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  • The developmental genetics of biological robustness
    C elegans is more sensitive to food starvation than changes in growth temperature Braendle and Felix 2008 The type of developmental errors also depends on the genetic background as different C elegans isolates respond differently to distinct perturbations Braendle and Felix 2008 Different tissues or cells within an organism may show different degrees of robustness For example despite the stereotypical nematode cell patterning vulval cell induction is more robust to stochastic noise than patterning of some other epithelial cells called seam cells Fig 1 This difference in robustness becomes even more pronounced when animals are grown at higher 25 C than standard 20 C temperature Fig 1 B It is of note that the more insensitive a system is it does not necessarily mean that it is a better model for robustness and depending on the biological question and approach a marginal degree of sensitivity may also be beneficial Robustness can also be studied theoretically using computational models that mimic a developmental process Again the phenotype of interest could be any developmental phenotype such as segmentation in flies bacterial chemotaxis or vulval cell fate patterning Barkai and Leibler 1997 von Dassow et al 2000 Ma et al 2006 Hoyos et al 2011 Computational models reinforce experimental results and make novel predictions about experimental outcomes For example leaf margin patterning in Arabidopsis thaliana relies on PINFORMED1 PIN1 mediated auxin maxima that appear sequentially along the margin of the growing leaf A computational model of leaf margin development predicted that the CUP SHAPED COTYLEDON2 CUC2 transcription factor stabilizes these maxima allowing the consistent generation of leaf margin serrations Bilsborough et al 2011 Mathematical models can have different degrees of complexity and abstraction They often include parameters such as half lives of mRNAs or binding rates whose values are randomly set as they are experimentally hard to quantify Robustness in this case refers to model output performance upon parameter change over a certain range For example a 40 parameter model reconstituting the known topology of the vulval gene network and explaining some key experimental results was challenged to a ten fold variation in model parameters It was shown that the model is robust to changes in many but not all parameters with one point of sensitivity being variation in EGF synthesis Hoyos et al 2011 Such theoretical approaches can generate novel experimental predictions about the underlying basis of developmental robustness In plants there is no single system on which scientists have focused efforts in order to quantify systematically robustness to various perturbations Similar to the nematode vulva quantifications can be performed for any developmental phenotype of interest such as organ number i e rosette leaf cauline leaf flower and branches organ or tissue size and architecture i e plant height hypocotyl length and rosette diameter or developmental timing traits i e flowering time Pouteau et al 2004 Fu et al 2009 Due to the plastic nature of plants most of these phenotypes are likely to be more responsive to perturbations and thus more variable than nematode cell patterning For example flowering time is sensitive to fluctuating environmental cues such as the seasonality of flowering times which is affected by the photoperiod light intensity and temperature changes acting through the circadian clock Samach and Coupland 2000 However some phenotypes in plants are thought to be quite invariable One example is the number of cotyledons which in angiosperms is either one or two with little variance and pleiocotyly is a developmental deviant pattern that is rare to find Conner and Agrawal 2005 Another example is petal or sepal number in arabidopsis that also shows very little variance Sieber et al 2007 We anticipate that advances in high throughput and automated phenotyping in plants will increase systematic and comparative quantification of developmental phenotypes in different genetic backgrounds and under various perturbations Tisne et al 2013 Yang et al 2013 Previous Section Next Section MEAN VS VARIANCE OF DEVELOPMENTAL TRAITS AND TWO SIDED PHENOTYPIC ERRORS Most of modern developmental biology is dominated by mean centric approaches where phenotypic averages are compared but details about phenotypic distributions in populations are usually ignored Geiler Samerotte et al 2013 However phenotypic distributions hide valuable information about the individuals of the population Phenotypic heterogeneity is in fact abundant even within genetically identical individuals Eldar et al 2009 Burga et al 2011 and in many cases this heterogeneity may be critical for cell differentiation patterning and species evolution Eldar and Elowitz 2010 Johnston and Desplan 2010 Balazsi et al 2011 For example bacterial heterogeneity in growth allows some cells to survive antibiotic treatment Bishop et al 2007 and growth heterogeneity also contributes to chemoresistance in tumours Roesch et al 2010 Sharma et al 2010 In plants considerable variability in growth has been found in the leaf epidermis and the meristem Elsner et al 2012 Kierzkowski et al 2012 Uyttewaal et al 2012 and cell heterogeneity and anisotropic growth were shown in another study to correlate with sepal growth Schiessl et al 2012 Cell to cell heterogeneities often arise from stochasticity in gene expression one example being photoreceptor choice of individual cone cells in mammals Jacobs 2009 or the monogenic expression of a single odorant receptor in olfactory sensory neurons Magklara and Lomvardas 2013 In arabidopsis cell to cell variation in FLOWERING LOCUS C FLC expression due to silencing may act as a way to register epigenetic memory of cold exposure