DELLA proteins restrict cell divisions by distinct mechanisms

by Jens Sundström
Swedish University of Agricultural Sciences

Breeding of cereal crops with reduced stem length, in so called semi-dwarf varieties, greatly contributed to the yield increases associated with the Green revolution. However, the semi-dwarf genotype was also associated with reduced inflorescence size. Now, researchers at the John Innes Centre in Norwich, UK, have demonstrated that these traits are regulated by distinct pathways (Serrano-Mislata et al., 2017).  This finding opens up new venues for breeding of semi-dwarf crops without compromising yields by reducing inflorescence size.

Breeding efforts between 1960 and 1985, in large carried out at international public goods institutions such as the International Maize and Wheat Improvement Centre in Mexico (CIMMYT), contributed to a massive increase in crop yields (Pingali, 2012). For instance, yields for wheat in many developing countries have increased almost 200% since the mid 1960s. One of the key traits introgressed in many high yielding varieties is the semi-dwarf genotype. Reduced stem elongation aids reduction of lodging and allows more resources to be allocated to other parts of the plant. Typically, varieties harbouring this trait are mutated in genes affecting responses to the plant hormone gibberellin (GA) (Daviere and Achard, 2013).

Jens blog Dec 2017 3


Fig. 1. Rye usually grow shoulder high. Field of rye-wheat in which the semi-dwarf genotype found in modern wheat varieties has been introgressed. The work by Serrano-Mislata et al. indicates that the semi-dwarf trait can be uncoupled from the reduction of inflorescence size.

Genetic analyses of GA response mutants, primarily carried out in the model species Arabidopsis thaliana, have contributed to a working model for GA activity, in which GA acts as an “inhibitor of an inhibitor” (Harberd et al., 2009). DELLA-proteins, which belong to a sub-family of the plant specific GRAS family, act as key repressors of GA responses (Daviere and Achard, 2013). In the absence of GA, DELLA-proteins bind other transcription factors and inhibit their activity. In the presence of GA, the DELLA proteins are degraded and transcription of GA-responsive genes can occur. Plants with mutated DELLA-proteins have pleiotropic phenotypes; for example, reduced seed germination and reduced stem length.

In a recent report, Serrano-Mislata and co-workers (2017) demonstrated that DELLA proteins inhibit shoot growth by negatively regulating cell division rather than cell expansion. The authors provided evidence for this by expressing a stabilized form of DELLA proteins in either the internodes of a stem or in the apical segment of an inflorescence (Fig. 1).

In both cases, expression of the stabilized DELLA-protein resulted in fewer dividing cells as compared to the wild type. These results suggested that DELLA-proteins act as inhibitors of genes involved in cell-cycle regulation or cell division. To test this hypothesis, the authors performed a chromatin immunoprecipitation (ChIP) experiment that allowed them to identify promoters to which the DELLA proteins bind. One of the candidate genes identified in the ChIP experiment encodes a protein belonging to a family of cell cycle inhibitors. Next, the authors made a cross between a knock-out mutant of the cell cycle inhibitor and the line expressing the stabilized form of the DELLA-proteins. Interestingly, the resulting line retained the semi-dwarf phenotype, but the number of cells in the shoot apical meristem were similar to that in the wild type. Hence, cell division were inhibited in the stem internodes but unaffected in the shoot apical meristem, suggesting that DELLA proteins, at least in part, control growth through the activity of cell cycle inhibitors and that this regulation occurs through distinct pathways in different parts of the plant.

While the mechanistic and genetic insights provided by Serrano-Mislata et al., (2017) are based on work done in Arabidopsis, they also provided evidence for the presence of a conserved mechanisms in cereals. Hence, their findings may provide future tools for breeding of high yielding semi-dwarf cereal varieties, without compromising growth in the seed-bearing parts of the plants.

References
Serrano-Mislata A, Bencivenga S, Bush M, Schiessl K, Boden S, Sablowski R. (2017). DELLA genes restrict inflorescence meristem function independently of plant height. Nature Plants 3(9):749-754. doi:10.1038/s41477-017-0003-y

Pingali PL. (2012). Green revolution: impacts, limits, and the path ahead. Proccedings of the Natural Academy of Sciences, USA 109(31):12302-12308. doi:10.1073/pnas.0912953109

Daviere JM and Achard P. (2013). Gibberellin signaling in plants. Development 140(6):1147-1151. doi: 10.1242/dev.087650

Harberd NP, Belfield E, Yasumura Y. (2009). The angiosperm gibberellin-GID1-DELLA growth regulatory mechanism: how an “inhibitor of an inhibitor” enables flexible response to fluctuating environments. The Plant Cell 21(5):1328-1339. https://doi.org/10.1105/tpc.109.066969

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Does gibberellin regulate the trade-off between flowering and runnering in strawberry?

by Timo Hytönen
Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland

Strawberry is one of the most economically-important berry crops in the world. It is a rosette plant that reproduces both generatively and vegetatively through stolons called runners. There is a strong trade-off between flowering and runnering, but runners are important because fruit production is based on clonally propagated plants. In a diploid woodland strawberry, two classical mutants affecting flowering and runnering are known. Recessive mutations in Seasonal flowering locus (SFL) and Runnering locus (R) cause perpetual flowering and runnerless phenotypes, respectively (Figure 1; Brown and Wareing 1965). SFL encodes a major floral repressor, the woodland strawberry homolog of TERMINAL FLOWER1 (Koskela et al. 2012; Iwata et al. 2012), which mediates photoperiodic and temperature signals to control seasonal flowering (Rantanen et al. 2015). The molecular nature of R, however, has remained elusive.

TFL1mutantFigure 1. Classical mutations in woodland strawberry. Recessive mutations in SFL and R genes cause perpetual flowering and inability to produce runners, respectively (left), whereas the plant with dominant alleles (right) is seasonal flowering and produces runners.

Guttridge and Thompson (1964) showed that exogenous gibberellin (GA) treatment induces runner formation and suppresses flowering in a runnerless perpetual flowering mutant of woodland strawberry, indicating that GA may play a role in the trade-off between flowering and runnering. Now, over 50 years later, two studies provided molecular evidence for the role of GA in the control of axillary bud differentiation to runners or branch crowns. Tenreira et al. (2017) identified a gene encoding a GA biosynthetic enzyme, GA20-oxidase, as a plausible candidate for R (see also commentary by Lockhart 2017), and Caruana et al. (2017) reported a single functional DELLA protein that suppresses runner formation in woodland strawberry.

Tenreira et al. (2017) identified FvGA20ox4 as a candidate gene for R by genetic mapping and whole-genome sequencing of a pooled mutant sample. They found a 9-bp deletion in the second exon of the gene and showed by enzyme assays that only non-mutated FvGA20ox4 was able to convert GA12 to GA20 which is the precursor of active GA1. Furthermore, in situ hybridization experiments showed FvGA20ox4 expression in axillary meristems. Together with previous growth regulator experiments (e.g. Guttridge and Thompson 1964; Hytönen et al. 2009), these new data provide strong evidence for FvGA20ox4 being the R gene. However, the role of four other GA20-oxidase encoding genes in axillary bud differentiation remains unresolved. Mutant complementation or targeted mutagenesis of FvGA20ox4 is still required to obtain a final proof.

