Application of Next-generation Sequencing Technology in Forensic Science

Next-generation sequencing （NGS） technology, with its high-throughput capacity and low cost, has developed rapidly in recent years and become an important analytical tool for many genomics researchers. New opportunities in the research domain of the forensic studies emerge by harnessing the power of NGS technology, which can be applied to simultaneously analyzing multi- ple loci of forensic interest in different genetic contexts, such as autosomes, mitochondrial and sex chromosomes. Furthermore, NGS technology can also have potential applications in many other aspects of research. These include DNA database construction, ancestry and phenotypic inference, monozygotic twin studies, body fluid and species identification, and forensic animal, plant and microbiological analyses. Here we review the application of NGS technology in the field of forensic science with the aim of providing a reference for future forensics studies and practice.     

TECHNICAL ADVANCES: Effects of genotyping protocols on success and errors in identifying individual river otters (Lontra canadensis) from their faeces

In noninvasive genetic sampling, when genotyping error rates are high and recapture rates are low, misidentification of individuals can lead to overestimation of population size. Thus, estimating genotyping errors is imperative. Nonetheless, conducting multiple polymerase chain reactions (PCRs) at multiple loci is time-consuming and costly. To address the controversy regarding the minimum number of PCRs required for obtaining a consensus genotype, we compared consumer-style the performance of two genotyping protocols (multiple-tubes and 'comparative method') in respect to genotyping success and error rates. Our results from 48 faecal samples of river otters (Lontra canadensis) collected in Wyoming in 2003, and from blood samples of five captive river otters amplified with four different primers, suggest that use of the comparative genotyping protocol can minimize the number of PCRs per locus. For all but five samples at one locus, the same consensus genotypes were reached with fewer PCRs and with reduced error rates with this protocol compared to the multiple-tubes method. This finding is reassuring because genotyping errors can occur at relatively high rates even in tissues such as blood and hair. In addition, we found that loci that amplify readily and yield consensus genotypes, may still exhibit high error rates (7-32%) and that amplification with different primers resulted in different types and rates of error. Thus, assigning a genotype based on a single PCR for several loci could result in misidentification of individuals. We recommend that programs designed to statistically assign consensus genotypes should be modified to allow the different treatment of heterozygotes and homozygotes intrinsic to the comparative method.     

Correlation between the number of false positive variants and the quality of results using Ion Torrent PGM™ sequencing to screen BRCA genes

Introduction: Next Generation Sequencing (NGS) is cost-effective and a faster method to study genes, but its protocol is challenging.Objective: To analyze different adjustments to the protocol for screening the BRCA genes using Ion Torrent PGM sequencing and correlate the results with the number of false positive (FP) variants.Material and methods: We conducted a library preparation process and analyzed the number of FP InDels, the library concentration, the number of cycles in the target amplification step, the purity of the nucleic acid, the input, and the number of samples/Ion 314 chips in association with the results obtained by NGS.Results: We carried out 51 reactions and nine adjustments of protocols and observed eight FP InDels in homopolymer regions. No FP Single-Nucleotide Polymorphism variant was observed; 67.5% of protocol variables were jointly associated with the quality of the results obtained (p<0.05). The number of FP InDels decreased when the quality of results increased.Conclusion: The Ion AmpliSeq BRCA1/BRCA2 Community Panel had a better performance using four samples per Ion-314 chip instead of eight and the optimum number of cycles in the amplification step, even when using high-quality DNA, was 23. We observed better results with the manual equalization process and not using the Ion Library Equalizer kit. These adjustments provided a higher coverage of the variants and fewer artifacts (6.7-fold). Laboratories must perform internal validation because FP InDel variants can vary according to the quality of results while the NGS assay should be validated with Sanger.     

Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample

Next-generation sequencing (NGS) is commonly used in metagenomic studies of complex microbial communities but whether or not different NGS platforms recover the same diversity from a sample and their assembled sequences are of comparable quality remain unclear. We compared the two most frequently used platforms, the Roche 454 FLX Titanium and the Illumina Genome Analyzer (GA) II, on the same DNA sample obtained from a complex freshwater planktonic community. Despite the substantial differences in read length and sequencing protocols, the platforms provided a comparable view of the community sampled. For instance, derived assemblies overlapped in ~90% of their total sequences and in situ abundances of genes and genotypes (estimated based on sequence coverage) correlated highly between the two platforms (R(2)>0.9). Evaluation of base-call error, frameshift frequency, and contig length suggested that Illumina offered equivalent, if not better, assemblies than Roche 454. The results from metagenomic samples were further validated against DNA samples of eighteen isolate genomes, which showed a range of genome sizes and G+C% content. We also provide quantitative estimates of the errors in gene and contig sequences assembled from datasets characterized by different levels of complexity and G+C% content. For instance, we noted that homopolymer-associated, single-base errors affected ~1% of the protein sequences recovered in Illumina contigs of 10× coverage and 50% G+C; this frequency increased to ~3% when non-homopolymer errors were also considered. Collectively, our results should serve as a useful practical guide for choosing proper sampling strategies and data possessing protocols for future metagenomic studies.     

dropout: a program to identify problem loci and samples for noninvasive genetic samples in a capture‐mark‐recapture framework

Abstract Genotyping error, often associated with low‐quantity/quality DNA samples, is an important issue when using genetic tags to estimate abundance using capture‐mark‐recapture (CMR). dropout , an MS‐Windows program, identifies both loci and samples that likely contain errors affecting CMR estimates. dropout uses a ‘bimodal test’, that enumerates the number of loci different between each pair of samples, and a ‘difference in capture history test’ (DCH) to determine those loci producing the most errors. Importantly, the DCH test allows one to determine that a data set is error‐free. dropout has been evaluated in McKelvey & Schwartz (2004) and is now available online.     

Next-generation hybridization and introgression

Hybridization has a major role in evolution-from the introgression of important phenotypic traits between species, to the creation of new species through hybrid speciation. Molecular studies of hybridization aim to understand the class of hybrids and the frequency of introgression, detect the signature of ancient hybridization, and understand the behaviour of introgressed loci in their new genomic background. This often involves a large investment in the design and application of molecular markers, leading to a compromise between the depth and breadth of genomic data. New techniques designed to assay a large sub-section of the genome, in association with next-generation sequencing (NGS) technologies, will allow genome-wide hybridization and introgression studies in organisms with no prior sequence data. These detailed genotypic data will unite the breadth of sampling of loci characteristic of population genetics with the depth of sequence information associated with molecular phylogenetics. In this review, we assess the theoretical and methodological constraints that limit our understanding of natural hybridization, and promote the use of NGS for detecting hybridization and introgression between non-model organisms. We also make recommendations for the ways in which emerging techniques, such as pooled barcoded amplicon sequencing and restriction site-associated DNA tags, should be used to overcome current limitations, and enhance our understanding of this evolutionary significant process.     

Using next-generation sequencing approaches to isolate simple sequence repeat (SSR) loci in the plant sciences

The application of next-generation sequencing (NGS) technologies for the development of simple sequence repeat (SSR) or microsatellite loci for genetic research in the botanical sciences is described. Microsatellite markers are one of the most informative and versatile DNA-based markers used in plant genetic research, but their development has traditionally been a difficult and costly process. NGS technologies allow the efficient identification of large numbers of microsatellites at a fraction of the cost and effort of traditional approaches. The major advantage of NGS methods is their ability to produce large amounts of sequence data from which to isolate and develop numerous genome-wide and gene-based microsatellite loci. The two major NGS technologies with emergent application in SSR isolation are 454 and Illumina. A review is provided of several recent studies demonstrating the efficient use of 454 and Illumina technologies for the discovery of microsatellites in plants. Additionally, important aspects during NGS isolation and development of microsatellites are discussed, including the use of computational tools and high-throughput genotyping methods. A data set of microsatellite loci in the plastome and mitochondriome of cranberry (Vaccinium macrocarpon Ait.) is provided to illustrate a successful application of 454 sequencing for SSR discovery. In the future, NGS technologies will massively increase the number of SSRs and other genetic markers available to conduct genetic research in understudied but economically important crops such as cranberry.     

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.     

