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Plant Science 180 (2011) 182–189

Contents lists available at ScienceDirect

Plant Science

journa l homepage: www.e lsev ier .com/ locate /p lantsc i

eview

romoting the promoter

incent Vedel ∗, Ivan ScottiMR ECOFOG, INRA, Ecological genetic, Campus Agronomique de Kourou, BP 709, 97387 Kourou, French Guiana

r t i c l e i n f o

rticle history:eceived 1 May 2010eceived in revised form3 September 2010ccepted 27 September 2010

a b s t r a c t

Recent evolutionary studies clearly indicate that evolution is mainly driven by changes in the complexmechanisms of gene regulation and not solely by polymorphism in protein-encoding genes themselves.After a short description of the cis-regulatory mechanism, we intend in this review to argue that by apply-ing newly available technologies and by merging research areas such as evolutionary and developmentalbiology, population genetics, ecology and molecular cell biology it is now possible to study evolution in an

eywords:is-Regulationvolutionary and developmental biologyntegrative evolutionlant development

integrative way. We contend that, by analysing the effects of promoter sequence variation on phenotypicdiversity in natural populations, we will soon be able to break the barrier between the study of extantgenetic variability and the study of major developmental changes. This will lead to an integrative viewof evolution at different scales. Because of their sessile nature and their continuous development, plantsmust permanently regulate their gene expression to react to their environment, and can, therefore, be

opulation geneticsranscription

considered as a remarkable model for these types of studies.© 2010 Elsevier Ireland Ltd. All rights reserved.

ontents

1. cis-Regulation: a central role in evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1821.1. cis-Regulation can explain both micro- and macro-evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1831.2. cis-Regulation is the key step of gene expression regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183

2. The transcription process, the promoter structures and how to find them . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1842.1. The transcription process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1842.2. The promoter structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1842.3. Identifying promoters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

3. Studying cis-regulatory sequences offers new perspectives for understanding evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1863.1. Studying cis-regulatory sequences in their ecological and evolutionary context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1863.2. An Evo-Devo approach to cis-regulation can explain macro-evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1863.3. A population genetics approach to cis-regulation can explain micro-evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1873.4. Studying the trans-regulators of cis-regulatory motifs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187

4. A step further: future developments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1885. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188

. cis-Regulation: a central role in evolution

Because of their sessile character and their continuous devel-

ing molecular regulation. Already previous studies have stressedthe fact that plant science might bridge molecular biology, ecologyand evolution [1] by using the model system Arabidopsis thaliana

pment, plants must constantly regulate and modulate theirevelopmental and homeostatic gene expression throughout theirntire life. These features allow them to react remarkably well tohe environment by physiological changes caused by the underly-

∗ Corresponding author. Tel.: +594 594329290.E-mail addresses: vincent.vedel@ecofog.gf, vinsvedel@gmail.com (V. Vedel).

168-9452/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved.oi:10.1016/j.plantsci.2010.09.009

as a basis. This is particularly true when it comes to the study ofthe evolutionary aspects of the complex mechanism of gene regu-lations [2,3].

Recent evolutionary studies, applying newly available tech-nologies (namely high-throughput sequencing and powerfulbioinformatics tools), clearly indicate that evolution is mainlydriven by changes in the complex mechanisms of gene regula-tion and not solely by polymorphism in protein-encoding genes

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hemselves [4–6]. The role of these two mechanisms in evolutions debated for a long time by the specialist community and this isllustrated by three world-leading scientists in the subject; Carroll’study [4], which favours the hypothesis of the central role of cis-egulatory regulations in evolution, found its antithesis by otheresults found by Hoekstra and Coynes’ lab [7], which gave birth to aamous argument between the two [8]. Nevertheless, both Carrolln one side and Hoekstra and Coynes on the other, agree that cis-egulatory mutations play a role in evolutionary change, althoughhe latter think that mutations in coding regions and other typesf regulation of the transcription process, besides mutations in cis-egulatory sequence, have also essential functions in evolution.

An investigation based on two yeast species and their hybridhows also that modifications of gene regulatory networks pro-oke gene expression divergence, and finally that the degree of thisivergence correlates with the capacity of genes to respond to thenvironment [9].

