Chromosome‐level hybrid de novo genome assemblies as an attainable option for nonmodel insects

The emergence of third‐generation sequencing (3GS; long‐reads) is bringing closer the goal of chromosome‐size fragments in de novo genome assemblies. This allows the exploration of new and broader questions on genome evolution for a number of nonmodel organisms. However, long‐read technologies result in higher sequencing error rates and therefore impose an elevated cost of sufficient coverage to achieve high enough quality. In this context, hybrid assemblies, combining short‐reads and long‐reads, provide an alternative efficient and cost‐effective approach to generate de novo, chromosome‐level genome assemblies. The array of available software programs for hybrid genome assembly, sequence correction and manipulation are constantly being expanded and improved. This makes it difficult for nonexperts to find efficient, fast and tractable computational solutions for genome assembly, especially in the case of nonmodel organisms lacking a reference genome or one from a closely related species. In this study, we review and test the most recent pipelines for hybrid assemblies, comparing the model organism Drosophila melanogaster to a nonmodel cactophilic Drosophila, D. mojavensis. We show that it is possible to achieve excellent contiguity on this nonmodel organism using the dbg2olc pipeline.     

Investigating the genomic basis of discrete phenotypes using a Pool‐Seq‐only approach: New insights into the genetics underlying colour variation in diverse taxa

While large‐scale genomic approaches are increasingly revealing the genetic basis of polymorphic phenotypes such as colour morphs, such approaches are almost exclusively conducted in species with high‐quality genomes and annotations. Here, we use Pool‐Seq data for both genome assembly and SNP frequency estimation, followed by scanning for F_ST outliers to identify divergent genomic regions. Using paired‐end, short‐read sequencing data from two groups of individuals expressing divergent phenotypes, we generate a de novo rough‐draft genome, identify SNPs and calculate genomewide F_ST differences between phenotypic groups. As genomes generated by Pool‐Seq data are highly fragmented, we also present an approach for super‐scaffolding contigs using existing protein‐coding data sets. Using this approach, we reanalysed genomic data from two recent studies of birds and butterflies investigating colour pattern variation and replicated their core findings, demonstrating the accuracy and power of a Pool‐Seq‐only approach. Additionally, we discovered new regions of high divergence and new annotations that together suggest novel parallels between birds and butterflies in the origins of their colour pattern variation.     

Inference of chromosomal inversion dynamics from Pool‐Seq data in natural and laboratory populations of Drosophila melanogaster

Sequencing of pools of individuals (Pool‐Seq) represents a reliable and cost‐effective approach for estimating genome‐wide SNP and transposable element insertion frequencies. However, Pool‐Seq does not provide direct information on haplotypes so that, for example, obtaining inversion frequencies has not been possible until now. Here, we have developed a new set of diagnostic marker SNPs for seven cosmopolitan inversions in Drosophila melanogaster that can be used to infer inversion frequencies from Pool‐Seq data. We applied our novel marker set to Pool‐Seq data from an experimental evolution study and from North American and Australian latitudinal clines. In the experimental evolution data, we find evidence that positive selection has driven the frequencies of In(3R)C and In(3R)Mo to increase over time. In the clinal data, we confirm the existence of frequency clines for In(2L)t, In(3L)P and In(3R)Payne in both North America and Australia and detect a previously unknown latitudinal cline for In(3R)Mo in North America. The inversion markers developed here provide a versatile and robust tool for characterizing inversion frequencies and their dynamics in Pool‐Seq data from diverse D. melanogaster populations.     

Minimum sample sizes for population genomics: an empirical study from an Amazonian plant species

High‐throughput DNA sequencing facilitates the analysis of large portions of the genome in nonmodel organisms, ensuring high accuracy of population genetic parameters. However, empirical studies evaluating the appropriate sample size for these kinds of studies are still scarce. In this study, we use double‐digest restriction‐associated DNA sequencing (ddRADseq) to recover thousands of single nucleotide polymorphisms (SNPs) for two physically isolated populations of Amphirrhox longifolia (Violaceae), a nonmodel plant species for which no reference genome is available. We used resampling techniques to construct simulated populations with a random subset of individuals and SNPs to determine how many individuals and biallelic markers should be sampled for accurate estimates of intra‐ and interpopulation genetic diversity. We identified 3646 and 4900 polymorphic SNPs for the two populations of A. longifolia, respectively. Our simulations show that, overall, a sample size greater than eight individuals has little impact on estimates of genetic diversity within A. longifolia populations, when 1000 SNPs or higher are used. Our results also show that even at a very small sample size (i.e. two individuals), accurate estimates of F_ST can be obtained with a large number of SNPs (≥1500). These results highlight the potential of high‐throughput genomic sequencing approaches to address questions related to evolutionary biology in nonmodel organisms. Furthermore, our findings also provide insights into the optimization of sampling strategies in the era of population genomics.     