Angel et al 2011 Analysing phenotypic distributions is very central to studying the genetics of robustness We argue here that distinguishing between gene effects on trait mean and variance is essential for studying robustness Fig 2 A In developmental genetic terms understanding the mechanisms of robustness entails identifying genes influencing phenotypic variance So let us consider as a phenotypic example the length of the primary root In contrast to the classical approach of isolating mutants showing a significant change in the average root length in the population a targeted robustness screen would rather focus on identifying factors specifically affecting root length variance without affecting the trait mean Fig 2 B The main reason for ideally selecting against changes in mean is that mutants tend to be generally more variable than the wild type as first postulated by Waddington 1942 so deviations from the wild type mean are commonly accompanied by changes in variance Genuine changes in variance are still possible when the trait mean is different However one would have to support that there is unexpectedly high variance for that given phenotypic mean This involves studying in detail the relationship between mean and variance which is phenotype dependent Levy and Siegal 2008 View larger version In this window In a new window Download as PowerPoint Slide Fig 2 Defining robustness genes and robustness to gene expression change A For any quantifiable phenotype classical developmental mutants are defined herein as those displacing the mean leading to either an increased or decreased mean whereas robustness mutants as those increasing the phenotypic variance without much effect on the mean In practice the most common case is mutants that do both at the same time sensu Waddington B An example showing a strict robustness defect using root length as the phenotype of interest C Examples illustrating the effect of changing gene expression levels on two different developmental phenotypes the nematodes vulval cell fate induction upper panel in response to EGF expression presented by the number of mRNA molecules quantified in situ showing that the induction index tolerates a change in expression ranging from 15 to 50 mRNA molecules Barkoulas et al 2013 Exposure to 15 mRNA molecules causes hypoinduction whereas expression of 50 mRNA molecules causes hyperinduction The lower panel illustrates the example of plant meristem size in response to change in expression level of CLAVATA3 CLV3 relative to the wild type 100 Meristem size is shown to tolerate a ten fold variation in CLV3 expression from 33 to 320 that of the wild type Muller et al 2006 An increase in trait variance coupled with changes in the mean can simply arise due to partial penetrance or variable expressivity of mutations and describing such defects in the light of robustness failure is a common problem in the recent literature For example in some robust systems with one example being the nematode vulva all mutations affecting developmental patterning show either partial penetrance or variable expressivity so any change in the mean is intrinsically linked with a change in phenotypic variance Barkoulas et al 2013 Moreover condition dependent effects on trait mean such as environmental sensitivity of mutations are indicative of genotype environment interactions but not good evidence for loss of developmental robustness Genotype environment interactions are indeed a common finding as demonstrated using the yeast knockout library in different culture environments Hillenmeyer et al 2008 It is conceivable that a certain perturbation may lead to a wider phenotypic distribution but would maintain the phenotypic mean if it results in two sided phenotypic errors within the population Going back to the root example discussed above a two sided phenotypic error would mean that some individuals respond to this perturbation by showing an increase and some others a decrease in root length within the same genotype Such two sided errors can be used as a proxy for developmental robustness defects in genetic screens and their developmental basis is interesting to understand in the context of loss of buffering However in some cases developmental constraints may only allow one sided phenotypic distributions Previous Section Next Section PROBING THE GENETICS OF TRAIT VARIANCE If developmental robustness evolves under natural selection there should be loci in the genome that act as suppressors of phenotypic variation As a consequence inducing mutations in these particular loci should increase phenotypic variance to a given perturbation Such trait variance controllers are often described in the literature as phenotypic capacitors Levy and Siegal 2008 or master regulators of robustness when several traits are affected Lempe et al 2013 From a developmental genetics point of view questions arising from the notion of having robustness genes include a whether these genes can be found frequently experimentally or are rare b what type of gene products they encode c whether they are specific to the trait and source of variation and d whether they harbour natural genetic variation that could explain within species differences in phenotypic robustness We discuss below how recent studies through a combination of classical genetic screens and quantitative genetics in different systems have just started providing some answers to these questions Deciphering the full spectrum and frequency of robustness genes would require unbiased and systematic screens to reveal all genetic factors shaping phenotypic variation As argued above these robustness screens should focus on discovering genes affecting specifically trait variance rather than phenotypic means Such screens have not yet been performed in plants or any other multicellular eukaryote but have been carried out in Saccharomyces cerevisiae Levy and