Kamel Bouzgou
email: kamel.bouzgou@univ-evry.fr

Laredj Benchikh
email: laredj.benchikh@univ-evry.fr

Lydie Nouveliere
email: lydie.nouveliere@univ-evry.fr

Yasmina Bestaoui

Zoubir Ahmed-Foitih

PD Sliding Mode Controller Based Decoupled Aerial Manipulation

Keywords: Aerial Manipulation, Decoupled Dynamic System, SMC, Sliding Mode Control, PD-SMC

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INTRODUCTION

Unmanned aerial manipulators (UAMs) are used for mobile manipulations thanks to their mobility which enables a simple hovering to aggressive manoeuvrers. It has emerged a need for the interaction of that UAVs with the environment that is not easily accessible by humans, for this aim, the researchers have used this structure for transporting, manipulation and grasping tasks. Moreover, the control of these aerial manipulator is a very challenging problem, considering that such system is under-actuation and the coupled dynamics between the two different platforms, and the contact with the environment during manipulation. Several survey papers deal with projects that the multi-link robotic arm attached to the UAV for manipulation tasks are used, the dynamic formalism and control technique developed. Authors in (Bouzgou et al., 2019a) have classified aerial manipulator systems based on aerial vehicles and the attached arm kind. For the simple grasping task, a magnet attached to the UAV is presented in [START_REF] Escareno | Task-based control of a multirotor miniature aerial vehicle having an onboard manipulator[END_REF]. A single Dof to push an object in the desired direction, in [START_REF] Srikanth | Controlled manipulation with multiple quadrotors[END_REF][START_REF] Yeol | Design and analysis of a multiple tentacle system for mobile manipulation in micro aerial vehicles[END_REF] is designed Figure 1: The structure of Q-PRR with principal frames as a non-prehensile manipulation and tentacle system. The most structure of aerial manipulator arm is when a 2-Dof robot arm iw mounted [START_REF] Aydemir | Disturbance rejection control of a quadrotor equipped with a 2 dof manipulator[END_REF][START_REF] Kim | Aerial manipulation using a quadrotor with a two dof robotic arm[END_REF], that number of dof can help users to avoid a singularity region in the manipulator arm workspace. A 3-Dof manipulator arm as revolute joints is used in [START_REF] Mello | Wholebody modeling and control of an unmanned aerial manipulator[END_REF], when 4-Dof multi-link manipulator arm is presented in [START_REF] Jimenez-Cano | Aerial manipulator with a compliant arm for bridge inspection[END_REF] as a serial robot placed at the upper part of the UAV for bridge inspection. In [START_REF] Kondak | Closed-loop behavior of an autonomous helicopter equipped with a robotic arm for aerial manipulation tasks[END_REF] authors are used a 5-Dof manipulator robot for environment interaction. An industrial manipulator as a redundant robot arm with n > 6 is used in [START_REF] Huber | First analysis and experiments in aerial manipulation using fully actuated redundant robot arm[END_REF] aerial manipulation with a 7-Dof based on a main-tail-rotor helicopter, in [START_REF] Danko | Design and control of a hyper-redundant manipulator for mobile manipulating unmanned aerial vehicles[END_REF] the Hyper-redundant manipulator is presented as 9-Dof for a wide reachable workspace. A delta structure fixed on side of UAV was introduced in [START_REF] Fumagalli | Developing an aerial manipulator prototype: Physical interaction with the environment[END_REF], when a parallel robot is used in [START_REF] Cho | Development of a visionenabled aerial manipulator using a parallel robot[END_REF][START_REF] Danko | A parallel manipulator for mobile manipulating uavs[END_REF]. For an object interaction and manipulation applying forces and torques, a dual 4-dof arm mounted on UAV is presented in [START_REF] Korpela | Dynamic stability of a mobile manipulating unmanned aerial vehicle[END_REF]. Researchers in [START_REF] Ruggiero | A multilayer control for multirotor uavs equipped with a servo robot arm[END_REF], have developed a structure with a moving battery of the UAV in one direction in order to hold the Multirotor CoG as close as possible to the vertical axis, The drawback of such structure is that battery movement is bounded when the end-effector tried to reach the position and battery position cannot always ensure the alignment of CoM of UAV and robot arm. A new aerial manipulator with a 3-Dof is developed in this paper [START_REF] Bouzgou | A novel aerial manipulation design, modelling and control for geometric com compensation[END_REF], the alignment of CoG of whole system can be ensured with a simple movement of a prismatic joint along x-axis Figure 1. wide workspace with this design and offering large possible configurations of the robot arm for a desired position and attitude without losing the optimum location of the Q-PRR CoG (Bouzgou and Ahmed-Foitih, 2015). An adaptive sliding controller based on a traditional Lagrange modeling method was proposed [START_REF] Kim | Aerial manipulation using a quadrotor with a two dof robotic arm[END_REF], An augmented adaptive sliding controller based on a closed-chain robot dynamics was presented for cooperative transportation of multiple [START_REF] Lee | Path planning and control of multiple aerial manipulators for a cooperative transportation[END_REF] online estimation of objects based on an augmented adaptive sliding controller was proposed.

MODELING

The configuration of the proposed aerial manipulator consists of two parts, the multi-rotor with the number of rotors that n r = 4 that can be called with the letter "Q" for Quadrotor more details see (Bouzgou et al., 2019a), and the manipulator arm attached to the bottom, whose geometric centers are considered to be in the same z axis ( b 3 ) of the mobile frame B. The manipulator consists of three degrees of freedom (3-Dof), Prismatic-Revolute-Revolute joints, called (Q-PRR), the first joint is prismatic and its axis (x 1 ) is parallel to the x-axis of the multirotor mobile frame B, this joint is considered actuated and it moves along the same axis, and it is bounded on both directions by a value r 0 , the distance between two axes x b and x 1 is denoted by (d 0 ), The second and third joints are revolute, their rotation axes (z 2 )and (z 3 )are parallel to the (y) axis of the B unit, where the manipulator arm movements are considered in the (x, z)-axis of the B mobile frame. The position of the B fixed frame with respect to the E inertial frame is given by the (3 × 1) vector denoted by p b , whereas its orientation denoted by R b is represented by the XY Z rotation sequence with the fixed frame axes, and its orientation by the fixed frame axes.

R b =   c θ c ψ s φ s θ c ψ -c φ s ψ c φ s θ c ψ + s φ s ψ c θ s ψ s φ s θ s ψ + c φ s ψ c φ s θ s ψ -s φ c ψ -s θ s φ c θ c φ c θ   (
T (φ b ) =   1 0 -s θ 0 c φ s φ c θ 0 -s φ c φ c θ   (5)
By differentiating (2), (3) and with taking into account (4), the translational and angular velocities of the end-effector with respect to E can be written as follows:

ṗe = ṗb -R b p b eb T (φ b ) φb + R b ṗb eb ( 6
)

ω e = T (φ b ) φb + R b ω b eb (7)
Where ṗb , ω b are the linear and angular velocities of the mobile frame B with respect to the E frame, respectively, and ṗb eb , ω b eb are the translational and angular velocities of the end-effector with respect to the mobile frame B. (.), the hat map that transforms a vector in R 3 to (3 × 3) Skew-symmetric matrix such that xy = x × y, ∀ x, y ∈ R 3 [START_REF] Kamel | Dynamic modeling, simulation and pid controller of unmanned aerial vehicle uav[END_REF].

The dynamic model of Q-PRR can be derived by considering the Lagrange formulation in details in [START_REF] Lippiello | Cartesian impedance control of a uav with a robotic arm[END_REF]. The function of Lagrangian is then expressed by L = E -U where E, U denote the kinematics and potential energy of the whole system, respectively. The Lagrange equations are given by

d dt δL δ ξi - δL δξ i = u + u ext (8)
Where i = 1, ..., 6 + n is the ith coordinate of ξ, and u i is the ((6 + n) × 1) vector of generalized forces and torques, and u ext denotes the vector of external disturbance forces and torques. the dynamic model of the global system can be written as

B(ξ) ξ +C(ξ, ξ) ξ + G(ξ) = u + u ext ( 9
)
Where G is a ((6 + n) × 1) vector of terms given by deriving the potential energy as G(ξ) = δP δξ And C is the matrix of Coriolis and centrifugal terms. more details see [START_REF] Bouzgou | A novel aerial manipulation design, modelling and control for geometric com compensation[END_REF]. u i is the vector of generalized forces at the i-th joint level. τ b is the vector of torques composed with τ φ , τ θ and τ ψ generated by the system computed around x,y and z axes respectively. Let µ be the vector of the force f r 0 applied to the prismatic joint and τ θ 2 , τ θ 3 torques applied by the revolute joint of the robot

arm. u =   u f b u τ b u µ   =   R b f b R T b T b τ b µ   =diag(R b , Q, I n ) f b =   0 0 f bz   , τ b =   τ φ τ θ τ ψ   , µ =   f r 0 τ θ 2 τ θ 3   f bz τ b =    1 1 1 1 0 l 0 -l -l 0 l 0 c -c c -c       f 1 f 2 f 3 f 4    ( 10
)
Where l is the distance from each motor to the multirotor centre of mass. When c is the drag factor. Since B(ξ i ) is symmetric B i j = B T ji , and Let the matrices M pp , M pϕ , M pq, M ϕϕ , M ϕq , M qq be defined by partitioning the mass matrix and by according to the equation defined in Equation 9 the decoupled dynamic model for the overall system is presented and a sub-matrices are given from that equation and can be rewrite as follows

B(ξ i ) =   B pp B pϕ B pq B T pϕ B ϕϕ B ϕq B T pq B T ϕq B qq   (11) C(ξ, ξ) =   C p C ϕ C q   , G(ξ i ) =   G p G ϕ G q  
The dynamic modeling of the decoupled system is presented as follows For the multirotor, a new coordinate joint can be defined as a part of the generalized coordinates xi i such that q m = p b ϕ b T . Multirotor motion equations Equations to respect the Lagrange formalism in Equation 9and the decomposition of the B,C and G matrices can be defined as follows

B pp pb + B pϕ φb +C p ṗb + G p + B pq qeb = u f b (12) B T pϕ pb + B ϕϕ φb +C ϕ φb + G ϕ + B ϕq qeb = u τ b (13)
B T pq pb + B T ϕq φb +C q qeb + G q + B qq qeb = u µ (14) From the equation 12 and 13, the dynamic model can be simplified with taking into account the decoupled terms. Rewrite that with the model defined in [START_REF] Kamel | Dynamic modeling, simulation and pid controller of unmanned aerial vehicle uav[END_REF], where M p = B pq qeb , M ϕ = B ϕq qeb and M q = B T pq pb + B T ϕq φb ∈ R 3×1 , such as

M p = M x M y M z and M ϕ b = M φ M θ M ψ . Equations becomes as m ẍ = (c φ s θ c ψ + s φ s ψ )u 1 -M x (15) m ÿ = (c φ s θ s ψ -s φ c ψ )u 1 -M y (16) mz = (c φ c θ )u 1 -mg -M z (17)
I x φ = θ ψ(I y -I z ) -J r θΩ r + lu 2 -M φ (18)
I y θ = φ ψ(I z -I x ) -J r ψΩ r + lu 3 -M θ ( 19
)
I z ψ = φθ (I x -I y ) + u 4 -M ψ (20)
where, Ω r = (ω 2 + ω 4ω 1ω 3 ), I x , I y , I z are the inertia matrix terms and m the multirotor mass.

