Next-generation data filtering in the genomics era

Genomic data are ubiquitous across disciplines, from agriculture to biodiversity, ecology, evolution and human health. However, these datasets often contain noise or errors and are missing information that can affect the accuracy and reliability of subsequent computational analyses and conclusions. A key step in genomic data analysis is filtering - removing sequencing bases, reads, genetic variants and/or individuals from a dataset - to improve data quality for downstream analyses. Researchers are confronted with a multitude of choices when filtering genomic data; they must choose which filters to apply and select appropriate thresholds. To help usher in the next generation of genomic data filtering, we review and suggest best practices to improve the implementation, reproducibility and reporting standards for filter types and thresholds commonly applied to genomic datasets. We focus mainly on filters for minor allele frequency, missing data per individual or per locus, linkage disequilibrium and Hardy-Weinberg deviations. Using simulated and empirical datasets, we illustrate the large effects of different filtering thresholds on common population genetics statistics, such as Tajima's D value, population differentiation (FST), nucleotide diversity (π) and effective population size (Ne).

Rapid and Repeated Climate Adaptation Involving Chromosome Inversions following Invasion of an Insect

Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.

Genomics and conservation: Guidance from training to analyses and applications

Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here.

Waste not, want not: Microsatellites remain an economical and informative technology for conservation genetics

Comparisons of microsatellites and single-nucleotide polymorphisms (SNPs) have found that SNPs outperform microsatellites in population genetic analyses, questioning the continued utility of microsatellites in population and landscape genetics. Yet, highly polymorphic markers may be of value in species that have reduced genetic variation. This study repeated previous analyses that used microsatellites with SNPs developed from ddRAD sequencing in the black-capped vireo source-sink system. SNPs provided greater resolution of genetic diversity, population differentiation, and migrant detection but could not reconstruct parentage relationships due to insufficient heterozygosities. The biological inferences made by both sets of markers were similar: asymmetrical gene flow from source sites to the remaining sink sites. With the landscape genetic analyses, we found different results between the two molecular markers, but associations of the top environmental features (riparian, open habitat, agriculture, and human development) with dispersal estimates were shared between marker types. Despite the higher precision of SNPs, we find that microsatellites effectively uncover population processes and patterns and are superior for parentage analyses in this species with reduced genetic diversity. This study illustrates the continued applicability and relevance of microsatellites in population genetic research.

Genome-Wide Evidence for Complex Hybridization and Demographic History in a Group of Cycas From China

Cycads represent one of the most ancestral living seed plants as well as one of the most threatened plant groups in the world. South China is a major center and potential origin of Cycas, the most rapidly diversified lineage of cycads. However, genomic-wide diversity of Cycas remains poorly understood due to the challenge of generating genomic markers associated with their inherent large genomes. Here, we perform a comprehensive conservation genomic study based on restriction-site associated DNA sequencing (RADseq) data in six representative species of Cycas in South China. Consistently low genetic diversity and strong genetic differentiation were detected across species. Both phylogenetic inference and genetic structure analysis via several methods revealed generally congruent groups among the six Cycas species. The analysis with ADMIXTURE showed low mixing of genetic composition among species, while individuals of C. dolichophylla exhibited substantial genetic admixture with C. bifida, C. changjiangensis, and C. balansae. Furthermore, the results from Treemix, f₄-statistic, and ABBA-BABA test were generally consistent and revealed the complex patterns of interspecific gene flow. Relatively strong signals of hybridization were detected between C. dolichophylla and C. szechuanensis, and the ancestor of C. taiwaniana and C. changjiangensis. Distinct patterns of demographic history were inferred for these species by Stairway Plot, and our results suggested that both climate fluctuation and frequent geological activities during the late Pleistocene exerted deep impacts on the population dynamics of these species in South China. Finally, we explore the practical implications of our findings for the development of conservation strategies in Cycas. The present study demonstrates the efficiency of RADseq for conservation genomic studies on non-model species with large and complex genomes. Given the great significance of cycads as a radical transition in the evolution of plant biodiversity, our study provides important insights into the mechanisms of diversification in such recently radiated living fossil taxa.

Population Genomics Training for the Next Generation of Conservation Geneticists: ConGen 2018 Workshop

The increasing availability and complexity of next-generation sequencing (NGS) data sets make ongoing training an essential component of conservation and population genetics research. A workshop entitled “ConGen 2018” was recently held to train researchers in conceptual and practical aspects of NGS data production and analysis for conservation and ecological applications. Sixteen instructors provided helpful lectures, discussions, and hands-on exercises regarding how to plan, produce, and analyze data for many important research questions. Lecture topics ranged from understanding probabilistic (e.g., Bayesian) genotype calling to the detection of local adaptation signatures from genomic, transcriptomic, and epigenomic data. We report on progress in addressing central questions of conservation genomics, advances in NGS data analysis, the potential for genomic tools to assess adaptive capacity, and strategies for training the next generation of conservation genomicists.

Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field

A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors-and beyond-to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.

