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Genomic sequence characteristics and the empiric accuracy of short-read sequencing

View ORCID ProfileMaximillian Marin, View ORCID ProfileRoger Vargas Jr, Michael Harris, Brendan Jeffrey, View ORCID ProfileL. Elaine Epperson, David Durbin, View ORCID ProfileMichael Strong, Max Salfinger, View ORCID ProfileZamin Iqbal, Irada Akhundova, Sergo Vashakidze, View ORCID ProfileValeriu Crudu, View ORCID ProfileAlex Rosenthal, View ORCID ProfileMaha Reda Farhat
doi: https://doi.org/10.1101/2021.04.08.438862
Maximillian Marin
1Department of Biomedical Informatics, Harvard Medical School, Boston, USA
2Department of Systems Biology, Harvard Medical School, Boston, USA
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  • For correspondence: mgmarin@g.harvard.edu Maha_Farhat@hms.harvard.edu
Roger Vargas Jr
1Department of Biomedical Informatics, Harvard Medical School, Boston, USA
2Department of Systems Biology, Harvard Medical School, Boston, USA
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Michael Harris
3Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA
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Brendan Jeffrey
3Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA
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L. Elaine Epperson
4Center for Genes, Environment, and Health, National Jewish Health, Denver, Colorado, USA
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David Durbin
5Mycobacteriology Reference Laboratory, Advanced Diagnostic Laboratories, National Jewish Health, Denver, Colorado, USA
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Michael Strong
4Center for Genes, Environment, and Health, National Jewish Health, Denver, Colorado, USA
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Max Salfinger
6College of Public Health & Morsani College of Medicine, University of South Florida, USA
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Zamin Iqbal
7EMBL-EBI, Wellcome Genome Campus, Hinxton, UK
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Irada Akhundova
8Scientific Research Institute of Lung Diseases, Ministry of Health, Baku, Azerbaijan
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Sergo Vashakidze
9National Center for Tuberculosis and Lung Diseases, Ministry of Health, Tbilisi, Georgia
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Valeriu Crudu
10Phthisiopneumology Institute, Chisinau, Moldova
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Alex Rosenthal
3Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA
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Maha Reda Farhat
1Department of Biomedical Informatics, Harvard Medical School, Boston, USA
11Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, USA
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  • For correspondence: mgmarin@g.harvard.edu Maha_Farhat@hms.harvard.edu
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Abstract

Background Short-read whole genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences, and sequencing bias, reduce the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. For the clonal pathogen Mycobacterium tuberculosis (Mtb), researchers frequently exclude 10.7% of the genome believed to be repetitive and prone to erroneous variant calls. To benchmark short-read variant calling, we used 36 diverse clinical Mtb isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically study the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias, and GC content.

Results Reference based Illumina variant calling had a recall ≥89.0% and precision ≥98.5% across parameters evaluated. The best balance between precision and recall was achieved by tuning the mapping quality (MQ) threshold, i.e. confidence of the read mapping (recall 85.8%, precision 99.1% at MQ ≥ 40). Masking repetitive sequence content is an alternative conservative approach to variant calling that maintains high precision (recall 70.2%, precision 99.6% at MQ≥40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52 of the 168 PE/PPE genes (34.5%). We present a refined list of low confidence regions and examine the largest sources of variant calling error.

Conclusions Our improved approach to variant calling has broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems, and more generally for WGS applications in other organisms.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://zenodo.org/record/4662193

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 11, 2021.
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Genomic sequence characteristics and the empiric accuracy of short-read sequencing
Maximillian Marin, Roger Vargas Jr, Michael Harris, Brendan Jeffrey, L. Elaine Epperson, David Durbin, Michael Strong, Max Salfinger, Zamin Iqbal, Irada Akhundova, Sergo Vashakidze, Valeriu Crudu, Alex Rosenthal, Maha Reda Farhat
bioRxiv 2021.04.08.438862; doi: https://doi.org/10.1101/2021.04.08.438862
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Genomic sequence characteristics and the empiric accuracy of short-read sequencing
Maximillian Marin, Roger Vargas Jr, Michael Harris, Brendan Jeffrey, L. Elaine Epperson, David Durbin, Michael Strong, Max Salfinger, Zamin Iqbal, Irada Akhundova, Sergo Vashakidze, Valeriu Crudu, Alex Rosenthal, Maha Reda Farhat
bioRxiv 2021.04.08.438862; doi: https://doi.org/10.1101/2021.04.08.438862

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