The dynamic modeling of the robot arm is defined using a Lagrange Formalism depicted in Equation 9, where the jacobians matrix are defined by using a Denavit-Hartenberg method depicted in (Bouzgou and Ahmed-Foitih, 2014)and its equation of movement can be presented as follow

f r 0 = (m 1 + m 2 + m 3 )r 0 + 1 2 m 3 ( 1 2 d 3 c θ 2 +θ 3 + d 2 c θ 2 ) + d 2 m 2 c θ 2 θ2 + 1 2 (d 3 m 3 c θ 2 +θ 3 ) θ3 - 1 2 2m 3 ( 1 2 d 3 s θ 2 +θ 3 + d 2 s θ 2 ) + d 2 m 2 s θ 2 θ2 2 - 1 2 d 3 m 3 s θ 2 +θ 3 θ2 3 -d 3 m 3 s θ 2 +θ 3 θ2 θ3 -g(m 1 + m 2 + m 3 ) (21) τ θ 2 = (m 3 ( 1 2 d 3 c θ 2 +θ 3 + d 2 c θ 2 ) + 1 2 d 2 m 2 c θ 2 )r 0 + I y3 + I z2 + 1 2 m 2 d 2 2 + d 2 2 m 3 + 1 4 m 3 d 2 3 + d 2 d 3 m 3 c θ 3 θ2 + 1 4 m 3 d 2 3 + 1 2 d 2 d 3 m 3 c (θ 3 ) + I y3 θ3 - 1 2 I x3 s 2θ 2 +2θ 3 -I z3 s 2θ 2 +2θ 3 + d 2 d 3 m 3 s θ 3 θ2 3 d 2 d 3 m 3 s θ 3 θ2 θ3 -g m 3 ( 1 2 d 3 c θ 2 +θ 3 + d 2 c θ 2 ) + 1 2 d 2 m 2 c θ 2 (22) τ θ 3 = 1 2 d 3 m 3 c θ 2 +θ 3 r0 + I y3 + 1 4 m 3 d 2 3 + 1 2 d 2 d 3 m 3 c θ 3 θ2 + I y3 + I z3 + 1 4 m 3 d 2 3 + I x3 s 2 θ 2 +θ 3 -I z3 s 2 θ 2 +θ 3 θ3 + 1 2 d 2 d 3 m 3 s (θ 3 θ2 2 + 1 2 2I x3 c θ 2 +θ 3 s θ 2 +θ 3 -2I z3 c θ 2 +θ 3 s θ 2 +θ 3 θ2 3 + s 2θ 2 +2θ 3 (I x3 -I z3 ) θ2 θ3 - 1 2 d 3 gm 3 c θ 2 +θ 3 (23)
Where, c * = cos( * ),s * = sin( * ). These equations can be rewritten as a matrix forms regarding to the Equation 14.

CONTROL DESIGN

This section describes the design of the controller for the decoupled system, it is composed into three parts, attitude control of the multirotor as a function of the position of the desired center of gravity; and control of the manipulator arm when the system reaches the target position point, the PID proportional integral derivative controller is used for the multirotor and the sliding mode technique for the manipulator arm and then it will be improve when the PID will be added in parallel. Figure 2 shows the diagram of the control strategy. From the dynamic equations , we have a decoupled system where the translational accelerations don't depend on angular acceleration, from the first three equations we can extract the pitch and roll angles when we introduce the desired position and attitude. From equations 15, 16, 17, θ and φ can be computed and its depended on multirotor position vector and altitude x y z ψ , therefore, it can be writing as follows

(θ) = ẍ + M x m c ψ + ÿ + M y m s ψ z + g + M z m (24) sin(φ) = ẍ + M x m s ψ + ÿ + M y m c ψ ẍ + M x m 2 + ÿ + M y m 2 + z + g + M z m 2 (25)
When the reference value for the roll and pitch angles has been calculated, the control inputs of those angles can be determined, and the feedback of the speed time derivative will be required to determine the input vector, in the continuous time,the parallel PID controller is defined, it have a following form

u(t) = K pζ e(t

Manipulator arm controller

For the manipulator arm, sliding mode control strategy will be presented, the main idea of this approach can be presented as follows Considering the non-linear n-order object defined as

x (n) (t) = f (x,t) + u(t) ( 27
)
where x is the state variable,u is the control law. Let be e is the error between desired and measured value of x, such as e = x desx, let be s = 0 as a sliding surface defined by s = e (n-1) + λ 1 .e (n-2) + ...

+ λ n-2 ė + λ n-1 .e (28)
Where λ is the coefficient of the sliding surface.

Derivative the equation 28, it can write ṡ = e n + λ 1 .e (n-1) + ... + λ n-2 .e 2 + λ n-1 . ė (29)

Using Equation 27and with choosing the input control vector u that ṡ = Ksgn(s) with K is positive defined. substituting into Equation 29, the following equation can be rewritten

u = -f (x,t)+x (n)
des +λ 1 .e (n-1) +...+λ n-1 . ė+Ksgn(s) (30) sgn is the sign function, applying equation 30 with n = 2 and for three link robot arm ẍ = f (x,t) + u(t). The input control law is as follows

u(t) = -f (x,t) + q des + λ. ė + Ksgn(s) (31)
With q des = r 0,des θ 2,des θ 3,des

T , λ = λ 1 λ 2 λ 3 T and K = K 1 K 2 K 3 T

SIMULATION AND RESULTS

Simulations were conducted to evaluate the performance of the aerial manipulator in maintaining an end-effector relative to fixed targets. the desired position of the multirotor is given by p b [m] = 20 30 10

T , and when the roll and pitch angles of the multirotor are considering as zero, the movement of the arm will be started, and the desired trajectory of all joints is given by p eb = 0.04 0.6 0.2 T [m,rad,rad]

The simulation results are summarized in Figure 3. The position errors of the end-effector can be summarized in the Figure 4 5 CONCLUSIONS In this paper, a mathematical model for a decoupled system (multirotor and robot arm) is presented by using the Denavit-Hartenberg approach for geometric modeling of a manipulator arm, and a Lagrange Formalism for dynamic modeling of both a Multirotor and arm . The system dynamics is decoupled in two separate subsystems, one concerning the position of the center of mass where a PID controller is used to keep a stability of the whole system during hovering, a second subsystem concerning the attitude of the manipulator arm, which the sliding mode controller is used to control each link for a path trajectory between a start point to a desired position of the endeffector. That controller is modified and PD terms are added for the sliding mode blocs in order to improve the output signal and defined good stability of the Q-PRR. Simulation works are presented which validate and show the efficiency of the proposed approach. Future works will present an another approach for a dynamic model by using a SimMechanics and VRML environment (Bouzgou et al., 2014) (Bouzgou et al., 2015).

  1) where s * = sin( * ), c * = cos( * ), Let R b e be the orientation matrix of the end-effector attached frame, and p b e = x eb y eb z eb T the position vector of the origin with respect to B fixed frame, and the absolute position vector and orientation matrix of the end-effector with respect to E, is given by the p e = x e y e z e T and R e , respectively, where the pair (p b , R b ) ∈ SE(3) denotes the vector position given by p b = x b y b z b T , and the orientation matrix of the multirotor with respect to the inertial frame E. The position and orientation equations of end-effector expressed in E are written as follows: p e = p b + R b p b e φb the time derivative of ϕ b . ω b = T (φ b ) φb (4) Where T (φ b ) is the transformation matrix between the time derivative of the Euler angles ϕ b and the angular velocity of the multirotor ω b .

Figure 2 :

 2 Figure 2: Diagram of the control strategy

  Position of the multirotor centre of gravity in Figure 3a, the orientation of the multirotor fixed frame B to respect to the reference frame E in the Figure 3b

Figure 4 :

 4 Figure 4: Position Errors of the CoM of Q-PRR

  = ζ dζ, is the error between the desired and measured value of ζ and K pζ , K iζ are Proportional and Integral gain,respectively.

	) + K iζ	0	t	e(τ)dτ + K dζ	de(t) dt	(26)
	ζ is the variable to be controlled. ζ ∈ {x, y, z, φ, θ, ψ}
	Where,e(t)


X Mougeot

M.-M Bé

V Chisté

C Dulieu

V Gorozhankin

M Loidl

Calculation of beta spectra for allowed and unique forbidden transitions

In ionizing radiation metrology, the energy spectra of beta decays are often needed, especially when measurements are carried out using Liquid Scintillation Counting. The uncertainties on activity measurements can be reduced with a precise knowledge of the shapes of the beta spectra. The few studies which have been conducted on this subject since the 1970s were mainly focused on allowed and first non-unique forbidden transitions. But it is also necessary to have a good knowledge of spectra for unique and non-unique forbidden transitions of higher orders. Our goal is to develop a computer program for calculating beta spectra, validated by experiments, including evaluated uncertainties on the shapes. The exhaustive evaluation of form factors measured so far shows that there are not enough good data to validate those complex calculations. All these considerations highlight the need for a consistent experimental program in which all the distortion phenomena of beta spectra should be analysed and quantified very carefully. This paper describes the present features of the computer program we have developed, BetaShape, and specifies the future work which should be undertaken to improve it.

Introduction

As evaluators of nuclear decay data, we notice an increasing demand from users for a precise knowledge of the shape in energy of beta spectra, coupled with well established uncertainties. For example, these spectra are useful in nuclear power plants for calculations of the residual power, or in medical care for calculations of doses delivered to patients' cells. In ionizing radiation metrology, a better knowledge of the spectra would reduce the uncertainties on the activity measurements carried out by ionisation chambers or Liquid Scintillation

Counting.