Regarding the F-word: The effects of data filtering on inferred genotype-environment associations

Genotype-environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to best filter genotype-by-sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the results, negatively affecting management strategies. Here, we investigate the effects of filtering on GEA results and the potential implications for assessment of adaptation to environment. We use empirical and simulated data sets derived from two widespread tree species to assess the effects of filtering on GEA outputs. Critically, we find that the level of filtering of missing data and minor allele frequency affect the identification of true positives. Even slight adjustments to these thresholds can change the rate of true positive detection. Using conservative thresholds for missing data and minor allele frequency substantially reduces the size of the data set, lessening the power to detect adaptive variants (i.e., simulated true positives) with strong and weak strengths of selection. Regardless, strength of selection was a good predictor for GEA detection, but even some SNPs under strong selection went undetected. False positive rates varied depending on the species and GEA method, and filtering significantly impacted the predictions of adaptive capacity in downstream analyses. We make several recommendations regarding filtering for GEA methods. Ultimately, there is no filtering panacea, but some choices are better than others, depending on the study system, availability of genomic resources, and desired objectives.

Double-digest RAD-sequencing: do pre- and post-sequencing protocol parameters impact biological results?

Next-generation sequencing technologies have opened a new era of research in population genetics. Following these new sequencing opportunities, the use of restriction enzyme-based genotyping techniques, such as restriction site-associated DNA sequencing (RAD-seq) or double-digest RAD-sequencing (ddRAD-seq), has dramatically increased in the last decade. From DNA sampling to SNP calling, the laboratory and bioinformatic parameters of enzyme-based techniques have been investigated in the literature. However, the impact of those parameters on downstream analyses and biological results remains less documented. In this study, we investigated the effects of sevral pre- and post-sequencing settings on ddRAD-seq results for two biological systems: a complex of butterfly species (Coenonympha sp.) and several populations of common beech (Fagus sylvatica). Our results suggest that pre-sequencing parameters (i.e., DNA quantity, number of PCR cycles during library preparation) have a significant impact on the number of recovered reads and SNPs, on the number of unique alleles and on individual heterozygosity. In the same way, we found that post-sequencing settings (i.e., clustering and minimum coverage thresholds) influenced loci reconstruction (e.g., number of loci, mean coverage) and SNP calling (e.g., number of SNPs; heterozygosity) but had only a marginal impact on downstream analyses (e.g., measure of genetic differentiation, estimation of individual admixture, and demographic inferences). In addition, replication analyses confirmed the reproducibility of the ddRAD-seq procedure. Overall, this study assesses the degree of sensitivity of ddRAD-seq data to pre- and post-sequencing protocols, and illustrates its robustness when studying population genetics.

The puzzling occurrence of the upside-down jellyfish Cassiopea (Cnidaria: Scyphozoa) along the Brazilian coast: a result of several invasion events?

The massive occurrence of jellyfish in several areas of the world is reported annually, but most of the data come from the northern hemisphere and often refer to a restricted group of species that are not in the genus Cassiopea. This study records a massive, clonal and non-native population of Cassiopea and discusses the possible scenarios that resulted in the invasion of the Brazilian coast by these organisms. The results indicate that this jellyfish might have invaded the Brazilian coast multiple times.

Genomics versus mtDNA for resolving stock structure in the silky shark (Carcharhinus falciformis)

Conservation genetic approaches for elasmobranchs have focused on regions of the mitochondrial genome or a handful of nuclear microsatellites. High-throughput sequencing offers a powerful alternative for examining population structure using many loci distributed across the nuclear and mitochondrial genomes. These single nucleotide polymorphisms are expected to provide finer scale and more accurate population level data; however, there have been few genomic studies applied to elasmobranch species. The desire to apply next-generation sequencing approaches is often tempered by the costs, which can be offset by pooling specimens prior to sequencing (pool-seq). In this study, we assess the utility of pool-seq by applying this method to the same individual silky sharks, Carcharhinus falciformis, previously surveyed with the mtDNA control region in the Atlantic and Indian Oceans. Pool-seq methods were able to recover the entire mitochondrial genome as well as thousands of nuclear markers. This volume of sequence data enabled the detection of population structure between regions of the Atlantic Ocean populations, undetected in the previous study (inter-Atlantic mitochondrial SNPs FST values comparison ranging from 0.029 to 0.135 and nuclear SNPs from 0.015 to 0.025). Our results reinforce the conclusion that sampling the mitochondrial control region alone may fail to detect fine-scale population structure, and additional sampling across the genome may increase resolution for some species. Additionally, this study shows that the costs of analyzing 4,988 loci using pool-seq methods are equivalent to the standard Sanger-sequenced markers and become less expensive when large numbers of individuals (>300) are analyzed.

Fine-scale population structure and evidence for local adaptation in Australian giant black tiger shrimp (Penaeus monodon) using SNP analysis

BACKGROUND

Restrictions to gene flow, genetic drift, and divergent selection associated with different environments are significant drivers of genetic differentiation. The black tiger shrimp (Penaeus monodon), is widely distributed throughout the Indian and Pacific Oceans including along the western, northern and eastern coastline of Australia, where it is an important aquaculture and fishery species. Understanding the genetic structure and the influence of environmental factors leading to adaptive differences among populations of this species is important for farm genetic improvement programs and sustainable fisheries management.

RESULTS

Based on 278 individuals obtained from seven geographically disparate Australian locations, 10,624 high-quality SNP loci were used to characterize genetic diversity, population structure, genetic connectivity, and adaptive divergence. Significant population structure and differentiation were revealed among wild populations (average F_ST = 0.001-0.107; p <  0.05). Eighty-nine putatively outlier SNPs were identified to be potentially associated with environmental variables by using both population differentiation (BayeScan and PCAdapt) and environmental association (redundancy analysis and latent factor mixed model) analysis methods. Clear population structure with similar spatial patterns were observed in both neutral and outlier markers with three genetically distinct groups identified (north Queensland, Northern Territory, and Western Australia). Redundancy, partial redundancy, and multiple regression on distance matrices analyses revealed that both geographical distance and environmental factors interact to generate the structure observed across Australian P. monodon populations.

