1.
Reduced Bias Small RNA
Library Prep with Gel-Free
or Low-Input Options
HERD TOGETHER.
®

2.
Small RNA sequencing is inherently
saddled with three distinct PROBLEMS!

3.
Substantial bias introduced during ligation steps
Need to gel purify final library
Lack of low-input protocols
PROBLEM #
1
PROBLEM #
2
PROBLEM #
3

4.
PROBLEM #
1
Research shows extensive bias is typically
seen in small RNA sequencing
Baran-Gale, J., Kurtz, L. C., Erdos, Sison, M. C., Young, A., Fannin, E. E., Chines, P. S. and Sethupathy, P. (2015)
Addressing bias in small RNA library preparation for sequencing: a new protocol recovers microRNAs that evade
capture by current methods. Frontiers in Genetics. doi: 10.3389/fgene.2015.00352.

5.
What causes this bias?

6.
Research shows these inconsistencies are
primarily caused by bias introduced during
the ligation step of library prep
Jayaprakash, A. D., Jabado O., Brown, B. D. and Sachidanandam, R. (Sept 2, 2011), Identification and remediation of
biases in the activity of RNA ligases in small-RNA deep sequencing Nuc Acid Res, 1–12. doi:10.1093/nar/gkr693
Zhang, et al. (2013) High-efficiency cloning enables accurate quantification of miRNA expression by deep sequencing.
Genome Biology 14 R109.
Sun, G. (2011) A bias-reducing strategy in profiling small RNAs using Solexa. RNA. 17: 2256-2262
Sorefan, K. et al. (2012) Reducing sequencing bias of small RNAs. Silence. doi:10.1186/1758-907X-3-4

7.
What is the SOLUTION?

8.
Published research shows randomized
adapters reduce ligation bias
Jayaprakash, A. D., Jabado O., Brown, B. D. and Sachidanandam, R. (Sept 2, 2011),
Identification and remediation of biases in the activity of RNA ligases in small-RNA
deep sequencing Nuc Acid Res, 1–12. doi:10.1093/nar/gkr693.

9.
Bioo Scientific makes the only small RNA
sequencing kits for Illumina platforms that
use randomized adapters to reduce ligase bias

10.
The NEXTflex Small RNA-Seq Kit v3
shows more equal coverage of an equimolar
pool of 24 miRNAs (miRNA calibrator),
demonstrating more accurate representation
of the original sample

11.
Figure 1. Sequencing results from small RNA libraries created in triplicate from 1 ng of miRNA
Calibrator, an equimolar mixture of 24 miRNAs. Values farther from 1 indicate more bias.
100
10
1
0.1
0.01
0.001
Observed/Expected
miRNA Calibrator
hsa-miR-92b-5p
hsa-miR-324-3p
dme-miR-6-3p
dme-miR-4-3p
has-miR-134
has-miR-23a-5p
hsa-miR-133a
hsa-miR-127-5p
hsa-miR-24-3p
hsa-let-7e-3p
hsa-miR-195-3p
hsa-miR-92a-3p
hsa-miR-34c-3p
hsa-miR-30c-1-3p
hsa-miR-320a
hsa-miR-218-1-3p
hsa-miR-34a-5p
hsa-miR-106b-5p
hsa-miR-141-3p
hsa-let-7c
hsa-miR-15a-5p
hsa-miR-21-5p
hsa-miR-29b-3p
hsa-miR-190a
CV
NEXTflex = 1.09
Illumina = 2.35
NEB = 2.31
NEXTflex Illumina NEB

12.
The NEXTflex Small RNA-Seq Kit v3
shows more even coverage with the Miltenyi
miRXplore Universal References, an
equimolar mixture of 963 miRNAs

