Genomic diversity,population structure,and migration following rapid range expansion in the Balsam Poplar,Populus balsamifera

Rapid range expansions can cause pervasive changes in the genetic diversity and structure of populations. The postglacial history of the Balsam Poplar, Populus balsamifera, involved the colonization of most of northern North America, an area largely covered by continental ice sheets during the last glacial maximum. To characterize how this expansion shaped genomic diversity within and among populations, we developed 412 SNP markers that we assayed for a range‐wide sample of 474 individuals sampled from 34 populations. We complemented the SNP data set with DNA sequence data from 11 nuclear loci from 94 individuals, and used coalescent analyses to estimate historical population size, demographic growth, and patterns of migration. Bayesian clustering identified three geographically separated demes found in the Northern, Central, and Eastern portions of the species’ range. These demes varied significantly in nucleotide diversity, the abundance of private polymorphisms, and population substructure. Most measures supported the Central deme as descended from the primary refuge of diversity. Both SNPs and sequence data suggested recent population growth, and coalescent analyses of historical migration suggested a massive expansion from the Centre to the North and East. Collectively, these data demonstrate the strong influence that range expansions exert on genomic diversity, both within local populations and across the range. Our results suggest that an in‐depth knowledge of nucleotide diversity following expansion requires sampling within multiple populations, and highlight the utility of combining insights from different data types in population genomic studies.     

Population structure and local selection yield high genomic variation in Mimulus guttatus

Across western North America, Mimulus guttatus exists as many local populations adapted to site‐specific environmental challenges. Gene flow between locally adapted populations will affect genetic diversity both within demes and across the larger metapopulation. Here, we analyse 34 whole‐genome sequences from the intensively studied Iron Mountain population (IM) in conjunction with sequences from 22 Mimulus individuals sampled from across western North America. Three striking features of these data address hypotheses about migration and selection in a locally adapted population. First, we find very high levels of intrapopulation polymorphism (synonymous π = 0.033). Variation outside of genes is likely even higher but difficult to estimate because excessive divergence reduces the efficiency of read mapping. Second, IM exhibits a significantly positive genomewide average for Tajima's D. This indicates allele frequencies are typically more intermediate than expected from neutrality, opposite the pattern observed in many other species. Third, IM exhibits a distinctive haplotype structure with a genomewide excess of positive associations between rarer alleles at linked loci. This suggests an important effect of gene flow from other Mimulus populations, although a residual effect of population founding might also contribute. The combination of multiple analyses, including a novel tree‐based analytic method, illustrates how the balance of local selection, limited dispersal and metapopulation dynamics manifests across the genome. The overall genomic pattern of sequence diversity suggests successful gene flow of divergent immigrant genotypes into IM. However, many loci show patterns indicative of local adaptation, particularly at SNPs associated with chromosomal inversions.     

Multilocus selection in subdivided populations II. Maintenance of polymorphism under weak or strong migration

The potential of maintaining multilocus polymorphism by migration-selection balance is studied. A large population of diploid individuals is distributed over finitely many demes connected by migration. Generations are discrete and nonoverlapping, selection may vary across demes, and loci are multiallelic. It is shown that if migration and recombination are strong relative to selection, then with weak or no epistasis and intermediate dominance at every locus and in every deme, arbitrarily many alleles can be maintained at arbitrarily many loci at a stable equilibrium. If migration is weak relative to selection and recombination, then with weak or no epistasis and intermediate dominance at every locus and in every deme, as many alleles as there are demes can be maintained at arbitrarily many loci at equilibrium. In both cases open sets of such parameter combinations are constructed, thus the results are robust with respect to small, but arbitrary, perturbations in the parameters. For weak migration, the number of demes is, in fact, a generic upper bound to the number of alleles that can be maintained at any locus. Thus, several scenarios are identified under which multilocus polymorphism can be maintained by migration-selection balance when this is impossible in a panmictic population.      

MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity

Background  

MTML-msBayes uses hierarchical approximate Bayesian computation (HABC) under a coalescent model to infer temporal patterns of divergence and gene flow across codistributed taxon-pairs. Under a model of multiple codistributed taxa that diverge into taxon-pairs with subsequent gene flow or isolation, one can estimate hyper-parameters that quantify the mean and variability in divergence times or test models of migration and isolation. The software uses multi-locus DNA sequence data collected from multiple taxon-pairs and allows variation across taxa in demographic parameters as well as heterogeneity in DNA mutation rates across loci. The method also allows a flexible sampling scheme: different numbers of loci of varying length can be sampled from different taxon-pairs.     

Retrospective coalescent methods and the reconstruction of metapopulation histories in the sea

Phylogeographic analyses are a key interface between ecological and evolutionary ways of knowing because such analyses integrate the cumulative effects of demographic (ecological) processes over geological (evolutionary) time scales. Newly developed coalescent methods allow evolutionary ecologists to overcome some limitations associated with inferring population history from classic methods such as Wright’s F _ST. Here we briefly contrast classic and coalescent methods for looking backward in time through a population genetic lens, focusing on the key advantages of the isolation-with-migration (IM) class of coalescent methods for distinguishing ancient connectedness from actual recurrent contemporary gene flow as causes of genetic similarity or differentiation among populations. Making this critical distinction can lead to the discovery of otherwise obscured histories underlying conventional patterns of spatial variation. We illustrate the importance of these insights using analyses of Pacific fishes, snails, and sea stars in which population sizes and divergence times are more important than rates of contemporary gene flow as determinants of population genetic differentiation. We then extend the IM method to genetic data from two model metapopulation species (California abalone, Australian damselfish). The analyses show the potential use of non-equilibrium IM methods for differentiating among metapopulation models that make different predictions about population parameters and have different implications for the design of marine protected areas and other conservation goals. At face value, the results largely rule out classic metapopulation dynamics (dominated by extinction and colonization rather than connectivity via ongoing recurrent gene flow) but, at the same time, do not strongly support a modern marine metapopulation dynamic (ecologically significant connectivity between demes). However, the results also highlight the need for much more data (i.e., loci) sampled on different spatial scales in order to determine whether metapopulation dynamics might exist on smaller scales than are typically sampled by most phylogeographers and landscape geneticists.     

Efficient Strategies for Calculating Blockwise Likelihoods Under the Coalescent

The inference of demographic history from genome data is hindered by a lack of efficient computational approaches. In particular, it has proved difficult to exploit the information contained in the distribution of genealogies across the genome. We have previously shown that the generating function (GF) of genealogies can be used to analytically compute likelihoods of demographic models from configurations of mutations in short sequence blocks (Lohse et al. 2011). Although the GF has a simple, recursive form, the size of such likelihood calculations explodes quickly with the number of individuals and applications of this framework have so far been mainly limited to small samples (pairs and triplets) for which the GF can be written by hand. Here we investigate several strategies for exploiting the inherent symmetries of the coalescent. In particular, we show that the GF of genealogies can be decomposed into a set of equivalence classes that allows likelihood calculations from nontrivial samples. Using this strategy, we automated blockwise likelihood calculations for a general set of demographic scenarios in Mathematica. These histories may involve population size changes, continuous migration, discrete divergence, and admixture between multiple populations. To give a concrete example, we calculate the likelihood for a model of isolation with migration (IM), assuming two diploid samples without phase and outgroup information. We demonstrate the new inference scheme with an analysis of two individual butterfly genomes from the sister species Heliconius melpomene rosina and H. cydno.     

High-resolution copy-number variation map reflects human olfactory receptor diversity and evolution

