Tuesday, 28 February 2017

Bumblebees show cognitive flexibility by improving on an observed complex behavior


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Science  24 Feb 2017:
Vol. 355, Issue 6327, pp. 833-836
DOI: 10.1126/science.aag2360

Very clever bees use tools

One hallmark of cognitive complexity is the ability to manipulate objects with a specific goal in mind. Such “tool use” at one time was ascribed to humans alone, but then to primates, next to marine mammals, and later to birds. Now we recognize that many species have the capacity to envision how a particular object might be used to achieve an end. Loukola et al. extend this insight to invertebrates. Bumblebees were trained to see that a ball could be used to produce a reward. These bees then spontaneously rolled the ball when given the chance.
Science, this issue p. 833


We explored bees’ behavioral flexibility in a task that required transporting a small ball to a defined location to gain a reward. Bees were pretrained to know the correct location of the ball. Subsequently, to obtain a reward, bees had to move a displaced ball to the defined location. Bees that observed demonstration of the technique from a live or model demonstrator learned the task more efficiently than did bees observing a “ghost” demonstration (ball moved via magnet) or without demonstration. Instead of copying demonstrators moving balls over long distances, observers solved the task more efficiently, using the ball positioned closest to the target, even if it was of a different color than the one previously observed. Such unprecedented cognitive flexibility hints that entirely novel behaviors could emerge relatively swiftly in species whose lifestyle demands advanced learning abilities, should relevant ecological pressures arise.

History of science: Trial by gender

Published online
Jennifer Rampling applauds an account of how Johannes Kepler saved his mother from being burned as a witch.

The Astronomer and the Witch: Johannes Kepler's Fight for his Mother

Ulinka Rublack Oxford University Press: 2015. ISBN: 9780198736776
Buy this book: US UK Japan
Katharina Kepler depicted here being threatened with torture.
On the cover of The Astronomer and the Witch is a portrait of Johannes Kepler: confident, well dressed, half-smiling. This is the image that the imperial mathematician projected to his peers and patrons. But it is not the Kepler whom we meet in Ulinka Rublack's enthralling book — anxious, harassed by financial and family problems, and not even the main character. Rublack's protagonist is the great astronomer's mother, the unfairly accused “witch” of the title. In placing Katharina centre stage, Rublack tells a new story, one that is as much social history as it is scientific revolution.
As women in early modern Europe aged and their fertility declined, so did their status. In a small town such as Leonberg in the duchy of Württemberg, part of present-day Germany, even a respectable property owner like Katharina Kepler could not escape the stigma of age. Yet women did not all face this challenge equally. Rublack juxtaposes Katharina's hard life with the luxurious retirement of Sibylle, widowed duchess of Württemberg, on whom, in a way, her fate came to depend.
While Katharina struggled to work her land and raise children, often without their father, the rough ground behind Leonberg Castle was cleared to provide Sibylle with spectacular gardens. Investing in medicinal plants added to the duchess's standing as a patroness of the poor and sick. Katharina, tired and short-tempered, did not enjoy the same indulgence. Her use of herbal remedies, common enough at the time, raised suspicion after a local woman blamed her illness on a “witches' brew” served by Katharina. After more allegations, and many delays, in 1619 Katharina was formally accused of witchcraft.
What distinguishes Katharina's case from thousands like it is the involvement of her famous son — the reason that the trial records have been preserved. Sifting through these, Rublack reconstructs an atmosphere of anxiety and suspicion as Württemberg slid into the Thirty Years' War. Accusations of witchcraft threw whole families under suspicion, and the taint of religious unorthodoxy could damage careers, as Johannes Kepler discovered when his Calvinist leanings blocked him from a post at the University of Tübingen. As Rublack notes, to win patronage required “not only a powerful intellect and vision, but also books, ink, piety, and perfect manners”. Having mastered these resources in his precarious career as mathematician to three emperors, Kepler now deployed them on behalf of his family. After all, he had achieved fame promoting a controversial position, Copernicanism, for which standards of proof were considerably higher than those required to burn a witch.
Rublack shows how Kepler bent his experience towards deconstructing faulty arguments and marshalling evidence for Katharina's defence. The legal system provided checks and balances, for example by requiring multiple witnesses, but in practice short cuts were taken. The case against Katharina was assembled by administrators sympathetic to her accusers, and witnesses gave conflicting evidence or described events from their childhoods. To this might be added, at any time, a 'confession' under torture. Convicted witches were usually burned alive.
In this fraught environment, Kepler repeatedly revised his Harmony of the World (1619): a five-part magnum opus that included his third law of planetary motion and his views on topics as diverse as musical theory and astrology. In a chapter on psychology, Kepler betrayed his own ambiguous feelings on his mother's plight, asking whether she had brought her misfortune on herself. Yet, by the time he prepared her final defence two years later, the astronomer had devised a new narrative: one that granted old women such as Katharina a role as knowledge-makers.
Rublack argues that Kepler justified his mother's medical practice by drawing a parallel with privileged women such as Sibylle. He claimed that women's experience and observation, gained (often painfully) over long periods of time, “constituted a basis for reputable and probable, if not certain knowledge”. Kepler defended his mother by using Sibylle as an unimpeachable role model of a pious woman dispensing medical care.
Kepler wins the day, for although Katharina spoke in her own defence, it is her son's arguments that are preserved verbatim in the trial documents, commenting on and judging women's behaviour. Chained in her cell at the centre of the controversy, Katharina's own voice is harder to hear. Rublack calls out Kepler's past biographers for dismissing his mother as quarrelsome, difficult, “witch-like”. If I have one criticism of the book, it is that its title plays to that stereotype, rather than to the nuanced characterization that the author has drawn. Rublack's vigorous, early modern anti-heroine was, surely, entitled to her anger.

Bibliometrics: The Leiden Manifesto for research metrics

Nature | Comment

Use these ten principles to guide research evaluation, urge Diana Hicks, Paul Wouters and colleagues.

Data are increasingly used to govern science. Research evaluations that were once bespoke and performed by peers are now routine and reliant on metrics1. The problem is that evaluation is now led by the data rather than by judgement. Metrics have proliferated: usually well intentioned, not always well informed, often ill applied. We risk damaging the system with the very tools designed to improve it, as evaluation is increasingly implemented by organizations without knowledge of, or advice on, good practice and interpretation.
Before 2000, there was the Science Citation Index on CD-ROM from the Institute for Scientific Information (ISI), used by experts for specialist analyses. In 2002, Thomson Reuters launched an integrated web platform, making the Web of Science database widely accessible. Competing citation indices were created: Elsevier's Scopus (released in 2004) and Google Scholar (beta version released in 2004). Web-based tools to easily compare institutional research productivity and impact were introduced, such as InCites (using the Web of Science) and SciVal (using Scopus), as well as software to analyse individual citation profiles using Google Scholar (Publish or Perish, released in 2007).
In 2005, Jorge Hirsch, a physicist at the University of California, San Diego, proposed the h-index, popularizing citation counting for individual researchers. Interest in the journal impact factor grew steadily after 1995 (see 'Impact-factor obsession').
Lately, metrics related to social usage and online comment have gained momentum — F1000Prime was established in 2002, Mendeley in 2008, and (supported by Macmillan Science and Education, which owns Nature Publishing Group) in 2011.
As scientometricians, social scientists and research administrators, we have watched with increasing alarm the pervasive misapplication of indicators to the evaluation of scientific performance. The following are just a few of numerous examples. Across the world, universities have become obsessed with their position in global rankings (such as the Shanghai Ranking and Times Higher Education's list), even when such lists are based on what are, in our view, inaccurate data and arbitrary indicators.
Some recruiters request h-index values for candidates. Several universities base promotion decisions on threshold h-index values and on the number of articles in 'high-impact' journals. Researchers' CVs have become opportunities to boast about these scores, notably in biomedicine. Everywhere, supervisors ask PhD students to publish in high-impact journals and acquire external funding before they are ready.
In Scandinavia and China, some universities allocate research funding or bonuses on the basis of a number: for example, by calculating individual impact scores to allocate 'performance resources' or by giving researchers a bonus for a publication in a journal with an impact factor higher than 15 (ref. 2).
In many cases, researchers and evaluators still exert balanced judgement. Yet the abuse of research metrics has become too widespread to ignore.
We therefore present the Leiden Manifesto, named after the conference at which it crystallized (see Its ten principles are not news to scientometricians, although none of us would be able to recite them in their entirety because codification has been lacking until now. Luminaries in the field, such as Eugene Garfield (founder of the ISI), are on record stating some of these principles3, 4. But they are not in the room when evaluators report back to university administrators who are not expert in the relevant methodology. Scientists searching for literature with which to contest an evaluation find the material scattered in what are, to them, obscure journals to which they lack access.
We offer this distillation of best practice in metrics-based research assessment so that researchers can hold evaluators to account, and evaluators can hold their indicators to account.
Data Source: Thomson Reuters Web of Science; Analysis: D.H., L.W.

