Laurent Boudin
email: laurent.boudin@upmc.fr

Lisl Weynans
email: lisl.weynans@math.u-bordeaux1.fr

SPRAY IMPINGEMENT ON A WALL IN THE CONTEXT OF THE UPPER AIRWAYS *

We here address the modelling of an aerosol hitting the walls of the airways or an endotracheal tube used for a mechanical ventilation, and the possible creation of secondary droplets that may follow. We present a kinetic modelling of the spray-wall interaction and propose a boundary term that takes into account the possible formation of secondary droplets. Next we answer the following question: when, modelling the delivery of solute therapeutic aerosols, is it necessary to take into account the apparition of secondary droplets? A study of empirical models of drop-wall interaction allows us to conclude that in usual respiratory conditions, no secondary droplets appear. Finally, we perform numerical simulations of an aerosol delivered in an endotracheal tube, in the mechanical ventilation case. The idea is to compare our numerical results to in silico experiments from aerosols specialists. We study the trajectories and the deposition locations of spray droplets.

Introduction

In this work, we address the modelling of the aerosol impingement on walls, in the context of human breathing. We are especially interested in the human upper airways, where the air behaviour is classically modelled by the incompressible Navier-Stokes equations, see for example [START_REF] Grandmont | A multiscale/multimodel approach of the respiration tree[END_REF]. Aerosols are used as medical treatment for many respiratory diseases. When they are liquid, which is the case we aim to study here, they are sent into the airways to the lungs by jet nebulizers. The aerosol can be delivered directly in the upper airways (trachea, larynx, pharynx), or through an endotracheal tube in case of mechanically ventilated patients. Part of the aerosol is lost by deposition on the wall. The treatment efficiency is obviously related to the proportion of the aerosol which reaches the lung. To estimate which proportion of the aerosol deposits on the endotracheal tube or the upper airways, and which proportion actually reaches the respiratory tract, in vitro studies, such as [START_REF] Vecellio | In vitro study and semiempirical model for aerosol delivery control during mechanical ventilation[END_REF], can be complemented by numerical simulations.

There are many ways to model an aerosol. If there are very few particles, one can treat each particle as a numerical individual and perform direct numerical simulations on it, as it is possible for particles in blood flows. Unfortunately, the medical aerosols are constituted of numerous particles, so that direct numerical simulations are too expensive. It then seems quite natural to use a kinetic model for the aerosols [START_REF] Baranger | A modeling of biospray for the upper airways[END_REF][START_REF] Gemci | A numerical and experimental study of spray dynamics in a simple throat model[END_REF]. As a matter of fact, that kind of fluid, which is in the frame of rarefied gases, allows to consider particles from a statistical point of view.

As already stated, this work is more specifically dedicated to the study of a particle impingement on the wall of the human airways. Droplets impinging on a solid surface (dry wall or thin fluid film) usually deposit or splash. In the latter case, secondary droplets are ejected from the wall. The boundary between deposition and splashing has been widely investigated in the last years, both empirically and theoretically. It is generally described using a parameter K, function of the Ohnesorge and Weber numbers of the impinging droplet [START_REF] Cossali | Impact of a single drop on a liquid film: experimental analysis and comparison with empirical models[END_REF][START_REF] Cossali | The impact of a single drop on a wetted solid surface[END_REF][START_REF] Mundo | Droplet-wall collisions: experimental studies of the deformation and breakup process[END_REF][START_REF] Mundo | On the modeling of liquid sprays impinging on surfaces[END_REF][START_REF] Tropea | Spray-wall interaction: How much physics do we need in our models?[END_REF]:

K = We Oh -2/5 , with We = ̺DV 2 0 σ , Oh = µ (̺σD) 1/2 ,
where ̺, σ and µ respectively denote the density, surface tension and viscosity of the droplet, D its diameter and V 0 its velocity. If K exceeds a threshold value K s , then the splashing occurs. Sometimes, the Weber number of the droplet is used as the splashing parameter instead of K [START_REF] Kalantari | Comparison between splash of a droplet in isolation and in a spray[END_REF][START_REF] Vander Wal | The splash/non splash boundary upon a dry surface and thin fluid film[END_REF]. For more details on the general droplet impingement phenomenon, we refer to the reviews of Rein [START_REF] Rein | Phenomena of liquid drop impact on solid and liquid surfaces[END_REF] and Yarin [START_REF] Yarin | Drop impact dynamics: splashing, spreading, receding, bouncing[END_REF].

Most models were built from observations made in the case of a one-droplet impingement, where the incoming velocity is normal to the wall [START_REF] Vander Wal | The splash/non splash boundary upon a dry surface and thin fluid film[END_REF][START_REF] Yarin | Impact of drops on solid surfaces: self-similar capillary waves, and splashing as a new type of kinematic discontinuity[END_REF]. However, some authors recently began to take into account the interactions between impinging droplets that exist in the case of a spray, as well as the effect of an inclined impingement.

We prefered Kalantari and Tropea's model [START_REF] Kalantari | Spray impact onto flat and rigid walls: empirical characterization and modelling[END_REF], because it is, to our knowledge, the only one established from real spray impingement observations. In particular, it accounts for inclined impingements. Details about this model and two other ones [START_REF] Marengo | Aufprall von Tropfen auf Flussigkeitsfilme[END_REF][START_REF] Mundo | Experimental studies of the deposition and splashing of small liquid droplets impinging on a flat surface[END_REF], quite comprehensive, are given in the appendix. Note that most existing models for secondary droplets are reviewed in [START_REF] Cossali | Impact of a single drop on a liquid film: experimental analysis and comparison with empirical models[END_REF].

Since the aerosol evolves in an ambient fluid (the air), there may be some interactions between them. A common assumption is that the aerosol has no effect on the air, in the context of the airways. Hence, the aerosol may be considered as a thin or a very thin spray. The difference between these two kinds of spray lies in the action of the aerosol on the air. We can assume, as in [START_REF] Gemci | A numerical and experimental study of spray dynamics in a simple throat model[END_REF], that the aerosol is thin, i.e. it does globally act on the air. The numerical context of [START_REF] Gemci | A numerical and experimental study of spray dynamics in a simple throat model[END_REF] mimics O'Rourke's [START_REF] O'rourke | Statistical properties and numerical implementation of a model for droplet dispersion in a turbulent gas[END_REF] and uses the Kiva-3V code [START_REF] Amsden | Kiva-3V: A block-structured Kiva program for engines with vertical or canted valves[END_REF]. Note that if we assumed that the aerosol was very thin, we would not eventually need a specific equation for the particles, for they would instantaneously get the air velocity. Hence we get a strongly coupled system, which is the following:

∂ t u + ∇ x • (u ⊗ u) + ∇ x p = 0, ∇ x • u = 0, ∂ t f + ∇ x • (vf ) + ∇ v • (af ) = 0,
where t is the time variable, x the space variable, v the droplet velocity, r its radius, u(t, x) the fluid velocity, p(t, x) the pressure, and a the acceleration of the aerosol droplets mainly due to the drag force exerted on the aerosol by the fluid. The probability density function f of the aerosol depends on t, x, v and r. The previous system is further detailed in Subsectn. 2.1. Such coupled fluid-kinetic models have been studied a lot recently from an analytical point of view. For instance, Hamdache [START_REF] Hamdache | Global existence and large time behaviour of solutions for the Vlasov-Stokes equations[END_REF] tackled the existence problem for the Vlasov-Stokes system. Baranger and Desvillettes [START_REF] Baranger | Coupling Euler and Vlasov equations in the context of sprays: the local-in-time, classical solutions[END_REF] proved the existence of classical solutions in small times for the Vlasov-Euler system. And more recently, Mellet and Vasseur [START_REF] Mellet | Existence and uniqueness of global strong solutions for one-dimensional compressible Navier-Stokes equations[END_REF] studied the existence of global weak solutions to the Vlasov-Fokker-Planck equations coupled with the Navier-Stokes equations. There have been lots of numerics dedicated works too: see [START_REF] Baranger | Modelling of oscillations, breakup and collisions for droplets: the establishment of kernels for the T.A.B. model[END_REF][START_REF] Hylkema | A random particle method to simulate coalescence phenomena in dense liquid sprays[END_REF][START_REF] Hylkema | Modélisation cinétique et simulation numérique des collisions entre gouttelettes d'alumine dans un propulseur à poudre[END_REF][START_REF] Mathiaud | Étude de systèmes de type gaz-particules[END_REF] for instance.

Our model is further discussed in the next two sections, then we address the effect of the impingement of a droplet on a wall, and eventually we present a numerical test in an endotracheal tube.

Aerosol modelling

Fluid-kinetic modelling

In the same way fluids are classically described by the Navier-Stokes equations, kinetic models are often used to model the behaviour of a set of numerous particles or droplets, with a statistical point of view. The associated equation gives the evolution with respect to time t of a probability density function (PDF) f , which in our case depends on t, space coordinates x, velocity v and radius r. Note that f may depend on other variables, such as the droplet temperature, its internal energy, etc. The quantity f (t, x, v, r) dr dv dx is the number of droplets at time t inside the elementary volume of the phase space, which can be abusively denoted by

[x, x + dx] × [v, v + dv] × [r, r + dr].
Assuming, like in [START_REF] Gemci | A numerical and experimental study of spray dynamics in a simple throat model[END_REF], that droplets neither collide, nor exert an action on the fluid, f solves a transport Vlasov-like equation. Eventually, here is the full system satisfied by f , the fluid velocity u and the pressure p, which depend on t and x:

∂ t u + ∇ x • (u ⊗ u) + ∇ x p = 0, (1)
∇ x • u = 0, (2)
∂ t f + ∇ x • (vf ) + ∇ v • (af ) = 0, (3)
where a, approximated here by the Stokes force, is given by

a = -6πµr(v -u). (4)
The boundary conditions (see Fig. 1) for the Navier-Stokes equations are the following:

u(t, x) = u 1 (t) if x ∈ Γ 1 , (5) u(t, x) = 0 if x ∈ Γ 2 , (6)
where u 1 is the profile of the incoming velocity in Ω. Note that there is no condition on Γ 3 .

Boundary conditions for the aerosol

To take into account the possible impingement of droplets on walls, one must add an adequate boundary condition to Eqn. (3) above. Actually, in order to describe the evolution of f , it is necessary to know if secondary droplets are created on the walls, and if there are, what their locations, velocities and radii are. Hence, we only need to prescribe, as a boundary condition, the value of f for velocities emerging from the wall.

