Arabidopsis Research Roundup: July 11th

A couple of weeks since the last update as it’s been quiet for UK Arabidopsis Research publications. However we now see a variety of publications that address some important questions in different signaling pathways. Firstly a multinational collaboration performs a genome-wide analysis of DELLA binding, followed by two studies looking different aspects of light signaling, specifically the link with the production of protective carotenoids and also with the tight control of protein degradation. Elsewhere there is the description of a systems biology approach developed to aid the definition of signaling pathways in non-model organisms and finally a commentary piece about some work on Arabidopsis Arenosa.


Genome Wide Binding Site Analysis Reveals Transcriptional Coactivation of Cytokinin-Responsive Genes by DELLA Proteins (2015) Marín-de la Rosa N, Pfeiffer A, Hill K, Locascio A, Bhalerao RP, Miskolczi P, Grønlund AL, Wanchoo-Kohli A, Thomas SG, Bennett MJ, Lohmann JU, Blázquez MA, Alabadí D PLoS Genet. 11(7):e1005337.

The Centre for Integrative Biology in Nottingham and Rothamstead Plant Science partner with groups from Sweden, Germany, Spain and Saudi Arabia in this truly international collaboration. They investigate the role of DELLA proteins in the relay of environmental cues to multiple transcriptional circuits. The primary experimentation in this study uses ChIP-Seq to analyse the DNA-binding sites of one DELLA protein. Perhaps as expected the DELLA protein binds multiple promotor regions yet with a particular enrichment in regions upstream of cytokinin-regulated genes, where they interact with type-B ARABIDOPSIS RESPONSE REGULATOR (ARR) proteins. The biological relevance of this mechanism is underpinned by the requirement for both DELLAs and B-type ARRs in the control of root growth and photomorphogenesis.


Regulation of carotenoid biosynthesis by shade relies on specific subsets of antagonistic transcription factors and co-factors (2015) Bou-Torrent J, Toledo-Ortiz G, Ortiz-Alcaide M, Cifuentes-Esquivel N, Halliday KJ, Martinez-Garcia JF, Rodriguez-Concepcion M Plant Physiol.

Karen Halliday at the University of Edinburgh is part of this UK-Spanish team that studied the regulation of carotenoid biosynthesis via a light signaling module formed by PIF1 and HY5. In shade conditions, PIF proteins signal for a decrease in carotenoid accumulation, thus saving the plant unneeded energy consumption. The PIF1 response focusses on the phytoene synthase (PSY) biosynthetic gene and is antagonised by the PAR1 transcriptional co-factor. However this is not a universal response carried out by known antagonisers of PIF1 function, demonstrating that carotenoid biosynthesis is finely regulated by a precise subset of regulatory proteins.


High-level expression and phosphorylation of phytochrome B modulates flowering time in Arabidopsis (2015) Hajdu A, Ádám É, Sheerin DJ, Dobos O, Bernula P, Hiltbrunner A,, Kozma-Bognár L, Nagy F Plant Journal

Professor Ferenc Nagy has dual appointments in Edinburgh and in Hungary and this output results from work performed in Hungary. This study looks at control of flowering via phytochrome B signalling, which has been previously shown to rely on the degradation of the CONSTANS (CO) protein that in turn delays flowering by attenuating FLOWERING LOCUS T (FT) expression. Therefore phyB mutants show accelerated flowering, yet this is unexpectedly also true following PHYB overexpression. The novelty of this study comes from showing that PHYB overexpression induces FT without affecting CO transcription but rather acts by causing accumulation of the CO protein, due to an affect on a COP1-ubiquitin ligase complex. This article adds further detail to the already complex relationship between light signaling, the circadian clock, protein degradation and de novo transcription in the control of flowering in Arabidopsis.


Inferring orthologous gene regulatory networks using interspecies data fusion (2015) Penfold CA, Millar JB, Wild DL. Bioinformatics. 31(12):i97-i105.

This study was led by David Wild from Warwick Systems Biology Centre. The authors have used two related Bayesian approaches to network inference that allow Gene Regulatory Networks (GRN) to be jointly inferred in, or leveraged between, several related species, for example between Arabidopsis and related crop species. Inferring gene function is achieved with more accuracy when GRNs are compared between species rather than attempting to use stand alone inference. The manuscript uses data from the yeast S.pombe but the broader principles could be applied to other experimental systems.


The High Life: Alpine Dwarfism in Arabidopsis (2015) Bomblies K Plant Physiol. 168(3):767.

This commentary piece about high altitude growth of Arabidopsis aernosa is the first published work from Kristen Bomblies since she moved her lab to the John Innes Centre from Havard (together with the lab of Levi Yant). Having these two talented young researchers relocate to the UK is be great for UK plant science so I sure everyone in the community wishes them all the best. Watch Kristen talk about her work at a New Phytologist conference from 2014.