To answer the users' demand, calculations are needed because all the wanted beta spectra cannot be measured: very short half-lives, compound spectra, etc. Carrying out experiments is also necessary to test and validate the models. The critical point is then to quantify all the phenomena that distort a measured beta spectrum: backscattering, bremsstrahlung, response function of the detector, dead zones, source quality (thickness, size and impurities), etc. Thanks to the increasing power of the computers, it is now possible to consider more complex models for the theory, and more complex Monte-Carlo simulations for the experiments.

While the allowed transitions are well known, this is not the case for spectra of unique and non-unique forbidden transitions of higher orders. V. Gorozhankin made a bibliographical compilation of the published form factors up to 2003 [11Go] in order to determine the mean form factors which could be applied to all spectra. However, it is clear that there are not enough experiments to validate the theoretical evaluations of forbidden transitions. Only about ten form factors have been published since 1976, and concerning the theory we are in the same situation: theorists are not working anymore on beta spectra.

The analysis of various available computer codes led us to develop our own program, which is called BetaShape. BetaShape was developed as a C++ class, allowing an easy implementation in a Monte-Carlo simulation code or in a nuclear database program. Most of these codes calculate only beta spectra of allowed transitions, and give the possibility to add an experimental shape factor. The energy dependence of these shape factors is usually determined using a Kurie plot (defined in section 2.5). The energy parameterizations are summarized in [START_REF] Behrens | Shapes of beta spectra[END_REF] and [11Go]. The Radlist program [START_REF] Burrows | The Program RADLST[END_REF] calculates spectra up to the third unique forbidding order without experimental shape factor. We have decided to follow the same approach and to improve it.

Calculation method

Basic formulae

A beta spectrum is the result of a weak interaction coupling constant g, a statistical phase space factor which reflects the momentum distribution between the electron and the neutrino, the so-called Fermi function F which corrects for the Coulomb effects, and a shape factor C which contains the relevant information about the nuclear structure. The number of beta particles emitted per unit of time with the energy W, in the range between W and W+dW,

is [69Be]:   dW W C W Z F W W W g dW W N ) ( ) , ( 2
² ) ( 2 0 3     (1)
where: the normalized energy W = 1 + E kin /m, with E kin the kinetic energy of the particle and m the electron mass at rest; the corresponding normalized momentum  = (W²-1) 1/2 ; the endpoint normalized energy W 0 = 1 + E max /m, with E max the end-point energy of the particle; and Z the atomic number of the daughter nucleus.

The transition order depends on the variations of the total angular momentum (J) and of the parity of the initial and final nuclear states. The shape factor C(W) depends on the transition order and on the nuclear matrix elements of the weak interaction operators, but their exact calculation is a difficult task. In the case of allowed and unique forbidden transitions, the energy dependence of the nuclear matrix elements can be factored out [START_REF] Gove | Log-f tables for beta decay[END_REF]. Thus, their energy independent part just appears as a normalization factor in the calculation of the shape of a given beta spectrum, and can be left out. This factorization is not possible in the case of the non unique forbidden transitions. The specific calculation of these transitions is difficult because of the large number of nuclear matrix elements to calculate. A usual approximation is to calculate non-unique transitions as unique transitions having the same variation of the total angular momentum.

As in the Radlist program [START_REF] Burrows | The Program RADLST[END_REF], the BetaShape program follows the Gove and Martin's approach [START_REF] Gove | Log-f tables for beta decay[END_REF]. The calculated spectrum is:

) , ( )² ( ) ( 0 W Z S W W W W N n   (2) with:             1 1 ) 1 ( 2 0 ) 1 ( 2 ]! 1 ) 1 ( 2 [ )! 1 2 ( ) ( ) , ( ) , ( n k k n k k n k n k W W W Z W Z S   (3), 2 1 2 2 ) ( ! )! 1 2 ( ² 2 ) , (             k k k k R k f g W Z    (4),
    0 ) ( ) ( ) ( 1 ) ( 0 ) ( ) ( ) ( 1 ) (             r g r V m E r f r r f dr d r f r V m E r g r r g dr d tot tot         (5)
where E tot is the total particle energy, V(r) the Coulomb potential generated by the Z protons of the nucleus, and  the angular momentum quantum number. , a non zero relative integer, is the eigenvalue of the operator

  1    L K    
, with  the Dirac's matrix,   the Pauli's matrices and p r L

    
the classical angular momentum operator.

If the nucleus is considered as a point source, the equations (5) can be solved analytically and the calculations are fast. They can also be solved numerically: the description of the nucleus can be then more realistic, but the calculations need a lot of computing power.

Therefore, theorists used to generate tables of data from which it is necessary to interpolate some values in order to calculate the needed beta spectra (

)] , , ( [ 1 )] , , ( [ 1 1 1 1 1 z b a F S Q W g z b a F S Q W f k k k k k k       (6) with: ) 1 2 ( 2 ) ( ) 2 ( 2 /      k k y k W R iy e R Q k      (7), iy W iy k e iy S k R i k k          / ) ( (8), )² ( ² Z k k     ,  ZW y  , iy a k    ) 1 ( , ) 1 2 (   k b  , and R i z  2  . (9)
Conventionally, Z is positive for beta minus decays and negative for beta plus decays.

1 F 1 (a,b,z) is the confluent hypergeometric function, defined using the (z) function.  is the fine structure constant.

When the particle momentum tends to zero, the electron spectrum tends to a finite value while the positron spectrum tends to zero. For W less than 1+510 -6 , the calculation of the electron wave functions is thus modified:

  2 1 2 2 2 1 1 1 2 ) ( 2 1 2 4 1 2 ) ( ) ( 1 2 4 1 2 ) ( ) 1 2 ( ) ( ) 2 ( 2 2                                                           k k k k k k k k k ZR ZR Z k k ZR Z Z R g f k k                 (10)
Three correction terms are added: the screening effect due to the electron cloud of the daughter atom, the finite nuclear size effect with regard to the electron Compton wavelength, and the radiative corrections.

Screening effect correction

To correct for the screening effect, the method of R.H. Good Jr is used [START_REF] Good | Effect of atomic electron screening on the shape of forbidden beta spectra[END_REF], taking a potential V 0 which depends on the beta decay type:

 378983 , 1 5 0 10 971217 , 6 ) ( Z V      , and W becomes (W-V 0 ) if (W-V 0 )>1,              ² exp ) ( ) ( 0 0     b a V V , (11) 102
          Z Z Z a , 0156 , 0 10 60 , 3 ² 10 83 , 3 10 42 , 2 5 6 3 8            Z Z Z b ,
and W becomes W+V 0 .

For beta minus transitions, this correction is applied only above a threshold energy mV 0 , which induces a non-physical discontinuity in the spectrum. For Z less than 100, this threshold is less than 20 keV. The normalized momentum  is recalculated with the new W value. These new values are introduced in the calculation of S n (Z,W) and in the phase space factor, except in the neutrino energy (W 0 -W).

Finite nuclear size correction

The finite nuclear size effect reflects the influence of the nuclear charge distribution on the beta spectrum. The adopted correction is given by [71Go]:

 ) , ( W Z k  becomes ] 1 [ k k      ,  0   k  if 1  k , or 50 ) (    Z , or 80 ) (    Z ,  ] ) 50 ( 10 4 10 25 )[ 50 ( ) ( 6 4 1 W Z Z              if 50 ) (    Z , (12)
                    ² 10 88 10 63 10 17 ) 80 ( ) ( 4 5 5 1 W W W Z   if 80 ) (    Z .
This correction is applied for heavy nuclei and if k = 1 only. The authors in [START_REF] Gove | Log-f tables for beta decay[END_REF] determined it from the

) , ( W Z k  
plots published by M.E. Rose and D.K. Holmes ([51Ro],

[57Ro]).

Radiative corrections

The radiative corrections take into account the energy loss of the electron in the electromagnetic field of the nucleus (virtual photons and internal bremsstrahlung). They are calculated as described in [START_REF] Behrens | Electron radial wave functions and nuclear beta decay[END_REF], [START_REF] Sirlin | General properties of the electromagnetic corrections to the beta decay of a physical nucleon[END_REF], and [START_REF] Jaus | Electromagnetic corrections of order Z² and Z² 3 to Fermi beta decays[END_REF]. The spectrum is corrected for using a factor  

) , ( 1 Z W R   calculated as follows: ) ( ) ( ) ( ) ( ) , ( 4 3 2 1 Z Z Z W Z W R          (13) with:  ) , ( 2 ) ( 0 1 W W g W     ,                                                                   arcth W W W arcth L W W W W W arcth m m W W g 4 ² 6 )² ( ² 1 2 1 2 4 2 ln 2 3 3 1 4 4 3 ln 3 ) , ( 0 0 0 0 (14), W /    ,    x dt t t x L 0 ) 1 ln( ) (
the Spence function, and m p the proton mass at rest,

          m m Z Z p ln ² 1 . 1 ) ( 2   , (15)                   m m Z Z p ln 3 ² 2 3 2 ln 3 ² ) ( 3 3     (16),           m m Z Z p 2 ln 2 ) ( 3 4    . (17)

Remarks

The beta spectrum is evaluated using equation (2) for a large number of energies. It is then normalized by its integral and the mean energy is determined. If an experimental spectrum is available, the BetaShape program calculates also the corresponding Kurie plot defined by: ) , (

) ( ) ( exp W Z WS W N W K n   . ( 18
)

Comparison of the results

Radlist

We compared the results of our calculations with those of the Radlist program [START_REF] Burrows | The Program RADLST[END_REF],

which uses the same assumptions but does not take into account the radiative corrections.

Thus, we switched them off for these comparisons. Numerical integration methods and digit precisions (double in BetaShape, float in Radlist) are also different.

We considered a wide range of Z, A, end-point energies and transition orders. A total of 38 transitions, listed in Table 1, were calculated. The non-unique transitions are calculated as unique transitions having the same variation of the total angular momentum.

Both codes give the same results over almost the entire spectrum (discrepancy less than 1 %). Because of the difference of the digit precisions, the energy thresholds mV 0 of the screening correction present a difference of about 200 eV. This implies a difference between 3 and 5 % over a narrow range, typically in one energy bin. For beta plus decay, the screening correction depends on the particle energy, and thus induces a shift over the entire spectrum. A difference higher than 10 % could be observed at very low energies, where this contribution has the greatest influence.

Beta Spectrum

The Beta Spectrum program has been developed by V. Gorozhankin et al. [11Go].

This program calculates the beta spectra shapes using the Behrens tables or the Dzhelepov tables for the Fermi function, according to the user's choice.

