Supplementary Appendix:
Supplementary methods online
Supplementary Table 1. Exome run summary
Supplementary Table 2. Clinical characteristics.
Supplementary Methods Online:
Patients and isolation of tumor cells:
Bone marrow samples were obtained from patients with AMGs following informed consent approved by
institutional boards. CD138+ tumor cells from the marrow were isolated by immuno-magnetic bead
selection and used to isolate tumor DNA. Purity of samples was monitored by flow cytometry and
exceeded 80%. All patients were followed every 3 months until progression to clinical MM requiring
therapy. In 4 patients (P1-P4), paired samples were available from baseline at initial registration, and
from the time of progression to clinical MM. As controls, we also utilized baseline samples from 6
patients (NP1-NP6) who did not progress to clinical MM with at least 2 years of follow up. Genomic DNA
was available from all patients.
Whole exome capture and sequencing:
Whole exome capture and sequencing was performed as previously described1,2. Briefly, germline and
tumor DNA were captured on a Roche NimbleGen Sequence Capture V2.0 human exome array (Roche
NimbleGen, Madison, WI) following the manufacturer’s protocol, with protocol modifications at the Yale
Center for Genome Analysis. Captured libraries were sequenced on the Illumina GA II or HiSeq 2000
sequencing system (Illumina, Inc. San Diego, CA). Image analysis and base calling was performed by
Illumina pipeline versions 1.3 and 1.4. The summary sequencing statistics are included in supplementary
data.
Data analysis and validation of mutations:
Analysis of raw data from Illumina sequencing was performed as previously described 1,2. Sequence
reads were mapped to the reference genome (hg18) using the ELAND software (Illumina, San Diego, CA).
Statistics on coverage was collected using in-house perl script. For insertion/deletion detection, the
Burrows-Wheeler Aligner was used to allow gapped alignment to the reference genome3. SAMtools was
used to call germline-originated variants. Differences of minor allele read frequencies from identical
germline-originated variants in tumor and germline were plotted for genome-wide LOH patterns.
Filtering and annotation was done with in-house perl scripts1. Somatic variants were defined as those
present in tumor DNA, but absent in germline as previously described2,4. In short, base coverage
information from matched tumor and germline was utilized to generate Fisher’s exact test P-values for
tumor-specific variants. Normal-specific calls were also produced for null distribution, which was used to
determine the P-value cutoff. Copy number aberration analysis was performed based on coverage ratio
of exome probes in paired tumor and normal samples from sequencing data similar to previously
described4. Selected mutations were verified by PCR amplification followed by Sanger sequencing. Data
from published myeloma genomes was utilized to compare findings in this dataset to those in patients
with clinical myeloma5,6,7.
Cellular frequency estimation and purity estimation:
The cellular frequency of each CNV event is estimated by using the formula adapted from Landau et al.,
2013 8.

f is segmental mean of the allelic frequency of the lesser allele, q1 is the copy number for the lesser
allele, q is total copy number ( e.g. if it is a deletion, q1=0, q=1, if it is gain of one copy, q1=1, q=3). a is
the cellular frequency of the CNV event.
From the above equation, we calculated the cellular frequency for all CNV segments and used the
highest frequency as estimation for sample purity.
References:
1.
Choi, M. et al. Genetic diagnosis by whole exome capture and massively parallel DNA
sequencChoi, M., Scholl, U. I., Ji, W., Liu, T., Tikhonova, I. R., Zumbo, P., Nayir, A., et al. (2009).
Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proceedings
of the National Academy of Sciences of the United States of America 106, 19096–101 (2009).
2.
Choi, M. et al. K+ channel mutations in adrenal aldosterone-producing adenomas and hereditary
hypertension. Science (New York, N.Y.) 331, 768–72 (2011).
3.
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform.
Bioinformatics (Oxford, England) 25, 1754–60 (2009).
4.
Zhao, S. et al. Landscape of somatic single-nucleotide and copy-number mutations in uterine
serous carcinoma. Proceedings of the National Academy of Sciences of the United States of
America 110, 2916–2921 (2013).
5.
Chapman, M. a et al. Suppl-Initial genome sequencing and analysis of multiple myeloma. Nature
471, 467–72 (2011).
6.
Walker, B. a et al. Intraclonal heterogeneity is a critical early event in the development of
myeloma and precedes the development of clinical symptoms. Leukemia
(2013).doi:10.1038/leu.2013.199
7.
Egan, J. B. et al. Whole genome sequencing of multiple myeloma from diagnosis to plasma cell
leukemia reveals genomic initiating events, evolution and clonal tides. Blood
(2012).doi:10.1182/blood-2012-01-405977
8.
Landau, D. a et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia.
Cell 152, 714–26 (2013).
Supplementary Table 1. Exome run summary
Progressive samples
Non-progressive samples
4
6
# of Patients
Sample condition
Germline MGUS/AMM
SE/PE
Read length
MM
Germline
MGUS/AMM
PE
PE
74bp
74bp
# of reads per lane (M)
92.2
84.9
89.8
129.6
253.7
Median coverage (X)
73.8
60.0
64.0
115.2
209.8
% of reads mapped on genome
93.5%
93.5%
93.6%
93.4%
94.0%
% of reads mapped on target
67.0%
66.2%
63.1%
73.3%
69.1%
% of targeted bases covered at least 8x
94.1%
93.5%
93.2%
95.0%
96.4%
Mean error rate
0.5%
0.5%
0.5%
0.7%
0.7%
% of PCR duplicated reads
16.0%
23.5%
17.8%
6.8%
13.0%
Supplementary Table 2. Patient Characteristics
Age
Study ID
(yrs)
Sex
%
M protein M spike
Marrow Diagnosis Progression
Race
(type)
(g/dl)
PC
TTP/Followup
P1
56 Female Black IgA kappa
1.2
19%
AMM
Yes
5 months
P2
58
Male White IgG kappa
2.7
4%
MGUS
Yes
9 months
P3
48
Male White
IgA
lambda
2.4
44%
AMM
Yes
9 months
P4
74
Male White
IgG
lambda
3
23%
AMM
Yes
4 months
NP1
67 Female White
IgG
lambda
1.8
8%
MGUS
No
> 2 yrs
NP2
78
Male Black IgG kappa
0.8
25%
AMM
No
> 2 yrs
NP3
88
Male White IgG kappa
2.4
21%
AMM
No
> 2 yrs
NP4
70
Male White
1.6
5%
MGUS
No
> 2 yrs
NP5
49 Female White IgG kappa
1.4
16%
AMM
No
> 2 yrs
NP6
72
1.4
20%
AMM
No
> 2 yrs
IgG
lambda
Male White IgA kappa