In another recent study, Caruana et al. (2017) performed a mutagenesis screen in a runnerless woodland strawberry. They found a mutant that continuously produced runners and, using a mapping-by-sequencing strategy, they identified a gene encoding a DELLA growth repressor FvRGA1, as the prime candidate. Next, they generated an inducible dominant negative version of the corresponding DELLA protein and showed that it was able to suppress the formation and elongation of runners in woodland strawberry indicating that a single DELLA protein controls axillary bud fate.

Does GA regulate the trade-off between flowering and runnering in strawberry then? The studies discussed here provide solid evidence for a role of the GA pathway in the control of axillary bud fate, and based on the presented evidence the following working model can be proposed: FvGA20ox4 likely encodes a rate-limiting enzyme of the GA biosynthetic pathway in the axillary bud. In the presence of an active GA20ox enzyme, GA20 is produced and further converted to GA1 by GA3-oxidases; GA1 then causes the degradation of FvRGA1 leading to runner growth, whereas the reduction of GA1 level leads to the accumulation of this DELLA protein and the differentiation of axillary buds to branch crowns. GA also indirectly affects flowering by controlling the number of shoots capable of producing an inflorescence (Tenreira et al. 2017; Caruana et al. 2017), but additional signals are required for floral induction in apical meristems of the crowns.

References

Brown T, Wareing PF. 1965. The genetical control of the everbearing habit and three other characters in varieties of Fragaria vesca. Euphytica 14: 97-112. https://doi.org/10.1007/BF00032819 

Caruana JC, Sittmann JW, Wang W, Liu Z. 2017. Suppressor of Runnerless encodes a DELLA protein that controls runner formation for asexual reproduction in strawberry. Molecular Plant http://dx.doi.org/10.1016/j.molp.2017.11.001

Guttridge CG, Thompson PA. 1964. The effect of gibberellins on growth and flowering of Fragaria and Duchesnea. Journal of Experimental Botany 15: 631–646. https://doi.org/10.1093/jxb/15.3.631.

Hytönen T, Elomaa P, Moritz T, Junttila O. 2009. Gibberellin mediates daylength controlled differentiation of vegetative meristems in strawberry (Fragaria x ananassa Duch.). BMC Plant Biology 9:18. doi:  10.1186/1471-2229-9-18

Iwata H, Gaston A, Remay A, Thouroude T, Jeauffre J, Kawamura K, Oyant LHS, Araki T, Denoyes B, Foucher  F. 2012. The TFL1 homologue KSN is a regulator of continuous flowering in rose and strawberry. Plant Journal 69: 116–125. http://doi.org/10.1111/j.1365-313X.2011.04776.x

Koskela E, Mouhu K, Albani MC, Kurokura T, Rantanen M, Sargent D, Battey NH, Coupland G, Elomaa P, Hytönen T. 2012. Mutation in TERMINAL FLOWER1 reverses the photoperiodic requirement for flowering in the wild strawberry, Fragaria vesca. Plant Physiology 159: 1043-1054. http://doi.org/10.1111/tpj.12809

Lockhart J. 2017. Flowering versus runnering: uncovering the protein behind a trait that matters in strawberry. Plant Cell 29: 2080-2081. https://doi.org/10.1105/tpc.17.00709

Rantanen M, Kurokura T, Jiang P, Mouhu K, Hytönen T. 2015. Strawberry homolog of TERMINAL FLOWER1 integrates photoperiod and temperature signals to inhibit flowering. Plant Journal 82: 163-173. http://doi.org/10.1111/tpj.12809

Tenreira T, Lange MJP, Lange T, Bres C, Labadie M, Monfort A, Hernould M, Rothan C, Denoyes B. 2017. A specific gibberellin 20-oxidase dictates the flowering-runnering decision in diploid strawberry. Plant Cell 29: 2168-2182. https://doi.org/10.1105/tpc.16.00949

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Enhancing the possibilities of promoter research

Rainer Melzer
School of Biology and Environmental Science, University College Dublin

Developmental regulatory genes have played a pivotal role during the evolution and domestication of plants. From a molecular genetics perspective, our understanding of those regulators is largely driven by the analysis of full loss-of-function mutants. This has provided profound insights into gene regulatory circuits governing developmental processes. However, from the analysis of evolutionary and domestication processes it is also evident that in many cases not loss-of-function mutations but variations in gene expression patterns and expression strength caused phenotypic change (Meyer and Purugganan, 2013). This is a least partly due to the pleiotropic functions of many developmental regulators: complete loss-of-function mutations often yield so dramatic phenotypes that the fitness of the plant is severely impaired, hence the relevance of null mutants during evolution and domestication is limited.

From the analysis of a few exemplary cases we know that the modularity of promoter architectures is one important component of pleiotropic gene functions. For example, APETALA3, a transcription factor coding gene that controls petal as well as stamen development, has specific enhancer regions that are required for AP3 expression in stamens (Hill et al., 1998). Studying promoter functions at the molecular level is therefore extremely valuable for our understanding of evolutionary and domestication processes. Detailed promoter studies are usually quite laborious, however, and are largely limited to a few genetic model plants. Promoter studies often encompass the identification of putative enhancer elements using in silico approaches and the expression of a reporter gene under control of a mutated promoter version lacking those elements (or containing multiples of them). Altered expression pattern of the reporter gene informs about the function of putative enhancer elements (Hernandez-Garcia and Finer, 2014). Although this approach has been very successful, in silico predictions do not always identify critical promoter elements (Hong et al., 2003). In many cases, a more unbiased approach to study promoter functions might be at least equally promising.

Figure_Tomatoes

Traditional breeding generated a large variation in tomato fruit size. The method presented by Rodríguez-Leal et al. (2017) has the potential to modify and fine-tune quantitative traits in just a few generations.

A recent paper by Rodríguez-Leal et al. (2017) presents a method that will substantially facilitate such an unbiased molecular genetic analysis. Using tomato fruit size as a model system, the authors target the promoter of Solanum lycopersicum CLAVATA3 (SlCLV3), a gene know to be involved in fruit size regulation, using CRISPR-Cas9. However, unlike more conventional CRISPR-Cas9 approaches that aim to generate full loss-of-function mutants, the authors designed not just one but eight guide RNAs that spanned a 2 kb range of the putative promoter region of SlCLV3. Because of variations in guide RNA directed cleavage activities and subsequent repair processes, many types of mutations can be induced, ranging from large promoter deletions to inversions, small deletions and single nucleotide substitutions (Rodríguez-Leal et al., 2017).

