Recent advances in conservation and population genomics data analysis

FecalSeq enrichment with RAD Sequencing from non-invasive environmental samples holds promise for genetic monitoring of an imperiled lagomorph

Despite advances in genomic sequencing and bioinformatics, conservation genomics is still often hindered by a reliance on non-invasive samples. The presence of exogenous DNA and the low quantity and poor quality of DNA in non-invasive samples have been a roadblock to sequencing, thereby limiting the potential for genomic monitoring of endangered species. Recent molecular advances, such as host DNA enrichment, hold promise for facilitating sequencing from non-invasive samples. We used the FecalSeq method to enrich DNA extracted from wild-collected fecal pellets of the imperiled New England cottontail and identified SNPs from 3RAD Sequencing. We obtained SNPs from rabbit pellets, including pellets that were collected in poor environmental conditions and samples that performed poorly with microsatellites. Measures of sequencing success improved with greater amounts of starting DNA and 32% of samples generated SNP genotypes that passed quality control filtering. Genotyping error rates were high, however, and the approach was unable to consistently distinguish unique individuals or matching genotypes, while it was suitable for recovering the expected population structure. Pairing FecalSeq enrichment with RADseq is a promising low-cost method for monitoring wild populations using non-invasive samples in an environmental context, but it may be better suited for informing conservation through population genomics.

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).

Low-coverage sequencing and Wahlund effect severely bias estimates of inbreeding, heterozygosity and effective population size in North American wolves

vonHoldt et al. ((2024), Molecular Ecology, 33, e17231) (vH24) used low-coverage (average ~ 7X read depth) restriction site-associated DNA sequence data to estimate individual inbreeding and heterozygosity, and recent effective population size (Ne), in Great Lakes (GL) and Northern Rocky Mountain (RM) wolves. They concluded that RM heterozygosity rapidly declined between 1991 and 2020, and that Ne declined substantially in GL and RM over the last 50 generations. Here, we evaluate the effects of low sequence coverage and sampling strategy on vH24's findings and provide general recommendations for using sequence data to evaluate inbreeding, heterozygosity and Ne. Low-coverage sequencing resulted in downwardly biased estimates of individual inbreeding and heterozygosity, and an erroneous large temporal decline in RM heterozygosity due to declining read depth through time. Additionally, vH24's sampling strategy-which combined individuals from several genetically differentiated populations and across at least eight wolf generations-is expected to have resulted in severe downward bias in estimates of recent Ne for RM. We recommend using high-coverage sequence data (≥ $$ \ge $$ 15-20X) to estimate inbreeding and heterozygosity. Carefully filtering individuals, loci and genotypes, and using genotype imputation or likelihoods can help to minimise bias when low-coverage sequence data must be used. For estimation of contemporary Ne, the marginal benefits of using more than 103-104 loci are small, so aggressive filtering of loci with low average read depth potentially can retain most individuals without sacrificing much precision. Individuals are relatively more valuable than loci because analyses of contemporary Ne should focus on roughly single-generation samples from local breeding populations.

Influence of molecular marker type on estimating effective population size and other genetic parameters in a critically endangered parrot

Genetics is a fast-moving field, and for conservation practitioners or ecologists, it can be bewildering. The choice of marker used in studies is fundamental; in the literature, preference has recently shifted from microsatellites to single nucleotide polymorphism (SNP) loci. Understanding how marker type affects estimates of population genetic parameters is important in the context of conservation, especially because the accuracy of estimates has a bearing on the actions taken to protect threatened species. We compare parameter estimates between seven microsatellites, 3761 SNP loci, and a random subset of 100 SNPs for the exact same 324 individual swift parrots, Lathamus discolor, and also use 457 additional samples from subsequent years to compare SNP estimates. Both marker types estimated a lower H O than H E. We show that microsatellites and SNPs mainly indicate a lack of spatial genetic structure, except when a priori collection locations were used on the SNP data in a discriminant analysis of principal components (DAPC). The 100-SNP subset gave comparable results to when the full dataset was used. Estimates of effective population size (N e) were comparable between markers when the same individuals were considered, but SNPs had narrower confidence intervals. This is reassuring because conservation assessments that rely on population genetic estimates based on a few microsatellites are unlikely to be nullified by the general shift toward SNPs in the literature. However, estimates between markers and datasets varied considerably when only adult samples were considered; hence, including samples of all age groups is recommended to be used when available. The estimated N e was higher for the full SNP dataset (2010-2019) than the smaller comparison data (2010-2015), which might be a better reflection of the species status. The lower precision of microsatellites may not necessarily be a barrier for most conservation applications; however, SNPs will improve confidence limits, which may be useful for practitioners.

Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples

Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Multiplexed targeted amplicon sequencing techniques, such as genotyping-in-thousands by sequencing (GT-seq), can provide cost-effective approaches for collecting genetic data from low-quality and quantity DNA samples, making them potentially useful for long-term wildlife monitoring using non-invasive and archival samples. Here, we developed a GT-seq panel as a potential monitoring tool for the American pika (Ochotona princeps) and evaluated its performance when applied to traditional, non-invasive, and archival samples, respectively. Specifically, we optimized a GT-seq panel (307 single nucleotide polymorphisms (SNPs)) that included neutral, sex-associated, and putatively adaptive SNPs using contemporary tissue samples (n = 77) from the Northern Rocky Mountains lineage of American pikas. The panel demonstrated high genotyping success (94.7%), low genotyping error (0.001%), and excellent performance identifying individuals, sex, relatedness, and population structure. We subsequently applied the GT-seq panel to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) collected within the Canadian Rocky Mountains to evaluate its effectiveness. Although the panel demonstrated high efficacy with archival tissue samples (90.5% genotyping success, 0.0% genotyping error), this was not the case for the fecal pellet samples (79.7% genotyping success, 28.4% genotyping error) likely due to the exceptionally low quality/quantity of recovered DNA using the approaches implemented. Overall, our study reinforced GT-seq as an effective tool using contemporary and archival tissue samples, providing future opportunities for temporal applications using historical specimens. Our results further highlight the need for additional optimization of sample and genetic data collection techniques prior to broader-scale implementation of a non-invasive genetic monitoring tool for American pikas.

