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.     

Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Molecular markers produced by next‐generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual‐based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user‐friendly application assessing the accuracy of allele frequency estimation from both pool‐ and individual‐based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site–associated DNA (RAD) sequencing in pool‐ and individual‐based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost‐effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome‐wide patterns of genetic variation for large numbers of individuals in multiple populations.     

Discovering and sequencing new plant viral genomes by next‐generation sequencing: description of a practical pipeline

Small‐scale sequencing has improved substantially in recent decades, culminating in the development of next‐generation sequencing (NGS) technologies. Modern NGS methods have helped the discovery of many new plant viruses. Nevertheless, there is still a need to establish solid assembly pipelines targeting small genomes characterised by low identities to known viral sequences. Here, we describe and discuss the fundamental steps required for discovering and sequencing new plant viral genomes by NGS. A practical pipeline and standard alternative tools used in NGS analysis are presented.     

A targeted next‐generation sequencing toolkit for exon‐based cichlid phylogenomics

Cichlid fishes (family Cichlidae) are models for evolutionary and ecological research. Massively parallel sequencing approaches have been successfully applied to study relatively recent diversification in groups of African and Neotropical cichlids, but such technologies have yet to be used for addressing larger‐scale phylogenetic questions of cichlid evolution. Here, we describe a process for identifying putative single‐copy exons from five African cichlid genomes and sequence the targeted exons for a range of divergent (>tens of millions of years) taxa with probes designed from a single reference species (Oreochromis niloticus, Nile tilapia). Targeted sequencing of 923 exons across 10 cichlid species that represent the family's major lineages and geographic distribution resulted in a complete taxon matrix of 564 exons (649 549 bp), representing 559 genes. Maximum likelihood and Bayesian analyses in both species tree and concatenation frameworks yielded the same fully resolved and highly supported topology, which matched the expected backbone phylogeny of the major cichlid lineages. This work adds to the body of evidence that it is possible to use a relatively divergent reference genome for exon target design and successful capture across a broad phylogenetic range of species. Furthermore, our results show that the use of a third‐party laboratory coupled with accessible bioinformatics tools makes such phylogenomics projects feasible for research groups that lack direct access to genomic facilities. We expect that these resources will be used in further cichlid evolution studies and hope the protocols and identified targets will also be useful for phylogenetic studies of a wider range of organisms.     

Exploring the tertiary gene pool of bread wheat: sequence assembly and analysis of chromosome 5Mg of Aegilops geniculata

Next‐generation sequencing (NGS) provides a powerful tool for the discovery of important genes and alleles in crop plants and their wild relatives. Despite great advances in NGS technologies, whole‐genome shotgun sequencing is cost‐prohibitive for species with complex genomes. An attractive option is to reduce genome complexity to a single chromosome prior to sequencing. This work describes a strategy for studying the genomes of distant wild relatives of wheat by isolating single chromosomes from addition or substitution lines, followed by chromosome sorting using flow cytometry and sequencing of chromosomal DNA by NGS technology. We flow‐sorted chromosome 5M^g from a wheat/Aegilops geniculata disomic substitution line [DS5M^g (5D)] and sequenced it using an Illumina HiSeq 2000 system at approximately 50 × coverage. Paired‐end sequences were assembled and used for structural and functional annotation. A total of 4236 genes were annotated on 5M^g, in close agreement with the predicted number of genes on wheat chromosome 5D (4286). Single‐gene FISH indicated no major chromosomal rearrangements between chromosomes 5M^g and 5D. Comparing chromosome 5M^g with model grass genomes identified synteny blocks in Brachypodium distachyon, rice (Oryza sativa), sorghum (Sorghum bicolor) and barley (Hordeum vulgare). Chromosome 5M^g‐specific SNPs and cytogenetic probe‐based resources were developed and validated. Deletion bin‐mapped and ordered 5M^g SNP markers will be useful to track 5M‐specific introgressions and translocations. This study provides a detailed sequence‐based analysis of the composition of a chromosome from a distant wild relative of bread wheat, and opens up opportunities to develop genomic resources for wild germplasm to facilitate crop improvement.     

Whole‐genome sequencing approaches for conservation biology: Advantages,limitations and practical recommendations

Whole‐genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled‐individual DNA (Pool‐seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.     

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 and accounting for genotyping errors in RAD‐seq experiments

In non‐model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy‐Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD‐seq), arguably the most popular reduced representation sequencing technique, revealed per‐allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome‐wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD‐seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.     

Genotyping‐by‐sequencing approaches to characterize crop genomes: choosing the right tool for the right application

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high‐throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping‐by‐sequencing (GBS) methods include over a dozen reduced‐representation sequencing (RRS) approaches and at least four whole‐genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best‐suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small‐ to moderate‐sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost‐effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost‐effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.     

Optimization of the genotyping‐by‐sequencing strategy for population genomic analysis in conifers

Flexibility and low cost make genotyping‐by‐sequencing (GBS) an ideal tool for population genomic studies of nonmodel species. However, to utilize the potential of the method fully, many parameters affecting library quality and single nucleotide polymorphism (SNP) discovery require optimization, especially for conifer genomes with a high repetitive DNA content. In this study, we explored strategies for effective GBS analysis in pine species. We constructed GBS libraries using HpaII, PstI and EcoRI‐MseI digestions with different multiplexing levels and examined the effect of restriction enzymes on library complexity and the impact of sequencing depth and size selection of restriction fragments on sequence coverage bias. We tested and compared UNEAK, Stacks and GATK pipelines for the GBS data, and then developed a reference‐free SNP calling strategy for haploid pine genomes. Our GBS procedure proved to be effective in SNP discovery, producing 7000–11 000 and 14 751 SNPs within and among three pine species, respectively, from a PstI library. This investigation provides guidance for the design and analysis of GBS experiments, particularly for organisms for which genomic information is lacking.     