13.
Figure 2. Sequencing results from small RNA libraries created in triplicate from 1 ng of
Miltenyi miRXplore Universal Reference, an equimolar mixture of 963 miRNAs.
1000
900
800
700
600
500
400
300
200
100
0
0
miRNAsdetected
miRNAs detected
Threshold (reads/100K)
NEXTflex Illumina NEB
10 20 30 40 50 60 70 80 90 100
CV
NEXTflex = 1.14
Illumina = 3.78
NEB = 1.67

14.
The use of randomized adapters in the
NEXTflex Small RNA-Seq Kit v3 greatly
improves accuracy of data by reducing
bias in small RNA library prep
CONCLUSION #
1

15.
The NEXTflex Small RNA-Seq Kit v3
allows detection of more miRNAs in
total RNA samples

16.
Figure 3. Small RNA libraries were created in duplicate from human brain total RNA and
sequenced on an Illumina MiSeq. The indicated number of reads was sampled from each library
and the average number of miRNA groups with ≥20 reads determined. The inset shows the
number of reads required to detect 100 miRNA groups at a threshold of ≥20 reads.
Sequencing depth versus miRNAs detected
mirRNAgroupswith≥20reads
Reads sampled
180
160
140
120
100
80
60
40
20
0
0 50000 100000 150000 200000
NEXTflex - 100 ng NEXTflex - 10 ng NEB - 100 ng Illumina - 100 ng

17.
The NEXTflex Small RNA-Seq Kit v3
detects the same number of miRNAs
with fewer reads

18.
Figure 4. 3 - 4.5x fewer reads are necessary to detect 100 miRNAs with
the NEXTflex Small RNA Seq-Kit v3.
Reads necessary to
detect 100 miRNAs
200000
150000
100000
50000
0
NEXTflex - 100 ng NEXTflex - 10 ng NEB - 100 ng Illumina - 100 ng

19.
Reduced bias small RNA library prep
using the NEXTflex Small RNA-Seq Kit
v3 allows detection of more small RNAs
at lower sequencing depth
CONCLUSION #
2

20.
PROBLEM #
2
Small RNA library preparation has historically
required PAGE gel purification due to the
presence of adapter-dimer products

21.
PAGE purification is tedious &
time consuming

22.
PAGE purification limits throughput &
prevents start-to-finish automation

23.
Elimination of adapter-dimer products allows
gel-free purification of small RNA libraries

24.
The NEXTflex Small RNA-Seq Kit v3 uses
a dual approach to substantially reduce
adapter-dimer formation, allowing gel-free
purification of final libraries

25.
Gel-free libraries prepared with the
NEXTflex Small RNA-Seq Kit v3 have
a higher proportion of reads mapping
to miRNAs

26.
Figure 5. Percent of total reads aligned to miRBase in gel-free libraries
created from 100 ng human brain total RNA input.
0
10
20
30
40
50
60
70
Bioo-100 ng Bioo- 10 ng
%miRBasealigned
Overall alignment rate% miRBase alignment
NEXTflex NEB
70
60
50
40
30
20
10
0

27.
Enhanced reduction of adapter-dimer
formation allows gel-free library preparation
CONCLUSION #
3

28.
PROBLEM #
3
Lack of low-input protocols

29.
Substantial reduction of
adapter-dimers also allows low
input library preparation

30.
Libraries can be prepared from
as little as 1 ng total RNA

31.
Low input libraries are achieved
by using up to 25 cycles of PCR

32.
PCR bias adds negligible bias to
small RNA libraries

33.
Correlation of miRNA expression
demonstrates negligible bias added by
additional PCR cycles
PCR Cycles 12 16 20 24 28
12 1 0.9999 0.9994 0.9966 0.9807
16 1 0.9996 0.9970 0.9813
20 1 0.9975 0.9824
24 1 0.9816
28 1
Table 1. Correlation of miRNA abundance in libraries created using serial 10x dilutions
of cDNA and the indicated number of PCR cycles. The Pearson correlation coefficients
calculated from the Log10(reads) values of miRNAs with ≥ 10 reads in all samples are shown

34.
Published data shows that additional
PCR cycles add negligible bias
to small RNA libraries
Jayaprakash, A.D., et al., Identification and remediation of biases in the activity of
RNA ligases in small-RNA deep sequencing. Nucleic Acids Res, 2011. 39(21): p. e141.
Hafner, M., et al., RNA-ligase-dependent biases in miRNA representation in deep-
sequenced small RNA cDNA libraries. RNA, 2011. 17(9): p. 1697-712.

