Methods developed over the past decade have made it possible to estimate molecular demographic parameters such as effective population size, divergence time, and gene flow with unprecedented accuracy and precision. However, they make simplifying assumptions about certain aspects of the species' histories and the nature of the genetic data, and it is not clear how robust they are to violations of these assumptions. Here, we use simulated data sets to examine the effects of a number of violations of the "Isolation with Migration" (IM) model, including intralocus recombination, population structure, gene flow from an unsampled species, linkage among loci, and divergent selection, on demographic parameter estimates made using the program IMA. We also examine the effect of having data that fit a nucleotide substitution model other than the two relatively simple models available in IMA. We find that IMA estimates are generally quite robust to small to moderate violations of the IM model assumptions, comparable with what is often encountered in real-world scenarios. In particular, population structure within species, a condition encountered to some degree in virtually all species, has little effect on parameter estimates even for fairly high levels of structure. Likewise, most parameter estimates are robust to significant levels of recombination when data sets are pared down to apparently nonrecombining blocks, although substantial bias is introduced to several estimates when the entire data set with recombination is included. In contrast, a poor fit to the nucleotide substitution model can result in an increased error rate, in some cases due to a predictable bias and in other cases due to an increase in variance in parameter estimates among data sets simulated under the same conditions.

Genome scans have become a common approach to identify genomic signatures of natural selection and reproductive isolation, as well as the genomic bases of ecologically relevant phenotypes, based on patterns of polymorphism and differentiation among populations or species. Here, we review the results of studies taking genome scan approaches in plants, consider the patterns of genomic differentiation documented and their possible causes, discuss the results in light of recent models of genomic differentiation during divergent adaptation and speciation, and consider assumptions and caveats in their interpretation. We find that genomic regions of high divergence generally appear quite small in comparisons of both closely and more distantly related populations, and for the most part, these differentiated regions are spread throughout the genome rather than strongly clustered. Thus, the genome scan approach appears well-suited for identifying genomic regions or even candidate genes that underlie adaptive divergence and/or reproductive barriers. We consider other methodologies that may be used in conjunction with genome scan approaches, and suggest further developments that would be valuable. These include broader use of sequence-based markers of known genomic location, greater attention to sampling strategies to make use of parallel environmental or phenotypic transitions, more integration with approaches such as quantitative trait loci mapping and measures of gene flow across the genome, and additional theoretical and simulation work on processes related to divergent adaptation and speciation.

The evolutionary significance of introgression has been discussed for decades. Questions about potential impacts of transgene flow into wild and weedy populations brought renewed attention to the introgression of crop alleles into those populations. In the past two decades, the field has advanced with considerable descriptive, experimental, and theoretical activity on the dynamics of crop gene introgression and its consequences. As illustrated by five case studies employing an array of different approaches, introgression of crop alleles has occurred for a wide array of species, sometimes without significant consequence, but on occasion leading to the evolution of increased weediness. A new theoretical context has emerged for analyzing empirical data, identifying factors that influence introgression, and predicting introgression's progress. With emerging molecular techniques and analyses, research on crop allele introgression into wild and weedy populations is positioned to make contributions to both transgene risk assessment and reticulate evolution.

Humans affect biodiversity at the genetic, species, community, and ecosystem levels. This impact on genetic diversity is critical, because genetic diversity is the raw material of evolutionary change, including adaptation and speciation. Two forces affecting genetic variation are genetic drift (which decreases genetic variation within but increases genetic differentiation among local populations) and gene flow (which increases variation within but decreases differentiation among local populations). Humans activities often augment drift and diminish gene flow for many species, which reduces genetic variation in local populations and prevents the spread of adaptive complexes outside their population of origin, thereby disrupting adaptive processes both locally and globally within a species. These impacts are illustrated with collared lizards (Crotaphytus collaris) in the Missouri Ozarks. Forest fire suppression has reduced habitat and disrupted gene flow in this lizard, thereby altering the balance toward drift and away from gene flow. This balance can be restored by managed landscape burns. Some have argued that, although human-induced fragmentation disrupts adaptation, it will also ultimately produce new species through founder effects. However, population genetic theory and experiments predict that most fragmentation events caused by human activities will facilitate not speciation, but local extinction. Founder events have played an important role in the macroevolution of certain groups, but only when ecological opportunities are expanding rather than contracting. The general impact of human activities on genetic diversity disrupts or diminishes the capacity for adaptation, speciation, and macroevolutionary change. This impact will ultimately diminish biodiversity at all levels.

