iMate Protocol Guide version 1.2

iMate Protocol (version 1.2) by GRAS – May 18, 2015
NGS and Phyloinfo in Kobe
http://www.clst.riken.jp/phylo/
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iMate Protocol: Improved and Inexpensive NexteraTM
Mate Pair Library Preparation
Authorized by Kaori Tatsumi, Osamu Nishimura, Kazu Itomi, Chiharu Tanegashima & Shigehiro Kuraku
Genome Resource & Analysis Station (GRAS)
operated by Phyloinformatics Unit
RIKEN Center for Life Science Technologies (CLST)
Notice: A benchmark paper introducing this protocol has been accepted for publication in the journal
Biotechniques. When you present or publish data based on technical guidance in this protocol, you could think
about citing this protocol at our web site and the benchmark paper (Tatsumi et al., 2015) published in
Biotechniques.
This protocol outlines the modifications to the ‘Gel-plus’ version of the standard protocol for
Nextera Mate Pair Library Preparation and the logical background for them. Desiring optimal
scaffolding performance, we have optimized the protocol under the possibly conservative policy
that only read pairs with junction adaptors (bona fide ‘mates’) should be passed on to scaffolding.
The keys for this protocol are optimizing the 1) tagmentation condition, 2) Covaris shearing
condition, and 3) sequence read length, in order to enhance the yield of libraries and the
capability of detecting the junction adaptor in reads.
Basically, we understand that 4μg of starting genomic DNA, as formulated in the standard
protocol, is enough for preparation of mate-pair libraries with mate distance of >10kb. Ideally, we
could optimize the tagmentation condition so that as much DNA as possible fall into the targeted
size range. For this purpose, perform tagment reaction with multiple conditions, for example, in
three tubes with 4, 8 and 12 μl of tagment enzyme supplied in the kit. The tagment buffer can be
self-made [1], which leads to cost-saving, if other limiting reagents are also saved.
Size distribution of tagmented DNA molecules should be analyzed with a trustworthy method,
such as pulse field electrophoresis (e.g., PippinPulse) or the Agilent TapeStation―the Agilent
Bioanalyzer does not perform well for this purpose. With comparable results from multiple
tagment reactions, you could figure out which tagment condition allows you to retrieve the largest
amount of DNA for the targeted size range.
Like the previous tagmentation step, the amounts of the supplied reagents used in this step are
the limiting factor in terms of how many libraries can be prepared with one purchased kit. Thus, it
would be preferable to find a way to decrease the amount of kit-supplied reagents required to
perform this step. Our solution is to perform strand displacement after size selection with
BluePippin. Using size-selected DNA as substrate, we usually perform strand displacement with
1/4 volume for all reaction components.
Do as instructed in the standard protocol.
We use a BluePippin in this step and usually set a size range of 4 kb in width (for example, from 6
kb to 10 kb) although this is a matter of further consideration. As mentioned above in the
step, performing this step before strand displacement reduces the
amount of DNA to be processed for strand displacement, resulting in saving enzyme and buffer
for strand displacement. We recommend quantifying the amount of DNA after size selection.

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After strand displacement and size selection (whether you perform these steps in this order or the
other way round), it is ideal to retain at least 100 ng of DNA. Although the standard protocol
mentions ‘150-400 ng’ (on page 27), 100-200ng is realistic and still promising, in our experience.
Shearing determines the length of library inserts, which should be coordinated with read length in
sequencing. A shearing condition we propose is the one which will ultimately result in the library
size distribution of 300 – 700 bp with the peak at 450-500bp in the step far
below. Note that this is markedly different from the size distribution illustrated in the standard
protocol (300-1200bp; on page 49). To achieve the size distribution proposed above, we
recommend performing successive shearing with multiple executions of the Covaris condition
instructed in the standard protocol. In our experience, shearing the genomes of different species
with the same condition can result in markedly different fragment size distributions. Thus, you
need to optimize the condition specifically for your species of interest. For one of the species we
worked on, we performed as many as 7 runs of Covaris shearing with the condition instructed in
the standard protocol.
You may feel an urge to perform QC with Bioanalyzer immediately after the Covaris shearing, but
it will not give you a fair assessment of shearing results because you do not want to use a large
amount of sheared DNA for QC. Thus, we recommend to save as much DNA as possible at this
stage and to measure the size distribution later in the step ‘ ’.
To get as many unique mate-pair reads as possible, it is strongly recommended to reduce PCR
cycles and avoid excessive amplification. We suggest performing no more than 10 cycles of PCR.
This warning is supported by our experience of getting enough amount of products with 10 PCR
cycles, even for samples that are supposed to require 15 cycles according to the standard
protocol (for example, 100ng for libraries with mate distant range of 6-10kb). In fact, we normally
perform 8 PCR cycles, and only when we find the yield too low after AMPure clean-up do we
perform additional PCR cycling (still, no more than 10 cycles in total). If you do not get enough
products within 10 cycles, you had better first optimize the tagment condition to increase the yield
for the targeted size range.
To have a clearer idea of how many PCR cycles are needed beforehand, you might want to use a
kit such as KAPA Real-Time Library Amplification Kit (KK2701). However, one crucial concern is
that beads attached to library DNA can interfere with the detection of SYBR Green in qPCR.
With the illumina system, it seems that the insert lengths of many reads actually sequenced are
shorter than the most frequent insert length of a library. Thus, be sure to perform greedy size
selection with AMPure to get rid of molecules with short inserts, as instructed in the standard
protocol (x0.67 AMPure to get rid of <300bp molecules), no matter what the size distribution of
library inserts is. Modest size selection can result in high proportion of read pairs with too small
lengths, and they may not suffice for effective scaffolding.