Levi Yant also has two postdoctoral posts currently available in his lab.


Genome Resequencing for Mutant Identification

As most biologists will be aware, the cost of DNA sequencing has been falling well in advance of the costs predicted by Moores law (although argued by Neil Hall a few years ago, this might not have been the best thing to happen, intellectually at least).

Instead of simply sequencing many genomes for the sake of it, this also offers opportunities for researchers to use this technology to ‘do-science’ that might previously have been prohibitively laborious or expensive. One such area where this is true is in the identification of novel mutations in plants, especially in Arabidopsis.

Classic approaches to identity the location of an EMS mutation involved mutant identification, backcrossing, selection, rough mapping by PCR or CAPS markers, probably more crossing and then a little guesswork toward the end..…..before using Sanger sequencing to identify what you hope is the causative mutation. Even with a strong following wind this process could take upwards of a year……. many a 1990s PhD thesis was written off the back of mutant identification. In contrast it is now relatively cheap to resequence the Arabidopsis genome so a lot of time can be taken out of this process. In addition, resequencing can remove some of the difficulty involved with selective of mutants that have a subtle phenotypes wherein inaccurate selection of putative mutants would significantly set back the process.

Back in 20111, Anthony Hall’s group in Liverpool University used resequencing in parallel with classic genetics to identify the lesion in the novel early bird1 gene (ebi1), which has a defect in function of the circadian clock. In this case ebi1, which was generated using EMS, was backcrossed 4 times to reduce the number of EMS-induced SNPs not associated with phenotype, and then sequenced alongside the original wildtype plant (from the WS ecotype). The critical part of the protocol came in the power of the software they used to detect homozygous SNPs in the ebi1 line. Indeed the researchers ran into some difficulties due to a high number of SNPs they initially identified. However, when they combined altering the stringency of SNP-calling together with classical rough mapping they were left with approximately 30 SNPs to finally assess. Using a priori knowledge of proposed gene function and by investigating expression changes in these candidates they ultimately identified a novel mutant. Although this process was ultimately successful, it took some extra time due to the difficulty of mutant selection, optimization of the SNP-calling software and subsequent analysis of gene expression.

A recent paper from the lab of Lucia Strader at Washington University in St Louis shows how powerful resequencing can be if you are using a robust method of mutant selection. In their case they isolated mutants with a defect in the root growth response to ABA, which is an unequivocal phenotype to score. They backcrossed their initial mutants, selected for ABA resistance in F2 generation before resequencing these resistant plants. Using this process the authors report that they narrowed their search to between 3-10 candidate genes and that they have subsequently identified novel (unpublished) genes using this method. In addition, as an exemplar of their protocol they used it to isolate novel alleles of known ABA-resistant mutants.

Schematic for mutant identification using NGS. Reproduced from Taylor and Francis PSB
Schematic for mutant identification using NGS. Reproduced from Taylor and Francis PSB


















In parallel they used a similar protocol to the Hall lab where they resequenced non-backcrossed plants and then selected SNPs that only lay within exons.Using this approach they identified between 100-200 homozygous SNPs, a potentially fifty-fold increase compared to their other method. Therefore when you are working with a strong robust phenotype it is probably worth the extra time to obtain a back-crossed population in order to have greater confidence you are isolated your mutant of interest.

The authors importantly note that one limitation of this protocol is that by only selecting for exonic mutations, they are removing the possibility of identifying mutants with splicing or non-coding defects, which may in turn rule out a number of candidate genes.


For me the take-home message from this second study is that if you have a robust phenotype to select for and are confident that your mutation is novel then use of ever-improving NGS is now a time and cost effective way of mutant identification.

In fact this technology might inspire a return to the forward genetic screens of the 80s and 90s , with the aim of identifying novel genes involved in well characterised signaling pathways……..except that PhD students might now have to characterise 10 novel genes prior to graduation….

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

Two GARNet Events

Image by for GARNet

We have some GARNet news to share!

First of all, we are pleased to finally open registration for the hands-on iPlant training workshop ‘Data Mining with iPlant‘. Unfortunately we’ve had to change the planned location, and it will now be at the University of Warwick. The date is still 17-20 September 2013.

For those who don’t know, iPlant is an incredible free resource which allows its users to access high performance computing power, large scale data storage, and analytical software needed for a variety of data- or compute- intensive research applications.

You can either come for just one day for a free hands-on introduction to iPlant, or stay for four days and get in depth training on how to analyse real data in iPlant. For more information go to:

Our second announcement is more of a save-the-date than an invitation. The GARNet general conference will return next year, possibly for one time only. GARNet 2014: The Past, Present and Future of the Genetic Model Revolution will be held at the University of Bristol on 9-10 September 2014. It will be a celebration of exciting new plant science, and a look at the evolving nature of model systems as well as the brilliant achievements made with them in the past.