The Behrens and Dzhelepov calculations correct for the screening effect and the finite nuclear size effect, but do not take into account the radiative corrections. The Dzhelepov tables are given from 5 keV to 10 MeV. The Behrens tables cover the range 2.6 keV to 25

MeV without corrections, so it is necessary to correct these data using other tables, also provided by Behrens, but more restricted in energy. V. Gorozhankin et al. showed that the choice of the tables used does not induce discrepancies higher than 1 % in most cases.

Discrepancies around 5 % could occur for radionuclei having a low Z or an end-point energy lower than 100 keV.

We compared the results of our calculations with those obtained with Beta Spectrum for the allowed and first non unique forbidden transitions listed in Table 1. We switched off the radiative corrections and we used the Dzhelepov tables. If we compare the relative difference between the two programs, the discrepancy is about 0.5 % and some fluctuations are present, which mainly come from the interpolation between the tabulated values of the Fermi function. It is noteworthy that this good agreement is obtained by switching off the screening correction in BetaShape. Otherwise, the discrepancy can be higher than 1 % in some cases, suggesting that the screening effect was not corrected in the Dzhelepov tables.

Influence of the various corrections

The magnitude of each correction is detailed in Table 2 for some nuclei.

In the calculation model of the BetaShape program, the spectrum shape depends on the adopted transition order. To illustrate the influence of the transition order on the spectra calculated by BetaShape, we took the 99 Tc spectrum as an example. Four cases are considered, as described in Figure 1: an allowed, first, second and third unique forbidden transitions. The shapes are very different from the beginning to the end of the spectrum and the mean energies differ by at least 15 %. The true order of this transition is second nonunique forbidden, calculated as a first unique forbidden according to our assumptions.

Obviously this approximation needs an experimental validation, with a careful analysis of the distortion sources of the measured spectrum.

One can observe, in Figure 1, a discontinuity at low energy due to the screening correction. As described in Section 2, it occurs below 20 keV for Z less than 100. This discontinuity could easily be smoothed out using different kinds of functions, but each function will affect the spectrum shape differently. Thus, we need some experimental spectra to derive a smooth function. The radiative corrections and the finite nuclear size correction are usually weak. The finite nuclear size correction is less than 0.5 %. The radiative corrections are important near the end-point energy (several tenths of percents), but as the statistics of the spectrum is low in this range, their influence on the spectrum shape is limited.

Experimental spectrum of 241 Pu

For spectra having low end-point energy, the metallic magnetic calorimeters will be helpful to obtain high precision measurements. The beta spectrum of 241 Pu was measured at LNHB with a metallic magnetic calorimeter, as described elsewhere [START_REF] Loidl | First measurement of the beta spectrum of 241 Pu with a cryogenic detector[END_REF]. It can be observed in Figure 2, with the X-rays which come from the decay of a 55 Fe source used for the energy calibration. The corresponding Kurie plot is given in Figure 3.

  the nucleus in /mc units. The parameter n equals |J|-1, with a value of zero for the allowed and first non unique forbidden transitions. f  (r) and g  (r) are the electronic radial wave functions, continuum state solutions of the Dirac equation for an electron into a Coulomb field [82Be]:

The 241 FiguresFigure 1 -

 2411 Figures

Figure 2 -

 2 Figure 2 -Beta spectrum of 241 Pu measured with a metallic magnetic calorimeter and

Figure 3 -

 3 Figure 3 -The corresponding Kurie plot of Figure 2. The agreement between the measured

Tables

  Allowed ( -) 3 H, 14 C,24 Na, 32 P, 33 P,35 S, 41 Ar, 45 Ca, 46 Sc, 60 Co, 63 Ni, 95 Nb, 106 Ru, 114 In, 133 Xe, 203 Hg ( + ) 11 C, 13 N, 15 O First non unique forbidden ( -) 79 Se, 91 Y, 143 Pr, 147 Pm, 151 Sm, 176 Lu, 206 Tl, 210 Bi, 241 Pu First unique forbidden ( -) 85 Kr, 89 Sr, 90 Sr, 90 Y Second non unique forbidden ( -) 36 Cl, 99 Tc, 129 I

	Second unique forbidden	( + ) 26 Al
	Third unique forbidden	( -) 40 K
	Fourth non unique forbidden ( -) 113 Cd

Table 1 -

 1 List of the 38 transitions calculated for a comparison with the Radlist program. The non-unique transitions are calculated as unique transitions having the same variation of the total angular momentum.

	Nucleus	Z Transition order	Finite nuclear size correction	Screening correction	Radiative corrections greater than 1 % if
	129 I	53 2 nd non-unique	~ 0.44 %	~ 17 %	E  78 % E max
	133 Xe	54	allowed	~ 0.007 %	~ 3 %	E  75 % E max
	176 Lu	71	1 st non-unique	~ 0.22 %	~ 4 %	E  72 % E max
	203 Hg	80	allowed	~ 0.16 %	~ 4.5 %	E  58 % E max
	241 Pu	94	1 st non-unique	~ 0.03 %	~ 4.7 %	E  53 % E max

Table 2 -

 2 Magnitude of each correction applied in BetaShape for some nuclei. The nonunique transitions are calculated as unique transitions having the same variation of the total angular momentum.

Acknowledgment

We wish to thank Dr. T.D. Huynh from the Service d'Études des Réacteurs et de Mathématiques Appliquées (CEA/DEN/DANS/DM2S/SERMA) for providing us results of his beta spectra calculation program, and for the fruitful discussions we had.

In order to answer users' demand, we have developed a specific program dedicated to the calculation of beta spectra shapes. BetaShape is based on the analytical approach from Gove and Martin described above. The Coulomb corrections depend on the forbidding order of the transition, but the non-unique forbidden transitions are not yet treated specifically. The screening effect due to the electron cloud, the finite nuclear size effect with regard to the electron Compton wavelength, and the radiative corrections are taken into account. This program must be tested and validated by experiments.

There is a lack of data to test the transitions with high forbidding order. Moreover, the oldest published experiments did not have the computing power for Monte-Carlo simulations to evaluate all the physical phenomena that could distort the spectra. It is necessary to carry out new and well analysed experiments. Metallic magnetic calorimeters provide very encouraging results. The analysis of the 241 Pu beta spectrum leads us to take into account the exchange effects in the calculations (currently in progress). Also, we are working on another experimental setup using a silicon detector. This setup will be complementary to the metallic magnetic calorimeters, providing spectra with energy ranging from 100 keV to 1 MeV.


R Delorme

HAL is

International Conference on Translational Research in Radio-Oncology and Physics for Health in Europe (ICTR-PHE 2012, Genève)

Présentation orale: Photo-activation therapy with high-Z nanoparticles : modelling at a micrometer level and experimental comparison

Rachel Delorme CEA, LIST, LM2S, 91191 Gif-Sur-Yvette, France rachel.delorme@cea.fr Purpose: An innovative approach using X-rays interactions with heavy elements seems to open a promising way of treatment for resistant cancers, such as high-grade gliomas. Such a technique is developed at the medical beam line of ESRF using monochromatic Xrays in the 50-100 keV range for the treatment of brain tumors [1,2]. The use of gold nanoparticles to treat mice bearing subcutaneous tumors led to encouraging results [3]. However, the physical processes and biological impact of the photon activation of nanoparticles are not well understood. The experimental results cannot be explained from macroscopic dose calculations [4,5].

The aim of this study was to evaluate, at the cellular level, the dose enhancement in presence of nanoparticles and the properties of the secondary electrons production using the Monte Carlo transport code PENELOPE.

Material and Method: At first, upstream studies were done around the behavior of gadolinium and gold nanoparticles (GdNP and AuNP) under irradiation. The mean range, yields and spectra of electrons produced from the interactions of X-rays with a AuNP and a GdNP were calculated for diameters of 2 to 100 nm when irradiated with monochromatic photons from 25 keV to 2 MeV. The dose enhancement was calculated in water at one micrometer around the AuNP.

On another hand, dose calculations were done in a cellular geometry containing gadolinium-water mixture in order to compare with experimentations realized on the ID17 beamline of ESRF. Clonogenic assays have been performed on F98 cells to measure the "Sensitizer Enhancement Ratio" for 4 Gy of irradiation (SER4Gy) with the presence of GdNP, for several irradiation energies (25 to 80 keV).

Results: An increase of electron production up to a factor 1000 is observed in presence of a AuNP. More electrons are produced from an AuNP than a GdNP because the gold is denser. The mean energy of the produced electrons increases with the beam energy, except after the K-edge of each element because of an enhancement of interactions with deeper atomic shells. The mean energy is lower after the gadolinium K-edge and provides a more local dose deposition compared to gold.

An auto-absorption of low energy electrons for NP with larger diameters is also observed.

From the comparison of the calculated dose enhancement factor (DEF) in the cellular geometry with the measured SER4Gy, encouraging results are obtained (see the figure) but in-depth studies are still required. The electron spectra incoming on nucleus were also studied and provide interesting correlations. Conclusions: In the near future, we plan to calculate the dose in a cellular geometry considering multiple nanoparticles instead of gadolinium-water mixture, and then considering many cells. With these results we aim to take into account the influence of multiple structures for a more realistic model and try to understand the current differences observed between the SER4Gy and the DEF. Better physical observables are also required to explain the tendency of the biological response as a function of beam energy.

1. Adam, J. F., H. Elleaume, et al. (2003).Int J Radiat Oncol Biol Phys 57(5): 1413-26. 2. Adam, J. F., A. Joubert, et al. (2006). Int J Radiat Oncol Biol Phys 64(2): 603-11. 3. Hainfeld, J. F., D. N. Slatkin, et al. (2004) Phys Med Biol 49(18): N309-15. 4. Cho, S. H., et al. (2005). Phys. Med. Biol. 50 N163-73 5. Zhang, S. X., et al. (2009). Biomed Microdevices 11:925-933

Figure :

 : Figure : Comparison of the calculated Dose Enhancement Factor into a cell and the measured SER for six differents energies and two differents localisation of GdNP


Pádraic J Flood
email: flood@mpipz.mpg.de

Tom P J M Theeuwen
email: tom.theeuwen@wur.nl

Korbinian Schneeberger

Paul Keizer

Willem Kruijer

Edouard Severing

Evangelos Kouklas

Jos A Hageman

Frank F M Becker

Sabine K Schnabel

Leo Willems

Wilco Ligterink

Jeroen Van Arkel

Roland Mumm

José M Gualberto

Linda Savage

David M Kramer

Joost J B Keurentjes

Fred Van Eeuwijk

Maarten Koornneef

Jeremy Harbinson

Mark G M Aarts

Erik Wijnker
email: erik.wijnker@wur.nl.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes

Keywords: Arabidopsis, Chloroplast, Cytonuclear interaction, Epistasis, Mitochondrion, Plant growth, Photosynthesis

Assessing the impact of variation in chloroplast and mitochondrial DNA (the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear derived variation (the nucleotype). By using haploid inducer lines as plasmotype donors we employed an efficient and precise method to generate a panel comprising all possible cytonuclear combinations (cybrids) of seven Arabidopsis thaliana accessions. We screened these lines for different plant performance parameters, yielding 1008 phenotypes. Plasmotype-induced phenotypic variation is highly epistatic with nuclear variation and can be of large effect, i.e. increasing plant biomass by as much as 23%. Four times as much variation is explained by cytonuclear interactions as opposed to an additive effect of the plasmotype. This quick and precise method allows the detection of cytonuclear interactions, and may allow improving plant performance through efficient screening for favourable nucleus-organelle combinations.