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.

A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics

The increasing availability of genomic resequencing data sets and high-quality reference genomes across the tree of life present exciting opportunities for comparative population genomic studies. However, substantial challenges prevent the simple reuse of data across different studies and species, arising from variability in variant calling pipelines, data quality, and the need for computationally intensive reanalysis. Here, we present snpArcher, a flexible and highly efficient workflow designed for the analysis of genomic resequencing data in nonmodel organisms. snpArcher provides a standardized variant calling pipeline and includes modules for variant quality control, data visualization, variant filtering, and other downstream analyses. Implemented in Snakemake, snpArcher is user-friendly, reproducible, and designed to be compatible with high-performance computing clusters and cloud environments. To demonstrate the flexibility of this pipeline, we applied snpArcher to 26 public resequencing data sets from nonmammalian vertebrates. These variant data sets are hosted publicly to enable future comparative population genomic analyses. With its extensibility and the availability of public data sets, snpArcher will contribute to a broader understanding of genetic variation across species by facilitating the rapid use and reuse of large genomic data sets.

Global determinants of insect mitochondrial genetic diversity

Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth's biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.

Importance of timely metadata curation to the global surveillance of genetic diversity

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.

Recent Advances in Genetics and Genomics of Snub-Nosed Monkeys (Rhinopithecus) and Their Implications for Phylogeny, Conservation, and Adaptation

The snub-nosed monkey genus Rhinopithecus (Colobinae) comprises five species (Rhinopithecus roxellana, Rhinopithecus brelichi, Rhinopithecus bieti, Rhinopithecus strykeri, and Rhinopithecus avunculus). They are range-restricted species occurring only in small areas in China, Vietnam, and Myanmar. All extant species are listed as endangered or critically endangered by the International Union for Conservation of Nature (IUCN) Red List, all with decreasing populations. With the development of molecular genetics and the improvement and cost reduction in whole-genome sequencing, knowledge about evolutionary processes has improved largely in recent years. Here, we review recent major advances in snub-nosed monkey genetics and genomics and their impact on our understanding of the phylogeny, phylogeography, population genetic structure, landscape genetics, demographic history, and molecular mechanisms of adaptation to folivory and high altitudes in this primate genus. We further discuss future directions in this research field, in particular how genomic information can contribute to the conservation of snub-nosed monkeys.

Implications of past and present genetic connectivity for management of the saltwater crocodile ( Crocodylus porosus )

Effective management of protected species requires information on appropriate evolutionary and geographic population boundaries and knowledge of how the physical environment and life-history traits combine to shape the population structure and connectivity. Saltwater crocodiles (Crocodylus porosus) are the largest and most widely distributed of living crocodilians, extending from Sri Lanka to Southeast Asia and down to northern Australia. Given the long-distance movement capabilities reported for C. porosus, management units are hypothesised to be highly connected by migration. However, the magnitude, scale, and consistency of connection across managed populations are not fully understood. Here we used an efficient genotyping method that combines DArTseq and sequence capture to survey ≈ 3000 high-quality genome-wide single nucleotide polymorphisms from 1176 C. porosus sampled across nearly the entire range of the species in Queensland, Australia. We investigated historical and present-day connectivity patterns using fixation and diversity indices coupled with clustering methods and the spatial distribution of kin pairs. We inferred kinship using forward simulation coupled with a kinship estimation method that is robust to unspecified population structure. The results demonstrated that the C. porosus population has substantial genetic structure with six broad populations correlated with geographical location. The rate of gene flow was highly correlated with spatial distance, with greater differentiation along the east coast compared to the west. Kinship analyses revealed evidence of reproductive philopatry and limited dispersal, with approximately 90% of reported first and second-degree relatives showing a pairwise distance of <50 km between sampling locations. Given the limited dispersal, lack of suitable habitat, low densities of crocodiles and the high proportion of immature animals in the population, future management and conservation interventions should be considered at regional and state-wide scales.

Population Subdivision in the Gopher Frog (Rana capito) across the Fragmented Longleaf Pine-Wiregrass Savanna of the Southeastern USA

Delineating genetically distinct population segments of threatened species and quantifying population connectivity are important steps in developing effective conservation and management strategies aimed at preventing extinction. The gopher frog (Rana capito) is a xeric-adapted, pond-breeding species endemic to the Gulf and Atlantic coastal plains of the southeastern United States. This species has experienced extensive habitat loss and fragmentation in the formerly widespread longleaf pine-wiregrass savanna where it lives, resulting in individual abundance declines and population extinctions throughout its range. We used individual-based clustering methods along with Bayesian inference of historical migration based on almost 1500 multilocus microsatellite genotypes to examine genetic structure in this taxon. Clustering analyses identified panhandle and peninsular populations in Florida as distinct genetic clusters separated by the Aucilla River, consistent with the division between the Coastal Plain and peninsular mitochondrial lineages, respectively. Analysis of historical migration indicated an east–west population divergence event followed by immigration to the east. Together, our results indicate that the genetically distinct Coastal Plain and peninsular Florida lineages should be considered separately for conservation and management purposes.