CONCLUSION

This study provides new insights on genetic population structure of Australian P. monodon in the face of environmental changes, which can be used to advance sustainable fisheries management and aquaculture breeding programs.

Customize and get the most out of your reduced-representation sequencing experiment with the new simulation software RADinitio

Whole-genome sequencing is still often a difficult, costly and time-consuming task. The emergence of various genome reduced-representation sequencing (RRS) protocols such as restriction site-associated DNA sequencing (RADseq) has facilitated the access to genome-wide information, without the need for whole-genome sequencing. Reaching the full potential of RRS protocols though requires adjustments and tailoring to the species under investigation. To that end, simulation software has been developed to guide researchers in the customization of their RADseq experiment, but the extent to which these tools mimic the behaviour of a protocol in generating sequencing data is limited. In this current issue of Molecular Ecology Resources, Rivera-Colón et al. (2020) introduce RADinitio, a new software for simulating RADseq data designed to perform simulations at the highest level of representativeness. By taking into account the effects of library preparation and sequencing parameters on the resulting sequences, RADinitio allows the precise identification of the sources of failure when designing a RADseq experiment. This new software represents a considerable advance in RADseq data simulation and will likely lead to increased success in RADseq experiments.

An Integrative Approach Using Phylogenomics and High-Resolution X-Ray Computed Tomography for Species Delimitation in Cryptic Taxa

Morphologically cryptic taxa have proved to be a long-standing challenge for taxonomists. Lineages that show strong genomic structuring across the landscape but are phenotypically similar pose a conundrum, with traditional morphological analyses of these cryptic lineages struggling to keep up with species delimitation advances. Micro X-ray computed tomography (CT) combined with geometric morphometric analyses provides a promising avenue for identification of morphologically cryptic taxa, given its ability to detect subtle differences in anatomical structures. However, this approach has yet to be used in combination with genomic data in a comparative analytical framework to distinguish cryptic taxa. We present an integrative approach incorporating genomic and geometric morphometric evidence to assess the species delimitation of grassland earless dragons (Tympanocryptis spp.) in north-eastern Australia. Using mitochondrial and nuclear genes (ND2 and RAG1, respectively), along with $>$8500 SNPs (nuclear single nucleotide polymorphisms), we assess the evolutionary independence of target lineages and several closely related species. We then integrate phylogenomic data with osteological cranial variation between lineages using landmark-based analyses of three-dimensional CT models. High levels of genomic differentiation between the three target lineages were uncovered, also supported by significant osteological differences. By incorporating multiple lines of evidence, we provide strong support for three undescribed cryptic lineages of Tympanocryptis in north-eastern Australia that warrant taxonomic review. Our approach demonstrates the successful application of CT with integrative taxonomic approaches for cryptic species delimitation, which is broadly applicable across vertebrates containing morphologically similar yet genetically distinct lineages. Additionally, we provide a review of recent integrative taxonomic approaches for cryptic species delimitation and an assessment of how our approach can value-add to taxonomic research.

Helping decision making for reliable and cost-effective 2b-RAD sequencing and genotyping analyses in non-model species

High-throughput sequencing has revolutionized population and conservation genetics. RAD sequencing methods, such as 2b-RAD, can be used on species lacking a reference genome. However, transferring protocols across taxa can potentially lead to poor results. We tested two different IIB enzymes (AlfI and CspCI) on two species with different genome sizes (the loggerhead turtle Caretta caretta and the sharpsnout seabream Diplodus puntazzo) to build a set of guidelines to improve 2b-RAD protocols on non-model organisms while optimising costs. Good results were obtained even with degraded samples, showing the value of 2b-RAD in studies with poor DNA quality. However, library quality was found to be a critical parameter on the number of reads and loci obtained for genotyping. Resampling analyses with different number of reads per individual showed a trade-off between number of loci and number of reads per sample. The resulting accumulation curves can be used as a tool to calculate the number of sequences per individual needed to reach a mean depth ≥20 reads to acquire good genotyping results. Finally, we demonstrated that selective-base ligation does not affect genomic differentiation between individuals, indicating that this technique can be used in species with large genome sizes to adjust the number of loci to the study scope, to reduce sequencing costs and to maintain suitable sequencing depth for a reliable genotyping without compromising the results. Here, we provide a set of guidelines to improve 2b-RAD protocols on non-model organisms with different genome sizes, helping decision-making for a reliable and cost-effective genotyping.