Several studies with animals demonstrated that only a fewutations in regulatory elements can reduce gene expression, and

ventually produce great morphological changes such as the lossf pelvic spines in the three-spined stickleback fish (Gasterosteusculeatus) [10], the modification of beak shape in finches [11] orhe darkening of the fruit fly wings (Drosophila melanogaster) [12].he first cited study demonstrates also that control of gene expres-ion is central for “quick” adaptation [10], loosely defined as anvent of increase in mean population fitness that occurs withinew (tens of) generations (see the end of chapter 2 for an expla-ation of why promoters may be prone to provoke adaptation in ahort evolutionary time). Significant physiological variations werebserved between chimps and humans, despite almost identicalets of proteins [13]. In the same idea, cnidarians and mammalssituated at the two most distant clades in the animal king-om phylogeny) share most of their developmental genes withheir common ancestors, but obviously have completely differenthenotypes [14,15]. Following this idea, numerous studies illus-rate the conservation of the same genes in development (e.g.,ox genes [16–18] are conserved among all organisms includ-

ng between plants and animals (reviewed in [19])). These genesre extremely well conserved between phyla and eventually pro-uce very different developmental outcomes. Regulation of theseenes differs between phyla and contributes to build very differentrganisms.

The liberation of the kernel from the hardened protective cas-ng during maize domestication (which facilitates edibility) is dueo human selection through the choice of seeds producing plantsith kernels easy to use as a food source [20]. This molecular evo-

ution analyses indicate that this significant morphological changeas controlled by a single gene, tga1, and only the regulatory regionad been the target of selection. In the same biological model, aransition in developmental plan (i.e., shortening of branches) wasue to evolutionary changes in the promoter of the tb1 gene, whichid not affect the coding region. Wang et al. [21] first proved branch

ength is determined by the accumulation of tb1 mRNA; then theyhowed that this major morphological change is associated to theeduction of polymorphism in the regulatory region of the tb1 gene.hese results lead to the conclusion that maize domestication wasssociated to the selection of the allele coding for a high rate of tb1ccumulation, which causes shorter branches. Conversely, no sig-ature of selection could be detected in the protein-coding region.gain, a central phenotypic change is caused only by a change in theene’s regulatory sequence and not in the protein it codes for. These

wo studies demonstrate that, thanks to the effect of recombina-ion, selection can act precisely on promoter sequences withoutffecting downstream transcribed regions.

All these results demonstrate that the primary focus for a finecale study on phenotypic and genotypic evolution has to be based

e 180 (2011) 182–189 183

on the study of cis-regulatory networks and not solely on presenceor absence of genes or on mutations in coding regions [22].

1.1. cis-Regulation can explain both micro- and macro-evolution

Evolutionary mechanisms are often divided into two types: (1)the macro-evolutionary ones, which lead to evolutionary noveltiesand differences between clades above species level, such as majorbody plan changes, and (2) the micro-evolutionary ones, whichproduce continuous phenotypic variation within and betweenpopulations (and between species during speciation processes).Evo-Devo (evolutionary and developmental biology) is a field thatfocuses on phenotypic evolutionary processes shaped by changesoccurring during development. A change in space, time or intensityof gene expression, during the development of an organism, willoften result in a different phenotype at sexual maturity. This mech-anistic approach well explains macro-evolution between cladesabove species level. Thus, the study of cis-regulation in key develop-mental genes results in a better understanding of the origin of majorphenotypic transitions. Conversely population genetics investi-gates polymorphisms among DNA sequences within species orspecies complexes. This genomic approach permits: (1) direct visu-alisation of DNA differences that may be the cause of phenotypicdifferences; and (2) assessment of whether these sequence variantsdiffer in frequency among populations and whether they are underselection. By applying these methods to regulatory sequences, wewould understand how changes in gene regulation affect the evolu-tion of adaptation to the environment and contribute to speciation.Such investigations would greatly advance our understanding ofthe role of regulatory sequences in micro-evolutionary processes.Thus, the study of cis-regulatory sequences provides an oppor-tunity to combine Evo-Devo and population genetics to improveour understanding of both micro- and macro- evolution, and tofurther our knowledge about the mechanisms of phenotype– andgenotype–environment interactions [5,22]. These methods are rou-tine and (for DNA sequencing) already high-throughput.