Evolutionary genomics: Insights from the invasive European starlings

Two fundamental questions for evolutionary studies are the speed at which evolution occurs, and the way that this evolution may present itself within an organism's genome. Evolutionary studies on invasive populations are poised to tackle some of these pressing questions, including understanding the mechanisms behind rapid adaptation, and how it facilitates population persistence within a novel environment. Investigation of these questions are assisted through recent developments in experimental, sequencing, and analytical protocols; in particular, the growing accessibility of next generation sequencing has enabled a broader range of taxa to be characterised. In this perspective, we discuss recent genetic findings within the invasive European starlings in Australia, and outline some critical next steps within this research system. Further, we use discoveries within this study system to guide discussion of pressing future research directions more generally within the fields of population and evolutionary genetics, including the use of historic specimens, phenotypic data, non-SNP genetic variants (e.g., structural variants), and pan-genomes. In particular, we emphasise the need for exploratory genomics studies across a range of invasive taxa so we can begin understanding broad mechanisms that underpin rapid adaptation in these systems. Understanding how genetic diversity arises and is maintained in a population, and how this contributes to adaptability, requires a deep understanding of how evolution functions at the molecular level, and is of fundamental importance for the future studies and preservation of biodiversity across the globe.

Is the genomics 'cart' before the restoration ecology 'horse'? Insights from qualitative interviews and trends from the literature

Harnessing new technologies is vital to achieve global imperatives to restore degraded ecosystems. We explored the potential of genomics as one such tool. We aimed to understand barriers hindering the uptake of genomics, and how to overcome them, via exploratory interviews with leading scholars in both restoration and its sister discipline of conservation-a discipline that has successfully leveraged genomics. We also conducted an examination of research trends to explore some insights that emerged from the interviews, including publication trends that have used genomics to address restoration and conservation questions. Our qualitative findings revealed varied perspectives on harnessing genomics. For example, scholars in restoration without genomics experience felt genomics was over-hyped. Scholars with genomics experience emphatically emphasized the need to proceed cautiously in using genomics in restoration. Both genomics-experienced and less-experienced scholars called for case studies to demonstrate the benefits of genomics in restoration. These qualitative data contrasted with our examination of research trends, which revealed 70 restoration genomics studies, particularly studies using environmental DNA as a monitoring tool. We provide a roadmap to facilitate the uptake of genomics into restoration, to help the restoration sector meet the monumental task of restoring huge areas to biodiverse and functional ecosystems. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

Evaluating sources of bias in pedigree-based estimates of breeding population size

Applications of genetic-based estimates of population size are expanding, especially for species for which traditional demographic estimation methods are intractable due to the rarity of adult encounters. Estimates of breeding population size (N_S ) are particularly amenable to genetic-based approaches as the parameter can be estimated using pedigrees reconstructed from genetic data gathered from discrete juvenile cohorts, therefore eliminating the need to sample adults in the population. However, a critical evaluation of how genotyping and sampling effort influence bias in pedigree reconstruction, and how these biases subsequently influence estimates of N_S , is needed to evaluate the efficacy of the approach under a range of scenarios. We simulated a model system to understand the interactive effects of genotyping and sampling effort on error in genetic pedigrees reconstructed from the program COLONY. We then evaluated how errors in pedigree reconstruction influenced bias and precision in estimates of N_S using three different rarefaction estimators. Results indicated that pedigree error can be minimal when adequate genetic data are available, such as when juvenile sample sizes are large and/or individuals are genotyped at many informative loci. However, even in cases for which data are limited, using results of the simulation analysis to understand the magnitude and sources of bias in reconstructed pedigrees can still be informative when estimating N_S . We applied results of the simulation analysis to evaluate N ̂ $$ \hat{N} $$ _S for a population of federally endangered Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) in the Delaware River, USA. Our results indicated that N_S is likely to be three orders of magnitude lower compared with historic breeding population sizes, which is a considerable advancement in our understanding of the population status of Atlantic sturgeon in the Delaware River. Our analyses are broadly applicable in the design and interpretation of studies seeking to estimate N_S and can help to guide conservation decisions when ecological uncertainty is high. The utility of these results is expected to grow as rapid advances in genetic technologies increase the popularity of genetic population monitoring and estimation.

Genomics of Serrasalmidae teleosts through the lens of microbiome fingerprinting

Associations between host genotype and host-associated microbiomes have been shown in a variety of animal clades, but studies on teleosts mostly show weak associations. Our study aimed to explore these relationships in four sympatric Serrasalmidae (i.e. piranha) teleosts from an Amazonian lake, using datasets from the hosts genomes (SNPs from GBS), skin and gut microbiomes (16S rRNA gene metataxonomics), and diets (COI metabarcoding) from the same fish individuals. Firstly, we investigated whether there were significant covariations of microbiome and fish genotypes at the inter and intraspecific levels. We also assessed the extent of co-variation between Serrasalmidae diet and microbiome, to isolate genotypic from dietary effects on community structure. We observed a significant covariation of skin microbiomes and host genotypes at interspecific (R² =24.4%) and intraspecific (R² =6.2%) levels, whereas gut microbiomes correlated poorly with host genotypes. Serrasalmidae diet composition was significantly correlated to fish genotype only at the interspecific level (R² =5.4%), but did not covary with gut microbiome composition (mantel R=-0.04). Secondly, we investigated whether the study of interspecific differentiation could benefit from considering host associated microbial communities in addition to host genotypes. By using a NMDS ordination-based approach, we observed that ordinations from skin and gut species-specific bacterial biomarkers identified through a random forest algorithm, could significantly increase the average interspecific differentiation detected through host genotype data alone. Although future studies encompassing additional species and environments are needed, our results suggest Serrasalmidae microbiomes could constitute an insightful trait to be considered when studying the interspecific differences between members of this clade.

