C. Alex Buerkle

Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery

BackgroundMassively parallel sequencing of cDNA is now an efficient route for generating enormous sequence collections that represent expressed genes. This approach provides a valuable starting point for characterizing functional genetic variation in non-model organisms, especially where whole genome sequencing efforts are currently cost and time prohibitive. The large and complex genomes of pines (Pinus spp.) have hindered the development of genomic resources, despite the ecological and economical importance of the group. While most genomic studies have focused on a single species (P. taeda), genomic level resources for other pines are insufficiently developed to facilitate ecological genomic research. Lodgepole pine (P. contorta) is an ecologically important foundation species of montane forest ecosystems and exhibits substantial adaptive variation across its range in western North America. Here we describe a sequencing study of expressed genes from P. contorta, including their assembly and annotation, and their potential for molecular marker development to support population and association genetic studies.ResultsWe obtained 586,732 sequencing reads from a 454 GS XLR70 Titanium pyrosequencer (mean length: 306 base pairs). A combination of reference-based and de novo assemblies yielded 63,657 contigs, with 239,793 reads remaining as singletons. Based on sequence similarity with known proteins, these sequences represent approximately 17,000 unique genes, many of which are well covered by contig sequences. This sequence collection also included a surprisingly large number of retrotransposon sequences, suggesting that they are highly transcriptionally active in the tissues we sampled. We located and characterized thousands of simple sequence repeats and single nucleotide polymorphisms as potential molecular markers in our assembled and annotated sequences. High quality PCR primers were designed for a substantial number of the SSR loci, and a large number of these were amplified successfully in initial screening.ConclusionsThis sequence collection represents a major genomic resource for P. contorta, and the large number of genetic markers characterized should contribute to future research in this and other pines. Our results illustrate the utility of next generation sequencing as a basis for marker development and population genomics in non-model species.

Genotyping‐by‐sequencing in ecological and conservation genomics

The fields of ecological and conservation genetics have developed greatly in recent decades through the use of molecular markers to investigate organisms in their natural habitat and to evaluate the effect of anthropogenic disturbances. However, many of these studies have been limited to narrow regions of the genome, allowing for limited inferences but making it difficult to generalize about the organisms and their evolutionary history. Tremendous advances in sequencing technology over the last decade (i.e. next-generation sequencing; NGS) have led to the ability to sample the genome much more densely and to observe the patterns of genetic variation that result from the full range of evolutionary processes acting across the genome (Allendorf et al. 2010; Stapley et al. 2010; Li et al. 2012). These studies are transforming molecular ecology by making many long-standing questions much more easily accessible in almost any organism. When studying the genetics of wild populations, it is desirable to samples tens, hundreds or even thousands of individuals. While it is now possible to sequence whole genomes for tens of individuals with small genome sizes, the sequencing of hundreds of individuals with large genomes remains prohibitively expensive, particularly where the genome sequence is unknown. Further, for the purpose of many studies, complete genomic sequence data for all individuals would be unnecessary and simply inflate the computational and bioinformatic costs. A major recent advance has been the development of genotyping-by-sequencing (GBS) approaches that allow a targeted fraction of the genome (a reduced representation library) to be sequenced with next-generation technology rather than the entire genome, even in species with little or no previous genomic information and large genomes. The subset of the genome to be sequenced in these GBS approaches may be targeted using restriction enzymes or capture probes or by sequencing the transcriptome (reviewed in Davey et al. 2011). In the future, as sequencing technology and computational and bioinformatic methods develop further, whole-genome resequencing may become the predominant method for ecological and conservation genomics. Currently, reduced representation approaches offer the ability to not only discover genetic variants such as SNPs but also genotype individuals at these newly discovered loci in the same data. This special issue on ‘Genotyping-by-Sequencing in Ecological and Conservation Genomics’ represents a diverse set of empirical and theoretical studies that demonstrate both the utility and some of the challenges of GBS in ecological and conservation genomics. The empirical studies include demonstrations of the utility of GBS for population genomics and association mapping, as well as the development of genomic resources (i.e. large SNP data sets) for target species. The studies also illustrate some of the differences between GBS methods, in particular, aligning paired-end reads to achieve longer consensus sequences in contrast to single-end reads with shorter alignments, and double-digest versus sonication methods to fragment DNA. In addition, several papers describe advanced data pipelines for handling GBS-related sequence data and critically evaluate best practices for GBS methods and potential biases and novel features associated with GBS data. Overall, this compilation of papers emphasizes that GBS has been quickly adopted by the scientific community and is expected to become a common tool for studies in molecular ecology.