Ten principles

1) Quantitative evaluation should support qualitative, expert assessment. Quantitative metrics can challenge bias tendencies in peer review and facilitate deliberation. This should strengthen peer review, because making judgements about colleagues is difficult without a range of relevant information. However, assessors must not be tempted to cede decision-making to the numbers. Indicators must not substitute for informed judgement. Everyone retains responsibility for their assessments.
2) Measure performance against the research missions of the institution, group or researcher. Programme goals should be stated at the start, and the indicators used to evaluate performance should relate clearly to those goals. The choice of indicators, and the ways in which they are used, should take into account the wider socio-economic and cultural contexts. Scientists have diverse research missions. Research that advances the frontiers of academic knowledge differs from research that is focused on delivering solutions to societal problems. Review may be based on merits relevant to policy, industry or the public rather than on academic ideas of excellence. No single evaluation model applies to all contexts.
3) Protect excellence in locally relevant research. In many parts of the world, research excellence is equated with English-language publication. Spanish law, for example, states the desirability of Spanish scholars publishing in high-impact journals. The impact factor is calculated for journals indexed in the US-based and still mostly English-language Web of Science. These biases are particularly problematic in the social sciences and humanities, in which research is more regionally and nationally engaged. Many other fields have a national or regional dimension — for instance, HIV epidemiology in sub-Saharan Africa.
This pluralism and societal relevance tends to be suppressed to create papers of interest to the gatekeepers of high impact: English-language journals. The Spanish sociologists that are highly cited in the Web of Science have worked on abstract models or study US data. Lost is the specificity of sociologists in high-impact Spanish-language papers: topics such as local labour law, family health care for the elderly or immigrant employment5. Metrics built on high-quality non-English literature would serve to identify and reward excellence in locally relevant research.
4) Keep data collection and analytical processes open, transparent and simple. The construction of the databases required for evaluation should follow clearly stated rules, set before the research has been completed. This was common practice among the academic and commercial groups that built bibliometric evaluation methodology over several decades. Those groups referenced protocols published in the peer-reviewed literature. This transparency enabled scrutiny. For example, in 2010, public debate on the technical properties of an important indicator used by one of our groups (the Centre for Science and Technology Studies at Leiden University in the Netherlands) led to a revision in the calculation of this indicator6. Recent commercial entrants should be held to the same standards; no one should accept a black-box evaluation machine.
Simplicity is a virtue in an indicator because it enhances transparency. But simplistic metrics can distort the record (see principle 7). Evaluators must strive for balance — simple indicators true to the complexity of the research process.
“Simplicity is a virtue in an indicator because it enhances transparency.”
5) Allow those evaluated to verify data and analysis. To ensure data quality, all researchers included in bibliometric studies should be able to check that their outputs have been correctly identified. Everyone directing and managing evaluation processes should assure data accuracy, through self-verification or third-party audit. Universities could implement this in their research information systems and it should be a guiding principle in the selection of providers of these systems. Accurate, high-quality data take time and money to collate and process. Budget for it.
6) Account for variation by field in publication and citation practices. Best practice is to select a suite of possible indicators and allow fields to choose among them. A few years ago, a European group of historians received a relatively low rating in a national peer-review assessment because they wrote books rather than articles in journals indexed by the Web of Science. The historians had the misfortune to be part of a psychology department. Historians and social scientists require books and national-language literature to be included in their publication counts; computer scientists require conference papers be counted.
Citation rates vary by field: top-ranked journals in mathematics have impact factors of around 3; top-ranked journals in cell biology have impact factors of about 30. Normalized indicators are required, and the most robust normalization method is based on percentiles: each paper is weighted on the basis of the percentile to which it belongs in the citation distribution of its field (the top 1%, 10% or 20%, for example). A single highly cited publication slightly improves the position of a university in a ranking that is based on percentile indicators, but may propel the university from the middle to the top of a ranking built on citation averages7.
7) Base assessment of individual researchers on a qualitative judgement of their portfolio. The older you are, the higher your h-index, even in the absence of new papers. The h-index varies by field: life scientists top out at 200; physicists at 100 and social scientists at 20–30 (ref. 8). It is database dependent: there are researchers in computer science who have an h-index of around 10 in the Web of Science but of 20–30 in Google Scholar9. Reading and judging a researcher's work is much more appropriate than relying on one number. Even when comparing large numbers of researchers, an approach that considers more information about an individual's expertise, experience, activities and influence is best.
8) Avoid misplaced concreteness and false precision. Science and technology indicators are prone to conceptual ambiguity and uncertainty and require strong assumptions that are not universally accepted. The meaning of citation counts, for example, has long been debated. Thus, best practice uses multiple indicators to provide a more robust and pluralistic picture. If uncertainty and error can be quantified, for instance using error bars, this information should accompany published indicator values. If this is not possible, indicator producers should at least avoid false precision. For example, the journal impact factor is published to three decimal places to avoid ties. However, given the conceptual ambiguity and random variability of citation counts, it makes no sense to distinguish between journals on the basis of very small impact factor differences. Avoid false precision: only one decimal is warranted.
9) Recognize the systemic effects of assessment and indicators. Indicators change the system through the incentives they establish. These effects should be anticipated. This means that a suite of indicators is always preferable — a single one will invite gaming and goal displacement (in which the measurement becomes the goal). For example, in the 1990s, Australia funded university research using a formula based largely on the number of papers published by an institute. Universities could calculate the 'value' of a paper in a refereed journal; in 2000, it was Aus$800 (around US$480 in 2000) in research funding. Predictably, the number of papers published by Australian researchers went up, but they were in less-cited journals, suggesting that article quality fell10.
10) Scrutinize indicators regularly and update them. Research missions and the goals of assessment shift and the research system itself co-evolves. Once-useful metrics become inadequate; new ones emerge. Indicator systems have to be reviewed and perhaps modified. Realizing the effects of its simplistic formula, Australia in 2010 introduced its more complex Excellence in Research for Australia initiative, which emphasizes quality.

Next steps

Abiding by these ten principles, research evaluation can play an important part in the development of science and its interactions with society. Research metrics can provide crucial information that would be difficult to gather or understand by means of individual expertise. But this quantitative information must not be allowed to morph from an instrument into the goal.
The best decisions are taken by combining robust statistics with sensitivity to the aim and nature of the research that is evaluated. Both quantitative and qualitative evidence are needed; each is objective in its own way. Decision-making about science must be based on high-quality processes that are informed by the highest quality data.


  1. Wouters, P. in Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact (eds Cronin, B. & Sugimoto, C.) 4766 (MIT Press, 2014).
    Show context
  2. Shao, J. & Shen, H. Learned Publ. 24, 9597 (2011).
    Show context
  3. Seglen, P. O. Br. Med. J. 314, 498502 (1997).
    Show context
  4. Garfield, E. J. Am. Med. Assoc. 295, 9093 (2006).
    Show context
  5. López Piñeiro, C. & Hicks, D. Res. Eval. 24, 7889 (2015).
    Show context
  6. van Raan, A. F. J., van Leeuwen, T. N., Visser, M. S., van Eck, N. J. & Waltman, L. J. Informetrics 4, 431435 (2010).
    Show context
  7. Waltman, L. et al. J. Am. Soc. Inf. Sci. Technol. 63, 24192432 (2012).
    Show context
  8. Hirsch, J. E. Proc. Natl Acad. Sci. USA 102, 1656916572 (2005).
    Show context
  9. Bar-Ilan, J. Scientometrics 74, 257271 (2008).
    Show context
  10. Butler, L. Res. Policy 32, 143155 (2003).

No Gold In Them Thar Hills: academic journal publishing

Monday, February 27, 2017

Image via.

A long time ago, there was an house I wanted to live in. I didn’t get to live in that house but, years later, I got to go a party there and, as I wandered from room to room, I had a brief glimpse into what my life would have been like if I had lived there. It would not necessarily have been better, but it definitely would have been different.

A couple weeks ago, I experienced the publishing equivalent of that not-better-but-different experience. I was at the copyediting stage with an article that had been accepted for publication at pretty great international journal. Fast forward through three rounds of peer review (real life social scientists making sense of my humanities-based approach) and I was finally at copyediting and signing the publishing agreement.

Along with the proofs came an email:

Dear Lily Cho

Your article listed above is currently in production with [Big Academic Publisher].

We are delighted that you have chosen to publish your paper in [Great International Journal]. This email is to tell you about the publication options available to you.

Standard publication route
Your article will be published in the journal, and made available online permanently for subscribers and licensed institutions throughout the world, including provision of online access through developing world initiatives. You will also receive a link via email that you can send to 50 colleagues who can download the article free of charge. After the embargo period for this journal, you may deposit the Accepted Manuscript into an institutional or subject repository (Green Open Access).

Gold Open Access publication
You have the option to pay a charge to make the final version of your article freely available online at the point of publication, permanently, for anyone to read (Gold Open Access). This requires payment of an Article Publishing Charge (APC). Please note that this option is strictly your choice, and is not required for publication in the journal. It is not available for research articles of less than two printed pages in length.
If you would like to publish your article via the Gold Open Access route please read the notes below:
• You will retain the rights in your article but will be asked to sign an appropriate article publishing agreement to enable us to publish the article.
• Many institutions and funders partner with [Big Five Academic Publisher] to offer authors a discount on the standard APC or enable them to publish open access at no cost to themselves. Please visit our Author Services website to find out if you are eligible.

Choosing the “Gold Open Access” would cost me somewhere in the neighbourhood of $2500. I went through one of those lightening fast thought processes that I go through when I am expecting to do something pretty routine (not my first time signing a publishing agreement, have allotted exactly two minutes for this routine task in the midst of a busy day, and am momentarily startled by a glitch in the two-minute plan (woah! Gold access? Whuuuut?) and then plough through to keep to my two-minute plan (whuuut? pay thousands of dollars so that my colleagues and students have a chance to read this article without having to click through proxy server? No, thanks).

I am not about to start on a rant about “Gold Open Access,” or other ways of further privatizing the (completely vital) circulation and exchange of academic work. Maybe another time. But this moment of deciding not to pay for the privilege of giving my brilliant work away did make me go back to a different moment.

