skip to main content


Search for: All records

Creators/Authors contains: "Buerkle, C. Alex"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Shade, Ashley (Ed.)

    Different methods are commonly used to assign core microbiome membership, leading to methodological inconsistencies across studies. In this study, we review a set of the most commonly used core microbiome assignment methods and compare their core assignments using both simulated and empirical data.

     
    more » « less
  2. Bulgarelli, Davide (Ed.)
    ABSTRACT The composition of microbial communities found in association with plants is influenced by host phenotype and genotype. However, the ways in which specific genetic architectures of host plants shape microbiomes are unknown. Genome duplication events are common in the evolutionary history of plants and influence many important plant traits, and thus, they may affect associated microbial communities. Using experimentally induced whole-genome duplication (WGD), we tested the effect of WGD on rhizosphere bacterial communities in Arabidopsis thaliana . We performed 16S rRNA amplicon sequencing to characterize differences between microbiomes associated with specific host genetic backgrounds (Columbia versus Landsberg) and ploidy levels (diploid versus tetraploid). We modeled relative abundances of bacterial taxa using a hierarchical Bayesian approach. We found that host genetic background and ploidy level affected rhizosphere community composition. We then tested to what extent microbiomes derived from a specific genetic background or ploidy level affected plant performance by inoculating sterile seedlings with microbial communities harvested from a prior generation. We found a negative effect of the tetraploid Columbia microbiome on growth of all four plant genetic backgrounds. These findings suggest an interplay between host genetic background and ploidy level and bacterial community assembly with potential ramifications for host fitness. Given the prevalence of ploidy-level variation in both wild and managed plant populations, the effects on microbiomes of this aspect of host genetic architecture could be a widespread driver of differences in plant microbiomes. IMPORTANCE Plants influence the composition of their associated microbial communities, yet the underlying host-associated genetic determinants are typically unknown. Genome duplication events are common in the evolutionary history of plants and affect many plant traits. Using Arabidopsis thaliana , we characterized how whole-genome duplication affected the composition of rhizosphere bacterial communities and how bacterial communities associated with two host plant genetic backgrounds and ploidy levels affected subsequent plant growth. We observed an interaction between ploidy level and genetic background that affected both bacterial community composition and function. This research reveals how genome duplication, a widespread genetic feature of both wild and crop plant species, influences bacterial assemblages and affects plant growth. 
    more » « less
  3. Plant–insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here, we address this knowledge gap using a recent host-range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a possible mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant–insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites. 
    more » « less
  4. Turnbaugh, Peter J. (Ed.)
    ABSTRACT New approaches to characterizing microbiomes via high-throughput sequencing provide impressive gains in efficiency and cost reduction compared to approaches that were standard just a few years ago. However, the speed of method development has been such that staying abreast of the latest technological advances is challenging. Moreover, shifting laboratory protocols to include new methods can be expensive and time consuming. To facilitate adoption of new techniques, we provide a guide and review of recent advances that are relevant for single-locus sequence-based study of microbiomes—from extraction to library preparation—including a primer regarding the use of liquid-handling automation in small-scale academic settings. Additionally, we describe several amendments to published techniques to improve throughput, track contamination, and reduce cost. Notably, we suggest adding synthetic DNA molecules to each sample during nucleic acid extraction, thus providing a method of documenting incidences of cross-contamination. We also describe a dual-indexing scheme for Illumina sequencers that allows multiplexing of many thousands of samples with minimal PhiX input. Collectively, the techniques that we describe demonstrate that laboratory technology need not impose strict limitations on the scale of molecular microbial ecology studies. IMPORTANCE New methods to characterize microbiomes reduce technology-imposed limitations to study design, but many new approaches have not been widely adopted. Here, we present techniques to increase throughput and reduce contamination alongside a thorough review of current best practices. 
    more » « less
  5. Abstract

