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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. 

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.

 

Although our understanding of the microbial diversity found within a given system expands as amplicon sequencing improves, technical aspects still drastically affect which members can be detected. Compared with prokaryotic members, the eukaryotic microorganisms associated with a host are understudied due to their underrepresentation in ribosomal databases, lower abundance compared with bacterial sequences, and higher ribosomal gene identity to their eukaryotic host. Peptide nucleic acid (PNA) blockers are often designed to reduce amplification of host DNA. Here we present a tool for PNA design called the Microbiome Amplification Preference Tool (MAPT). We examine the effectiveness of a PNA designed to block genomic Medicago sativa DNA (gPNA) compared with unrelated surrounding plants from the same location. We applied mitochondrial PNA and plastid PNA to block the majority of DNA from plant mitochondria and plastid 16S ribosomal RNA genes, as well as the novel gPNA. Until now, amplifying both eukaryotic and prokaryotic reads using 515F-Y and 926R has not been applied to a host. We investigate the efficacy of this gPNA using three approaches: (i) in silico prediction of blocking potential in MAPT, (ii) amplicon sequencing with and without the addition of PNAs, and (iii) comparison with cultured fungal representatives. When gPNA is added during amplicon library preparation, the diversity of unique eukaryotic amplicon sequence variants present in M. sativa increases. We provide a layered examination of the costs and benefits of using PNAs during sequencing. The application of MAPT enables scientists to design PNAs specifically to enable capturing greater diversity in their system. 

To understand factors that influence the assembly of microbial communities, we inoculatedMedicago sativawith a series of nested bacterial synthetic communities and grew plants in distinct nitrogen concentrations. Two isolates in our eight‐member synthetic community,Williamsiasp. R60 andPantoeasp. R4, consistently dominate community structure across nitrogen regimes. WhilePantoeasp. R4 consistently colonizes plants to a higher degree compared to the other six organisms across each community and each nutrient level,Williamsiasp. R60 exhibits nutrient specific colonization differences.Williamsiasp. R60 is more abundant in plants grown at higher nitrogen concentrations, but exhibits the opposite trend when no plant is present, indicating plant‐driven influence over colonization. Our research discovered unique, repeatable colonization phenotypes for individual microbes during plant microbiome assembly, and identified alterations caused by the host plant, microbes, and available nutrients.