Arabidopsis Research Roundup: December 9th.

This December 9th Arabidopsis Research Roundup includes four rather different studies. Firstly we include an excellent audio description from David Salt about a new type of GWAS analysis that his lab was involved in developing. This allowed identification of new genetic loci involved in molybdenum signalling. Secondly Isabelle Carre’s group from Warwick presents a study into the interactions that define the functioning of the circadian clock. Thirdly Mike Blatt leads a study that models stomatal opening and finally we include an investigation of the DOG1 gene, that includes a contribution from Fuquan Liu.

Forsberg SK, Andreatta ME, Huang XY, Danku J, Salt DE, Carlborg Ö (2015) The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance PLoS Genet. e1005648. Open Access.

Current GARNet Chairman David Salt (Aberdeen) is the UK lead on this collaboration with the lab of Orjan Carlborg from Uppsala in Sweden. The novelty of this paper is in the development of a new technique to measure Genome-Wide Association using the variance in SNP differences instead of using the mean. Professor Salt explained this vGWA technique in the attached audio-file, which is especially useful for people not so familiar with GWAS. Using this vGWA technique the authors were able to re-analyse an old dataset to gain additional understanding of how certain genetic loci are regulated to explain differences in the production of the essential nutrient molybdenum. Overall this paper introduces an analysis technique that can hopefully be used by other members of the community to analyse/re-analyse their data with increased rigour.

This is the 10minute audio file where David explains the paper:

Adams S, Manfield I, Stockley P, Carré IA (2015) Revised Morning Loops of the Arabidopsis Circadian Clock Based on Analyses of Direct Regulatory Interactions. PLoS One.10(12):e0143943. 10.1371/journal.pone.0143943 Open Access

This collaboration between the Universities of Warwick and Leeds is led by Isabelle Carré and investigates the Arabidopsis circadian clock. They analysed the in vivo interactions of the LATE ELONGATED HYPOCOTYL (LHY) protein with promotors of other clock components. This uncovered a novel regulatory loop between LHY and the CIRCADIAN CLOCK ASSOCIATED-1 (CCA1) gene. Furthermore they show LHY acts as a repressor of all other clock components, clearly placing this protein as a key regulatory component of the Arabidopsis clock.

Minguet-Parramona C, Wang Y, Hills A, Vialet-Chabrand S, Griffiths H, Rogers S, Lawson T, Lew V, Blatt MR (2015) An optimal frequency in Ca2+ oscillations for stomatal closure is an emergent property of ion transport in guard cells. Plant Physiol. Open Access

Mike Blatt is the corresponding author for this collaboration between Glasgow, Cambridge and Essex Universities. There are a good number of UK researchers who investigate the factors that regulate stomatal opening and this study looks at the role of calcium oscillations in this process. They have used the Arabidopsis OnGuard model that faithfully reproduces the optimum 10minute period of Ca2+ oscillation in guard cells. They used experimentally derived kinetics to describe the activity of ion transporters in the plasma membrane and tonoplast. Overall they discovered that the calcium oscillations are actually a by-product of the ion transport that determines stomatal aperature and not the overall controlling factor.

Cyrek M, Fedak H, Ciesielski A, Guo Y, Śliwa A, Brzeźniak L, Krzyczmonik K, Pietras Z, Liu F, Kaczanowski S, Swiezewski S (2015) Seed dormancy in Arabidopsis thaliana is controlled by alternative polyadenylation of DOG1 Plant Physiol.

Fuquan Liu (Queens, Belfast) is the UK contributor to this Polish-led study focused on the DOG1 gene, which is a key regulator of Arabidopsis seed dormancy. Previously it had been shown that the C-terminus of DOG1 is not conserved in many other plant species. The DOG1 transcript is alternatively polyadenylated and the authors show that Arabidopsis mutants that lack current 3’ RNA processing also show defects in seed dormancy. The shorter version of DOG1 is able to rescue the dog1 phenotype, which allows the authors to propose that DOG1 is a key regulator of seed dormancy and that the phenotypes of RNA processing mutants are linked to the incorrect processing of this specific mRNA species.

