RAISING: a high-performance method for identifying random transgene integration sites Article Swipe

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Yusaku Wada , Tomoo Sato , Hiroo Hasegawa , Takahiro Matsudaira , Naganori Nao , Ariella Coler‐Reilly , Tomohiko Tasaka , Shunsuke Yamauchi , Tomohiro Okagawa , Haruka Momose , Michikazu Tanio , Madoka Kuramitsu , Daisuke Sasaki , Naoko Yagishita , Junji Yamauchi , Natsumi Araya , Kenichiro Tanabe , Makoto Yamagishi , Makoto Nakashima , Shingo Nakahata , Hidekatsu Iha , Masao Ogata , Yoshitaka Imaizumi , Kaoru Uchimaru , Yasushi Miyazaki , Satoru Konnai , Katsunori Yanagihara , Kazuhiro Morishita , Toshiki Watanabe , Yoshihisa Yamano , Masumichi Saito ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.21203/rs.3.rs-526444/v1

Both natural viral infections and therapeutic interventions using viral vectors pose significant risks of malignant transformation. Monitoring for clonal expansion of infected cells is important for detecting cancer. Here we developed a novel method of tracking transgene integration sites. RAISING (Rapid Amplification of Integration Sites without Interference by Genomic DNA contamination) is a sensitive, inexpensive alternative to established methods. Its compatibility with Sanger sequencing combined with our CLOVA (Clonality Value) software is critical for those without access to expensive next-generation sequencing. To model our method, we analyzed samples from 698 patients infected with the retrovirus HTLV-1, which causes adult T-cell leukemia/lymphoma (ATL). We defined a clonality value identifying ATL patients with 100% sensitivity and 95.3% specificity, and our preliminary longitudinal analysis suggests this may also be useful for ATL risk assessment. We anticipate future studies will confirm the broad applicability of our technology, especially in the emerging gene therapy sector.

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Raising (metalworking) Transgene Computer science Biology Mathematics Genetics Gene Geometry

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Type: preprint
Language: en
Landing Page: https://doi.org/10.21203/rs.3.rs-526444/v1
PDF: https://www.researchsquare.com/article/rs-526444/v1.pdf?c=1631882530000
OA Status: gold
Cited By: 1
Related Works: 10
OpenAlex ID: https://openalex.org/W3206066079

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OpenAlex ID: https://openalex.org/W3206066079

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DOI: https://doi.org/10.21203/rs.3.rs-526444/v1

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Title: RAISING: a high-performance method for identifying random transgene integration sites

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Type: preprint

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Language: en

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Publication year: 2021

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Publication date: 2021-05-25

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Authors: Yusaku Wada, Tomoo Sato, Hiroo Hasegawa, Takahiro Matsudaira, Naganori Nao, Ariella Coler‐Reilly, Tomohiko Tasaka, Shunsuke Yamauchi, Tomohiro Okagawa, Haruka Momose, Michikazu Tanio, Madoka Kuramitsu, Daisuke Sasaki, Naoko Yagishita, Junji Yamauchi, Natsumi Araya, Kenichiro Tanabe, Makoto Yamagishi, Makoto Nakashima, Shingo Nakahata, Hidekatsu Iha, Masao Ogata, Yoshitaka Imaizumi, Kaoru Uchimaru, Yasushi Miyazaki, Satoru Konnai, Katsunori Yanagihara, Kazuhiro Morishita, Toshiki Watanabe, Yoshihisa Yamano, Masumichi Saito

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Landing page: https://doi.org/10.21203/rs.3.rs-526444/v1

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PDF URL: https://www.researchsquare.com/article/rs-526444/v1.pdf?c=1631882530000

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OA URL: https://www.researchsquare.com/article/rs-526444/v1.pdf?c=1631882530000

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Concepts: Raising (metalworking), Transgene, Computer science, Biology, Mathematics, Genetics, Gene, Geometry

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Cited by: 1

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