Commonly used Hardy-Weinberg equilibrium filtering schemes impact population structure inferences using RADseq data

Reduced representation sequencing (RRS) is a widely used method to assay the diversity of genetic loci across the genome of an organism. The dominant class of RRS approaches assay loci associated with restriction sites within the genome (restriction site associated DNA sequencing, or RADseq). RADseq is frequently applied to non‐model organisms since it enables population genetic studies without relying on well‐characterized reference genomes. However, RADseq requires the use of many bioinformatic filters to ensure the quality of genotyping calls. These filters can have direct impacts on population genetic inference, and therefore require careful consideration. One widely used filtering approach is the removal of loci that do not conform to expectations of Hardy–Weinberg equilibrium (HWE). Despite being widely used, we show that this filtering approach is rarely described in sufficient detail to enable replication. Furthermore, through analyses of in silico and empirical data sets we show that some of the most widely used HWE filtering approaches dramatically impact inference of population structure. In particular, the removal of loci exhibiting departures from HWE after pooling across samples significantly reduces the degree of inferred population structure within a data set (despite this approach being widely used). Based on these results, we provide recommendations for best practice regarding the implementation of HWE filtering for RADseq data sets.

Landscape connectivity and genetic structure in a mainstem and a tributary stonefly (Plecoptera) species using a novel reference genome

Understanding how environmental variation influences population genetic structure can help predict how environmental change influences population connectivity, genetic diversity, and evolutionary potential. We used riverscape genomics modelling to investigate how climatic and habitat variables relate to patterns of genetic variation in two stonefly species, one from mainstem river habitats (Sweltsa coloradensis) and one from tributaries (Sweltsa fidelis) in 40 sites in northwest Montana, USA. We produced a draft genome assembly for S. coloradensis (N50 = 0.251 Mbp, BUSCO &gt; 95% using “insecta_ob9” reference genes). We genotyped 1930 SNPs in 372 individuals for S. coloradensis and 520 SNPs in 153 individuals for S. fidelis. We found higher genetic diversity for S. coloradensis compared to S. fidelis, but nearly identical genetic differentiation among sites within each species (both had global loci median FST = 0.000), despite differences in stream network location. For landscape genomics and testing for selection, we produced a less stringently filtered data set (3454 and 1070 SNPs for S. coloradensis and S. fidelis, respectively). Environmental variables (mean summer precipitation, slope, aspect, mean June stream temperature, land cover type) were correlated with 19 putative adaptive loci for S. coloradensis. but there was only one putative adaptive locus for S. fidelis (correlated with aspect). Interestingly, we also detected potential hybridization between multiple Sweltsa species which has never been previously detected. Studies like ours, that test for adaptive variation in multiple related species are needed to help assess landscape connectivity and the vulnerability of populations and communities to environmental change.

Divergence With Gene Flow and Contrasting Population Size Blur the Species Boundary in Cycas Sect. Asiorientales, as Inferred From Morphology and RAD-Seq Data

The divergence process of incipient species is fascinating but elusive by incomplete lineage sorting or gene flow. Species delimitation is also challenging among those morphologically similar allopatric species, especially when lacking comprehensive data. Cycas sect. Asiorientales, comprised of C. taitungensis and C. revoluta in the Ryukyu Archipelago and Taiwan, diverged recently with continuous gene flow, resulting in a reciprocal paraphyletic relationship. Their previous evolutionary inferences are questioned from few genetic markers, incomplete sampling, and incomprehensive morphological comparison by a long-term taxonomic misconception. By whole range sampling, this study tests the geographic mode of speciation in the two species of Asiorientales by approximate Bayesian computation (ABC) using genome-wide single nucleotide polymorphisms (SNPs). The individual tree was reconstructed to delimit the species and track the gene-flow trajectory. With the comparison of diagnostic morphological traits and genetic data, the allopatric speciation was rejected. Alternatively, continuous but spatially heterogeneous gene flow driven by transoceanic vegetative dispersal and pollen flow with contrasting population sizes blurred their species boundary. On the basis of morphological, genetic, and evolutionary evidence, we synonymized these two Cycas species. This study highlights not only the importance of the Kuroshio Current to species evolution but also the disadvantage of using species with geographically structured genealogies as conservation units.

Whole genome sequencing and the application of a SNP panel reveal primary evolutionary lineages and genomic variation in the lion (Panthera leo)

Background

Previous phylogeographic studies of the lion (Panthera leo) have improved our insight into the distribution of genetic variation, as well as a revised taxonomy which now recognizes a northern (Panthera leo leo) and a southern (Panthera leo melanochaita) subspecies. However, existing whole range phylogeographic studies on lions either consist of very limited numbers of samples, or are focused on mitochondrial DNA and/or a limited set of microsatellites. The geographic extent of genetic lineages and their phylogenetic relationships remain uncertain, clouded by massive sampling gaps, sex-biased dispersal and incomplete lineage sorting.