As the analysis of the mutant plants proved difficult because different mutations are introduced in the two alleles of the target gene, the authors devised a genetic screen in which they crossed a wild-type plant with a transgenic plant that expressed the eight guide RNAs and Cas9, and also carried a full loss-of-function allele of SlCLV3. In the resulting progeny, mutations were induced by CRISPR-Cas9 in the wild-type allele. In this set-up, the phenotypic effects of even mutations causing only subtle phenotypic changes are relatively easy to detect as the second SlCLV3 allele is a null allele. Thus, the authors essentially developed an elegant yet simple procedure to randomly mutagenize one particular locus and screen for phenotypic consequences of the mutations. Indeed, using this system, it was possible to create an allelic series of 14 SlCLV3 mutant alleles that showed a continuous variation in carpel number (thus leading to a variation in fruit size) (Rodríguez-Leal et al., 2017).

This method is potentially of huge importance for dissection promoter functions. It may be possible to quickly generate a large number of random mutations and analyse their phenotypic effect in a streamlined way. This will prove to be very powerful to untangle the functional elements in promoters. In turn, our understanding of how master regulators of development may have contributed to morphological evolution may be substantially increased. For example, it has been proposed that alterations in the expression of floral homeotic transcription factors contributed to floral diversity (reviewed by Theißen and Melzer, 2007). The approach presented by Rodríguez-Leal et al. (2017) constitutes a promising avenue to test whether and how promoter mutations can induce such phenotypic changes. Theoretically, a large number of mutant alleles can be generated from one transgenic plant. Thus, the approach may also be suitable for phylogenetically informative non-model plants that are difficult to transform.
Last but not least, plant domestication and crop improvement also often proceeds via variations in quantitative traits. Rodríguez-Leal et al. (2017) demonstrated that a substantial variation in tomato fruit size can be obtained in just a few generations, bypassing years of breeding efforts. It will be interesting to see to which extent the same method can be applied to other quantitative traits in crops.

References

Hernandez-Garcia CM, Finer JJ. 2014. Identification and validation of promoters and cis-acting regulatory elements. Plant Science 217, 109-119. https://doi.org/10.1016/j.plantsci.2013.12.007

Hill TA, Day CD, Zondlo SC, Thackeray AG, Irish VF. 1998. Discrete spatial and temporal cis-acting elements regulate transcription of the Arabidopsis floral homeotic gene APETALA3. Development 125, 1711-1721.

Hong RL, Hamaguchi L, Busch MA, Weigel D. 2003. Regulatory elements of the floral homeotic gene AGAMOUS identified by phylogenetic footprinting and shadowing. The Plant Cell 15, 1296-1309. https://doi.org/10.1105/tpc.009548

Meyer RS, Purugganan MD. 2013. Evolution of crop species: genetics of domestication and diversification. Nature Reviews Genetics 14, 840-852. https://doi.org/10.1038/nrg3605

Rodríguez-Leal D, Lemmon ZH, Man J, Bartlett ME, Lippman ZB. 2017. Engineering quantitative trait variation for crop improvement by genome editing. Cell 171, 470-480. https://doi.org/10.1016/j.cell.2017.08.030

Theißen G, Melzer R. 2007. Molecular mechanisms underlying origin and diversification of the angiosperm flower. Annals of Botany 100, 603-619. https://doi-org./10.1093/aob/mcm143

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Untangling complexity: shedding a new light on LEAFY and APETALA1 interactions

by Leonie Verhage and Francois Parcy
Institut de Biosciences et Biotechnologies de Grenoble (France)

Ever since their discovery almost 30 years ago, the transcription factors LEAFY (LFY) and APETALA1 (AP1) (together with its paralog CAULIFLOWER (CAL)) have been extensively studied for their roles in floral transition. Early genetic and molecular experiments indicated that LFY and AP1/CAL were partly redundant and partly complementary in the process of floral initiation, and numerous subsequent studies fit this model (see Denay et al., 2017 and Wils and Kaufmann, 2017 for recent reviews). However, combining a set of new experiments with published datasets, Goslin and colleagues manage to stir up the prevalent view (Goslin et al., 2017).

FrancoisParcyImage2

Scanning electron micrograph of an ap1 cal mutant. Floral meristems are transformed into proliferative inflorescence meristems. This mutant background was used by Goslin and colleagues. (Image courtesy of Marie le Masson and Christine Lancelon Pin)

To unravel the redundancy of LFY and AP1/CAL, the authors utilized a mutant line harboring a 35S:LFY-GR construct in an ap1/cal background (Wagner et al., 1999). With this line, they performed induction experiments and microarray analysis, in the same way as was previously performed with 35S:AP1-GR in the ap1/cal background (Kaufmann et al., 2010), to make the datasets comparable. This allowed them to compare the downstream genes that are regulated by LFY in the absence of AP1/CAL to genes that are regulated by AP1 in the presence of LFY.

Among the many things uncovered by these analyses, a few were expected and many completely unanticipated.

As already reported by Winter et al., 2015, there is a large overlap between the genes that are differentially regulated upon induction of LFY-GR or AP1-GR. It is likely that this represents true redundancy, where LFY and AP1 can regulate genes in the same way, independent of each other. However, due to a lack of experiments where AP1 is induced in the absence of LFY, it cannot be excluded that this set of genes can be regulated by LFY alone, or by LFY and AP1 together.

More surprisingly, many direct targets of LFY were found to be down-regulated, whereas most of the well-known targets are induced (such as the floral organ identity genes or the LATE MERISTEM IDENTITY genes).

Interestingly, a subset of genes showed differential expression in ap1 cal upon AP1 induction but not upon induction of LFY. By comparing these genes with previously published ChIP-seq data of LFY, the authors could identify a set of genes to which LFY is able to bind, but that are not differentially regulated in absence of AP1. This was the case for APETALA3 (AP3) and AGAMOUS (AG), consistent with a previous report showing that AP1 can act on these genes (Ng and Yanofsky, 2001). Hence, for regulation of these B- and C- type floral organ identity genes, LFY and AP1 appear to act interdependently.

The most surprising result, however, was the presence of genes that are differentially expressed upon LFY or AP1 induction, but in different directions. Apparently, besides acting redundantly or interdependently, LFY and AP1 can also act antagonistically. Notably, this turned out to be the case for several genes involved in inflorescence meristem identity, including TERMINAL FLOWER1 (TFL1). Contrary to the longstanding belief that AP1 and LFY are both repressors of TFL1, only AP1 repressed TFL1, whereas LFY actually activates this gene. It is not completely clear why LFY would up-regulate a gene that inhibits floral meristem identity. The authors speculate that it might be a way to better define the floral transition, so that it occurs only when AP1 is expressed high enough to overcome TFL1.