Main Text: Mitochondria and chloroplasts play essential roles in plant respiration, photosynthesis and primary metabolism. Their genomes contain genes essential for these processes, but their functioning requires tight coordination with the nucleus since the majority of organellar proteins are encoded in the nucleus. This dependence, together with signaling pathways that modulate nuclear and organellar gene expression (Kleine and Leister, 2016), can cause complex interactions and non-additive, nonlinear effects (epistasis). The phenotypic consequences of epistasis can be detected when a plasmotype causes phenotypic effects in combination with some, but not all nuclear backgrounds. Indeed, recent studies suggest that cytonuclear epistasis is not uncommon (Joseph et al., 2013;

plasmotypes can be studied using backcross designs where plasmotypes are introgressed into different nuclear backgrounds [START_REF] Miclaus | Maize Cytolines Unmask Key Nuclear Genes That Are under the Control of Retrograde Signaling Pathways in Plants[END_REF][START_REF] Roux | Cytonuclear interactions affect adaptive traits of the annual plant Arabidopsis thaliana in the field[END_REF], but backcross approaches are lengthy and any undetected nuclear introgressions may confound the results.

To precisely and rapidly address the contribution of organellar variation to plant phenotypes, we explored the use of a haploid inducer line available in Arabidopsis (GFP-tailswap) [START_REF] Ravi | Haploid plants produced by centromere-mediated genome elimination[END_REF]. This line expresses a GFP-tagged CENTROMERE HISTONE 3 protein in a cenh3/htr12 mutant background. When pollinated with a wild-type plant, the GFP-tailswap nuclear genome is lost from the zygote through uniparental genome elimination, generating haploid offspring (Fig. 1). Since the plasmotype of the resulting offspring is maternal in origin, the haploid offspring are cybrids, combining a paternal nucleus with the maternal GFP-tailswap mitochondria and chloroplasts. These haploid plants produce diploid (doubled haploid) offspring following genome duplication or restitutional meiosis [START_REF] Ravi | Haploid plants produced by centromere-mediated genome elimination[END_REF]. Using the GFP-tailswap it is possible to generate cybrids in two generations, and in just four generations for all possible nucleotype-plasmotype combinations (Fig. 1A and1B) [START_REF] Kindiger | Generation of Haploids in Maize: A Modification of the Indeterminate Gametophyte (ig) System[END_REF][START_REF] Ravi | Haploid plants produced by centromere-mediated genome elimination[END_REF][START_REF] Ravi | A haploid genetics toolbox for Arabidopsis thaliana[END_REF]. We set out to test the use of this approach to investigate how plasmotypic variation affects plant phenotypes and to what extent this variation manifests itself as additive variation or as cytonuclear epistasis.

Seven different Arabidopsis accessions were selected: six that represent a snapshot of natural variation, and one accession (Ely) that has a large-effect mutation in the chloroplast-encoded PsbA gene which results in reduced photosystem II efficiency and a constitutively oxidized plastoquinone pool under light-limited conditions [START_REF] El-Lithy | Altered photosynthetic performance of a natural Arabidopsis accession is associated with atrazine resistance[END_REF][START_REF] Flood | Natural variation in phosphorylation of photosystem II proteins in Arabidopsis thaliana: is it caused by genetic variation in the STN kinases?[END_REF]. The Ely accession was included to evaluate the consequence of a strong plasmotype effect in our test-panel. We first generated haploid inducers for all seven plasmotypes and then used each inducer to generate cybrid offspring for all seven nucleotypes (Fig. 1C). Wild-type nucleotype-plasmotype combinations were also regenerated in this way (hereafter referred to as self-cybrids) to later compare these with their wildtype progenitors. Nuclear, mitochondrial and chloroplastic genotypes of cybrids were verified by whole genome sequencing, confirming that the cybrid genotypes were as expected and there were no nuclear introgressions (Supplementary Fig. 1 and2). SNP data were used to generate neighbor joining trees for the nuclear, mitochondrial and chloroplastic genomes (Supplementary Fig. 3). The nucleotypes are approximately equidistant whilst the mitochondrial and chloroplastic genomes showed larger variance in relatedness, with Sha being most diverged. with a HI (male) results in a hybrid F1. A diploid F1 is selected in which no genome elimination has occurred. Self-fertilization generates an F2 population in the plasmotype of the wild-type mother. From this an F2 is selected that is homozygous for the cenh3/htr12 mutation, but carries the GFP-tailswap. This F2 plant is a new HI line and can serve as plasmotype donor when used as female in crosses.

Vertical bars represent the nucleotype, and the ovals represent the plasmotype. HI centromeres are indicated in green (signifying GFP-tagged CENH3/HTR12 proteins as encoded by the GFP-tailswap construct) that cause uniparental genome-elimination. C) Full diallel of all nuclear-plasmotype combinations. The diagonal line highlights the wild-type (WT) nucleotype-plasmotype combinations that were generated by crossing wild-type plants to plasmotype donors with the identical plasmotype.

These wild-type nucleotype-plasmotype combinations are referred to as "self-cybrids".

. We phenotyped the cybrid panel for absolute and relative growth rate, biomass accumulation, epinastic leaf movement, photosystem II efficiency (φPSII), non-photochemical quenching (NPQ) including rapidly relaxing (qE) and slowly relaxing (qI) components of NPQ, a reflectance-based estimate of chlorophyll, flowering time and germination under constant environmental conditions. In addition, to reflect more natural conditions we screened the panel under fluctuating light for all photosynthesis-related traits, and assayed germination rates under osmotic stress and after a controlled deterioration treatment. We also measured 41 primary metabolites using gas chromatography coupled with time-of-flight mass spectrometry (GC-ToF-MS). A total of 1008 phenotypes were scored, counting individual metabolite concentrations and single time points in time series as separate phenotypes (Supplementary Data 1). Phenotypes with a broad sense heritability (H 2 ) of less than 5% were removed from analysis, leaving a total of 906 phenotypes. To avoid overrepresentation of time series and highly correlated traits, we selected a subset of 34 representative phenotypes (Supplementary Table 1) comprising 22 from constant growth conditions and 12 from fluctuating environmental conditions which we used for further analysis. The analysis using the full set of 906 phenotypes is included in the supplemental material. Comparison of self-cybrids with their genetically identical wild-type progenitors did not reveal any phenotypic differences (Supplementary Table 1) from which we infer that cybridization through uniparental genome elimination is a robust method to generate cybrids. To determine the relative contributions of nucleotype, plasmotype, and their interaction, to the observed phenotypic variation we estimated the fraction of the broad sense heritability (H 2 ) explained by each. Across the entire panel the average contribution to H 2 of nucleotype, plasmotype and nucleotype-plasmotype interaction was 58.7%, 34.4% and 6.8% respectively (Supplementary Table 2 and3; Supplementary Data 1). Most of the variation in the plasmotype was caused by the Ely plasmotype, probably arising from the mutation in its PsbA gene. When this plasmotype was excluded from the analysis, the nucleotype, plasmotype and their interaction account for 95.2%, 1.0% and 3.8% of the genetic variation (Fig. 2). So, while nucleotype-derived additive variation is the main genetic determinant of the cybrid phenotype, variation caused by cytonuclear interactions (epistasis) is almost four times larger than the additive effect of the plasmotype (p=0.000095). Though the total explained variance due to the cytonuclear interaction is only 3.8% on average, this interaction can be large for specific phenotypes or in specific cybrids. For example, as much as 7.2% of the total genetic variation for rosette dry weight (biomass) is explained by cytonuclear interactions. In the cybrid with a Bur nucleotype and Ler plasmotype (Bur Ler ) this amounts to an increase of 23% in shoot biomass when compared to the wild-type Bur Bur cytonuclear combination (p=0.008). In another example, 9.7% of the total genetic variance for NPQ under fluctuating light is explained by cytonuclear interactions, with Bur Ler showing a 17.2% reduction as compared to Bur Bur . This effect is only triggered under more challenging conditions, since this difference in NPQ does not occur under continuous light (Fig. 3C and3D).

Considering that most of the observed phenotypic changes result from epistasis, and these are unique to specific nucleotype-plasmotype combinations, we sought to assess whether there are general patterns in how specific nucleotypes and plasmotypes interact. We therefore compared wildtype nucleotype-plasmotype combinations with all their iso-nuclear cybrid lines (Table 1). The Bur nucleotype shows significant differences for 28 phenotypes when combined with non-native plasmotypes (excluding the Ely plasmotype) (Table 1). In contrast, Col and Sha show just one and three, respectively, thus within the scope of this panel their nucleotypes are most tolerant of genetic variation in the plasmotype. Conversely, cybrids with the Bur plasmotype show just three significantly altered phenotypes as compared to 21 in cybrids that have a Sha plasmotype. Sha, which is the most genetically distant plasmotype (Supplementary Fig. 3) in our panel, causes most significant phenotypic changes in combination with other nucleotypes. Thus, plasmotypes and nucleotypes differ in their likelihood of producing significant cytonuclear interactions, with genetic distance possibly influencing the extent of epistasis. The Ely plasmotype is unique in our panel because it contributes strong additive effects due to the lower quantum yield of electron transport caused by the PsbA mutation in its chloroplast. The PsbA mutation was selected for in response to the use of triazine herbicides along English railways from the 1960s onwards (Flood et al., 2016). Cybrids with the Ely plasmotype all have a lower PSII efficiency (Fig. 3A) and lower values for other photosynthesis related traits i.e. NPQ, qE and chlorophyll content (Fig. 3C and Supplementary Fig. 5). The reduced PSII efficiency (φPSII) is likely to be responsible for the concomitant reductions in biomass (Fig. 3B), growth rate and seed size (Supplementary Data 2). There is also a reduction in serine and glycine content of cybrids with Ely plasmotye, which is often associated with lower photorespiration and may result from reduced carbon fixation [START_REF] Somerville | Photorespiration mutants of Arabidopsis thaliana deficient in serine-glyoxylate aminotransferase activity[END_REF]. In the presence of the Ely plasmotype we detected additive changes in 30 out of 34 selected phenotypes and changes in the concentrations of 28 out of 41 measured primary metabolites (Supplementary Data 2). Interestingly, the Ely nucleus shows a 15% increase in NPQ under fluctuating light conditions as compared to the average of all other nuclei in our panel (Fig. 3D). It is tempting to hypothesize that this results from a compensatory mutation to balance the 21% loss of NPQ conferred by the Ely plasmotype. Although, whether the high NPQ in the Ely nucleus then results from genuine co-adaptation, or whether it was a pre-existing nuclear trait that may have facilitated the selection for atrazine resistant chloroplasts we cannot say with our current dataset.