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Use Bioanalyzer or equivalent in this final QC before sequencing. Keep in mind that the size
distribution is determined mostly by shearing condition and AMPure clean-up, rather than the
choice of size range of mate distance.
We use KAPA Library Quantification Kit (KK4835) in this step. Quantification should not be tricky
if the library has an ordinary unimodal size distribution. The standard protocol says that you need
1.5nM-20nM of the synthesized library, but we think that 2nM is enough unless the sequencing
facility you are working with requests much more than required in an actual sequencing run.
In your first trial, it is advised to run a MiSeq for small-scale pilot sequencing to get 300bp-long
paired-end reads from prepared libraries―sequencing as many as 10 libraries per MiSeq run
should allow you fair validation of libraries. Obtained 300bp-long paired-end reads could also be
used for simulating which read length yields the highest proportion of reads with junction adaptor,
by chopping them at 100bp, 127bp and 171bp for example (if sequencing with HiSeq is planned
next).
The lengths of 127bp and 171bp may sound unusual, but with Rapid Run on HiSeq, one can
obtain reads of these lengths by making the best use of extra cycles inherently assigned for
Nextera dual indexing which we do not need in mate-pair sequencing. This trick allows you to get
127bp and 171bp, using three and four of the TruSeq Rapid SBS Kit for 50 cycles, respectively
(see page 6 of the official manual for TruSeq Rapid SBS Kit). Please consult with the sequencing
facility that you plan to work with, about the possibility of this extra-cycle sequencing.
In our experience, Rapid Run mode with v1 chemistry on older HCS (HiSeq Control Software)
seems to be vulnerable to suboptimal library pooling, such as the ‘low plex pooling’ issue (see
this document by illumina). In the course of your mate pair sequencing, you may encounter a
situation in which you have only 4 or fewer libraries to be sequenced in a Rapid Run. In this case
there is a high chance that base composition in index reads will be too homogeneous, and you
will get lower QV in index reads, resulting in a larger proportion of reads that failed in
demultiplexing. To reduce this unfavorable effect, you could introduce multiple indices per library
in the step above . As long as demultiplexing between libraries works out
without any overlap of indices, this strategy is supposed to produce as many valid reads as
possible, only with the cost of handling more data files in post-sequencing informatics steps. The
latest versions of HCS (version 2.2.38 or higher) seems to be robust against low diversity
samples, so you are suggested to contact the sequencing facility you are working with in advance
to make sure if you need to be concerned with the low plex pooling issue.
We recommend to first run on raw fastq files a recent version of FastQC (v0.11 or higher) to
monitor some standard metrics, including the frequency of junction adaptor appearance along
base positions (in the ‘Adapter Content’ view newly added in v0.11).
After the primary QC, run the program NextClip [2] and assess PCR duplicate rate and what
proportion of reads has the junction adaptors. After the NextClip run, be sure to rerun FastQC on
processed fastq files of Category A, B and C, separately, in order to confirm that junction/external
adaptors and low-quality bases were properly trimmed.
1. Wang Q, Gu L, Adey A, Radlwimmer B, Wang W, Hovestadt V, Bahr M, Wolf S, Shendure J, Eils R et al:
Tagmentation-based whole-genome bisulfite sequencing. Nature protocols 2013, 8(10):2022-2032.
2. Leggett RM, Clavijo BJ, Clissold L, Clark MD, Caccamo M: NextClip: an analysis and read preparation tool
for Nextera Long Mate Pair libraries. Bioinformatics 2014, 30(4):566-568.

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