Dataset Information

Alternate-locus aware variant calling in whole genome sequencing.

ABSTRACT: BACKGROUND:The last two human genome assemblies have extended the previous linear golden-path paradigm of the human genome to a graph-like model to better represent regions with a high degree of structural variability. The new model offers opportunities to improve the technical validity of variant calling in whole-genome sequencing (WGS). METHODS:We developed an algorithm that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38 genome assembly, and infers whether a given sample is most likely to contain sequences from the primary assembly, an alternate locus, or their heterozygous combination at each of these 178 regions. We investigate 121 in-house WGS datasets that have been aligned to the GRCh37 and GRCh38 assemblies. RESULTS:We show that stretches of sequences that are largely but not entirely identical between the primary assembly and an alternate locus can result in multiple variant calls against regions of the primary assembly. In WGS analysis, this results in characteristic and recognizable patterns of variant calls at positions that we term alignable scaffold-discrepant positions (ASDPs). In 121 in-house genomes, on average 51.8±3.8 of the 178 regions were found to correspond best to an alternate locus rather than the primary assembly sequence, and filtering these genomes with our algorithm led to the identification of 7863 variant calls per genome that colocalized with ASDPs. Additionally, we found that 437 of 791 genome-wide association study hits located within one of the regions corresponded to ASDPs. CONCLUSIONS:Our algorithm uses the information contained in the 178 structurally variable regions of the GRCh38 genome assembly to avoid spurious variant calls in cases where samples contain an alternate locus rather than the corresponding segment of the primary assembly. These results suggest the great potential of fully incorporating the resources of graph-like genome assemblies into variant calling, but also underscore the importance of developing computational resources that will allow a full reconstruction of the genotype in personal genomes. Our algorithm is freely available at https://github.com/charite/asdpex .

SUBMITTER: Jager M

PROVIDER: S-EPMC5155401 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Alternate-locus aware variant calling in whole genome sequencing.

Jäger Marten M Schubach Max M Zemojtel Tomasz T Reinert Knut K Church Deanna M DM Robinson Peter N PN

Genome medicine 20161213 1

<h4>Background</h4>The last two human genome assemblies have extended the previous linear golden-path paradigm of the human genome to a graph-like model to better represent regions with a high degree of structural variability. The new model offers opportunities to improve the technical validity of variant calling in whole-genome sequencing (WGS).<h4>Methods</h4>We developed an algorithm that analyzes the patterns of variant calls in the 178 structurally variable regions of the GRCh38 genome asse ...[more]

PMID: 27964746

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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.

Dataset Information

Alternate-locus aware variant calling in whole genome sequencing.

Publications

Alternate-locus aware variant calling in whole genome sequencing.

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