In this review we intend to argue that the time is ripe for merg-ing research areas that have been kept separate, and that the greatopportunities provided by current knowledge and methods willsoon disclose the links between the two. We contend that, byanalysing the effects of promoter sequence variation on pheno-typic diversity in natural populations, we will soon be able to breakthe barrier between the study of present genetic variability andthe study of major developmental changes. This will lead to anintegrative view of evolution at different levels.

1.2. cis-Regulation is the key step of gene expression regulation

There are several levels of control of gene expression, frominitiation of transcription until post-translational modifications.Initiation is the focus of cis-regulation, defined as the control oftranscription based on the interaction between short DNA motifs,situated on the same chromosome as the regulated gene, andtrans-proteins (called transcription factors or TFs). All the otherregulation steps are defined as ARLs (alternative regulatory levels)[23] including the role of small RNAs (e.g., microRNA) which controlgene expression patterns by acting as trans-factors [24–29].

Transcriptional regulation mechanisms vary among taxa andamong gene classes: for instance, the Saccharomyces cerevisiaePH05 gene is regulated at the chromatin- opening step [30–32]while the Drosophila Hsp70 gene is regulated at the pause-escape

step [33,34]. Nevertheless, as the fluctuation of cellular conditionsmodifies the concentration of proteins acting as TF cofactors [35],transcriptional initiation is not only the first step leading to geneexpression but also generally represents the key step in gene reg-ulation [35,36]; therefore we naturally concentrate our review

184 V. Vedel, I. Scotti / Plant Science 180 (2011) 182–189

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ig. 1. Role of cis-regulation in the different areas in genomic research. Studying theregulation) and, thus, whole DNA architecture in the genome. Part of the transcraving enhancers located in these regions. The arrow shows that the transcriptome

n cis-regulation. Its position in genomic studies is described inig. 1. In the next sections we discuss cis-regulation mechanismsn depth; we also describe the tools available to investigate regu-atory sequences and the promising issues and perspectives they

ill offer in the next years.

. The transcription process, the promoter structures andow to find them

The next three paragraphs are a review of basic molecular biol-gy knowledge about promoters. Expert readers may directly jumpo the beginning of the 4th paragraph.

.1. The transcription process

The transcription of mRNA from DNA is a multistep process splitnto three main steps (initiation, elongation and termination). The

hole process was recently divided into eight separated phaseshat may limit or increase transcription rate [37]. During transcrip-ion, a DNA sequence is read by RNA polymerase; we will focus heren RNA polymerase II, which produces messenger RNA (mRNA) forll protein-coding genes. RNA polymerase II includes more than tenubunits and requires a set of transcription factors (TFs) (proteinsontaining one or more DNA-binding domains) to initiate transcrip-ion [38,39]. All these trans-acting proteins bind to specific sitesn the DNA (cis-regulatory elements) and shape the transcriptionrocess. More than 1500 TFs have been identified in plants [36]nd each of them influences the expression of hundreds of targetenes in complex signalling pathways [40,41]. cis-Regulatory ele-ents are short and variable motifs located in the DNA sequence,

hich bind to specific TF. The association of TFs to their specific

F binding sites largely depends on gene class and on cell, organnd organism identity. This characteristic allows an extremely fineegulation, depending more on the context than on the sequencetself: with few types of transcription factors, gene regulation can

A sequences represents one of the keys to understand dynamics of gene structurese (introns and untranslated regions in 5′ and 3′) belongs also to the regulome, byulated by the regulome and it is thus dependent on the regulatory mechanisms.

respond to a large number of signals mainly due to the cellularstate.

2.2. The promoter structure

Regulatory sequences (the whole cis-regulatory elements) arecomposed of: a core promoter of about 200 base pairs near the tran-scription start site (TSS), situated at the 5′ end of genes; proximalregulators situated on either side of this core promoter downstreamor upstream; and finally remote regulators called enhancers, whichcan be in the introns of the gene or several kilobases upstream ordownstream [38,42]. Autonomous enhancer modules may vary insize from 50 bp to 1.5 kbp [43] and enhance the transcription levelsof a gene by binding activator proteins and not by acting directly tothe TF motifs.