Table 1. Plasmotype changes cause significant changes in plant phenotypes

We contrasted the transcriptome of the Bur, Ler and Ely accessions and their six reciprocal cybrids (Supplementary Data 3) to better understand the Ely additive effect and determine which transcriptional pathways changed in reciprocal cybrids between Bur and Ler for which we observed significant phenotypes for the Bur Ler (GO:0006091)(Supplementary Data 3). Across all three nucleotypes only 23 genes are significantly differently expressed when either the Bur or Ler plasmotype is replaced by Ely. Only one of these 23 genes, the pathogen response induced β-1,3-GLUCANASE 3 (BG3, AT3G57240), is always upregulated when the Ely plasmotype is present (Supplementary Table 6). β-1,3-Glucanases act in the degradation of 1,3-β-D-glucosidic bonds which are frequently found in cell walls of many fungi, and in callose, a plant polysaccharide consisting mainly of β-1,3-glucans [START_REF] Chen | Callose synthesis in higher plants[END_REF]. Callose degradation can improve cell-to-cell trafficking of nutrients and signaling molecules through opening of plasmodesmata, although so far, BG3 has not been implicated in this [START_REF] Zavaliev | Subcellular Dynamics and Role of Arabidopsis β-1,3-Glucanases in Cell-to-Cell Movement of Tobamoviruses[END_REF]. The other 22 genes have different directions of response depending on the nuclear background. For example expression of LUTEIN DEFICIENT 5 (CYP97A3), which encodes a heme-containing cytochrome P450 involved in the biosynthesis of xanthophylls and important in NPQ, is downregulated in the Bur and Ely nucleotypes while upregulated in the Ler nucleotype. Thus, despite its additive effect on higher order phenotypes, the Ely plasmotype causes almost exclusively unique transcriptional changes in each nuclear background, highlighting that at the transcriptional level the Ely plasmotype effect is epistatic.

In the case of changing the Bur plasmotype for that of Ler we detected no significant additive effects for any of the higher order phenotypes. Nonetheless, in the Bur nucleotype background, 820 nuclear genes were differentially expressed between Bur Bur and Bur Ler (Supplementary Fig. 6). Of these genes, 13 were classified under the GO term "glutathione transferase activity" (GO:0004364) and 8 under "glutamate receptor activity" (GO:0008066). Glutathione transferases (GSTs) have evolved to perform a range of functional roles, amongst which they have been implicated in acclimation to high light [START_REF] Lv | β-cyclocitral upregulates salicylic acid signalling to enhance excess light acclimation in Arabidopsis[END_REF]. Glutamate receptor-like proteins remain largely undescribed, but are linked to non-selective cation channels involved in metabolic and defense signaling mechanisms [START_REF] Forde | Glutamate receptor-like channels in plants: a role as amino acid sensors in plant defence? F[END_REF][START_REF] Toyota | Glutamate triggers long-distance, calcium-based plant defense signaling[END_REF][START_REF] Nguyen | Identification of cell populations necessary for leaf-to-leaf electrical signaling in a wounded plant[END_REF]). The epistatic nature of cytonuclear interactions implies that these transcriptional changes (and the accompanying phenotypic differences, including the 23% difference in plant biomass) can only be observed and understood within the context of the Bur nucleus. In the Ler nucleotype, the same Bur to Ler plasmotype change affects gene expression of only three genes, and does not cause any significant change in higher order plant phenotypes (Table 1).

Our experiments have shown that a clean, systematic exploration of plasmotype variation in a plant species is feasible. The development of inducer lines for crop species would allow elite nucleotypes to be brought into new plasmotypic backgrounds to explore plamotype-nucleotype interactions and ultimately to optimize crop performance. Our data indicate that substantial gains in plant productivity can be made. We detected increases of as much as 23% for plant biomass, and a difference of 17.2% in NPQ under fluctuating light, which is increasingly recognized as important for plant productivity [START_REF] Kromdijk | Improving photosynthesis and crop productivity by accelerating recovery from photoprotection[END_REF]. Exploring the potential of plasmotypic variation via the use of inducer lines is promising both for plant breeding and for understanding the ecological role such variation plays in plant adaptation [START_REF] Bock | On the adaptive value of cytoplasmic genomes in plants[END_REF][START_REF] Dobler | A meta-analysis of the strength and nature of cytoplasmic genetic effects[END_REF].

Materials and Methods:

Plant materials

Seven Arabidopsis accessions were chosen for the construction of a full nucleotype-plasmotype diallel. Ely (CS28631) is atrazine resistant due to a chloroplast-encoded mutation in PsbA which leads to a modified D2 protein that greatly reduces PSII efficiency [START_REF] El-Lithy | Altered photosynthetic performance of a natural Arabidopsis accession is associated with atrazine resistance[END_REF]. Ws-4 (CS5390) was included for its unusual photosystem II phosphorylation dynamics [START_REF] Yin | Photosystem II Function and Dynamics in Three Widely Used Arabidopsis thaliana Accessions[END_REF]. Bur (CS76105) is commonly used in diversity panels and is a standard reference accession. Sha (CS76227) was selected based on its capacity to induce cytoplasmic male sterility in some crosses [START_REF] Gobron | A Cryptic Cytoplasmic Male Sterility Unveils a Possible Gynodioecious Past for Arabidopsis thaliana[END_REF]. The set was completed by adding Ler (CS76164), Col (CS76113) and C24 (CS76106) which are three widely used genotypes in Arabidopsis research. Col is the reference genome for nuclear and chloroplast sequences and C24 for the mitochondrial sequence. The GFP-tailswap haploid-inducer [START_REF] Ravi | Haploid plants produced by centromere-mediated genome elimination[END_REF] is in a Col background.

Generation of a nucleotype-plasmotype diallel

To generate new nucleotype-plasmotype combinations, plants of all seven accessions (Bur, C24, Col, Ely, Ler, Sha and Ws-4) were crossed as males to GFP-tailswap (the Col plasmotype donor) as well as six newly generated haploid inducer lines (Fig. 1B). The haploids arising from these 49 crosses were identified based on their phenotype (as described in [START_REF] Wijnker | Hybrid recreation by reverse breeding in Arabidopsis thaliana[END_REF]). These haploid lines were self-fertilized to obtain doubled haploid offspring (Fig. 1A). The resulting 49 lines comprise a full diallel of 21 pairs of reciprocal nucleotype-plasmotype combinations (cybrids) as well as seven nucleotype-plasmotype combinations that have the same nucleotype-plasmotype combinations as their wild-type progenitors (self-cybrids; Fig. 1B, diagonal). All cybrids and the wild-type accessions were propagated for one generation before use in further experiments, with the exception of Ely Sha of which the original haploid died and had to be recreated thus limiting our analyses to 48 rather than 49 cybrids. Even though self-cybrids are genetically identical to their wild-type accessions, the parental lines were included in the screens to test for possible unforeseen effects of cybrid production (which involves a haploid growth stage). This brings the number of lines included in this study to a total of 55 (41 cybrids, 7 self-cybrids and 7 wild types).

Genotype confirmation

To confirm that all cybrids in our panel are authentic, all 49 cybrids and 7 wild-type progenitors were whole-genome sequenced at the Max Planck-Genome-centre Cologne (Germany) using Illumina Hiseq 2500 150-bp paired-end sequencing. The cybrids were sequenced at 8.5X coverage and the wild-type progenitors at 40X coverage. Reads were aligned against the TAIR10 reference sequence, including organellar sequences, followed by variant calling using SHORE and GenomeMapper [START_REF] Ossowski | Sequencing of natural strains of Arabidopsis thaliana with short reads[END_REF][START_REF] Schneeberger | SHOREmap: simultaneous mapping and mutation identification by deep sequencing[END_REF]. For the nucleus we used a phred quality score of 40, leaving 92022 SNPs and for the chloroplast used a phred quality score of 15, leaving 289 SNPs.

46 cybrids were found to have the correct genotypes. With one line, Bur Ws-4 , there was a sample mixup during library preparation with Sha Sha . To confirm sequences we therefore used the Sha genotype (CS76382) from the 1001 genomes project (The 1001 Genomes Consortium, 2016). Two other lines, C24 C24 and Ws-4 Col , had a high number of heterozygous calls, which we attributed to sample contamination. To ensure that the sample mix-up and the putative event of cross-contamination occurred in the laboratory, we designed KASP TM makers (LGC, https://www.lgcgroup.com) and genotyped all lines. These KASP TM markers are chloroplast specific and were designed based on the obtained sequence data (Supplementary Table 7). All lines showed the correct genotypes, and no heterozygosity was observed in any of the lines, including C24 C24 and Ws-4 Col . In summary we confirmed that all 49 cybrids had the correct genotype. Unfortunately the Ely Sha used for sequencing died before setting seed and although it has since been recreated, it could not be included in our phenotypic analyses.

Phenotyping

Cybrids were phenotypically assessed using different platforms. Growth, PSII efficiency, chlorophyll reflectance and leaf movement (all parameters at n=24) was screened in the Phenovator platform, a high-throughput phenotyping facility located in a climate-controlled growth chamber (Flood et al., 2016). This phenotyping platform measured the plants for: photosynthetic efficiency (φPSII) using chlorophyll fluorescence, reflectance at 480 nm, 532 nm, 550 nm, 570 nm, 660 nm, 700 nm, 750 nm and 790 nm, and projected leaf area (PLA) based on pixel counts of near infra-red (NIR) images (Flood et al., 2016). The growth chamber was set to a 10 h day/14 h night regime, at 20°C day and 18°C night temperature, 200 µmol m -2 s -1 irradiance, and 70% relative humidity. The plants were grown on a rockwool substrate and irrigated daily with a nutrient solution as described in Flood et al. (2016).