35.
Expression values are reproducible across
different sample inputs
Figure 6. Correlation of miRNA expression between samples created with 100 ng and 10 ng
of human brain total RNA with the NEXTflex Small RNA-Seq kit v3. The Pearson correlation
coefficient is shown.
1
1.5
2
2.5
3
3.5
4
4.5
5
1 1.5 2 2.5 3 3.5 4 4.5 5
Log10(reads)100ng
Log10(reads) 10 ng
100 ng vs 10 ng100 ng vs 10 ngLog10(reads)100ng
Log10(reads) 100 ng
5
4.5
4
3.5
3
2.5
2
1.5
1
1 1.5 2 2.5 3 3.5 4 4.5 5
R = 0.964

36.
Gel purification of low-input small
RNA libraries is still necessary

37.
Enhanced reduction of adapter-dimer
formation allows library preparation
from as little as 1 ng of total RNA
CONCLUSION #
4

38.
The NEXTflex Small RNA-Seq Kit v3 is the
only commercially available kit that includes
randomized adapters to reduce bias and
allows gel-free or low-input library prep

39.
NEXTflex™ Small RNA-Seq Kit v3
(Illumina® Compatible)
• 48 unique barcodes for multiplexing included with 48 reaction kit
• 8 reaction kit includes barcodes that allow low-level multiplexing

40.
Learn more about the NEXTflex™ Small
RNA-Seq Kit v3 to obtain more accurate
results from small RNA sequencing
NEXTflex™
Small RNA-Seq Kit v3
(Illumina Compatible)
Catalog #: 5132-05 (8 reactions)
GEL-FREE & LOW INPUT OPTIONS
©Bioo Scientific Corporation · 2015 V15.11
®
®
nextgen@biooscientific.com THE NGS EXPERTS™
Reduced-Bias Small RNA Library Preparation with Gel-Free or
Low-Input Options
INTRODUCTION
Changes in microRNA (miRNA) expression have been shown to be associated with a variety of normal physiological processes, as
well as diseases including cancer. Studies have already shown that miRNAs may provide useful markers for the development of disease
-
Bias is introduced into small RNA libraries during the ligation steps. Small RNA library preparation involves ligating adapters directly
onto the 3’ and 5’ ends of the RNA molecule in two separate steps, and each of these ligation steps has been shown to introduce severe
bias into library preparation. Recent studies have shown that inserting random bases at the ends of the adapters greatly reduces bias in
comparison to using non-randomized adapters [1-4].
-
ration. In typical DNA or RNA library prep, insert-containing molecules are at least 100 bp larger than adapter-dimer molecules, and
thus can be removed using SPRI magnetic beads. However, since insert-containing molecules are only ~20 bp larger than adapter-dimer
size selection greatly limits both throughput and automation potential of small RNA library preparation, as only a limited number of
libraries can be run on a single gel and it is a labor-intensive process that is not amenable to automation.
unique in that additional PCR cycles result in negligible bias; thus it should theoretically be possible to create low-input small RNA
products and leading to sequencing data where very few of the reads are useful. A number of methods have been developed to reduce
such an extent that gel-free or low-input small RNA library preparation is possible.
method that utilizes randomized adapters for greatly reduced bias and features gel-free or low-input protocols, which are possible due
.
®
DOWNLOAD MANUAL PURCHASE KIT DOWNLOAD WHITEPAPER

41.
If you have any questions email us at
nextgen@biooscientific.com
or visit our website at
BiooScientific.com/smallRNA