Siegal 2008 Rinott et al 2011 Bauer et al 2015 There are a number of messages emerging from these studies in yeast First there are a large number of single genes that contribute to developmental robustness This was anticipated by early theoretical work showing extensive loss of robustness in simulations of single mutants of evolved robust networks Bergman and Siegal 2003 predicting that single gene disruption can be sufficient to result in a robustness breakdown More recently Levy and Siegal 2008 identified 300 yeast mutants in a yeast knockout library that exhibit reduced robustness of quantitative morphological markers to stochastic variation and Rinott et al 2011 characterized multiple genes buffering cell cell stochastic variability using reporter gene expression as the phenotypic read out These conclusions are supported from studies in flies where Takahashi used genomic deficiency lines to identify multiple genomic regions harbouring loci that are necessary to buffer wing shape to genetic variation and sensory bristles to environmental variation Takahashi et al 2012 Takahashi 2013 A second message emerging from the yeast studies involves the molecular identity of phenotypic capacitors which share the characteristic of being part of highly connected nodes in cellular networks such as chromatin maintenance factors cell cycle proteins transcriptional regulators and components of the stress response Levy and Siegal 2008 Rinott et al 2011 Interestingly some deletions in genes involved in clathrin dependent vesicle transport or transcription regulation were found to decrease rather than increase the phenotypic variance in growth rate Levy et al 2012 This suggests that some loci in the genome may also act as variance amplifiers for certain phenotypes A more recent study reported a high proportion of phenotypic stabilizers among essential genes Bauer et al 2015 Therefore the molecular identity of these factors suggests that phenotypic capacitors may be broad regulators of cell homeostasis buffering many developmental phenotypes at once as a result of their high connectivity with several other cellular gene networks It is still unclear to what extent some tissue specific components may also affect system robustness One example comes from studies in flies where mutations in the transcription factor gene TAILESS have been shown to affect embryo to embryo variability in segmentation gene expression patterns Janssens et al 2013 Single genes acting as phenotypic capacitors have also been identified through candidate gene approaches The classical example is heat shock protein 90 HSP 90 which is an ATP dependent chaperone helping the maturation of a wide range of proteins through its association with various co chaperones and cofactors Whitesell and Lindquist 2005 Impairment of HSP 90 function first in flies and later in other organisms including plants revealed a wide range of developmental abnormalities Rutherford and Lindquist 1998 Queitsch et al 2002 Samakovli et al 2007 Sangster et al 2008 HSP 90 may contribute to system robustness to standing genetic variation or noise either directly through association with mutant interactors such as kinases ubiquitin ligases and transcription factors or indirectly by regulating the activity of signal transduction pathways However developmental abnormalities upon HSP 90 inhibition have been mostly studied in a qualitative rather than a quantitative way in the literature so it is unclear in many cases whether HSP 90 impairment affects specifically trait variance see Rohner et al 2013 for a recent exception to this Another single gene disruption in plants related to robustness involves the circadian clock regulator EARLY FLOWERING 4 ELF4 In this case two sided phenotypic errors in the circadian clock period have been found in elf4 mutants in arabidopsis Doyle et al 2002 A class of genes thought to be key players in developmental robustness is micro RNAs miRNAs Hornstein and Shomron 2006 miRNAs are post transcriptional regulators of gene expression in both animals and plants Bartel 2009 Rubio Somoza and Weigel 2011 They function by tuning the expression levels of their target genes setting up sharp developmental boundaries of differential gene expression They also participate in feedback and feedforward loops within developmental networks buffering the stochastic expression of their target genes Wu et al 2009 Siciliano et al 2011 One example in arabidopsis involves the mir164 family mir164abc triple mutants show increased variance in stem internode size as a consequence of derepressing CUC1 and CUC2 gene expression Sieber et al 2007 However miRNAs are often considered as robustness factors simply based on the condition dependent developmental defects of many miRNA mutants for example showing phenotypes specifically in one environment and not in another Once again we argue that distinguishing the effects on mean and variance is very important in order to determine on a case by case basis whether miRNAs are indeed regulators of developmental robustness sensu stricto In plants the distinction between gene effects on trait mean and variance has mostly been discussed so far in the context of natural variation in robustness Quantitative trait locus QTL mapping approaches have proved successful in identifying effects on trait variance not just the mean Weller et al 1988 and QTL studies and genome wide association studies have since been pursued in plants including maize and arabidopsi s to identify loci affecting specifically trait variance upon a given perturbation Hall et al 2007 Ordas et al 2008 Jimenez Gomez et al 2011 Shen et al 2012 Phenotypes of choice include gross plant morphology metabolite profiling or gene expression and the most common perturbation is microenvironmental or environmental variation Similar to lab induced mutations a main message emerging from these studies is