There are several classes of structurally different core promot-ers in eukaryotes (Fig. 2). The most common class of promoters andthe easiest to identify possesses a TATA-box (a short motif looselyhomologous to the nucleotide sequence that provides its name),located 30 bases upstream of the transcription start. It is bound bya protein subunit called TBP (TATA binding protein) [44,45]. Somepromoters do not have a TATA-box (referred to as TATA-less). Inthese promoters, the exact position of the TSS may instead be con-trolled by another basic element known as the initiator with a looseconsensus PyPyAN[TA]PyPy, where Py is a pyrimidine (C or T) andN any nucleotide. This type of promoter is typically weaker thanthe TATA-box-containing ones [46]. In some TATA-less promoters,a downstream promoter element (DPE) assists the initiator in con-trolling precise transcription initiation. This promoter element is

located 30 bp downstream of the TSS and plays a role similar toa TATA-box, although with weaker effects (Fig. 2). Interestingly,some promoters lack all of these motifs, yet they are functional.Also, a core promoter often needs enhancers see above to sustaintranscription in vivo [47,48].

V. Vedel, I. Scotti / Plant Science 180 (2011) 182–189 185

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ig. 2. General structure of a cis-regulation sequence. It is divided into the core prolymerase binding sites (TATA-box, initiator and downstream promoter elementownstream or upstream of the promoting sequence.

These cis-regulatory elements are the functional DNA sequenceshat, by their modular and combinatorial nature, precisely controlemporal and spatial expression patterns of the tens of thousandsf genes expressed in higher eukaryotic cells: cis-elements arerouped into different cis-regulatory modules and integrate theombined signals of multiple TFs. This results in a highly specificnd nuanced pattern of gene expression [40]. Promoters are char-cterised by modularity and redundancy of regulatory sequenceotifs; moreover the order in which the latter appear is relatively

rrelevant for promoter functionality. As a consequence, recombi-ation and mutation can be expected to provoke fewer deleteriousffects on gene function, and at the same time to produce largerariability, when they occur in promoters than when they hit pro-ein coding regions. As a consequence, a large population mayarbour several functional, although slightly different, variants ofgene’s promoter; this variability will be the raw material that

llows selection to rapidly lead to new adaptive equilibria. Glob-lly, promoters are characterised by a higher degree of modularityhan proteins (motifs are shorter than protein domains and moreumerous per promoter than domains are per protein); as a conse-uence, new functional assemblages in regulatory sequences maye easier to obtain than in transcribed regions and therefore regu-

atory sequences can be less conserved than the coding ones whileetaining their functionality.

.3. Identifying promoters

In spite of the complexity and diversity of promoter motifs, sev-ral ways to identify promoter sequences and their TF binding sitesxist. For model system organisms such as D. melanogaster, Caenor-bditis elegans, Homo sapiens in animals, or A. thaliana, Zea maysnd Populus trichocarpa for example in plants, the genome has beenntirely sequenced, and promoters can be found positionally – byooking at sequences upstream of coding regions. With the rise ofext-generation sequencing, this list is increasing quickly. The sec-nd approach is more laborious but can be applied to almost everyrganism. Based on known coding sequences, promoter sequencesre isolated by techniques such as either Tail PCR [49] or gene walk-ng [50], which rely on the possibility to extend primers, designedn the known sequence, to obtain unknown, neighbouring genomicequences by PCR.

Promoter sequences thus identified have to be then analysednd annotated using dedicated bioinformatic tools. This analysisims to identify potential cis-regulatory elements including coreromoters and other TF binding sites. Recognising these elements

y eye in a sequence is almost impossible, as each motif may beighly degenerate; actually the functional meaning of motifs, andf sites within motifs, is highly context-dependent, and the recog-ition of an active motif solely based on its composition is largelyisleading. Another difficulty of identifying TF motifs is due to the

rs, which are generally located between 0 and −200 bp downstream and are DNAinding sites, and enhancers, situated on the same chromosomes but possibly far

high variability of these independent short motifs, which makescomparison between genes or gene families quite complicated.Thousands of types of transcriptional regulatory sequences existand many remain still uncharacterised. Because of their modularstructure these so-far undetected promoters may be composed ofmodules that appear in known regulatory sequences, but in entirelynew combinations which will often be missed by visual inspectionor even by plain sequence alignment. The use of different recogni-tion algorithms is indispensable.