Define in every point x of the wall the normal vector to the wall n(x). We consider that the droplet located in x, with velocity v and radius r does hit the wall if x is really on the wall, and if velocity v satisfies v • n(x) < 0, which means that the droplet is heading to the wall.

We propose the following boundary condition, for x ∈ Γ 2 and v • n(x) < 0,

f (t, x, v, r) = r * ∈R + v * ∈R 2 χ [v * .n(x)<0] (x, v * ) N sec (K, v * , v, r * , r)f (t, x, v * , r * ) dv * dr * .
In the previous equation, N sec (K, v * , v, r * , r) represents the number of secondary droplets of velocity v and radius r, appearing because of the impingement of droplets of radius between r * and r * + dr * with velocity between v * and v * + dv * . It depends on K: if K does not exceed a threshold value K s , then the droplet simply deposits on the wall, and no secondary droplet is created, so that N sec (K, v * , v, r * , r) = 0. It can be a Gaussian distribution, as in [START_REF] Mundo | Experimental studies of the deposition and splashing of small liquid droplets impinging on a flat surface[END_REF] and [START_REF] Kalantari | Comparison between splash of a droplet in isolation and in a spray[END_REF], or a punctual distribution, as in [START_REF] Marengo | Aufprall von Tropfen auf Flussigkeitsfilme[END_REF]. Note that kinetic equations with similar boundary conditions have been studied from the mathematical point of view by Mischler [START_REF] Mischler | On the initial boundary value problem for the Vlasov-Poisson-Boltzmann system[END_REF][START_REF] Mischler | On the trace problem for solutions of the Vlasov equation[END_REF].

Splashing or deposition?

Here we want to discuss if the drop splashing in the endotracheal tube can occur during a mechanical ventilation. Note that a droplet splashing cannot occur on the upper airway walls, because these walls are covered of viscous mucus that absorbs and retains every droplet reaching its surface. Thus discussing splashing or deposition is only relevant in the endotracheal tube.

According to [START_REF] Kalantari | Spray impact onto flat and rigid walls: empirical characterization and modelling[END_REF], the critical Weber number for splashing for a droplet impinging on a wall is approximately above 80. We here suppose that the aerosol solution properties are similar to water properties. Consequently, its viscosity µ, surface tension σ and density ̺ are: µ = 9.78 10 -4 Pa.s, σ = 7.28 10 -4 N.cm -1 , ̺ = 1.0 kg.m -3 .

Experiments with the endotracheal tube performed by aerosol specialists [START_REF] Duparque | [END_REF][START_REF] Vecellio | In vitro study and semiempirical model for aerosol delivery control during mechanical ventilation[END_REF] deal with velocities between 0.25 and 1 m.s -1 . With such velocities, the Weber number of spray droplets in the airways does not exceed the value 0.15. We conclude that splashing cannot occur in the endotracheal tube under usual ventilation conditions. Consequently, in the sequel, we shall not address either any more the possibility of splashing when considering the endotracheal tube. The boundary condition on f then simply becomes

f (t, x, v, r) = 0, if x ∈ Γ 2 , v • n(x) < 0. ( 7
)
3. Numerics

Numerical solving

We use a standard P 1 -P 2 finite element computation for the air flow, a particle method for the aerosol, to solve (1)- [START_REF] Cossali | Impact of a single drop on a liquid film: experimental analysis and comparison with empirical models[END_REF]. We do not give any detail on the fluid computation, since (1)-( 2), ( 5)-( 6) are solved thanks to the Navier-Stokes routine of the Freefem++ software [START_REF]Freefem++, finite elements software[END_REF]. Note that our numerical code is inspired from an engineering project performed under B. Maury's supervision [START_REF] Dérumeaux | Modélisation du dépôt de particules dans les bronches[END_REF].

Particle method

The equation describing the evolution of the PDF f involves a phase space of high dimension. Thus, using finite volume or finite difference methods to solve this equation, or simply performing direct numerical simulations on the droplets, would be too expensive. Particle methods appear to be an adequate compromise between the previous solutions. The same choice has been made in a previous attempt to model therapeutic sprays in [START_REF] Baranger | A modeling of biospray for the upper airways[END_REF].

Let us fastly present the particle method we here use. Since there are numerous droplets described from a statistical point of view, one must distinguish the physical droplets from the numerical particles. Let N P the total number of numerical particles, N P is almost always much smaller than the number of droplets N D . The PDF f is discretized in the following way:

f (t, x, v, r) = NP p=1 ω p (t)δ xp(t) (x)δ vp(t) (v)δ rp(t) (r),
where t → (x p (t), v p (t), r p (t)) is the trajectory of the numerical particle p in the phase space, and ω p (t) its representativity at time t. A particle p somehow gives the average behaviour of a set of droplets whose physical characteristics and coordinates are very close to the ones of p. Note that the average value of ω p is approximately of the order N D /N P .

Impingement resolution

A crucial aspect of the numerical solving is the detection of impingements. In order to ascertain if a droplet actually reaches the wall or not, we need to evaluate accurately the distance between this droplet and the wall. In [START_REF] Dérumeaux | Modélisation du dépôt de particules dans les bronches[END_REF], a method to estimate this distance is proposed, which consists in numerically solving the following problem in the computational domain:

-∆θ = 1 in Ω, θ = 0 on ∂Ω. (8)
For small values of θ, isovalues of θ approximate the distance to the walls, and the function Θ = θ/||∇θ|| represents a good approximation of this distance. In our numerical code, Equation ( 8) is solved. If the value of Θ computed at the location of a particle is smaller than an numerical threshold, then we consider that this particle has hit the wall. More details about this way of estimating the distance can be found in [START_REF] Strang | Level sets and the fast marching method[END_REF].

Numerical test

Here we want to numerically predict the trajectories and deposition locations of aerosol droplets in the endotracheal tube used for the mechanical ventilation (Fig. 2). We aim to compare our numerical results with the results obtained with in vitro experiments by aerosols specialists [START_REF] Duparque | [END_REF]. The simulations are performed with the scientific computation software Freefem++ [START_REF]Freefem++, finite elements software[END_REF]. Numerical results are plotted with the visualization software medit [START_REF]Medit, scientific visualization software[END_REF]. The time step is 0.1 s, and 300 time steps are computed, so the total simulation length is 30 s. Because the droplet motion varies faster than the fluid flow, each computational time step for the fluid solving is divided into 50 time sub-steps to solve the particle motion.

The computational domain reproduces in 2D the exact measures of the endotracheal tube used for the mechanical ventilation in the experimental tests. The endotracheal tube is shaped like the upper airways of a lying down patient (see Fig. 2). It is curved, and can be contained in a box of height 25.5 cm and length 21.6 cm. The computational parameters reproduce an experiment performed by aerosol specialists [START_REF] Duparque | [END_REF]. In particular, several identical ejections happen in a row, in order to mimic the continuous aerosol diffusion of the experiment. More precisely, 20 ejections of 50 particles happen, separated from each other by 6 time steps. All particles have a radius of 1.85 µm. The rate of flow at the entrance of the tube is 34 l/min, which corresponds to an average incoming velocity of 2 m.s -1 , and is stationary, because the experiments involved a stationary flow in the tube. All the physical quantities used for the test were given by our fellow experimenters from Inserm Tours, and detailed in [START_REF] Duparque | [END_REF]. Fig. 3 show particle locations, after the first ejection (a), and after several ejections (b), (c).

A. Appendix: Splashing models

In this appendix, we present a selection of splashing models established from experimental results. As the splashing phenomenon occurs in three dimensions, several parameters need to be known in order to correctly describe the creation of secondary droplets, as the number of secondary droplets, their sizes and velocities. In the following, the index b denotes the values before impingement, and a the values after impingement. The authors performed an experimental analysis of the secondary droplet characteristics, but only with water. The model can be used for a quasi-normal impingement angle: α > 80 • , with α denoting the angle between the wall and the direction of the velocity of the impinging droplet, for K r = K/1000 < 4, and for δ = h/D the adimensionalized thickness of the liquid film between 0.5 et 2, with h the liquid film thickness and D the impinging droplet diameter. The parameters u a /u b , v a /v b , d 10 /D and d 32 /D, describing the size and velocity of secondary droplets, are expressed by the general formula: The number d 10 denotes the arithmetical mean diameter of the secondary droplets, and d 32 represents the mean Sauter diameter of the droplets, i.e. the diameter of a droplet having the same volume/surface area ratio as the whole set of secondary droplets.

(A 1 + A 2 δ) + (A 3 + A 4 δ)(K r -K 0 ). with K r = K/1000 et K 0 = K s /
The relationship between the deposited mass, concentration and number of secondary droplets and the impinging (or primary) quantities are the following:

m sec /m prim = (B 1 + B 2 δ)(K r -K 0 ) (B3+B4δ) , N sec /N prim = (B 1 + B 2 δ)(K r -K 0 ) (B3+B4δ) , C sec = max 0, 1 + B 1 + B 1 (K r -K 0 ) 1 -e Kr-K0 2 (B2+B3δ)(Kr-K0) if K r = K 0 ,
where the values of B [START_REF] Mundo | Experimental studies of the deposition and splashing of small liquid droplets impinging on a flat surface[END_REF] This model was established from experimental results reported in [START_REF] Mundo | Droplet-wall collisions: experimental studies of the deformation and breakup process[END_REF][START_REF] Mundo | Experimental studies of the deposition and splashing of small liquid droplets impinging on a flat surface[END_REF] in the case of a liquid film of adimensionalized thickness δ = h/D = 0.03. The velocities of secondary droplets obey a Gaussian distribution around average values depending on the size of the impinging droplet and the velocity before impingement. Splashing occurs when K exceeds the value 57.7. The deposited mass fraction, the diameter and the number of secondary droplets obey the following laws: A.3. Kalantari and Tropea [START_REF] Kalantari | Spray impact onto flat and rigid walls: empirical characterization and modelling[END_REF] This model holds for a negligible surface roughness, with the entire target surface exposed to the impinging spray. The accumulated wall film thickness must stand in the range 8 µm ≤ h ≤ 107 µm, the impingement Weber number (based on the normal component of velocity before the impact) in the range 10 ≤ We n ≤ 160, and the fluid viscosity must be low (Oh ≪ 0.1). The Weber numbers We n and We t are respectively computed with the normal and the tangential components of the impinging velocity.

Γ 1 Γ 2 Γ 3 ΩFigure 1 .