Stick insect genomes reveal natural selection's role in parallel speciation.

Stick to the Bush Can the underlying genetic changes driving the divergence of populations into new species be predicted or repeated? Soria-Carrasco et al. (p. 738) investigated the genetic changes observed after one generation when stick insect (Timema cristinae) populations were transplanted from their preferred host plants to alternative hosts. Diverged genetic regions were relatively small, with most loci showing divergence in a single population pair. However, the number of loci showing parallel divergence was greater than expected by chance. Thus, selection can drive parallel phenotypic evolution via parallel genetic changes. Parallel speciation in insects shows both convergent and divergent selection after one generation. Natural selection can drive the repeated evolution of reproductive isolation, but the genomic basis of parallel speciation remains poorly understood. We analyzed whole-genome divergence between replicate pairs of stick insect populations that are adapted to different host plants and undergoing parallel speciation. We found thousands of modest-sized genomic regions of accentuated divergence between populations, most of which are unique to individual population pairs. We also detected parallel genomic divergence across population pairs involving an excess of coding genes with specific molecular functions. Regions of parallel genomic divergence in nature exhibited exceptional allele frequency changes between hosts in a field transplant experiment. The results advance understanding of biological diversification by providing convergent observational and experimental evidence for selection’s role in driving repeatable genomic divergence.

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.

A powerful regression‐based method for admixture mapping of isolation across the genome of hybrids

We propose a novel method that uses natural admixture between divergent lineages (hybridization) to investigate the genetic architecture of reproductive isolation and adaptive introgression. Our method employs multinomial regression to estimate genomic clines and to quantify introgression for individual loci relative to the genomic background (clines in genotype frequency along a genomic admixture gradient). Loci with patterns of introgression that deviate significantly from null expectations based on the remainder of the genome are potentially subject to selection and thus of interest to understanding adaptation and the evolution of reproductive isolation. Using simulations, we show that different forms of selection modify these genomic clines in predictable ways and that our method has good power to detect moderate to strong selection for multiple forms of selection. Using individual‐based simulations, we demonstrate that our method generally has a low false positive rate, except when genetic drift is particularly pronounced (e.g. low population size, low migration rates from parental populations, and substantial time since initial admixture). Additional individual‐based simulations reveal that moderate selection against heterozygotes can be detected as much as 50 cm away from the focal locus directly experiencing selection, but is not detected at unlinked loci. Finally, we apply our analytical method to previously published data sets from a mouse (Mus musculus and M. domesticus) and two sunflower (Helianthus petiolaris and H. annuus) hybrid zones. This method should be applicable to numerous species that are currently the focus of research in evolution and ecology and should help bring about new insights regarding the processes underlying the origin and maintenance of biological diversity.

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.