Several programs are currently available and broadly used tosearch for TF motifs, to predict TF motifs and even to predictwhole promoters [35,40,51]. Some are generalists for all organisms,while others exclusively focus on plant promoters (PLACE (Plantcis-acting regulatory DNA elements) [52], Strawberries TSSP [53]).

Some algorithms (e.g., PLACE [52]) analyse a given sequence andidentify potential TF binding sites, already described in databases,they look only for single TF binding sites without considering theneed for potential association with other sites to form an activecis-complex of transcription. The main advantage of this type ofprogram is also its main drawback: it identifies each putative motifindependently, without attempting to integrate them in a promoteror verifying that their position (e.g., relative to coding regions)matches their putative function. It takes into consideration mod-ules one by one and not altogether. Regulatory regions are searchedfor by similarity with regulatory sequences characterised in othergenes and in other organisms. The interpretation of the resultsand therefore the decision whether the recognized TF binding sitesbelong to a promoting region or not, is entirely left to the user.

Another type of software (e.g., Strawberries TSSP [53] and Prom-search [54]) answers the question “Does this sequence contain apromoter? If yes, where are its TF binding sites?” For this purpose,they make use of several algorithms for the prediction of promot-ers, TSS, and TF binding sites in eukaryotic DNA sequences. Theydo not search for single TF binding sites but for a combination ofmotifs with a known transcriptional function; they assume that co-regulated genes share similar TF binding motifs. Then, the numberof observed 3–6-bp motifs found in the sequence is compared tothe number expected by chance specifically for each motif in eachspecies, based on sequence nucleotide composition. Sequences thatshow a significant departure (excess of motifs) from random expec-tation are considered as true promoters. The advantage of thismethod is that the results about individual motifs are integratedto estimate the overall probability that the target sequence as awhole belongs to a promoter. The programs determine whetherthe concentration of potential TF binding motifs is high enough

to form a promoter. They take into consideration the combinato-rial dimension of a promoter and avoid therefore many potentialTF binding motifs which have no transcriptional function. Theyalso provide the structure and the position of TSSs (there maybe several) and TF binding sites. Nonetheless, many authors do

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ot consider these algorithms as powerful enough yet to be useds standalone tools in promoter search [35,40,51,55,56]. Becausef the complexity of TFB site characterisation, these algorithmsave high false positive and false negative error rates. For instance,ATA-box weight matrices (that identify potential TATA-boxes)redict on average one TATA-box every 120 bp [55], which leadso the identification of large numbers of false positives. In addition,he databases used to predict promoters are still incomplete, andumerous promoters are not recognized (especially the complexnes such as TATA-less promoters). The same sequence, analysedy different promoter prediction programs, might give differentesults. Improvements are regularly being made to predict theseites, for example at the DNA sequence level, by adding parame-ers such as phylogenetic footprinting, a method which comparesenomic sequences between related species to find conserved reg-latory elements [57]. Another approach, which participates torediction algorithms improvement, consists of adding to algo-ithms for TF binding site detection, a background model by Gibbsampling (a stochastic maximum likelihood algorithm that esti-ates the probabilistic model parameters of clustered TF bindingotifs [58]).We reckon that a mix of the two types of software described

bove is necessary to confirm the presence of TF binding sites and aotential promoter. Although some very good step-by-step meth-ds to safely characterise promoter regions are available in theiterature [54], a personal combination of analyses with all theseoftware packages, adjusted to the types of genes and organismsnder scrutiny, remains the best option.

