(*contributed equally to this work) Published: Vol 9, Iss 13, Jul 5, 2019 DOI: 10.21769/BioProtoc.3283 Views: 4744
Reviewed by: Chiara AmbrogioEnrico PatruccoMauro Sbroggio'
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Abstract
Detecting heteroplasmies in the mitochondrial DNA (mtDNA) has been a challenge for many years. In the past, Sanger sequencing was the main option to perform this analysis, however, this method could not detect low frequency heteroplasmies. Massive Parallel Sequencing (MPS) provides the opportunity to study the mtDNA in depth, but a controlled pipeline is necessary to reliably retrieve and quantify the low frequency variants. It has been shown that differences in methods can significantly affect the number and frequency of the retrieved variants.
In this protocol, we present a method involving both wet lab and bioinformatics that allows identifying and quantifying single nucleotide variants in the full mtDNA sequence, down to a heteroplasmic load of 1.5%. For this, we set up a PCR-based amplification of the mtDNA, followed by MPS using Illumina chemistry, and variant calling with two different algorithms, mtDNA server and Mutect.
The PCR amplification is used to enrich the mitochondrial fraction, while the bioinformatic processing with two algorithms is used to discriminate the true heteroplasmies from background noise. The protocol described here allows for deep sequencing of the mitochondrial DNA in bulk DNA samples as well as single cells (both large cells such as human oocytes, and small-sized single cells such as human embryonic stem cells) with minor modifications to the protocol.
Background
In the past, the methods used for studying the mtDNA were amongst others PCR-RFLP (PCR-restriction fragment length polymorphism), Sanger sequencing and mitochondrial DNA re-sequencing using Affymetrix’s MitoChip. However, these methods are not able to accurately quantify the heteroplasmic load under 10%. Massive Parallel Sequencing (MPS) represents, in all likelihood, the best solution to investigate variants in the mitochondrial genome. However, when analyzing mtDNA there are two key factors that make mtDNA analysis less straightforward compared to the nuclear genome. First, the mtDNA contains regions with significant homology to regions dispersed within the nuclear genome called nuclear mitochondrial DNA sequences (NuMTS). Second, multiple mtDNA copies are present within a cell, and variants can be present at frequencies ranging between 0 and 100%. For this reason, when performing MPS analysis of the mtDNA different strategies might be applied to accurately identify and quantify single nucleotide variants (SNVs). The best approach to overcome the first problem is to enrich the sample for its mitochondrial genome only. This can be achieved by selectively amplifying the mtDNA by long-range PCR, by isolating the mtDNA using mtDNA enrichment kits, or by isolating the mitochondria themselves prior to DNA extraction (Just et al., 2015). The second issue is more challenging. Whilst MPS provides the ideal type of data to simultaneously identify SNVs and/or rearrangements and calculating their loads, the manner in which the data are generated and processed will not only determine the type of variants that can be detected, but also their lower threshold. If an SNV is present at a very low frequency, its signal will be undistinguishable from the systems sequencing errors (Bai and Wong, 2004; Rohlin et al., 2009; Zhang et al., 2012; Ye et al., 2014). Recently, many pipelines have been released to identify and quantify variants. However, bioinformatic processing does not represent the only critical step in these analyses. In our hands, we found that the initial amplification of the template is an extremely important step for the correct evaluation of SNV frequencies, such that a suboptimal PCR amplification leads to a gross overestimation of the retrieved frequencies (Zambelli et al., 2017). This is especially the case for PCR protocols with higher cycle numbers and primer sets that do not result in a linear amplification. The method we present here can be used to accurately detect and quantify single nucleotide variants at a low heteroplasmic load (as low as 1.5%) in both bulk DNA samples and single cells (Zambelli et al., 2017 and 2018). We here describe amplification conditions and bioinformatic processing for both bulk DNA and single cells with detailed information and screenshots about the bioinformatic steps.
Materials and Reagents
Note: These two primer sets (Items 12 and 13) were selected because they were able to amplify large fragments of the mtDNA and tested negative when amplifying Rho Zero cells, indicating that they did not amplify NuMTS in the nuclear genome. These primer sets were also evaluated for their performance in low frequency heteroplasmy calling by performing spike-in experiments and were shown to give the better estimation of the low frequency variants (Zambelli et al., 2017).
Equipment
Software
Procedure
Data analysis
Recipes
Acknowledgments
This work was funded by the Wetenschappelijke Fonds Willy Gepts (UZ Brussel), the Fonds voor Wetenschappelijk Onderzoek (FWO, 1506616N) and the Methusalem grant of the Vrije Universiteit Brussel to Prof. Karen Sermon.
Competing interests
None.
Ethics
In this protocol, we have used human mtDNA for optimization only. All donors gave their informed consent and all studies related to this protocol received approval of appropriate local ethical committees.
References
Article Information
Copyright
© 2019 The Authors; exclusive licensee Bio-protocol LLC.
How to cite
Mertens, J., Zambelli, F., Daneels, D., Caljon, B., Sermon, K. and Spits, C. (2019). Detection of Heteroplasmic Variants in the Mitochondrial Genome through Massive Parallel Sequencing. Bio-protocol 9(13): e3283. DOI: 10.21769/BioProtoc.3283.
Category
Molecular Biology > DNA > DNA sequencing
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