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Evaluation of whole-genome sequencing of four Chinese crested dogs for variant detection using the ion proton system.

ABSTRACT: BACKGROUND:Next generation sequencing (NGS) has traditionally been performed by large genome centers, but in recent years, the costs for whole-genome sequencing (WGS) have decreased substantially. With the introduction of smaller and less expensive "desktop" systems, NGS is now moving into the general laboratory. To evaluate the Ion Proton system for WGS we sequenced four Chinese Crested dogs and analyzed the data quality in terms of genome and exome coverage, the number of detected single nucleotide variants (SNVs) and insertions and deletions (INDELs) and the genotype concordance with the Illumina HD canine SNP array. For each of the four dogs, a 200 bp fragment library was constructed from genomic DNA and sequenced on two Ion PI chips per dog to reach mean coverage of 6-8x of the canine genome (genome size???2.4 Gb). RESULTS:On average, each Ion PI chip yielded approximately 73.3 million reads with a mean read length of 130 bp (~9.5 Gb sequence data) of which 98.5 % could be aligned to the canine reference genome (CanFam3.1). By sequencing a single dog using one fragment library and two Ion PI chips, on average 80 % of the genome and 77 % exome was covered by at least four reads. After removing duplicate reads (20.7 %) the mean coverage across the whole genome was 6x. Using sequence data from all four individuals (four fragment libraries and eight Ion PI chips) the genome and exome coverage could be further increased to 97.2 and 94.3 %, respectively. We detected 4.83 million unique SNPs and 6.10 million unique INDEL positions across all individuals. A comparison between SNP genotypes detected with the WGS and the 170 K Illumina HD canine SNP array showed 90 % concordance. CONCLUSIONS:We have evaluated whole-genome sequencing on the Ion Proton system for genetic variant detection in four Chinese crested dogs. Even though INDEL calling with Ion Proton data is challenging due to specific platform errors, in case of SNP calling it can serve as an alternative to other next-generation sequencing platforms and SNP genotyping arrays, in studies aiming to identify causative mutations for rare monogenic diseases. In addition, we have identified new genetic variants of the Chinese Crested dog that will contribute to further whole-genome sequencing studies aimed to identify mutations associated with monogenic diseases with autosomal recessive inheritance.

SUBMITTER: Viluma A

PROVIDER: S-EPMC4599337 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Evaluation of whole-genome sequencing of four Chinese crested dogs for variant detection using the ion proton system.

Viluma Agnese A Sayyab Shumaila S Mikko Sofia S Andersson Göran G Bergström Tomas F TF

Canine genetics and epidemiology 20151008

<h4>Background</h4>Next generation sequencing (NGS) has traditionally been performed by large genome centers, but in recent years, the costs for whole-genome sequencing (WGS) have decreased substantially. With the introduction of smaller and less expensive "desktop" systems, NGS is now moving into the general laboratory. To evaluate the Ion Proton system for WGS we sequenced four Chinese Crested dogs and analyzed the data quality in terms of genome and exome coverage, the number of detected sing ...[more]

PMID: 26457193

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Project description:The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illumina's HiSeq2000, Life Technologies' SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics' technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies' platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes.

Project description:BackgroundLess than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions.ResultsWe have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS.ConclusionsFrom an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications.

Project description:IntroductionWhole-genome sequencing using nanopore technologies can uncover structural variants, which are DNA rearrangements larger than 50 base pairs. Nanopore technologies can also characterize their boundaries with single-base accuracy, owing to the kilobase-long reads that encompass either full variants or their junctions. Other methods, such as next-generation short read sequencing or PCR assays, are limited in their capabilities to detect or characterize structural variants. However, the existing software for nanopore sequencing data analysis still reports incomplete variant sets, which also contain erroneous calls, a considerable obstacle for the molecular diagnosis or accurate genotyping of populations.MethodsWe compared multiple factors affecting variant calling, such as reference genome version, aligner (minimap2, NGMLR, and lra) choice, and variant caller combinations (Sniffles, CuteSV, SVIM, and NanoVar), to find the optimal group of tools for calling large (>50 kb) deletions and duplications, using data from seven patients exhibiting gross gene defects on SERPINC1 and from a reference variant set as the control. The goal was to obtain the most complete, yet reasonably specific group of large variants using a single cell of PromethION sequencing, which yielded lower depth coverage than short-read sequencing. We also used a custom method for the statistical analysis of the coverage value to refine the resulting datasets.ResultsWe found that for large deletions and duplications (>50 kb), the existing software performed worse than for smaller ones, in terms of both sensitivity and specificity, and newer tools had not improved this. Our novel software, disCoverage, could polish variant callers' results, improving specificity by up to 62% and sensitivity by 15%, the latter requiring other data or samples.ConclusionWe analyzed the current situation of >50-kb copy number variants with nanopore sequencing, which could be improved. The methods presented in this work could help to identify the known deletions and duplications in a set of patients, while also helping to filter out erroneous calls for these variants, which might aid the efforts to characterize a not-yet well-known fraction of genetic variability in the human genome.

Dataset Information

Evaluation of whole-genome sequencing of four Chinese crested dogs for variant detection using the ion proton system.

Publications

Evaluation of whole-genome sequencing of four Chinese crested dogs for variant detection using the ion proton system.

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