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.     

Model‐Based Quality Assessment and Base‐Calling for Second‐Generation Sequencing Data

Summary Second‐generation sequencing (sec‐gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads—strings of A,C,G, or T's, between 30 and 100 characters long—which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base‐calling. The complexity of the base‐calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across‐sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec‐gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base‐calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base‐calling allowing for informative and easily interpretable metrics that capture the variability in sequencing quality. Our model provides these informative estimates readily usable in quality assessment tools while significantly improving base‐calling performance.     

Elucidating cryptic dynamics of Theileria communities in African buffalo using a high‐throughput sequencing informatics approach

1. Increasing access to next‐generation sequencing (NGS) technologies is revolutionizing the life sciences. In disease ecology, NGS‐based methods have the potential to provide higher‐resolution data on communities of parasites found in individual hosts as well as host populations.
2. Here, we demonstrate how a novel analytical method, utilizing high‐throughput sequencing of PCR amplicons, can be used to explore variation in blood‐borne parasite (Theileria—Apicomplexa: Piroplasmida) communities of African buffalo at higher resolutions than has been obtained with conventional molecular tools.
3. Results reveal temporal patterns of synchronized and opposite fluctuations of prevalence and relative abundance of Theileria spp. within the host population, suggesting heterogeneous transmission across taxa. Furthermore, we show that the community composition of Theileria spp. and their subtypes varies considerably between buffalo, with differences in composition reflected in mean and variance of overall parasitemia, thereby showing potential to elucidate previously unexplained contrasts in infection outcomes for host individuals.
4. Importantly, our methods are generalizable as they can be utilized to describe blood‐borne parasite communities in any host species. Furthermore, our methodological framework can be adapted to any parasite system given the appropriate genetic marker.
5. The findings of this study demonstrate how a novel NGS‐based analytical approach can provide fine‐scale, quantitative data, unlocking opportunities for discovery in disease ecology.

     

amplisas: a web server for multilocus genotyping using next‐generation amplicon sequencing data

Next‐generation sequencing (NGS) technologies are revolutionizing the fields of biology and medicine as powerful tools for amplicon sequencing (AS). Using combinations of primers and barcodes, it is possible to sequence targeted genomic regions with deep coverage for hundreds, even thousands, of individuals in a single experiment. This is extremely valuable for the genotyping of gene families in which locus‐specific primers are often difficult to design, such as the major histocompatibility complex (MHC). The utility of AS is, however, limited by the high intrinsic sequencing error rates of NGS technologies and other sources of error such as polymerase amplification or chimera formation. Correcting these errors requires extensive bioinformatic post‐processing of NGS data. Amplicon Sequence Assignment (amplisas ) is a tool that performs analysis of AS results in a simple and efficient way, while offering customization options for advanced users. amplisas is designed as a three‐step pipeline consisting of (i) read demultiplexing, (ii) unique sequence clustering and (iii) erroneous sequence filtering. Allele sequences and frequencies are retrieved in excel spreadsheet format, making them easy to interpret. amplisas performance has been successfully benchmarked against previously published genotyped MHC data sets obtained with various NGS technologies.     

Sequence capture and next‐generation sequencing of ultraconserved elements in a large‐genome salamander

Amidst the rapid advancement in next‐generation sequencing (NGS) technology over the last few years, salamanders have been left behind. Salamanders have enormous genomes—up to 40 times the size of the human genome—and this poses challenges to generating NGS data sets of quality and quantity similar to those of other vertebrates. However, optimization of laboratory protocols is time‐consuming and often cost prohibitive, and continued omission of salamanders from novel phylogeographic research is detrimental to species facing decline. Here, we use a salamander endemic to the southeastern United States, Plethodon serratus, to test the utility of an established protocol for sequence capture of ultraconserved elements (UCEs) in resolving intraspecific phylogeographic relationships and delimiting cryptic species. Without modifying the standard laboratory protocol, we generated a data set consisting of over 600 million reads for 85 P. serratus samples. Species delimitation analyses support recognition of seven species within P. serratus sensu lato, and all phylogenetic relationships among the seven species are fully resolved under a coalescent model. Results also corroborate previous data suggesting nonmonophyly of the Ouachita and Louisiana regions. Our results demonstrate that established UCE protocols can successfully be used in phylogeographic studies of salamander species, providing a powerful tool for future research on evolutionary history of amphibians and other organisms with large genomes.     

Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird‐of‐paradise

Genome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies now enable assembling genomes at unprecedented quality and contiguity. However, the difficulty in assembling repeat‐rich and GC‐rich regions (genomic “dark matter”) limits insights into the evolution of genome structure and regulatory networks. Here, we compare the efficiency of currently available sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter. By adopting different de novo assembly strategies, we compare individual draft assemblies to a curated multiplatform reference assembly and identify the genomic features that cause gaps within each assembly. We show that a multiplatform assembly implementing long‐read, linked‐read and proximity sequencing technologies performs best at recovering transposable elements, multicopy MHC genes, GC‐rich microchromosomes and the repeat‐rich W chromosome. Telomere‐to‐telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is now possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects for optimized completeness of both the coding and noncoding parts of nonmodel genomes.