Association Mapping for Epistasis and Environmental Interaction of Yield Traits in 323 Cotton Cultivars under 9 Different Environments

Improving yield is a major objective for cotton breeding schemes, and lint yield and its three component traits (boll number, boll weight and lint percentage) are complex traits controlled by multiple genes and various environments. Association mapping was performed to detect markers associated with these four traits using 651 simple sequence repeats (SSRs). A mixed linear model including epistasis and environmental interaction was used to screen the loci associated with these four yield traits by 323 accessions of Gossypium hirsutum L. evaluated in nine different environments. 251 significant loci were detected to be associated with lint yield and its three components, including 69 loci with individual effects and all involved in epistasis interactions. These significant loci explain ∼ 62.05% of the phenotypic variance (ranging from 49.06% ∼ 72.29% for these four traits). It was indicated by high contribution of environmental interaction to the phenotypic variance for lint yield and boll numbers, that genetic effects of SSR loci were susceptible to environment factors. Shared loci were also observed among these four traits, which may be used for simultaneous improvement in cotton breeding for yield traits. Furthermore, consistent and elite loci were screened with −Log₁₀ (P-value) >8.0 based on predicted effects of loci detected in different environments. There was one locus and 6 pairs of epistasis for lint yield, 4 loci and 10 epistasis for boll number, 15 loci and 2 epistasis for boll weight, and 2 loci and 5 epistasis for lint percentage, respectively. These results provided insights into the genetic basis of lint yield and its components and may be useful for marker-assisted breeding to improve cotton production.     

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.     

Developing genomic resources in two Linum species via 454 pyrosequencing and genomic reduction

Recent advances in next-generation DNA sequencing (NGS) have enhanced the development of genomic resources such as contigs or single-nucleotide polymorphisms (SNPs) for evolutionary studies of a nonmodel species with a complex and unsequenced genome. This study presents an application of a NGS technique in combination with genomic reduction and advanced bioinformatics tools to identify contigs and SNPs from multiple samples of two Linum species. A full Roche 454 GS FLX run of 16 diverse Linum samples representing cultivated flax (Linum usitatissimum L.) and its wild progenitor (Linum bienne Mill.) generated approximately 1.6 million sequence reads with a total length of 498 Mbp. Application of the computational pipeline de novo identification of alleles identified 713 contigs and 1067 SNPs. A blast search revealed alignments of all 713 contigs with 491 existing Linum scaffolds and gene annotations associated with 512 contigs. Sanger sequencing confirmed 95% of 79 selected contigs and 94% of 272 SNPs and identified 211 new SNPs and 19 new indels. The scored 454 SNP data were highly imbalanced for assayed samples. These findings not only are useful for evolutionary studies of Linum species but also help to illustrate the utility of NGS technologies in SNP discovery for nonmodel organisms.     

Testing for Hardy–Weinberg equilibrium in structured populations using genotype or low‐depth next generation sequencing data

Testing for deviations from Hardy–Weinberg equilibrium (HWE) is a common practice for quality control in genetic studies. Variable sites violating HWE may be identified as technical errors in the sequencing or genotyping process, or they may be of particular evolutionary interest. Large‐scale genetic studies based on next‐generation sequencing (NGS) methods have become more prevalent as cost is decreasing but these methods are still associated with statistical uncertainty. The large‐scale studies usually consist of samples from diverse ancestries that make the existence of some degree of population structure almost inevitable. Precautions are therefore needed when analysing these data set, as population structure causes deviations from HWE. Here we propose a method that takes population structure into account in the testing for HWE, such that other factors causing deviations from HWE can be detected. We show the effectiveness of PCAngsd in low‐depth NGS data, as well as in genotype data, for both simulated and real data set, where the use of genotype likelihoods enables us to model the uncertainty.     

Quantifying genotyping errors in noninvasive population genetics

The use of noninvasively collected samples greatly expands the range of ecological issues that may be investigated through population genetics. Furthermore, the difficulty of obtaining reliable genotypes with samples containing low quantities of amplifiable DNA may be overcome by designing optimal genotyping schemes. Such protocols are mainly determined by the rates of genotyping errors caused by false alleles and allelic dropouts. These errors may not be avoided through laboratory procedure and hence must be quantified. However, the definition of genotyping error rates remains elusive and various estimation methods have been reported in the literature. In this paper we proposed accurate codification for the frequencies of false alleles and allelic dropouts. We then reviewed other estimation methods employed in hair- or faeces-based population genetics studies and modelled the bias associated with erroneous methods. It is emphasized that error rates may be substantially underestimated when using an erroneous approach. Genotyping error rates may be important determinants of the outcome of noninvasive studies and hence should be carefully computed and reported.     

