exonsampler: a computer program for genome‐wide and candidate gene exon sampling for targeted next‐generation sequencing

The computer program exonsampler automates the sampling of thousands of exon sequences from publicly available reference genome sequences and gene annotation databases. It was designed to provide exon sequences for the efficient, next‐generation gene sequencing method called exon capture. The exon sequences can be sampled by a list of gene name abbreviations (e.g. IFNG, TLR1), or by sampling exons from genes spaced evenly across chromosomes. It provides a list of genomic coordinates (a bed file), as well as a set of sequences in fasta format. User‐adjustable parameters for collecting exon sequences include a minimum and maximum acceptable exon length, maximum number of exonic base pairs (bp) to sample per gene, and maximum total bp for the entire collection. It allows for partial sampling of very large exons. It can preferentially sample upstream (5 prime) exons, downstream (3 prime) exons, both external exons, or all internal exons. It is written in the Python programming language using its free libraries. We describe the use of exonsampler to collect exon sequences from the domestic cow (Bos taurus) genome for the design of an exon‐capture microarray to sequence exons from related species, including the zebu cow and wild bison. We collected ~10% of the exome (~3 million bp), including 155 candidate genes, and ~16 000 exons evenly spaced genomewide. We prioritized the collection of 5 prime exons to facilitate discovery and genotyping of SNPs near upstream gene regulatory DNA sequences, which control gene expression and are often under natural selection.     

DNA barcodes from century‐old type specimens using next‐generation sequencing

Type specimens have high scientific importance because they provide the only certain connection between the application of a Linnean name and a physical specimen. Many other individuals may have been identified as a particular species, but their linkage to the taxon concept is inferential. Because type specimens are often more than a century old and have experienced conditions unfavourable for DNA preservation, success in sequence recovery has been uncertain. This study addresses this challenge by employing next‐generation sequencing (NGS) to recover sequences for the barcode region of the cytochrome c oxidase 1 gene from small amounts of template DNA. DNA quality was first screened in more than 1800 century‐old type specimens of Lepidoptera by attempting to recover 164‐bp and 94‐bp reads via Sanger sequencing. This analysis permitted the assignment of each specimen to one of three DNA quality categories – high (164‐bp sequence), medium (94‐bp sequence) or low (no sequence). Ten specimens from each category were subsequently analysed via a PCR‐based NGS protocol requiring very little template DNA. It recovered sequence information from all specimens with average read lengths ranging from 458 bp to 610 bp for the three DNA categories. By sequencing ten specimens in each NGS run, costs were similar to Sanger analysis. Future increases in the number of specimens processed in each run promise substantial reductions in cost, making it possible to anticipate a future where barcode sequences are available from most type specimens.     

High‐throughput SNP discovery in the rabbit (Oryctolagus cuniculus) genome by next‐generation semiconductor‐based sequencing

The European rabbit (Oryctolagus cuniculus) is a domesticated species with one of the broadest ranges of economic and scientific applications and fields of investigation. Rabbit genome information and assembly are available (oryCun2.0), but so far few studies have investigated its variability, and massive discovery of polymorphisms has not been published yet for this species. Here, we sequenced two reduced representation libraries (RRLs) to identify single nucleotide polymorphisms (SNPs) in the rabbit genome. Genomic DNA of 10 rabbits belonging to different breeds was pooled and digested with two restriction enzymes (HaeIII and RsaI) to create two RRLs which were sequenced using the Ion Torrent Personal Genome Machine. The two RRLs produced 2 917 879 and 4 046 871 reads, for a total of 280.51 Mb (248.49 Mb with quality >20) and 417.28 Mb (360.89 Mb with quality >20) respectively of sequenced DNA. About 90% and 91% respectively of the obtained reads were mapped on the rabbit genome, covering a total of 15.82% of the oryCun2.0 genome version. The mapping and ad hoc filtering procedures allowed to reliably call 62 491 SNPs. SNPs in a few genomic regions were validated by Sanger sequencing. The Variant Effect Predictor Web tool was used to map SNPs on the current version of the rabbit genome. The obtained results will be useful for many applied and basic research programs for this species and will contribute to the development of cost‐effective solutions for high‐throughput SNP genotyping in the rabbit.     

Multiplex restriction amplicon sequencing: a novel next‐generation sequencing‐based marker platform for high‐throughput genotyping

To enable rapid selection of traits in marker‐assisted breeding, markers must be technically simple, low‐cost, high‐throughput and randomly distributed in a genome. We developed such a technology, designated as Multiplex Restriction Amplicon Sequencing (MRASeq), which reduces genome complexity by polymerase chain reaction (PCR) amplification of amplicons flanked by restriction sites. The first PCR primers contain restriction site sequences at 3’‐ends, preceded by 6‐10 bases of specific or degenerate nucleotide sequences and then by a unique M13‐tail sequence which serves as a binding site for a second PCR that adds sequencing primers and barcodes to allow sample multiplexing for sequencing. The sequences of restriction sites and adjacent nucleotides can be altered to suit different species. Physical mapping of MRASeq SNPs from a biparental population of allohexaploid wheat (Triticum aestivum L.) showed a random distribution of SNPs across the genome. MRASeq generated thousands of SNPs from a wheat biparental population and natural populations of wheat and barley (Hordeum vulgare L.). This novel, next‐generation sequencing‐based genotyping platform can be used for linkage mapping to screen quantitative trait loci (QTL), background selection in breeding and many other genetics and breeding applications of various species.     