Olfactory receptors (ORs), which are involved in odorant recognition, form the largest mammalian protein superfamily. The genomic content of OR genes is considerably reduced in humans, as reflected by the relatively small repertoire size and the high fraction ( approximately 55%) of human pseudogenes. Since several recent low-resolution surveys suggested that OR genomic loci are frequently affected by copy-number variants (CNVs), we hypothesized that CNVs may play an important role in the evolution of the human olfactory repertoire. We used high-resolution oligonucleotide tiling microarrays to detect CNVs across 851 OR gene and pseudogene loci. Examining genomic DNA from 25 individuals with ancestry from three populations, we identified 93 OR gene loci and 151 pseudogene loci affected by CNVs, generating a mosaic of OR dosages across persons. Our data suggest that approximately 50% of the CNVs involve more than one OR, with the largest CNV spanning 11 loci. In contrast to earlier reports, we observe that CNVs are more frequent among OR pseudogenes than among intact genes, presumably due to both selective constraints and CNV formation biases. Furthermore, our results show an enrichment of CNVs among ORs with a close human paralog or lacking a one-to-one ortholog in chimpanzee. Interestingly, among the latter we observed an enrichment in CNV losses over gains, a finding potentially related to the known diminution of the human OR repertoire. Quantitative PCR experiments performed for 122 sampled ORs agreed well with the microarray results and uncovered 23 additional CNVs. Importantly, these experiments allowed us to uncover nine common deletion alleles that affect 15 OR genes and five pseudogenes. Comparison to the chimpanzee reference genome revealed that all of the deletion alleles are human derived, therefore indicating a profound effect of human-specific deletions on the individual OR gene content. Furthermore, these deletion alleles may be used in future genetic association studies of olfactory inter-individual differences.     

Multilocus selection in subdivided populations I. Convergence properties for weak or strong migration

The dynamics and equilibrium structure of a deterministic population-genetic model of migration and selection acting on multiple multiallelic loci is studied. A large population of diploid individuals is distributed over finitely many demes connected by migration. Generations are discrete and nonoverlapping, migration is irreducible and aperiodic, all pairwise recombination rates are positive, and selection may vary across demes. It is proved that, in the absence of selection, all trajectories converge at a geometric rate to a manifold on which global linkage equilibrium holds and allele frequencies are identical across demes. Various limiting cases are derived in which one or more of the three evolutionary forces, selection, migration, and recombination, are weak relative to the others. Two are particularly interesting. If migration and recombination are strong relative to selection, the dynamics can be conceived as a perturbation of the so-called weak-selection limit, a simple dynamical system for suitably averaged allele frequencies. Under nondegeneracy assumptions on this weak-selection limit which are generic, every equilibrium of the full dynamics is a perturbation of an equilibrium of the weak-selection limit and has the same stability properties. The number of equilibria is the same in both systems, equilibria in the full (perturbed) system are in quasi-linkage equilibrium, and differences among allele frequencies across demes are small. If migration is weak relative to recombination and epistasis is also weak, then every equilibrium is a perturbation of an equilibrium of the corresponding system without migration, has the same stability properties, and is in quasi-linkage equilibrium. In both cases, every trajectory converges to an equilibrium, thus no cycling or complicated dynamics can occur.      

Extracting ‘legacy loci’ from an invertebrate sequence capture data set

Sequence capture studies result in rich data sets comprising hundreds to thousands of targeted genomic regions that are superseding Sanger-based data sets comprised of a few well-known loci with historical uses in phylogenetics (‘legacy loci’). However, integrating sequence capture and Sanger-based data sets is of interest as legacy loci can include different types of loci (e.g. mitochondrial and nuclear) across a potentially larger sample of species from past studies. Sequence capture data sets include nontargeted sequences, and there has been recent interest in extracting legacy loci from invertebrate data sets. Here, we use published legacy data from leaf-footed bugs (Hemiptera: Coreoidea) to recover 15 mitochondrial and seven nuclear legacy loci from off-target sequences in a sequence capture data set, explore approaches to improve legacy locus recovery, and combine these loci with sequence capture data for phylogenetic analysis. Two nuclear loci were determined to already be targeted by sequence capture baits. Most of the remaining loci were successfully recovered from off-target sequences, but this recovery varied greatly. Additionally, complementing complete mitogenomes with additional reference mitochondrial sequences from a genetic depository did not offer improvement for most of our taxa; however, supplementing these reference sequences with extracted legacy loci offered ≥6% improvement across taxa for a given mitochondrial locus (negligible improvement for nuclear loci). Phylogenetic analysis of legacy and sequence capture data produced a topology generally congruent with recent studies, but support was lower. Thus, future studies may employ the approaches used in this study to integrate legacy data with newly generated sequence capture data sets without added expenses.     

