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Webinar Q&A: How library preparation affects sequencing accuracy
Q:	How would you limit DNA damage in the typical DNA
extraction/library prep?

A:	
Damage can be limited by performing acoustic shearing of genomic DNA

Q:	How do you correct for substitution mutations in your library?

What would you want to consider if you are looking for somatic
mutations in your sample?

in 1X TE (10 mM Tris pH 8, 1 mM EDTA), rather than less buffered
A: Higher coverage can help distinguish substitution errors from true somatic
variation, so obtaining greater sequencing depth may help. True somatic
solutions. Treating the genomic DNA with the NEBNext FFPE DNA
Repair Mix after shearing, but before library preparation, will also reduce
variation is more likely to appear in multiple reads, while sequencing errors
and polymerase substitutions are more likely to be randomly distributed. For
DNA damage prior to sequencing. More information about DNA damage
and repair mixes can be found on our website.
removing substitution and sequencing errors completely, different library
preparation methods are required. PCR-free library preparation methods are	Additional reference: Costello, M., Pugh, T. J., Fennell, T. J., Stewart,
available, as well as methods that utilize Unique Molecular Identifiers (seeC., Lichtenstein, L., Meldrim, J. C., et al. (2013). Discovery andreferences below).
characterization of artifactual mutations in deep coverage targeted
capture sequencing data due to oxidative DNA damage during sample	For detecting somatic variation, it is also recommended to be aware of DNA
damage that can be introduced during library preparation (especially during
preparation. Nucleic Acids Research, 41(6), e67–e67.
shearing). To reduce oxidative damage during acoustic shearing, sonication
in a buffered solution (1X TE, pH 8) is recommended. In addition, DNA
Q:	Can you talk a little more about PreCR repair?
repair after shearing, but before library preparation, will repair oxidative andHow does it work?
other types of DNA damage. Additionally, calculating the GIV score can beused for quality control analysis.
A:	
The PreCR Repair Mix and the NEBNext FFPE DNA Repair Mix
are enzyme cocktails that recognize and repair DNA damage. Both	(1) Kinde, I., Wu, J., Papadopoulos, N., Kinzler, K. W., & Vogelstein, B.
DNA repair mixes contain DNA repair enzymes that recognize and(2011). Detection and quantification of rare mutations with massively
remove damaged bases; then a DNA polymerase and ligase will replaceparallel sequencing. PNAS U.S.A., 108(23), 9530-9535.
the excised base and seal the resulting nick. Multiple repair enzymes	(2) Schmitt, M. W., Kennedy, S. R., Salk, J. J., Fox, E. J., Hiatt, J. B., & Loeb,
recognize specific types of DNA damage typically resulting from
L. A. (2012). Detection of ultra-rare mutations by next-generationoxidation, hydrolysis, UV irradiation and shearing. The ligase present insequencing. PNAS U.S.A., 109(36), 14508–14513.
the mixture will not ligate blunt DNA ends, nor nicks near a mismatch,
thereby avoiding ligation chimeras. We have also shown that DNA repair
reduces false positive mutations significantly, but does not change variant Q:	
In other words, if you are limited by the errors originating
frequency (indicating that DNA repair does not introduce new mutations).
from library prep, is it worth improving sequencing accuracy
Both the PreCR Repair Mix and the NEBNext FFPE DNA Repair Mix
at this point?
repair the same spectrum of DNA damage, but the NEBNext FFPE DNA
A:	
Yes, there is still a need to improve sequencing accuracy to allow greater
Repair Mix has been optimized and validated for use in next-generation
sensitivity for detecting rare mutations. Technology development tosequencing workflows.
improve sequencing accuracy remains an active area of research.

Q:	Would you recommend DNA damage repair before Illumina
sequencing as a normal part of a protocol?

A:	
For routine sequencing (fresh samples, high input and high sequencing

coverage), DNA damage repair is probably not necessary. However, for
low input samples, archived clinical samples (especially DNA extracted
from FFPE samples), or for detecting low-frequency variation inheterogeneous populations, then DNA damage repair can help increaselibrary yields, sequencing quality and reduce false positive mutation calls.

Q:	With Illumina sequencing and NEBNext, what percentage oferrors (on average) originate from sample prep? How does thenumber of PCR-mediated mutations introduced compare to thenumber of mutations introduced during the actual sequencing?

A:	For most applications, Illumina sequencing errors from single-pass reads
will be more abundant than the errors originating from DNA damageor PCR. However, for examining low-frequency variation (for example,
tumor heterogeneity), errors originating from DNA damage or PCR canlook very similar to low-frequency variation, making it more difficult to
identify true allelic variation.