that multiple independent genomic regions contribute to natural variation in trait variance with some of these regions affecting at the same time the trait mean and variance while others act specifically on one or the other Hall et al 2007 Ordas et al 2008 Jimenez Gomez et al 2011 Additionally some QTLs were found to affect sensitivity in many different phenotypes or to act as hotspots in the genome underlying system wide buffering of many phenotypic traits Hall et al 2007 Fu et al 2009 However in very few cases have the causative alleles for trait variance been identified down to the nucleotide level One example is a QTL identified for variance of rosette leaf number under long day photoperiods between the two most widely used A thaliana accessions Columbia and Landsberg erecta This QTL maps closely to the ERECTA ER gene a member of the leucine rich repeat receptor like protein kinases which has pleiotropic functions in plant development van Zanten et al 2009 Interestingly the effect of ER in this case was found to be allele specific with only one of the available mutations in ER reproducing the variance defect Hall et al 2007 Another example is genetic variation in the ELF3 gene another core component of the circadian clock and protein interactor of ELF4 which was found to affect differences between the Bayreuth and Shahdara A thaliana accessions for sensitivity to noise in many phenotypes Interestingly the Shahdara ELF3 allele affects noise in a context dependent manner increasing trait variance for some phenotypes and decreasing variance for others This suggests that the exact direction of the effects for genes influencing trait variance may be phenotype dependent Another good example from yeast revealed the molecular identity of loci controlling trait variance in natural populations Using five isogenic yeast strains it was shown that loci related to uracil metabolism and sensing the environment buffer cell to cell stochastic variation in GFP green fluorescent protein reporter gene expression Ansel et al 2008 Fehrmann et al 2013 Findings from single gene perturbations support the idea that phenotypic robustness can be genotype specific especially when studying related or interconnected traits Bauer et al 2015 However robustness can also be trait specific Extensive phenotyping of cell morphology and intracellular organization in wild yeast isolates revealed that most strains show trait specific noise variation although some strains can be globally variable for many phenotypes The genetic diversity of the globally variable strains suggested multiple evolutionary transitions to high global variance under different ecological pressures Yvert et al 2013 Previous Section Next Section MECHANISMS AND EVOLUTION The identification of single genes buffering developmental phenotypes raises the question of how robustness is mechanistically achieved Developmental robustness is linked to functional redundancy which ensures trait stability in the face of perturbations by providing back up opportunities for a given system Redundancy in biological systems can be found at many different levels such as in cells genes and regulatory elements Wagner 2007 For example in the developmental context of the vulva a common phenotypic error is mis centring of the anchor cell above the P5 p cell upon environmental variation whereas normally the anchor cell is located above P6 p However three competent cells P 3 4 8 p provide back up cell redundancy and such mis centring is buffered without leading to phenotypic consequences Gene redundancy can provide mutational robustness when a gene duplicate can substitute for a mutated paralogue or when gene duplicates show different sensitivities to environmental factors such as temperature Hsiao and Vitkup 2008 Keane et al 2014 Further focusing down at the nucleotide level redundancy of regulatory elements such as transcriptional enhancers ensures insensitivity of gene expression programmes to macroenvironmental perturbations Frankel et al 2010 Perry et al 2010 The mechanistic basis of robustness lies not only in redundant parts but also in the distribution and connections of parts within a system In this case several components of a system contribute to the flow of information and thus system function Distributed robustness is very common in metabolic and developmental networks Felix and Wagner 2008 Network topology including feedback or feedforward regulatory loops and signalling pathway cross talk are important for developmental robustness Posadas and Carthew 2014 In plants multiple interconnected feedback loops are important for the stability of the circadian clock Mas and Yanovsky 2009 For example work on the arabidopsis circadian clock showed that the feedback regulatory loop between the LIGHT REGULATED WD1 LWD1 and PSEUDO RESPONSE REGULATOR9 PRR9 is important for the robustness of the circadian rhythm which is variable in lwd1 lwd2 double mutant plants under continuous dark conditions Y Wang et al 2011 Feedback regulation has been shown in many different systems to result in threshold like system behaviour and thus to increase output stability to stochastic environmental and standing genetic variation Becskei and Serrano 2000 Ramsey et al 2006 Shinar et al 2007 Denby et al 2012 Phenotypic variance may be explained through variation in gene expression across individuals Variable gene expression can arise upon many different genetic perturbations For example overexpression of the chromatin remodelling SWI SNF2 type ATPase AtCHR23 in arabidopsis leads to increased variation in gene expression between individual plants Folta et al 2014 Continuous variation in gene expression may propagate as a bimodal output for another downstream gene and this was shown to be the underlying basis of partial penetrance for some intestinal mutations in C elegans Raj et al 2010 However biological systems can be