Literature DB >> 32199980

Library preparation for next generation sequencing: A review of automation strategies.

J F Hess1, T A Kohl2, M Kotrová3, K Rönsch4, T Paprotka4, V Mohr5, T Hutzenlaub6, M Brüggemann3, R Zengerle6, S Niemann2, N Paust7.   

Abstract

Next generation sequencing is in the process of evolving from a technology used for research purposes to one which is applied in clinical diagnostics. Recently introduced high throughput and benchtop instruments offer fully automated sequencing runs at a lower cost per base and faster assay times. In turn, the complex and cumbersome library preparation, starting with isolated nucleic acids and resulting in amplified and barcoded DNA with sequencing adapters, has been identified as a significant bottleneck. Library preparation protocols usually consist of a multistep process and require costly reagents and substantial hands-on-time. Considerable emphasis will need to be placed on standardisation to ensure robustness and reproducibility. This review presents an overview of the current state of automation of library preparation for next generation sequencing. Major challenges associated with library preparation are outlined and different automation strategies are classified according to their functional principle. Pipetting workstations allow high-throughput processing yet offer limited flexibility, whereas microfluidic solutions offer great potential due to miniaturisation and decreased investment costs. For the emerging field of single cell transcriptomics for example, microfluidics enable singularisation of tens of thousands of cells in nanolitre droplets and barcoding of the RNA to assign each nucleic acid sequence to its cell of origin. Finally, two applications, the characterisation of bacterial pathogens and the sequencing within human immunogenetics, are outlined and benefits of automation are discussed.
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Year:  2020        PMID: 32199980     DOI: 10.1016/j.biotechadv.2020.107537

Source DB:  PubMed          Journal:  Biotechnol Adv        ISSN: 0734-9750            Impact factor:   14.227


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