Q:	Could you explain the GIV score a bit more?
A:	
DNA damage only affects one nucleotide of a pair, leading to an imbalanceof one particular type of mutation. Thus, DNA damage results in asystematic and global excess of particular mutations (for example G toT) and a specific signature: an excess of one mutation in the first paired
read (R1), and a corresponding excess of the reverse complement of themutation in the second paired read (R2). To estimate the extent of DNA
damage in an Illumina data set, we compute a global imbalance value(GIV) score. A GIV score greater than 1 indicates DNA damage, whileundamaged DNA will have a GIV score of 1.
	More specifically, the analysis strategy consists of deconvoluting both theorigin and orientation of variants and computing a global imbalance value(GIV). The GIV score is determined using the following equation:
	GIVG_T = ((C1v + C2v) / (C1 + C2)) / ((C1v_RC + C2v_RC)/(C1_RC+C2_RC))
continued on page 2

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	With C1v = Number of G to T variants in R1 (read 1); C1 = Total
number of G in R1; C2v = Number of C to A variants in R2 (read2); C2 = Total number of C in R2; C1v_RC = Number of C to
A variants in R1; C1_RC = Total number of C in R1; C2v_RC =Number of G to T variants in R2; C2_RC = Total number of G
in R2. For more information see Chen, L., et. al., Science (2017),
355(6326):752-756.
The source code to calculate the GIV score is available at here.

Q:	Can you use a GIV score to remove low frequency variants

caused by DNA damage? If so does it work with downstream
analysis.

A:	
The current algorithm will not support the removal of variants caused
by DNA damage. The GIV score is a global measure of the imbalancein the dataset, and is indicative of the extent of DNA damage, butcannot pinpoint which particular mutations originate from damage.

Q:	So the best route to minimize damage is to use a high fidelity
polymerase and DNA repair enzymes?

A:	
Yes, using the NEBNext FFPE DNA Repair mix to repair damage,and a high-fidelity DNA polymerase (like the NEBNext Ultra II Q5
Master Mix), will reduce sequencing errors due to DNA damage and
PCR polymerase mistakes. Reducing the number of PCR cycles will
also help.

Q:	What are the sequencing accuracy (e.g. SNP calling)
implications of cross over events during PCR?

A:	
The implications of template-switching in PCR is most applicableto NGS assays that rely on amplifying and sequencing very similartargets. Amplicon sequencing applications such as microbial
identification by 16S rRNA, HLA genotyping, or viral population
studies can be affected by PCR-mediated recombination artifacts.
PCR-based multiplex target enrichment strategies could also beaffected. Calling individual SNPs in distinct genomic sequences
probably won't be affected.

Q:	Why did you only do the tests with 16 cycles and not 30–40
cycles as most PCRs?

A:	
We used 16 cycles of PCR in our assays to ensure that theamplification is still in the linear range (meaning that the replication
efficiency per cycle is constant throughout amplification). We could
then determine the number of template doublings that occurred
based on the input DNA amount and PCR yield, and then normalize
the raw error rate (errors counted after PCR) to the number ofdoubling events for each polymerase. This allows us to determine
the errors per replication event, which makes it easier to compare
different polymerases (regardless of the replication efficiency of eachenzyme) and compare our results to previous studies.

Q:	You used PacBio sequencing to analyze the types of error.

WEBINAR Q&A

we expect plasmid DNA to have an undetectable error rate in our assay.
Any errors detected in the plasmid libraries were attributed to PacBio
sequencing and library preparation. The background error rate for the
fidelity assay was determined to be 9.6 x 10-8 substitutions per base,
but higher for insertions/deletions (3.1 x 10-6 per base). Note, ourassay is for single-stranded consensus reads (top and bottom strand
separately). The standard PacBio sequence analysis tools analyze
duplex reads (top and bottom strand combined), which is moreaccurate. For example, duplex reads will compensate for sequencing
artifacts resulting from DNA damage.

Q:	Is there a preferential genomic content for Taq errors?
A: Taq DNA polymerase prefers to make mistakes at A's and T's, so A/Trich templates would produce more errors than G/C rich templates. In
contrast, the high-fidelity polymerases (related to Family B) generally
make more mistakes at G's and C's, so G/C rich templates will be
relatively more error-prone than A/T rich templates (though theoverall mutation rate will be reduced compared to Taq).

Q:	Why is Q5 able to maintain an extremely low error rate whilethermal cycling seems to introduce significant DNA damage?

A:	
Q5 (and archaeal Family B DNA polymerases in general) are unable

to replicate past deoxyuridine (dU) in a template strand. As cytosine
deamination (conversion to dU) was found to be the major mutagenic
DNA damage observed during thermocycling, the polymerase ispreferentially replicating undamaged templates, and this may partly
account for the observed low error rate.

Q:	Is there a way to reduce or avoid primer dimers during

amplification? And what method can be used to remove
primer dimers?

A:	
Some primer sets seem to be more prone to forming dimers thanothers; however it is unclear what causes some primers to be more
susceptible to dimerization. One possible experiment is to try todesign new primer pairs using online primer design or other sequence
analysis tools, and testing several primer sets to see if any produce
less primer dimers. For next-generation sequencing library prep,
adaptor dimers can be removed by using a size selection protocol withSPRISelect® or AMPure® beads after PCR.

