Literature DB >> 29106624

Regulation of flowering time: a splicy business.

Rainer Melzer1.   

Abstract

Entities:  

Keywords:  Alternative splicing; Arabidopsis; FLM isoforms; FLOWERING LOCUS M (FLM); flowering time; temperature-dependent mediated flowering

Mesh:

Substances:

Year:  2017        PMID: 29106624      PMCID: PMC5853935          DOI: 10.1093/jxb/erx353

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


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The mechanisms regulating flowering time at ambient temperatures are controversial. One hypothesis ascribes prominent roles to two competing protein isoforms of FLOWERING LOCUS M (FLM) which are produced by alternative splicing. Now, Few decisions in life are more important than getting the time for reproduction right. If a bad choice is made one may not be able to find a suitable partner, conditions for producing progeny might be suboptimal or the progeny might be forced to grow up in an unsuitable environment. To prevent that, elaborate mechanisms have evolved in many species. In plants, the switch from vegetative to reproductive development is controlled by dozens of genes integrated in numerous well known pathways (Srikanth and Schmid, 2011). However, it was discovered only relatively recently that ambient temperature plays a critical role in controlling flowering time: many Arabidopsis ecotypes flower substantially earlier at 27°C than at the more usual growth temperature of 23°C (Balasubramanian ). This ambient temperature pathway has been the subject of intense research over the past few years, not least because in times of global warming the analysis of genetic circuits responding to temperature changes has gained considerable importance. One of the key genes identified was FLOWERING LOCUS M, which encodes a MADS-domain transcription factor (Scortecci ; Balasubramanian ). In Arabidopsis plants in which FLM is deleted, early flowering is observed no matter whether the plants are grown at 23°C or 27°C (Balasubramanian ). This indicates that FLM is a repressor of early flowering at lower temperatures (Balasubramanian ). To exert its repressive effect, FLM interacts with another MADS-domain protein, SHORT VEGETATIVE PHASE (SVP) (Lee ). Like FLM, SVP is also involved in regulating flowering time at ambient temperatures (Lee ). The current view is that SVP/SVP homomeric and SVP/FLM heteromeric protein complexes delay flowering at lower temperatures by repressing genes that act as floral activators (Lee ; Pose ). But exactly how is this repression released at higher temperatures? In the case of SVP, one hypothesis is that the protein shows a marked decrease in stability at higher temperatures (Lee ). FLM, on the other hand, is subject to alternative splicing, and the occurrence of specific splice forms is correlated to the growth temperature (Balasubramanian ; Pose ). The two major splice forms of FLM are designated FLM-β and FLM-δ (Scortecci ). FLM-β is the predominant transcript at lower temperatures, whereas FLM-δ appears to be more enriched at higher temperatures (Pose ). The FLM-β and FLM-δ proteins are capable of interacting with SVP. However, only FLM-β and not FLM-δ forms DNA-binding complexes with SVP (Pose ). In addition, overexpression of FLM-β resulted in late flowering, whereas overexpression of FLM-δ led to earlier flowering in comparison to wild-type plants (Pose ). This gave rise to an appealing hypothesis: the FLM-β and FLM-δ proteins compete with each other in binding to SVP. However, only the FLM-β/SVP complex is capable of repressing flowering, because FLM-δ/SVP lacks DNA-binding activity. At lower temperatures, FLM-β/SVP and SVP/SVP complexes predominate and hence flowering is repressed. In contrast, with an increase in temperature, FLM-δ becomes more abundant, outcompetes FLM-β and SVP itself for SVP binding and hence flowering is activated (Pose ).