Evolution and polymorphism in the multilocus Levene model with no or weak epistasis

Evolution and the maintenance of polymorphism under the multilocus Levene model with soft selection are studied. The number of loci and alleles, the number of demes, the linkage map, and the degree of dominance are arbitrary, but epistasis is absent or weak. We prove that, without epistasis and under mild, generic conditions, every trajectory converges to a stationary point in linkage equilibrium. Consequently, the equilibrium and stability structure can be determined by investigating the much simpler gene-frequency dynamics on the linkage-equilibrium manifold. For a haploid species an analogous result is shown. For weak epistasis, global convergence to quasi-linkage equilibrium is established. As an application, the maintenance of multilocus polymorphism is explored if the degree of dominance is intermediate at every locus and epistasis is absent or weak. If there are at least two demes, then arbitrarily many multiallelic loci can be maintained polymorphic at a globally asymptotically stable equilibrium. Because this holds for an open set of parameters, such equilibria are structurally stable. If the degree of dominance is not only intermediate but also deme independent, and loci are diallelic, an open set of parameters yielding an internal equilibrium exists only if the number of loci is strictly less than the number of demes. Otherwise, a fully polymorphic equilibrium exists only nongenerically, and if it exists, it consists of a manifold of equilibria. Its dimension is determined. In the absence of genotype-by-environment interaction, however, a manifold of equilibria occurs for an open set of parameters. In this case, the equilibrium structure is not robust to small deviations from no genotype-by-environment interaction. In a quantitative-genetic setting, the assumptions of no epistasis and intermediate dominance are equivalent to assuming that in every deme directional selection acts on a trait that is determined additively, i.e., by nonepistatic loci with dominance. Some of our results are exemplified in this quantitative-genetic context.     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.     

Genome-wide association genetics of an adaptive trait in lodgepole pine

Pine cones that remain closed and retain seeds until fire causes the cones to open (cone serotiny) represent a key adaptive trait in a variety of pine species. In lodgepole pine, there is substantial geographical variation in serotiny across the Rocky Mountain region. This variation in serotiny has evolved as a result of geographically divergent selection, with consequences that extend to forest communities and ecosystems. An understanding of the genetic architecture of this trait is of interest owing to the wide-reaching ecological consequences of serotiny and also because of the repeated evolution of the trait across the genus. Here, we present and utilize an inexpensive and time-effective method for generating population genomic data. The method uses restriction enzymes and PCR amplification to generate a library of fragments that can be sequenced with a high level of multiplexing. We obtained data for more than 95,000 single nucleotide polymorphisms across 98 serotinous and nonserotinous lodgepole pines from three populations. We used a Bayesian generalized linear model (GLM) to test for an association between genotypic variation at these loci and serotiny. The probability of serotiny varied by genotype at 11 loci, and the association between genotype and serotiny at these loci was consistent in each of the three populations of pines. Genetic variation across these 11 loci explained 50% of the phenotypic variation in serotiny. Our results provide a first genome-wide association map of serotiny in pines and demonstrate an inexpensive and efficient method for generating population genomic data.     

Proceedings of the SMBE Tri-National Young Investigators' Workshop 2005. Coalescent-based estimation of population parameters when the number of demes changes over time

We expand a coalescent-based method that uses serially sampled genetic data from a subdivided population to incorporate changes to the number of demes and patterns of colonization. Often, when estimating population parameters or other parameters of interest from genetic data, the demographic structure and parameters are not constant over evolutionary time. In this paper, we develop a Bayesian Markov chain Monte Carlo method that allows for step changes in mutation, migration, and population sizes, as well as changing numbers of demes, where the times of these changes are also estimated. We show that in parameter ranges of interest, reliable estimates can often be obtained, including the historical times of parameter changes. However, posterior densities of migration rates can be quite diffuse and estimators somewhat biased, as reported by other authors.     

Parentage in natural populations: novel methods to detect parent-offspring pairs in large data sets