Results

In this study we present results of low depth whole genome sequencing and subsequent variant calling in ten lions sampled throughout the geographic range, resulting in the discovery of >150,000 Single Nucleotide Polymorphisms (SNPs). Phylogenetic analyses revealed the same basal split between northern and southern populations, as well as four population clusters on a more local scale. Further, we designed a SNP panel, including 125 autosomal and 14 mitochondrial SNPs, which was tested on >200 lions from across their range. Results allow us to assign individuals to one of these four major clades (West & Central Africa, India, East Africa, or Southern Africa) and delineate these clades in more detail.

Conclusions

The results presented here, particularly the validated SNP panel, have important applications, not only for studying populations on a local geographic scale, but also for tracing samples of unknown origin for forensic purposes, and for guiding conservation management of ex situ populations. Thus, these genomic resources not only contribute to our understanding of the evolutionary history of the lion, but may also play a crucial role in conservation efforts aimed at protecting the species in its full diversity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08510-y.

Gene Pool Boundaries for the Yosemite Toad (Anaxyrus canorus) Reveal Asymmetrical Migration Within Meadow Neighborhoods

The Yosemite toad (Anaxyrus [Bufo] canorus) is a federally threatened species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. The species is one of the first amphibians to undergo a large demographic collapse that was well-documented, and is reputed to remain in low abundance throughout its range. Recent phylogeographic work has demonstrated that Pleistocene toad lineages diverged and then admixed to differing extents across an elevational gradient. Although lineage divisions may have significant effects on evolutionary trajectories over large spatial and temporal scales, present-day population dynamics must be delineated in order to manage and conserve the species effectively. In this study, we used a double-digest RADseq dataset to address three primary questions: (1) Are single meadows or neighborhoods of nearby meadows most correlated with population boundaries? (2) Does asymmetrical migration occur among neighborhoods of nearby meadows? (3) What topographic or hydrological variables predict such asymmetrical migration in these meadow neighborhoods? Hierarchical STRUCTURE and AMOVA analyses suggested that populations are typically circumscribed by a single meadow, although 84% of meadows exist in neighborhoods of at least two meadows connected by low levels of migration, and over half (53%) of neighborhoods examined display strong asymmetrical migration. Meadow neighborhoods often contain one or more large and flat “hub” meadows that experience net immigration, surrounded by smaller and topographically rugged “satellite” meadows with net emigration. Hubs tend to contain more genetic diversity and could be prioritized for conservation and habitat management and as potential sources for reestablishment efforts.

Demographic decline and lineage-specific adaptations characterize New Zealand kiwi

Small and fragmented populations may become rapidly differentiated due to genetic drift, making it difficult to distinguish whether neutral genetic structure is a signature of recent demographic events, or of long-term evolutionary processes that could have allowed populations to adaptively diverge. We sequenced 52 whole genomes to examine Holocene demographic history and patterns of adaptation in kiwi (Apteryx), and recovered 11 strongly differentiated genetic clusters corresponding to previously recognized lineages. Demographic models suggest that all 11 lineages experienced dramatic population crashes relative to early- or mid-Holocene levels. Small population size is associated with low genetic diversity and elevated genetic differentiation (FST), suggesting that population declines have strengthened genetic structure and led to the loss of genetic diversity. However, population size is not correlated with inbreeding rates. Eight lineages show signatures of lineage-specific selective sweeps (284 sweeps total) that are unlikely to have been caused by demographic stochasticity. Overall, these results suggest that despite strong genetic drift associated with recent bottlenecks, most kiwi lineages possess unique adaptations and should be recognized as separate adaptive units in conservation contexts. Our work highlights how whole-genome datasets can address longstanding uncertainty about the evolutionary and conservation significance of small and fragmented populations of threatened species.

Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub

The spatial structure of genomic and phenotypic variation across populations reflects historical and demographic processes as well as evolution via natural selection. Characterizing such variation can provide an important perspective for understanding the evolutionary consequences of changing climate and for guiding ecological restoration. While evidence for local adaptation has been traditionally evaluated using phenotypic data, modern methods for generating and analyzing landscape genomic data can directly quantify local adaptation by associating allelic variation with environmental variation. Here, we analyze both genomic and phenotypic variation of rubber rabbitbrush (Ericameria nauseosa), a foundational shrub species of western North America. To quantify landscape genomic structure and provide perspective on patterns of local adaptation, we generated reduced representation sequencing data for 17 wild populations (222 individuals; 38,615 loci) spanning a range of environmental conditions. Population genetic analyses illustrated pronounced landscape genomic structure jointly shaped by geography and environment. Genetic-environment association (GEA) analyses using both redundancy analysis (RDA) and a machine-learning approach (Gradient Forest) indicated environmental variables (precipitation seasonality, slope, aspect, elevation, and annual precipitation) influenced spatial genomic structure and were correlated with allele frequency shifts indicative of local adaptation at a consistent set of genomic regions. We compared our GEA-based inference of local adaptation with phenotypic data collected by growing seeds from each population in a greenhouse common garden. Population differentiation in seed weight, emergence, and seedling traits was associated with environmental variables (e.g., precipitation seasonality) that were also implicated in GEA analyses, suggesting complementary conclusions about the drivers of local adaptation across different methods and data sources. Our results provide a baseline understanding of spatial genomic structure for E. nauseosa across the western Great Basin and illustrate the utility of GEA analyses for detecting the environmental causes and genetic signatures of local adaptation in a widely distributed plant species of restoration significance.