Goslin et al.  paper is a nice example of how to combine new experiments and existing datasets in a time with ever growing amounts of genome-wide data, with a surprising outcome. Two transcription factors that were long thought to function similarly in initiation of flower formation suddenly turn out to have a much more intriguing relationship, posing many new questions. When LFY and AP1 act together, the biochemical basis of their interaction is elusive. They might be part of the same regulatory complex, especially since their binding sites have been reported to be adjacent (Winter et al., 2015), but a direct interaction between the two proteins has not been observed. Analysis by targeted proteomics has uncovered AP1 interactors in floral tissue (Smaczniak et al., 2012), but has never been analyzed in earlier tissue in which LFY is expressed. Another question is how LFY and AP1 sometimes work together, and sometimes do not, sometimes activate and other times repress. One possibility is that there might be spatio-temporal differences in expression of interaction partners of LFY and AP1 (see also the previous Flowering Highlight on Spatially resolved floral transcriptome profiling by Aalt-Jan van Dijk). Altogether, there is still a lot to be understood about these two ‘very well known’ regulators!

References

Denay G, Chahtane H, Tichtinsky G, Parcy F. 2017. A flower is born: an update on Arabidopsis floral meristem formation. Current Opinion in Plant Biology 35, 15–22. https://doi.org/10.1016/j.pbi.2016.09.003

Goslin K, Zheng B, Serrano-Mislata A, et al. 2017. Transcription Factor Interplay between LEAFY and APETALA1/CAULIFLOWER during Floral Initiation. Plant Physiology 174, 1097–1109. https://doi.org/10.1104/pp.17.00098

Kaufmann K, Wellmer F, Muiño JM, et al. 2010. Orchestration of floral initiation by APETALA1. Science 328, 85–89.  https://doi.org/10.1126/science.1185244

Ng M, Yanofsky MF. 2001. Activation of the Arabidopsis B class homeotic genes by APETALA1. The Plant Cell 13, 739–753. https://doi.org/10.1105/tpc.13.4.739

Smaczniak C, Immink RGH, Muiño JM, et al. 2012. Characterization of MADS-domain transcription factor complexes in Arabidopsis flower development. Proceedings of the National Academy of Sciences 109, 1560–1565. https://doi.org/10.1073/pnas.1112871109

Wagner D, Sablowski RW, Meyerowitz EM. 1999. Transcriptional activation of APETALA1 by LEAFY. Science 285, 582–584.  https://doi.org/10.1126/science.285.5427.582

Wils CR, Kaufmann K. 2017. Gene-regulatory networks controlling inflorescence and flower development in Arabidopsis thaliana. BBA – Gene Regulatory Mechanisms 1860, 95–105. https://doi.org/10.1016/j.bbagrm.2016.07.014

Winter CM, Yamaguchi N, Wu M-F, Wagner D. 2015. Transcriptional programs regulated by both LEAFY and APETALA1 at the time of flower formation. Physiologia Plantarum 155, 55–73. https://doi.org/10.1111/ppl.12357

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Spatially resolved floral transcriptome profiling

by Alt-Jan Van Dijk
Plant Research International, Wageningen University

Progress in sequencing technology has had a clear impact on flowering research. For example, ChIP-seq has been applied to study molecular aspects of transcriptional regulation of flowering. Also, RNA-seq data for different stages of flower development have been generated in various species (e.g. Singh et al., 2013, Wang et al., 2014, Mantegazza et al., 2014, Han et al., 2017). However, what is still lacking to a large extent is the high-resolution characterization of spatial variation in gene expression. This holds true for plant transcriptomes in general but also specifically for flower development.

A paper by Giacomello et al., 2017 presents an approach to profile plant transcriptomes with high spatial resolution. To do so, it employs semi-randomized primers with barcodes, which indicate the position of a primer on an ~1,000 spot array. Each spot is 100 μm in diameter and provides spatial resolution. After fixation and permeabilization of tissue sections on the array, polyadenylated transcripts are captured by the primers. The transcripts are then converted into cDNA and analyzed by sequencing.

van dijk june 2017

Schematic overview of the approach to profile spatially resolved floral transcriptomes. (Left) Floral tissue is positioned on top of the array surface. (Middle) Transcripts bind to barcoded primers, enabling to recover with high resolution the spatial location from which transcripts originated. Here, brown circles indicate spots on the array, and colours indicate expression of different genes in different locations. (Right) The resulting high-resolution spatial transcriptome was analysed using a model to connect spatial location (i.e. location on the array, indicated here by brown circles) to gene network expression (purple diagram).

Amongst others, Giacomello and colleagues applied their approach to analyze Arabidopsis inflorescence tissue. Comparison with the AtGenExpress Development dataset (Schmid et al., 2005) for five broadly defined tissue domains (stem, meristem, flowers of stage 9, 11 and 12) revealed a reasonable overlap. Note that, of course, the key difference between AtGenExpress and the data by Giacomello et al. is that this new data provides a much higher spatial resolution. Some of the patterns provided for individual genes are rather convincing. For example, they observed ubiquitous expression of the housekeeping gene TUB2, whereas the floral organ identity genes showed expression specifically in flowers. In spots under stamens, markedly higher expression was observed for AP3, PI, and AG than for AP1 and AP2, in agreement with the known expression patterns of these genes. When going through results from individual replicates, for example for AP3 and PI, there also seems to be quite a bit of variation between the replicates. Whether this is evidence of true biological variation or still might indicate technical variation, is not clear to me.

Be that as it may, this study not only presents high resolution data on spatial transcriptomes in floral tissues. In addition, it demonstrates how such data can be analysed. To do so, two key steps are taken. First, not just gene expression levels are used as the variable of interest, but ‘pathway scores’ which reflect the expression level of groups of genes that constitute pathways. Second, the influence of location on expression of the pathways is analysed by not just comparing each pair of locations to each other. Instead, a model is built to analyze the influence that various factors have on expression levels. These factors involve in particular the spatial location, both at the tissue level and at the level of the different spots on the array. One of the reported findings is the enrichment of the stamen filament development pathway in floral stage 11, and that the pollen exine formation pathway was altered in floral stages 10 and 11. Note that these stages indeed produce exine, one of the major constituents of the pollen wall that is deposited on the pre-pollen cells.

This paper represents the next step in the application of sequencing technology to study flowering. It is interesting to see how more and more data relevant for the study of flowers and their development is being generated using sequencing-related techniques. Time course data has been available for a while. Given the increased resolution with which spatial aspects of transcriptome expression can be measured, an important next step will be to measure the expression with both high temporal and high spatial resolution. In addition, it will be exciting to see if applications of sequencing such as ChIP-seq also can be given high spatial resolution.