Q:	How many recombination event/kb can we expect?
A:	
We measured the rate of recombination to be on average 1 x 10-4 perbase for Taq polymerase, which corresponds to once every 10 kb
replicated. However, as PCR errors get copied in later cycles, the actual
number of recombinants in the final product will be much higher(depending on the number of cycles and replication efficiency of thetarget). There is also evidence in the literature that certain sequence
contexts can also promote recombination, so this rate will likely besequence-dependent.
continued on page 3

How would one analyze errors from the PacBio process?

A:	
To determine the background error rate for our PacBio-based fidelity
assay, we sequenced plasmid DNA (that had been repaired using
PreCR to remove background DNA damage). Based on the typicalsequencing output and the in vivo error rate of plasmid replication,2

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Q:	Is there a preferential genomic content for cross-overs mediatedby Taq polymerase?

A:	
In our study, we identified specific inverted repeat elements (in thelacZ gene) that promote template-switching (but between the top- andbottom- strand), suggesting that template-switching can be inducedby specific sequence contexts. For the recombination assay describedin this webinar (template-switching between different strands), thetemplates were designed to be random sequences and not prone tosecondary structure, and we could not see any obvious sequence bias
for recombination events.

Q:	Is there a way to reduce chimeric events (for long range PCRsin particular)? Is there any way to minimize PCR mediatedrecombination in your samples?

A:	
We want to further study this issue. Reducing the number of cycles isthe easiest way to reduce the number of recombinants in the final PCR
product.

Q:	Was cytosine deamination in any way, shape, or form affectedby methylation or genomic CpG content?

Q:	Do you think repair of the amplified libraries (to correct for

DNA damage arising from thermocycling) should be added tolibrary prep workflows?

A:	
For applications where DNA repair is recommended (low frequency

variant-calling, archived clinical samples, or low input libraries),
repairing genomic DNA prior to library preparation is recommended(rather than repairing after library preparation and PCR). Unrepaired
DNA damage (especially cytosine deamination and guanine oxidation)
will be captured as mutations during PCR, and the resulting
mutations won't be recognized as damaged bases subject to DNA
repair. Regarding a possible second DNA repair step after PCR
and thermocycling, we have not looked at whether DNA damage
from thermocycling affects variant-calling. My guess is that PCR
thermocycling damage will have less of an effect on variant-calling thandamage from shearing, as thermocycling damage will be distributed
among the copies of each sequence, whereas mutagenic damage fromshearing will be replicated in all subsequent copies.

Q:	Would lowering the ramping rate (i.e. 2°C /sec) prevent
amplification bias?

A:	
We haven’t explicitly studied the effect of ramp rate on amplification

A:	
We did not examine the effect of methylation or CpG content on

bias so it’s difficult to answer. We do know that adjusting the extension
temperature can have a significant impact on bias so it’s possible that
adjusting the time spent getting to temperature could also impact
overall bias profiles.

cytosine deamination.

Q:	For a diverse multiplex PCR library, how much of a factor
do differences in priming efficiency affect final biases?

Q:	Would the PCR errors, for example the ones caused by heating

A:	
For multiplex amplification reactions, with multiple primer sets

amplifying multiple targets, differences in priming efficiency has beenshown to introduce bias. Primer pairs that are less effective at priming
may result in that amplicon being artificially underrepresented in the
final product. Amplification bias can also affect the final representationof each target. Amplification biases can be reduced by increasing thetemplate concentration and performing fewer PCR cycles.

Q:	Does the rate of heating and cooling during the PCR reaction
affect DNA damage?

A:	
We did not study DNA damage for different temperature cycling

protocols, however, it is likely that longer denaturation times increase
damage. Slower ramp times may increase the amount of time atelevated temperatures, and may influence the amount of DNA damage.
More likely, the total number of PCR cycles will have a larger effect.

Q:	Do you believe most errors in the PCR experiments comefrom damage to the bases in the template or growing strand
or from damage to the nucleotide pool? Does the fact that
thermal cycling itself causes damage suggest it is damage in thetemplate? Maybe different types of damage in the template vsthe nucleotide pool?

A:	
Thermal cycling can damage dNTP pools as well as DNA templates.

and cooling during thermocycling, affect Sanger sequencing as
it does NGS?

A:	
DNA damage during thermocycling likely does not affect Sanger

sequences as much as next-generation sequencing. If the PCR productis directly sequenced, then the sequencing read will be the consensus
of the entire population, and all of the individual, randomly-distributed
errors (from substitutions or damage) would not appear in thesequencing read. If the PCR product was cloned into a vector andsequenced from bacterial colonies, then the bacterial repair pathways
would correct DNA damage before sequencing.

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In our study, cytosine deamination was the major cause of mutagenic
DNA damage to template DNA. In a separate unpublished study, we
found that cytosine deamination was also the major damage to dNTP
pools.

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