Obviously, describing promoter sequences is not the end of thetory. A precise knowledge of their interactions with transcrip-ional regulators is also necessary. As the accumulation of DNAequence data accelerates, molecular cell biology must follow athe same pace, for DNA sequence information to be really use-ul. Therefore, methods to study regulatory mechanisms must alsonter the high-throughput stage. In order to investigate transcrip-ion factors, high-throughput immunoprecipitation techniques areeing developed in many organisms such as yeast [59], mammals60,61], plants [62,63] where genome-wide analyses of transcrip-ion factor binding sites, based on chromatin immunoprecipitationt high scale, were already successful. Chromatin immunoprecip-tation (ChIP) is a well-established procedure used to investigatenteractions between proteins and DNA. Recent studies demon-trated the possibility of describing how TFs choose specific bindingites by studying their interactions with sequences in the wholeenome [35]. A combination of the study of RNA polymerase II tran-cription cycle with genome-wide mapping of transcription factorso identify key regulatory steps and factors of gene regulation waslso recently performed [40]. The integration of all these data couldink the presence of the TF-binding motifs in the sequence, celltates, the presence of the TFs, and their interactions with RNAolymerase II, the activity of this polymerase II and finally generanscription levels. All cis- and trans-elements could be measuredn the specific context, and the result of gene expressions quantifiedy micro-array.

. Studying cis-regulatory sequences offers newerspectives for understanding evolution

Most studies of promoter regions stress the limits of our capacitynd tools to study them. Thanks to recent technological advances,

e are offered new possibilities to study cis-regulatory regions.

ome are already feasible but not widely applied yet; others will ben the near future. Here we will detail the innovative perspectiveso understand macro- and micro-evolutionary processes from anntegrative point of view.

ce 180 (2011) 182–189

3.1. Studying cis-regulatory sequences in their ecological andevolutionary context

We will demonstrate here that analysing promoter regions andtheir TF binding sites will unravel mechanisms of macro- andmicro-evolution at different scales, from gene expression to thecommunity level (Fig. 3). This means that new methods for high-throughput analysis of regulatory sequences can join forces notonly to link within-species genetic diversity with large-scale evo-lutionary patterns, but also to connect with ecological studies thataim at the identification of the interactions between species in com-munities [64]. This is possible by understanding interactions amongand between genes and ecological forces shaping community com-position. This can be done by comparing large sets of cis-regulatorysequence of genes coming from individuals located at differentenvironmental conditions [64,65] to provide crucial informationabout the degree at which plant communities are shaped by neutralor adaptive forces [66,67].

Most if not all studies of promoter sequences have focused onthe mechanisms that govern their functions, without accounting forthe evolutionary forces and constraints that may have determinedtheir structure and function over evolutionary time in natural pop-ulations. In plants, only one study has attempted to bridge this gap,focusing on the evolution of light-regulated plant promoters [68].The authors found that flowering plant light-responsive element(LRE) genes share promoter motifs with LRE genes from conifers,ferns and mosses and that structurally similar promoters play simi-lar roles in these very distantly related plant taxa. These later groupsare more ancient than flowering plant and their LRE genes do nothave a function in light response, but might have another role. Theauthors concluded, therefore, that composite LRE genes might haveevolved from ancient cis-regulatory modules involved in other pro-moter functions. This type of study should be extended to a largerscale to gain both wider knowledge about regulation sequencestructures and to build a complete reference database. Compar-ison of the cis-regulatory sequence structures and their putativefunctions would unravel gene promoter history and evolutionarytrends.

3.2. An Evo-Devo approach to cis-regulation can explainmacro-evolution

Such a strategy could be advantageous in an evolutionary aswell as in a developmental biology perspective. Comparing pro-moter sequences of developmental genes, with their expressionpatterns, across taxa could unveil the role of regulatory motifsduring development. The two main techniques used in Evo-Devoto investigate gene expression are in situ hybridization and RNAinterference. They specifically (and respectively) show the spatio-temporal expression pattern of developmental genes in wholeembryos and the function of these genes by focusing on vari-ations in mRNA concentration. Comparative methods should beapplied to the analysis of promoter sequence differences amongorganisms with divergent spatio-temporal or functional patternsof gene the expression, to identify the link between promotersequence variation and gene expression modulation. As Evo-Devomethods analyse mRNA, and therefore transcriptional processes, itshould be easy to establish a causative link between promoter vari-ability (that drives variability in transcription levels) and mRNAsynthesis and expression (which are driven by promoters). Thiswas already recommended and applied in some reviews [5] to

investigate macro-evolutionary processes. Plants are particularlyinteresting for such a study due to their lifetime continuous devel-opment. Studying multiple genes in known regulatory networkswith this approach may lead to disclosure of the complex inter-actions between gene function, genetic variability and regulatory

V. Vedel, I. Scotti / Plant Science 180 (2011) 182–189 187

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ig. 3. The different levels of evolution accessible by studying cis-regulatory sequencecond level describes the biological phenomena, within these fields, concerned. Tho the study of the cis-regulatory sequences. Analysis of these sequences drives us t

etwork structure. For example, the fascinating enigma of plantvolutionary novelties such as leaf morphogenesis [69], the devel-pment of drought resistance [70] and the establishment of floralymmetry [71] might be solved.

