Jim R Hughes

Jim R Hughes


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 July 2016 in Nature Genetics
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DHDeborah Hay
Deborah Hay
JHJim R Hughes
Jim R Hughes
CBChristian Babbs
Christian Babbs
JDJames O J Davies
James O J Davies
BGBryony J Graham
Bryony J Graham
DHDouglas R Higgs
Douglas R Higgs

23 November 2015 in Nature Methods
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Journal Article
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JDJames O J Davies
James O J Davies
JTJelena M Telenius
Jelena M Telenius
SMSimon J McGowan
Simon J McGowan
NRNigel A Roberts
Nigel A Roberts
STStephen Taylor
Stephen Taylor
JHJim R Hughes
Jim R Hughes
Pooling barcoded 3C libraries and simultaneously capturing interactions at many loci of interest generates reproducible cis- and trans-interaction maps at high resolution from low amounts of input material. This allows for the comparison of interactions in different cell types using common software designed for differential analysis of sequence count data, rather than requiring software specifically designed for 3C experiments. Methods for analyzing chromosome conformation in mammalian cells are either low resolution or low throughput and are technically challenging. In next-generation (NG) Capture-C, we have redesigned the Capture-C method to achieve unprecedented levels of sensitivity and reproducibility. NG Capture-C can be used to analyze many genetic loci and samples simultaneously. High-resolution data can be produced with as few as 100,000 cells, and single-nucleotide polymorphisms can be used to generate allele-specific tracks. The method is straightforward to perform and should greatly facilitate the investigation of many questions related to gene regulation as well as the functional dissection of traits examined in genome-wide association studies.

24 July 2017 in Nature Cell Biology
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LHLars L. P. Hanssen
Lars L. P. Hanssen
MKMira T. Kassouf
Mira T. Kassouf
AOA. Marieke Oudelaar
A. Marieke Oudelaar
DBDaniel Biggs
Daniel Biggs
CPChris Preece
Chris Preece
DHDouglas R. Higgs
Douglas R. Higgs
The genome is organized via CTCF–cohesin-binding sites, which partition chromosomes into 1–5 megabase (Mb) topologically associated domains (TADs), and further into smaller sub-domains (sub-TADs). Here we examined in vivo an ∼80 kb sub-TAD, containing the mouse α-globin gene cluster, lying within a ∼1 Mb TAD. We find that the sub-TAD is flanked by predominantly convergent CTCF–cohesin sites that are ubiquitously bound by CTCF but only interact during erythropoiesis, defining a self-interacting erythroid compartment. Whereas the α-globin regulatory elements normally act solely on promoters downstream of the enhancers, removal of a conserved upstream CTCF–cohesin boundary extends the sub-TAD to adjacent upstream CTCF–cohesin-binding sites. The α-globin enhancers now interact with the flanking chromatin, upregulating expression of genes within this extended sub-TAD. Rather than acting solely as a barrier to chromatin modification, CTCF–cohesin boundaries in this sub-TAD delimit the region of chromatin to which enhancers have access and within which they interact with receptive promoters.

12 October 2020 in Nature Methods
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RSRon Schwessinger
Ron Schwessinger
MGMatthew Gosden
Matthew Gosden
DDDamien Downes
Damien Downes
RBRichard C. Brown
Richard C. Brown
AOA. Marieke Oudelaar
A. Marieke Oudelaar
JHJim R Hughes
Jim R Hughes

29 October 2018 in Nature Genetics
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Journal Article
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AOA. Marieke Oudelaar
A. Marieke Oudelaar
JDJames O. J. Davies
James O. J. Davies
LHLars L. P. Hanssen
Lars L. P. Hanssen
JTJelena M. Telenius
Jelena M. Telenius
RSRon Schwessinger
Ron Schwessinger
JHJim R Hughes
Jim R Hughes

9 June 2021 in Nature
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Journal Article
Closed access
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PHPeng Hua
Peng Hua
MBMohsin Badat
Mohsin Badat
LHLars L. P. Hanssen
Lars L. P. Hanssen
LHLance D. Hentges
Lance D. Hentges
NCNicholas Crump
Nicholas Crump
JDJames O. J. Davies
James O. J. Davies