Genomic signatures of inbreeding in a critically endangered parrot, the kākāpō

Events of inbreeding are inevitable in critically endangered species. Reduced population sizes and unique life-history traits can increase the severity of inbreeding, leading to declines in fitness and increased risk of extinction. Here, we investigate levels of inbreeding in a critically endangered flightless parrot, the kākāpō (Strigops habroptilus), wherein a highly inbred island population and one individual from the mainland of New Zealand founded the entire extant population. Genotyping-by-sequencing (GBS), and a genotype calling approach using a chromosome-level genome assembly, identified a filtered set of 12,241 single-nucleotide polymorphisms (SNPs) among 161 kākāpō, which together encompass the total genetic potential of the extant population. Multiple molecular-based estimates of inbreeding were compared, including genome-wide estimates of heterozygosity (FH), the diagonal elements of a genomic-relatedness matrix (FGRM), and runs of homozygosity (RoH, FRoH). In addition, we compared levels of inbreeding in chicks from a recent breeding season to examine if inbreeding is associated with offspring survival. The density of SNPs generated with GBS was sufficient to identify chromosomes that were largely homozygous with RoH distributed in similar patterns to other inbred species. Measures of inbreeding were largely correlated and differed significantly between descendants of the two founding populations. However, neither inbreeding nor ancestry was found to be associated with reduced survivorship in chicks, owing to unexpected mortality in chicks exhibiting low levels of inbreeding. Our study highlights important considerations for estimating inbreeding in critically endangered species, such as the impacts of small population sizes and admixture between diverse lineages.

Local climate adaptation and gene flow in the native range of two co-occurring fruit moths with contrasting invasiveness

Invasive species pose increasing threats to global biodiversity and ecosystems. While previous studies have characterized successful invaders based on ecological traits, characteristics related to evolutionary processes have rarely been investigated. Here we compared gene flow and local adaptation using demographic analyses and outlier tests in two co-occurring moth pests across their common native range of China, one of which (the peach fruit moth, Carposina sasakii) has maintained its native distribution, while the other (the oriental fruit moth, Grapholita molesta) has expanded its range globally during the past century. We found that both species showed a pattern of genetic differentiation and an evolutionary history consistent with a common southwestern origin and northward expansion in their native range. However, for the noninvasive species, genetic differentiation was closely aligned with the environment, and there was a relatively low level of gene flow, whereas in the invasive species, genetic differentiation was associated with geography. Genome scans indicated stronger patterns of climate-associated loci in the noninvasive species. While strong local adaptation and reduced gene flow across its native range may have decreased the invasiveness of C. sasakii, this requires further validation with additional comparisons of invasive and noninvasive species across their native range.

Whole genome sequencing reveals high differentiation, low levels of genetic diversity and short runs of homozygosity among Swedish wels catfish

The use of genetic markers in the context of conservation is largely being outcompeted by whole-genome data. Comparative studies between the two are sparse, and the knowledge about potential effects of this methodology shift is limited. Here, we used whole-genome sequencing data to assess the genetic status of peripheral populations of the wels catfish (Silurus glanis), and discuss the results in light of a recent microsatellite study of the same populations. The Swedish populations of the wels catfish have suffered from severe declines during the last centuries and persists in only a few isolated water systems. Fragmented populations generally are at greater risk of extinction, for example due to loss of genetic diversity, and may thus require conservation actions. We sequenced individuals from the three remaining native populations (Båven, Emån, and Möckeln) and one reintroduced population of admixed origin (Helge å), and found that genetic diversity was highest in Emån but low overall, with strong differentiation among the populations. No signature of recent inbreeding was found, but a considerable number of short runs of homozygosity were present in all populations, likely linked to historically small population sizes and bottleneck events. Genetic substructure within any of the native populations was at best weak. Individuals from the admixed population Helge å shared most genetic ancestry with the Båven population (72%). Our results are largely in agreement with the microsatellite study, and stresses the need to protect these isolated populations at the northern edge of the distribution of the species.

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.

Limits and convergence properties of the sequentially Markovian coalescent

Several methods based on the sequentially Markovian coalescent (SMC) make use of full genome sequence data from samples to infer population demographic history including past changes in population size, admixture, migration events and population structure. More recently, the original theoretical framework has been extended to allow the simultaneous estimation of population size changes along with other life history traits such as selfing or seed banking. The latter developments enhance the applicability of SMC methods to nonmodel species. Although convergence proofs have been given using simulated data in a few specific cases, an in-depth investigation of the limitations of SMC methods is lacking. In order to explore such limits, we first develop a tool inferring the best case convergence of SMC methods assuming the true underlying coalescent genealogies are known. This tool can be used to quantify the amount and type of information that can be confidently retrieved from given data sets prior to the analysis of the real data. Second, we assess the inference accuracy when the assumptions of SMC approaches are violated due to departures from the model, namely the presence of transposable elements, variable recombination and mutation rates along the sequence, and SNP calling errors. Third, we deliver a new interpretation of SMC methods by highlighting the importance of the transition matrix, which we argue can be used as a set of summary statistics in other statistical inference methods, uncoupling the SMC from hidden Markov models (HMMs). We finally offer recommendations to better apply SMC methods and build adequate data sets under budget constraints.

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.