THE VARIABLE GENOMIC ARCHITECTURE OF ISOLATION BETWEEN HYBRIDIZING SPECIES OF HOUSE MICE

Studies of the genetics of hybrid zones can provide insight into the genomic architecture of species boundaries. By examining patterns of introgression of multiple loci across a hybrid zone, it may be possible to identify regions of the genome that have experienced selection. Here, we present a comparison of introgression in two replicate transects through the house mouse hybrid zone through central Europe, using data from 41 single nucleotide markers. Using both genomic and geographic clines, we found many differences in patterns of introgression between the two transects, as well as some similarities. We found that many loci may have experienced the effects of selection at linked sites, including selection against hybrid genotypes, as well as positive selection in the form of genotypes introgressed into a foreign genetic background. We also found many positive associations of conspecific alleles among unlinked markers, which could be caused by epistatic interactions. Different patterns of introgression in the two transects highlight the challenge of using hybrid zones to identify genes underlying isolation and raise the possibility that the genetic basis of isolation between these species may be dependent on the local population genetic make‐up or the local ecological setting.

Admixture as the basis for genetic mapping

Genetic mapping in natural populations is increasing rapidly in feasibility and accessibility. As with many areas in genetics, advances in molecular techniques and statistics are drastically altering how we can investigate inheritance in wild organisms. For ecology and evolution, this is particularly significant and promising, because many of the organisms of interest are not amenable to conventional genetic approaches. Admixture mapping falls within a family of statistical approaches that use natural recombination and linkage disequilibrium between genetic markers and phenotypes as the basis for mapping. Our aim in this review is to provide a snapshot of previous and ongoing research, existing methods and challenges, the nature of questions that can be investigated and prospects for the future of admixture mapping.

GENOMIC REGIONS WITH A HISTORY OF DIVERGENT SELECTION AFFECT FITNESS OF HYBRIDS BETWEEN TWO BUTTERFLY SPECIES

Speciation is the process by which reproductively isolated lineages arise, and is one of the fundamental means by which the diversity of life increases. Whereas numerous studies have documented an association between ecological divergence and reproductive isolation, relatively little is known about the role of natural selection in genome divergence during the process of speciation. Here, we use genome‐wide DNA sequences and Bayesian models to test the hypothesis that loci under divergent selection between two butterfly species (Lycaeides idas and L. melissa) also affect fitness in an admixed population. Locus‐specific measures of genetic differentiation between L. idas and L. melissa and genomic introgression in hybrids varied across the genome. The most differentiated genetic regions were characterized by elevated L. idas ancestry in the admixed population, which occurs in L. idas‐like habitat, consistent with the hypothesis that local adaptation contributes to speciation. Moreover, locus‐specific measures of genetic differentiation (a metric of divergent selection) were positively associated with extreme genomic introgression (a metric of hybrid fitness). Interestingly, concordance of differentiation and introgression was only partial. We discuss multiple, complementary explanations for this partial concordance.

Bayesian analysis of molecular variance in pyrosequences quantifies population genetic structure across the genome of Lycaeides butterflies.

The distribution of genetic variation within and among populations is commonly used to infer their demographic and evolutionary histories. This endeavour has the potential to benefit substantially from high‐throughput next‐generation sequencing technologies through a rapid increase in the amount of data available and a corresponding increase in the precision of parameter estimation. Here we report the results of a phylogeographic study of the North American butterfly genus Lycaeides using 454 sequence data. This study serves the dual purpose of demonstrating novel molecular and analytical methods for population genetic analyses with 454 sequence data and expanding our knowledge of the phylogeographic history of Lycaeides. We obtained 341 045 sequence reads from 12 populations that we were able to assemble into 15 262 contigs (most of which were variable), representing one of the largest population genetic data sets for a non‐model organism to date. We examined patterns of genetic variation using a hierarchical Bayesian analysis of molecular variance model, which provides precise estimates of genome‐level φST while appropriately modelling uncertainty in locus‐specific φST. We found that approximately 36% of sequence variation was partitioned among populations, suggesting historical or current isolation among the sampled populations. Estimates of pairwise genome‐level φST were largely consistent with a previous phylogeographic model for Lycaeides, suggesting fragmentation into two to three refugia during Pleistocene glacial cycles followed by post‐Pleistocene range expansion and secondary contact leading to introgressive hybridization. This study demonstrates the potential of using genome‐level data to better understand the phylogeographic history of populations.