robust to a range of changes in gene dosage Acar et al 2010 Barkoulas et al 2013 For example vulva cell fate patterning is sensitive to changes in the level of EGF like signalling and exhibits two distinct thresholds one below which the vulva is underinduced and another above which the vulva is overinduced Barkoulas et al 2013 These boundaries of the robustness of cell induction to EGF expression variation were determined at single molecule resolution by quantitative in situ hybridization in C elegans Fig 2 C Barkoulas et al 2013 In plants Müller and colleagues addressed what is the range of variation in CLAVATA3 CLV3 expression that the meristem can buffer without changing its size Muller et al 2006 The authors used CLV3 promoter deletion derivatives to modulate the expression levels of CLV3 and showed that shoot and flower meristem size is robust to a ten fold change Muller et al 2006 Fig 2 C Are changes in phenotypic variance adaptive Developmental robustness is just an observable property so a lack or low levels of phenotypic variation does not necessarily imply that this is the product of selection It may arise neutrally because of non linearity between parameters and phenotypic effects in biological systems resulting in robustness plateaux Lynch 2007 Fig 2 C It may also arise pleiotropically due to selection for another phenotype or due to selection for robustness to another perturbation The latter is because it has been shown that at least in some cases there is similarity between the responses to two different types of variation For example alleles selected for environmental canalization may also be responsible for genetic canalization Meiklejohn and Hartl 2002 To address experimentally whether a certain phenotype is maintained under stabilizing selection in the lab mutation accumulation lines are very useful which are constructed in self fertile or hermaphrodite species by continuing with a random single individual for many generations thus minimizing the effect of selection Such lines were used in C elegans to show that the high degree of robustness of the vulval cell fate pattern is likely to be maintained under selection as it rapidly breaks down upon random mutation accumulation Braendle et al 2010 The genetic basis of trait variance suggests that natural selection may act to optimize phenotypic variation within a population Is it better for a system to be robust or sensitive to perturbations A high degree of developmental robustness and so low phenotypic variation in the population may in some cases be beneficial for it to withstand various perturbations However phenotypic plasticity and high phenotypic variation can also be key in order to cope with environmental challenges or spark evolutionary innovation Therefore depending on the phenotype of interest and the ecological circumstances natural selection may act either to stabilize or to destabilize phenotypic traits A recent example concerning gene expression compared the effects of natural polymorphisms in the promoter of the glucose metabolism gene TDH3 within 85 S cerevisiae strains with those of random point mutations in this promoter Metzger et al 2015 This study suggested that selection on gene expression noise has had a greater impact on sequence variation than selection on mean expression levels highlighting that purifying selection constrains variation in TDH3 expression among isogenic individuals Metzger et al 2015 It is important in the future to better link phenotypic variation with fitness Phenotypic capacitors identified in genetic screens in yeast represent highly connected nodes in cellular networks and network hubs that are probably enriched for pleiotropic effects Costanzo et al 2010 This suggests that increased phenotypic variation in such mutant backgrounds may only come as a side effect due to a broader reduction in fitness G Z Wang et al 2011 This is not however a general conclusion since increased morphological variation in yeast was not found to correlate with a decrease in fitness Bauer et al 2015 Robust systems are still adaptable and they do evolve by accumulating cryptic genetic variation Paaby and Rockman 2014 This is abundant genetic variation that is normally buffered so it is silent at the phenotypic level but can be revealed upon system perturbation such as experimental introgression of mutations or cell ablations Milloz et al 2008 For example in the case of HSP 90 mediated buffering functional impairment of this chaperone pharamcologically or perhaps by temperature in the wild leads to background dependent pleiotropic defects in develepment Rutherford and Lindquist 1998 The release of cyptic genetic variation in the form of phenotypic variation can be enriched by selection allowing adaptation to new environments Rohner et al 2013 Previous Section Next Section CONCLUSIONS By drawing on findings in animals and yeast we discuss here how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation They will also benefit from a clear distinction between gene effects on trait mean and trait variance Such a distinction has been discussed in the context of plant quantitative genetics but very little in the plant development field Recent advances in quantitative developmental biology and high throughput phenotyping now allow the design of targeted genetic screens to identify genes amplifying or restricting developmental trait variance and study how variation propagates across different phenotypic levels in biological systems The molecular characterization of more QTLs affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved Previous Section Next Section ACKNOWLEDGEMENTS We thank Miltos Tsiantis and Jie Song for comment and Marie Anne Félix for valuable discussions Research on developmental robustness in the Barkoulas lab is supported by a Biotechnology and Biological Sciences Research Council award BB L021455 1 The Author 2015 Published by Oxford University Press on behalf of the Annals of Botany Company All rights reserved For Permissions please email journals 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  • The developmental genetics of biological robustness