 1231 Figure 1. Domain and boundaries

Figure 2 .Figure 3 .A. 1 .

 231 Figure 2. Experimental device with the endotracheal tube (T. Duparque, Inserm Tours)

Diameter d a = min 8 .

 8 72 exp(-0.0281K), 1 d b , Number of sec. droplets n a = 1.676 × 10 -5 K 2.539 n b

  1000 and the values of A 1 , A 2 , A 3 and A 4 given in the following table.

		A 1	A 2	A 3	A 4
	u a /u b	0.056 0.057	0.038	0.00
	v a /v b	0.311 -0.077 -0.009 -0.024
	d 10 /D mean diameter	0.209 0.100 -0.096 0.005
	d 32 /D mean Sauter diameter 0.250 0.238 -0.022 -0.128

  1 , B 2 , B 3 and B 4 are given in the table below. N sec /N prim 0.285 0.073 0.630 -0.100 A.2. Mundo, Sommerfeld and Tropea

		B 1	B 2	B 3	B 4
	m sec /m prim 0.363 0.242 2.928 -1.521
	C sec	60.8 0.685 0.036	n/a

Acknowledgement. The authors would like to thank Marcela Szopos for her big contribution and Vincent Ducrot for his help, both on the post processing part of this work during Cemracs '07, and Céline Grandmont for the discussions we shared on the topic.

* This work has been funded by the ACI lepoumonvousdisje (resp. B. Maury) and by the INRIA Rocquencourt project team REO (resp. J.-F. Gerbeau).

Parameter

General correlation Normal component of velocity (m/s) u a /u b = -1.1We


Antoine Hoguin

Ouardia Ait

Chris Bowler

Auguste Genovesio

Fabio Rocha Jimenez Vieira

Leila Tirichine
email: tirichine-l@univ-nantes.fr

Evolutionary analysis of DNA methyltransferases in microeukaryotes: Insights from the model diatom Phaeodactylum tricornutum

Cytosine DNA methylation is an important epigenetic mark in eukaryotes that is involved in the transcriptional control of mainly transposable elements in mammals, plants, and fungi. Eukaryotes encode a diverse set of DNA methyltransferases that were iteratively acquired and lost during evolution. The Stramenopiles-Alveolate-Rhizaria (SAR) lineages are a major group of ecologically important marine microeukaryotes that include the main phytoplankton classes such as diatoms and dinoflagellates. However, little is known about the diversity of DNA methyltransferases and their role in the deposition and maintenance of DNA methylation in microalgae.

We performed a phylogenetic analysis of DNA methyltransferase families found in marine microeukaryotes and show that they encode divergent DNMT3, DNMT4, DNMT5 and DNMT6 enzymes family revisiting previously established phylogenies. Furthermore, we reveal a novel group of DNMTs with three classes of enzymes within the DNMT5 family. Using a CRISPR/Cas9 strategy we demonstrate that the loss of the DNMT5 gene correlates with a global depletion of DNA methylation and overexpression of transposable elements in the model diatom Phaeodactylum tricornutum. The study provides a pioneering view of the structure and function of a DNMT family in the SAR supergroup.

3

Background

In eukaryotes the methylation of the fifth carbon of cytosines (5mC) is a recognized epigenetic mark involved in chromosome X inactivation, genomic imprinting, stability of repeat rich centromeric and telomeric regions as well as transposable elements (TEs) repression [START_REF] Kato | Role of CG and non-CG methylation in immobilization of transposons in Arabidopsis[END_REF][START_REF] Zilberman | The evolving functions of DNA methylation[END_REF][START_REF] Barlow | Genomic imprinting in mammals[END_REF][START_REF] Galupa | X-Chromosome Inactivation: A Crossroads Between Chromosome Architecture and Gene Regulation[END_REF] . 5mC is deposited by DNA methyltransferases (DNMTs) capable of de novo methylation and is propagated through subsequent cell division by maintenance enzymes. Eukaryotes have acquired a diverse set of DNA methyltransferases (DNMTs) by horizontal gene transfer of bacterial DNA Cytosine methyltransferase (DCM) enzymes involved in the Restriction Methylation system [START_REF] Bestor | DNA methylation: evolution of a bacterial immune function into a regulator of gene expression and genome structure in higher eukaryotes[END_REF] . All DNMTs are composed of a catalytic protein domain composed of ten conserved motifs (annotated I to X) that provide binding affinity to DNA substrate and the methyl donor cofactor S-Adenosyl methionine (SAM) to process the transfer of a methyl group to unmethylated cytosines [START_REF] Kumar | The DNA (cytosine-5) methyltransferases[END_REF][START_REF] Cheng | Crystal structure of the HhaI DNA methyltransferase[END_REF] . DNMTs have further diversified over evolutionary time scales in eukaryote lineages and acquired chromatin associated recognition and binding domains giving rise to a wide diversity of DNA methylation patterning [START_REF] Zemach | Evolution of eukaryotic DNA methylation and the pursuit of safer sex[END_REF][START_REF] Zemach | Genome-wide evolutionary analysis of eukaryotic DNA methylation[END_REF] . The loss and gain of DNMTs have been associated with profound divergence in cell biology and in the control of gene expression. To date, six main eukaryotic DNMT families have been described and named DNMT1, DNMT2, DNMT3, DNMT4, DNMT5 and DNMT6 [START_REF] Ponger | Evolutionary diversification of DNA methyltransferases in eukaryotic genomes[END_REF][START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] . In metazoans, the concert activity of the DNMT3 family and DNMT1 enzymes allow the deposition and the maintenance of DNA methylation pattern during the successive developmental waves of DNA demethylation and remethylation [START_REF] Greenberg | The diverse roles of DNA methylation in mammalian development and disease[END_REF] . In fungi, the DNA methylation machinery consists in a maintenance activity by DNMT1/DIM2, as in Neurospora crassa [START_REF] Kouzminova | Dim-2 encodes a DNA methyltransferase responsible for all known cytosine methylation in Neurospora[END_REF] , or by the activity of ATPase-DNMT5 enzymes as reported in Cryptococcus neoformans [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] , [START_REF] Dumesic | ATP Hydrolysis by the SNF2 Domain of Dnmt5 Is Coupled to Both Specific Recognition and Modification of Hemimethylated DNA[END_REF] . Fungal DNMT4 relatives are involved in the DNA methylation related process known as Repeat-Induced Point Mutation (RIP) and Methylation Induced Premeiotically (MIP) that leads to transposable elements extinction and or stage specific repression as observed in Aspergillus and Neurospora species [START_REF] Gladyshev | Repeat-Induced Point Mutation and Other Genome Defense Mechanisms in Fungi[END_REF][START_REF] Galagan | The evolutionary cost of genome defense[END_REF][START_REF] Yang | The DmtA methyltransferase contributes to Aspergillus flavus conidiation, sclerotial production, aflatoxin biosynthesis and virulence[END_REF][START_REF] Malagnac | A gene essential for de novo methylation and development in ascobolus reveals a novel type of eukaryotic DNA methyltransferase structure[END_REF] . Successive gains and loss of DNMT1 and DNMT3 occurred during insect evolution leading to secondary loss of global 5mC methylation as in diptera lineages [START_REF] Bewick | Evolution of DNA methylation across insects[END_REF] . In plants, the acquisition of new DNMT1 proteins named Chromomethylases (CMTs) and the divergence of the DNMT3 family led to the spreading of the asymmetrical non-CG patterns of DNA methylation that is extensively found in angiosperms [START_REF] Feng | Conservation and divergence of methylation patterning in plants and animals[END_REF][START_REF] Vanyushin | DNA methylation in plants[END_REF][START_REF] Zhong | Molecular mechanism of action of plant DRM de novo DNA methyltransferases[END_REF] . In Micromonas pusilla, the pelagophyte Aureococcus annophagefferens and the haptophyte Emiliania huxleyi, the presence of a DNMT5 enzyme correlates with a heavy histone linker DNA methylation landscape [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] . Importantly, 5mC have been now reported in more diverse eukaryotes of the SAR lineages as in dinoflagellates [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF] , diatoms [START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] and kelps [START_REF] Fan | Single-base methylome profiling of the giant kelp Saccharina japonica reveals significant differences in DNA methylation to microalgae and plants[END_REF] . However, due to the severe underrepresentation of marine unicellular eukaryotes in modern sequencing databases, our understanding of the DNA methylation machinery in microalgae remains scarce.

Diatoms are a dominant, abundant, and highly diverse group of unicellular brown micro-algae (from 2 to 200 µm) of the stramenopile lineage. It is estimated that diatoms are responsible for nearly 20% of earth primary production [START_REF] Armbrust | The life of diatoms in the world's oceans[END_REF][START_REF] Malviya | Insights into global diatom distribution and diversity in the world's ocean[END_REF] . They are known to dominate marine polar areas and are major contributors of phytoplankton oceanic blooms. To date, 5mC has been reported in four diatoms, namely the centrics Thalassiosira pseudonana [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] and Cyclotella cryptica [START_REF] Traller | Genome and methylome of the oleaginous diatom Cyclotella cryptica reveal genetic flexibility toward a high lipid phenotype[END_REF] , as well as in Fragilariopsis cylindrus [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] and Phaeodactylum tricornutum [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] , a polar and temperate pennate diatom respectively. Diatoms methylation pattern strongly contrasts with the patterns observed in animals but also dinoflagellates and plants [START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF] . Firstly in P. tricornutum, T. pseudonana and F. cylindrus, total levels of DNA methylation range from 8% to as low as 1% of Cytosines in the CG context [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] over repeats and transposable elements usually (but not exclusively) concentrated in telomeric regions [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] . Non-CG methylation is also detected but is scarce. Diatom genomes are thus mainly composed of isolated highly CG methylated TE islands in an otherwise unmethylated genome and to that regards are remarkably similar to fungi methylation profiles. In all diatoms studied so far, methylated TEs often have low expression [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF][START_REF] Traller | Genome and methylome of the oleaginous diatom Cyclotella cryptica reveal genetic flexibility toward a high lipid phenotype[END_REF] . This is very consistent with the repressive role of DNA methylation in other eukaryotes and further traces back 5mC mediated control of TE expression to the last eukaryotic common ancestor.

Nonetheless, direct evidence of the repressive role of 5mC at transposable elements in diatoms is lacking.

The recent advance in high throughput RNA sequencing technologies applied to microeukaryotes led to the development of the Microbial Eukaryote Transcriptome Sequencing Project (MMETSP) consortium. The MMETSP concatenates more than 650 transcriptomes from diverse microeukaryote lineages as diatoms and dinoflagellates making it the biggest sequence database for marine microeukaryotes.