Unlocking the secondary gene‐pool of barley with next‐generation sequencing

Crop wild relatives (CWR) provide an important source of allelic diversity for any given crop plant species for counteracting the erosion of genetic diversity caused by domestication and elite breeding bottlenecks. Hordeum bulbosum L. is representing the secondary gene pool of the genus Hordeum. It has been used as a source of genetic introgressions for improving elite barley germplasm (Hordeum vulgare L.). However, genetic introgressions from H. bulbosum have yet not been broadly applied, due to a lack of suitable molecular tools for locating, characterizing, and decreasing by recombination and marker‐assisted backcrossing the size of introgressed segments. We applied next‐generation sequencing (NGS) based strategies for unlocking genetic diversity of three diploid introgression lines of cultivated barley containing chromosomal segments of its close relative H. bulbosum. Firstly, exome capture‐based (re)‐sequencing revealed large numbers of single nucleotide polymorphisms (SNPs) enabling the precise allocation of H. bulbosum introgressions. This SNP resource was further exploited by designing a custom multiplex SNP genotyping assay. Secondly, two‐enzyme‐based genotyping‐by‐sequencing (GBS) was employed to allocate the introgressed H. bulbosum segments and to genotype a mapping population. Both methods provided fast and reliable detection and mapping of the introgressed segments and enabled the identification of recombinant plants. Thus, the utilization of H. bulbosum as a resource of natural genetic diversity in barley crop improvement will be greatly facilitated by these tools in the future.     

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.     

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.     

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.     

Efficient and sensitive identification and quantification of airborne pollen using next‐generation DNA sequencing

Pollen monitoring is an important and widely used tool in allergy research and creation of awareness in pollen‐allergic patients. Current pollen monitoring methods are microscope‐based, labour intensive and cannot identify pollen to the genus level in some relevant allergenic plant groups. Therefore, a more efficient, cost‐effective and sensitive method is needed. Here, we present a method for identification and quantification of airborne pollen using DNA sequencing. Pollen is collected from ambient air using standard techniques. DNA is extracted from the collected pollen, and a fragment of the chloroplast gene trnL is amplified using PCR. The PCR product is subsequently sequenced on a next‐generation sequencing platform (Ion Torrent). Amplicon molecules are sequenced individually, allowing identification of different sequences from a mixed sample. We show that this method provides an accurate qualitative and quantitative view of the species composition of samples of airborne pollen grains. We also show that it correctly identifies the individual grass genera present in a mixed sample of grass pollen, which cannot be achieved using microscopic pollen identification. We conclude that our method is more efficient and sensitive than current pollen monitoring techniques and therefore has the potential to increase the throughput of pollen monitoring.     

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.     

Isolation and characterization of microsatellite markers for Viola mirabilis (Violaceae) using a next‐generation sequencing platform

We isolated and characterized microsatellite loci in Viola mirabilis (Violaceae), an endangered species from South Korea. Twenty‐three polymorphic microsatellite loci were developed and tested in Korean, Chinese and Japanese populations. The number of alleles per locus varied from two to eight. The observed and expected heterozygosities within the three populations were 0.000–0.625 and 0.469–0.695, respectively. A total of six loci in the Korean population, one locus in the Chinese population and seven loci in the Japanese population deviated from Hardy–Weinberg equilibrium. We expect that these newly developed microsatellite markers will contribute to understanding the phylogeography and population genetics of V. mirabilis, which will aid in developing conservation strategies for this species.     

ReadTools: A universal toolkit for handling sequence data from different sequencing platforms

Sequencing whole genomes has become a standard research tool in many disciplines including Molecular Ecology, but the rapid technological advances in combination with several competing platforms have resulted in a confusing diversity of formats. This lack of standard formats causes several problems, such as undocumented preprocessing steps or the loss of information in downstream software tools, which do not account for the specifics of the different available formats. ReadTools is an open‐source Java toolkit designed to standardize and preprocess read data from different platforms. It manages FASTQ‐ and SAM‐formatted inputs while dealing with platform‐specific peculiarities and provides a standard SAM compliant output. The code and executable are available at https://github.com/magicDGS/ReadTools .     