Knowledge status and sampling strategies to maximize cost-benefit ratio of studies in landscape genomics of wild plants

To avoid local extinction due to the changes in their natural ecosystems, introduced by anthropogenic activities, species undergo local adaptation. Landscape genomics approach, through genome–environment association studies, has helped evaluate the local adaptation in natural populations. Landscape genomics, is still a developing discipline, requiring refinement of guidelines in sampling design, especially for studies conducted in the backdrop of stark socioeconomic realities of the rainforest ecologies, which are global biodiversity hotspots. In this study we aimed to devise strategies to improve the cost-benefit ratio of landscape genomics studies by surveying sampling designs and genome sequencing strategies used in existing studies. We conducted meta-analyses to evaluate the importance of sampling designs, in terms of (i) number of populations sampled, (ii) number of individuals sampled per population, (iii) total number of individuals sampled, and (iv) number of SNPs used in different studies, in discerning the molecular mechanisms underlying local adaptation of wild plant species. Using the linear mixed effects model, we demonstrated that the total number of individuals sampled and the number of SNPs used, significantly influenced the detection of loci underlying the local adaptation. Thus, based on our findings, in order to optimize the cost-benefit ratio of landscape genomics studies, we suggest focusing on increasing the total number of individuals sampled and using a targeted (e.g. sequencing capture) Pool-Seq approach and/or a random (e.g. RAD-Seq) Pool-Seq approach to detect SNPs and identify SNPs under selection for a given environmental cline. We also found that the existing molecular evidences are inadequate in predicting the local adaptations to climate change in tropical forest ecosystems.

How "simple" methodological decisions affect interpretation of population structure based on reduced representation library DNA sequencing: A case study using the lake whitefish

Reduced representation (RRL) sequencing approaches (e.g., RADSeq, genotyping by sequencing) require decisions about how much to invest in genome coverage and sequencing depth, as well as choices of values for adjustable bioinformatics parameters. To empirically explore the importance of these “simple” methodological decisions, we generated two independent sequencing libraries for the same 142 individual lake whitefish (Coregonus clupeaformis) using a nextRAD RRL approach: (1) a larger number of loci at low sequencing depth based on a 9mer (library A); and (2) fewer loci at higher sequencing depth based on a 10mer (library B). The fish were selected from populations with different levels of expected genetic subdivision. Each library was analyzed using the STACKS pipeline followed by three types of population structure assessment (F_ST, DAPC and ADMIXTURE) with iterative increases in the stringency of sequencing depth and missing data requirements, as well as more specific a priori population maps. Library B was always able to resolve strong population differentiation in all three types of assessment regardless of the selected parameters, largely due to retention of more loci in analyses. In contrast, library A produced more variable results; increasing the minimum sequencing depth threshold (-m) resulted in a reduced number of retained loci, and therefore lost resolution at high -m values for F_ST and ADMIXTURE, but not DAPC. When detecting fine population differentiation, the population map influenced the number of loci and missing data, which generated artefacts in all downstream analyses tested. Similarly, when examining fine scale population subdivision, library B was robust to changing parameters but library A lost resolution depending on the parameter set. We used library B to examine actual subdivision in our study populations. All three types of analysis found complete subdivision among populations in Lake Huron, ON and Dore Lake, SK, Canada using 10,640 SNP loci. Weak population subdivision was detected in Lake Huron with fish from sites in the north-west, Search Bay, North Point and Hammond Bay, showing slight differentiation. Overall, we show that apparently simple decisions about library construction and bioinformatics parameters can have important impacts on the interpretation of population subdivision. Although potentially more costly on a per-locus basis, early investment in striking a balance between the number of loci and sequencing effort is well worth the reduced genomic coverage for population genetics studies. More conservative stringency settings on STACKS parameters lead to a final dataset that was more consistent and robust when examining both weak and strong population differentiation. Overall, we recommend that researchers approach “simple” methodological decisions with caution, especially when working on non-model species for the first time.

Applications of Next-Generation Sequencing Technologies and Computational Tools in Molecular Evolution and Aquatic Animals Conservation Studies: A Short Review

Aquatic ecosystems that form major biodiversity hotspots are critically threatened due to environmental and anthropogenic stressors. We believe that, in this genomic era, computational methods can be applied to promote aquatic biodiversity conservation by addressing questions related to the evolutionary history of aquatic organisms at the molecular level. However, huge amounts of genomics data generated can only be discerned through the use of bioinformatics. Here, we examine the applications of next-generation sequencing technologies and bioinformatics tools to study the molecular evolution of aquatic animals and discuss the current challenges and future perspectives of using bioinformatics toward aquatic animal conservation efforts.

Utilizing field collected insects for next generation sequencing: Effects of sampling, storage, and DNA extraction methods

DNA sequencing technologies continue to advance the biological sciences, expanding opportunities for genomic studies of non-model organisms for basic and applied questions. Despite these opportunities, many next generation sequencing protocols have been developed assuming a substantial quantity of high molecular weight DNA (>100 ng), which can be difficult to obtain for many study systems. In particular, the ability to sequence field-collected specimens that exhibit varying levels of DNA degradation remains largely unexplored. In this study we investigate the influence of five traditional insect capture and curation methods on Double-Digest Restriction Enzyme Associated DNA (ddRAD) sequencing success for three wild bee species. We sequenced a total of 105 specimens (between 7-13 specimens per species and treatment). We additionally investigated how different DNA quality metrics (including pre-sequence concentration and contamination) predicted downstream sequencing success, and also compared two DNA extraction methods. We report successful library preparation for all specimens, with all treatments and extraction methods producing enough highly reliable loci for population genetic analyses. Although results varied between species, we found that specimens collected by net sampling directly into 100% EtOH, or by passive trapping followed by 100% EtOH storage before pinning tended to produce higher quality ddRAD assemblies, likely as a result of rapid specimen desiccation. Surprisingly, we found that specimens preserved in propylene glycol during field sampling exhibited lower-quality assemblies. We provide recommendations for each treatment, extraction method, and DNA quality assessment, and further encourage researchers to consider utilizing a wider variety of specimens for genomic analyses.