Back when I co-edited an academic journal, we were approached by more than one of the Big Academic Publishers. This particular publisher, the one that just offered me “Gold Access,” came closer than any of others to taking over the journal. At the time, the offer was enticing for someone like me. They offered to deal with all the non-academic stuff (subscription management, marketing, manuscript submission processes). We would keep all the editorial control but they would take all the money and the content. I say the offer was enticing because there were definitely things we could have done better and it was all so much work. Keep in mind that editing the journal was essentially a volunteer position. There was no money at all for doing it. There was no course release (there might have been a little before but there was no release by the time I signed up). This work wasn’t even listed as a “professional contribution” under my university’s promotion and tenure guidelines. It is considered to be “service” (and under my department’s p & t standards, service does not rate the same way as teaching and professional contribution aka research) and I was very happy to serve. (All you journal editors out there, I see you and I admire you and know that you are working your butt off only to have everyone mad at you because their article is stuck in peer review limbo when it is totally not your fault.) Given these conditions, you can see how dreamy it would be for a Big Academic Publisher to swoop in and save me. I could actually edit and they would take care of the all the essential but nit-picky stuff.

But the editorial board, in all its wisdom, voted against the offer from the Big Academic Publisher. They thought about our credibility as a journal, what it would mean to ask our colleagues to peer review when the journal would then turn around and charge huge fees for access to the finished work, and many other things besides.

For me, turning down the offer to let someone else manage the journal was a lot like not getting to live in that house. I remember once reading a book called Life Would Be Perfect If I Lived in That House. I don’t remember the book now, but I do remember that sentiment. That belief, no matter how silly, that everything wrong would somehow be fixed if I could just live there. 

Going through production for my article was like living through a weird alternate world where I got to experience, albeit as an author and not an editor, what it would have been like if the journal I had co-edited had gone down that other route, had moved into that other house.

Everything was so smooth. The submission process was so elegant. The turnaround on production was so fast. There was an official Academic Editor overseeing the copyediting AND a copyeditor. All this in addition to the editors of the special issue, and the editors of the journal itself. So much editing was being done so seamlessly. I admired the web interface for uploading copyedits, the way they streamlined copyediting queries, the professionalism of everyone working at this Big Academic Publisher.

It was like I was at that party in that house that I didn’t get to live and I wandered around saying quietly to myself things like, Wow, these floors! This window! This light fixture! I didn’t actually want to live there anymore. I had moved on. But it was just a moment where I could see what that other life might have been.

I thought of all this again when I saw yet another news story about a major university having to cut its subscriptions to journals because the publishers have once again raised the prices. It is no secret that academic publishing has become an oligopoly:

Combined, the top five most prolific publishers account for more than 50% of all papers published in 2013. Disciplines in the social sciences have the highest level of concentration (70% of papers from the top five publishers), while the humanities have remained relatively independent (20% from top five publishers). (Larivière, Haustein, and Mongeon).

In the humanities, we are still choosing, more than most disciplines, to support journals that are outside of the circuit of the big publishers: Reed-Elsevier, Wiley-Blackwell, Springer, and Taylor & Francis. By support, I mean we are still choosing to read, publish, and teach articles that are published outside of these circuits. It seems to me that now, more than ever, we have to pay attention to these questions of ownership. Next time you submit an article for publication, or assign an article to teach, look at who owns the journal, and think about whether or not you want your work to be aligned with that publisher. I know I will.

And I know that this is easier said than done. This year, I am serving on my university’s Senate Tenure and Promotion Committee. That means I read a LOT of Tenure and Promotion files belonging to colleagues across every discipline at York. I know that there is a fight about metrics going down. It is not just optics. Publishing with a big journal means that your work will be promoted differently. It will likely register differently in terms of citation and general circulation. How widely your article circulates, and how often you are cited, matters more than ever.

But there are options and it is worth exploring them. In my own field, I am really lucky that there are amazing journals edited by amazing people that are not (yet) part of the oligopoly (hello thereARIELCanadian LiteratureESCImaginations,  Postcolonial TextSmall AxeStudies in Canadian LiteratureTOPIA, and many, many more). Not all of these are open access. Most are not. Some are owned or managed by reasonably big publishers too but, as far as I can tell, these publishers have arrangements with the journals that are pretty fair and equitable. These arrangements can be actually be a good thing. For example, ESC’s relationship with Johns Hopkins offers a real benefit to all members of the main scholarly association in my field, ACCUTE.  

There are no fast and easy solutions. As someone who has grappled with the budget of getting a journal out, I can tell you that open access is not the silver bullet for fighting “Gold Open Access.” And I actually don’t really believe that academics should be paid for their academic writing. It is a basic and important part of our job. I also don’t believe in paying for peer review. That is also a basic and important part of my job. It is invisible and thankless labour. But, as with so many things, I do it because  that’s what it means to be part of an intellectual community and I am grateful every single day for the great privilege of being in this community.

But, at the very least, I want to remember that my life would definitely not be perfect if I lived in that other house. And I want to stay alert to the politics and possibilities of the vibrant intellectual life outside and beyond the oligopoly.

A vindication of ethnobotany: Between social and natural science

Article · June 2015
DOI: 10.7203/metode.6.4402
Ethnobotany, a discipline located at the intersection between natural science and social science, is sometimes misunderstood by researchers from one or other of these fields. In this article we discuss the positive and negative aspects of interdisciplinarity regarding this subject, and we argue for its status as a true science from different points of view. Our conclusion is that ethnobotanical research – like all ethnobiological research in general – undoubtedly exists within the scientific field and is successfully established, active and productive. In addition, ethnobotany is a citizen science: the participation of the population is essential for research, which must be communicated to academia and to the general citizen

Carole Brousse, « L’ethnobotanique au carrefour du Muséum national d’Histoire naturelle et du Musée ethnologique de Salagon (Alpes-de-Haute-Provence)

», Revue d’ethnoécologie [En ligne], 7 | 2015, mis en ligne le 30 juin 2015, consulté le 28 février 2017. URL : ; DOI : 10.4000/ethnoecologie.2157 

The striking and unexpected cytogenetic diversity of genus Tanacetum L. (Asteraceae): A cytometric and fluorescent in situ hybridisation study of Iranian taxa

ArticleinBMC Plant Biology 15(1):174 · July 2015
DOI: 10.1186/s12870-015-0564-8 · Source: PubMed · License: CC BY 4.0
Although karyologically well studied, the genus Tanacetum (Asteraceae) is poorly known from the perspective of molecular cytogenetics. The prevalence of polyploidy, including odd ploidy warranted an extensive cytogenetic study. We studied several species native to Iran, one of the most important centres of diversity of the genus. We aimed to characterise Tanacetum genomes through fluorochrome banding, fluorescent in situ hybridisation (FISH) of rRNA genes and the assessment of genome size by flow cytometry. We appraise the effect of polyploidy and evaluate the existence of intraspecific variation based on the number and distribution of GC-rich bands and rDNA loci. Finally, we infer ancestral genome size and other cytogenetic traits considering phylogenetic relationships within the genus. We report first genome size (2C) estimates ranging from 3.84 to 24.87 pg representing about 11 % of those recognised for the genus. We found striking cytogenetic diversity both in the number of GC-rich bands and rDNA loci. There is variation even at the population level and some species have undergone massive heterochromatic or rDNA amplification. Certain morphometric data, such as pollen size or inflorescence architecture, bear some relationship with genome size. Reconstruction of ancestral genome size, number of CMA+ bands and number of rDNA loci show that ups and downs have occurred during the evolution of these traits, although genome size has mostly increased and the number of CMA+ bands and rDNA loci have decreased in present-day taxa compared with ancestral values. Tanacetum genomes are highly unstable in the number of GC-rich bands and rDNA loci, although some patterns can be established at the diploid and tetraploid levels. In particular, aneuploid taxa and some odd ploidy species show greater cytogenetic instability than the rest of the genus. We have also confirmed a linked rDNA arrangement for all the studied Tanacetum species. The labile scenario found in Tanacetum proves that some cytogenetic features previously regarded as relatively constant, or even diagnostic, can display high variability, which is better interpreted within a phylogenetic context.

The striking and unexpected cytogenetic diversity of genus Tanacetum L. (Asteraceae): a cytometric and fluorescent in situ hybridisation study of Iranian taxa

BMC Plant Biology201515:174
DOI: 10.1186/s12870-015-0564-8
Received: 17 April 2015
Accepted: 26 June 2015
Published: 8 July 2015



Although karyologically well studied, the genus Tanacetum (Asteraceae) is poorly known from the perspective of molecular cytogenetics. The prevalence of polyploidy, including odd ploidy warranted an extensive cytogenetic study. We studied several species native to Iran, one of the most important centres of diversity of the genus. We aimed to characterise Tanacetum genomes through fluorochrome banding, fluorescent in situ hybridisation (FISH) of rRNA genes and the assessment of genome size by flow cytometry. We appraise the effect of polyploidy and evaluate the existence of intraspecific variation based on the number and distribution of GC-rich bands and rDNA loci. Finally, we infer ancestral genome size and other cytogenetic traits considering phylogenetic relationships within the genus.


We report first genome size (2C) estimates ranging from 3.84 to 24.87 pg representing about 11 % of those recognised for the genus. We found striking cytogenetic diversity both in the number of GC-rich bands and rDNA loci. There is variation even at the population level and some species have undergone massive heterochromatic or rDNA amplification. Certain morphometric data, such as pollen size or inflorescence architecture, bear some relationship with genome size. Reconstruction of ancestral genome size, number of CMA+ bands and number of rDNA loci show that ups and downs have occurred during the evolution of these traits, although genome size has mostly increased and the number of CMA+ bands and rDNA loci have decreased in present-day taxa compared with ancestral values.