Parentage analysis in natural populations presents a valuable yet unique challenge because of large numbers of pairwise comparisons, marker set limitations and few sampled true parent-offspring pairs. These limitations can result in the incorrect assignment of false parent-offspring pairs that share alleles across multi-locus genotypes by chance alone. I first define a probability, Pr(δ), to estimate the expected number of false parent-offspring pairs within a data set. This probability can be used to determine whether one can accept all putative parent-offspring pairs with strict exclusion. I next define the probability Pr(φ|λ), which employs Bayes' theorem to determine the probability of a putative parent-offspring pair being false given the frequencies of shared alleles. This probability can be used to separate true parent-offspring pairs from false pairs that occur by chance when a data set lacks sufficient numbers of loci to accept all putative parent-offspring pairs. Finally, I propose a method to quantitatively determine how many loci to let mismatch for study-specific error rates and demonstrate that few data sets should need to allow more than two loci to mismatch. I test all theoretical predictions with simulated data and find that, first, Pr(δ) and Pr(φ|λ) have very low bias, and second, that power increases with lower sample sizes, uniform allele frequency distributions, and higher numbers of loci and alleles per locus. Comparisons of Pr(φ|λ) to strict exclusion and CERVUS demonstrate that this method may be most appropriate for large natural populations when supplemental data (e.g. genealogies, candidate parents) are absent.     

A performance study of the impact of recombination on species tree analysis

Background

The most widely used state-of-the-art methods for reconstructing species phylogenies from genomic sequence data assume that sampled loci are identically and independently distributed. In principle, free recombination between loci and a lack of intra-locus recombination are necessary to satisfy this assumption. Few studies have quantified the practical impact of recombination on species tree inference methods, and even fewer have used genomic sequence data for this purpose. One prominent exception is the 2012 study of Lanier and Knowles. A main finding from the study was that species tree inference methods are relatively robust to intra-locus recombination, assuming free recombination between loci. The latter assumption means that the open question regarding the impact of recombination on species tree analysis is not fully resolved.

Results

The goal of this study is to further investigate this open question. Using simulations based upon the multi-species coalescent-with-recombination model as well as empirical datasets, we compared common pipeline-based techniques for inferring species phylogenies. The simulation conditions included a range of dataset sizes and several choices for recombination rate which was either uniform across loci or incorporated recombination hotspots. We found that pipelines which explicitly utilize inferred recombination breakpoints to delineate recombination-free intervals result in greater accuracy compared to widely used alternatives that preprocess sequences based upon linkage disequilibrium decay. Furthermore, the use of a relatively simple approach for recombination breakpoint inference does not degrade the accuracy of downstream species tree inference compared to more accurate alternatives.

Conclusions

Our findings clarify the impact of recombination upon current phylogenomic pipelines for species tree inference. Pipeline-based approaches which utilize inferred recombination breakpoints to densely sample loci across genomic sequences can tolerate intra-locus recombination and violations of the assumption of free recombination between loci.

     

Spatial heterogeneity in the strength of selection against deleterious alleles and the mutation load

According to current estimates of genomic deleterious mutation rates (which are often of the order 0.1-1) the mutation load (defined as a reduction in the average fitness of a population due to the presence of deleterious alleles) may be important in many populations. In this paper, I use multilocus simulations to explore the effect of spatial heterogeneity in the strength of selection against deleterious alleles on the mutation load (for example, it has been suggested that stressful environments may increase the strength of selection). These simulations show contrasted results: in some situations, spatial heterogeneity may greatly reduce the mutation load, due to the fact that migrants coming from demes under stronger selection carry relatively few deleterious alleles, and benefit from a strong advantage within demes under weaker selection (where individuals carry many more deleterious alleles); in other situations, however, deleterious alleles accumulate within demes under stronger selection, due to migration pressure from demes under weaker selection, leading to fitness erosion within those demes. This second situation is more frequent when the productivity of the different demes is proportional to their mean fitness. The effect of spatial heterogeneity is greatly reduced, however, when the response to environmental differences is inconsistent across loci.     

Maximum Likelihood Implementation of an Isolation-with-Migration Model with Three Species for Testing Speciation with Gene Flow

We implement an isolation with migration model for three species, with migration occurring between two closely related species while an out-group species is used to provide further information concerning gene trees and model parameters. The model is implemented in the likelihood framework for analyzing multilocus genomic sequence alignments, with one sequence sampled from each of the three species. The prior distribution of gene tree topology and branch lengths at every locus is calculated using a Markov chain characterization of the genealogical process of coalescent and migration, which integrates over the histories of migration events analytically. The likelihood function is calculated by integrating over branch lengths in the gene trees (coalescent times) numerically. We analyze the model to study the gene tree-species tree mismatch probability and the time to the most recent common ancestor at a locus. The model is used to construct a likelihood ratio test (LRT) of speciation with gene flow. We conduct computer simulations to evaluate the LRT and found that the test is in general conservative, with the false positive rate well below the significance level. For the test to have substantial power, hundreds of loci are needed. Application of the test to a human-chimpanzee-gorilla genomic data set suggests gene flow around the time of speciation of the human and the chimpanzee.     