FLM-δ under scrutiny

However, as exciting as the hypothesis of a dominant-negative protein variant generated by alternative splicing is (especially for those researchers with a strong interest in the biophysics of transcription factor functions), it has been challenged in recent years. For example, although FLM-β transcripts decrease with increased temperatures, a concomitant increase in FLM-δ cannot always be detected (Sureshkumar ). Those and other findings led to the competing hypothesis that the decrease in FLM-β transcripts (and with this FLM-β protein) is the main determinant of early flowering at higher temperatures and that the contribution of the FLM-δ protein is negligible (Lutz ; Sureshkumar ; Lutz ). Capovilla take a fresh look at the role of FLM-δ in flowering-time regulation. Towards that goal, they produced Arabidopsis lines that are incapable of expressing either FLM-β or FLM-δ . To circumvent potential problems and artefacts associated with the expression of transgenic FLM versions, the genomic FLM locus was edited using CRISPR-Cas9, creating plants that lacked either the 2nd or 3rd exon of FLM. As the 2nd exon is part of the FLM-β but not of the FLM-δ transcript, plants lacking it can produce FLM-δ but not FLM-β . Conversely, plants lacking the 3rd exon are incapable of producing FLM-δ but can produce FLM-β . This set-up makes it possible to more clearly distinguish whether the FLM-δ transcript (and protein) plays an important role in controlling flowering time: if the FLM-δ protein is a dominant-negative version that competes with FLM-β for binding to SVP (Pose ), plants expressing only FLM-δ might be expected to flower earlier than flm loss-of-function mutants. This is because in those plants FLM-δ would prevent SVP homodimer formation (something that wouldn’t be possible in flm loss-of-function mutants) and hence flowering can proceed. This, however, was not observed. The ‘FLM-δ only’ plants flowered as early as full loss-of-function mutants, indicating that there is no substantial dominant-negative effect exerted by the FLM-δ protein. Thus, the results clearly favour the idea that decreasing levels of the FLM-β transcripts alone trigger flowering at elevated temperatures (Capovilla ).

Splicing and the quest for the temperature signalling pathway in plants

One surprising result from the study of Capovilla was that plants only capable of producing FLM-β and not FLM- δ flowered later than wild-type plants. This is initially not easy to reconcile with the idea that FLM-δ is a non-functional transcript. After all, if FLM-δ has no function, why should it matter whether the plant is capable of producing it? Transcript analysis provides an important clue here: the results of Capovilla and others (Sureshkumar ) indicate that the temperature-dependent variation in FLM-β levels is not achieved by different rates of transcription but by alternative splicing. At higher temperatures, splicing produces less FLM-β and more alternative transcripts, among them FLM-δ but also others, many of which contain premature stop codons and may be subjected to nonsense-mediated decay (Sureshkumar ). Intriguingly, one of the major temperature-sensitive splice donor sites that is predominantly used at higher temperatures is that of intron 3, and exactly that site was removed in the ‘FLM-β only’ plants (Sureshkumar ; Capovilla ). So, what presumably happens in those plants is that more FLM-β is produced because the alternative splice site for producing FLM-δ and other splice variants is missing. And more FLM-β leads to delayed flowering. This highlights an important corollary of alternative splicing: the production of alternative, non-functional transcripts can be an important regulatory mechanism to reduce the amount of functional transcripts (Reddy ). It is becoming increasingly clear that transcript abundance of many genes is regulated by this ‘alternative splicing nonsense-mediated decay’ pathway (Reddy ). Interestingly, many of the RNA-binding proteins implicated in alternative splicing are subject to alternative splicing themselves, and this splicing can also be susceptible to temperature variations (Lazar and Goodman, 2000; Duque, 2011; Capovilla ). It is therefore tempting to speculate that the temperature-dependent variation in abundance and/or activity of splicing factors is responsible for temperature-dependent splicing of FLM (Box 1). An ‘alternative splicing–alternative splicing’ cascade may exist in which FLM utilizes a pre-existing circuit that is susceptible to temperature variations (Verhage ). Importantly, it was recently discovered that Phytochromes act as temperature sensors in plants and that they possess RNA-binding activity (Jung ; Legris ; Reichel ). One may therefore speculate that Phytochromes act as splicing factors that are involved in the temperature-dependent regulation of FLM (Köster ). In general, the secondary structure of RNA is also highly susceptible to temperature changes and an important factor that determines splicing patterns (Reddy ; Vandivier ). It does therefore also appear possible that the structure of the FLM pre-mRNA or the pre-mRNA structure of a splice factor acts as a sensor in the ambient temperature pathway (Box 1). This would also explain why a more ‘common’ developmental mechanisms of transcript abundance regulation, like a temperature-dependent rate of transcription, is not observed for FLM: if the RNA of FLM or a splice factor is a temperature sensor, FLM has to be expressed to sense the temperature.