Growth (n=24) and subsequently above ground biomass (n=12) was measured in another highthroughput phenotyping facility [START_REF] Kokorian | An ImageJ based measurement setup for automated phenotyping of plants[END_REF], where projected leaf area was measured three times per day with 14 fixed cameras (uEye Camera, IDS Imaging Development Systems GmbH, Obersulm, Germany). This growth chamber was set to a 10 h day/14 h night regime, at 20°C day and 14°C night temperature, 200 µmol m -2 s -1 light and 70% relative humidity. Plants were grown on rockwool and irrigated weekly with a nutrient solution as described before. Non-fluctuating and fluctuating light treatments were performed in the DEPI phenotyping facility (n=4) [START_REF] Cruz | Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes[END_REF].

This facility is able to measure the chlorophyll fluorescence derived photosynthetic parameters, φPSII, NPQ, qE, qI. Three week old plants were moved into the facility, where they were left to acclimatize for 24 hours after which three days of phenotyping was performed under different light regimes. On the first day the plants were illuminated with a constant light intensity of 200 µmol m -2 s -1 . On the second day the plants received a sinusoidal light treatment where the light intensity began low and gradually increased to a maximum of 500 µmol m -2 s -1 light from which it deceased back down to 0. On the third day the plants received a fluctuating light treatment ranging between 0 and 1000 µmol m -2 s -1 light in short intervals. For further details see [START_REF] Cruz | Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes[END_REF]. Bolting time and flowering time were measured on all cybrids (n=10) in a greenhouse experiment in April 2017, with the exception of Ely nucleotype cybrids which needed vernalisation and were not included in this experiment. Additional lighting was turned on when the natural light intensity fell below 685.5 µmol m -2 s -1 , and turned off when the light intensity reached 1142.5 µmol m -2 s -1 , with a maximum of 16 h per day.

Seeds for the germination experiments were stratified on wet filter paper for four days at 4°C before being assayed in the Germinator platform [START_REF] Joosen | germinator: a software package for high-throughput scoring and curve fitting of Arabidopsis seed germination[END_REF] for seed size, germination rate and total germination percentage. All seeds were generated from two rounds of propagation. In the first round seeds were first sown in a growth chamber set to a 10 h day/14 h night regime, at 20°C day and 18°C night temperature. 200 µmolm -2 s -1 light intensity, and 70% relative humidity. After three weeks they were moved to an illuminated cold room at 4°C for six weeks of vernalization. After vernalization all plants (n=8) were moved to a temperature-controlled greenhouse (20°C) for flowering and seed ripening. Exceptions to this were Ler Ely , Ler Ws-4 , and Ely Ws-4 for which no doubled haploid seed was available at the beginning of the first propagation round. Ler Ely and Ler Ws-4 were sown later, during the vernalization stage and flowered at the same time as the vernalized plants. Ely Ws-4 produced haploid seed at a later stage and could not be included in the first propagation round. Plants were grown in a temperature-controlled greenhouse set at 20°C. In this round only lines with the Ely nucleotype were vernalized.

Metabolomics

Plant material for primary metabolite analysis was obtained from the 'Phenovator' photosynthetic phenotyping experiment. Plants were harvested 26 days after sowing, which due to the 10-hr photoperiod was prior to bolting for all lines. Samples were frozen in liquid nitrogen, and samples of each genotype were subsequently combined into four pools each made up of material of approximately six replicates. Each pool was ground and homogenized before an aliquot was taken for further analysis. Reference samples for the metabolite analysis were composed of material from all seven parents in equal amounts and then homogenized. The method used for the extraction of polar metabolites from Arabidopsis leaves was adapted from [START_REF] Lisec | Gas chromatography mass spectrometry-based metabolite profiling in plants[END_REF] as described by [START_REF] Carreno-Quintero | Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality[END_REF]. Specific adjustments for Arabidopsis samples were made as follows; the polar metabolite fractions were extracted from 100 mg of Arabidopsis leaf material (fresh weight, with max.

5% deviation). After the extraction procedure, 100 μL aliquots of the polar phase were dried by vacuum centrifugation for 16 hours. The derivatization was performed on-line similar as described by [START_REF] Lisec | Gas chromatography mass spectrometry-based metabolite profiling in plants[END_REF] and the derivatized samples were analyzed by a GC-ToF-MS system composed of an Optic 3 high-performance injector (ATAS TM , GL Sciences, Eindhoven, The Netherlands) and an Agilent 6890 gas chromatograph (Agilent Technologies, Santa Clara, United States) coupled to a

Pegasus III time-of-flight mass spectrometer (Leco Instruments, St. Joseph, United States). Two microliters of each sample were introduced in the injector at 70°C using 5% of the sample (split 20).

The detector voltage was set to 1750 Volts. All samples were analyzed in random order in four separate batches. The systematic variation that inadvertently is introduced by working in batches, was removed upon analysis of covariance. In this model the batch number was used as a factor (four levels) and "run number within a batch" as a covariate since it is also expected that (some) variation will be introduced by the sample run order within each batch. For this the S2 method described by [START_REF] Wehrens | Improved batch correction in untargeted MS-based metabolomics[END_REF] was used to perform the least-squares regression. After quality control and removing metabolites with more than 20% missing data and a broad sense heritability (H 2 ) of less than 5%, we were left with data on 41 primary metabolites. Metabolites were identified based on the level of identification standard by the Metabolomics Standards Initiative [START_REF] Sumner | Proposed minimum reporting standards for chemical analysis[END_REF].

Transcriptome analysis

Using the same material as described in the metabolome analysis, total RNA was extracted from all nine reciprocal cybrids between accessions Bur, Ler and Ely, with three replicates per genotype, totaling 27 plants. Library preparation was done with a selection on 3' polyadenylated tails to preferentially include nuclear mRNA. Read alignment was done using TopHat [START_REF] Trapnell | TopHat: discovering splice junctions with RNA-Seq[END_REF].

Any chloroplast and mitochondrial genes remaining were excluded from further analysis. The raw counts were normalized and analyzed using the DeSeq2 package in R [START_REF] Love | Moderated estimation of fold change and dispersion for RNAseq data with DESeq2[END_REF]. Genes for which the expression levels were significantly different between two cybrids were determined by comparing two genotypes using the contrast function of DeSeq2. P-values were determined using the Wald test, and p-values were adjusted using the Benjamini-Hochberg correction (α=0.05). GO enrichment analysis was done using default setting in g:profiler Compact Compare of Annotations (g:Cocoa). The complete set of detected genes in each cybrid was used as a statistical background in the analysis [START_REF] Reimand | g:Profiler-a web server for functional interpretation of gene lists (2016 update)[END_REF].

Phenotypic data analysis

We used the self-cybrids as our baseline in phenotypic comparisons to control for any possible effects of cybrid creation. Raw data was directly analyzed except for time series data of growth and chlorophyll reflectance which was preprocessed as follows. Time series data were fitted with a smooth spline using the gam function from the mgcv package in R [START_REF] Wood | Smoothing Parameter and Model Selection for General Smooth Models[END_REF]. The fitted B-spline was subsequently used to derive several curve parameters. In addition, we calculated relative growth rate per time point by dividing the growth rate, relative to the plant size (Flood et al., 2016). All raw parameters and derived parameters were analyzed by fitting either a linear mixed model or a linear model. The linear mixed model was used when a random correction parameter was present, when such random correction parameters were absent a linear model was used. The models were analyzed using the Restricted Maximum Likelihood (REML) procedure for each relevant trait using the lme4 package in R [START_REF] Bates | Fitting linear mixed-effects models using lme4[END_REF]. As each experiment had a different design, several models were employed (Supplementary Table 4). The following model was generally used, in some instances random terms (underlined below) were added:

𝑌 = 𝑁𝑢𝑐𝑙𝑒𝑜𝑡𝑦𝑝𝑒 + 𝑃𝑙𝑎𝑠𝑚𝑜𝑡𝑦𝑝𝑒 + (𝑁𝑢𝑐𝑙𝑒𝑜𝑡𝑦𝑝𝑒 * 𝑃𝑙𝑎𝑠𝑚𝑜𝑡𝑦𝑝𝑒) + 𝐵𝑙𝑜𝑐𝑘 + 𝜀 (1)
For every model, normality and equal variances were checked. Next for every phenotypic parameter it was determined whether an interaction model or a plasmotype additive model would suit best. This was done by ANOVA in which Kenward-Roger approximation for degrees of freedom was used. As posthoc tests we used Dunnett's test, where we tested (two sided) whether a given cybrid was different from the self-cybrid control. The significance threshold for the posthoc tests was set at α=0.05. The contribution of the nucleotype, plasmotype and the interaction between the two, was determined by estimating the variance components in mixed models containing the same terms as in model ( 1). However the fixed terms were taken as random: 𝑌 = 𝑁𝑢𝑐𝑙𝑒𝑜𝑡𝑦𝑝𝑒 + 𝑃𝑙𝑎𝑠𝑚𝑜𝑡𝑦𝑝𝑒 + (𝑁𝑢𝑐𝑙𝑒𝑜𝑡𝑦𝑝𝑒 * 𝑃𝑙𝑎𝑠𝑚𝑜𝑡𝑦𝑝𝑒) + 𝐵𝑙𝑜𝑐𝑘 + 𝜀 ,

Where the variance components were estimated by the VarCorr function from the lme4 package. Total variance was calculated by summing all the variance components, after which the fraction explained variance for every term in the model was calculated. The broad sense heritability, in our case equal to repeatability [START_REF] Falconer | Introduction to quatitative genetics[END_REF], is determined by the three genetic components, i.e.

nucleotype, plasmotype and the interaction, together. The fraction of broad sense heritability explained by the separate genetic components was calculated subsequently.

In total we measured 1008 phenotypes. However many were highly correlated, particularly in the time series data. After data processing, further analysis was only conducted on phenotypes with a broad sense heritability higher than 5%, removing phenotypes that were non-informative, leaving with 906 phenotypes. Furthermore, to avoid biases in the results due to overly correlated data, when stating summary statistics, we wanted to get a representative set of phenotypes from the remaining 906 phenotypes (Supplementary Table 1). Using a threshold based purely on correlation would favor the inclusion of variation largely driven by the nucleotype, thus we sought to include a subset of time points from each time series. We therefore selected the following representative phenotypes. For time series in which we scored for up to 25 days after germination, we selected mornings of day 8, 13, 18 and 23. The time series analysis of fluctuating light were only measured for three days in a row, with each day a different treatment. As these treatments reached their extremes in the middle of the day, these time points were selected. For the different seed treatments we used the germination time until 50% of the seeds germinated. In addition we included biomass, leaf movement, seed size and flowering time as single phenotypes. All data on the 1008 phenotypes are available in Supplementary Data 1.