 References

Giacomello S, Salmén F, Terebieniec BK, et al. 2017.  Spatially resolved transcriptome profiling in model plant species. Nature Plants 3:17061. doi: 10.1038/nplants.2017.61

Han Y,  WanH,  Cheng T,  Wang J,  Yang W, Pan H, Zhang Q.  2017. Comparative RNA-seq analysis of transcriptome dynamics during petal development in Rosa chinensis. Scientific Reports 7: 43382. doi:10.1038/srep43382

Mantegazza O, Gregis V, Chiara M, Selva C, Leo G, Horner DS, and Kater MM. 2014. Gene coexpression patterns during early development of the native Arabidopsis reproductive meristem: novel candidate developmental regulators and patterns of functional redundancy. Plant Journal 79:861-877. doi:10.1111/tpj.12585

Schmid M, Davison TS, Henz SR, Pape UJ, Demar M, Vingron M, Schölkopf B, Weigel D, Lohmann JU.  2005. A gene expression map of Arabidopsis thaliana development. Nature Genetics  37, 501. doi:10.1038/ng1543

Singh VK, Garg R, Jain M. 2013. A global view of transcriptome dynamics during flower development in chickpea by deep sequencing. Plant Journal 11, 691. doi: 10.1111/pbi.12059

Wang H, You C, Chang F, Wang Y, Wang L,Qi J, Ma H. 2014. Alternative splicing during Arabidopsis flower development results in constitutive and stage-regulated isoforms. Frontiers in Genetics 5: doi:25. 10.3389/fgene.2014.00025

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A miraculous mirabilis: the gymnosperm Welwitschia provides new insights into the origin of flowers

by Frank Wellmer
Smurfit Institute of Genetics, Trinity College Dublin, Ireland

The specification of male and female reproductive organs in gymnosperms and angiosperms is thought to be remarkably similar and to depend on the activities of B and C class MADS domain transcription factors. When B and C class factors are co-expressed, male organs are formed, while C class activity alone leads to the development of female organs. It has been shown that the expression of gymnosperm B and C class genes can rescue the developmental defects of floral mutants, in which the homologous organ identity genes are disrupted (Zhang et al., 2004). Thus, it appears that the biochemical activities of the corresponding transcription factors have remained largely unchanged since the two groups of seed bearing plants diverged around 150 million years ago.

Despite these similarities, it is not known how in angiosperms male and female organs became part of the same reproductive unit (i.e. the flower), while in gymnosperms they are separated in unisexual structures (e.g., male and female cones). It has been proposed that changes in the expression patterns of B and/or C function genes, leading to partially overlapping domains of expression and activity, were crucial to the origin of bisexual flowers. However, how these changes may have been brought about is currently not known. To address this question, detailed knowledge on the regulation of B and C class genes in both gymnosperms and angiosperms is required. While over the past 25 years, the regulation of floral organ identity genes has been extensively studied especially in the model angiosperm Arabidopsis thaliana, little is known about how the expression of orthologous genes in gymnosperms is controlled.

800px-Welwitschia_mirabilis(2)

A female Welwitschia mirabilis in the Namibian desert by Thomas Schoch

Using Welwitschia mirabilis, a recent study addressed this knowledge gap and provided molecular evidence for the regulation of B class genes by the plant-specific transcription factor LEAFY (LFY) (Moyroud et al., 2017). LFY has been shown previously to be pivotal for triggering the expression of floral organ identity genes during early flower development in Arabidopsis (Busch et al., 1999; Parcy et al., 1998).

In contrast to extant angiosperms, which possess a single LFY gene, gymnosperms typically have two LFY paralogs, one that is LFY-like and one termed NEEDLY (NDLY) or NDLY-like (Frohlich and Parker, 2000). It thus appears that early on during their evolution, angiosperms lost the NDLY-like gene and retained only the gene that is LFY-like. It is attractive to speculate that this change in the complement of known key regulators of B and C class genes may have been a crucial step in the evolution of flowers. However, what are the functions of the LFY and NDLY transcription factors in gymnosperms and how similar are they to those of LFY in angiosperms?

To answer these questions, Moyroud and colleagues first characterized the expression of LFY, NDLY as well as of likely B and C class genes in developing male cones of Welwitschia. They found that the expression of both LFY and NDLY precedes or parallels that of the organ identity genes as would be expected if the corresponding transcription factors were involved, as LFY in angiosperms, in activating the expression of B and C class genes. Furthermore, they observed that at later stages of male cone development the expression of LFY and B class genes was noticeably different to that of NDLY and the C class gene under study. Thus, based on the expression patterns of these genes alone, it can be hypothesized that LFY may control B class genes, while NDLY might be involved in the control of C class gene activity. In support of this idea, Moyroud and colleagues showed, using advanced biochemical and biophysical techniques, that LFY and NDLY have overlapping but distinct sets of binding sites. They further demonstrated that LFY from Welwitschia as well as from other gymnosperms can bind to putative regulatory elements in the promoters of B class genes.

Thus, it appears that LFY in both gymnosperms and angiosperms plays a key role in the control of these organ identity genes. While the molecular activities of NDLY need to be further characterized, the study by Moyroud et al., (2017) led to the attractive and testable hypothesis that this transcription factor may not share all functions with its paralog LFY and might control C class gene activity in gymnosperms.

References

Busch MA, Bomblies K, Weigel D. 1999. Activation of a floral homeotic gene in Arabidopsis. Science 285, 585-587. https://doi.org/10.1126/science.285.5427.585
Frohlich MW, Parker DS. 2000. The mostly male theory of flower evolutionary origins: from genes to fossils. Systematic Botany 25, 155-170. http://dx.doi.org/10.2307/2666635
Moyroud E, Monniaux M, Thevenon E, Dumas R, Scutt CP, Frohlich MW, Parcy F. 2017. A link between LEAFY and B-gene homologues in Welwitschia mirabilis sheds light on ancestral mechanisms prefiguring floral development. New Phytologist DOI: https://doi.org/10.1111/nph.14483
Parcy F, Nilsson O, Busch MA, Lee I, Weigel D. 1998. A genetic framework for floral patterning. Nature 395, 561-566. https://doi.org/10.1038/26903
Zhang P, Tan HT, Pwee KH, Kumar PP. 2004. Conservation of class C function of floral organ development during 300 million years of evolution from gymnosperms to angiosperms. The Plant Journal 37, 566-577. https://doi.org/10.1046/j.1365-313X.2003.01983.x

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Focusing on TERMINAL FLOWER 1 (TFL1) regulation

by Timo Hytönen
University of Helsinki, Finland

FLOWERING LOCUS T (FT) and TERMINAL FLOWER 1 (TFL1) are small closely related proteins that have a great impact on the production of agricultural and horticultural crops and forest trees. FT functions as a mobile signaling molecule that travels from leaves to shoot meristems to mediate information about the suitable season to induce flowers, produce tubers or set a bud (reviewed by Wickland & Hanzawa, 2015). TFL1, in contrast, is a repressor of flowering that is expressed locally in meristems. In species with indeterminate growth habit, one of the main functions of TFL1 is to maintain indeterminate inflorescence meristem and to allow flower bud development only in the flanks of the meristem. This has a direct effect on yield because it affects the number of seeds or fruits. In some other species with closed inflorescence structures, high TFL1 expression can completely prevent floral development (Costes et al., 2014).

Both FT and TFL1 are transcriptional cofactors that bind with the same transcription factor FD, and there is increasing evidence that the balance of these antagonistic signals determines the developmental output (Hanano & Goto, 2011; Wickland & Hanzawa, 2015). The molecular control of FT has been studied in detail especially in Arabidopsis, but much less is known about factors controlling spatiotemporal expression pattern of TFL1.

timo-wp_20161209_12_49_01_pro

Indeterminate inflorescences at the lava desert of El Teide.