Here using the newly defined enhanced Domain Architecture Framework (eDAF) methodology [START_REF] Zhao | Probing the Diversity of Polycomb and Trithorax Proteins in Cultured and Environmentally Sampled Microalgae[END_REF] , we first explored the structural and phylogenetic diversity of DNMTs sequences in marine microeukaryotes from the publicly available MMETSP sequencing databases. Using an integrative approach with available genomes and phylogenetic studies, we provide a DNMT phylogeny focused on the structural and domain diversity found in microeukaryote enzymes and discuss their evolutionary origins. We found that marine microeukaryotes encode a wide set of DNMTs that lack chromatin domains such as in DNMT6 and in divergent DNMT3 enzymes. We report an unprecedented diversity in the DNMT5 family and define the DNMT5a, b and c enzymes based on structure and phylogenetic assessment. We found that this diversity remarkably contrasts with the apparent lack of DNMT1 in most of the MMETSP and microeukaryotes databases. Secondly, using a CRIPSR/Cas9 knock out approach, we present the direct experimental characterization of the newly defined DNMT5a family of enzymes in the model diatom P. tricornutum demonstrating, for the first time in any SAR, the role of the DNMT5 family in the maintenance of DNA methylation and the role of DNA methylation in the repression of transposable elements in an early diverging eukaryote lineage.

Results

Diversity of DNA methyltransferases in microeukaryotes

In order to capture the diversity of 5-cytosines DNA methyltransferases encoded in microalga, we applied a relaxed HMMER search (e-value=1 as the cut-off threshold) for the PFAM DNMT (PF00145) domain on the whole transcriptomes of the MMETSP database. We complemented MMETSP with 7 diatoms transcriptomes and genomes from the top 20 most abundant diatoms found in TARA Oceans database (courtesy of the GENOSCOPE sequencing project). Next, we eliminated the expected high number of false positives using eDAF [START_REF] Zhao | Probing the Diversity of Polycomb and Trithorax Proteins in Cultured and Environmentally Sampled Microalgae[END_REF] . We also performed reciprocal BLAST best hit analysis on a phylogenetically optimized genomic and transcriptomic database as previously described [START_REF] Dorrell | Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome[END_REF] . We kept enzymes that showed conserved DNMT domains and depicted their domain structures by eDAF curation [START_REF] Zhao | Probing the Diversity of Polycomb and Trithorax Proteins in Cultured and Environmentally Sampled Microalgae[END_REF] . We build a representative phylogeny of DNA methyltransferases based on the alignment of DNMT motifs of conserved DNMTs (Figure 1a, supplementary Figure 1, supplementary table S1). We also compiled the observed structure of microalgal enzymes based on the analysis of DAMA 32 /CLADE [START_REF] Bernardes | Improvement in Protein Domain Identification Is Reached by Breaking Consensus, with the Agreement of Many Profiles and Domain Co-occurrence[END_REF] guided eDAF annotation of representative enzymes used for phylogeny (Figure 1b, Supplementary table S2). In this study we focused on the DNMT1, DNMT3, DNMT4, DNMT5 and DNMT6 gene families that are known or putative DNA modifying enzymes.

Within lineages, a species level summary of presence absence of each gene family can be found in supplementary table S3.

Our results reaffirm and strengthen previously established phylogenies [START_REF] Ponger | Evolutionary diversification of DNA methyltransferases in eukaryotic genomes[END_REF][START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] and we report the six mains eukaryotic DNMT families accordingly (Figure 1a, supplementary Figure 1). We found however that the DNMT5 families branches into three highly supported subfamilies of enzymes that we hereafter named DNMT5a, b and c (Figure 1a, supplementary Figure 1). To our knowledge these gene families have never been described. The DNMT domain of DNMT5 families diverged at motifs I and IV (Figure 3). The DNMT5a and b families share an SNF2 related C-terminal domain composed of two helicases complemented or not by a RING finger domain (Figure 1b, supplementary table S2) while the DNMT5c family is composed of enzymes sharing a long (~1kb) N-terminal amino acid sequence with no annotated functional domains (Figure 1b, supplementary table S2). We found that diatoms DNMT5b enzymes contain an N-terminal laminin B receptor domain as in T. pseudonana (Figure 1b, supplementary table S2). Other DNMT5b contain N-terminal CpG methyl binding domains, HAND and TUDOR domains (supplementary table S2). In addition, the DNMT domain of DNMT5b enzymes is longer than other DNMT5s between motifs VI and VII. These differences in structures probably highlight profound functional diversification between the DNMT5 subfamilies relative to ATPase activity and substrate specificity.

We found 76 species with at least one DNMT5 orthologue. This includes green algal DNMT5s as in Tetraselmis astigmatica that are similar to the published Micromonas pusilla enzyme (Figure 1b, supplementary table S2). Green algal DNMT5s are found within the DNMT5a subfamily (supplementary figure S1). We also found a DNMT5a transcript in the marine photosynthetic excavate euglenozoa Eutreptiella gymnastica closely related to green algal DNMT5as (Figure 2, supplementary Figure S1, supplementary table S3). The DNMT5 family is also widespread in diatom species in which DNMT5a enzymes are mainly found in pennate genomes while DNMT5b is found in both pennates and centrics. Interestingly, our data do not strongly support the presence of the DNMT5b family outside diatoms (Figure 2). Emiliania huxleyi has two annotated DNMT5s, one DNMT5a and one DNMT5b enzyme, but we could not find DNMT5 enzymes in other haptophytes of the MMETSP database suggesting horizontal acquisition of this enzyme family. DNMT5 transcripts identified in dinoflagellates transcriptomes fall into the DNMT5c family, and reciprocally, no DNMT5c enzymes are found in other lineages (Figure 2, supplementary table S3). Overall, our data support the absence of SNF2 containing DNMT5s in dinoflagellates with a few exceptions of partial DNMT5a/b enzymes (supplementary figure 1, supplementary table S2). Within DNMT5a, we identify at least 3 monophyletic group of enzymes: diatoms DNMT5as, Pelagophyte/Dictyochophyte DNMT5as and green algal DNMT5as. However, fungal enzymes are not monophyletic, and we failed to recover monophyletic relationship between ochrophyte stramenopiles suggesting a complex phylogenetic history of DNMT5 subfamilies. In addition, DNMT5 is absent from non-photosynthetic stramenopiles such as labyrinthumycetes and raphidophytes (Figure 2).

In our phylogeny the DNMT4 and DNMT1 clade form a moderately supported gene family as previously described [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Bewick | Diversity of cytosine methylation across the fungal tree of life[END_REF] (Figure 1a, supplementary Figure 1). DNMT1s often associate DNMT catalytic domain with chromatin binding domains as bromo-adjacent homology (BAH) domains, Plant Homeo Domains (PHDs), chromodomains and domains required for the interaction with accessory proteins. We isolated DNMT1/MET1 transcripts similar to the plant MET1 enzyme in 7 green algae species of the MMETSP database as in Chlamydomonas species (Figure 1b, Figure 2, supplementary Figure 1, supplementary table S3), reaffirming that the DNMT1 family was acquired early during plant evolution. CMT enzymes are divergent DNMT1 related enzymes that likely appeared in the very first plant lineages. Its conservation in green algae is more contrasted as many partial CMT enzymes as well as misannotated DNMT1 transcripts were found in early reports [START_REF] Bewick | The evolution of CHROMOMETHYLASES and gene body DNA methylation in plants[END_REF] . Accordingly, we could not find bona fide CMT transcripts in green algae species of the MMETSP data base and instead found two partial CMT transcripts in Polytomella parva and Chlamydomonas chlamydogama that lack BAH, PHD and chromodomains (supplementary Figure 1, supplementary table S2). Interestingly, we found a DNMT1 related enzyme in three haptophytes species (Gephyrocapsa oceanica, Isochrysis.sp-CCMP1324 and Coccolithus pelagicus) of the MMETSP database that cluster with annotated CMTs found in the coccolithophore Emiliania huxleyi (Figure 1a, supplementary Figure 1).

Haptophytes enzymes distantly relate to the conserved green algae CMTs (hCMT2) enzymes (Figure 1a, supplementary Figure S1). We found that the enzymes of Gephyrocapsa oceanica (CAMPEP_0188208858), Isochrysis-CCMP1324 (CAMPEP_0188844028) and Emiliania huxleyi (jgi_458278) have DNMT1-like structures with a Replication Foci Domain (RFD) followed by a BAH (in Emiliana huxleyi only) and a conserved DNMT domain (Figure 1b, supplementary table S2). We also found two putative DNMT1-like enzymes in the transcriptomic database of Raphidophyceae brown microalgae Heterosigma akashiwo and Chatonella subsala.

They are composed of a conserved DNMT domain and a plant homeodomain (PHD) (Figure 1b, supplementary figure 1, Figure 2, supplementary table S2). Raphidophycea enzymes poorly define a DNMT family by themselves and distantly relate to the DNMT1 enzymes (Figure 1a, Supplementary Figure 1). We could not find compelling evidence for bona fide DNMT1s in any other microalgae. Our data support the hypothesis that the DNMT1 maintenance machinery is absent from the main microeukaryote lineages that therefore rely on DNMT1-independent mechanisms for the maintenance of their DNA methylation pattern as previously suggested [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] .

DNMT4 enzymes have been identified in fungi and are involved in the MIP or RIP processes. Closely related to DIM2 enzymes in fungi [START_REF] Bewick | Diversity of cytosine methylation across the fungal tree of life[END_REF] ; two DNMT4 enzymes were also found in the pennate diatom F. cylindrus and the centric diatom T. pseudonana [START_REF] Ponger | Evolutionary diversification of DNA methyltransferases in eukaryotic genomes[END_REF] .

Accordingly, we identified a monophyletic diatom enzyme family that relate to the fungal DNMT4 gene family (Figure 1a, Supplementary Figure 1). Diatoms and RID/DMTA enzymes as well as DNMT1 proteins form a moderately supported monophyletic clade. A total of 31 diatoms, pennate and centric species expresses or encodes at least one DNMT4 related transcript (supplementary table S4). This indicates that the DNMT4 family was acquired early during diatoms evolution. Most diatoms DNMT4 enzymes are composed of a single DNMT domain as in T.

pseudonana, which contrasts with fungal enzymes (Figure 1b supplementary table S2). However, 9 diatom's DNMT4 proteins possess an additional N-ter chromodomain as observed in Thalassiosira miniscula (Fig. 1b, supplementary table S2 andS4). We found the microalgal DNMT4 family is restricted to diatoms. The DNMT4 family is thus only observed in two very distantly related microeukaryote lineages questioning the evolutionary origin of this gene family in eukaryotes.

