11 - Brian Young, Ph.D.

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Short Tandem Repeat (STR) Typing from
Short Read Sequencing Data: STRTyper
Daniel Bornman, Seth Faith, Jared Schuetter, Aaron Sander, Joe Regensburger, Nancy McMillan, Angela Minard-Smith, Manjula Kasoji,
and Brian Young
Battelle Memorial Institute, Columbus, OH
ABSTRACT
RESULTS
To enable the analysis of STR from next generation
sequencing (NGS) data we modified the approach for
standard reference genome alignment yet preserved the
ability to leverage open-source short read alignment
software. We performed multiplexed sequencing on an
Illumina GAIIx of five individuals, plus an equal parts
mixture on two of the five samples. This sequencing run
generated read lengths of 150 nucleotides that were
aligned to a modified reference genome specifically
constructed to enable analysis of diploid STR polymorphic
patterns. Analysis of the final sequence alignment data
enabled us to correctly estimate (with complete
concordance to CE) STR allele status for the entire set of
core CODIS loci from each sample including the single 1:1
mixture sample. Some exceptions included two instances
where the repeat pattern for the D21S11 locus had repeat
lengths greater than could be covered by the current
maximum 150bp read length. Data are also presented that
demonstrate the use of a novel filtering method for
preprocessing raw sequencing data for enrichment of short
reads containing STR patterns. In addition, we applied this
method to recently generated whole genome sequencing
data from the Illumina HiSeq 2500 platform.
Comparison to Capillary Electrophoresis (CE) Method
For each sample, allele calls were compared to results
obtained by the standard CE method of STR genotyping.
Allele calls were made from alignment data using a simple
heuristic decision model similar to the technique for
determining over-representation of genes mapping to
molecular pathways in gene expression studies. Alleles
were called positive if the calculated probability score was
within a predefined threshold. Using this technique, all core
13 CODIS STR markers were successfully identified with
some exceptions attributed to likely technical artifacts.
Locus
TPOX
D3S1358
Method
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
CE
8
8
16
16
22/23
22/23
11/12
11/12
11/13
11/13
10/11
10/11
13
13
6/9.3
6/9.3
16/17
16/17
11/13
11/13
12/13
12/13
13/17
13/17
30/34.2
*30
X
X
10/12
10/12
14
14
22/25
22/25
12
12
11/12
11/12
10/11
10/11
13/14
13/14
6/9.3
6/9.3
15/19
15/19
8/12
8/12
11/12
11/12
13/17
13/17
28/30
28/30
XY
XY
8
8
17/19
17/19
21
21
10/12
10/12
13
13
10/11
10/11
13/15
13/15
7/9.3
7/9.3
15/16
15/16
11
11
9/11
9/11
14/15
*15
30
30
XY
XY
8/10
8/10
16
16
22/26
22/26
10/12
10/12
11/13
11/13
11
11
13/15
13/15
6/9
6/9
14/18
14/18
11/12
11/12
11/14
11/14
13/15
13/15
28/30.2
28/30.2
XY
XY
8/11
8/11
15/18
15/18
21/25
21/25
10/11
10/11
10/13
10/13
12/13
12/13
13/14
13/14
6/9.3
6/9.3
15
15
11/12
11/12
12/13
12/13
14/17
*17
31.2/32.2
*31.2
XY
XY
NA
8/10
NA
16
NA
22/23/26
NA
10/11/13
NA
11/13
NA
10/11
NA
13/15
NA
6/9/9.3
NA
14/16/17/18
NA
11/12/13
NA
11/12/13/14
NA
13/15/17
NA
28/30/30.2
NA
XXY
NGS
CE
NGS
FGA
CE
NGS
CSF1PO
CE
NGS
D5S818
CE
NGS
D7S820
CE
NGS
D8S1179
CE
NGS
TH01
CE
NGS
TECHNICAL APPROACH
VWA
CE
NGS
D13S317
CE
NGS
Reference Alignment with a Modified Genome
A reference sequence consisting of common CODIS STR
alleles was used for alignment of short read sequences.