Genomic insights into the vulnerability of sympatric whitefish species flocks

The erosion of habitat heterogeneity can reduce species diversity directly but can also lead to the loss of distinctiveness of sympatric species through speciation reversal. We know little about changes in genomic differentiation during the early stages of these processes, which can be mediated by anthropogenic perturbation. Here, we analyse three sympatric whitefish species (Coregonus spp) sampled across two neighbouring and connected Swiss pre‐alpine lakes, which have been differentially affected by anthropogenic eutrophication. Our data set comprises 16,173 loci genotyped across 138 whitefish using restriction‐site associated DNA sequencing (RADseq). Our analysis suggests that in each of the two lakes, the population of a different, but ecologically similar, whitefish species declined following a recent period of eutrophication. Genomic signatures consistent with hybridization are more pronounced in the more severely impacted lake. Comparisons between sympatric pairs of whitefish species with contrasting ecology, where one is shallow benthic and the other one more profundal pelagic, reveal genomic differentiation that is largely correlated along the genome, while differentiation is uncorrelated between pairs of allopatric provenance with similar ecology. We identify four genomic loci that provide evidence of parallel divergent adaptation between the shallow benthic species and the two different more profundal species. Functional annotations available for two of those loci are consistent with divergent ecological adaptation. Our genomic analysis indicates the action of divergent natural selection between sympatric whitefish species in pre‐alpine lakes and reveals the vulnerability of these species to anthropogenic alterations of the environment and associated adaptive landscape.     

Detecting Isolation by Distance Using Phylogenies of Genes

We introduce a method for analyzing phylogenies of genes sampled from a geographically structured population. A parsimony method can be used to compute s, the minimum number of migration events between pairs of populations sampled, and the value of s can be used to estimate the effective migration rate M, the value of Nm in an island model with local populations of size N and a migration rate m that would yield the same value of s. Extensive simulations show that there is a simple relationship between M and the geographic distance between pairs of samples in one- and two-dimensional models of isolation by distance. Both stepping-stone and lattice models were simulated. If two demes k steps apart are sampled, then, s, the average value of s, is a function only of k/(Nm) in a one-dimensional model and is a function only of k/(Nm)2 in a two-dimensional model. Furthermore, log(M) is approximately a linear function of log(k). In a one-dimensional model, the regression coefficient is approximately -1 and in a two-dimensional model the regression coefficient is approximately -0.5. Using data from several locations, the regression of log(M) on log(distance) may indicate whether there is isolation by distance in a population at equilibrium and may allow an estimate of the effective migration rate between adjacent sampling locations. Alternative methods for analyzing DNA sequence data from a geographically structured population are discussed. An application of our method to the data of R. L. Cann, M. Stoneking and A. C. Wilson on human mitochondrial DNA is presented.     

Microfluidic droplet enrichment for targeted sequencing

Targeted sequence enrichment enables better identification of genetic variation by providing increased sequencing coverage for genomic regions of interest. Here, we report the development of a new target enrichment technology that is highly differentiated from other approaches currently in use. Our method, MESA (Microfluidic droplet Enrichment for Sequence Analysis), isolates genomic DNA fragments in microfluidic droplets and performs TaqMan PCR reactions to identify droplets containing a desired target sequence. The TaqMan positive droplets are subsequently recovered via dielectrophoretic sorting, and the TaqMan amplicons are removed enzymatically prior to sequencing. We demonstrated the utility of this approach by generating an average 31.6-fold sequence enrichment across 250 kb of targeted genomic DNA from five unique genomic loci. Significantly, this enrichment enabled a more comprehensive identification of genetic polymorphisms within the targeted loci. MESA requires low amounts of input DNA, minimal prior locus sequence information and enriches the target region without PCR bias or artifacts. These features make it well suited for the study of genetic variation in a number of research and diagnostic applications.