Development of a universal double‐digest RAD sequencing approach for a group of nonmodel,ecologically and economically important insect and fish taxa

The generation of genome‐scale data is critical for a wide range of questions in basic biology using model organisms, but also in questions of applied biology in nonmodel organisms (agriculture, natural resources, conservation and public health biology). Using a genome‐scale approach on a diverse group of nonmodel organisms and with the goal of lowering costs of the method, we modified a multiplexed, high‐throughput genomic scan technique utilizing two restriction enzymes. We analysed several pairs of restriction enzymes and completed double‐digestion RAD sequencing libraries for nine different species and five genera of insects and fish. We found one particular enzyme pair produced consistently higher number of sequence‐able fragments across all nine species. Building libraries off this enzyme pair, we found a range of usable SNPs between 4000 and 37 000 SNPS per species and we found a greater number of usable SNPs using reference genomes than de novo pipelines in STACKS. We also found fewer reads in the Read 2 fragments from the paired‐end Illumina Hiseq run. Overall, the results of this study provide empirical evidence of the utility of this method for producing consistent data for diverse nonmodel species and suggest specific considerations for sequencing analysis strategies.     

Pool‐hmm: a Python program for estimating the allele frequency spectrum and detecting selective sweeps from next generation sequencing of pooled samples

Due to its cost effectiveness, next generation sequencing of pools of individuals (Pool‐Seq) is becoming a popular strategy for genome‐wide estimation of allele frequencies in population samples. As the allele frequency spectrum provides information about past episodes of selection, Pool‐seq is also a promising design for genomic scans for selection. However, no software tool has yet been developed for selection scans based on Pool‐Seq data. We introduce Pool‐hmm, a Python program for the estimation of allele frequencies and the detection of selective sweeps in a Pool‐Seq sample. Pool‐hmm includes several options that allow a flexible analysis of Pool‐Seq data, and can be run in parallel on several processors. Source code and documentation for Pool‐hmm is freely available at https://qgsp.jouy.inra.fr/ .     

SNP discovery in nonmodel organisms: strand bias and base‐substitution errors reduce conversion rates

Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep‐sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize ‘bycatch’—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand‐bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single‐copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.     

Double‐digest RAD sequencing using Ion Proton semiconductor platform (ddRADseq‐ion) with nonmodel organisms

Research in evolutionary biology involving nonmodel organisms is rapidly shifting from using traditional molecular markers such as mtDNA and microsatellites to higher throughput SNP genotyping methodologies to address questions in population genetics, phylogenetics and genetic mapping. Restriction site associated DNA sequencing (RAD sequencing or RADseq) has become an established method for SNP genotyping on Illumina sequencing platforms. Here, we developed a protocol and adapters for double‐digest RAD sequencing for Ion Torrent (Life Technologies; Ion Proton, Ion PGM) semiconductor sequencing. We sequenced thirteen genomic libraries of three different nonmodel vertebrate species on Ion Proton with PI chips: Arctic charr Salvelinus alpinus, European whitefish Coregonus lavaretus and common lizard Zootoca vivipara. This resulted in ~962 million single‐end reads overall and a mean of ~74 million reads per library. We filtered the genomic data using Stacks, a bioinformatic tool to process RAD sequencing data. On average, we obtained ~11 000 polymorphic loci per library of 6–30 individuals. We validate our new method by technical and biological replication, by reconstructing phylogenetic relationships, and using a hybrid genetic cross to track genomic variants. Finally, we discuss the differences between using the different sequencing platforms in the context of RAD sequencing, assessing possible advantages and disadvantages. We show that our protocol can be used for Ion semiconductor sequencing platforms for the rapid and cost‐effective generation of variable and reproducible genetic markers.     

Using genic sequence capture in combination with a syntenic pseudo genome to map a deletion mutant in a wheat species

Mapping‐by‐sequencing analyses have largely required a complete reference sequence and employed whole genome re‐sequencing. In species such as wheat, no finished genome reference sequence is available. Additionally, because of its large genome size (17 Gb), re‐sequencing at sufficient depth of coverage is not practical. Here, we extend the utility of mapping by sequencing, developing a bespoke pipeline and algorithm to map an early‐flowering locus in einkorn wheat (Triticum monococcum L.) that is closely related to the bread wheat genome A progenitor. We have developed a genomic enrichment approach using the gene‐rich regions of hexaploid bread wheat to design a 110‐Mbp NimbleGen SeqCap EZ in solution capture probe set, representing the majority of genes in wheat. Here, we use the capture probe set to enrich and sequence an F₂ mapping population of the mutant. The mutant locus was identified in T. monococcum, which lacks a complete genome reference sequence, by mapping the enriched data set onto pseudo‐chromosomes derived from the capture probe target sequence, with a long‐range order of genes based on synteny of wheat with Brachypodium distachyon. Using this approach we are able to map the region and identify a set of deleted genes within the interval.     

