Paul A. Hohenlohe

Genome-wide genetic marker discovery and genotyping using next-generation sequencing

The advent of next-generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for the discovery, validation and assessment of genetic markers in populations. Here we review and discuss best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target. These new methods — which include reduced-representation sequencing using reduced-representation libraries (RRLs) or complexity reduction of polymorphic sequences (CRoPS), restriction-site-associated DNA sequencing (RAD-seq) and low coverage genotyping — are applicable to both model organisms with high-quality reference genome sequences and, excitingly, to non-model species with no existing genomic data.

Population Genomics of Parallel Adaptation in Threespine Stickleback using Sequenced RAD Tags

Next-generation sequencing technology provides novel opportunities for gathering genome-scale sequence data in natural populations, laying the empirical foundation for the evolving field of population genomics. Here we conducted a genome scan of nucleotide diversity and differentiation in natural populations of threespine stickleback (Gasterosteus aculeatus). We used Illumina-sequenced RAD tags to identify and type over 45,000 single nucleotide polymorphisms (SNPs) in each of 100 individuals from two oceanic and three freshwater populations. Overall estimates of genetic diversity and differentiation among populations confirm the biogeographic hypothesis that large panmictic oceanic populations have repeatedly given rise to phenotypically divergent freshwater populations. Genomic regions exhibiting signatures of both balancing and divergent selection were remarkably consistent across multiple, independently derived populations, indicating that replicate parallel phenotypic evolution in stickleback may be occurring through extensive, parallel genetic evolution at a genome-wide scale. Some of these genomic regions co-localize with previously identified QTL for stickleback phenotypic variation identified using laboratory mapping crosses. In addition, we have identified several novel regions showing parallel differentiation across independent populations. Annotation of these regions revealed numerous genes that are candidates for stickleback phenotypic evolution and will form the basis of future genetic analyses in this and other organisms. This study represents the first high-density SNP–based genome scan of genetic diversity and differentiation for populations of threespine stickleback in the wild. These data illustrate the complementary nature of laboratory crosses and population genomic scans by confirming the adaptive significance of previously identified genomic regions, elucidating the particular evolutionary and demographic history of such regions in natural populations, and identifying new genomic regions and candidate genes of evolutionary significance.

Stacks: an analysis tool set for population genomics

Massively parallel short‐read sequencing technologies, coupled with powerful software platforms, are enabling investigators to analyse tens of thousands of genetic markers. This wealth of data is rapidly expanding and allowing biological questions to be addressed with unprecedented scope and precision. The sizes of the data sets are now posing significant data processing and analysis challenges. Here we describe an extension of the Stacks software package to efficiently use genotype‐by‐sequencing data for studies of populations of organisms. Stacks now produces core population genomic summary statistics and SNP‐by‐SNP statistical tests. These statistics can be analysed across a reference genome using a smoothed sliding window. Stacks also now provides several output formats for several commonly used downstream analysis packages. The expanded population genomics functions in Stacks will make it a useful tool to harness the newest generation of massively parallel genotyping data for ecological and evolutionary genetics.

Stacks: Building and Genotyping Loci De Novo From Short-Read Sequences

Advances in sequencing technology provide special opportunities for genotyping individuals with speed and thrift, but the lack of software to automate the calling of tens of thousands of genotypes over hundreds of individuals has hindered progress. Stacks is a software system that uses short-read sequence data to identify and genotype loci in a set of individuals either de novo or by comparison to a reference genome. From reduced representation Illumina sequence data, such as RAD-tags, Stacks can recover thousands of single nucleotide polymorphism (SNP) markers useful for the genetic analysis of crosses or populations. Stacks can generate markers for ultra-dense genetic linkage maps, facilitate the examination of population phylogeography, and help in reference genome assembly. We report here the algorithms implemented in Stacks and demonstrate their efficacy by constructing loci from simulated RAD-tags taken from the stickleback reference genome and by recapitulating and improving a genetic map of the zebrafish, Danio rerio.

Genomics and the future of conservation genetics

We will soon have complete genome sequences from thousands of species, as well as from many individuals within species. This coming explosion of information will transform our understanding of the amount, distribution and functional significance of genetic variation in natural populations. Now is a crucial time to explore the potential implications of this information revolution for conservation genetics and to recognize limitations in applying genomic tools to conservation issues. We identify and discuss those problems for which genomics will be most valuable for curbing the accelerating worldwide loss of biodiversity. We also provide guidance on which genomics tools and approaches will be most appropriate to use for different aspects of conservation.

Harnessing genomics for delineating conservation units

Genomic data have the potential to revolutionize the delineation of conservation units (CUs) by allowing the detection of adaptive genetic variation, which is otherwise difficult for rare, endangered species. In contrast to previous recommendations, we propose that the use of neutral versus adaptive markers should not be viewed as alternatives. Rather, neutral and adaptive markers provide different types of information that should be combined to make optimal management decisions. Genetic patterns at neutral markers reflect the interaction of gene flow and genetic drift that affects genome-wide variation within and among populations. This population genetic structure is what natural selection operates on to cause adaptive divergence. Here, we provide a new framework to integrate data on neutral and adaptive markers to protect biodiversity.

ESTIMATING NONLINEAR SELECTION GRADIENTS USING QUADRATIC REGRESSION COEFFICIENTS: DOUBLE OR NOTHING?

Abstract The use of regression analysis has been instrumental in allowing evolutionary biologists to estimate the strength and mode of natural selection. Although directional and correlational selection gradients are equal to their corresponding regression coefficients, quadratic regression coefficients must be doubled to estimate stabilizing/disruptive selection gradients. Based on a sample of 33 papers published in Evolution between 2002 and 2007, at least 78% of papers have not doubled quadratic regression coefficients, leading to an appreciable underestimate of the strength of stabilizing and disruptive selection. Proper treatment of quadratic regression coefficients is necessary for estimation of fitness surfaces and contour plots, canonical analysis of the γ matrix, and modeling the evolution of populations on an adaptive landscape.

Resolving postglacial phylogeography using high-throughput sequencing

The distinction between model and nonmodel organisms is becoming increasingly blurred. High-throughput, second-generation sequencing approaches are being applied to organisms based on their interesting ecological, physiological, developmental, or evolutionary properties and not on the depth of genetic information available for them. Here, we illustrate this point using a low-cost, efficient technique to determine the fine-scale phylogenetic relationships among recently diverged populations in a species. This application of restriction site-associated DNA tags (RAD tags) reveals previously unresolved genetic structure and direction of evolution in the pitcher plant mosquito, Wyeomyia smithii, from a southern Appalachian Mountain refugium following recession of the Laurentide Ice Sheet at 22,000–19,000 B.P. The RAD tag method can be used to identify detailed patterns of phylogeography in any organism regardless of existing genomic data, and, more broadly, to identify incipient speciation and genome-wide variation in natural populations in general.

Harnessing the power of RADseq for ecological and evolutionary genomics

High-throughput techniques based on restriction site-associated DNA sequencing (RADseq) are enabling the low-cost discovery and genotyping of thousands of genetic markers for any species, including non-model organisms, which is revolutionizing ecological, evolutionary and conservation genetics. Technical differences among these methods lead to important considerations for all steps of genomics studies, from the specific scientific questions that can be addressed, and the costs of library preparation and sequencing, to the types of bias and error inherent in the resulting data. In this Review, we provide a comprehensive discussion of RADseq methods to aid researchers in choosing among the many different approaches and avoiding erroneous scientific conclusions from RADseq data, a problem that has plagued other genetic marker types in the past.

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.