Our data indicate that the DNMT3 family is not particularly abundant in microalgae (Figure 2, supplementary table S3). DNMT3 is absent in most stramenopiles except for diatoms; in which both genomic and transcriptomic data strongly support its presence (supplementary table S4). DNMT3 seems absent in haptophytes (Figure 2, supplementary table S3). Only one transcript from the cryptomonad Goniomonas pacifica could be annotated as DNMT3. In addition, we could not identify DNMT3 enzymes in any green algae of the MMETSP database, but it is present in red algae as found in the genomes of Cyanidioschyzon merolae and Galdieria sulphuraria (Figure 2, supplementary table S3). We also report few additional DNMT3 transcripts in dinoflagellates as previously described [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF] (Figure 2, supplementary table S3). Upon alignment, dinoflagellates DNMT3 enzymes (including former annotated enzymes [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF] ) and Goniomonas pacifica DNMT3s are closely related to red algal genes but diverged compared to other DNMT3s while diatoms form their own DNMT3 family (Supplementary figure 1). This suggest that the DNMT3 family was iteratively lost and acquired several times during microalgae evolution. As observed in P. tricornutum, DNMT3 enzymes found in microalgae all lack chromatin associated domains (Figure 1b, supplementary table S2). This contrasts with mammalian DNMT3s [START_REF] Jurkowska | Structure and Function of Mammalian DNA Methyltransferases[END_REF] that interact with histone post-translational modifications.

We found that the DNMT6 enzymes are among the most widespread DNMTs in microeukaryotes. We found a DNMT6 transcript in the MMETSP transcriptomes of 3

Tetraselmis green algae and 7 dinoflagellates (Figure 2 supplementary table S3). In addition, DNMT6 is extensively found in stramenopiles as in Dictyochophyceae, Crysophyceae and Pelagophyceae (Figure 2, supplementary table S3). In diatoms, DNMT6 is very abundant (Supplementary table S4). DNMT6 is also present in the nonphotosynthetic labyrinthulomycetes Aplanochytrium stocchinoi and probably in Aplanochytrium keurgelense (Figure 2, supplementary table S3). In addition, our data also strongly support the presence of DNMT6 orthologue in the major Chromalveolata lineage of Rhizaria (Figure 2, supplementary table S3) as suggested in previous reports [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF] . DNMT6 enzymes are for most part homogeneous and do not contain chromatin associated signatures, as in P. tricornutum DNMT6 and DNMT3 enzymes (Figure 1b, supplementary table S2). Monophyletic relationships within the DNMT6 family and between micro-eukaryotes could not be resolved (supplementary figure 1).

Functional study of DNMT5 in the model diatom Pheaodactylum tricornutum

To our knowledge no DNMTs have been functionally characterized in SARs.

The pennate P. tricornutum is the model species that we and others used to decipher the epigenomic landscape in diatoms, shedding light into the conservation and divergence of the methylation patterns in early diverging eukaryotes [START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF][START_REF] Veluchamy | An integrative analysis of post-translational histone modifications in the marine diatom Phaeodactylum tricornutum[END_REF] . P.

tricornutum encodes a DNMT3, DNMT6 and DNMT5a orthologues in single copy but lacks a DNMT4 and DNMT5b orthologues found in other diatoms (supplementary table S4). We asked whether any of those DNMTs had DNA methylation function(s) in vivo.

Using a CRISPR/Cas9 mediated knock-out approach we screened P. tricornutum genome for DNMTs loss of function mutants (see material and methods). In this work, we report two independent mutants with homozygous out of frame deletions generating premature STOP codons in the coding sequence of DNMT5a (Figure 4). DNMT5:KOs will be hereafter referred to as the 'M23' and 'M25' lines respectively. No DNMT3 or DNMT6 mutations could be generated using our CRISPR/Cas9 strategy.

Using sets of primer pairs targeting the DNMT domain as well as the DEADX helicase-SNF2 like domain of DNMT5 transcripts, we monitored by quantitative RT-PCR a 4 to 5-fold loss in mRNAs levels in both M23 and M25 lines (Supplementary Figure 2). 5mC dot blot screening revealed that all DNMT5:KOs had a 4-3 fold loss of DNA methylation compared to the Pt18.6 reference ('wild-type') and Cas9:mock controls (Supplemental Figure 2) consistent with the putative role of DNMT5 in maintaining DNA methylation patterns in diatoms.

To get a quantitative single base resolution of DNA methylation loss in DNMT5:KOs, we performed whole genome bisulfite sequencing on the M23, M25 and the reference Pt18.6 line. To assess highly methylated regions, we first filtered cytosines by coverage and methylation levels considering a 5X coverage threshold and 60% methylation levels in all lines. In the reference Pt18.6, we identified 10349 methylated CGs (0.3% of all analyzed CGs), 129 methylated CHHs (3/10000) and 12 methylated CHGs (<5/10^6). About 76% of methylated cytosines are found within TEs confirming that repeated sequences are the main targets of CG methylation in P.

tricornutum genome (Figure 5a). In comparison only 9% of methylated cytosines overlap with genes (Figure 5a). As a result, 876/3406 (25%) of transposable elements and 170/9416 (1,8%) of genes are marked by at least one methylated CG in Pt18.6.

Among methylated TEs, 711 (81%) were also found methylated in the reference strain in earlier reports [START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] and reciprocally (supplementary Figure 3). Gene methylation was less consistent between already published reports [START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] as 230 (63%) of known methylated genes are not found methylated in the present study (supplementary Figure 3), which might be due to differences in culture conditions and/or coverage depths and methods used to profile DNA methylation. In DNMT5:KOs, a maximum of 2 cytosines in any context are found methylated. Methylated cytosines identified in the reference strain show background levels of DNA methylation in DNMT5:KOs (Figure 5 (supplementary Figure S3). We found that ~83% of DMRs overlap with transposable elements and their regulatory regions (~5%) (Figure 5 b). Reciprocally, 584 (~15%) annotated transposable elements are found within DMRs (+/-500bp) in DNMT5:KOs lines (Figure 5 c, Supplementary table 7). Among them 544 showed at least one highly methylated CG (Figure 5c). We found that 70% of all methylated cytosines in the reference strain concentrate in TEs that overlap with DMRs and 90% of all methylation found at TEs are found within DMR-TEs (supplementary figure S3). Outside DMRs, methylated TEs show less than 2 methylated cytosines while within DMRs TEs show extensive methylation (supplementary Figure 3). Our DMR analysis thus identified a significant loss of DNA methylation at transposons that also concentrate most of densely methylated cytosines in P. tricornutum. There is a low overlap of DMRs with genes or their regulatory regions and only ~0.5% of all protein coding genes (30% of genes with at least one highly methylated CGs) are found within DMRs (Figure 4c).

Nonetheless, genes within DMRs concentrate more than 80% of methylation found in genes in the reference strain. As for TEs, genes identified in hypoDMRs are also among the most methylated genes in the reference strain. We then asked whether DMRs associate with known regions marked by histone posttranslational modifications. Interestingly, between 80% and 90% of all DMRs overlap with known regions marked by H3K27me3, H3K9me3 or H3K9me2 defined in the reference Pt18.6 line [START_REF] Veluchamy | An integrative analysis of post-translational histone modifications in the marine diatom Phaeodactylum tricornutum[END_REF] (Figure 5d). We found that 70% of DMRs are found within regions co-marked by all three repressive histone marks in association or not with active marks. Our DMR analysis thus retrieved the denser and highly heterochromatic regions of P. tricornutum genome that are reported targets of CG methylation in the reference strain. Our data are consistent with a global loss of DNA methylation in DNMT5:KOs at TE-rich DNA methylated-H3K27me3, H3K9me2 and H3K9me3 rich regions of P. tricornutum genome. Of note, one hypermethylated region was found in the mutant M23 in the promoter region of the gene Phatr3_J46344. Consistent with the low level of CHH and CHG methylation in the reference strain we found no CHG and CHH hypo nor hyper DMRs.

The control of transposable elements by the DNA methyltransferases family is a key unifying feature within eukaryotes 2 . We hence monitored the transcriptional effect of the loss of DNMT5 in M23/M25 by whole RNA high throughput sequencing (Material and Methods). To identify the most significant changes in mRNA levels, we focused our analysis on genes showing a significant 2 folds induction or reduction of expression in mutants compared to the reference line (LFC > |1| and an FDR< 0.01).

We also analyzed expression of genes overlapping with TE annotations (TE-genes) as previously described [START_REF] Rastogi | Integrative analysis of large scale transcriptome data draws a comprehensive landscape of Phaeodactylum tricornutum genome and evolutionary origin of diatoms[END_REF] . In both DNMT5:KOs, we observed a global overexpression of genes and TE-genes and comparatively fewer downregulation (Figure 6a). TE-genes show higher level of overexpression than genes that show milder inductions suggesting that primary targets of DNA methylation in the reference strains are also the first to respond to the loss of DNA methylation in DNMT5:KOs. Gene overexpression is inconsistent between lines (Figure 6b). At the transcriptional level, M23 shows up to 1133 up regulated genes and M25 shows 393 upregulated genes.

