Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots
Progression of malignancy to overt disease requires multiple genetic hits. Activation-induced deaminase (AID) can drive lymphomagenesis by generating off-target DNA breaks at loci that harbor highly active enhancers and display convergent transcription. The first active transcriptional profiles from...
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doaj-3c703075f0d84e4b921da632d6e73ade2021-05-05T00:29:22ZengeLife Sciences Publications LtdeLife2050-084X2016-07-01510.7554/eLife.13087Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspotsMerja Heinäniemi0https://orcid.org/0000-0001-6190-3439Tapio Vuorenmaa1Susanna Teppo2https://orcid.org/0000-0003-2569-8030Minna U Kaikkonen3Maria Bouvy-Liivrand4Juha Mehtonen5Henri Niskanen6Vasilios Zachariadis7Saara Laukkanen8Thomas Liuksiala9Kaisa Teittinen10Olli Lohi11https://orcid.org/0000-0001-9195-0797School of Medicine, University of Eastern Finland, Kuopio, FinlandSchool of Medicine, University of Eastern Finland, Kuopio, Finland; A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, FinlandSchool of Medicine, University of Tampere, Tampere, FinlandA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, FinlandSchool of Medicine, University of Eastern Finland, Kuopio, FinlandSchool of Medicine, University of Eastern Finland, Kuopio, FinlandA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, FinlandDepartment of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, SwedenSchool of Medicine, University of Tampere, Tampere, FinlandSchool of Medicine, University of Tampere, Tampere, FinlandSchool of Medicine, University of Tampere, Tampere, FinlandSchool of Medicine, University of Tampere, Tampere, Finland; Tampere University Hospital, Tampere, FinlandProgression of malignancy to overt disease requires multiple genetic hits. Activation-induced deaminase (AID) can drive lymphomagenesis by generating off-target DNA breaks at loci that harbor highly active enhancers and display convergent transcription. The first active transcriptional profiles from acute lymphoblastic leukemia (ALL) patients acquired here reveal striking similarity at structural variation (SV) sites. Specific transcriptional features, namely convergent transcription and Pol2 stalling, were detected at breakpoints. The overlap was most prominent at SV with recognition motifs for the recombination activating genes (RAG). We present signal feature analysis to detect vulnerable regions and quantified from human cells how convergent transcription contributes to R-loop generation and RNA polymerase stalling. Wide stalling regions were characterized by high DNAse hypersensitivity and unusually broad H3K4me3 signal. Based on 1382 pre-B-ALL patients, the ETV6-RUNX1 fusion positive patients had over ten-fold elevation in RAG1 while high expression of AID marked pre-B-ALL lacking common cytogenetic changes.https://elifesciences.org/articles/13087genetic instabilityleukemiaGRO-seqtranscriptionsignal feature analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Merja Heinäniemi Tapio Vuorenmaa Susanna Teppo Minna U Kaikkonen Maria Bouvy-Liivrand Juha Mehtonen Henri Niskanen Vasilios Zachariadis Saara Laukkanen Thomas Liuksiala Kaisa Teittinen Olli Lohi |
spellingShingle |
Merja Heinäniemi Tapio Vuorenmaa Susanna Teppo Minna U Kaikkonen Maria Bouvy-Liivrand Juha Mehtonen Henri Niskanen Vasilios Zachariadis Saara Laukkanen Thomas Liuksiala Kaisa Teittinen Olli Lohi Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots eLife genetic instability leukemia GRO-seq transcription signal feature analysis |
author_facet |
Merja Heinäniemi Tapio Vuorenmaa Susanna Teppo Minna U Kaikkonen Maria Bouvy-Liivrand Juha Mehtonen Henri Niskanen Vasilios Zachariadis Saara Laukkanen Thomas Liuksiala Kaisa Teittinen Olli Lohi |
author_sort |
Merja Heinäniemi |
title |
Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
title_short |
Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
title_full |
Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
title_fullStr |
Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
title_full_unstemmed |
Transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
title_sort |
transcription-coupled genetic instability marks acute lymphoblastic leukemia structural variation hotspots |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2016-07-01 |
description |
Progression of malignancy to overt disease requires multiple genetic hits. Activation-induced deaminase (AID) can drive lymphomagenesis by generating off-target DNA breaks at loci that harbor highly active enhancers and display convergent transcription. The first active transcriptional profiles from acute lymphoblastic leukemia (ALL) patients acquired here reveal striking similarity at structural variation (SV) sites. Specific transcriptional features, namely convergent transcription and Pol2 stalling, were detected at breakpoints. The overlap was most prominent at SV with recognition motifs for the recombination activating genes (RAG). We present signal feature analysis to detect vulnerable regions and quantified from human cells how convergent transcription contributes to R-loop generation and RNA polymerase stalling. Wide stalling regions were characterized by high DNAse hypersensitivity and unusually broad H3K4me3 signal. Based on 1382 pre-B-ALL patients, the ETV6-RUNX1 fusion positive patients had over ten-fold elevation in RAG1 while high expression of AID marked pre-B-ALL lacking common cytogenetic changes. |
topic |
genetic instability leukemia GRO-seq transcription signal feature analysis |
url |
https://elifesciences.org/articles/13087 |
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