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Sequencing Strategies for Fusion Gene Detection
Author(s) -
Heyer Erin E.,
Blackburn James
Publication year - 2020
Publication title -
bioessays
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.175
H-Index - 184
eISSN - 1521-1878
pISSN - 0265-9247
DOI - 10.1002/bies.202000016
Subject(s) - fusion gene , context (archaeology) , computational biology , dna sequencing , computer science , fusion , sensor fusion , gene , biology , artificial intelligence , genetics , paleontology , linguistics , philosophy
Fusion genes formed by chromosomal rearrangements are common drivers of cancer. Recent innovations in the field of next‐generation sequencing (NGS) have seen a dynamic shift from traditional fusion detection approaches, such as visual characterization by fluorescence, to more precise multiplexed methods. There are many different NGS‐based approaches to fusion gene detection and deciding on the most appropriate method can be difficult. Beyond the experimental approach, consideration needs to be given to factors such as the ease of implementation, processing time, associated costs, and the level of expertise required for data analysis. Here, the different NGS‐based methods for fusion gene detection, the basic principles underlying the techniques, and the benefits and limitations of each approach are reviewed. This article concludes with a discussion of how NGS will impact fusion gene detection in a clinical context and from where the next innovations are evolving.