Erythroxylum in Focus: An Interdisciplinary Review of an Overlooked Genus

The genus Erythroxylum contains species used by indigenous people of South America long before the domestication of plants. Two species, E. coca and E. novogranatense, have been utilized for thousands of years specifically for their tropane alkaloid content. While abuse of the narcotic cocaine has impacted society on many levels, these species and their wild relatives contain untapped resources for the benefit of mankind in the form of foods, pharmaceuticals, phytotherapeutic products, and other high-value plant-derived metabolites. In this review, we describe the current state of knowledge of members within the genus and the recent advances in the realm of molecular biology and biochemistry.

Worldwide relationships in the fern genus Pteridium (bracken) based on nuclear genome markers

PREMISE

Spore-bearing plants are capable of dispersing very long distances. However, it is not known if gene flow can prevent genetic divergence in widely distributed taxa. Here we address this issue, and examine systematic relationships at a global geographic scale for the fern genus Pteridium.

METHODS

We sampled plants from 100 localities worldwide, and generated nucleotide data from four nuclear genes and two plastid regions. We also examined 2801 single nucleotide polymorphisms detected by a restriction site-associated DNA approach.

RESULTS

We found evidence for two distinct diploid species and two allotetraploids between them. The "northern" species (Pteridium aquilinum) has distinct groups at the continental scale (Europe, Asia, Africa, and North America). The northern European subspecies pinetorum appears to involve admixture among all of these. A sample from the Hawaiian Islands contained elements of both North American and Asian P. aquilinum. The "southern" species, P. esculentum, shows little genetic differentiation between South American and Australian samples. Components of African genotypes are detected on all continents.

CONCLUSIONS

We find evidence of distinct continental-scale genetic differentiation in Pteridium. However, on top of this is a clear signal of recent hybridization. Thus, spore-bearing plants are clearly capable of extensive long-distance gene flow; yet appear to have differentiated genetically at the continental scale. Either gene flow in the past was at a reduced level, or vicariance is possible even in the face of long-distance gene flow.

Coalescent models characterize sources and demographic history of recent round goby colonization of Great Lakes and inland waters

The establishment and spread of aquatic invasive species are ecologically and economically harmful and a source of conservation concern internationally. Processes of species invasion have traditionally been inferred from observational data of species presence/absence and relative abundance. However, genetic-based approaches can provide valuable sources of inference. Restriction site-associated DNA sequencing was used to identify and genotype single nucleotide polymorphism (SNP) loci for Round Gobies (Neogobius melanostomus) (N = 440) from 18 sampling locations in the Great Lakes and in three Michigan, USA, drainages (Flint, Au Sable, and Cheboygan River basins). Sampled rivers differed in size, accessibility, and physical characteristics including man-made dispersal barriers. Population levels of genetic diversity and interpopulation variance in SNP allele frequency were used in coalescence-based approximate Bayesian computation (ABC) to statistically compare models representing competing hypotheses regarding source population, postcolonization dispersal, and demographic history in the Great Lakes and inland waters. Results indicate different patterns of colonization across the three drainages. In the Flint River, models indicate a strong population bottleneck (<3% of contemporary effective population size) and a single founding event from Saginaw Bay led to the colonization of inland river segments. In the Au Sable River, analyses could not distinguish potential source populations, but supported models indicated multiple introductions from one source population. In the Cheboygan River, supported models indicated that colonization likely proceeded from east (Lake Huron source) to west among inland locales sampled in the system. Despite the recent occupancy of Great Lakes and inland habitats, large numbers of loci analyzed in an ABC framework enable statistically supported identification of source populations and reconstruction of the direction of inland spread and demographic history following establishment. Information from analyses can direct management actions to limit the spread of invasive species from identified sources and most probable vectors into additional inland aquatic habitats.

MobiSeq: De novo SNP discovery in model and non-model species through sequencing the flanking region of transposable elements

In recent years, the availability of reduced representation library (RRL) methods has catalysed an expansion of genome-scale studies to characterize both model and non-model organisms. Most of these methods rely on the use of restriction enzymes to obtain DNA sequences at a genome-wide level. These approaches have been widely used to sequence thousands of markers across individuals for many organisms at a reasonable cost, revolutionizing the field of population genomics. However, there are still some limitations associated with these methods, in particular the high molecular weight DNA required as starting material, the reduced number of common loci among investigated samples, and the short length of the sequenced site-associated DNA. Here, we present MobiSeq, a RRL protocol exploiting simple laboratory techniques, that generates genomic data based on PCR targeted enrichment of transposable elements and the sequencing of the associated flanking region. We validate its performance across 103 DNA extracts derived from three mammalian species: grey wolf (Canis lupus), red deer complex (Cervus sp.) and brown rat (Rattus norvegicus). MobiSeq enables the sequencing of hundreds of thousands loci across the genome and performs SNP discovery with relatively low rates of clonality. Given the ease and flexibility of MobiSeq protocol, the method has the potential to be implemented for marker discovery and population genomics across a wide range of organisms-enabling the exploration of diverse evolutionary and conservation questions.