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  • The developmental genetics of biological robustness
    less robust compared with the vulval induction index note the increase in standard error in seam cell number Note the difference in information that can be inferred from analysing the mean panels in the centre and phenotypic distribution right hand panels For example phenotype 2 distribution is wider at 25 C with a bias towards an increase in seam cell number Data in both A and B come from our lab after phenotyping 50 animals of the lab reference strain N2 View larger version In this window In a new window Download as PowerPoint Slide Fig 2 Defining robustness genes and robustness to gene expression change A For any quantifiable phenotype classical developmental mutants are defined herein as those displacing the mean leading to either an increased or decreased mean whereas robustness mutants as those increasing the phenotypic variance without much effect on the mean In practice the most common case is mutants that do both at the same time sensu Waddington B An example showing a strict robustness defect using root length as the phenotype of interest C Examples illustrating the effect of changing gene expression levels on two different developmental phenotypes the nematodes vulval cell fate induction upper panel in response to EGF expression presented by the number of mRNA molecules quantified in situ showing that the induction index tolerates a change in expression ranging from 15 to 50 mRNA molecules Barkoulas et al 2013 Exposure to 15 mRNA molecules causes hypoinduction whereas expression of 50 mRNA molecules causes hyperinduction The lower panel illustrates the example of plant meristem size in response to change in expression level of CLAVATA3 CLV3 relative to the wild type 100 Meristem size is shown to tolerate a ten fold variation in CLV3 expression from 33 to 320 that of the wild type Muller et al 2006 The Author 2015 Published by Oxford University Press on behalf of the Annals of Botany Company All rights reserved For Permissions please email journals permissions oup com This Article Ann Bot 2015 doi 10 1093 aob mcv128 First published online August 20 2015 Abstract Free Free Figures Free Full Text HTML Free Full Text PDF Free Classifications Viewpoint Services Article metrics Alert me when cited Alert me if corrected Alert me if commented Find similar articles Similar articles in PubMed Add to my archive Download citation Request Permissions Responses Submit a response No responses published Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Google Scholar Articles by Mestek Boukhibar L Articles by Barkoulas M Search for related content PubMed PubMed citation Articles by Mestek Boukhibar L Articles by Barkoulas M Agricola Articles by Mestek Boukhibar L Articles by Barkoulas M Related Content Load related web page information Share Email this article CiteULike Delicious Facebook Google Mendeley Twitter What s this Search this journal Advanced Current Issue February 2016 117 2 Alert me to new issues The Journal About this journal Annals of Botany Collections AoB article attracts media coverage We

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  • Development and evolution of extreme synorganization in angiosperm flowers and diversity: a comparison of Apocynaceae and Orchidaceae
    two families is presented Key Findings There is a tendency of protracted development of synorganized parts in Apocynaceae and Orchidaceae development of synorganization of two or more organs begins earlier the more accentuated it is at anthesis Synorganization or complexity also paves the way for novel structures One of the most conspicuous such novel structures in Apocynaceae is the corona which is not the product of synorganization of existing organs however it is probably enhanced by synorganization of other existing floral parts In contrast to synorganized parts the corona appears developmentally late Conclusions Synorganization of floral organs may lead to a large number of convergences in clades that are only very distantly related The convergences that have been highlighted in this comparative study should be developmentally investigated directly in parallel in future studies Key words Apocynaceae Orchidaceae angiosperm flower development flower evolution flower symmetry synorganization congenital fusion postgenital fusion pollinium pollinarium species diversity The Author 2015 Published by Oxford University Press on behalf of the Annals of Botany Company All rights reserved For Permissions please email journals permissions oup com This Article Ann Bot 2015 doi 10 1093 aob mcv119 First published online August 20 2015 Abstract Free Free Figures Free Full Text HTML Full Text PDF Classifications Review Services Article metrics Alert me when cited Alert me if corrected Alert me if commented Find similar articles Similar articles in PubMed Add to my archive Download citation Request Permissions Responses Submit a response No responses published Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Google Scholar Articles by Endress P K Search for related content PubMed PubMed citation Articles by Endress P K Agricola Articles by Endress P K Related Content Load related web page information Share Email this article CiteULike Delicious Facebook Google Mendeley Twitter What s this Search this journal Advanced Current Issue February 2016 117 2 Alert me to new issues The Journal About this journal Annals of Botany Collections AoB article attracts media coverage We are mobile find out more Journals Career Network Published on behalf of The Annals of Botany Company