Glutaredoxin regulation of primary root growth is associated with early drought stress tolerance in pearl millet

Seedling root traits impact plant establishment under challenging environments. Pearl millet is one of the most heat and drought tolerant cereal crops that provides a vital food source across the sub-Saharan Sahel region. Pearl millet’s early root system features a single fast-growing primary root which we hypothesize is an adaptation to the Sahelian climate. Using crop modeling, we demonstrate that early drought stress is an important constraint in agrosystems in the Sahel where pearl millet was domesticated. Furthermore, we show that increased pearl millet primary root growth is correlated with increased early water stress tolerance in field conditions. Genetics including genome-wide association study and quantitative trait loci (QTL) approaches identify genomic regions controlling this key root trait. Combining gene expression data, re-sequencing and re-annotation of one of these genomic regions identified a glutaredoxin-encoding gene PgGRXC9 as the candidate stress resilience root growth regulator. Functional characterization of its closest Arabidopsis homolog AtROXY19 revealed a novel role for this glutaredoxin (GRX) gene clade in regulating cell elongation. In summary, our study suggests a conserved function for GRX genes in conferring root cell elongation and enhancing resilience of pearl millet to its Sahelian environment

Techniques de modelisation stochastique pour la reconnaissance de la parole

SIGLEINIST T 76427 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Combinaisons markoviennes et semi-markoviennes de modèles de régression (application à la croissance d'arbres forestiers)

Ce travail est consacré à l'étude des combinaisons markoviennes et semi-markoviennes de modèles de régression, i.e. des mélanges finis de modèles de régression avec dépendances (semi-)markoviennes. Cette famille de modèles statistiques permet l'analyse de données structurées en phases successives asynchrones entre individus, influencées par des covariables pouvant varier dans le temps et présentant une hétérogénéité inter-individuelle. L'algorithme d'inférence proposé pour les combinaisons (semi-)markoviennes de modèles linéaires généralisés est un algorithme du gradient EM. Pour les combinaisons (semi-)markoviennes de modèles linéaires mixtes, nous proposons des algorithmes de type MCEM où l'étape E se décompose en deux étapes de restauration conditionnelle: une pour les séquences d'états sachant les effets aléatoires (et les données observées) et une pour les effets aléatoires sachant les séquences d'états (et les données observées). Différentes méthodes de restauration conditionnelle sont présentées. Nous étudions deux types d'effets aléatoires: des effets aléatoires individuels et des effets aléatoires temporels. L'intérêt de cette famille de modèles est illustré par l'analyse de la croissance d'arbres forestiers en fonctions de facteurs climatiques. Ces modèles nous permettent d'identifier et de caractériser les trois principales composantes de la croissance (la composante ontogénique, la composante environnementale et la composante individuelle). Nous montrons que le poids de chaque composante varie en fonction de l'espèce et des interventions sylvicolesThis work focuses on Markov and semi-Markov switching regression models, i.e. finite mixtures of regression models with (semi-)Markovian dependencies. These statistical models enable to analyse data structured as a succession of stationary phases that are asynchronous between individuals, influenced by time-varying covariates and which present inter-individual heterogeneity. The proposed inference algorithm for (semi-)Markov switching generalized linear models is a gradient EM algorithm. For (semi-)Markov switching linear mixed models, we propose MCEM-like algorithms whose E-step decomposes into two conditional restoration steps: one for the random effects given the state sequences (and the observed data) and one for the state sequences given the random effects (and the observed data). Various conditional restoration steps are presented. We study two types of random effects: individual-wise random effects and environmental random effects. The relevance of these models is illustrated by the analysis of forest tree growth influenced by climatic covariates. These models allow us to identify and characterize the three main growth components (ontogenetic component, environmental component and individual component). We show that the weight of each component varies according to species and silvicultural interventionsMONTPELLIER-BU Sciences (341722106) / SudocSudocFranceF