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

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

Single‐nucleotide polymorphism discovery in Leptographium longiclavatum,a mountain pine beetle‐associated symbiotic fungus,using whole‐genome resequencing

Single‐nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost‐effective approaches to uncover genome‐wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole‐genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N₅₀ = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17 266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina^® Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species.     

The impact of library preparation protocols on the consistency of allele frequency estimates in Pool‐Seq data

Sequencing pools of individuals (Pool‐Seq) is a cost‐effective method to determine genome‐wide allele frequency estimates. Given the importance of meta‐analyses combining data sets, we determined the influence of different genomic library preparation protocols on the consistency of allele frequency estimates. We found that typically no more than 1% of the variation in allele frequency estimates could be attributed to differences in library preparation. Also read length had only a minor effect on the consistency of allele frequency estimates. By far, the most pronounced influence could be attributed to sequence coverage. Increasing the coverage from 30‐ to 50‐fold improved the consistency of allele frequency estimates by at least 27%. We conclude that Pool‐Seq data can be easily combined across different library preparation methods, but sufficient sequence coverage is key to reliable results.     

Cross‐platform compatibility of de novo‐aligned SNPs in a nonmodel butterfly genus

High‐throughput sequencing methods for genotyping genome‐wide markers are being rapidly adopted for phylogenetics of nonmodel organisms in conservation and biodiversity studies. However, the reproducibility of SNP genotyping and degree of marker overlap or compatibility between datasets from different methodologies have not been tested in nonmodel systems. Using double‐digest restriction site‐associated DNA sequencing, we sequenced a common set of 22 specimens from the butterfly genus Speyeria on two different Illumina platforms, using two variations of library preparation. We then used a de novo approach to bioinformatic locus assembly and SNP discovery for subsequent phylogenetic analyses. We found a high rate of locus recovery despite differences in library preparation and sequencing platforms, as well as overall high levels of data compatibility after data processing and filtering. These results provide the first application of NGS methods for phylogenetic reconstruction in Speyeria and support the use and long‐term viability of SNP genotyping applications in nonmodel systems.     

Targeted multiplex next‐generation sequencing: advances in techniques of mitochondrial and nuclear DNA sequencing for population genomics

Next‐generation sequencing (NGS) is emerging as an efficient and cost‐effective tool in population genomic analyses of nonmodel organisms, allowing simultaneous resequencing of many regions of multi‐genomic DNA from multiplexed samples. Here, we detail our synthesis of protocols for targeted resequencing of mitochondrial and nuclear loci by generating indexed genomic libraries for multiplexing up to 100 individuals in a single sequencing pool, and then enriching the pooled library using custom DNA capture arrays. Our use of DNA sequence from one species to capture and enrich the sequencing libraries of another species (i.e. cross‐species DNA capture) indicates that efficient enrichment occurs when sequences are up to about 12% divergent, allowing us to take advantage of genomic information in one species to sequence orthologous regions in related species. In addition to a complete mitochondrial genome on each array, we have included between 43 and 118 nuclear loci for low‐coverage sequencing of between 18 kb and 87 kb of DNA sequence per individual for single nucleotide polymorphisms discovery from 50 to 100 individuals in a single sequencing lane. Using this method, we have generated a total of over 500 whole mitochondrial genomes from seven cetacean species and green sea turtles. The greater variation detected in mitogenomes relative to short mtDNA sequences is helping to resolve genetic structure ranging from geographic to species‐level differences. These NGS and analysis techniques have allowed for simultaneous population genomic studies of mtDNA and nDNA with greater genomic coverage and phylogeographic resolution than has previously been possible in marine mammals and turtles.     

Comparing Pool‐seq,Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost‐effective sequencing approaches, namely Pool‐seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping‐by‐sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool‐seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool‐seq data showed F_ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F_ST estimates, indicating that individual‐based approaches provided more congruent results than Pool‐seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost‐effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.     

Barley whole exome capture: a tool for genomic research in the genus Hordeum and beyond

Advanced resources for genome‐assisted research in barley (Hordeum vulgare) including a whole‐genome shotgun assembly and an integrated physical map have recently become available. These have made possible studies that aim to assess genetic diversity or to isolate single genes by whole‐genome resequencing and in silico variant detection. However such an approach remains expensive given the 5 Gb size of the barley genome. Targeted sequencing of the mRNA‐coding exome reduces barley genomic complexity more than 50‐fold, thus dramatically reducing this heavy sequencing and analysis load. We have developed and employed an in‐solution hybridization‐based sequence capture platform to selectively enrich for a 61.6 megabase coding sequence target that includes predicted genes from the genome assembly of the cultivar Morex as well as publicly available full‐length cDNAs and de novo assembled RNA‐Seq consensus sequence contigs. The platform provides a highly specific capture with substantial and reproducible enrichment of targeted exons, both for cultivated barley and related species. We show that this exome capture platform provides a clear path towards a broader and deeper understanding of the natural variation residing in the mRNA‐coding part of the barley genome and will thus constitute a valuable resource for applications such as mapping‐by‐sequencing and genetic diversity analyzes.