Scale-dependent signatures of local adaptation in a foundation tree species

Understanding local adaptation is critical for conservation management under rapidly changing environmental conditions. Local adaptation inferred from genotype-environment associations may show different genomic patterns depending on the spatial scale of sampling, due to differences in the slope of environmental gradients and the level of gene flow. We compared signatures of local adaptation across the genome of mountain ash (Eucalyptus regnans) at two spatial scales: A species-wide data set and a topographically-complex subregional data set. We genotyped 367 individual trees at over 3700 single-nucleotide polymorphisms (SNPs), quantified patterns of spatial genetic structure among populations, and used two analytical methods to identify loci associated with at least one of three environmental variables at each spatial scale. Together, the analyses identified 549 potentially adaptive SNPs at the subregion scale, and 435 SNPs at the range-wide scale. A total of 39 genic or near-genic SNPs, associated with 28 genes, were identified at both spatial scales, although no SNP was identified by both methods at both scales. We observed that nongenic regions had significantly higher homozygote excess than genic regions, possibly due to selective elimination of inbred genotypes during stand development. Our results suggest that strong environmental selection occurs in mountain ash, and that the identification of putatively adaptive loci can differ substantially depending on the spatial scale of analyses. We also highlight the importance of multiple adaptive genetic architectures for understanding patterns of local adaptation across large heterogenous landscapes, with comparison of putatively adaptive loci among spatial scales providing crucial insights into the process of adaptation.

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.

Thermal adaptation rather than demographic history drives genetic structure inferred by copy number variants in a marine fish

Increasing evidence shows that structural variants represent an overlooked aspect of genetic variation with consequential evolutionary roles. Among those, copy number variants (CNVs), including duplicated genomic regions and transposable elements (TEs), may contribute to local adaptation and/or reproductive isolation among divergent populations. Those mechanisms suppose that CNVs could be used to infer neutral and/or adaptive population genetic structure, whose study has been restricted to microsatellites, mitochondrial DNA and Amplified fragment length polymorphism markers in the past and more recently the use of single nucleotide polymorphisms (SNPs). Taking advantage of recent developments allowing CNV analysis from RAD-seq data, we investigated how variation in fitness-related traits, local environmental conditions and demographic history are associated with CNVs, and how subsequent copy number variation drives population genetic structure in a marine fish, the capelin (Mallotus villosus). We collected 1538 DNA samples from 35 sampling sites in the north Atlantic Ocean and identified 6620 putative CNVs. We found associations between CNVs and the gonadosomatic index, suggesting that six duplicated regions could affect female fitness by modulating oocyte production. We also detected 105 CNV candidates associated with water temperature, among which 20% corresponded to genomic regions located within the sequence of protein-coding genes, suggesting local adaptation to cold water by means of gene sequence amplification. We also identified 175 CNVs associated with the divergence of three previously defined parapatric glacial lineages, of which 24% were located within protein-coding genes, making those loci potential candidates for reproductive isolation. Lastly, our analyses unveiled a hierarchical, complex CNV population structure determined by temperature and local geography, which was in stark contrast to that inferred based on SNPs in a previous study. Our findings underline the complementarity of those two types of genomic variation in population genomics studies.

Low impact of different SNP panels from two building-loci pipelines on RAD-Seq population genomic metrics: case study on five diverse aquatic species

Background

The irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control.

Results

Despite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons.

Conclusions

Tested building-loci pipelines for selection of SNP panels seem to have low influence on population genetics inference across the diverse case-study scenarios here studied. However, preliminary trials with different bioinformatic pipelines are suggested to evaluate their influence on population parameters according with the specific goals of each study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07465-w.

LEA 3: Factor models in population genetics and ecological genomics with R

A major objective of evolutionary biology is to understand the processes by which organisms have adapted to various environments, and to predict the response of organisms to new or future conditions. The availability of large genomic and environmental data sets provides an opportunity to address those questions, and the R package LEA has been introduced to facilitate population and ecological genomic analyses in this context. By using latent factor models, the program computes ancestry coefficients from population genetic data and performs genotype-environment association analyses with correction for unobserved confounding variables. In this study, we present new functionalities of LEA, which include imputation of missing genotypes, fast algorithms for latent factor mixed models using multivariate predictors for genotype-environment association studies, population differentiation tests for admixed or continuous populations, and estimation of genetic offset based on climate models. The new functionalities are implemented in version 3.1 and higher releases of the package. Using simulated and real data sets, our study provides evaluations and examples of applications, outlining important practical considerations when analysing ecological genomic data in R.

Conservation Genomics of the Threatened Western Spadefoot, Spea hammondii, in Urbanized Southern California

Populations of the western spadefoot (Spea hammondii) in southern California occur in one of the most urbanized and fragmented landscapes on the planet and have lost up to 80% of their native habitat. Orange County is one of the last strongholds for this pond-breeding amphibian in the region, and ongoing restoration efforts targeting S. hammondii have involved habitat protection and the construction of artificial breeding ponds. These efforts have successfully increased breeding activity, but genetic characterization of the populations, including estimates of effective population size and admixture between the gene pools of constructed artificial and natural ponds, has never been undertaken. Using thousands of genome-wide single-nucleotide polymorphisms, we characterized the population structure, genetic diversity, and genetic connectivity of spadefoots in Orange County to guide ongoing and future management efforts. We identified at least 2, and possibly 3 major genetic clusters, with additional substructure within clusters indicating that individual ponds are often genetically distinct. Estimates of landscape resistance suggest that ponds on either side of the Los Angeles Basin were likely interconnected historically, but intense urban development has rendered them essentially isolated, and the resulting risk of interruption to natural metapopulation dynamics appears to be high. Resistance surfaces show that the existing artificial ponds were well-placed and connected to natural populations by low-resistance corridors. Toad samples from all ponds (natural and artificial) returned extremely low estimates of effective population size, possibly due to a bottleneck caused by a recent multi-year drought. Management efforts should focus on maintaining gene flow among natural and artificial ponds by both assisted migration and construction of new ponds to bolster the existing pond network in the region.