Analysis of bearing and branching behavior of two apricot cultivars

International audienceThe nature of axillary production along shoots is one of the main factors influencing both vegetative and reproductive growth in apricot. This study aimed at analyzing the morphology and branching pattern of one-year-old shoots of 'Velkopavlovicka' cultivar in comparison with 'Bergeron'. 'Velkopavlovicka' is a classical, medium vigor, Czech cultivar which has naturally a spherical crown. In twelve-year-old trees grafted on apricot seedlings and pruned to an open vase, lateral branches were described from the second to the fourth orders. Each shoot was described as a sequence of metamers, and for each metamer the fate (latent, vegetative or floral) of the central bud as well as the number of associated flowers were noted. The presence or absence of development of axillary shoots from vegetative buds was also considered. A hidden semi-Markov chain was built for each cultivar on the basis of the sample of bivariate sequences corresponding to the two observed categorical variables, pooling all one-year-old annual shoots whatever the year. Both cultivars could be characterized by a similar organization in zones, but with different probabilities of occurrence of the median flower bud zone as well as by different mean number of central and associated flowers within this zone. Cultivar 'Bergeron' proved to be more floribund than 'Velkopavlovicka'. Moreover, they revealed biennial bearing in Central European conditions, but different reasons could be responsible for this behavior depending on the cultivar

Modeling developmental growth stages in mango on the basis of absolute vs. relative growth rates

International audiencePlant development, the change in plant structure, and growth, the increase of organ size over time are often studied as two separate processes. The concept of developmental growth stages has been recently proposed in mango to integrate both morphological traits and growth measurements. These stages rely on a strong match between developmental (i.e., phenological) stages and growth stages deduced from absolute growth rate (AGR) sequences. In this study, we explore growth stages deduced from relative growth rate (RGR) sequences. For a given mango cultivar (Cogshall or José) and either growth units (GUs) or inflorescences, a multistage model based on RGR sequences was first built. Growth stages deduced from this model were then compared with developmental stages determined visually. For GUs, the match rates between RGR-based stages and developmental stages were similar to the match rates between AGR-based stages and developmental stages, because of the rich information provided by the four organs modeled (the axis and three selected leaves). The match rates were far lower for the inflorescences where only the main axis was modeled. This is related to the fact that, compared to AGRs, RGRs amplify the variations at the beginning of growth of an organ while damping the variations at the end of growth. This explains the low match rates at the end of inflorescence growth. In plant growth studies, RGRs are often preferred to AGRs with the objective to take account of sink strength and to abstract from the effect of organ size. This latter argument is not relevant in our case since our probabilistic multistage model intrinsically abstracts from the organ size and only relies on the overlap of growth rate distributions for successive stages

Estimating the genetic value of F1 apple progenies for irregular bearing during first years of production

Highlights: Flowering regularity in apple trees during the beginning of their mature phase was assessed using new descriptors based on annual yields. These descriptors were approximated using subsamples of annual shoot sequences at axis scale to allow genotype evaluation at reasonable sampling costs. The approximation provided a good discrimination between regular and alternate bearing genotypes. QTLs were detected for some descriptors

Impact of three lateral root types identified in pearl millet on water uptake

Context: Diversity has been observed in the anatomy and growth patterns of lateral roots in cereals. This may impact water uptake and could therefore increase cereal performances under drought. This study focuses on pearl millet, a key crop for food security especially tolerant to drought. Objectives: The objective was to provide an integrated description of pearl millet lateral root development at early stages and to assess the impact of the existing diversity among lateral roots on water uptake using simulations

A multi-scale pipeline for reproducible analyses of tomato leaf expansion and its plasticity

Cell division and expansion both contribute to final leaf size in different plant species (Gonzalez et al., 2012). Correlations between final leaf size and cell number suggest that the cell cycle is a key process in leaf growth control. In some species, cells can also enter the specialized endoreduplication cycle. This variant of the cell cycle allows iterative DNA replication without cell division