Impact factor 3 654 5 Yr impact factor 4 338 Eigenfactor 0 02603 Rank 10 200 SCImago Score 1 461 Rank 124 1873 Chief Editor Professor J S Pat Heslop Harrison View full editorial board International Review Board For Authors Submitting a manuscript online Self archiving policy Instructions for authors Low Rate Open Access Fees Open access options for authors visit Oxford Open Visit HighWire Press 3hWaciBYRk30rSOQ7UOpP6viAxsZnEle true Looking for your next opportunity Looking for jobs Alerting Services Email table of contents Email Advance Access CiteTrack XML RSS feed Rights Permissions This journal is a member of the Committee on Publication Ethics COPE Corporate Services Advertising sales Reprints Supplements Widget Get a Widget Most Most Read Calcium in Plants Pollen Tube Distribution in the Kiwifruit Actinidia deliciosaA Chev C F Liang Pistil in Relation to its Reproductive Process Homeosis in Araceae Flowers The Case of Philodendron melinonii The

    Original URL path: https://aob.oxfordjournals.org/content/early/2015/08/19/aob.mcv119.abstract (2016-02-18)
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  • Sign In
    Sign in via OpenAthens If your organization uses OpenAthens you can log in using your OpenAthens username and password Contact your library for more details List of OpenAthens registered sites including contact details Login via Your Institution Login via your institution You may be able to gain access using your login credentials for your institution Contact your library if you do not have a username and password Register or Subscribe Subscribe to the Journal Subscribe to the print and or online journal Register Register online for access to selected content and to use Pay per View Registration is free This Article Ann Bot 2015 doi 10 1093 aob mcv119 First published online August 20 2015 Abstract Free Free Figures Free Full Text HTML Full Text PDF Classifications Review Services Article metrics Alert me when cited Alert me if corrected Alert me if commented Find similar articles Similar articles in PubMed Add to my archive Download citation Request Permissions Responses Submit a response No responses published Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Google Scholar Articles by Endress P K Search for related content PubMed PubMed citation Articles by Endress P K Agricola Articles by Endress P K Related Content Load related web page information Share Email this article Search this journal Advanced Current Issue February 2016 117 2 Alert me to new issues The Journal About this journal Annals of Botany Collections AoB article attracts media coverage We are mobile find out more Journals Career Network Published on behalf of The Annals of Botany Company Impact factor 3 654 5 Yr impact factor 4 338 Eigenfactor 0 02603 Rank 10 200 SCImago Score 1 461 Rank 124 1873 Chief Editor Professor J S Pat Heslop Harrison View full editorial board International Review Board

    Original URL path: https://aob.oxfordjournals.org/content/early/2015/08/19/aob.mcv119.full (2016-02-18)
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    OpenAthens If your organization uses OpenAthens you can log in using your OpenAthens username and password Contact your library for more details List of OpenAthens registered sites including contact details Login via Your Institution Login via your institution You may be able to gain access using your login credentials for your institution Contact your library if you do not have a username and password Register or Subscribe Subscribe to the Journal Subscribe to the print and or online journal Register Register online for access to selected content and to use Pay per View Registration is free This Article Ann Bot 2015 doi 10 1093 aob mcv119 First published online August 20 2015 Show PDF in full window Abstract Free Free Figures Free Full Text HTML Full Text PDF Classifications Review Services Article metrics Alert me when cited Alert me if corrected Alert me if commented Find similar articles Similar articles in PubMed Add to my archive Download citation Request Permissions Responses Submit a response No responses published Citing Articles Load citing article information Citing articles via CrossRef Citing articles via Scopus Google Scholar Articles by Endress P K Search for related content PubMed PubMed citation Articles by Endress P K Agricola Articles by Endress P K Related Content Load related web page information Share Email this article Search this journal Advanced Current Issue February 2016 117 2 Alert me to new issues The Journal About this journal Annals of Botany Collections AoB article attracts media coverage We are mobile find out more Journals Career Network Published on behalf of The Annals of Botany Company Impact factor 3 654 5 Yr impact factor 4 338 Eigenfactor 0 02603 Rank 10 200 SCImago Score 1 461 Rank 124 1873 Chief Editor Professor J S Pat Heslop Harrison View full editorial board International

    Original URL path: https://aob.oxfordjournals.org/content/early/2015/08/19/aob.mcv119.full.pdf+html (2016-02-18)
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  • Development and evolution of extreme synorganization in angiosperm flowers and diversity: a comparison of Apocynaceae and Orchidaceae