Tanacetum genomes are highly unstable in the number of GC-rich bands and rDNA loci, although some patterns can be established at the diploid and tetraploid levels. In particular, aneuploid taxa and some odd ploidy species show greater cytogenetic instability than the rest of the genus. We have also confirmed a linked rDNA arrangement for all the studied Tanacetum species. The labile scenario found in Tanacetum proves that some cytogenetic features previously regarded as relatively constant, or even diagnostic, can display high variability, which is better interpreted within a phylogenetic context.


5S 35S Aneuploidy Evolutionary cytogenetics Genomic instability L-type arrangement Polyploidy Odd ploidy Ribosomal DNA


Tanacetum L. is a genus of the family Asteraceae Bercht. & J. Presl and includes approximately 160 species [1]. It is one of the largest genera within the tribe Anthemideae Cass., together with genera such as Artemisia L., Achillea L. and Anthemis L. Commonly known as tansies, Tanacetum species are native to many areas of the Northern Hemisphere, occupying the temperate zones of Europe, Asia, North Africa and North America, but particularly abundant in the Mediterranean and Irano-Turanian regions. Although the presence of Tanacetum in the Southern Hemisphere is much less common [1, 2], some species are grown worldwide such as T. parthenium (L.) Sch. Bip., which can behave as a weed outside its native range.
Tanacetum species are mostly perennial herbs, although the genus has some annuals and some subshrubs. They usually form rhizomes and are aromatic plants. Their capitula, solitary or arranged in more or less dense or loose compound inflorescences, always contain disc flowers (flosculous, yellow, numerous — up to 300), sometimes with ray flowers (ligulate, white, yellow or pale pink). Tanacetum is considered to hold a crucial position for understanding the phylogenetic relationships within its tribe, but available phylogenetic reconstructions show that these species form an imbroglio whose generic relationships and infrageneric arrangement are still unsettled [3]. Many species of Tanacetum are widely distributed and are used as sources of medicines, food or forage. In particular, several studies have shown that essential oils from T. parthenium [4, 5, 6] and T. balsamita L. [7, 8, 9] have strong antibacterial, cytotoxic, neuroprotective and antioxidant activity. T. balsamita has also shown anti-inflammatory properties [10]. West and central Asia are two important speciation centres of the genus [11], and Iran is one of the main areas of speciation and diversification, promoted by a unique combination of ecosystems. In Iran the genus is represented by 36 species according to the most recent revisions, including 16 endemic taxa [3, 12, 13, 14, 15, 16, 17].
The karyology of Tanacetum has been extensively studied, with chromosome counts known for a considerable number of its species [18, 19, 20, 21]. Its basic chromosome number is x = 9, as in most Anthemideae and Asteraceae; indeed x = 9 is likely the ancestral basic number for the family as a whole [22]. Ploidy levels are found up to 10× [23]. Recent work has added more karyological information for this genus; it seems that polyploidy is an important evolutionary force and the existence of odd ploidy, aneuploidy and presence of B-chromosomes is not uncommon [18, 20].
Methods such as fluorochrome banding and fluorescent in situ hybridisation (FISH) of 5S and 18S-5.8S-26S (35S) ribosomal RNA genes (rDNA) provide chromosome markers, excellent tools to improve karyotype description [24]. These methods have proven useful for comparing taxa at different levels, particularly in plants (see, for example, [25] on several Asteraceae genera; [26], on Fragaria L.; [27] on Thinopyrum Á. Löve). However broader cytogenetic information is largely missing for Tanacetum, as happens for many wild species, unlike crops or other economically interesting plants whose chromosomes have been more deeply investigated. Genome size estimation, easily obtained by flow cytometry, has been used in a similar way (see, for example, [28] on Tripleurospermum Sch. Bip.; [29] on Carthamus L.; [30] on Artemisia L.). The combination of these methods can improve our understanding of chromosome evolution and genome organisation processes in plants [31]. Moreover, molecular cytogenetic studies, together with genome size evaluation, are also useful in a wide range of biological fields, from taxonomy, evaluation and conservation of genetic resources, to plant breading [24, 32, 33, 34].
Despite being a large and well-known genus, molecular cytogenetic studies of Tanacetum are limited to a single work reporting data on two species: T. achilleifolium (M. Bieb.) Sch. Bip. and T. parthenium [35]. That study described co-localisation of both 5S and 35S ribosomal RNA genes in Tanacetum, the so-called linked type (L-type) arrangement of rDNA, confirming preliminary findings for this genus [25]. This rDNA organisation is typical of several Asteraceae members, particularly those belonging to tribes Anthemideae and the Heliantheae Cass. alliance (see [25, 36] for details). However, the most common rDNA organisation in plants, and also in family Asteraceae, is that in which both rRNA genes are separated (S-type arrangement). Remarkably, [35] found that one 35S rDNA locus was separated in T. achilleifolium, while the other one remained co-localised with the 5S. This dual organisation of rDNA in the same species (i.e. both L-type and S-type coexisting) is exceptional.
Likewise, genome sizes for Tanacetum are only known for few species, reduced to three research works to our knowledge [37, 38, 39]. In this study, we establish a deeper knowledge of Tanacetum genomes through molecular cytogenetic and genome size analysis. We focus on several species native to Iran, since this area constitutes a centre of speciation and diversification of the genus. All ploidy levels previously reported for the genus (from 2x to 10x) exist in Iran [20], many of the studied tansies grow there in polyploid series, and odd stable ploidy, aneuploidy and presence of B-chromosomes have been found [3, 20]. Our specific goals were (1) to characterise the genomes of Tanacetum species by flow cytometry, fluorochrome banding and FISH of rRNA genes, and particularly, to observe the rDNA organisation in these species, (2) to detect the karyotype and genome size patterns of the genus and describe their typical models, if any, (3) to address the presence of polymorphisms at the cytogenetic level, (4) to assess the impact of polyploidy in Tanacetum genomes, and (5) to reconstruct ancestral character states of genome size and karyotype features such as number of rDNA loci and CMA+ bands to infer genome evolution in the context of a phylogenetic framework of the genus.