Only 219 genes have consistent upregulation in both mutants. Transposable element showed more overlap. We found that 339 TE-genes with up-regulation in at least one mutant are consistently up-regulated in both (Figure 6c). We performed GOterm enrichment using TopGO tools [START_REF] Alexa | Gene set enrichment analysis with topGO[END_REF] and found that overexpressed genes in both mutants are enriched for GOs associated with protein folding responses as well as nucleotide phosphate metabolism and nucleotide binding activity. This is typified by the overexpression of chaperone DnaJ domain containing proteins and Hsp90 like proteins (Supplementary tables S10 and S11). The recent advances in high through output RNA sequencing technologies led to the recent identification of gene co-regulatory networks in P. tricornutum [START_REF] Ait-Mohamed | PhaeoNet: A Holistic RNAseq-Based Portrait of Transcriptional Coordination in the Model Diatom Phaeodactylum tricornutum[END_REF] . Genes with overexpression in DNMT5:KOs are enriched within the "salmon" and "steelblue" coregulatory gene modules. The 'salmon' module contains genes associated with chloroplast biology as well as amino acid related enzymes which might highlight metabolic defects. The 'steelBlue' regulatory module associates with protein translation as well as nucleotide metabolism and is enriched in genes involved in purine and pyrimidine cellular pathways [START_REF] Ait-Mohamed | PhaeoNet: A Holistic RNAseq-Based Portrait of Transcriptional Coordination in the Model Diatom Phaeodactylum tricornutum[END_REF] . Accordingly, some upregulated proteins are involved in ribosome biosynthesis and RNA processing. The chaperone like enzymes found upregulated in DNMT5:KOs are part of both the 'salmon' and 'steelblue' pathway (supplementary table S12). Only 36 genes showed consistent down-regulation in both lines in a DNA methylation independent manner (Supplementary figure 4). Among those genes we found back DNMT5a, that shows a 3-fold loss in both mutants confirming qpcr analysis and suggesting that premature stop codons triggered mRNA degradation (Supplementary table S13). We could not find compelling GO enrichment nor coregulation network enrichment for downregulated genes in DNMT5:KOs. A handful of TE genes show loss of expression in DNMT5:KOs that is not associated with DNA methylation loss (Supplementary figure 4).

We asked if we could directly or indirectly link upregulation of genes and TEs to DNA hypomethylation in DNMT5:KOs. Interestingly, we found that gene upregulation is not linked to gene loss of DNA methylation since 31 (60%) of genes in shared hypo DMR do not show changes in mRNA levels in any mutants (Supplementary figure S4).

However, 66% (226) of TE-genes with upregulation in both DNMT5:KOs also overlap with hypoDMRs (Supplementary figure S4). Reciprocally, half of TE-genes overlapping with bona fide TEs found in hypoDMRs are upregulated in at least one DNMT5:KOs..

Consistent with the association of TEs and DMRs, we found that up regulated TEgenes fall into regions that typify the repressive epigenetic landscape of P. tricornutum that also overlap with DMRs identified in M23 (figure 7a, supplementary table S9).

Notably, 80% of TE-genes marked by H3K27me3 and in hypoDMRs are overexpressed in both DNMT5:KOs (Figure 7a and E categories (Figure 7b). In conclusion, our data show that loss of DNA methylation primarily associates with reactivation of a subset of highly repressed TEs, but not genes, found in heterochromatic regions of P. tricornutum genome.

Discussion

This work extends earlier studies in the field and further demonstrates that DNA methyltransferases are much diversified in microalgae. Studies on the evolutionary history of DNMTs have established that the DNA methylation machinery diverged between eukaryotes along with their respective epigenetic landscape. Using the MMETSP we found that secondary endosymbionts rather encode a combination of DNMT5, DNMT3 and DNMT6 enzymes. We nonetheless identified CMTs with DNMT1like features in haptophytes as well as new DNMT1-like enzyme in Raphidophyceae.

This suggests that CMTs and DNMT1 type of enzymes might have originated prior to the chlorophyta-embryophyta divergence and in the common heterotrophic ancestor but were extensively lost in a lineage specific manner. Alternatively, horizontal gene transfer of DNMT1 type of enzymes between microalgae, such as during endosymbiotic events, could have sustained continuous flow of this gene family in secondary and tertiary endosymbiotic lineages such as haptophytes and stramenopiles.

In our phylogeny, the RID/DMTA and the diatoms DNMT4 enzymes are clearly related as shown by Huff and Zilberman [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF] and Punger and Li [START_REF] Ponger | Evolutionary diversification of DNA methyltransferases in eukaryotic genomes[END_REF] . Within fungi, RID proteins were found closely related to DIM2 enzymes [START_REF] Bewick | Diversity of cytosine methylation across the fungal tree of life[END_REF] for which we have not found any related orthologue in diatoms. We make the hypothesis that the DNMT4 family is closely related to DNMT1 enzymes and arose by convergence in the diatom and fungi lineages. The function of DNMT4 in diatoms is unknown. Whether RID or MIP process occur in any DNMT4 containing diatom also remain an open question. The presence of chromodomains that are known to bind histone post translational modifications as in CMT enzymes [START_REF] Kato | Role of CG and non-CG methylation in immobilization of transposons in Arabidopsis[END_REF][START_REF] Stroud | Non-CG methylation patterns shape the epigenetic landscape in Arabidopsis[END_REF] nonetheless suggests that diatoms DNMT4 might be functional as either de novo or maintenance enzymes.

DNMT6 enzymes are very well detected in diatoms and dinoflagellates. Our study independently reports the same DNMT6 enzymes found in Bigelowella natans and Aplanochytrium stochhinoi by earlier works although not specified by the authors [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF] .

As it is reported in trypanosomes [START_REF] Ponger | Evolutionary diversification of DNA methyltransferases in eukaryotic genomes[END_REF] , we suggest that DNMT6 likely emerged prior to the Chromalveolata radiation. It is the only known DNMT enzyme in Trypanosomes that does not show extensive DNA methylation pattern in any context [START_REF] Cuypers | C-5 DNA methyltransferase 6 does not generate detectable DNA methylation in Leishmania[END_REF] . DNMT6 is not active in Leishmania species [START_REF] Cuypers | C-5 DNA methyltransferase 6 does not generate detectable DNA methylation in Leishmania[END_REF] . Its presence in several lineages, hence, does not predict DNA methylation per se and must be further investigated.

We showed that the DNMT domain of the different DNMT5s are conserved within each other's and diverged compared to other DNMTs supporting a common evolutionary origin for all DNMT5 enzymes. It was proposed that DNMT5s are ancestral to eukaryotes. However, we found that DNMT5s are more diverse than previously thought as showed by the structural divergence between DNMT5s subfamilies apart of their DNMT domain. It was established that DNMT5s rely on the ATPase activity of their SNF2 like domains to methylate hemi-methylated cytosines [START_REF] Dumesic | ATP Hydrolysis by the SNF2 Domain of Dnmt5 Is Coupled to Both Specific Recognition and Modification of Hemimethylated DNA[END_REF] .

In that regards DNMT5c that are also dinoflagellate specific, lacks ATPases. The DNMT5 family also likely diverged in diatom species as DNMT5b enzymes specially in centric diatoms. DNMT5b might be multifunctional related DNMT5 enzymes as it is suggested by the presence of N-ter HAND domains, which are found in chromatin remodelers [START_REF] Grüne | Crystal structure and functional analysis of a nucleosome recognition module of the remodeling factor ISWI[END_REF] , as well as TUDOR domains that are found in histone modifying enzymes and readers [START_REF] Lu | A versatile family of histone methylation 'readers[END_REF] and small RNA interacting proteins 4647 . In the genomes of Fragilariopsis cylindrus species as well as in Synedra both DNMT5a and b are found. This supports a scenario in which both DNMT5a and b were acquired early in diatoms and might be paralogues. In other diatoms, DNMT5a is however phylogenetically restricted. It is almost exclusively found in annotated genomes of pennate diatoms. Corethron pennatum is the only centric diatom with a DNMT5a transcript. Besides transcriptomic evidence, the absence of DNMT5a in centric diatoms is further supported by genomic data in 5 centric species in which at least another DNMT could be detected, especially DNMT5b (table S4). The diatoms DNMT5a enzymes might originate from a pennate specific horizontal gene transfer with another stramenopiles encoding DNMT5a and or within diatoms themselves.

The independent accession of DNMT5s in ochrophyte algae is supported by our phylogenies in which diatoms and pelagophytes/dictyochophytes enzymes are not monophyletic. DNMT5 enzymes are thus related gene families that show lineage specific divergence. The origin of the DNMT5c is also intriguing since it is both highly divergent compared to other DNMT5s and dinoflagellate specific. In DNMT5 enzymes, we noticed that the DNMT motifs I; involved in the binding of S-Adenosyl-methionine;

and IV; the catalytic site; are highly divergent compared to other DNMTs suggesting that DNMT5 enzymes might require accessory proteins aside of their ATPase activity.

In addition, the lack of chromatin associated domains in DNMT3 proteins, but also DNMT6 and DNMT4 proteins suggest that the link, if any, between DNA methylation and histone modifications is more indirect than observed in plants and mammals (more discussed below) and might also require the activity of accessory proteins such as UHRF1 type [START_REF] Bostick | UHRF1 plays a role in maintaining DNA methylation in mammalian cells[END_REF] or DNMT3-like [START_REF] Ooi | DNMT3L connects unmethylated lysine 4 of histone H3 to de novo methylation of DNA[END_REF] enzymes that we have not investigated in this study.

Several species presented in this study are not known to have DNA methylation.

Crosschecking the diversity in DNA methyltransferases with bona fide in vivo functions should retain much attention. In this context, we investigated the role of DNMT5a which is conserved in the pennate diatom P. tricornutum. As discussed above, the DNMT5a enzyme of P. tricornutum is not shared with many other diatoms but is an orthologue of the DNMT5a protein from Cryptococcus neoformans which is involved in the maintenance of DNA methylation patterns [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Dumesic | ATP Hydrolysis by the SNF2 Domain of Dnmt5 Is Coupled to Both Specific Recognition and Modification of Hemimethylated DNA[END_REF] . In laboratory conditions, P. tricornutum propagates via mitotic division. Our study demonstrates that the 'somatic' (i.e. clonal) loss of DNMT5 was sufficient alone to generate a global loss of CG methylation upon repeated cellular divisions. For this reason, we state here that we monitored a loss due to defective maintenance activity. TEs are major targets of DNA methylation in numerous eukaryote lineages including dinoflagellates and diatoms anchoring these features to the origin of eukaryotes [START_REF] De Mendoza | Recurrent acquisition of cytosine methyltransferases into eukaryotic retrotransposons[END_REF][START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] . Our DMR analysis de novo identified regions that show extensive methylation in the reference strain i.e TEs that were also reported in earlier studies [START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] (supplementary figure S3).

We further demonstrate that only 15% of TEs concentrate more than 70% of DNA methylation in P. tricornutum. We found that most TEs associate with active epigenetic marks alone. It strongly suggests that although TE methylation is indeed observed, TE regulation in diatoms is for most part not directly dependent of DNA methylation in general. Genes showed low overlap with both DMRs and previous reports (supplementary figure 3) strongly suggesting that gene methylation is more labile even within independent lines of P. tricornutum. In addition, the loss of DNA methylation did not trigger extensive changes in gene expression but a reactivation of transposable elements. This is a strong support for the hypothesis that 5mC was recruited to keep TEs directly or indirectly at bay in the very first eukaryotic radiations.