In their recent study, Serrano-Mislata et al. (2016) explored cis-regulatory elements of TFL1 using various experimental approaches including mutant complementation, phylogenetic shadowing and promoter::GUS fusion lines. First, they tried to complement tfl1 mutant using a genomic construct containing full 5’ and 3’ intergenic regions and a similar construct lacking introns. Both constructs similarly complemented the mutant phenotype indicating that introns are not needed for the transcriptional regulation of TFL1. Next, using phylogenetic shadowing of TFL1 orthologues of several Brassicaceae species, they found seven conserved blocks that were tested further using genomic constructs of different lengths as well as similar constructs containing GUS reporter in the place of TFL1. Using these constructs the authors successfully dissected the roles of different promoter blocks in controlling TFL1 expression and shoot architecture. They found that 300 bp upstream and 3.3 kb downstream regions are needed to fully complement the defects of tfl1 mutant and to drive similar expression of GUS reporter than the full-length genomic construct. This short 5’ region is needed to maintain high TFL1 expression level, whereas separate 3’ elements control its spatiotemporal expression in different meristems. A 3’ region +2.8-3.3 kb after the stop codon is needed to maintain TFL1 expression in the inflorescence meristem, and another region at +1.6-2.2 kb controls its expression in axillary meristems. Finally, 3’ region between +1.0 and +1.3 is required to control flowering time by affecting TFL1 expression in vegetative meristems as well as its up-regulation following floral transition.

161205hytonen_figure1

TFL1 promoter elements controlling its spatiotemporal expression pattern (based on Serrano-Mislata et al. (2016).

The authors suggested that a modular structure of TFL1 promoter might facilitate gene evolution to generate different plant architectures as already observed in Leavenforthia crassa. More importantly, the identification of these modules is instrumental for future research focusing on upstream regulators of TFL1 that may control inflorescence architecture and/or flowering time in different species. One important question is what is causing the up-regulation of TFL1 in the vegetative meristem upon flower induction. One of the suggested regulators is a MADS transcription factor XAANTAL2 that shows sequence similarity with SUPPRESSOR OF THE OVEREXPRESSION OF CONSTANS1 (SOC1) (Pérez-Ruiz et al., 2015). Interestingly, also SOC1 is highly expressed in the inflorescence meristem (Immink et al., 2012), and the strawberry orthologue of SOC1 has been shown to up-regulate TFL1 (Mouhu et al., 2013). In addition, an early study indicated that CO may induce the expression of TFL1 (Simon et al., 1996), perhaps through FT. Using tools produced by Serrano-Mislata et al. (2016), time is now ripen to focus on the molecular control of TFL1 expression that may translate to increased crop yields.

References

Costes E, Crespel L, Denoyes B, Morel P, Demene M, Lauri P & Wenden B. 2014. Bud structure, position and fate generate various branching patterns along shoots of closely related Rosaceae species: a review. Frontiers in Plant Science 5: 666. https://doi.org/10.3389/fpls.2014.00666

Hanano S & Goto K. 2011. Arabidopsis TERMINAL FLOWER1 is involved in the regulation of flowering time and inflorescence development through transcriptional repression. The Plant Cell 23: 3172–3184. http:/​/​dx.​doi.​org/​10.​1105/​tpc.​111.​088641

Immink RGH, Posé D, Ferrario S, Ott F, Kaufmann K, Valentim FL, de Folter S, van der Wal F, van Dijk ADJ, Schmid M & Angenent GC. 2012. Characterization of SOC1’s central role in flowering by the identification of its upstream and downstream regulators. Plant Physiology 160: 433–449. http:/​/​dx.​doi.​org/​10.​1104/​pp.​112.​202614

Mouhu K, Kurokura T, Koskela EA, Albert VA, Elomaa P & Hytönen T. 2013. The Fragaria vesca homolog of SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 represses flowering and promotes vegetative growth. The Plant Cell 25: 3296–3310. http:/​/​dx.​doi.​org/​10.​1105/​tpc.​113.​115055

Pérez-Ruiz RV, García-Ponce B, Marsch-Martínez N, Ugartechea-Chirino Y, Villajuana-Bonequi M, de Folter S, Azpeitia E, Dávila-Velderrain J, Cruz-Sánchez D, Garay-Arroyo A, de la Paz Sánchez M, Estévez-Palmas JM, Álvarez-Buylla ER. 2015. XAANTAL2 (AGL14) is an important component of the complex gene regulatory network that underlies Arabidopsis shoot apical meristem transitions. Molecular Plant 8: 796–813. http://dx.doi.org/10.1016/j.molp.2015.01.017

Serrano-Mislata A, Fernández-Nohales P, Doménech MJ, Hanzawa J, Bradley J, Madueño F. 2016. Separate elements of the TERMINAL FLOWER 1 cis-regulatory region integrate pathways to control flowering time and shoot meristem identity. Development 143: 3315–3327. https://doi.org/10.1242/dev.135269

Simon R, Igeño MI, Coupland G. 1996. Activation of floral meristem identity genes in Arabidopsis. Nature 384: 59–62.

Wickland DP & Hanzawa Y. 2015. The FLOWERING LOCUS T/TERMINAL FLOWER 1 gene family: functional evolution and molecular mechanisms. Molecular Plant 8: 983–997. http://dx.doi.org/10.1016/j.molp.2015.01.007

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A new comparative approach to understand local adaptation

Martin Lascoux
Department of Ecology and Genetics, Uppsala University

This is a flowering highlight that only indirectly concerns flowering. Furthermore the study does not address the molecular basis of flowering as is often the case in these columns but instead is highly relevant to the understanding of its adaptive basis. Indeed the study by Yeaman et al. (2016) may well herald a new era in the analysis of local adaptation.  While there is ample evidence of local adaptation for flowering time and other putatively adaptive traits (Savolainen et al., 2013) it has proven harder to identify the genes associated with it. There are various methods to do so, all of them with strengths and weaknesses. One popular approach is to test for statistical association between flowering time variation and genetic polymorphisms along the genome. A major issue with this approach is that the signal of local adaptation can be confounded by population genetic structure.

local adaptation.jpg

Picea obovata on Mount Iremel in south Urals

For example, if one samples plants along a latitudinal gradient in Scandinavia, any difference between individuals from the North and the South could reflect the fact that Scandinavia was recolonized along two main routes after the Last Glacial Maximum (18,000 years ago), one entering Scandinavia from the south and the other from the north. So plants from northern Scandinavia can differ from their southern counterparts simply because they have different origins and differences between them cannot automatically be assigned to adaptation to the local environment. Of course, there are methods to correct for population structure, but if adaptation and demographic history go hand in hand, removing one may well end up removing the other leading to false negatives.