    Infections by maternally inherited bacterial endosymbionts, especially Wolbachia, are common in insects and other invertebrates but infection dynamics across species ranges are largely under studied. Specifically, we lack a broad understanding of the origin of Wolbachia infections in novel hosts, and the historical and geographical dynamics of infections that are critical for identifying the factors governing their spread. We used Genotype-by-Sequencing data from previous population genomics studies for range-wide surveys of Wolbachia presence and genetic diversity in North American butterflies of the genus Lycaeides. As few as one sequence read identified by assembly to a Wolbachia reference genome provided high accuracy in detecting infections in host butterflies as determined by confirmatory PCR tests, and maximum accuracy was achieved with a threshold of only 5 sequence reads per host individual. Using this threshold, we detected Wolbachia in all but 2 of the 107 sampling localities spanning the continent, with infection frequencies within populations ranging from 0% to 100% of individuals, but with most localities having high infection frequencies (mean = 91% infection rate). Three major lineages of Wolbachia were identified as separate strains that appear to represent 3 separate invasions of Lycaeides butterflies by Wolbachia. Overall, we found extensive evidence for acquisition of Wolbachia through interspecific transfer between host lineages. Strain wLycC was confined to a single butterfly taxon, hybrid lineages derived from it, and closely adjacent populations in other taxa. While the other 2 strains were detected throughout the rest of the continent, strain wLycB almost always co-occurred with wLycA. Our demographic modeling suggests wLycB is a recent invasion. Within strain wLycA, the 2 most frequent haplotypes are confined almost exclusively to separate butterfly taxa with haplotype A1 observed largely in Lycaeides melissa and haplotype A2 observed most often in Lycaeides idas localities, consistent with either cladogenic mode of infection acquisition from a common ancestor or by hybridization and accompanying mutation. More than 1 major Wolbachia strain was observed in 15 localities. These results demonstrate the utility of using resequencing data from hosts to quantify Wolbachia genetic variation and infection frequency and provide evidence of multiple colonizations of novel hosts through hybridization between butterfly lineages and complex dynamics between Wolbachia strains.

     
    more » « less
  6. Abstract

    Endophytes are microbes that live, for at least a portion of their life history, within plant tissues. Endophyte assemblages are often composed of a few abundant taxa and many infrequently observed, low-biomass taxa that are, in a word, rare. The ways in which most endophytes affect host phenotype are unknown; however, certain dominant endophytes can influence plants in ecologically meaningful ways—including by affecting growth and immune system functioning. In contrast, the effects of rare endophytes on their hosts have been unexplored, including how rare endophytes might interact with abundant endophytes to shape plant phenotype. Here, we manipulate both the suite of rare foliar endophytes (including both fungi and bacteria) and Alternaria fulva–a vertically transmitted and usually abundant fungus–within the fabaceous forb Astragalus lentiginosus. We report that rare, low-biomass endophytes affected host size and foliar %N, but only when the heritable fungal endophyte (A. fulva) was not present. A. fulva also reduced plant size and %N, but these deleterious effects on the host could be offset by a negative association we observed between this heritable fungus and a foliar pathogen. These results demonstrate how interactions among endophytic taxa determine the net effects on host plants and suggest that the myriad rare endophytes within plant leaves may be more than a collection of uninfluential, commensal organisms, but instead have meaningful ecological roles.

     
    more » « less
  7. Abstract

    Genomic outcomes of hybridization depend on selection and recombination in hybrids. Whether these processes have similar effects on hybrid genome composition in contemporary hybrid zones versus ancient hybrid lineages is unknown. Here we show that patterns of introgression in a contemporary hybrid zone inLycaeidesbutterflies predict patterns of ancestry in geographically adjacent, older hybrid populations. We find a particularly striking lack of ancestry from one of the hybridizing taxa,Lycaeides melissa, on the Z chromosome in both the old and contemporary hybrids. The same pattern of reducedL. melissaancestry on the Z chromosome is seen in two other ancient hybrid lineages. More generally, we find that patterns of ancestry in old or ancient hybrids are remarkably predictable from contemporary hybrids, which suggests selection and recombination affect hybrid genomes in a similar way across disparate time scales and during distinct stages of speciation and species breakdown.

     
    more » « less
  8. Abstract

    Molecular ecology regularly requires the analysis of count data that reflect the relative abundance of features of a composition (e.g., taxa in a community, gene transcripts in a tissue). The sampling process that generates these data can be modelled using the multinomial distribution. Replicate multinomial samples inform the relative abundances of features in an underlying Dirichlet distribution. These distributions together form a hierarchical model for relative abundances among replicates and sampling groups. This type of Dirichlet‐multinomial modelling (DMM) has been described previously, but its benefits and limitations are largely untested. With simulated data, we quantified the ability of DMM to detect differences in proportions between treatment and control groups, and compared the efficacy of three computational methods to implement DMM—Hamiltonian Monte Carlo (HMC), variational inference (VI), and Gibbs Markov chain Monte Carlo. We report that DMM was better able to detect shifts in relative abundances than analogous analytical tools, while identifying an acceptably low number of false positives. Among methods for implementing DMM, HMC provided the most accurate estimates of relative abundances, and VI was the most computationally efficient. The sensitivity of DMM was exemplified through analysis of previously published data describing lung microbiomes. We report that DMM identified several potentially pathogenic, bacterial taxa as more abundant in the lungs of children who aspirated foreign material during swallowing; these differences went undetected with different statistical approaches. Our results suggest that DMM has strong potential as a statistical method to guide inference in molecular ecology.

     
    more » « less
  9. Abstract

    Non‐random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed‐ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, calledentropy, which can use low‐depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed‐ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade‐off between sequencing depth and genome coverage and found lower error associated with low‐depth sequencing across a larger fraction of the genome than with high‐depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploidArabidopsis arenosa.

     
    more » « less