Community Parameters and Genome-Wide RAD-Seq Loci of Ceratothoa oestroides Imply Its Transfer between Farmed European Sea Bass and Wild Farm-Aggregating Fish

Wild fish assemblages that aggregate within commercial marine aquaculture sites for feeding and shelter have been considered as a primary source of pathogenic parasites vectored to farmed fish maintained in net pens at an elevated density. In order to evaluate whether Ceratothoa oestroides (Isopoda, Cymothoidae), a generalist and pestilent isopod that is frequently found in Adriatic and Greek stocks of farmed European sea bass (Dicentrarchus labrax), transfers between wild and farmed fish, a RAD-Seq (restriction-site-associated DNA sequencing)-mediated genetic screening approach was employed. The double-digest RAD-Seq of 310 C. oestroides specimens collected from farmed European sea bass (138) and different wild farm-aggregating fish (172) identified 313 robust SNPs that evidenced a close genetic relatedness between the “wild” and “farmed” genotypes. ddRAD-Seq proved to be an effective method for detecting the discrete genetic structuring of C. oestroides and genotype intermixing between two populations. The parasite prevalence in the farmed sea bass was 1.02%, with a mean intensity of 2.0 and mean abundance of 0.02, while in the wild fish, the prevalence was 8.1%; the mean intensity, 1.81; and the mean abundance, 0.15. Such differences are likely a consequence of human interventions during the farmed fish’s rearing cycle that, nevertheless, did not affect the transfer of C. oestroides.

Effective double-digest RAD sequencing and genotyping despite large genome size

Obtaining informative data is the ambition of any genomic project, but in nonmodel species with very large genomes, pursuing such a goal requires surmounting a series of analytical challenges. Double-digest RAD sequencing is routinely used in nonmodel organisms and offers some control over the volume of data obtained. However, the volume of data recovered is not always an indication of the reliability of data sets, and quality checks are necessary to ensure that true and artefactual information is set apart. In the present study, we aim to fill the gap existing between the known applicability of RAD sequencing methods in plants with large genomes and the use of the retrieved loci for population genetic inference. By analysing two populations of Cypripedium calceolus, a nonmodel orchid species with a large genome size (1C ~ 31.6 Gbp), we provide a complete workflow from library preparation to bioinformatic filtering and inference of genetic diversity and differentiation. We show how filtering strategies to dismiss potentially misleading data need to be explored and adapted to data set-specific features. Moreover, we suggest that the occurrence of organellar sequences in libraries should not be neglected when planning the experiment and analysing the results. Finally, we explain how, in the absence of prior information about the genome of the species, seeking high standards of quality during library preparation and sequencing can provide an insurance against unpredicted technical or biological constraints.

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.

Current State and Perspectives in Population Genomics of the Common Bean

* Correspondence: r [...].

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.

Estimating effective population size using RADseq: Effects of SNP selection and sample size

Effective population size (Ne ) is a key parameter of population genetics. However, N e remains challenging to estimate for natural populations as several factors are likely to bias estimates. These factors include sampling design, sequencing method, and data filtering. One issue inherent to the restriction site-associated DNA sequencing (RADseq) protocol is missing data and SNP selection criteria (e.g., minimum minor allele frequency, number of SNPs). To evaluate the potential impact of SNP selection criteria on Ne estimates (Linkage Disequilibrium method) we used RADseq data for a nonmodel species, the thornback ray. In this data set, the inbreeding coefficient F IS was positively correlated with the amount of missing data, implying data were missing nonrandomly. The precision of Ne estimates decreased with the number of SNPs. Mean Ne estimates (averaged across 50 random data sets with2000 SNPs) ranged between 237 and 1784. Increasing the percentage of missing data from 25% to 50% increased Ne estimates between 82% and 120%, while increasing the minor allele frequency (MAF) threshold from 0.01 to 0.1 decreased estimates between 71% and 75%. Considering these effects is important when interpreting RADseq data-derived estimates of effective population size in empirical studies.

A haplotype-resolved draft genome of the European sardine (Sardina pilchardus)

Background

The European sardine (Sardina pilchardus Walbaum, 1792) is culturally and economically important throughout its distribution. Monitoring studies of sardine populations report an alarming decrease in stocks due to overfishing and environmental change, which has resulted in historically low captures along the Iberian Atlantic coast. Important biological and ecological features such as population diversity, structure, and migratory patterns can be addressed with the development and use of genomics resources.

Findings

The genome of a single female individual was sequenced using Illumina HiSeq X Ten 10x Genomics linked reads, generating 113.8 gigabase pairs of data. Three draft genomes were assembled: 2 haploid genomes with a total size of 935 megabase pairs (N50 103 kilobase pairs) each, and a consensus genome of total size 950 megabase pairs (N50 97 kilobase pairs). The genome completeness assessment captured 84% of Actinopterygii Benchmarking Universal Single-Copy Orthologs. To obtain a more complete analysis, the transcriptomes of 11 tissues were sequenced to aid the functional annotation of the genome, resulting in 40,777 genes predicted. Variant calling on nearly half of the haplotype genome resulted in the identification of >2.3 million phased single-nucleotide polymorphisms with heterozygous loci.

Conclusions

A draft genome was obtained, despite a high level of sequence repeats and heterozygosity, which are expected genome characteristics of a wild sardine. The reference sardine genome and respective variant data will be a cornerstone resource of ongoing population genomics studies to be integrated into future sardine stock assessment modelling to better manage this valuable resource.