Arabidopsis Information Portal at PAGXXIII

Last Monday the Arabidopsis community gathered for the Arabidopsis Information Portal workshop at PAG XXIII. The Arabidopsis Informatics Portal (AIP) was funded by NSF and BBSRC to move beyond the Arabidopsis genome resource provided by TAIR toward linking the genome to the epigenome, proteome, transcriptome and interactome.

AraportThe first talk was a short update from Eva Huala, formerly of TAIR and now of Phoenix Bioinformatics, the nonprofit company she started in order to keep TAIR going. Huala explained that after TAIR’s NSF funding ended, the pay-to-access model was chosen over the alternative pay-to-submit (open access) approach. This means TAIR is focussed on ensuring the subscribers get the best possible value for money by providing the best possible database curation, manual annotation and user experience. Most TAIR subscription fees are paid by libraries, as if it was a journal, but researchers from institutions whose libraries do not pay the fee will be able to access TAIR’s manual annotation after a year’s embargo.

Next, Sean May (NASC, University of Nottingham) explained that NASC is a module of AIP and is currently integrating with the ABRC. He is consulting the community about the development of NASC, so make sure you have your say in the NASC Strategy Survey:

Chia-yi Cheng (JCVI) gave an overview of Araport, the online home of the AIP. Araport federates diverse datasets from other places, for example TAIR, UniProt and BAR, and maintains the Col-0 ‘gold standard’ annotation. It uses JBrowse as the default genome browser and hosts datasets including the CoGe epigenomics resource, which I blogged about last week. (more…)


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Published on: January 11, 2015

Happy New Year! We at GARNet enjoyed a long Christmas break and some of us have returned to work via California! Ruth, Jim and I are in San Diego this week for the Plant and Animal Genome Conference (PAG).

PAG is an enormous conference – take a look at the Twitter stream (PAGXXIII) for an idea of how many sessions run at any one time. Yesterday I went to sessions on Ontologies, Brassica and Tritaceae, and I thought I’d quickly update our blog readers about a workshop about the CoGe online tool. I mentioned CoGe in this post about the EPIC conference and it’s also featured in the June 2013 edition of GARNish.

Eric Lyons, one of the creators of CoGe, began the session by explaining that CoGe is a platform for managing, visualising, analysing and comparing genomes. It can deal with unlimited numbers of genomes of unlimited size—though there is a limit for the number of annotations per genome—and while there are tools set up for ease of use, users can perform custom, on-the-fly analysis too.

Throughout the session, Lyons was clear that CoGe is ‘Powered by iPlant.’ It uses iPlant middleware to enable data storage, universal log-in and much more functionality that the user might not be aware of but which makes their experience smooth and relatively stress-free. (more…)

Natural variation in Arabidopsis, the MAGIC way

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Published on: November 24, 2014

The research: Finding the causes of variation in seed size and number

In the Arabidopsis Research Round-up a few weeks ago, Lisa highlighted a paper from a team at the University of Bath about natural variation in Arabidopsis seeds. Lead author Paula Kover and her team investigated the genetic basis of variation in seed size and number.

All plants negotiate a trade-off between the number and size of their seeds, so it was a surprise to learn that of 9 QTL for seed number and 8 for seed size, there was only 1 overlapping QTL. The strong negative correlation seen in size and number is logically due to resource use efficiency, but these data suggest that this is not determined genetically.

There is enough of a positive correlation between seed number and fruit length that fruit length is sometimes used to estimate seed number – though the correlation is not strong. Here too there was only 1 QTL overlapping between the two traits, suggesting that any correlation is not inherent and may vary according to environmental or internal factors.

Based on QTL analysis, Kover et al. identify five potential genes that underlie quantitative variation in seed size and number: AAP1 (AT1G58360) and KLUH (AT1G13710) on chromosome 1; and JAGGED LATERAL ORGANS (AT4G00220), YABBY 3 (AT4G00180), and BEL1 (AT5G41410) on chromosomes 4 and 5.