.3. A population genetics approach to cis-regulation can explainicro-evolution

In addition, although most developmental geneticists concen-rate on major mutations, the comparison of polymorphisms (i.e.,NPs in [72]) in promoter sequences could also provide insights ondaptation and micro-evolution. Accumulation of polymorphismn natural populations is the basis and the raw material for adap-ation and speciation [5]. Quick local adaptation is an evolutionaryhenomenon that may be caused by changes in gene regulationather than by protein sequences [5]. Plants, due to their sessileifestyle, provide excellent model studies for investigating pop-lation structure and molecular adaptation to the environment.he comparison of regulatory sequences of individuals belongingo different populations or ecotypes could show motifs adaptedo specific environmental conditions; the direction and nature ofelection on promoters could be analysed through population-enetic statistical methods based on the standard neutral modelf molecular evolution [5,73,74] and on a derivation of Wright’s F-tatistics [75,76]. In both cases the strategy is to compare patterns ofequence diversity to the expectations provided by a neutral model;oci that do not conform to these expectations are considered toe under selection. Then, one could conclude whether selectionhapes promoter sequences, and compare selective pressure lev-

ls on regulatory and protein-coding sequences [20,21]. If selectionetermines population differentiation at promoter sequences, thenhese sequences may even be used to identify populations adaptedo different environments, by comparing genetic divergence in pro-

oters and habitat divergence. The study of local adaptation should

e first level (from top to bottom) indicates the different research areas involved. Thed level shows the type of cis-regulatory mechanisms involved. They all converged

ntegrative view of evolutionary mechanism, from gene to phylum level.

be carried out in natural environments to account for complexecological interactions and therefore avoid simplifying biases. Thisapproach, applied for instance to stress response genes, could tellus by which genetic mechanisms two closely related plant speciescould be adapted to two different habitats. This would represent afirst, but paradigmatic, step towards the understanding of differ-entiation through local adaptation between closely related speciesand between populations.

3.4. Studying the trans-regulators of cis-regulatory motifs

Finally, high-throughput specific immunoprecipitation, whichwill be soon developed, applied to many individuals (from popula-tions to phylum level), would provide the type, the concentrationand the spatio-temporal distribution of specific transcription fac-tors in relation to a specific pattern of gene activation and to theTF binding structure of a gene [40]. New advances in molecular cellbiology pave the way to a precise understanding of transcriptionmechanism itself. When this technique will be available, we willbe able to study the differential affinity of the same TF for differentvariants of the same promoter and of different variants of the sameTF protein for the same promoter sequence, belonging to taxonom-ical groups or populations adapted to different habitats. Then, bycomparison, it could be possible to link environmental impact andcomplex protein–DNA interactions at the transcriptional level. Thisapproach can be completed by the brand new evolutionary modelfor promoters Sunflower [77], which predicts binding profiles ofTFs to DNA motifs by using population genetics tests. This wouldresult, in the medium term key, in a general better understand-

ing of the interaction between proteins and DNA and even someepigenetic mechanisms.

Thus, the potential results of a combinatorial approach to study-ing cis-regulation would explain evolution as an integrative phe-nomenon by describing and connecting: (1) macro-evolutionary

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echanisms such as body plan evolution or evolutionary novelties,y linking developmental gene expression pattern and TF bind-

ng motifs; (2) micro-evolutionary mechanisms such as adaptationnd speciation, by looking at patterns of genetic diversity and ofignatures of selection acting on cis-regulatory sequences; (3) inter-ctions between cis-regulatory elements and trans-proteins in cellsy proteomics; and (4) consequences of environmental constraintsf specific habitats, on all the above mechanisms.