The Journal of Experimental Botany kindly recorded and uploaded talks from the last GARNet conference in 2011. Here is Katherine Denby of the University of Warwick talking about the PRESTA project, which since this talk has produced two Plant Cell papers (1,2). You can see the rest of the talks from GARNet 2011 on the JXB website.

Mathematics in the Plant Sciences

Categories: bioinformatics, Workshops
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Published on: April 17, 2013

After the ELIXIR/GOBLET workshop before Easter, I headed to Nottingham for another workshop, this time as an onlooker. In a brilliantly eccentric set-up there were actually two parallel workshops, and the participants hopped between the two and had lunch, dinner, and tea breaks in the same rooms. The event I was officially attending was the final meeting of the ‘Systems approaches to study hormone regulated root growth’ US Partnering Award (USPA). The Sixth Mathematics in the Plant Sciences Study Group was in its final two days during the USPA workshop, and some of its attendees presented their research at the USPA meeting or sat in on a session they were particularly interested in.

The Study Groups are hackathon-style workshops at which mathematicians and computer scientists take on problems set by plant scientists. This year’s problems included analysing 300 standing-electron microscopy images of cell walls, and modelling nitrogen release from the symbiosome. As someone with a traditional science background, of course the solutions the teams came up with were a bit beyond me – which is, after all, the whole point of the Study Group. I was impressed by the solutions that had appeared after just four days of work, which ranged from programmes to quantify subtle differences in images, to a model which predicted the optimum light input for photosynthesis and explained plant acclimatisation to variable light sources.

There will be another Study Group and when it is announced, we’ll keep you informed. If you know any mathematicians or computer scientists with a liking for academic science problems and who likes hackathon events, let them know about Study Groups and encourage them to send their details to Susie Lydon, who organises the events. Similarly if your plant research has thrown up a thorny problem which needs specialist expertise, think about submitting it for the next Study Group.

Bioinformatics and Data Analysis Training for Plant Scientists

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Published on: April 11, 2013

Large datasets are now the norm in modern biology. Modelling is progressing from the protein and molecular interaction level to tissue, organ, and whole-plant scales; while everything from genomics through to phenomics and, increasingly, field-level and multi-scale biology involves high throughput experiments. All of these necessitate ever greater computing power and use of complex analysis tools and software. We need you to tell us (click for extremely short survey) which areas of bioinformatics and data analysis you would benefit from training in, ahead of an upcoming GARNet workshop (in association with iPlant and the Hartree Centre).

The iPlant Collaborative is a community of researchers, educators, and students working to deliver a useful and usable cyberinfrastructure for plant science. Users are able to store and analyse their data online, and use iPlant tools for genome assembly, comparative genomics, CHiP and RNA Seq analysis, and much more. A working group is developing modelling tools at the moment, which will take advantage of the high performance computing power iPlant provides, and will support the construction, parameter estimation, sensitivity analysis, and utilization of models. All the resources are free for users worldwide and all are web based, requiring no specialist hardware at the user’s location. (more…)

Bioinformatics: Training the Trainers

Categories: bioinformatics, Workshops
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Published on: April 9, 2013

My apologies for the GARNet radio silence over the last couple of weeks – we’ve been busy helping with PlantSci 2013 preparations as well as working on our own 2013 meetings (announcement of our September workshop coming soon!), going to a few external meetings, and enjoying that arctic Easter break too.

The week before Easter I went to an ELIXIR/GOBLET Training the Trainers workshop at TGAC (The Genome Analysis Centre). If you don’t know what ELIXIR or GOBLET are … don’t worry. They’re fairly new bodies and at the moment have quite a niche target market/audience, but they will be influencing bioinformatics and computational biology use and training over the next few years.

The ELIXIR project was FP7-funded in 2007 and aims to establish a sustainable European infrastructure for biological information. The infrastructure should eventually be a place for data storage, access, and analysis – for anyone who wants to use it in one of the member countries. Sixteen countries are participating, and each has a ‘node’ responsible for a different aspect of the project. ELIXIR-UK is based at the EBI in Cambridge, and is both the co-ordinating hub of the entire project and the training node.

GOBLET is the unusually straightforward acronym for Global Organisation for Bioinformatics Learning, Education and Training. Its mission is essentially to support trainers and educators in bioinformatics and computational biology. ‘Training’ can be either a full-time job, or incorporated into another job. Their aims include establishing guidelines and standards for training, gather funding, and forming a networking and support hub where resources can be shared internationally.


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