How did Yeaman et al. (2016) address this thorny issue? Well, they chose not to address it directly; instead they took a different road. Here is the main thrust of their reasoning. Lodgepole pine (Pinus contorta) and interior spruce (Picea glauca, Picea engelmannii and their hybrids) are two common conifer species in western Canada. Pines and spruces diverged some 140 million years ago, and we therefore do not expect to see shared polymorphism left between the two species. Being a complex species interior spruce has a particularly intricate population structure. So rather than risking a high number of false negatives by attempting to correct for population structure they assessed the relationship between genome-wide SNP variation, on the one hand, and 17 phenotypic traits assessed in growth chamber and 22 environmental variables, on the other hand, in both species. This was done without correcting for population structure. For each species they then obtained a list of top candidate genes. Of course many of them are likely false positives. But which ones are false positives and which ones true candidate genes?

In order to find out which genes could be good candidate genes for local adaptation, and incidentally test for convergent local adaptation, the authors looked for genes that are top candidates in both species. Top candidates were defined as genes with an exceptional proportion of their total SNPs being associated to either phenotype or environment. Depending on how stringent the False Discovery Rate (FDR) is the number of genes with strong signature of convergent local adaptation varied between 6 and 83. For a FDR=0.05 the number was 47. Many of those 47 top candidates had conserved patterns of differential expression in both species and/or were enriched for transcription factors and genes involved in biological regulation.  Several of the convergent genes such as Pseudo-response regulator 5 (PPR5) that regulates the circadian clock or FY that indirectly regulates FLOWERING LOCUS C are part of the pathways controlling flowering time in Arabidopsis thaliana and are prime candidates for being involved in the control of phenology in trees.

So, after all, this study is not that far from the usual topic of this column. But, in my view, its foremost value is its very innovative use of comparative genomics. It is not the first comparative study of local adaptation in trees (see Chen et al., 2012, 2014) but it is certainly the first to be carried out on a genomic scale and on highly diverged species.  I do not doubt that it will have a strong impact on future studies of local adaptation for phenological traits, in general, and on flowering time, in particular. Associated with functional studies the general approach developed by Yeaman et al. (2016) could lead to new insights on the evolution of the basic molecular mechanisms associated with local adaptation.

References

Yeaman S., Hodgins KA, Lotterhos KE, Suren H, Nadeau S, Degner JC, et al. 2016. Convergent local adaptation to climate in distantly related conifers. Science 353(6306), 1431–1433.

Chen J, Källman, T, Ma X, Gyllenstrand N, Zaina G, Morgante M, et al. 2012. Disentangling the roles of history and local selection in shaping clinal variation of allele frequencies and gene expression in Norway spruce (Picea abies). Genetics 191, 865–881.

Chen J, Tsuda Y, Stocks M, Källman T, Xu N, Kärkkäinen K, et al. 2014. Clinal variation at phenology-related genes in spruce: parallel evolution in FTL2 and Gigantea? Genetics 197(3), 1025–1038.

Savolainen O, Lascoux M, & Merilä J. 2013. Ecological genomics of local adaptation. Nature Reviews Genetics 14(11), 807–820.

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New insights into LEAFY structure and function

by Frank Wellmer
Smurfit Institute of Genetics, Trinity College Dublin, Ireland

The plant-specific transcription factor LEAFY (LFY) is a master regulator of early flower development (Weigel et al., 1992). It orchestrates the onset of flowering and is involved in activating the expression of floral organ identity genes (Busch et al., 1999; Parcy et al., 1998), which specify the different types of floral organs. Because of LFY’s central role in reproductive development, its function and molecular evolution have been studied in detail over the past 25 years using a multitude of different experimental approaches. In fact, there are arguably few plant transcriptional regulators that have been studied as extensively as LFY. However, the protein structure of LFY remained unknown for many years, precluding detailed insights in the molecular mechanism underlying its activity. This knowledge gap was partially closed in 2008, when the structure of the highly conserved carboxy-terminal DNA binding domain was resolved through X-ray crystallography (Hames et al., 2008). This work showed that the DNA binding domain is composed of a helix-turn-helix motif and binds DNA as a dimer. In contrast, the function of the amino-terminal half of LFY, which contains another conserved domain, remained unknown.

wellmer-figure

A LEAFY dimer bound to DNA. The N-terminal SAM and C-terminal DNA binding domains are shown. Image kindly provided by Dr. François Parcy.

Using LFY from the gymnosperm Gingko biloba, Sayou et al., 2016 recently succeeded in crystallizing the N-terminal domain and resolved its structure at 2.3 Å resolution. They found that the domain resembles a Sterile Alpha Motif (SAM) and is composed of five α-helices that are connected by four loops. SAM domains are common structural motifs in eukaryotes mediating the interaction with nucleic acids, lipids and other proteins. Some SAM domains have also been shown to trigger protein oligomerization. The SAM domain in LFY appears to belong to this latter group as indicated by the formation of LFY-SAM domain polymer chains in a crystal, where monomers contact each other in a head-to-tail arrangement.
What is the functional relevance of this oligomerization event and is it required for LFY activity? To investigate this, Sayou et al. first identified the amino acid residues that are essential for oligomerization. To this end, they used the structural information they had obtained as well as data from the analysis of other SAM domain-containing proteins. They then carried out a series of experiments with modified LFY proteins in which these essential amino acid residues had been substituted, leading to the suppression of oligomerization. They found that the expression of the mutated form of LFY in plants resulted in a much reduced activity when compared to wild-type LFY protein, thus implying that oligomerization is required for proper LFY function. Additional tests showed that the SAM domain prevents LFY from binding to DNA as a monomer and hence promotes dimer formation. Furthermore, the results of genome-wide localization studies showed that the mutated form of LFY exhibited a substantial decrease in its overall ability to bind to DNA.
In addition to regulating the binding properties of LFY, the SAM domain also appears to be involved in binding site selection. Specifically, Sayou et al. showed that the SAM domain mediates cooperative binding of LFY protein oligomers to multiple binding sites and facilitates binding to sites with low affinity for LFY. Thus, the SAM domain plays a central role in regulating the DNA binding activity of the LFY transcription factor.
Another interesting observation reported by Sayou et al. is that the SAM domain appears to promote binding of LFY to regions of chromatin with low accessibility. Because it has been shown previously that LFY can interact with chromatin remodelling factors it is possible that LFY acts as a ‘pioneer transcription factor’ and recruits these proteins to regions of closed chromatin to bring about changes in chromatin conformation and gene expression. Notably, it has been suggested that some of the floral organ identity factors, which mediate floral organ specification, also function as pioneer factors (Pajoro et al., 2014). These include the MADS-domain protein APETALA1, which controls early flower development together with LFY. Thus, pioneer factor activity may be at the core of the mechanism that regulates the onset of flower formation, possibly explaining the massive changes in gene expression observed during this developmental stage.

