similarity did not predict nor preclude genetic introgression between species. Phenotypic assimilation in body coloration was evident between distantly related Hercules beetles codistributed in Central America, where directional introgression was also statistically supported from the putative donor to receiver lineages. The number of introgressed loci was significantly higher between species with than without phenotypic similarity. I discuss the implications of recent studies on adaptive genetic introgression by providing supporting evidence from the Hercules beetle system.

opencc-zeroDec 2012View details →

Data from: Morphological change and phenotypic plasticity in native and non–native pumpkinseed sunfish in response to sustained water velocities

Phenotypic plasticity can contribute to the proliferation and invasion success of nonindigenous species by promoting phenotypic changes that increase fitness, facilitate range expansion and improve survival. In this study, differences in phenotypic plasticity were investigated using young-of-year pumpkinseed sunfish from colonies established with lentic and lotic populations originating in Canada (native) and Spain (non-native). Individuals were subjected to static and flowing water treatments for 80 days. Inter- and intra-population differences were tested using ancova and discriminant function analysis, and differences in phenotypic plasticity were tested through a manova of discriminant function scores. Differences between Iberian and North American populations were observed in dorsal fin length, pectoral fin position and caudal peduncle length. Phenotypic plasticity had less influence on morphology than genetic factors, regardless of population origin. Contrary to predictions, Iberian pumpkinseed exhibited lower levels of phenotypic plasticity than native populations, suggesting that canalization may have occurred in the non-native populations during the processes of introduction and range expansion.

Data from: Ocean acidification influences host DNA methylation and phenotypic plasticity in environmentally susceptible corals

As climate change challenges organismal fitness by creating a phenotype–environment mismatch, phenotypic plasticity generated by epigenetic mechanisms (e.g., DNA methylation) can provide a temporal buffer for genetic adaptation. Epigenetic mechanisms may be crucial for sessile benthic marine organisms, such as reef-building corals, where ocean acidification (OA) and warming reflect in strong negative responses. We tested the potential for scleractinian corals to exhibit phenotypic plasticity associated with a change in DNA methylation in response to OA. Clonal coral fragments of the environmentally sensitive Pocillopora damicornis and more environmentally robust Montipora capitata were exposed to fluctuating ambient pH (7.9–7.65) and low pH (7.6–7.35) conditions in common garden tanks for ~6 weeks. M. capitata responded weakly, or acclimated more quickly, to OA, with no difference in calcification, minimal separation of metabolomic profiles, and no change in DNA methylation between treatments. Conversely, P. damicornis exhibited diminished calcification at low pH, stronger separation in metabolomic profiles, and responsiveness of DNA methylation to treatment. Our data suggest corals differ in their temporal dynamics and sensitivity for environmentally triggered real-time epigenetic reprogramming. The generation of potentially heritable plasticity via environmental induction of DNA methylation provides an avenue for assisted evolution applications in corals under rapid climate change.