Rise and fall of a hypothesis

The achievements in unravelling the molecular mechanism of FLM function notwithstanding, the study by Capovilla might be even more important from the perspective of how science is conducted. The original idea of FLM-δ acting as a dominant-negative protein version made perfect sense at the time it was published (Pose ). Indeed, it soon became a standard example on the importance of protein isoforms produced by alternative splicing in plants (Staiger and Brown, 2013; Pajoro ). But subsequent papers didn’t find evidence for an important role of the FLM-δ protein (Lutz ; Sureshkumar ; Lutz ). So, the same group that developed the original hypothesis was also involved in studies contradicting it (Lutz ), and with Capovilla they themselves provided the last nail in the coffin of the FLM-δ hypothesis. This is the essence of how science should be conducted: formulating a hypothesis, testing it rigorously and, if necessary, rejecting it. However, we all know that this is not always easy. As Max Planck once put it (Planck, 1949): ‘A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.’ Capovilla prove that this is not always the case and that scientists can (and maybe more often should) change their mind in the light of new evidence.

Box 1. Hypothetical scenario as to how FLM controls flowering time in response to temperature differences

At lower temperatures (left), the FLM pre-mRNA is correctly spliced, yielding the FLM-β transcript. The FLM-β protein represses flowering. At higher temperatures (right), splicing is disturbed, triggering nonsense-mediated decay through premature stop codons (red octagon). Consequently, less (or no) FLM-β protein is produced and flowering is activated. FLM-δ is very likely also produced, but is not shown here as the protein presumably has no role in flowering-time regulation. The presence/absence of splicing factors (SF) may contribute to alternative splicing. It is not yet entirely clear how plants sense temperature differences, but one possibility is that temperature-dependent RNA structures (symbolized by the presence/absence of the stem-loop structure) are involved.
  22 in total

1.  Regulation of temperature-responsive flowering by MADS-box transcription factor repressors.

Authors:  Jeong Hwan Lee; Hak-Seung Ryu; Kyung Sook Chung; David Posé; Soonkap Kim; Markus Schmid; Ji Hoon Ahn
Journal:  Science       Date:  2013-09-12       Impact factor: 47.728

Review 2.  Alternative splicing at the intersection of biological timing, development, and stress responses.

Authors:  Dorothee Staiger; John W S Brown
Journal:  Plant Cell       Date:  2013-10-31       Impact factor: 11.277

Review 3.  RNA-Binding Proteins Revisited - The Emerging Arabidopsis mRNA Interactome.

Authors:  Tino Köster; Claudius Marondedze; Katja Meyer; Dorothee Staiger
Journal:  Trends Plant Sci       Date:  2017-04-12       Impact factor: 18.313

Review 4.  Regulation of flowering time: all roads lead to Rome.

Authors:  Anusha Srikanth; Markus Schmid
Journal:  Cell Mol Life Sci       Date:  2011-04-06       Impact factor: 9.261

5.  Identification of a MADS-box gene, FLOWERING LOCUS M, that represses flowering.

Authors:  K C Scortecci; S D Michaels; R M Amasino
Journal:  Plant J       Date:  2001-04       Impact factor: 6.417

6.  Temperature-dependent regulation of flowering by antagonistic FLM variants.

Authors:  David Posé; Leonie Verhage; Felix Ott; Levi Yant; Johannes Mathieu; Gerco C Angenent; Richard G H Immink; Markus Schmid
Journal:  Nature       Date:  2013-09-25       Impact factor: 49.962

Review 7.  The (r)evolution of gene regulatory networks controlling Arabidopsis plant reproduction: a two-decade history.

