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High-resolution three-dimensional chromatin profiling of the Chinese hamster ovary cell genome.
Bevan S, Schoenfelder S, Young RJ, Zhang L, Andrews S, Fraser P, O'Callaghan PM
Chinese hamster ovary (CHO) cell lines are the pillars of a multi-billion dollar biopharmaceutical industry producing recombinant therapeutic proteins. The effects of local chromatin organisation and epigenetic repression within these cell lines result in unpredictable and unstable transgene expression following random integration. Limited knowledge of the CHO genome and its higher-order chromatin organisation has thus far impeded functional genomics approaches required to tackle these issues. Here, we present an integrative three-dimensional (3D) map of genome organisation within the CHOK1SV® 10E9 cell line in conjunction with an improved, less fragmented CHOK1SV® 10E9 genome assembly. Using our high-resolution chromatin conformation datasets, we have assigned ≈ 90% of sequence to a chromosome-scale genome assembly. Our genome-wide 3D map identifies higher-order chromatin structures such as topologically associated domains, incorporates our chromatin accessibility data to enhance the identification of active cis-regulatory elements and importantly links these cis-regulatory elements to target promoters in a 3D promoter interactome. We demonstrate the power of our improved functional annotation by evaluating the 3D landscape of a transgene integration site and two phenotypically different cell lines. Our work opens up further novel genome engineering targets, has the potential to inform vital improvements for industrial biotherapeutic production, and represents a significant advancement for CHO cell line development. This article is protected by copyright. All rights reserved.
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Biotechnology and bioengineering,
1,
1,
23 Oct 2020
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LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications.
Alvarez-Jarreta J, Rodrigues PRS, Fahy E, O'Connor A, Price A, Gaud C, Andrews S, Benton P, Siuzdak G, Hawksworth JI, Valdivia-Garcia M, Allen SM, O'Donnell VB
We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate (FDR) method, utilizing a target-decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder's online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools.
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Bioinformatics (Oxford, England),
1,
1,
07 Oct 2020
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Correction to: DNA methylation changes during preimplantation development reveal interspecies differences and reprogramming events at imprinted genes.
Ivanova E, Canovas S, Garcia-Martínez S, Romar R, Lopes JS, Rizos D, Sanchez-Calabuig MJ, Krueger F, Andrews S, Perez-Sanz F, Kelsey G, Coy P
An amendment to this paper has been published and can be accessed via the original article.
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Clinical epigenetics,
12,
1,
29 Jun 2020
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