The chromosome counts here represent most ploidy levels found in Tanacetum to present, all x = 9-based. We found B-chromosomes in one of the populations of T. pinnatum and in T. fisherae, and some of the populations investigated, such as those of T. archibaldii and T. aureum (Lam.) Greuter, M.V.Agab. & Wagenitz, presented mixed ploidy. In addition, several of the studied taxa are odd polyploids, such as the case of triploid T. joharchii Sonboli & Kaz. Osaloo and T. kotschyi (Boiss.) Grierson, and the pentaploid T. fisherae Aitch. & Hemsl. which is also a hypoaneuploid since it has lost one chromosome out of the 45 expected. More detailed karyological information is in Table 1.
Table 1
Provenance and voucher number from the Medicinal Plants and Drug Research Institute Herbarium (MPH), Shahid Beheshti University (Tehran) of the populations of Tanacetum studied, together with genome size, number of CMA+ bands and number of rDNA sites
T. archibaldii Podl.
Mazandaran: Pole Zangoleh road (1790)
56itc (50, 54, 66)
T. balsamita L.
Mazandaran: Pole Zangooleh road (1788)
40tc (24, 30, 34, 36, 40, 42, 44)
T. budjnurdense (Rech.f) Tzvel.
Khorasan: Bujnourd (1477)
T. canescens DC.
Zanjan: Soltanieh (1912)
4, 6 and 8tc
6 (8)
T. aureum (Lam.) Greuter, M.V.Agab. & Wagenitz
Urmia: Meyab (1848)
28tc (26, 32, 34)
10 (8)
T. aureum (Lam.) Greuter, M.V.Agab. & Wagenitz
Urmia: Suluk Waterfall (1861)
6 and 10t (3, 4, 5)
T. heimerlii (Nabělek) Parsa
Urmia: Sero road, Golsheykhan (1227)
4t (2, 3, 5, 6)
4 and 6
T. oligocephalum (DC.) Sch.Bip.
Urmia: Chaldoran (1914)
6t (4)
T. oligocephalum (DC.) Sch.Bip.
Urmia: Naghadeh (1868)
22t(10, 12, 14, 20, 24)
12 (8, 10)
T. oligocephalum (DC.) Sch.Bip.
Urmia: Mamakan (1911)
10t (8, 9)
T. fisherae Aitch. & Hemsley.
Kerman Mehr mountain, north and east slopes (1916)
30 tc (8, 14, 22, 24, 28)
10 (5, 7, 6, 12, 15)
T. hololeucum (Bornm.) Podl.
Mazandaran: Pole Zangoleh road (1791)
14 and 16t (18, 20, 22)
T. joharchii Sonboli & Kaz.Osaloo
Khorasan, Chenaran, (1620)
24itc (32 and 36)
6 (5, 8)
T. kotschyi (Boiss.) Grierson
Urmia, Anhar road, Suluk (1129)
24tc (20, 28, 32, 34)
T. kotschyi (Boiss.) Grierson
Tabriz: Mishodagh (1339)
44tc (28, 32, 42, 44, 48)
T. kotschyi (Boiss.) Grierson
Zanjan: Ghidar (1419)
18tc (20, 22, 26)
T. parthenifolium (Willd.) Sch.Bip.
Urmia: Suluk Waterfall (1127)
T. parthenium (L.) Sch.Bip.
Tehran: Tochal (1483)
2t (3, 4)
2 (3, 4)
T. parthenium (L.) Sch.Bip.
Tehran: Shahid Beheshti University, agricultural field of research. Cultivated (1633)
14tc (8, 10)
T. parthenium (L.) Sch.Bip.
Hamadan: Dare Morad Beig (1903)
3t (2,4)
2(3, 4)
T. persicum (Boiss.) Mozaff.
Chahar Mahal & Bakhtiari: Sabz Kuh (1502)
T. pinnatum Boiss.
Hamadan: Asad Abad (1895)
T. pinnatum Boiss.
Hamadan: Malayer (1896)
4t (6)
T. pinnatum Boiss.
Hamadan: Razan (1894)
6t (3, 4, 5)
4 and 6 (8)
T. polycephalum Sch.Bip. ssp. argyrophyllum (K.Koch) Podlech
Urmia: Meshkin Shahr (1884)
6t (5, 7, 8, 10)
6 (7, 8)
T. polycephalum Sch.Bip. ssp. argyrophyllum (K.Koch) Podlech
Urmia: Ghasemloo Valley (1866)
8 and 10t (5, 6, 13)
12 (14)
T. polycephalum Sch.Bip. ssp. argyrophyllum (K.Koch) Podlech
Urmia: Oshnaviyeh (1867)
6, 10, 20 and 24t
14 (10, 11, 12, 13, 15)
T. polycephalum Sch.Bip. ssp. argyrophyllum (K.Koch) Podlech
Urmia: Marand (1856)
32 and 36t (8, 20)
12 (14)
T. polycephalum Sch.Bip.ssp. azerbaijanicum Podlech
Urmia: Ghishchi (1212)
16t (8, 14)
T. polycephalum Sch.Bip. ssp. duderanum (Boiss.) Podlech
Mazandaran: Pole Zangoleh road (1795)
14tc (18, 20, 22, 24)
12 (11)
T. polycephalum Sch.Bip. ssp. farsicum Podlech
Hamadan: Kabudar Ahang (1901)
22 and 24t (18, 20, 26)
13 (14, 17)
T. polycephalum Sch.Bip. ssp. heterophyllum (Boiss.) Podlech
Mazandaran: Pole Zangoleh road (1797)
18 and 22t (16, 18, 20, 30, 32)
12 (9, 10, 11)
T. polycephalum Sch.Bip.ssp. heterophyllum (Boiss.) Podlech
Hamadan: Asad Abad (1899)
8t (10, 12, 14, 16)
18 (15, 16, 17)
T. sonbolii Mozaff.
(305) Urmia: Takab
5t (4, 6, 8)
T. tabrisianum (Boiss.) Sosn. & Takht.
Urmia: Ahar (1905)
20 and 26t (14, 16, 27)
14 and 16 (10, 12)
T. tabrisianum (Boiss.) Sosn. & Takht.
Urmia: Ahar (1906)
50t (28, 40)
16 (14, 15, 26)
T. tenuisectum (Boiss.) Podl.
Tehran: Damavand (863)
32, 34 and 46tc
6 (8, 10)
T. tenuissimum (Trautv.) Grossh.
Urmia: Jolfa (1855)
16 and 22 tc
All populations are native to Iran. (1) ploidy; (2) chromosome number; (3) genome size in pg; Petunia hybrida ‘PxPC6’ (2C = 2.85 pg), (*) Pisum sativum ‘Express Long’ (2C = 8.37 pg), and (**) Triticum aestivum ‘Chinese Spring’ (2C = 30.9 pg) were used as internal standards; (4) genome size in Mbp (1 pg = 978 Mbp); (5) standard deviation; (6) monoploid genome size; (7) half peak coefficient of variation for each population; (8) most commonly found number of CMA+ bands, together with the most usual position found for them (I = interstitial, t = terminal or subterminal, c = centromeric or pericentromeric); in brackets, other numbers of CMA+ bands found; (9) most commonly found number of rDNA sites; in brackets other numbers of rDNA sites found (position of rDNA sites is always terminal or subterminal). AThe expected number for a pentaploid would be 2n = 45 but there is an already described hypoaneuploidy for this taxon, sometimes presenting a B chromosome (2n = 44 + 1B, [105]); Btwo to three B-chromosomes occasionally found

Genome size

Table 1 presents holoploid genome size data (2C), together with other karyological features of the studied species, as well as information on some closely related taxa for comparison. We analysed 38 populations of 20 species and five subspecies of Tanacetum, including ploidy from 2x to 6x. Genome sizes (2C) ranged from 3.84 pg (belonging to one of the diploid populations of T. parthenium) to 24.87 pg (from a tetraploid population of T. pinnatum Boiss.), an overall 6.47-fold range, and a 3.29-fold range at the diploid level. Mean 2C at diploid level is 8.05 pg. The low Half Peak Coefficient of Variation (HPCV) mean value (2.29 %) indicates good quality of the flow cytometric assessments. Fluorescence histograms from the flow cytometer are presented in Fig. 1 to illustrate the accuracy of measurements with all internal standards used.
Fig. 1
Fluorescence histograms of the genome size assessments of (a) T. heimerlii 2x population (2) with Petunia hybrida (1) as internal standard, (b) T. pinnatum 4x population (4) with Pisum sativum (3) as internal standard and (c) T. polycephalum ssp. heterophyllum 6x population (5) with Triticum aestivum (6) as internal standard
We found intraspecific genome size differences in most cases in which several populations were assessed, reaching 22.18 % in the triploid T. kotschyi, 16.04 % in the diploid T. parthenium, 9.43 % in the tetraploid populations of T. aureum, 8.10 % in the tetraploid T. polycephalum Sch. Bip., 1.89 % in the hexaploid T. tabrisianum (Boiss.) Sons. & Takht., and negligible variability (<0.1 %) among diploid T. pinnatum populations.
Genome size (2C) and total karyotype length (TKL) were significantly (p < 0.0001) and positively correlated with ploidy, but monoploid genome size (1Cx) did not decrease with ploidy. Nevertheless, when data of the same species at different ploidy levels was compared, there was a trend to genome downsizing i.e. reduction of monoploid genome size in T. polycephalum and T. pinnatum, whose 4× and 6× polyploids present, respectively, 6.07 % and 17.96 % less genome size than expected from the genome size in their diploid populations. In addition, genome size is positively correlated with TKL (p = 0.003), with the number of rDNA signals (p < 0.0001) and with pollen morphometric characters such as polar axis (p = 0.03) and equatorial diameter (p = 0.02). Species with different compound inflorescences have significantly different genome sizes (p = 0.009); species with solitary capitula have the smallest genome compared to species presenting corymbs of capitula, which have the greatest amounts of DNA (5.54 pg vs 13.2 pg at the diploid level).

GC-rich regions

Table 1 shows the results of fluorochrome banding with chromomycin and FISH assays, and Figs. 2 and 3 present selected representative Tanacetum metaphases. For the sake of clarity, only three chromosomal locations have been considered both for chromomycin A3 (CMA) and rDNA signals, following the treatment used in the These are: (peri)centromeric, interstitial and (sub)terminal. Results of chromomycin banding, which stains GC-rich DNA portions, are highly variable within and between Tanacetum species and even among individuals in some cases. In only four species is the number of bands always constant (the diploids T. parthenifolium Sch. Bip., T. persicum (Boiss.) Mozaff., T. pinnatum and T. budjnurdense (Rech.f.) Tzvelev) and low — four, see picture of T. pinnatum (Fig. 2a). However, from a minimum of two CMA+ bands in a wild population of the diploid T. parthenium (Fig. 3g) to a maximum of 66 bands for the diploid T. archibaldii Podlech (Fig. 3a) there are myriad variations. In most cases, however, there is a considerable range of variability within a species. The preferred position is usually (sub)terminal, and sometimes detached or terminal decondensed DNA (probably rDNA) is clearly seen with this staining (see Fig. 3k). Several species also present pericentromeric bands, and in two species (T. archibaldii and T. joharchii), several intercalary signals are also visible (Fig. 3a and 3k). Pericentromeric (and to a lesser extent, intercalary) bands appear in species that already present a high number of GC-rich bands.
Fig. 2
Chromomycin A3-positive (CMA+) and FISH images of the most commonly found metaphases of representative species of each ploidy level in Tanacetum. CMA+ bands are marked yellow, 26S-5S rDNA signals, marked orange in images. CMA+ positive bands are marked yellow, 26S-5S rDNA signals, are marked red-green in the schematic representation of chromosomes. (a, b, c) Tanacetum pinnatum, 2x population (Asad Abad, 1895) showing four CMA+ and four rDNA signals; (d, e, f) T. kotschyii, 3x population (Urmia, 1129) showing up to 24 CMA and six rDNA signals; large CMA+ bands indicated with asterisks; (g, h, i) T. oligocephalum, 4x population (Mamakan, 1911), showing 10 CMA+ and 10 rDNA signals; large CMA+ bands indicated with asterisks and faint bands indicated with arrows; (j, k, l) T. fisherae, 5x population, showing up to 30 CMA+ and 10 rDNA signals; large rDNA signals indicated with asterisks; (m, n, o) T. tabrisianum 6x population (Ahar, 1906), showing up to 50 CMA+ and 16 rDNA signals; large rDNA signals indicated with asterisks. Scale bars = 10 μm
Fig. 3
Chromomycin A3-positive (CMA+) FISH images of cytogenetically variable Tanacetum species, in which CMA+ bands are marked yellow, 26S-5S rDNA signals and marked orange. (a, b) T. archibaldii (2x) with 56 CMA signals (asterisks indicate interacalary CMA+ bands) and with 4 rDNA signals; (c, d) T. balsamita, 2x, with 40 CMA+ signals (many of them pericentromeric, indicated with asterisks) and with four rDNA signals – a slightly decondensed rDNA is indicated with an arrow; cultivated (e, f) and wild (g,h) T. parthenium (from Shahid Beheshti University, 1633 and Tochal, 1483, respectively), both 2x with 14 and six CMA+ and six and two rDNA signals observed, respectively; (i, j) T. kotschyi (Tabriz, Mishodagh, 1339), 3x, with 44 CMA+ signals and six rDNA signals and (k, l) T. joharchii, 3x, with 24 CMA and six rDNA signals; note faint or interstitial CMA+ bands indicated with asterisks and decondensed rDNAs indicated with arrows in both pictures. Scale bars = 10 μm
Several taxa of different ploidy (different populations from T. aureum, T. heimerlii (Nábělek) Farsa, T. parthenium, T. polycephalum Sch. Bip. subsp. argyrophyllum (K.Koch) Podlech, T. pinnatum, T. sonbolii Mozaff. and T. tabrisianum) show odd numbers of bands in different individuals (Table 1). Intensity and size differences of chromomycin signals are clearly visible in several species, such as T. kotschyi (Fig. 2d), T. oligocephalum (DC.) Sch. Bip. (Fig. 2g), T. balsamita (Fig. 3c) and T. joharchii (Fig. 3k).
There is no significant relationship between ploidy and the most commonly found number of signals for a given species, nor with genome size. In addition, the number of GC-rich bands is positively correlated with the altitude at which species occur, considering all taxa (p = 0.04) and only diploids (p = 0.006).