The tool: MAGIC Arabidopsis lines

All the above work was carried out using Mulitparent Advanced Generation Inter-Cross (MAGIC) Arabidopsis lines. Kover and others developed these lines to improve methods of identifying natural allelic variation that underlies variable phenotypic traits. The lines are recombinant, inbred over 6 generations, that originate from an intermated hereogenous stock. This pedigree means they represent a large diversity of genes in mostly homozygous lines; ideal for accurate QTL mapping. The original MAGIC paper from 2009 paper states ‘MAGIC lines occupy an intermediate niche between naturally occurring accessions and existing synthetic populations.’

The MAGIC lines are an incredible open resource for studying natural variation in Arabidopsis: they enable a researcher to map a trait to within 300kb. All lines in the 2009 paper are available from NASC. A set of digital tools, hosted at the Wellcome Trust Centre for Human Genetics, contains the (open source) software needed to run the QTL analysis and the data files associated with the lines.


Highlighted paper: Gnan, Priest and Kover. The genetic basis of natural variation in seed size and seed number and their trade-off using Arabidopsis thaliana MAGIC lines. Genetics, 2014. 10.1534/genetics.114.170746

Also cited: Kover et al. A multiparent advanced generation inter-cross to fine-map quantitative traits in Arabidopsis thaliana. PLOS Genetics, 2009. DOI: 10.1371/journal.pgen.1000551

For a comparison of resources for studying natural variation, see Weigel, Plant Phys, 2012 158:2-22

Adjusting the Circadian Clock

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Published on: June 3, 2014

As highlighted in Lisa’s excellent weekly Arabidopsis Research Round-up two weeks ago, a paper on the feedback loop mechanisms that give the circadian clock flexibility was recently published in New Phytologist Early View (DOI: 10.1111/nph.12853Open Access) by GARNet 2014 speaker Andrew Millar. Here first author Laura Dixon, post-doctoral researcher in flowering regulation in the Department of Crop Genetics at the John Innes Centre, explains the research.

Dixon May2014
Arabidopsis thaliana (left) and single celled green alga Ostreococcus tauri

The circadian clock is an innate time-keeping mechanism found in most organisms, and has a period of about 24 hours. The circadian rhythm syncs to the environment as the clock mechanism adjusts to long or short photoperiods, or environmental summer and winter, and so co-ordinates many biological processes with respect to time of day and season. How quickly these adjustments can occur varies between species, and is believed to be a property of how many interlocking feedback loops the circadian clock mechanism is comprised of.

To empirically test the idea that clock flexibility is linked to the number of interlocking feedback loops within the circadian clock mechanism, we compared the fairly complex Arabidopsis thaliana clock to the very reduced clock of the smallest free-living eukaryote, unicellular green alga Ostreococcus tauri. We use A. thaliana as a plant model as it is a simple system relative to often very complex crop species. Many crop species are polyploid and so have very complicated signalling pathways; Arabidopsis is simpler but still contains complex regulation which can inform crop research. The Arabidopsis clock is a network of interlocking feedback loops. Groups of gene families encode clock components and at least 10 photoreceptor proteins.

We switched photoperiod conditions directly between short day and long day and observed what happened in the two systems. In combination with network analysis through mathematical modelling of the proposed possible clock structures, we showed that flexibility of entrainment to environmental conditions is a property of both the number of interlocking loops and the number of light inputs to the clock mechanism. Our research highlights one of the mechanisms through which circadian clock transcriptional and translational loops are flexible and adaptable in response to environmental conditions.

Images: A. thaliana from GARNet; TEM of Ostreococcus from Eikrem and Throndsen University of Oslo

GEO for plant scientists: Sharing data

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Published on: February 13, 2014

There is currently no microarray service provider in the UK that uploads your plant science microarray data to GEO on your behalf, but publication requires your data to be shared. The most common request from journals is that it is shared on GEO.

