Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer

Zuojian Tang; Jared P. Steranka; Sisi Ma; Mark Grivainis; Nemanja Rodić; Cheng Ran Lisa Huang; Ie Ming Shih; Tian Li Wang; Jef D. Boeke; David Fenyö; Kathleen H. Burns

doi:10.1073/pnas.1619797114

Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer

Zuojian Tang, Jared P. Steranka, Sisi Ma, Mark Grivainis, Nemanja Rodić, Cheng Ran Lisa Huang, Ie Ming Shih, Tian Li Wang, Jef D. Boeke, David Fenyö, Kathleen H. Burns

Research output: Contribution to journal › Article › peer-review

73 Scopus citations

Abstract

Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in highgrade ovarian serous carcinoma.

Original language	English (US)
Pages (from-to)	E733-E740
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	114
Issue number	5
DOIs	https://doi.org/10.1073/pnas.1619797114
State	Published - Jan 31 2017

Bibliographical note

Funding Information:
This work was supported by the Sol Goldman Pancreatic Cancer Research Center and the Health, Empowerment, Research, and Awareness Women's Cancer Foundation (N.R.); a Burroughs Wellcome Fund Career Award for Biomedical Scientists Program (K.H.B.); US NIH Awards R01CA161210 (to J.D.B.), R01CA163705 (to K.H.B.), and R01GM103999 (to K.H.B.); as well as National Institute of General Medical Sciences Center for Systems Biology of Retrotransposition Grant P50GM107632 (to K.H.B. and J.D.B.).

Keywords

Human
LINE-1
Ovarian cancer
Retrotransposon
TIPseq

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1073/pnas.1619797114

Find It

Find It at U of M Libraries

Cite this

Tang, Z., Steranka, J. P., Ma, S., Grivainis, M., Rodić, N., Huang, C. R. L., Shih, I. M., Wang, T. L., Boeke, J. D., Fenyö, D., & Burns, K. H. (2017). Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer. Proceedings of the National Academy of Sciences of the United States of America, 114(5), E733-E740. https://doi.org/10.1073/pnas.1619797114

Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer. / Tang, Zuojian; Steranka, Jared P.; Ma, Sisi et al.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 114, No. 5, 31.01.2017, p. E733-E740.

Research output: Contribution to journal › Article › peer-review

Tang, Z, Steranka, JP, Ma, S, Grivainis, M, Rodić, N, Huang, CRL, Shih, IM, Wang, TL, Boeke, JD, Fenyö, D & Burns, KH 2017, 'Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer', Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no. 5, pp. E733-E740. https://doi.org/10.1073/pnas.1619797114

@article{4b7f0b22f8044591a914c411808b183c,

title = "Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer",

abstract = "Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in highgrade ovarian serous carcinoma.",

keywords = "Human, LINE-1, Ovarian cancer, Retrotransposon, TIPseq",

author = "Zuojian Tang and Steranka, {Jared P.} and Sisi Ma and Mark Grivainis and Nemanja Rodi{\'c} and Huang, {Cheng Ran Lisa} and Shih, {Ie Ming} and Wang, {Tian Li} and Boeke, {Jef D.} and David Feny{\"o} and Burns, {Kathleen H.}",

note = "Funding Information: This work was supported by the Sol Goldman Pancreatic Cancer Research Center and the Health, Empowerment, Research, and Awareness Women's Cancer Foundation (N.R.); a Burroughs Wellcome Fund Career Award for Biomedical Scientists Program (K.H.B.); US NIH Awards R01CA161210 (to J.D.B.), R01CA163705 (to K.H.B.), and R01GM103999 (to K.H.B.); as well as National Institute of General Medical Sciences Center for Systems Biology of Retrotransposition Grant P50GM107632 (to K.H.B. and J.D.B.).",

year = "2017",

month = jan,

day = "31",

doi = "10.1073/pnas.1619797114",

language = "English (US)",

volume = "114",

pages = "E733--E740",

journal = "Proceedings of the National Academy of Sciences of the United States of America",

issn = "0027-8424",

publisher = "National Academy of Sciences",

number = "5",

}

TY - JOUR

T1 - Human transposon insertion profiling

T2 - Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer

AU - Tang, Zuojian

AU - Steranka, Jared P.

AU - Ma, Sisi

AU - Grivainis, Mark

AU - Rodić, Nemanja

AU - Huang, Cheng Ran Lisa

AU - Shih, Ie Ming

AU - Wang, Tian Li

AU - Boeke, Jef D.

AU - Fenyö, David

AU - Burns, Kathleen H.

N1 - Funding Information: This work was supported by the Sol Goldman Pancreatic Cancer Research Center and the Health, Empowerment, Research, and Awareness Women's Cancer Foundation (N.R.); a Burroughs Wellcome Fund Career Award for Biomedical Scientists Program (K.H.B.); US NIH Awards R01CA161210 (to J.D.B.), R01CA163705 (to K.H.B.), and R01GM103999 (to K.H.B.); as well as National Institute of General Medical Sciences Center for Systems Biology of Retrotransposition Grant P50GM107632 (to K.H.B. and J.D.B.).

PY - 2017/1/31

Y1 - 2017/1/31

N2 - Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in highgrade ovarian serous carcinoma.

AB - Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in highgrade ovarian serous carcinoma.

KW - Human

KW - LINE-1

KW - Ovarian cancer

KW - Retrotransposon

KW - TIPseq

UR - http://www.scopus.com/inward/record.url?scp=85011277389&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85011277389&partnerID=8YFLogxK

U2 - 10.1073/pnas.1619797114

DO - 10.1073/pnas.1619797114

M3 - Article

C2 - 28096347

AN - SCOPUS:85011277389

SN - 0027-8424

VL - 114

SP - E733-E740

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

IS - 5

ER -

Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer

Abstract

Bibliographical note

Keywords

UN SDGs

Publisher link

Find It

Other files and links

Fingerprint

Cite this