Summary Gene duplication provides an important source of genetic raw material for phenotypic diversification [1, 2], but few studies have detailed the mechanisms through which duplications produce evolutionary novelty within species [3–6]. Here, we investigate how a set of recently duplicated homologs of the floral inducer FLOWERING LOCUS T (FT) has contributed to sunflower domestication. We find that changes in expression of these duplicates are associated with differences in flowering behavior between wild and domesticated sunflower. In addition, we present genetic and functional evidence demonstrating that a frameshift mutation in one paralog, Helianthus annuus FT 1 (HaFT1), underlies a major QTL for flowering time and experienced a selective sweep during early domestication. Notably, this dominant-negative allele delays flowering through interference with action of another paralog, HaFT4. Together, these data reveal that changes affecting the expression, sequence, and gene interactions of HaFT paralogs have played key roles during sunflower domestication. Our findings also illustrate the important role that evolving interactions between new gene family members may play in fostering phenotypic change.

Hybridization between distinct species may lead to introgression of genes across species boundaries, and this pattern can potentially persist for extended periods as long as selection at some loci or genomic regions prevents thorough mixing of gene pools. However, very few reliable estimates of long-term levels of effective migration are available between hybridizing species throughout their history. Accurate estimates of divergence dates and levels of gene flow require data from multiple unlinked loci as well as an analytical framework that can distinguish between lineage sorting and gene flow and incorporate the effects of demographic changes within each species. Here we use sequence data from 18 anonymous nuclear loci in two broadly sympatric sunflower species, Helianthus annuus and H. petiolaris, analyzed within an "isolation with migration" framework to make genome-wide estimates of the ages of these two species, long-term rates of gene flow between them, and effective population sizes and historical patterns of population growth. Our results indicate that H. annuus and H. petiolaris are approximately one million years old and have exchanged genes at a surprisingly high rate (long-term N(ef)m estimates of approximately 0.5 in each direction), with somewhat higher rates of introgression from H. annuus into H. petiolaris than vice versa. In addition, each species has undergone dramatic population expansion since divergence, and both species have among the highest levels of genetic diversity reported for flowering plants. Our results provide the most comprehensive estimate to date of long-term patterns of gene flow and historical demography in a nonmodel plant system, and they indicate that species integrity can be maintained even in the face of extensive gene flow over a prolonged period.

The role of adaptation in the divergence of lineages has long been a central question in evolutionary biology, and as multilocus sequence data sets have become available for a wide range of taxa, empirical estimates of levels of adaptive molecular evolution are increasingly common. Estimates vary widely among taxa, with high levels of adaptive evolution in Drosophila, bacteria, and viruses but very little evidence of widespread adaptive evolution in hominids. Although estimates in plants are more limited, some recent work has suggested that rates of adaptive evolution in a range of plant taxa are surprisingly low and that there is little association between adaptive evolution and effective population size in contrast to patterns seen in other taxa. Here, we analyze data from 35 loci for six sunflower species that vary dramatically in effective population size. We find that rates of adaptive evolution are positively correlated with effective population size in these species, with a significant fraction of amino acid substitutions driven by positive selection in the species with the largest effective population sizes but little or no evidence of adaptive evolution in species with smaller effective population sizes. Although other factors likely contribute as well, in sunflowers effective population size appears to be an important determinant of rates of adaptive evolution.

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