This approach allowed for utilization of off-the-shelf opensource reference alignment software with robust capability
for accurately aligning sequencing data.
TPOX_13
TPOX_6
FUTURE DEVELOPMENTS
D16S539
CE
NGS
D18S51
CE
NGS
D21S11
CE
NGS
AMEL
CE
NGS
These results indicate that short read sequencing
technology may be applicable to genotyping CODIS STR
loci. The results showed that the NGS method was
concordant with the CE results for all 13 CODIS plus
AMEL. While further validation is needed to utilize this
technology for routine forensic analysis, several technical
considerations may be critical for widespread use.
Analysis of sequencing data typically requires large
computing resources and may take considerable time to
complete. In addition to the significant decrease in time
and resources required using the reference genome
presented here, we developed a read filtering algorithm
based on signal processing that can detect reads
containing short tandem repeats. This filter reduces even
further the time and computing resources needed to
process sequence data for making STR calls (Figure 3).
Using this prefiltering step, we were able to process an
entire lane of data from a GAIIx in less than 20min using a
single computing core which is comparable to a modern
desktop computer.
The current study used PCR-enrichment of each STR
location to maximize coverage at each locus. We recently
demonstrated the ability to make STR calls directly from
deep sequencing Illumina data from the HiSeq 2500
platform. We are currently developing a method for
applying match probabilities in these cases where STR
coverage may be relatively low.
Table 1: The STR genotype reported for each locus in all 5 samples assayed
including the 1:1 mixture sample (Sample 6). Sample 6was generated using equal
amounts of starting DNA from Sample 1 and Sample 4 prior to sequencing. Near
complete concordance was attained with comparison to CE. (*) Detected
differences between the NGS and CE methods.
(7,8,9,10,11,12)
TPOX
D3S1358
FGA
CSF1PO
A
(7,8,9,10,11,12,13,14)
CSF1PO_6
Figure 3: Computing time of the modified reference alignment approach with and
without read filtering. Read filtering greatly reduced the total runtime for processing
short read sequencing data while retaining the sensitivity of correctly calling alleles.
All stringency setting resulted in reduced time and resources required as compared
to performing reference alignment on all sequence reads.
CSF1PO_15
Figure 1: The common alleles for each STR locus were concatenated into a
reference sequence along with short flanking sequences. This concatenated
reference sequence was used for reference alignment.
B
C
D
1682
Sample 1
Reads mapping to alleles
852
747
2645
631
F
Sample 4
Sample 6
(1:1 mixture)
TPOX_8
TPOX_10
Figure 2: Reference alignment results visualized in IGV for two individuals including
a 1:1 mixture of each sample. The viewer is currently focused on the TPOX
“chromosome”.
E
Figure 4: Circular plot of the reference sequence used for alignment with the
Bowtie short read sequence aligner. Each of the 13 STR loci examined are
arranged around the circular plot as individual “chromosomes” (A). STR
genotyping results obtained from NGS and CE methods for two individual
samples including the mixture sample are plotted against the STR modified
genome. Blue = Sample 1; Red = Sample 4; Black = Sample 6. (B) Individual
alleles represented at each locus are labeled as their defined repeat number. (C)
Coverage data is plotted at each 100bp interval. Coverage data for the mixture
sample is separated from the individual samples for visual comparison. (D) A
heatmap plot is provided adjacent to the coverage plot to indicate the read
alignment signal strength. (E) Data obtained from the CE method is plotted as
small circles above the heatmap for a comparison between methods. Note that
allele calls by CE are not able to distinguish between variant alleles for the
sample repeat number. (F) Data obtained from the Illumina HiSeq 2500 platform
from a single individual sequenced to an average depth of 30X with 150bp reads
was analyzed by the present method. Allele calls made from this data are plotted
in green. The sample sequenced on the HiSeq 2500 was a Yoruban HapMap
sample, NA18507.
This work was performed under internal research funding at Battelle Memorial Institute.
www.battelle.org
[email protected]
Data published in Bornman DM, et al.. BioTechniques Rapid Dispatches. April 2012.
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