GEO has this information page about data submission. While the high-throughput sequence submission guidelines are a still little complicated, microarray experiments have well-established (and enforced!) minimum information requirements and the four main microarray chip providers have customized information pages. An email address is provided for users to email enquiries and ask for help from GEO’s curators.

The Affymetrix page is probably the most useful for UK plant sciences. Spreadsheet-based submission is recommended for Affymetrix deposits, so users should submit an Excel metadata worksheet, CEL files, and processed data for example a Tiling Array. The page gives advice on how to find certain information is given on finding GEO-specific information, and there are template and example spreadsheets.

Once submitted, your dataset becomes a GEO accession and can be identified with a unique accession number. The accession number should be used when you or anyone else references or links to your dataset, which seems like an easy means of tracking its usage within the community.

GEO for plant scientists: How to find Arabidopsis microarray data

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Published on: February 13, 2014

Submission of gene expression data to the Gene Expression Omnibus is now a requirement of publication in most journals, so it is an extremely valuable resource. It is also extremely big, and full of data that isn’t relevant to your question or task at hand – but it is easy to find the right data using the search bar if you follow a few rules. There are example searches on the GEO homepage.

To find data relating to Arabidopsis thaliana, search: (Arabidopsis thaliana[organism])

To find Arabidopsis microarray data, search: (Arabidopsis thaliana[organism]) AND “expression profiling by array”

The easiest way to find other Arabidopsis datasets is to search: (Arabidopsis thaliana[organism]). On the left hand side of the window, there is a ‘Study type’ section. If you click on ‘More…’ a list of study types pops up from which you can select the data type you are looking for (see screen shot below).

You can add any search term you like to the search bar. For example, you could specify author, publication time, types of tissue or stress… or any combination of these. Just keep adding AND in between each term. For example: (Arabidopsis thaliana[organism]) AND “expression profiling by array” AND leaf

GEO provides an informative guide to how to download original records or curated datasets individually or in bulk. You can download data directly from Accession Viewer pages (eg this one) in SOFT, MINiML or TXT formats. Raw data is also available in TAR. You can also do bulk downloads via GEO’s FTP site. All files are compressed using gzip.

It’s also possible to access GEO programmatically in order to, for example, quickly retrieve CEL files from Arabidopsis stress experiments. Again, GEO provide a guide to this, although this is probably something better tackled with some pre-existing knowledge of programming.

GEO post

How do plants remember winter?

Martin Howard is a Professor at the John Innes Centre, one of a small cluster of research institutes in Norwich. In the fourth of our Celebrating Basic Plant Science series, he explains how he uses mathematical modelling to understand how plants remember winter cold and respond to it throughout the year. 

How do plants ‘know’ the correct time to flower? Getting this timing right is vital for reproductive success; flowering in the middle of winter is unlikely to be optimal! Many factors are integrated together to make this critical decision, including the day length.

We have been studying one aspect of this question: How the plant Arabidopsis thaliana perceives and then remembers exposure to winter cold. This fundamental mechanism ensures that flowering doesn’t occur until winter has passed. Interestingly, this memory is quantitative – a longer winter means flowering is faster once it starts (see the image below).  This process is a very nice example of what’s called an epigenetic phenomenon, as the plants store information about winter cold exposure even after the environmental stimulus (cold) has been removed.

So how is this information about cold stored? In Arabidopsis, this is centred on a gene called FLC (Flowering Locus C). When the plant is cold, the FLC gene is turned off. The products of this gene prevent flowering, so turning it off actually stimulates the plant to flower. Over recent years, we have learned a great deal about the operation of FLC and associated genes through genetics and biochemistry, in large part through the work of my experimental collaborator, Caroline Dean. However, despite all this knowledge it was still not clear overall how the epigenetic memory system worked. This was partly due to feedback among the different components, which made arriving at an intuitive understanding a very difficult task. For these reasons, we began to model the dynamics of FLC mathematically in the hope of making sense of these interactions and, we hoped, revealing some underlying simplicity in how the system operated.

Mathematical modelling turned out to be very informative and suggested that FLC gene silencing occurred in an all or nothing fashion inside each cell. (more…)

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