rDNA loci

The FISH assays of a large sample representing genus Tanacetum show a totally homogeneous L-type organisation of ribosomal RNA genes. The number of signals within a species (even within a population) and between species at the same ploidy is usually heterogeneous although not as heterogeneous as the number of CMA+ bands. The minimum number of signals found was two (one locus) for one population of T. parthenium and the maximum was 26 (13 loci) for some individuals of one population of T. tabrisianum (although most T. tabrisianum had eight loci, see Fig. 2n). In all cases, rDNA signals occupied terminal or subterminal positions, always coincidental with CMA+ signals, and sometimes appearing as decondensed (as T. joharchii in Fig. 3d, l arrows). Species such as T. fisherae and T. tabrisianum (Fig. 2k, n, asterisks), presented locus size differences, but in general, this was homogeneous. The number of rDNA signals was positively and significantly correlated with ploidy and genome size (p < 0.0001 for both), but there was no reduction in number of loci, as the number of signals per haploid genome did not diminish significantly with increasing ploidy. However, a reduction in the number of signals was detected in individual polyploid series for T. pinnatum and three out of four of T. polycephalum. In all other cases there was additivity; that is, the tetraploid had exactly twice as many signals as the diploid, except in the case of one tetraploid T. polycephalum population, in which there was upsizing by one locus.
The heterogeneity in the number of signals for a given species (that is, the different number of rDNA loci that could be found in metaphases coming from the same species) was positively correlated with ploidy (p < 0.0001) which means that with increasing ploidy there was a tendency to instability in the number of rDNA signals. In particular, the hypoaneuploid T. fisherae (2n = 5x = 44) and T. polycephalum var. argyrophyllum (2n = 4x = 35) were the most unstable with respect to the number of rDNA signals.

Phylogenetic relationships among species and ancestral characters

Statistical analyses at the genus level should consider phylogenetic relationships among taxa to be as unbiased as possible. However, due to lack of enough data, these comparisons could not be done in most cases. Still, we detected significant and positive correlations using the phylogenetic generalised least squares method (PGLS) between genome size (2C), ploidy, and number of rDNA signals (p < 0.0001), i.e. all parameters increase/decrease in concert. The reconstruction of character evolution into the phylogeny (Fig. 4), based on diploid taxa, provides ancestral 2C values ranging from 7.98 to 8.84 pg, from 10 to 13 for CMA+ bands, and from 4 to 6 rDNA signals for Tanacetum species.
Fig. 4
Ancestral state reconstruction of number of rDNA signals (left) and genome size (right) for diploid Tanacetum taxa. The model of reconstruction was Parsimony as implemented in Mesquite (v.3.02), and ancestral state reconstruction was estimated using the 50 % majority-rule consensus topology obtained by Bayesian inference phylogenetic analysis of the internal transcribed spacer 1 (ITS1), ITS2 and trnH-psbA data sequence. The Bayesian clade-credibility values (posterior probability > 0.5) are given above branches. Schematic representation of chromosomes with the most commonly found numbers of rDNA signals and bars that depict genome sizes (2C values) with a red line indicating the mean 2C value at the diploid level. (*) Tanacetum polycephalum ssp. argyrophyllum


All species investigated present x = 9 as the basic chromosome number confirming previous research [20, 23]. In contrast to other Anthemideae, in which other basic chromosome numbers have been found (e.g. Artemisia presents x = 7, 8, 9, 10, 11; Pentzia Thunb., x = 7, 8, 9, Lasiospermum Fisch., x = 9, 10 [40]) x = 9 it is the only found in Tanacetum until present [41].
To our knowledge, genome size was available for only four species of the genus, the diploid T. vulgare (mean 2C = 8.85 pg, [37]), a tetraploid population of T. cinerariifolium (Trevir.) Sch. Bip. (2C = 14.53 pg, [38]) and some hexaploid populations of T. balsamita and T. corymbosum (L.) Sch. Bip. (2C = 21.44 pg and 2C = 19.95 pg, respectively, [39]). Therefore this research contributes new genome sizes for all species and subspecies studied here (with the exception of T. balsamita), representing approximately 11 % of the recognised species of the genus. The amount of nuclear DNA is mostly intermediate in Tanacetum. According to the genome size categories in plants established by [42], three of the 20 species we studied (17.65 %) have small genome sizes (2.8 ≤ 2C < 7 pg), whereas the remaining have intermediate genome sizes (7 ≤ 2C < 28 pg), including all ploidy levels. Mean genome size of the diploid taxa studied (8.35 pg) was coincidental with the mean of the tribe Anthemideae (8.30 pg) and of the family Asteraceae (2C = 8.20 pg), according to data from the Genome Size in Asteraceae Database ( Closely related diploid genera, such as Artemisia, have similar mean genome sizes (2C = 7.75 pg) whereas the majority of diploid Tanacetum allies present remarkably lower mean 2C values (2C = 5.9 pg for Achillea, 2C = 6.4 pg for Anacyclus L., 2C = 5.12 for Anthemis, 2C = 5.71 for Matricaria L., 2C = 5.13 for Tripleurospermum). The comparatively larger mean genome size of Tanacetum could be because our sample lacks annual representatives (as does most of the genus) which, quite often — though not always — tend to present lower genome sizes than their counterparts [43].

Genome downsizing and polyploidy in Tanacetum

Polyploidy and hybridisation are important evolutionary forces shaping plant genomes and underlying the huge angiosperm diversity. Both can confer evolutionary advantages [44, 45, 46] attributed to the plasticity of plant genomes and to increased genetic variability, generating individuals capable of exploiting new niches [47]. Polyploidy is linked to numerous epigenetic/genomic changes such as chromosome rearrangements, transposable element mobilisation, gene silencing or genome downsizing [48, 49, 50]. Certainly, genome downsizing would be a widespread biological response to polyploidisation [51]. This may lead to diploidisation of the polyploid genome [52, 53, 54]. There is no evidence of genome downsizing across Tanacetum ploidy levels. However, there are genome size trends within separately polyploid series of particular species. Tetraploid T. pinnatum presents up to 6.07 % lower 1Cx than expected from the 1Cx of the diploid populations, and hexaploid and tetraploid T. polycephalum present, respectively, 17.96 % and 4.28 % lower 1Cx than expected from the 1Cx of the diploid population. This is consistent with previous observations of more pronounced genome downsizing with higher ploidy [30, 45, 55, 56, 57]. Recent work [57] has demonstrated erosion of low copy-number repetitive DNA in allopolyploids, sometimes counteracted by expansion of a few repeat types. Age and genomic similarity of the parental genome donors of the polyploids play a role in the extent of genome size change with polyploidy [56] and a deeper understanding of the likely hybridogenic origin of some of the Tanacetum polyploids studied would allow more robust hypotheses on the balancing genomic processes these taxa may have undergone.

Small genome size and invasiveness

Tanacetum parthenium appears listed in several countries as an invasive weed [58, 59]. Its genome size was the smallest obtained in our study (three populations were analysed whose mean was 2C = 4.12 pg). This is consistent with previous findings [60], which detected that many weeds (including those in family Asteraceae) had smaller amounts of DNA than closely related (non-weedy) species. This relationship is supported by recent work [61, 62]. The other species with small genome sizes in our sample (T. parthenifolium and T. persicum) have not, however, been recorded as weeds. Therefore a small genome size (particularly, smaller than that of closely related species) is a necessary but not sufficient condition for a plant to become a weed. A recent review [63] concluded that invasive species were characterised by small and very small genomes, yet this conclusion may be biased by the general trend of land plants to small genome sizes as a whole [42].