A striking new species of leaf warbler from the Lesser Sundas as uncovered through morphology and genomics

Leaf warblers (Aves; Phylloscopidae) are a diverse clade of insectivorous, canopy-dwelling songbirds widespread across the Old World. The taxonomy of Australasian leaf warblers is particularly complex, with multiple species-level divergences between island taxa in the region requiring further scrutiny. We use a combination of morphology, bioacoustics, and analysis of thousands of genome-wide markers to investigate and describe a new species of Phylloscopus leaf warbler from the island of Rote in the Lesser Sundas, Indonesia. We show that this new Rote Leaf Warbler is morphologically and genomically highly distinct from its congenerics, but do not find vocal differentiation between different island taxa. We discuss the behaviour and ecology of this highly distinctive new species, and make recommendations about its conservation status. We believe this constitutes the first description of a novel bird species that is partly based on insights from massive amounts of genome-wide DNA markers.

Genome-wide SNP analyses reveal high gene flow and signatures of local adaptation among the scalloped spiny lobster (Panulirus homarus) along the Omani coastline

BACKGROUND

The scalloped spiny lobster (Panulirus homarus) is a popular seafood commodity worldwide and an important export item from Oman. Annual catches in commercial fisheries are in serious decline, which has resulted in calls for the development of an integrated stock management approach. In Oman, the scalloped spiny lobster is currently treated as a single management unit (MU) or stock and there is an absence of information on the genetic population structure of the species that can inform management decisions, particularly at a fine-scale level. This work is the first to identify genome-wide single nucleotide polymorphisms (SNPs) for P. homarus using Diversity Arrays Technology sequencing (DArT-seq) and to elucidate any stock structure in the species.

RESULTS

After stringent filtering, 7988 high utility SNPs were discovered and used to assess the genetic diversity, connectivity and structure of P. homarus populations from Al Ashkharah, Masirah Island, Duqm, Ras Madrakah, Haitam, Ashuwaymiyah, Mirbat and Dhalkut landing sites. Pairwise FST estimates revealed low differentiation among populations (pairwise FST range = - 0.0008 - 0.0021). Analysis of genetic variation using putatively directional FST outliers (504 SNPs) revealed higher and significant pairwise differentiation (p < 0.01) for all locations, with Ashuwaymiyah being the most diverged population (Ashuwaymiyah pairwise FST range = 0.0288-0.0736). Analysis of population structure using Discriminant Analysis of Principal Components (DAPC) revealed a broad admixture among P. homarus, however, Ashuwaymiyah stock appeared to be potentially under local adaptive pressures. Fine scale analysis using Netview R provided further support for the general admixture of P. homarus.

CONCLUSIONS

Findings here suggested that stocks of P. homarus along the Omani coastline are admixed. Yet, fishery managers need to treat the lobster stock from Ashuwaymiyah with caution as it might be subject to local adaptive pressures. We emphasize further study with larger number of samples to confirm the genetic status of the Ashuwaymiyah stock. The approach utilised in this study has high transferability in conservation and management of other marine stocks with similar biological and ecological attributes.

De novo Assembly and Transcriptome Characterization of Opisthopappus (Asteraceae) for Population Differentiation and Adaption

Opisthopappus Shih (Asteraceae), an endangered genus endemic to the Taihang Mountains of China, is a high-value ornamental and medicinal plant consisting of two species, Opisthopappus longilobus shih and Opisthopappus taihangensis (Ling) Shih. However, the evolutionary relationships and the taxonomic characteristics between the two species remain unknown. In this study, high-throughput transcriptome sequencing was used to analyze the differential metabolic activity and gene expression and screened special molecular markers for exploring the genetic variation and species differentiation in Opisthopappus Shih. The results showed that 33,974 unigenes with an average size of 801 bp were obtained with optimization of de novo assembly. The comprehensive functional annotation based on Gene Ontology (GO), Cluster of Orthologous Group (COG) and Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) revealed that these unigenes were mainly related to many physiological, metabolic, and molecular processes. Furthermore, the comparative transcriptome analysis indicated that 3,410 differentially expressed genes were mainly involved in lipid, carbohydrate and amino acid metabolism, xenobiotics biodegradation and metabolism as well as environment adaptation via KEGG. Such as the CYP710A, GST, HSP90A and so on, could be the potential candidate genes for further investigating the molecular mechanism of physiological variations between O. taihangensis and O. longilobus. In addition, the potential 71,804 high quality single nucleotide polymorphisms (SNPs) and 1,444 simple sequence repeats (SSRs) were estimated. Based on the predicted SNP, we have developed eight SNP markers for population genetic analysis in Opisthopappus Shih. A significantly high level of genetic differentiation between the populations of O. longilobus and O. taihangensis were found, and they were clearly grouped into two distinct genetic clusters. These results conformed to the record of Flora Reipublicae Popularis Sinicae (FRPS) and unsupported the taxonomic status in the Flora of China. The transcriptome analysis of Opisthopappus Shih can contribute to in-depth exploring of internal mechanisms in species variation and differentiation based on molecular evidence. With the rich and valuable data resources, the more novel structural, functional, and comparative genomic studies will provide comprehensive insights into the evolutionary relationships between O. taihangensis and O. longilobus.