Applications of studies on promoters are still in their infancynd one of the “most attractive problems in sequence analysis”51], so we are entering an exciting time with the perspectives ofnravelling some fundamental evolutionary enigmas.

. A step further: future developments

Some complementary ideas, more speculative, using toolsxpected to be developed in the near future, could enrich cis-egulatory sequence studies by investigating molecular evolutionrom a wider perspective.

The specificity between a TF and its binding site depends onell state and determines the role of the gene in a given organism.herefore, characterising the affinity of variants of promoters to apecific TF, or the affinity of a specific promoter to different TFs, byighly sensitive protein–DNA crosslinking technologies, could pro-ide a better understanding of the role of TF–TF binding interactionsor several cell states. However, the breadth and depth these stud-es can reach still heavily depend on technological improvementsn sequencing, chromatin precipitation and microscopy techniques40].

As we have stated above, there are many steps controllingene expression, with more numerous and more complex feedbackoops of key signalling pathways in higher eukaryotes. It wouldlso be worthwhile to investigate these loops to fully understandene regulation mechanisms. For example, very little is knownbout the regulation of accessibility of genes to transcription byodification of chromatin condensation state, or about TF and

olymerase degradation rates. Understanding how promoter motifodules (combinations of motifs) regulate transcriptional kinetics,

ow alternative splicing profiles are determined, and how variousost-transcriptional steps, including the regulation of this post-ranscriptional step by miRNAs [25,37] take place, would also beecessary.

Furthermore, we could also speculate whether plasticity and/orpigenetic mechanisms are based on cis- or trans-regulation. Plas-icity refers to cases in which a single genotype can produce aange of phenotypes in response to variations to external conditions78]. Epigenetics defines the inheritance of phenotypic variationaused by factors other than variation in the underlying DNAequence (e.g., DNA methylation) [79]. Both play a role in quickdaptive mechanisms (phenotypic changes take place in few gen-rations), which rely on transient changes in the expression profilef genes and do not depend on standing genetic variation. Regula-ory sequences are the ideal target for such mechanisms, as theyontrol gene expression and regulatory networks. The activity ofranscription complexes depends on secondary and tertiary struc-ures of double-stranded DNA and chromatin [10,80,81]; it mighte interesting to combine studies of cis-regulatory mechanismsith investigations of epigenetic processes, studied by Chromatin

mmunoprecipitation for example at the chromatin level. Such inte-rative studies would help to understand whether plasticity and/or

pigenetic effects are more likely to be caused by cell state, throughhe action of TF and their cofactors, or by transient, covalent mod-fications of DNA sequences or their associated proteins. Plasticityould be the consequence of these interactions between geneticnd epigenetic mechanisms in quick evolution.

[

[

ce 180 (2011) 182–189

5. Conclusion

Studying transcriptional regulatory sequences is central tounderstanding of both micro- and macro-evolution. By combiningEvo-Devo and population-genetic approaches, the barrier betweenthese two research areas can be cracked, and mechanisms of evolu-tion can be studied in an integrative way. Due to their complexityand their multiple interactions, cis-regulatory sequences shouldalso be studied in their ecological contexts, in situ, to avoid anyexperimental bias. Specifically, characterisation of these sequencesand their interactions with trans-proteins will permit us to under-stand mechanisms of evolution in the broad sense at many levels,from single gene to body development plan to ecological interac-tions.

The ultimate aim is to obtain an integrative map of the regula-tory network of each organism [56], in an evolutionary context. AsPan et al. stated [35], “increasing complexity in organisms may lead,from an evolutionary standpoint, to a better–orchestrated cellu-lar network”. Therefore, understanding the complexity of the generegulation with all its subtleties would represent a major step inthe comprehension of evolutionary and adaptive mechanisms incomplex organisms such as plants.

Acknowledgements

The authors are grateful to Ana Stambolia-Kovach and CarolLoopstra from scientific advices on promoter works. We also thankfour anonymous reviewers who gave constructive and helpfulcomments on the manuscript. This research was funded by INRA(Institut National pour la Recherche Agronomique) “Hagneré” post-doc program and the EU-funded ENERGIRAVI project.

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