Intraspecific instability and massive amplification of GC-rich DNA occur in several Tanacetum species

We found that ribosomal DNA is always CMA+ in Tanacetum (see Discussion on rDNA loci below), common to other studies [45, 64, 65] although exceptions are found [66]. For most of the studied populations, the number of CMA+ bands significantly exceeded that of rDNA signals and there was no apparent relationship with ploidy or with genome size (Table 1). The number of CMA+ bands is neither stable within a species nor within a population. The presence of odd and of non-homologous signals was occasionally observed, for example in T. aureum and in T. oligocephalum (Table 1), where a single chromosome with two CMA+ bands at each end was observed instead of the two identical chromosomes expected. Odd ploidy species, such as T. fisherae (5x) and T. kotschyi (3x), were particularly labile with respect to the number of CMA+ bands. However, the greatest variability in number of CMA+ bands corresponded to the diploid T. balsamita, in which sevendifferent numbers of signals were found (Table 1 and Fig. 3c). Such instability in the number of GC-rich bands was unexpected and has seldom been reported. Only the highly variable CMA+ banding pattern previously found in Citrus L. and close genera [67] is similar to the variability found in Tanacetum, probably as a consequence of amplification or reduction in satellite sequences known to be particularly GC-rich [68]. It is possible that some as yet undescribed satellite DNA type, specific to Tanacetum, is in part responsible for these karyotype features.
Another characteristic of the CMA+ banding pattern in Tanacetum was the striking number of signals found in certain species, particularly in diploid taxa (Table 1, Fig. 3a, 3c, 3i, 3k). This contrasts with previous work on genus Artemisia [69, 70], in which a large number of CMA+ bands was only detected in some polyploids, while the only CMA+ bands in diploids were those exactly corresponding to rDNA loci. In other Asteraceae genera, such as Cheirolophus Cass., a large number of CMA+ bands was also reported, mostly coincidental with 35S rDNA signals [71]; this was also the case for Filifolium [72]. In Centaurea L. [73] the number of CMA+ bands was the same as or smaller than the number of 35S rDNA signals, while in some Xeranthemum L. [74], Galinsoga Ruiz & Pav. and Chaptalia Vent. [75], few additional GC-rich bands were observed.
While most bands are in terminal position, pericentromeric GC-rich heterochromatin was detected in several species, some of them closely related, such as T. polycephalum, T. aureum and T. canescens DC. on one hand (Table 1), and T. fisherae (Fig. 2j), T. kotschyi (Fig. 2d), T. tenuisectum Sch.Bip. and T. joharchii (Fig. 3k) on the other. In fact, in Arabidopsis thaliana (L.) Heynh., centromeres are one of the most GC-rich genomic regions [76]. Differences in total GC% among eukaryotes are largely driven by the composition of non-coding DNA of which retrotransposons are the most abundant (for example, LTR Huck elements contain more than 60 % GC, [77]). Possibly, some centromere-specific LTR could have undergone amplification in these closely related Tanacetum genomes.
What can this fluctuating distribution of CMA+ bands mean, and what are the implications? It is feasible that a specific satellite and/or retroelement family may be expanded or contracted in Tanacetum genomes. Although the number and the distribution of CMA+ bands are thought to be relatively constant features of plant karyotypes [24, 70], our results strongly argue against this view, since variability was found even within a population. In addition, there were few evident ecological or geographic patterns in Tanacetum, that is, few significant relationships were found between the number or variability of GC-rich signals and geographical distribution, weedy behaviour, or soil features. The only significant association is with altitude: Tanacetum species living at higher altitudes tend to present more GC-rich DNA. In line with this hypothesis, [78] found a large number of heterochromatic bands (both GC- and AT-rich) in species from the Asteraceae genus Myopordon Boiss. inhabiting high mountain areas. These authors related the development of such heterochromatic bands in terminal regions with an adaptation to protect telomere function from UV radiation, a major genome-damaging agent, particularly in high mountains. Heterochromatin expansion in terminal regions (as in Tanacetum) has also been suggested to enhance chromosomal pairing during cell division [79].

Genomic organisation of rDNA and typical distribution pattern of Tanacetum

Our cytogenetic study confirmed that both the 5S and the 35S rRNA genes are co-localised (L-type arrangement) in all chromosomes. Such organisation was found in Artemisia for the first time in higher plants [36], and subsequently inferred for at least 25 % of Asteraceae species [25]. In the latter study, Southern blot hybridisation was performed on a sample of T. parthenium, and the profile obtained also suggested L-type organisation for its rDNA. Prior to our study, the only evidence of this particular rDNA organisation directly in chromosomes was from T. achilleifolium and T. parthenium [35]. Curiously, these authors found one unlinked 5S locus additional to two regular L-type loci in T. achilleifolium, while T. parthenium showed L-type arrangement in all loci. Within the sample studied we could not find a single species with unhomogenised rDNA (i.e. that both kinds of rDNA arrangement, linked and separated, were present in the same species), since both rDNA probes invariably overlapped in all loci. Nevertheless, possible incomplete homogenisation of rRNA genes may also be present in other close genera such as Achillea and Chrysanthemum L. [72, 80]. Besides, in some metaphases decondensed rDNA signals are detected. These probably correspond to active nucleolar organizer regions (NORs), i.e. rDNA that is being actively transcribed, visible in T. balsamita (Fig. 3d, one signal) and in T. joharchi (Fig. 3l, two signals). Decondensed rDNA, however, is not always detected during metaphase.

Unexpected variation in number of rDNA loci

The number of rDNA signals was always smaller and less variable than that of CMA+ bands, as found previously in other closely related species (in Artemisia, [45, 70]) and even in other families (genus Ipomoea from Convolvulaceae, [81]). In particular, the most common number of rDNA loci at the diploid (with two to three loci) and tetraploid (with five to six loci) levels was relatively constant and consistent with previous data for Tanacetum [35, 82] or for the closely related genera Matricaria and Tripleurospermum [25]. However, taxa with odd, higher ploidy or aneuploid levels often displayed higher intraspecific polymorphism in the number of signals. Of these, the hypoaneuploid population of T. polycephalum var. argyrophyllum was particularly striking, since metaphases with 10, 11, 12, 13, 14 and 15 rDNA signals were observed; the hypoaneuploid T. fisherae (2n = 5x = 44) showed a similar condition (Table 1). Thus, processes of hypoaneuploidy could affect genomic stability producing this variation in number of loci.
Although it would be expected that the number of signals remain relatively constant for a given species, cases of intraspecific polymorphism in the number of signals are increasingly reported. As for Tanacetum, diversity in the number of rDNA signals for a given species has been found in Fragaria vesca L. [26] and in Phaseolus vulgaris L. [83], for example. However, what is exceptional in Tanacetum is that these polymorphisms happen even at the population level and, albeit very rarely, sometimes within the same individual. All this, together with the unexceptional situation of odd numbers of signals in many taxa (which otherwise is rare) illustrates how dynamic Tanacetum genomes are.
Given these fluctuations, the constantly terminal position of rDNA signals in all the species studied could be considered surprising. However, this is so in most plants: [84] argued that there seems to be a strong positive selection favouring the location of 35S rDNA at chromosome ends, probably as a result of homologous recombination constraints.
As with the number of CMA+ bands, there was no global reduction in the number of signals per haploid genome with increasing ploidy. Similarly, the number of rDNA loci did not show any apparent relationship with genome size.
Our analyses have allowed us to distinguish some interesting relationships between several of the traits studied. As others have found [85, 86] morphological data regarding pollen size are tightly linked with genome size in Tanacetum, i.e. pollen size reflects genome size in this genus. In addition, species of Tanacetum with solitary capitula have smaller genome sizes than those with capitula organised in complex inflorescences. It is known that sometimes polyploids tend to present larger reproductive organs and more flowers per inflorescence than their diploid relatives [87], but few studies have approached the relationship of genome size or polyploidy with natural patterns, such as inflorescence architecture [88]. Suggested that the shift in inflorescence phyllotaxis from spiral to distichous would have occurred at the same time as the expansion of genome size characterising several groups of grasses [89], though admitting no clear reason why genome size as such should affect inflorescence architecture.
In addition, the reconstruction of ancestral cytogenetic traits brings evidence that these characters have followed increases and decreases during evolution in Tanacetum (Fig. 4). In general, it seems that genome size and the number of rDNA loci have increased, while the number of CMA+ bands has decreased in most present taxa. Few studies have specifically approached the evolution of cytogenetic traits within a temporal and phylogenetic perspective and, while events favouring increase in genome size and number of rDNA signals during evolution have been detected [56], there is no discernible pattern in the direction of these changes. For example, [90] found a decrease in number of rDNA loci during the evolution of Hypochaeris L. The overall decrease of GC-rich DNA could also respond to depletion of certain repeated DNA sequences during evolution in Tanacetum.


This work is the first extensive cytogenetic report on Tanacetum species. We have confirmed linkage of both rDNAs in all chromosomal loci. Tanacetum stands out as variable, particularly in the number of rDNA sites and CMA+ bands. These vary widely even within a given population. In particular, aneuploid and odd ploidy taxa appear more unstable. The observed intrapopulation differences are likely a reflection of genomic differentiation which could complement further population biology studies. Besides, the number of GC-rich DNA bands found in certain species is striking and deserves more study. A possible cause is the amplification of repeat families or TEs in these species compared to others showing utterly different profiles. Polyploidy and aneuploidy are important evolutionary forces in this genus. Several of the studied populations present spontaneous mixed ploidy, another sign of its current genomic dynamism.
It is difficult to set general patterns in the evolution of genome size, number of rDNA loci or heterochromatin in plants. Yet, studies such as ours contribute to the knowledge of these cytogenetic features at a larger scale. Finally, the particularly labile cytogenetic scenario observed in Tanacetum is uncommon and has been seldom reported. Both chromosomal markers (rDNA loci and GC-rich bands) tend to be relatively constant at the species level, a feature that has allowed their use in biosystematics. Still, even at the population level, these traits can be variable in Tanacetum and this variation is better understood considering evolutionary relationships between species.


