Optimizing Cancer Genome Sequencing and Analysis

Malachi Griffith; Christopher A. Miller; Obi L. Griffith; Kilannin Krysiak; Zachary L. Skidmore; Avinash Ramu; Jason R. Walker; Ha X. Dang; Lee Trani; David E. Larson; Ryan T. Demeter; Michael C. Wendl; Joshua F. McMichael; Rachel E. Austin; Vincent Magrini; Sean D. McGrath; Amy Ly; Shashikant Kulkarni; Matthew G. Cordes; Catrina C. Fronick; Robert S. Fulton; Christopher A. Maher; Li Ding; Jeffery M. Klco; Elaine R. Mardis; Timothy J. Ley; Richard K. Wilson

doi:10.1016/j.cels.2015.08.015

Optimizing Cancer Genome Sequencing and Analysis

Malachi Griffith, Christopher A. Miller, Obi L. Griffith, Kilannin Krysiak, Zachary L. Skidmore, Avinash Ramu, Jason R. Walker, Ha X. Dang, Lee Trani, David E. Larson, Ryan T. Demeter, Michael C. Wendl, Joshua F. McMichael, Rachel E. Austin, Vincent Magrini, Sean D. McGrath, Amy Ly, Shashikant Kulkarni, Matthew G. Cordes, Catrina C. FronickRobert S. Fulton, Christopher A. Maher, Li Ding, Jeffery M. Klco, Elaine R. Mardis, Timothy J. Ley, Richard K. Wilson

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Abstract

Summary Tumors are typically sequenced to depths of 75x-100x (exome) or 30x-50x (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid, or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ∼312x) whole genome sequencing and exome capture (up to ∼433x) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ∼200,000 putative SNVs by sequencing them to depths of ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and ddPCR assays provided up to ∼250,000x sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP: phs000159).

Original language	English
Article number	35
Pages (from-to)	210-223
Number of pages	14
Journal	Cell Systems
Volume	1
Issue number	3
DOIs	https://doi.org/10.1016/j.cels.2015.08.015
State	Published - Sep 23 2015

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Griffith, M., Miller, C. A., Griffith, O. L., Krysiak, K., Skidmore, Z. L., Ramu, A., Walker, J. R., Dang, H. X., Trani, L., Larson, D. E., Demeter, R. T., Wendl, M. C., McMichael, J. F., Austin, R. E., Magrini, V., McGrath, S. D., Ly, A., Kulkarni, S., Cordes, M. G., ... Wilson, R. K. (2015). Optimizing Cancer Genome Sequencing and Analysis. Cell Systems, 1(3), 210-223. Article 35. https://doi.org/10.1016/j.cels.2015.08.015

@article{ff9a96bdcf1a45c58610183ba4d0f21d,

title = "Optimizing Cancer Genome Sequencing and Analysis",

abstract = "Summary Tumors are typically sequenced to depths of 75x-100x (exome) or 30x-50x (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid, or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ∼312x) whole genome sequencing and exome capture (up to ∼433x) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ∼200,000 putative SNVs by sequencing them to depths of ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and ddPCR assays provided up to ∼250,000x sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP: phs000159).",

author = "Malachi Griffith and Miller, {Christopher A.} and Griffith, {Obi L.} and Kilannin Krysiak and Skidmore, {Zachary L.} and Avinash Ramu and Walker, {Jason R.} and Dang, {Ha X.} and Lee Trani and Larson, {David E.} and Demeter, {Ryan T.} and Wendl, {Michael C.} and McMichael, {Joshua F.} and Austin, {Rachel E.} and Vincent Magrini and McGrath, {Sean D.} and Amy Ly and Shashikant Kulkarni and Cordes, {Matthew G.} and Fronick, {Catrina C.} and Fulton, {Robert S.} and Maher, {Christopher A.} and Li Ding and Klco, {Jeffery M.} and Mardis, {Elaine R.} and Ley, {Timothy J.} and Wilson, {Richard K.}",

note = "Publisher Copyright: {\textcopyright} 2015 Elsevier Inc.",

year = "2015",

month = sep,

day = "23",

doi = "10.1016/j.cels.2015.08.015",

language = "English",

volume = "1",

pages = "210--223",

journal = "Cell Systems",

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Griffith, M , Miller, CA , Griffith, OL , Krysiak, K, Skidmore, ZL, Ramu, A, Walker, JR, Dang, HX, Trani, L, Larson, DE, Demeter, RT, Wendl, MC, McMichael, JF, Austin, RE, Magrini, V, McGrath, SD, Ly, A, Kulkarni, S, Cordes, MG, Fronick, CC, Fulton, RS , Maher, CA , Ding, L, Klco, JM, Mardis, ER, Ley, TJ & Wilson, RK 2015, 'Optimizing Cancer Genome Sequencing and Analysis', Cell Systems, vol. 1, no. 3, 35, pp. 210-223. https://doi.org/10.1016/j.cels.2015.08.015

TY - JOUR

T1 - Optimizing Cancer Genome Sequencing and Analysis

AU - Griffith, Malachi

AU - Miller, Christopher A.

AU - Griffith, Obi L.

AU - Krysiak, Kilannin

AU - Skidmore, Zachary L.

AU - Ramu, Avinash

AU - Walker, Jason R.

AU - Dang, Ha X.

AU - Trani, Lee

AU - Larson, David E.

AU - Demeter, Ryan T.

AU - Wendl, Michael C.

AU - McMichael, Joshua F.

AU - Austin, Rachel E.

AU - Magrini, Vincent

AU - McGrath, Sean D.

AU - Ly, Amy

AU - Kulkarni, Shashikant

AU - Cordes, Matthew G.

AU - Fronick, Catrina C.

AU - Fulton, Robert S.

AU - Maher, Christopher A.

AU - Ding, Li

AU - Klco, Jeffery M.

AU - Mardis, Elaine R.

AU - Ley, Timothy J.

AU - Wilson, Richard K.

PY - 2015/9/23

Y1 - 2015/9/23

N2 - Summary Tumors are typically sequenced to depths of 75x-100x (exome) or 30x-50x (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid, or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ∼312x) whole genome sequencing and exome capture (up to ∼433x) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ∼200,000 putative SNVs by sequencing them to depths of ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and ddPCR assays provided up to ∼250,000x sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP: phs000159).

AB - Summary Tumors are typically sequenced to depths of 75x-100x (exome) or 30x-50x (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid, or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ∼312x) whole genome sequencing and exome capture (up to ∼433x) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ∼200,000 putative SNVs by sequencing them to depths of ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and ddPCR assays provided up to ∼250,000x sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP: phs000159).

UR - http://www.scopus.com/inward/record.url?scp=84942239424&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2015.08.015

DO - 10.1016/j.cels.2015.08.015

M3 - Article

C2 - 26645048

AN - SCOPUS:84942239424

SN - 2405-4712

VL - 1

SP - 210

EP - 223

JO - Cell Systems

JF - Cell Systems

IS - 3

M1 - 35

ER -

Optimizing Cancer Genome Sequencing and Analysis

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