Germline and somatic variant identification using BGISEQ-500 and HiSeq X Ten whole genome sequencing

Our plain-English summary of Germline and somatic variant identification using BGISEQ-500 and HiSeq X Ten whole genome sequencing, by A.M. Patch, K. Nones, S.H. Kazakoff, et al (PloS One, 2018).

The study

• Authors: A.M. Patch, K. Nones, S.H. Kazakoff, F. Newell, S. Wood, C. Leonard, O. Holmes, Q. Xu, V. Addala, J. Creaney, B.W. Robinson, S. Fu, C. Geng, T. Li, W. Zhang, X. Liang, J. Rao, J. Wang, M. Tian, Y. Zhao, F. Teng, H. Gou, B. Yang, H. Jiang, F. Mu, J.V. Pearson, N. Waddell
• Journal: PloS One
• Published: 2018;13(1):e0190264
• Cited by: 44 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Technological innovation and increased affordability have contributed to the widespread adoption of genome sequencing technologies in biomedical research. In particular large cancer research consortia have embraced next generation sequencing, and have used the technology to define the somatic mutation landscape of multiple cancer types. These studies have primarily utilised the Illumina HiSeq platforms. In this study we performed whole genome sequencing of three malignant pleural mesothelioma and matched normal samples using a new platform, the BGISEQ-500, and compared the results obtained with Illumina HiSeq X Ten. Germline and somatic, single nucleotide variants and small insertions or deletions were independently identified from data aligned human genome reference. The BGISEQ-500 and HiSeq X Ten platforms showed high concordance for germline calls with genotypes from SNP arrays (>99%). The germline and somatic single nucleotide variants identified in both sequencing platforms were highly concordant (86% and 72% respectively). These results indicate the potential applicability of the BGISEQ-500 platform for the identification of somatic and germline single nucleotide variants by whole genome sequencing. The BGISEQ-500 datasets described here represent the first publicly-available cancer genome sequencing performed using this platform.

In plain English

This was a technical study comparing two machines that read a person's full DNA sequence: the newer BGISEQ-500 and the Illumina HiSeq X Ten. The authors sequenced tumour DNA from pleural fluid and matched normal DNA from the blood of three patients diagnosed with malignant pleural mesothelioma in Perth, Western Australia. The article does not report the patients' asbestos exposure. Both machines matched standard SNP array results more than 99% of the time. For inherited (germline) single-letter DNA changes, 86% were found by both machines. For small inherited insertions or deletions, the figure was 81.5%. For single-letter changes acquired by the tumour (somatic), 72% were found by both machines. Only 38% of somatic insertions or deletions were found by both. Of 156 somatic mutations in gene coding regions, 109 (70%) were found by both machines, including one in BAP1, which the authors call a known mesothelioma driver gene. The authors attributed part of the disagreement to the BGISEQ-500's shorter reads and to an analysis pipeline built for longer reads. The authors concluded that the two platforms showed high concordance.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Laboratory comparison of two whole genome sequencing platforms (BGISEQ-500 and Illumina HiSeq X Ten), using the same tumour and matched normal DNA samples
• Who was studied: Three patients (identified as 9869, 11202 and 11398) diagnosed with malignant pleural mesothelioma at Sir Charles Gairdner Hospital, Perth, Western Australia. Tumour DNA came from pleural effusion and normal DNA from blood. Estimated tumour content was 89%, 78% and 81% respectively. Dates of collection are not given.
• Exposure: The article does not report asbestos or any other exposure for the patients. What the study compared was two sequencing platforms.
• Main results:
  • Both platforms agreed with SNP array genotypes more than 99% of the time (about 99.79% for each patient on each platform).
  • 86% of germline single nucleotide variants (SNV) were identified by both platforms.
  • 81.5% of germline small insertions or deletions (indels) were identified by both platforms.
  • Across the 3 patients, 197,434 germline SNVs (1.85%) were truly unique to the HiSeq X Ten. 38,236 (0.36% of the total) were truly unique to the BGISEQ-500.
  • 96.8% of the 9,272,840 germline SNVs called by both platforms had been reported in the gnomAD population database.
  • The HiSeq X Ten detected more germline indels longer than 8 base pairs.
  • Of 10,890 somatic SNVs across all three patients, 72% were identified by both platforms, 14% only by the HiSeq X Ten and 14% only by the BGISEQ-500.
  • 38% of somatic indels were identified by both platforms. Table 2 counts are 479 in both platforms, 306 HiSeq X Ten only and 487 BGISEQ-500 only, out of 1,272.
  • 156 somatic mutations (141 SNV and 15 indels) were in gene coding regions. Of these, 109 (70%) were identified by both platforms, including a mutation in BAP1.
  • The three tumours had between 0.85 and 1.52 somatic mutations per megabase. The authors described this as at the low end across cancers.
• The authors' conclusion: The authors concluded that both platforms showed high concordance with SNP array genotypes. They also concluded that the two platforms showed high concordance with each other for detecting germline and somatic SNVs and indels.
• Limitations the authors state:
  • The platforms used different read lengths (50 bp for BGISEQ-500, 150 bp for HiSeq X Ten), which contributed to differences in variant calls.
  • The alignment software used (BWA-MEM) was designed for reads over 70 bp and may have penalised the shorter BGISEQ-500 reads.
  • The same analysis pipeline, built for long Illumina reads, was applied to both datasets.
  • Random sampling of DNA molecules during library preparation and sequencing likely caused some discordant calls.
  • Library preparation differed between platforms, introducing bias that could particularly affect somatic variant calling.

Topics

Medical terms in this study, explained in our Lexicon: Somatic Mutation, Pleural Mesothelioma.

Related studies

• Whole exome and targeted deep sequencing identify genome-wide allelic loss and frequent SETDB1 mutations in malignant pleural mesotheliomas — H.C. Kang, H.K. Kim, et al. (2016)
• Establishment and mutation analysis of a novel malignant peritoneal mesothelioma cell line, TU-MM-1, using whole genome sequencing — N. Oumi, H. Itamochi, et al. (2016)
• Genome Evolution Analysis of Recurrent Testicular Malignant Mesothelioma by Whole-Genome Sequencing — S. Zhang, Q. Zhang, et al. (2018)
• Whole-genome sequencing of human malignant mesothelioma tumours and cell lines — H. Oey, M. Daniels, et al. (2019)
• Comprehensive genomic and tumour immune profiling reveals potential therapeutic targets in malignant pleural mesothelioma — J. Creaney, A.M. Patch, et al. (2022)
• Whole exome sequencing of an asbestos-induced wild-type murine model of malignant mesothelioma — S. Sneddon, A.M. Patch, et al. (2017)

Browse more research in PloS One, or return to medical research.