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Caroline Dean

Researcher at John Innes Centre

Publications -  239
Citations -  34351

Caroline Dean is an academic researcher from John Innes Centre. The author has contributed to research in topics: Arabidopsis & Flowering Locus C. The author has an hindex of 90, co-authored 223 publications receiving 31556 citations. Previous affiliations of Caroline Dean include University of California, San Diego & DuPont Pioneer.

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Mutually exclusive sense–antisense transcription at FLC facilitates environmentally induced gene repression

TL;DR: It is demonstrated that while sense and antisense transcripts can co-occur in the same cell they are mutually exclusive at individual loci and through the mutually exclusive relationship facilitates shutdown of sense FLC transcription in cis.
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Identification of a mobile endogenous transposon in Arabidopsis thaliana

TL;DR: Tag1 provides a tool for the insertional mutagenesis of plant genes essential for biological processes of agronomic importance.
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QTL analysis of flowering time in Arabidopsis thaliana

TL;DR: Quantitative trait loci analyses based on restriction fragment length polymorphism maps have been used to resolve the genetic control of flowering time in a cross between two Arabidopsis thaliana ecotypes H51 and Landsbergerecta, differing widely in flowering time.
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Slow Chromatin Dynamics Allow Polycomb Target Genes to Filter Fluctuations in Transcription Factor Activity.

TL;DR: It is observed that when chromatin modification dynamics are slow, transient pulses of transcriptional activation or repression are effectively filtered, such that epigenetic memory is retained, and noise filtering thus depends on slow chromatin dynamics and may represent an important function of PRC2-based regulation.
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Protocol: A simple phenol-based method for 96-well extraction of high quality RNA from Arabidopsis.

TL;DR: The development of the HTP96 protocol has vastly increased the sample throughput, allowing us to fully exploit the large sample capacity of modern real time qRT-PCR thermocyclers, and develop an effective high-throughput gene expression platform.