Authors:  Alice Pajoro; Sandra Biewers; Evangelia Dougali; Felipe Leal Valentim; Marta Adelina Mendes; Aimone Porri; George Coupland; Yves Van de Peer; Aalt D J van Dijk; Lucia Colombo; Brendan Davies; Gerco C Angenent
Journal:  J Exp Bot       Date:  2014-06-09       Impact factor: 6.992

8.  Phytochrome B integrates light and temperature signals in Arabidopsis.

Authors:  Martina Legris; Cornelia Klose; E Sethe Burgie; Cecilia Costigliolo Rojas Rojas; Maximiliano Neme; Andreas Hiltbrunner; Philip A Wigge; Eberhard Schäfer; Richard D Vierstra; Jorge J Casal
Journal:  Science       Date:  2016-10-27       Impact factor: 47.728

9.  Potent induction of Arabidopsis thaliana flowering by elevated growth temperature.

Authors:  Sureshkumar Balasubramanian; Sridevi Sureshkumar; Janne Lempe; Detlef Weigel
Journal:  PLoS Genet       Date:  2006-05-26       Impact factor: 5.917

10.  Natural haplotypes of FLM non-coding sequences fine-tune flowering time in ambient spring temperatures in Arabidopsis.

Authors:  Ulrich Lutz; Thomas Nussbaumer; Manuel Spannagl; Julia Diener; Klaus Fx Mayer; Claus Schwechheimer
Journal:  Elife       Date:  2017-03-15       Impact factor: 8.140

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  7 in total

1.  Regulation of flowering time using temperature, photoperiod and spermidine treatments in Anoectochilus roxburghii.

Authors:  Tingting Han; Enting Xu; Linna Yao; Bingsong Zheng; Adnan Younis; Qingsong Shao
Journal:  Physiol Mol Biol Plants       Date:  2020-01-01

2.  Global spatial analysis of Arabidopsis natural variants implicates 5'UTR splicing of LATE ELONGATED HYPOCOTYL in responses to temperature.

Authors:  Allan B James; Stuart Sullivan; Hugh G Nimmo
Journal:  Plant Cell Environ       Date:  2018-04-15       Impact factor: 7.228

3.  Identification of FT family genes that respond to photoperiod, temperature and genotype in relation to flowering in cassava (Manihot esculenta, Crantz).

Authors:  Oluwabusayo Sarah Adeyemo; Peter T Hyde; Tim L Setter
Journal:  Plant Reprod       Date:  2018-12-12       Impact factor: 3.767

Review 4.  RNA Splicing of FLC Modulates the Transition to Flowering.

Authors:  Hao-Dong Qi; Yi Lin; Qiu-Ping Ren; Yu-Yi Wang; Feng Xiong; Xiu-Ling Wang
Journal:  Front Plant Sci       Date:  2019-12-17       Impact factor: 5.753

Review 5.  Temperature-Dependent Alternative Splicing of Precursor mRNAs and Its Biological Significance: A Review Focused on Post-Transcriptional Regulation of a Cold Shock Protein Gene in Hibernating Mammals.

Authors:  Takahiko Shiina; Yasutake Shimizu
Journal:  Int J Mol Sci       Date:  2020-10-14       Impact factor: 5.923

6.  Genome-Wide Analysis of PEBP Genes in Dendrobium huoshanense: Unveiling the Antagonistic Functions of FT/TFL1 in Flowering Time.

Authors:  Cheng Song; Guohui Li; Jun Dai; Hui Deng
Journal:  Front Genet       Date:  2021-07-09       Impact factor: 4.599

7.  Multi-omics sequencing provides insight into floral transition in Catalpa bungei. C.A. Mey.

Authors:  Zhi Wang; Wenjun Ma; Tianqing Zhu; Nan Lu; Fangqun Ouyang; Nan Wang; Guijuan Yang; Lisheng Kong; Guanzheng Qu; Shougong Zhang; Junhui Wang
Journal:  BMC Genomics       Date:  2020-07-22       Impact factor: 3.969

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