    the two main carpellary vascular bundles still distinct B Level of postgenital fusion of anther flanks with style head and histological reinforcement of anther flanks for guide rail function C Level of the five stigmas at lower end of style head D Level of the five nectaries in the five grooves below the guide rails The five corona portions congenitally fused with the stamens E Level of the five corona stamen portions congenitally fused with each other leaving five holes between them The two carpels free F Level of corona and stamens forming a ring around the gynoecium at the base of the five holes Carpels at the upper portion of the ovary Scale bars all 500 µm View larger version In this window In a new window Download as PowerPoint Slide F ig 6 Style head moulding from disymmetry to pentasymmetry in two developmental stages from above in Gomphocarpus fruticosus Apocynaceae Asclepiadoideae scanning electron micrographs modified from Endress 2006 A Very young stage with the two carpels still distinct B Older stage with the two carpels postgenitally united and outline changed to five angled Scale bars A 50 µm B 500 µm View larger version In this window In a new window Download as PowerPoint Slide F ig 7 Flowers of Apocynaceae Asclepiadoideae to show diversity in proportions of petals p and corona c A Vincetoxicum nigrum with relatively small and simple corona B Asclepias curassavica with relatively large and complex corona View larger version In this window In a new window Download as PowerPoint Slide F ig 8 Diversity in extension of the edges of the style head marked with red depth of the guide rails marked with yellow together with uppermost part of the stamens and exposition of the pollinaria marked with pink correlated with pollinator size in Apocynaceae Asclepiadoideae A Gomphocarpus fruticosus style head edges not extended guide rails deep pollinaria hidden for large pollinators B Caralluma penicillata style head edges long extended guide rails shallow pollinaria exposed for small pollinators Scale bars both 500 µm View larger version In this window In a new window Download as PowerPoint Slide F ig 9 Flowers with extremely complex corolla A Ceropegia distincta Apocynaceae Asclepiadoideae B Coryanthes macrantha Orchidaceae Epidendroideae View larger version In this window In a new window Download as PowerPoint Slide F ig 10 Longitudinal differentiation of corolla and differential opening of zone of postgenital fusion of petals at anthesis in Ceropegia distincta Apocynaceae Asclepiadoideae Left floral bud Corolla congenitally fused in the lower half postgenitally fused in the upper half Right open flower Corolla with five zones from base to top 1 congenitally fused floral tube 2 open five entrances with gliding zones for pollinators 3 postgenitally fused stalk of flag 4 open osmophoric flag 5 postgenitally fused upper end of flag View larger version In this window In a new window Download as PowerPoint Slide F ig 11 Congenital fusion of all organs in very young flowers of Oncidium ornithorhynchum Orchidaceae Epidendroideae scanning

    Original URL path: https://aob.oxfordjournals.org/content/early/2015/08/19/aob.mcv119.figures-only (2016-02-18)
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  • Annals of Botany Advance Access (section view)
    and Jie Wu Relationships between root diameter root length and root branching along lateral roots in adult field grown maize Ann Bot mcv185 first published online January 7 2016 doi 10 1093 aob mcv185 12 pages Abstract Full Text HTML Full Text PDF Free Figures Supplementary Data Select this article Article Ge Yin Spencer C H Barrett Yi Bo Luo and Wei Ning Bai Seasonal variation in the mating system of a selfing annual with large floral displays Ann Bot mcv186 first published online December 31 2015 doi 10 1093 aob mcv186 10 pages Abstract Full Text HTML Full Text PDF Free Figures Supplementary Data Select this article Article Shahanara Begum Kayo Kudo Yugo Matsuoka Satoshi Nakaba Yusuke Yamagishi Eri Nabeshima Md Hasnat Rahman Widyanto Dwi Nugroho Yuichiro Oribe Hyun O Jin and Ryo Funada Localized cooling of stems induces latewood formation and cambial dormancy during seasons of active cambium in conifers Ann Bot mcv181 first published online December 24 2015 doi 10 1093 aob mcv181 13 pages Abstract Full Text HTML Full Text PDF Free Figures Select this article Article Shi Dan Zhu Rong Hua Li Juan Song Peng Cheng He Hui Liu Frank Berninger and Qing Ye Different leaf cost benefit strategies of ferns distributed in contrasting light habitats of sub tropical forests Ann Bot mcv179 first published online December 18 2015 doi 10 1093 aob mcv179 10 pages Abstract Full Text HTML Full Text PDF Free Figures Supplementary Data Select this article Article Marie Monniaux Bjorn Pieper and Angela Hay Stochastic variation in Cardamine hirsuta petal number Ann Bot mcv131 first published online September 7 2015 doi 10 1093 aob mcv131 7 pages Abstract Full Text HTML Full Text PDF Free Figures Supplementary Data Supplementary Data Research in Context Select this article Research in Context Jack W Oyston Martin Hughes Sylvain Gerber and Matthew A Wills Why should we investigate the morphological disparity of plant clades Ann Bot mcv135 first published online December 9 2015 doi 10 1093 aob mcv135 21 pages Abstract Full Text HTML Full Text PDF Free Figures Supplementary Data Reviews Select this article Review Yanfang Xue Haiyong Xia Peter Christie Zheng Zhang Long Li and Caixian Tang Crop acquisition of phosphorus iron and zinc from soil in cereal legume intercropping systems a critical review Ann Bot mcv182 first published online January 8 2016 doi 10 1093 aob mcv182 15 pages Abstract Full Text HTML Full Text PDF Free Figures Select this article Review Rolf Rutishauser Evolution of unusual morphologies in Lentibulariaceae bladderworts and allies and Podostemaceae river weeds a pictorial report at the interface of developmental biology and morphological diversification Ann Bot mcv172 first published online November 20 2015 doi 10 1093 aob mcv172 22 pages Abstract Full Text HTML Full Text PDF Free Figures OPEN ACCESS Select this article Review Jennifer Lachowiec Christine Queitsch and Daniel J Kliebenstein Molecular mechanisms governing differential robustness of development and environmental responses in plants Ann Bot mcv151 first published online October 14 2015 doi 10 1093

    Original URL path: https://aob.oxfordjournals.org/content/early/by/section (2016-02-18)
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