The quest for absolute abundance: The use of internal standards for DNA-based community ecology.

To characterize microbiomes and other ecological assemblages, ecologists routinely sequence and compare loci that differ among focal taxa. Counts of these sequences convey information regarding the occurrence and relative abundances of taxa, but provide no direct measure of their absolute abundances, due to the technical limitations of the sequencing process. The relative abundances in compositional data are inherently constrained and difficult to interpret. The incorporation of internal standards (ISDs; colloquially referred to as 'spike-ins') into DNA pools can ameliorate the problems posed by relative abundance data and allow absolute abundances to be approximated. Unfortunately, many laboratory and sampling biases cause ISDs to underperform or fail. Here, we discuss how careful deployment of ISDs can avoid these complications and be an integral component of well-designed studies seeking to characterize ecological assemblages via sequencing of DNA.

Geographically multifarious phenotypic divergence during speciation.

Speciation is an important evolutionary process that occurs when barriers to gene flow evolve between previously panmictic populations. Although individual barriers to gene flow have been studied extensively, we know relatively little regarding the number of barriers that isolate species or whether these barriers are polymorphic within species. Herein, we use a series of field and lab experiments to quantify phenotypic divergence and identify possible barriers to gene flow between the butterfly species Lycaeides idas and Lycaeides melissa. We found evidence that L. idas and L. melissa have diverged along multiple phenotypic axes. Specifically, we identified major phenotypic differences in female oviposition preference and diapause initiation, and more moderate divergence in mate preference. Multiple phenotypic differences might operate as barriers to gene flow, as shown by correlations between genetic distance and phenotypic divergence and patterns of phenotypic variation in admixed Lycaeides populations. Although some of these traits differed primarily between species (e.g., diapause initiation), several traits also varied among conspecific populations (e.g., male mate preference and oviposition preference).

Specificity, rank preference, and the colonization of a non-native host plant by the Melissa blue butterfly.

Animals often express behavioral preferences for different types of food or other resources, and these preferences can evolve or shift following association with novel food types. Shifts in preference can involve at least two phenomena: a change in rank preference or a change in specificity. The former corresponds to a change in the order in which hosts are preferred, while a shift in specificity can be an increase in the tendency to utilize multiple hosts. These possibilities have been examined in relatively few systems that include extensive population-level replication. The Melissa blue butterfly, Lycaeides melissa, has colonized exotic alfalfa, Medicago sativa, throughout western North America. We assayed the host preferences of 229 females from ten populations associated with novel and native hosts. In four out of five native-associated populations, a native host was preferred over the exotic host, while preference for a native host characterized only two out of five of the alfalfa-associated populations. Across all individuals from alfalfa-associated populations, there appears to have been a decrease in specificity: females from these populations lay fewer eggs on the native host and more eggs on the exotic relative to females from native-host populations. However, females from alfalfa-associated populations did not lay more eggs on a third plant species, which suggests that preferences for specific hosts in this system can potentially be gained and lost independently. Geographic variation in oviposition preference in L. melissa highlights the value of surveying a large number of populations when studying the evolution of a complex behavioral trait.

Population genomics based on low coverage sequencing: how low should we go?

Research in molecular ecology is now often based on large numbers of DNA sequence reads. Given a time and financial budget for DNA sequencing, the question arises as to how to allocate the finite number of sequence reads among three dimensions: (i) sequencing individual nucleotide positions repeatedly and achieving high confidence in the true genotype of individuals, (ii) sampling larger numbers of individuals from a population, and (iii) sampling a larger fraction of the genome. Leaving aside the question of what fraction of the genome to sample, we analyze the trade-off between repeatedly sequencing the same nucleotide position (coverage depth) and the number of individuals in the sample. We review simple Bayesian models for allele frequencies and utilize these in the analysis of how to obtain maximal information about population genetic parameters. The models indicate that sampling larger numbers of individuals, at the expense of coverage depth per nucleotide position, provides more information about population parameters. Dividing the sequencing effort maximally among individuals and obtaining approximately one read per locus and individual (1 × coverage) yields the most information about a population. Some analyses require genetic parameters for individuals, in which case Bayesian population models also support inference from lower coverage sequence data than are required for simple likelihood models. Low coverage sequencing is not only sufficient to support inference, but it is optimal to design studies to utilize low coverage because they will yield highly accurate and precise parameter estimates based on more individuals or sites in the genome.

introgress: a software package for mapping components of isolation in hybrids.

A new software package (introgress) provides functions for analysing introgression of genotypes between divergent, hybridizing lineages, including estimating genomic clines from multi-locus genotype data and testing for deviations from neutral expectations. The software works with co-dominant, dominant and haploid marker data, and does not require fixed allelic differences between parental populations for the sampled genetic markers. Permutation and parametric procedures generate neutral expectations for introgression and provide a basis for significance tests of observed genomic clines. The software also implements maximum likelihood estimates of hybrid index from genotypic data and a number of graphical analyses. The package is an extension of the R statistical software, is written in the R language and is freely available through the Comprehensive R Archive Network (CRAN; http://cran.r-project.org/). In this study, we describe introgress and demonstrate its use with a sample data set.