A RAD-sequencing approach to genome-wide marker discovery, genotyping, and phylogenetic inference in a diverse radiation of primates

Until recently, most phylogenetic and population genetics studies of nonhuman primates have relied on mitochondrial DNA and/or a small number of nuclear DNA markers, which can limit our understanding of primate evolutionary and population history. Here, we describe a cost-effective reduced representation method (ddRAD-seq) for identifying and genotyping large numbers of SNP loci for taxa from across the New World monkeys, a diverse radiation of primates that shared a common ancestor ~20-26 mya. We also estimate, for the first time, the phylogenetic relationships among 15 of the 22 currently-recognized genera of New World monkeys using ddRAD-seq SNP data using both maximum likelihood and quartet-based coalescent methods. Our phylogenetic analyses robustly reconstructed three monophyletic clades corresponding to the three families of extant platyrrhines (Atelidae, Pitheciidae and Cebidae), with Pitheciidae as basal within the radiation. At the genus level, our results conformed well with previous phylogenetic studies and provide additional information relevant to the problematic position of the owl monkey (Aotus) within the family Cebidae, suggesting a need for further exploration of incomplete lineage sorting and other explanations for phylogenetic discordance, including introgression. Our study additionally provides one of the first applications of next-generation sequencing methods to the inference of phylogenetic history across an old, diverse radiation of mammals and highlights the broad promise and utility of ddRAD-seq data for molecular primatology.

Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation

Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.

Rapid evolution in insect pests: the importance of space and time in population genomics studies

Pest species in agroecosystems often exhibit patterns of rapid evolution to environmental and human-imposed selection pressures. Although the role of adaptive processes is well accepted, few insect pests have been studied in detail and most research has focused on selection at insecticide resistance candidate genes. Emerging genomic datasets provide opportunities to detect and quantify selection in insect pest populations, and address long-standing questions about mechanisms underlying rapid evolutionary change. We examine the strengths of recent studies that stratify population samples both in space (along environmental gradients and comparing ancestral vs. derived populations) and in time (using chronological sampling, museum specimens and comparative phylogenomics), resulting in critical insights on evolutionary processes, and providing new directions for studying pests in agroecosystems.

Fantastic Beasts and How To Sequence Them: Ecological Genomics for Obscure Model Organisms

The application of genomic approaches to 'obscure model organisms' (OMOs), meaning species with no prior genomic resources, enables increasingly sophisticated studies of the genomic basis of evolution, acclimatization, and adaptation in real ecological contexts. I consider here ecological questions that can be addressed using OMOs, and indicate optimal sequencing and data-handling solutions for each case. With this I hope to promote the diversity of OMO-based projects that would capitalize on the peculiarities of the natural history of OMOs and could feasibly be completed within the scope of a single PhD thesis.

Evaluation of ddRADseq for reduced representation metagenome sequencing

Background

Profiling of microbial communities via metagenomic shotgun sequencing has enabled researches to gain unprecedented insight into microbial community structure and the functional roles of community members. This study describes a method and basic analysis for a metagenomic adaptation of the double digest restriction site associated DNA sequencing (ddRADseq) protocol for reduced representation metagenome profiling.

Methods

This technique takes advantage of the sequence specificity of restriction endonucleases to construct an Illumina-compatible sequencing library containing DNA fragments that are between a pair of restriction sites located within close proximity. This results in a reduced sequencing library with coverage breadth that can be tuned by size selection. We assessed the performance of the metagenomic ddRADseq approach by applying the full method to human stool samples and generating sequence data.

Results

The ddRADseq data yields a similar estimate of community taxonomic profile as obtained from shotgun metagenome sequencing of the same human stool samples. No obvious bias with respect to genomic G + C content and the estimated relative species abundance was detected.

Discussion

Although ddRADseq does introduce some bias in taxonomic representation, the bias is likely to be small relative to DNA extraction bias. ddRADseq appears feasible and could have value as a tool for metagenome-wide association studies.

Best Practices for Population Genetic Analyses

Population genetic analysis is a powerful tool to understand how pathogens emerge and adapt. However, determining the genetic structure of populations requires complex knowledge on a range of subtle skills that are often not explicitly stated in book chapters or review articles on population genetics. What is a good sampling strategy? How many isolates should I sample? How do I include positive and negative controls in my molecular assays? What marker system should I use? This review will attempt to address many of these practical questions that are often not readily answered from reading books or reviews on the topic, but emerge from discussions with colleagues and from practical experience. A further complication for microbial or pathogen populations is the frequent observation of clonality or partial clonality. Clonality invariably makes analyses of population data difficult because many assumptions underlying the theory from which analysis methods were derived are often violated. This review provides practical guidance on how to navigate through the complex web of data analyses of pathogens that may violate typical population genetics assumptions. We also provide resources and examples for analysis in the R programming environment.

Efficiency of ddRAD target enriched sequencing across spiny rock lobster species (Palinuridae: Jasus)

Double digest restriction site-associated DNA sequencing (ddRADseq) and target capture sequencing methods are used to explore population and phylogenetic questions in non-model organisms. ddRADseq offers a simple and reliable protocol for population genomic studies, however it can result in a large amount of missing data due to allelic dropout. Target capture sequencing offers an opportunity to increase sequencing coverage with little missing data and consistent orthologous loci across samples, although this approach has generally been applied to conserved markers for deeper evolutionary questions. Here, we combine both methods to generate high quality sequencing data for population genomic studies of all marine lobster species from the genus Jasus. We designed probes based on ddRADseq libraries of two lobster species (Jasus edwardsii and Sagmariasus verreauxi) and evaluated the captured sequencing data in five other Jasus species. We validated 4,465 polymorphic loci amongst these species using a cost effective sequencing protocol, of which 1,730 were recovered from all species, and 4,026 were present in at least three species. The method was also successfully applied to DNA samples obtained from museum specimens. This data will be further used to assess spatial-temporal genetic variation in Jasus species found in the Southern Hemisphere.