Figure 1 .

 1 Figure 1. Generation of a cybrid test panel. A) Haploid-inducers (HI) can function as plasmotype donors when used as a female parent. In this case, uniparental genome elimination (red arrow) leads to a haploid offspring plant with the nucleotype of the wild-type (WT) male parent, but the plasmotype of the HI mother. B) Generation of a HI line with a new plasmotype. A cross of a wild type (female)

Figure 2 .

 2 Figure 2. The nucleotype-plasmotype interaction explains more variation than the plasmotype. Distribution of the fraction of broad sense heritability (H 2 ) for the three genetic components (nucleotype, plasmotype and the nucleotype-plasmotype interaction). Data given for 34 representative phenotypes. Dashed lines indicate the average H 2 for each component; B) is a subset of A). See Supplementary Fig. 5 for plots on the complete set of 906 phenotypes.

Figure 3 .

 3 Figure 3. Plasmotype changes result in cytonuclear epistasis, except in the case of cybrids with the Ely plasmotype which show additive effects. Phenotypes of the 48 examined cybrid lines for A) PSII efficiency (φPSII) for electron transport at 13.4 days after sowing (DAS) (n=24) B) Shoot dry matter biomass (g) at 30 DAS (n=12) C) NPQ at 17.96h into the measurement during constant environmental conditions of 200 µmol m -2 s -1 (n=4) D) NPQ at 66.79h into the measurement on the same plants as in C), measured at 496 µmol m -2 s -1 right after 1000 µmol m -2 s -1 (n=4). Error bars represent the standard error of the mean.

  . Significant changes in plant phenotypes between wild-type nucleotype-plasmotype combinations (self-cybrids) and cybrids with different plasmotypes for 34 selected phenotypes (Supplementary data 2 for underlying phenotypes). Rows indicate the number of significant effects when comparing self-cybrids to cybrids with identical nucleotype but non-native plasmotype. Columns indicate the changes when plasmotype is kept constant. Note that the Ely Ely self-cybrid shows many significant changes compared with Ely XXX cybrids (bottom row) and that the XXX Ely cybrids show many significant changes compared with XXX XXX self-cybrids (last column), which is due to the large-effect mutation in the chloroplast-encoded PsbA gene of the Ely plasmotype. Posthoc test done with Dunnet, α = 0.05. nd = not determined. For underlying p-values, see Supplementary data 2. Yellow cells indicate low numbers of significant changes; blue cells show higher number of significant changes.

Author contributions: P.J.F. and E.W. conceived and designed the study. T.P.J.M.T. designed and performed the statistical analysis with help from P.J.F., W.K. and F.v.E.. P.J.F., T.P.J.M.T., E.K., F.F.M.B., L.W., J.v.A., J.M.G., and L.S. performed experiments. P.J.F., T.P.J.M.T., K.S., P.K., E.S., J.A.H., S.K.S., W.L., R.M., F.v.E. and E.W. analysed data. D.M.K., J.J.B.K., M.K., J.H. and M.G.M.A. contributed to the interpretation of results. P.J.F., T.P.J.M.T. and E.W. wrote the paper with significant contributions from M.K., J.H. and M.G.M.A. All authors read and approved the final manuscript. Data availability: Sequencing and transcriptome data will be available in the European Nucleotide Archive with the primary accession code PRJEB29654. The raw datasets will be made available through Dryad, a reporting summary will be provided. The analysed datasets that support our findings are available as supplementary datasets. The associated raw data for Figures 2 and3 are provided in Supplementary data 1, the raw data for Table 1 are provided in Supplementary data 2. The germplasm generated in this project will be available via NASC.


Maëlle Biotteau

Sébastien Dejean

Sandrine Lelong

Stéphanie Iannuzzi

Nathalie Faure-Marie

Pierre Castelnau

Francois Rivier

Valérie Lauwers-Cances

Éloïse Baudou

Yves Chaix

Sporadic and Familial Variants in NF1: An Explanation of the Wide Variability in Neurocognitive Phenotype?

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.


Bernard Sellato Petualangan

Unjung Dan

Mbui Kuvong

Bernard Sellato|

Nicolas Césard

Antonio Guerreiro

Petualangan Antonia Soriente

Bernard Sellato
email: bernard.sellato@wanadoo.fr

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This volume appears as a late sequel of a research program, Culture and Conservation in East Kalimantan (C&C), carried out from 1990 to 1997 in Bulungan (now Malinau) District with recurrent funding from the Ford Foundation in Jakarta, and focused on the immense Kayan Mentarang Nature Reserve (then 1.6 million hectares; later gazetted as a National Park), where WWF Indonesia Programme then started running the Kayan Mentarang Conservation Project on behalf of the Directorate General of Forest Protection and Nature Conservation (PHPA) and in collaboration with the Indonesian Institute of Science (LIPI). The C&C program, in its heyday involving up to fifty people, investigated the many facets of local traditional peoples' interaction with their forested environment, including their views of the forest as transpiring through their language, oral literature, and customary law (adat) (Two volumes of selected C&C research report, respectively 573 pp. and 297 pp., see: C. Eghenter and B. Sellato 1999;C. Eghenter, B. Sellato, and G.S. Devung 2003).

In 1995, the Foundation for Research and Development in Borneo (Yayasan Pengkajian dan Pengembangan Borneo) was registered in Jakarta, and it soon established in Samarinda a Center for Culture and Nature in Kalimantan (Pusat Kebudayaan dan Alam Kalimantan), also known as the Kalimantan Resource Center (KRC). The KRC library collection, then holding about 1,400 titles, was later (2010) transferred to Balikpapan and expanded to over 3,000 titles, possibly making it the largest library collection on Borneo located in Kalimantan. It is now nicely accommodated at Rumah Bhakti Lestari (Jl. Wiluyo Puspoyudho No. 13, Klandasan, Balikpapan; see also http://totalindonesia-foundation.com/).

Among C&C researchers were several linguists, as well as a large number of Kalimantan scholars and students, to document the local languages and collect oral literature and history. KRC's mission included the publication of C&C research output, in several series -"Dictionaries" (vernacular languages), "Oral Literature" (bilingual), "Adat", and "History" -and its dissemination to source communities and a wider readership, in the hope that this output could be used as "local content" (muatan lokal) at village schools. By 1998, when it came to a standstill, KRC had released seven titles.

Almost two decades later, this new volume merges revised and expanded versions of two 1998 KRC volumes by Drs Dollop Mamung on the language and folk literature of the Punan Tubu (or Tufu'), an important traditional community established in Malinau District. The Punan Tubu -here encompassing closely related groups in the Malinau, Mentarang, and Sekatak river drainages -are scattered in some forty settlements (maps pp. 27, 32), for a total population of 3,500 to 4,000 people (pp. 26, 33). The Punan Tubu language has been listed as part of the North Sarawak Group, but its exact position remains ambiguous (pp. 47-49).

The volume's preliminaries include a short Preface by Antonio Guerreiro, an experienced French scholar of Borneo, and a substantial Introduction (pp. 21-45) by Nicolas Césard and Antonia Soriente. Césard, a French anthropologist, wrote his doctoral thesis on social change among Punan Tubu; Soriente, an Italian linguist with an MA degree from Universitas Indonesia, took her PhD in Kuala Lumpur on Borneo languages and spent years in East Kalimantan.

Dollop, himself a Punan Tubu and an officer of the Punan Adat Council of East Kalimantan, described the "Fonologi bahasa daerah Dayak Punan Tubu" in his 1981 BA (S1) thesis. He then toiled on his own on a Punan Tubu dictionary, generating in 1994 a thick typed draft, which was turned into his 1998 KRC publication. Later yet, he and Soriente painstakingly revised the phonology and transcription system, expanded the dictionary's corpus, and extensively revised the oral literature texts and Indonesian translations.

After a general presentation of former nomadic groups in Borneo, the book's Introduction offers a brief history of the Punan Tubu and describes their modern situation, from the 1970s government-prompted resettlement schemes to recent migratory moves back to their upriver territories. It then focuses on their linguistic situation: Punan Tubu, like its Malinau and Mentarang variants, is an endangered language, due to intense cultural mixing in Malinau District and current coal mining activity, and the same holds true of their oral literature.

Albeit dwindling, the Punan Tubu corpus of oral literature -folk tales (mbui), folk songs (keledu'), epics (ketuya'), and healing ritual texts (wanglangit) (p. 35) -is quite rich. However, most of the texts that had been recorded since the 1980s have yet to be transcribed and translated. And the present volume, taking its title from the names of two major characters -Unjung, the quintessential beautiful, daring, and independent-minded woman, and Kuvong, a fearless, though somewhat thoughtless, (male) hero -only offers a selection of nine short folk tales (mbui), as a small tribute to this literary wealth.

Soriente then discusses at some length the problems met in committing oral texts to paper, the particulars of this corpus, the selected stories, their contents and mythical components, their construction, their performance and its context, their environment (the village, forest, and river) and the animal characters featured. She concludes by stressing the tales' unique cultural and moral teachings from the not-so-remote times when Punan Tubu were still roaming the hinterland's thick forests as nomads (p. 43).

The folk tale section itself covers a hundred pages (pp. 63-163) with text in Punan Tubu and Indonesian on facing pages. It is preceded by Soriente's brief description of Punan Tubu language (pp. 47-62), successively examining its phonology and morphology, and finally the Punan Tubu kinship system. The 3,000-entry revised Punan Tubu dictionary (pp. 195-372) is preceded by a few introductory pages. A short section devoted to medicinal plants (pp. 165-185) stands as a sort of annex, derived from a 2007 manuscript by Kasim Amat, a Punan Tubu expert, listing 44 species with bilingual descriptions and guidelines for folk medicinal use on facing pages, complete with Linnaean names. In a list of fifteen Punan Tubu informants (p. 373), surprisingly, only one is a woman. The final pages include the editors' biodata and a list of references. A page of Errata was later circulated.

This volume is a most welcome addition to our knowledge of the languages and literatures of Borneo, and in my eyes especially important as it is one of extremely few that ever focused on a minority community of former nomadic hunter-gatherers. Despite a few factual errors -for example, Bulungan is a Murutic isolect, like Tingalan (or Agabag) and Tidung, not a Malay dialect (p. 13) -it is an invaluable accomplishment, for which it would only have been fair that Dollop and Soriente be properly credited as the book's principal editors.