In summary, the detailed insights into LFY structure and function obtained by Sayou et al. represent a major breakthrough in the analysis of this master regulator of flower development. They will undoubtedly open up new avenues for experimentation that will lead to an even deeper mechanistic understanding of the activities of LFY during plant reproduction.

REFERENCES
Busch MA, Bomblies K, Weigel D. 1999. Activation of a floral homeotic gene in Arabidopsis. Science 285, 585-587. http://doi.org/10.1126/science.285.5427.585

Hames C, Ptchelkine D, Grimm C, Thevenon E, Moyroud E, Gerard F, Martiel JL, Benlloch R, Parcy F, Muller CW. 2008. Structural basis for LEAFY floral switch function and similarity with helix-turn-helix proteins. Embo Journal 27, 2628-2637.  http://doi.org/10.1038/emboj.2008.184

Pajoro A, Madrigal P, Muino JM, Matus JT, Jin J, Mecchia MA, Debernardi JM, Palatnik JF, Balazadeh S, Arif M, O’Maoileidigh DS, Wellmer F, Krajewski P, Riechmann JL, Angenent GC, Kaufmann K. 2014. Dynamics of chromatin accessibility and gene regulation by MADS-domain transcription factors in flower development. Genome Biology 15, R41. http://doi.org/10.1186/gb-2014-15-3-r41

Parcy F, Nilsson O, Busch MA, Lee I, Weigel D. 1998. A genetic framework for floral patterning. Nature 395, 561-566. http://doi.org/10.1038/26903

Sayou C, Nanao MH, Jamin M, Pose D, Thevenon E, Gregoire L, Tichtinsky G, Denay G, Ott F, Peirats Llobet M, Schmid M, Dumas R, Parcy F. 2016. A SAM oligomerization domain shapes the genomic binding landscape of the LEAFY transcription factor. Nature Communications 7, 11222. http://doi.org/10.1038/ncomms11222

Weigel D, Alvarez J, Smyth DR, Yanofsky MF, Meyerowitz EM. 1992. LEAFY controls floral meristem identity in Arabidopsis. Cell 69, 843-859. http://dx.doi.org/10.1016/0092-8674(92)90295-N

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The interactions they are a changin’ – The complex role of protein interactions in the evolution of flower development

by Aalt-Jan Van Dijk

Among the various transcription factors involved in regulating flowering, no doubt MADS domain proteins involve some of the best studied. B-class proteins are a specific type of MADS domain proteins, named after their role in the classic ABC model for floral development. According to the ABC model, B-class proteins are involved in petal and stamen formation; for more background information on this model, you might want to read the recent post by Theissen and Parcy  (which focusses on other components of the ABC model, namely A-class proteins). B-class proteins can either form heterodimers, involving two different B-class proteins, or homodimers. Variation in B-class proteins has been suggested to be relevant for variation in floral organ development. However, a lot is still unclear about how variation in these proteins and their interactions influences phenotypic differences related to flowering. Better understanding of the evolution of B-class dimerization is clearly needed. A recent paper in Molecular Biology and Evolution  (Bartlett et al., 2016) uncovers various layers of complexity of this evolution.

First, Bartlett et al., 2016 characterized obligate heterodimerization versus homodimerization in taxa spanning the Poales (the order that contains the grass family), and found multiple transitions between factultative homodimerization and obligate heterodimerization. Such evolutionary changes were also present specifically within the grasses.

The next layer of complexity is, that there is a clear context-dependence of the effect of specific amino acids on the dimerization landscape. This is demonstrated by results from the experiments presented by Bartlett et al. to find sequence regions influencing homodimerization versus heterodimerization. These experiments involved three B-class proteins, two of which formed homodimers: J-PI (from the grass relative Joinvillea) and BdSTS1 (from Brachypodium distachyon) and a third one forming heterodimers (STS1, a maize protein). See figure for a schematic overview of the main findings of these experiments.

Figure1

Context-dependence of the effect of specific domains on dimerization.
Ovals represent B-class proteins: green, B. distachyon BdSTS1; blue, maize STS1; red, Joinvillea J-PI. Dashed line indicates homodimerization. The STS1 I-domain (small blue oval) disrupts homodimerization in the context of J-PI, but not so in BdSTS1. Similarly, the J-PI I-domain (small red oval) enables homodimerization of STS1, but the BdSTS1 I-domain (small green oval) does not.

It was found that the I-domain of J-PI   is sufficient for homodimerization of STS1; here the I-domain refers to a specific domain in MADS proteins. This domain is in fact known to be relevant for MADS domain interaction specificity in general. However the I-domain of BdSTS1 was not sufficient for homodimerization of STS1. Reciprocally, the STS1 I-domain was sufficient to abolish J-PI homodimerization but did not affect BdSTS1 homodimerization.  A comparison of I-domain sequence of STS1 and J-PI showed four amino acid differences. A single amino acid change (Gly81 to Asp) was sufficient to confer homodimerization ability on STS1, and the reciprocal change of Asp to Gly prevented J-PI from homodimerization. Intriguingly, however, the homodimerizing BdSTS1 I-domain also contains Asp at position 81, but this domain was not sufficient to confer homodimerization ability to STS1. BdSTS1 contains Ile at position 73, and introducing this Ile abolished the homodimerization capacity that the Gly81Asp mutation conferred on STS1. In brief, this indicates that a specific amino acid (Asp) can be sufficient to allow homodimerization in one sequence context but not so in another sequence context. This context-dependence of the role of specific amino acids provides insight to the multiple evolutionary routes via which B-class heterodimerization versus homodimerization evolved.

It is interesting to see that two computational methods contributed to the identification of relevant amino acids (Bartlett et al., 2016). One involves the analysis of positive selection. The other involves the prediction of interaction motifs. Both approaches were used for further identification of amino acids that contribute to dimerization landscape.

A final level of complexity in their analysis is the interconnectedness of coding and non-coding changes. Note that Theissen and Parcy on their post on the floral A-function gave an example of the importance of non-coding changes. Bartlett et al. found that the (homodimerizing) J-PI and the (non-homodimerizing) STS1 both showed similar rescue of an Arabidopsis pi mutant, and both could not rescue an ap3 mutant. (PI and AP3 are the two Arabidopsis B-class proteins). However, they found a distinction between J-PI and STS1 when they were expressed at a high level in developing sepals. Only J-PI expression resulted in transformation of the first whorl organs into petals. This shows that J-PI, when expressed at a high level in a novel domain, differs from STS1 in its effect on floral development. The J-PI homodimer on its own is not sufficient to confer B-class function in Arabidopsis, but as a novel protein complex in a novel domain it can effect phenotypic change. The interactions they are a changin – but the effect of changing protein interactions clearly depends on the expression pattern of the protein in question, and of its interactors.

Reference
Bartlett M, Thompson B, Brabazon H, Del Gizzi R, Zhang T and Whipple C. 2016. Evolutionary Dynamics of Floral Homeotic Transcription Factor Protein–Protein Interactions. Molecular Biology and Evolution 33(6):1486–1501. doi:10.1093/molbev/msw031

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