Pipeliner: software to evaluate the performance of bioinformatics pipelines for next‐generation resequencing

The choice of technology and bioinformatics approach is critical in obtaining accurate and reliable information from next‐generation sequencing (NGS) experiments. An increasing number of software and methodological guidelines are being published, but deciding upon which approach and experimental design to use can depend on the particularities of the species and on the aims of the study. This leaves researchers unable to produce informed decisions on these central questions. To address these issues, we developed pipeliner – a tool to evaluate, by simulation, the performance of NGS pipelines in resequencing studies. Pipeliner provides a graphical interface allowing the users to write and test their own bioinformatics pipelines with publicly available or custom software. It computes a number of statistics summarizing the performance in SNP calling, including the recovery, sensitivity and false discovery rate for heterozygous and homozygous SNP genotypes. Pipeliner can be used to answer many practical questions, for example, for a limited amount of NGS effort, how many more reliable SNPs can be detected by doubling coverage and halving sample size or what is the false discovery rate provided by different SNP calling algorithms and options. Pipeliner thus allows researchers to carefully plan their study's sampling design and compare the suitability of alternative bioinformatics approaches for their specific study systems. Pipeliner is written in C++ and is freely available from http://github.com/brunonevado/Pipeliner .     

NGS‐based targeted resequencing identified rare subtypes of albinism: Providing accurate molecular diagnosis for Japanese patients with albinism

Albinism, which is commonly inherited as an autosomal recessive trait, is characterized by a reduction or absence of melanin in the eyes, skin, and hair. To date, more than 20 causal genes for albinism have been identified; thus, the accurate diagnosis of albinism requires next‐generation sequencing (NGS). In this study, we analyzed 46 patients who tested negative for oculocutaneous albinism (OCA)1–4 and Hermansky‐Pudlak syndrome (HPS)1 based on conventional analysis, in addition to 28 new Japanese patients, using NGS‐based targeted resequencing. We identified a genetic background for albinism in 18 of the 46 patients (39%), who were previously tested negative according to the conventional analysis. In addition, we unveiled a genetic predisposition toward albinism in 23 of the 28 new patients (82%). We identified six patients with rare subtypes of albinism, including HPS3, HPS4, and HPS6, and found 12 novel pathological mutations in albinism‐related genes. Furthermore, most patients who were not diagnosed with albinism by the NGS analysis showed mild manifestations of albinism without apparent eye symptoms and harbored only one heterozygous mutation, occasionally in combination with skin‐color associated gene variants.     

Diet assessment of the Atlantic Sea Nettle Chrysaora quinquecirrha in Barnegat Bay,New Jersey,using next‐generation sequencing

Next‐generation sequencing (NGS) methodologies have proven useful in deciphering the food items of generalist predators, but have yet to be applied to gelatinous animal gut and tentacle content. NGS can potentially supplement traditional methods of visual identification. Chrysaora quinquecirrha (Atlantic sea nettle) has progressively become more abundant in Mid‐Atlantic United States’ estuaries including Barnegat Bay (New Jersey), potentially having detrimental effects on both marine organisms and human enterprises. Full characterization of this predator's diet is essential for a comprehensive understanding of its impact on the food web and its management. Here, we tested the efficacy of NGS for prey item determination in the Atlantic sea nettle. We implemented a NGS ‘shotgun’ approach to randomly sequence DNA fragments isolated from gut lavages and gastric pouch/tentacle picks of eight and 84 sea nettles, respectively. These results were verified by visual identification and co‐occurring plankton tows. Over 550 000 contigs were assembled from ~110 million paired‐end reads. Of these, 100 contigs were confidently assigned to 23 different taxa, including soft‐bodied organisms previously undocumented as prey species, including copepods, fish, ctenophores, anemones, amphipods, barnacles, shrimp, polychaete worms, flukes, flatworms, echinoderms, gastropods, bivalves and hemichordates. Our results not only indicate that a ‘shotgun’ NGS approach can supplement visual identification methods, but targeted enrichment of a specific amplicon/gene is not a prerequisite for identifying Atlantic sea nettle prey items.     

A MinION™‐based pipeline for fast and cost‐effective DNA barcoding

DNA barcodes are useful for species discovery and species identification, but obtaining barcodes currently requires a well‐equipped molecular laboratory and is time‐consuming, and/or expensive. We here address these issues by developing a barcoding pipeline for Oxford Nanopore MinION? and demonstrating that one flow cell can generate barcodes for ~500 specimens despite the high basecall error rates of MinION? reads. The pipeline overcomes these errors by first summarizing all reads for the same tagged amplicon as a consensus barcode. Consensus barcodes are overall mismatch‐free but retain indel errors that are concentrated in homopolymeric regions. They are addressed with an optional error correction pipeline that is based on conserved amino acid motifs from publicly available barcodes. The effectiveness of this pipeline is documented by analysing reads from three MinION? runs that represent three different stages of MinION? development. They generated data for (i) 511 specimens of a mixed Diptera sample, (ii) 575 specimens of ants and (iii) 50 specimens of Chironomidae. The run based on the latest chemistry yielded MinION? barcodes for 490 of the 511 specimens which were assessed against reference Sanger barcodes (N = 471). Overall, the MinION? barcodes have an accuracy of 99.3%–100% with the number of ambiguous bases after correction ranging from <0.01% to 1.5% depending on which correction pipeline is used. We demonstrate that it requires ~2 hr of sequencing to gather all information needed for obtaining reliable barcodes for most specimens (>90%). We estimate that up to 1,000 barcodes can be generated in one flow cell and that the cost per barcode can be 相似文献