Nonetheless, our data also show that not all TEs are responsive to the loss of DNA methylation independently of their methylation levels. In P.tricornutum, chromatin immunoprecipitation studies followed by high throughput sequencing demonstrated that a subset of TEs are co-marked by DNA methylation as well as repressive histone modifications such as H3K27me3 and H3K9me2/3 suggesting redundancy or dependency within the epigenetic code of diatoms [START_REF] Veluchamy | An integrative analysis of post-translational histone modifications in the marine diatom Phaeodactylum tricornutum[END_REF] . Interestingly, we found that upregulation is also associated with TEs in highly heterochromatic regions including transposable elements co-marked by DNA methylation and H3K27me3. This combination of repressive marks at TEs is remarkable. DNA methylation is known to interact with histone modifications. The interdependency of DNA methylation and H3K9 methylation is well documented in plants [START_REF] Jackson | Control of CpNpG DNA methylation by the KRYPTONITE histone H3 methyltransferase[END_REF] , fungi [START_REF] Honda | Direct Interaction between DNA Methyltransferase DIM-2 and HP1 Is Required for DNA Methylation in Neurospora crassa[END_REF] and mammals [START_REF] Estève | Direct interaction between DNMT1 and G9a coordinates DNA and histone methylation during replication[END_REF] , [START_REF] Ikegami | Genome-wide and locus-specific DNA hypomethylation in G9a deficient mouse embryonic stem cells[END_REF] . In Arabidopsis thaliana, upon loss of CG methylation in met-1 (DNMT1) mutants,

H3K27me3 is relocated at specific hypomethylated TEs [START_REF] Mathieu | Distinct regulation of histone H3 methylation at lysines 27 and 9 by CpG methylation in Arabidopsis[END_REF] . Similar observations were made in ddm1 mutants defective for heterochromatic cytosine methylation [START_REF] Rougée | Polycomb mutant partially suppresses DNA hypomethylationassociated phenotypes in Arabidopsis[END_REF] . In mammalian systems, compensatory relocation mechanisms of H3K27me3, but also H3K9me3, occur upon extensive DNA hypomethylation to maintain repression in a loci specific but also TE family specific manner [START_REF] Walter | An epigenetic switch ensures transposon repression upon dynamic loss of DNA methylation in embryonic stem cells[END_REF] . We make the hypothesis that, aside direct repressive roles, the loss of DNA methylation also triggered genome wide changes within the epigenetic landscape of P. tricornutum in turn controlling the expression of a subclass of TEs. It was found that a subset of transposons are responsive to nitrogen depletion in conjunction with hypomethylation in P.

tricornutum [START_REF] Maumus | Potential impact of stress activated retrotransposons on genome evolution in a marine diatom[END_REF] . It is thus possible that TE expression also relies on condition specific transcription factor binding that are not fully recapitulated in our growth conditions.

Previous studies hinted for a potential RNA dependent DNA methylation system, [START_REF] Rogato | The diversity of small non-coding RNAs in the diatom Phaeodactylum tricornutum[END_REF] however, the mechanism of de novo methylation, if any, in diatoms is elusive.

We did not found evidences for loss or gain of expression of other DNMTs nor putative DICER and AGO proteins in DNMT5:KOs. In addition, given that no regions retained DNA methylation upon loss of DNMT5:KOs alone we did not put in evidence direct compensatory de novo DNA methylation mechanisms in P. tricornutum DNMT5:KOs.

It is possible that de novo methylation activity is performed by DNMT3 and or DNMT6 and or also directly or indirectly require DNMT5 activity. We could not generate DNMT3 or DNMT6 KOs. Complementation studies using ectopic expression of DNMT3, DNMT6 and or heterologous DNMT4 enzymes in P. tricornutum DNMT5:KOs loss of methylation background are conceivable experiments that could shed light into the mechanisms behind the setting or resetting of DNA methylation in diatoms.

DNMT5 mutant lines are viable in conditions used in routine for P. tricornutum culture which indicate that in optimal conditions loss of DNA methylation is not associated with drastic biological effects. Metabolic changes in DNMT5:KOs should be further determined in future experiments under stress conditions. In mammals, the release of TE repression by loss of DNMT3 enzymes triggered strong meiotic defects due to genomic instability. DNA methylation mediated TE control is also linked to the sexual cycle of cells as in MIP processes. Contrary to P. tricornutum, diatom species amenable for direct genetic approaches are also known to undergo sexual reproduction. It is however unknown if DNA methylation plays a critical role in protecting the genome of diatom cells during meiosis. We would also like to highlight that P. tricornutum encode a unique set of DNMTs even within diatoms. In addition, closely related diatom species often encode a different combination of enzymes as we show for DNMT5b and DNMT5a clades between centrics and pennates. Within pennates, DNMT4 and DNMT3 were likely lost multiple times. We make the hypothesis that diatoms show extensive diversity in their DNA methylation machinery.

In conclusion, we provide the first report of the function of DNMT5 in Stramenopiles and update our knowledge about its diversity in eukaryotes with the identification of three new subclasses within this family of enzymes. As for the conservation of DNMT5 in other ochrophyte and green algae, we firmly hypothesize that its function is also conserved. DNMT5 is likely a major functional DNMT family that has expanded in SAR lineages as did DNMT1 in metazoans and land plants.

Material and Methods

Phylogenetic analysis of DNMTs in microeukaryotes

HMMER and RBH analysis

We performed an extensive scan of the MMETSP database by HMMER-search using the model PF00145 to fetch any DNMT-like, including partial transcripts, sequence within micro eukaryotes. We ran HMMER in a no-stringent fashion aiming to do not miss positives DNMT sequences. We used eDAF approach to filter the expected high number of false positives. It is worth noting that we initially use HMMER for screening instead of the built-in module of eDAF due to the time complexity of the latter for extensive searches (tens to hundreds of times slower than HMMER). Reciprocal BLAST best hit analysis was performed as previously described [START_REF] Dorrell | Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome[END_REF] . The DNMT3 (Phatr3_J47136), DNMT4 (Thaps3_11011), DNMT5 (Phatr3_EG02369) and DNMT6 (Phatr3_J47357) orthologues found in P. tricornutum or T. pseudonana (for DNMT4)

were blasted on a phylogenetically optimized database that include MMETSP transcriptomes. Upon reciprocal BLAST, putative DNMT sequence hits giving back the corresponding enzyme (DNMT3, DNMT4, DNMT5 or DNMT6) at the threshold of e-value of 1 × 10^-5 in the corresponding diatom were retained. Candidate enzymes were then analyzed using eDAF.

eDAF-guided domain architecture analysis enhanced Domain Architecture Framework (eDAF) is a four module computational tool for gene prediction, gene ontology and functional domain predictions [START_REF] Zhao | Probing the Diversity of Polycomb and Trithorax Proteins in Cultured and Environmentally Sampled Microalgae[END_REF] . As previously described for Polycomb and Trithorax enzymes [START_REF] Zhao | Probing the Diversity of Polycomb and Trithorax Proteins in Cultured and Environmentally Sampled Microalgae[END_REF] , candidate DNMTs identified by RBH and HMMER-search were analyzed using the DAMA-CLADE guided built-in functional domain architecture. The domain architecture of representative enzymes used in this study can be found in Supplementary table S2.

Phylogenetic tree analysis

The DNMT domain of candidate enzymes were aligned using ClustalΩ [START_REF] Madeira | The EMBL-EBI search and sequence analysis tools APIs in 2019[END_REF] . The alignment was manually curated and trimmed using trimAL (removing >25% gap column) to align corresponding DNMT motifs in all gene families. A convergent phylogenetic tree was then generated using the online CIPRES Science gateway program [START_REF] Miller | Creating the CIPRES Science Gateway for inference of large phylogenetic trees[END_REF] using MrBAYES built-in algorithm. Default parameters were used with the following specifications for calculation of the posterior probability of partition:

sumt.burninfraction =0.5, sump.burningfraction = 0.5.

Cell cultures

Axenic Phaeodactylum tricornutum CCMP2561 clone Pt18.

CRISPR/Cas9 mediated gene extinction

The CRSIPR/Cas9 knock outs were performed as previously described [START_REF] Nymark | A CRISPR/Cas9 system adapted for gene editing in marine algae[END_REF] pPHAT-eGFP were co-transformed by biolistic in the Pt18.6 'Wild Type' strain as described in [START_REF] Nymark | A CRISPR/Cas9 system adapted for gene editing in marine algae[END_REF] . We also generated a line that was transformed with pPHAT-eGFP and pDEST-hCas9-HA but no guide RNAs. This line is referred as the Cas9:Mock line.

RNA and DNA extraction

Total

RT-QPCR and analysis

qPCR primers were designed using the online PRIMER3 program v0.4.0 defining 110-150 amplicon size and annealing temperature between 58°C and 62°C. Primer specificity was checked by BLAST on P. tricornutum genome at ENSEMBL. For cDNA synthesis, 1µg of total RNA was reverse transcribed using the SuperScript™ III First-Strand (Invitrogen) protocol. For quantitative reverse transcription polymerase chain reaction (RT-qPCR) analysis, cDNA was amplified using SYBR Premix ExTaq (Takara, Madison, WI, USA) according to manufacturer's instructions. CT values for genes of interest were generated on a Roche lightcycler® 480 qpcr system. CT values were normalized on housekeeping genes using the deltaCT method. Normalized CT values for amplifications using multiple couple of primers targeting several cDNA regions of the genes of interest were then averaged and used as RNA levels proxies.

Dot blot

gDNA samples were boiled at 95°C for 10 min for denaturation. Samples were immediately placed on ice for 5 min, and 250-500 ng were loaded on regular nitrocellulose membranes. DNA was then autocrosslinked in a UVC 500 crosslinker -2 times at 1200uj (*100). The membranes were blocked for 1 hr in 5% PBST-BSA.

Membranes were probed for 1 hr at room temperature or overnight at 4°C with 1:1000 dilution of 5mC antibody (OptimAbtm Anti-5-Methylcytosine -BY-MECY 100). 5mC signals were revealed using 1:5000 dilution of HRP conjugated antirabbit IgG secondary antibody for 1 hr at room temperature followed by chemo luminescence.

Loading was measured using methylene blue staining.

RNA sequencing and

Bisulfite sequencing analysis

Bisulfite analysis was performed using Bismark-bowtie 2 (babraham bionfinformatics).