Plant materials

Seeds of 38 populations of Tanacetum species were collected from the wild for molecular cytogenetics and genome size assessments (Table 1). Specimen vouchers of the studied materials have been deposited at the Medicinal Plants and Drug Research Institute Herbarium (MPH) of the Shahid Beheshti University, Tehran.

Chromosome preparations

Root tip meristems were obtained by germinating achenes on moist filter paper in Petri dishes at room temperature in the dark. They were pre-treated with 2 mM 8-hydroxyquinoline at room temperature for 3–3.5 h. Subsequently, the material was fixed in 3:1 v/v absolute ethanol:glacial acetic acid and stored at 4 °C for 24 h, and then stored in 70 % ethanol at 4 °C until use. For fluorochrome banding and fluorescence in situ hybridisation (FISH), the chromosome spreads were obtained using the air-drying technique of [91], with modifications. Fixed root tips were washed three times in distilled water with shaking and later in citrate buffer (0.01 M citric acid-sodium citrate, pH 4.6) for 30 min, excised and incubated for 20–35 min at 37 °C in an enzymatic mixture [4 % cellulase Onozuka R10 (Yakult Honsha), 1 % pectolyase Y23 (Sigma) and 4 % hemicellulase (Sigma)]. Digested root tips were placed on a slide, excess enzymatic solution was removed and protoplasts were obtained by applying gentle pressure in a drop of 45 % acetic acid. The metaphase plates were evaluated using a phase contrast microscope and slides were frozen for at least 24 h at -80 °C. Later, the coverslip was quickly removed, the slide rinsed with absolute ethanol and then air dried for at least two days protected from dust.

Fluorochrome banding

In order to reveal GC-rich bands, the chromosomes were stained with the fluorochrome chromomycin A3 (CMA), according to [24, 92] with slight modifications. The slides were incubated in McIlvaine buffer pH 7, MgSO4 (0.1 g/L in McIlvaine buffer, pH 7) for 15 min, stained with CMA3 (0.2 mg/ml in McIlvaine buffer pH 7 MgSO4) for 90 min in the dark, rinsed in McIlvaine buffer pH 7, and counterstained with methyl green (0.1 % in McIlvaine buffer pH 5.5) for 10 min; rinsed in McIlvaine buffer pH 5.5, dried briefly at room temperature, also in the dark, and mounted in two small drops of Citifluor AF1 (glycerol/PBS solution).

Labelling of rDNA probes and FISH

For hybridisation experiments we mostly used the same slides as for fluorochrome banding with CMA after destaining with fixative, dehydration through an ethanol series (70 %, 90 % and 100 %) and drying for two days. The probe used for 35S rDNA localisation was a plasmid carrying a 2.5 kb insert of 26S rRNA gene from Lycopersicum esculentum Mill. labelled with Cy3 (Jena Biosciences) using the Nick Translation Mix (Roche). The 5S rDNA probe was an approximately 0.7 kb-long trimer of 5S rRNA genes from Artemisia tridentata Nutt., labelled with Green dUTP using the Nick Translation Mix (Abbott Molecular). This probe contained three units of the 5S rRNA gene (120 bp) and the non-coding intergenic spacers (about 290 bp). Both probes have been used following previous research [25, 65]. FISH was carried out according to [24] with slight modifications. Slides were incubated in 100 μg/ml DNase-free RNase in 2 × SSC (0.03 M sodium citrate and 0.3 M sodium chloride) for 1 h at 37 °C, washed in 2xSSC three times for 5 min with slow shaking, rinsed in 0.01 N HCl for 2 min and incubated in pepsin (0.1 mg/ml in 0.01 N HCl) for 15 min at 37 °C, washed in 2xSSC for 5 min twice, dehydrated in an ethanol series (70 %, 90 % and 100 %, for 3 min in each) and air dried. The probe hybridisation mixture contained 25–100 ng/μl rDNA probes, formamide, 50 % (w/v) dextran sulphate, and 20 × SSC. This was denatured at 75 °C for 10 min and chilled on ice for 5 min. A volume of 30 μl was loaded onto slides and covered with plastic coverslips. The preparations were denatured at 75 °C for 10 min and transferred at 55 °C for 5 min. Hybridisation was carried out for more than 18 h at 37 °C in a humidified chamber. Following hybridisation, the slides were washed with shaking in 2 × SSC, 0.1 × SSC and 2 × SSC at 42 °C for 5 min twice each, and then once in 2 × SSC for 5 min, once in 4 × SSCT for 7 min, briefly rinsed in 1 × PBS and dried.
Samples were counterstained with Vectashield (Vector Laboratories, Inc., Burlingame, CA, USA), a mounting medium containing 500 ng/μl of 4’,6-diamidino-2-phenylindole (DAPI). The fluorescence signals were analysed and photographed using a digital camera (AxioCam HRm, Zeiss) coupled to a Zeiss Axioplan microscope; images were analysed with Axiovision HR Rev3, version 4.8 (Zeiss) and processed for colour balance, contrast and brightness uniformity in Adobe Photoshop. A minimum of 10 metaphase plates per population were analysed. Graphics were assembled with PowerPoint 2010 (Microsoft). The data were submitted to the Plant rDNA database, a database compiling information on rDNA signal number, position and organisation [93, 94].

Flow cytometric measurements

For flow cytometric measurements of leaf tissue, seedlings were obtained from seeds grown in pots in the greenhouse of the Faculty of Pharmacy, University of Barcelona. Five individuals per population of the different Tanacetum species were studied, and of these, two samples of each were individually processed. Petunia hybrida Vilm. ‘PxPc6’ (2C = 2.85 pg), Pisum sativum L. ‘Express Long’ (2C = 8.37 pg) and Triticum aestivum L. ‘Chinese Spring’ (2C = 30.9 pg) from [95] were used as the internal standards. Fresh leaf tissue for the standard and the target species were chopped up together in 600 μl of LB01 buffer (8 % Triton X-100; [96]) supplemented with 100 μg/ml ribonuclease A (RNase A, Boehringer, Meylan, France) and stained with 36 μl of 1 mg/ml propidium iodide (Sigma-Aldrich, Alcobendas, Madrid, 60 μg/ml) to a final concentration of 60 μg/ml, and kept on ice for 20 min. The fluorescence measurements were performed using an Epics XL flow cytometer (Coulter Corporation, Miami, FL, USA) at the Centres Científics i Tecnològics, University of Barcelona. More details about the method are in [55]. The data have been submitted to the GSAD (Genome Size in Asteraceae Database) [97, 98].

Phylogenetic analyses and reconstruction of character evolution

The nuclear ITS1 + ITS2 and chloroplast trnH-psbA sequences (listed in Additional file 1) were edited by BioEdit v. [99] followed by manual adjustment. Artemisia taxa were considered as outgroups [3]. All taxa used for the phylogenetic analysis were diploid in order to avoid the effect of polyploidy in the estimated nuclear DNA contents, number of rDNA sites or GC-rich bands. Bayesian phylogenetic analysis was performed in MrBayes 3.1.2 [100] using a SYM + G model determined from jModeltest v. 2.1.3 [101] under the Akaike information criterion (AIC; [102]), to ascertain phylogenetic relationships. The Markov chain Monte Carlo (MCMC) sampling approach was used to calculate posterior probabilities (PPs). Four consecutive MCMC computations were run for 2,000,000 generations, with tree sampling every 100 generations. Data from the first 1000 generations were discarded as the burn-in period. PPs were estimated through the construction of a 50 % majority-rule consensus tree.
The ancestral character reconstructions (genome size, number of rDNA sites and number of CMA+ bands) were conducted using unordered maximum parsimony as implemented for continuous and meristic characters in Mesquite v. 3.02 software [103] using the 50 % majority-rule consensus tree resulting from the Bayesian inference analysis as the input tree file. The output trees were edited with Mesquite v. 3.02.

Statistical analyses

Analyses of regression, one-way ANOVA, X 2, Shapiro-Wilk test for normality and Barlett’s test for equality of variances were performed with RStudio, v.0.98.1078. In addition, the phylogenetic generalised least squares (PGLS) algorithm as implemented in the nlme package for R (Version 3.1-118) was used to analyse variation of genome size, number of rDNA sites and number of CMA+ bands in a phylogenetic context. Data on genome size and ribosomal DNA loci for the complementary and outgroup species were extracted from the Plant rDNA database [93].

Availability of supporting data

The data sets supporting the results of this article are available in the TreeBase repository, ID 17805 and [104].


Monoploid Genome Size
Holoploid Genome Size
Chromomycin A3
Fluorescent in situ Hybridisation
Nucleolar Organizer Region
Phylogenetic Generalised Least Squares
Ribosomal DNA (or ribosomal RNA genes)
Ribosomal RNA
Total Karyotype Length



This work was supported by the Dirección General de Investigación Científica y Técnica, Government of Spain (CGL2010-22234-C02-01 and 02/BOS and CGL2013-49097-C2-2-P) and the Generalitat de Catalunya, Government of Catalonia ("Ajuts a grups de recerca consolidats", 2009SGR0439 and 2014SGR514). SG benefitted from a Juan de la Cierva postdoctoral contract from the Ministry of Economy and Competitiveness, Government of Spain. NO benefitted from a fellowship from the Science, Research and Technology Ministry of Iran. Aleš Kovařík is acknowledged for supplying the rDNA probes and Spencer C. Brown for supplying internal standards for flow cytometry. We thank the technical staff of the Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, who helped us with fieldwork. Ricard Àlvarez, Jaume Comas, Chari González and Sonia Ruiz are acknowledged for their assistance in flow cytometric analyses. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through the Unit of Information Resources for Research (URICI).


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