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Discovery of potential causative mutations in human coding and noncoding genome with the interactive software BasePlayer

Nature Protocols volume 13, pages 2580–2600 (2018)Cite this article

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Abstract

Next-generation sequencing (NGS) is routinely applied in life sciences and clinical practice, but interpretation of the massive quantities of genomic data produced has become a critical challenge. The genome-wide mutation analyses enabled by NGS have had a revolutionary impact in revealing the predisposing and driving DNA alterations behind a multitude of disorders. The workflow to identify causative mutations from NGS data, for example in cancer and rare diseases, commonly involves phases such as quality filtering, case–control comparison, genome annotation, and visual validation, which require multiple processing steps and usage of various tools and scripts. To this end, we have introduced an interactive and user-friendly multi-platform-compatible software, BasePlayer, which allows scientists, regardless of bioinformatics training, to carry out variant analysis in disease genetics settings. A genome-wide scan of regulatory regions for mutation clusters can be carried out with a desktop computer in ~10 min with a dataset of 3 million somatic variants in 200 whole-genome-sequenced (WGS) cancers.

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Fig. 1: Overview of the NGS data analysis capabilities and features of BasePlayer.
Fig. 2: The main window of BasePlayer, displaying three samples, a genomic region track and a population control data track.
Fig. 3: Variant Manager user interface and functions.
Fig. 4: Candidate genes in the result table and variant visualization.
Fig. 5: Somatic variants in the regulatory genome.
Fig. 6: Variant Manager settings in somatic cluster analysis.
Fig. 7: Somatic clustering results.
Fig. 8: Variant quality validation by read-level inspection.

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Data availability

No previously unpublished data sets were generated or analyzed during the current study.

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Acknowledgements

We thank T. Kivioja for his guidance in regard to the SELEX data and A. Ollikainen for the voice-over in the demonstration videos. We thank B. Pradhan and L. Kauppi for sharing their unpublished Nanopore data. We also thank M. Aavikko, L. van den Berg, D. Berta, O. Kilpivaara, J. Kondelin, H. Kuisma, Y. Li, M. Mehine, H. Metsola, J. Ravantti, L. Sipilä, T. Tanskanen, P. Vahteristo and N. Välimäki for testing BasePlayer and giving suggestions and additional support. We acknowledge ZeroTurnaround for creating the JRebel plugin for Eclipse (IDE). This work was supported by grants from the Biomedicum Helsinki Foundation; the Cancer Society of Finland; the Emil Aaltonen Foundation; the Juhani Aho Foundation for Medical Research; the Sigrid Juselius Foundation; the Academy of Finland (Finnish Center of Excellence Program 2012–2017, 250345); the European Research Council (ERC, 268648); a European Union Framework Programme 7 Collaborative Project (SYSCOL, 258236); the Nordic Information for Action eScience Center (NIASC); and a Nordic Center of Excellence grant financed by NordForsk (62721 to K.P.).

Author information

Authors and Affiliations

  1. Genome-Scale Biology Research Program, Research Programs Unit, University of Helsinki, Helsinki, Finland

    Riku Katainen, Iikki Donner, Tatiana Cajuso, Eevi Kaasinen, Kimmo Palin, Lauri A. Aaltonen & Esa Pitkänen

  2. Department of Medical and Clinical Genetics, Medicum, University of Helsinki, Helsinki, Finland

    Riku Katainen, Iikki Donner, Tatiana Cajuso, Eevi Kaasinen, Kimmo Palin, Lauri A. Aaltonen & Esa Pitkänen

  3. Department of Computer Science and Helsinki Institute for Information Technology, University of Helsinki, Helsinki, Finland

    Veli Mäkinen

  4. Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany

    Esa Pitkänen

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  1. Riku Katainen
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Contributions

R.K. designed and developed the protocol. R.K. and E.P. wrote the protocol. I.D. contributed to writing the protocol. I.D., T.C., E.K. and K.P. assisted in developing and testing the software. E.P., V.M. and L.A.A. supervised the research.

Corresponding authors

Correspondence to Riku Katainen or Esa Pitkänen.

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The authors declare no competing interests.

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Related links

Key references using this protocol

1. Katainen, R. et al. Nat. Genet. 47, 818–821 (2015): https://doi.org/10.1038/ng.3335

2. Pradhan, B. et al. Sci. Rep. 7, 14521 (2017): https://doi.org/10.1038/s41598-017-15076-3

3. Donner, I. et al. Genes Chromosomes Cancer 56, 453–459 (2017): https://doi.org/10.1002/gcc.22448

Integrated supplementary information

Supplementary Figure 1 BasePlayer settings for variant analysis in recessive case.

A family trio and gnomAD exome control files are opened. Son (uppermost sample track) is set as an affected male. The parents are selected accordingly from the dropdown menus. “Recessive” checkbox is selected in “Inheritance” tab of the “Variant Manager”.

Supplementary Figure 2 Visualization of long-read sequencing data in BasePlayer.

Three split views are shown, tracking the split mappings for a single long read. An inset info panel shows information on the selected read and a schematic illustration of split read orientations (bottom of the info panel).

Supplementary Figure 3 TF binding affinity change prediction settings in BasePlayer.

(a) Affinity change annotation settings without variant filtering. (b) Affinity change annotation settings with variant filtering. Value limit is set to “1”. (c) Annotation results. Affinity change for each overlapping TFs are shown in the variant row of the result table (red circle). In the circled case, the variant occurs at the HOXD12 binding site, which has affinity score of 6.57 at that locus and variant decreases the binding affinity by 1.52. (d) TF motif and variant visualization at sequence level zoom. Affinity changes for each overlapping TFs are reported in “VCF info” dialog (bottom-right) if the track is applied and “report affinity change” is selected in the track settings.

Supplementary Figure 4 CADD prediction settings in BasePlayer.

(a) The column selector for TSV files. (b) Selected column headers for the CADD TSV file. (c) Track settings for the CADD annotation. (d) Annotation results. CADD annotation is shown in the variant row of the result table (red circle).

Supplementary Figure 5 Variant analysis steps in Procedure Case 1.

The effects of filtering, comparison and annotation on variant counts (top right corner of the Variant Manager) in chromosome 10. (a) Initial setup with no filters applied. (b) Quality and coverage filtering thresholds are set. (c) Only coding variants shared by all samples are visible. (d) Linkage compatible regions applied. Variants outside these regions are excluded. (e) Control file (gnomAD exomes) applied, resulting in one shared variant.

Supplementary Figure 6 M-CAP annotation settings in BasePlayer.

(a) Column selector for M-CAP file. Fourth column is set as “Base”. (b) Track settings for M-CAP track. Value limit is set to 0.025 and “Intersect” is unselected. “File format” button opens the “Column selector”.

Supplementary Figure 7 ClinVar annotation settings in BasePlayer.

“Annotation” checkbox is selected for the VCF track.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Table 1 and Supplementary Tutorials 1–5

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Katainen, R., Donner, I., Cajuso, T. et al. Discovery of potential causative mutations in human coding and noncoding genome with the interactive software BasePlayer. Nat Protoc 13, 2580–2600 (2018). https://doi.org/10.1038/s41596-018-0052-3

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