We used the default Bowtie2 implements of bismark with the specifications that only uniquely mapped reads should be aligned. We also clearly specified that no discordant pairs of the pair-end reads should be aligned.

R version and tools

Analysis and graphs were made using R version 4.0.3. DMR calling analysis was performed using the DMRcaller package v1.22.0. UpSet plots were computed using UpSetR v1.4.0. Genomic overlaps were computed using genomation v1.22.0

DMR calling

Differentially methylated regions were called using the DMRcaller Rpackage [START_REF] Catoni | A versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts[END_REF] . Given the low level of correlation of DNA methylation observed in P. tricornutum [START_REF] Huff | Dnmt1-independent CG methylation contributes to nucleosome positioning in diverse eukaryotes[END_REF][START_REF] Veluchamy | Insights into the role of DNA methylation in diatoms by genome-wide profiling in Phaeodactylum tricornutum[END_REF] and low sequencing coverage in Pt18.6 (supplementary Figure S3), only cytosines with >=5X coverage in all three lines were kept for further analysis (supplementary Figure S3) and the bins strategy was favored over other built-in DMRcaller tools. DMRs were defined as 100bp regions with at least an average 20% loss/gain of DNA methylation in either one of the DNMT5:KOs compared to the reference strain. The 'Score test' method was used to calculate statistical significance and threshold was set at p.value <0.01. In addition, to separate isolated differentially methylated cytosines from regions with significant loss of DNA methylations, each hypoDMRs must contain at least 4 methylated cytosines in the reference strain.

Overlap with histone post translational modifications and genomic annotations.

Percentage overlaps between DMRs as well as the overlap of gene and TEs coordinates with histone posttranslational modifications and DMRs were calculated using the genomation R package computation [START_REF] Akalin | Genomation: A toolkit to summarize, annotate and visualize genomic intervals[END_REF] and the 'annotateWithFeature' and 'getMembers' functions. DMRs were extended 500bp in 5' and 3' to account for promoter and regulatory region marking. For RNAseq analysis, we analyzed the expression of TEgenes previously defined 39 . To define TE genes in DMRs we crosscheck overlapping TEgenes annotations with bona fide TEs in DMRs using 'annotatewithFeature' function

RNAseq analysis

150bp pair-end sequenced reads were aligned on the reference genome of P. tricornutum (Phatr3) using STAR (v2.5.3a). Expression levels were quantified using HTseq v 0.7.2. Differentially expressed genes were analyzed using DESeq2 v1.19.37.

FDR values are corrected P. values using the Benjamin and Hochberg method. categories.

Legend

Legend of supplemental information

Cladogram of the phylogenies of DNMTs (Figure 1a).

  a). The knockout of DNMT5 thus generated a global loss of all cytosine methylation in P. tricornutum.We asked whether the extensive loss of DNA methylation in DNMT5:KOs could define differentially methylated regions (DMRs) and computed DMRs between DNMT5:KOs and WT lines using the bins built-in DMRcaller 38 tools (material and method). DMRs corresponding to hypo methylated regions in DNMT5:KOs cover ~0.8% of P. tricornutum genome. In addition, 96% of DMRs found in M23 and M25 are shared while about 4% of DMRs are found in one mutant only, showing the consistent loss of DNA methylation in independent cell lines upon knockout of DNMT5

  and bcategory F). Up-regulation is also associated with hypoDMR regions co-marked by H3K27me, H3K9me3, H3K9me2, H3K4me3 and to a lesser extent H3K19_14Ac (Figure7aand b -category B, D and E). Interestingly, a subset of TEs in regions that were not highly methylated in the reference strain but marked by H3K27me3, H3K9me2 and H3K9me3 also show upregulation (Figure7a, bcategory C). TEs that overlap with hypoDMRs and heterochromatin regions of the genome are among the most highly expressed TEs in our datasets (Figure7bcategory B, D, E and F). Between mutants, M23 shows the highest number of TEs with significant changes in expression per epigenetic categories. However, levels of inductions are not statistically different except for the C

  . Our strategy consisted in the generation of short deletions and insertions to disrupt the open reading frame of putative DNMTs of P. tricornutum. We introduced by biolistic the guide RNAs independently of the Cas9 and ShBle plasmids, conferring resistance to Phleomycin, into the reference strain Pt18.6 (referred hereafter as 'reference line' or 'wild-type'-WT). Briefly, specific target guide RNAs were designed in the first exon of Phatr3_EG02369 (DNMT5), Phatr3_J47357 (DNMT6) and Phatr3_J36137 (DNMT3) using the PHYTO/CRISPR-EX 62 software and cloned into the pU6::AOX-sgRNA plasmid by PCR amplification. For PCR amplification, plasmid sequences were added in 3' of the guide RNA sequence (minus -NGG) which are used in a PCR reaction with the template pU6::AOX-sgRNA. Forward primer -sgRNA seq + GTTTTAGAGCTAGAAATAGC. Reverse primer -sequence to add in 3' reverse sgRNA seq + CGACTTTGAAGGTGTTTTTTG. This will amplify a new pU6::AOX-(your_sgRNA). The PCR product is digested by the enzyme DPN1 (NEB) in order to remove the template plasmid and cloned in TOPO10 E. coli. The sgRNA plasmid, the pDEST-hCas9-HA and the ShBLE Phleomycin resistance gene cloned into the plasmid

  RNA extraction was performed by classical TRIZOL/Chloroform isolations and precipitation by isopropanol. Frozen cell pellets were extracted at a time in a series of 3 technical extraction/duplicates and pooled. RNA was DNAse treated using DNAse I (ThermoFisher) as per manufacturer's instructions. DNA extraction was performed using the Invitrogen™ Easy-DNA™ gDNA Purification Kit following 'Protocol #3' instructions provided by the manufacturer. Extracted nucleic acids were measured using QUBIT fluorometer and NANODROP spectrometer. RNA and gDNA Integrity were controlled by electrophoresis on 1% agarose gels.

Figure 1 A.Figure 2

 12 Figure 1

Figure 3

 3 Figure 3

Figure 4 Figure 5 A.

 45 Figure 4Homozygous mutations generated by CRISPR/Cas9 in M23 and M25 lines at two independent target sequences. In M25, the mutation consists in 16 base pair out of frame deletion around CRISPR/Cas9 cutting sites that generates a loss of amino acids 28 to 34 leading to a premature STOP codon at amino acid 280. M23 has a 11 base pair out of frame deletion that generates a loss of amino acids 58 to 60/61 followed by a premature STOP codon at amino acid position 179-180 from ATG

Figure 6 A.

 6 Figure 6 A. Volcano plot of gene and TE genes overexpression in DNMT5:Kos M25 and M23 show upregulation of transposons. B. Overlap between gene and C. TEs overexpression between DNMT5:KOs.

Figure 7 A.

 7 Figure 7

  D2 : DNMT2 family; D3 : DNMT3 family; D4 : DNMT4 family; D5(abc): DNMT5 subfamilies; D6: DNMT6 family; D1: DNMT1 family; CMT: chromomethylase family. Sequences are colored by lineage assignment. The phylogenetic tree depicted in figure 2 is also showed.

Figure S2 A.

 S2 Figure S2

Acknowledgements

We thank Catherine Cantrel form IBENS for media preparation. LT acknowledges funds from the CNRS, the region of Pays de la Loire (ConnecTalent EPIALG project) and Epicycle ANR project (ANR-19-CE20-0028-02). CB acknowledges funding from the ERC Advanced Award Diatomite.

and 7C6 are DNMT5:KOs lines not further investigated in this study. We could not detect DNA methylation at comparable levels to the reference strain in any DNMT5:KO lines. D. As for C with serial dilutions of DNMT5:KOs M23 genomic DNA. Background level of DNA methylation are observed. Loading control is obtained by methylene blue staining.

Figure S3

A. And B. Intersection between genes and TEs found methylated in this study compared to previously identified methylated genes and TEs (Veluchamy et

Supplementary table S1

List of putative DNMTs fetched by HMMER in the MMETSP database ("HMMER hits") and reciprocal best hits search in the phylogenetically optimized database described in [START_REF] Dorrell | Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome[END_REF] . When already reported in other studies we added references. We also added enzymes found in reference database and literature in the tree for comparison purposes. References -MMETSP [START_REF] Keeling | The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing[END_REF]

Supplementary table S2

Representative microeukaryote enzymes used for phylogenetic analysis (Figure 1a) and their structure as given by eDAF pipeline.

Supplementary table S3

Species level summary of DNMTs found in microeukaryotes. Presence "1" or absence "x" of at least one DNMT transcript or gene per species.

Supplementary table S4

Summary of number of DNMTs per diatom species. Numbers indicate the number of putative paralogues for each gene family in each species. The common ancestor of diatoms likely possessed a DNMT3, DNMT6, DNMT5b and DNMT2 enzyme while DNMT5a is restricted to pennate diatoms. Iterative lineage specific loss of DNMTs is observed as between Fistulifera solaris, Fragilariopsis cylindrus and P. tricornutum. P. tricornutum (in red) is the reference species for epigenomics in diatoms and lack DNMT5b and DNMT4 orthologues. c-chromodomain containing-DNMT4 ; genzyme found in annotated genomes.

Supplementary table S5 and S6

Summary of DMR analysis in DNMT5:KOs M23 and M25 respectively. For each mutants, DMR coordinates, number of methylated reads/unmethylated reads and pooled %level of DNA methylation are showed. loss = hypoDMRs, gain = hyperDMRs

Supplementary table S7

Methylation of genes and transposable elements in the reference strain and overlap with hypoDMRs in M23/M25. For each gene and transposable element, the number of methylated cytosines and associated average DNA methylation level, methylated and unmethylated read counts are showed.

Supplementary table S8

Summary of RNAseq analysis.

Supplementary table S9

TE genes association with the epigenetic landscape of P.tricornutum in respect to upregulation in D5:Kos

Supplementary table 10

TopGO results of molecular function gene ontology enrichment of genes upregulated in both DNMT5:KOs. For each GO, the number of significant genes and the associated Fischer p.value is indicated. Only GOs with Fisher exact p.value <0.05 are shown.

Supplementary table S11

TopGO results of biological process gene ontology enrichment of genes upregulated in both DNMT5:KOs. For each GO, the number of significant genes and the associated Fischer p.value is indicated. Only GOs with p.value <0.05 are shown.

Supplementary table S12

Summary and list of upregulated genes in DNMT5:KOs.

Supplementary table S13

Summary and list of downregulated genes in DNMT5:KOs.

Author Contributions