Quality indexes to assess the reliability of genotypes in studies using noninvasive sampling and multiple‐tube approach

In noninvasive studies, the intersample variance in DNA quality and quantity is large, and produces multilocus genotypes of highly variable quality. Here we propose a standardized method for testing the reliability of the genotyping procedure when using the multiple‐tube approach. The quality indexes generated will allow reliable comparisons among samples, loci, studies, and field and/or laboratory protocols. These indexes represent a powerful tool for the quality management of noninvasive studies.     

Development of microsatellite genetic markers in Siberian stone pine (<Emphasis Type="Italic">Pinus sibirica</Emphasis> Du Tour) based on the <Emphasis Type="Italic">de novo</Emphasis> whole genome sequencing

Siberian stone pine, Pinus sibirica Du Tour is one of the most economically and environmentally important forest-forming species of conifers in Russia. To study these forests a large number of highly polymorphic molecular genetic markers, such as microsatellite loci, are required. Prior to the new high-throughput next generation sequencing (NGS) methods, discovery of microsatellite loci and development of micro-satellite markers were very time consuming and laborious. The recently developed draft assembly of the Siberian stone pine genome, sequenced using the NGS methods, allowed us to identify a large number of microsatellite loci in the Siberian stone pine genome and to develop species-specific PCR primers for amplification and genotyping of 70 microsatellite loci. The primers were designed using contigs containing short simple sequence tandem repeats from the Siberian stone pine whole genome draft assembly. Based on the testing of primers for 70 microsatellite loci with tri-, tetra- or pentanucleotide repeats, 18 most promising, reliable and polymorphic loci were selected that can be used further as molecular genetic markers in population genetic studies of Siberian stone pine.     

Customisation of the exome data analysis pipeline using a combinatorial approach

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.     

Assembly errors cause false tandem duplicate regions in the chicken (Gallus gallus) genome sequence

The complexity of eukaryote genomes makes assembly errors inevitable in the process of constructing reference genomes. Next-generation sequencing (NGS) could provide an efficient way to validate previously assembled genomes. Here, we exploited NGS data to interrogate the chicken reference genome and identified 35 pairs of nearly identical regions with >99.5 % sequence similarity and a median size of 109 kb. Several lines of evidence, including read depth, the composition of junction sequences, and sequence similarity, suggest that these regions present genome assembly errors and should be excluded from forthcoming genomic studies.     

Characterization of AT-rich microsatellites in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Polymorphism of microsatellite markers is often associated with the simple sequence repeat motif targeted. AT-rich microsatellites tend to be highly variable and this appears to be notable, especially in legume genomes. To analyze the value of AT-rich microsatellites for common bean (Phaseolus vulgaris L.), we developed a total of 85 new microsatellite markers, 74 of which targeted ATA or other AT-rich motif loci and 11 of which were made for GA, CA or CAC motif loci. We evaluated the loci for the level of allelic diversity in comparison to previously characterized microsatellites using a panel of 18 standard genotypes and genetically mapped any loci polymorphic in the DOR364 × G19833 population. The majority of the microsatellites produced single bands and detected single loci, however, 15 of the AT-rich microsatellites produced multiple or double banding patterns; while only one of the GA or CA-rich microsatellites did. The polymorphism information content (PIC) values averaged 0.892 and 0.600 for the AT and ATA motif microsatellites, respectively, but only 0.140 for the CA-rich microsatellites. GA microsatellites, which had a large average number of repeats, had high to intermediate PIC, averaging 0.706. A total of 45 loci could be genetically mapped and distribution of the loci across the genome was skewed towards non-distal locations with a greater prevalence of loci on linkage groups b02, b09 and b11. AT-rich microsatellites were found to be a useful source of polymorphic markers for mapping and diversity assessment in common bean that appears to uncover higher diversity than other types of simple sequence repeat markers.