Optimized double-digest genotyping by sequencing (ddGBS) method with high-density SNP markers and high genotyping accuracy for chickens

High-density single nucleotide polymorphism (SNP) markers are crucial to improve the resolution and accuracy of genome-wide association study (GWAS) and genomic selection (GS). Numerous approaches, including whole genome sequencing, genome sampling sequencing, and SNP chips are able to discover or genotype markers at different densities and costs. Achieving an optimal balance between sequencing resolution and budgets, especially in large-scale population genetics research, constitutes a major challenge. Here, we performed improved double-enzyme digestion genotyping by sequencing (ddGBS) on chicken. We evaluated eight double-enzyme digestion combinations, and EcoR I- Mse I was chosen as the optimal combination for the chicken genome. We firstly proposed that two parameters, optimal read-count point (ORP) and saturated read-count point (SRP), could be utilized to determine the optimal sequencing volume. A total of 291,772 high-density SNPs from 824 animals were identified. By validation using the SNP chip, we found that the consistency between ddGBS data and the SNP chip is over 99%. The approach that we developed in chickens, which is high-quality, high-density, cost-effective (300 K, $30/sample), and time-saving (within 48 h), will have broad applications in animal breeding programs.

Genetic load in marine animals: a review

Marine invertebrates and fish are well known for their remarkable genetic diversity, which is commonly explained by large population size and the characteristic dispersive nature of their early, planktonic life history. Other potential sources of diversity in marine animals, such as a higher mutation rate, have been much less considered, though evidence for a high genetic load in marine bivalves has been accumulating for nearly half a century. In this review, I examine evidence for a higher genetic load in marine animals from studies of molecular marker segregation and linkage over the last 40 years, and survey recent work examining mutational load with molecular evolution approaches. Overall, marine animals appear to have higher genetic load than terrestrial animals (higher dn/ds ratios, inbreeding load, and segregation dis`tortion), though results are mixed for marine fish and data are lacking for many marine animal groups. Bivalves (oysters) have the highest loads observed among marine animals, comparable only to long-lived plants; however, more data is needed from other bivalves and more marine invertebrate taxa generally. For oysters, a higher load may be related to a chronically lower effective population size that, in concert with a higher mutational rate, elevate the number of deleterious mutations observed. I suggest that future studies use high-throughput sequencing approaches to examine (1) polymorphism in genome-scale datasets across a wider range of marine animals at the population level and (2) intergenerational mutational changes between parents and offspring in crosses of aquaculture species to quantify mutation rates.

How and how much does RAD-seq bias genetic diversity estimates?

BACKGROUND

RAD-seq is a powerful tool, increasingly used in population genomics. However, earlier studies have raised red flags regarding possible biases associated with this technique. In particular, polymorphism on restriction sites results in preferential sampling of closely related haplotypes, so that RAD data tends to underestimate genetic diversity.

RESULTS

Here we (1) clarify the theoretical basis of this bias, highlighting the potential confounding effects of population structure and selection, (2) confront predictions to real data from in silico digestion of full genomes and (3) provide a proof of concept toward an ABC-based correction of the RAD-seq bias. Under a neutral and panmictic model, we confirm the previously established relationship between the true polymorphism and its RAD-based estimation, showing a more pronounced bias when polymorphism is high. Using more elaborate models, we show that selection, resulting in heterogeneous levels of polymorphism along the genome, exacerbates the bias and leads to a more pronounced underestimation. On the contrary, spatial genetic structure tends to reduce the bias. We confront the neutral and panmictic model to "ideal" empirical data (in silico RAD-sequencing) using full genomes from natural populations of the fruit fly Drosophila melanogaster and the fungus Shizophyllum commune, harbouring respectively moderate and high genetic diversity. In D. melanogaster, predictions fit the model, but the small difference between the true and RAD polymorphism makes this comparison insensitive to deviations from the model. In the highly polymorphic fungus, the model captures a large part of the bias but makes inaccurate predictions. Accordingly, ABC corrections based on this model improve the estimations, albeit with some imprecisions.

CONCLUSION

The RAD-seq underestimation of genetic diversity associated with polymorphism in restriction sites becomes more pronounced when polymorphism is high. In practice, this means that in many systems where polymorphism does not exceed 2 %, the bias is of minor importance in the face of other sources of uncertainty, such as heterogeneous bases composition or technical artefacts. The neutral panmictic model provides a practical mean to correct the bias through ABC, albeit with some imprecisions. More elaborate ABC methods might integrate additional parameters, such as population structure and selection, but their opposite effects could hinder accurate corrections.

Linking genomics and population genetics with R

Population genetics and genomics have developed and been treated as independent fields of study despite having common roots. The continuous progress of sequencing technologies is contributing to (re-)connect these two disciplines. We review the challenges faced by data analysts and software developers when handling very big genetic data sets collected on many individuals. We then expose how r, as a computing language and development environment, proposes some solutions to meet these challenges. We focus on some specific issues that are often encountered in practice: handling and analysing single-nucleotide polymorphism data, handling and reading variant call format files, analysing haplotypes and linkage disequilibrium and performing multivariate analyses. We illustrate these implementations with some analyses of three recently published data sets that contain between 60 000 and 1 000 000 loci. We conclude with some perspectives on future developments of r software for population genomics.