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Oat, Avena sativa , is an important crop traditionally grown in cool-temperate regions. However, its cultivated area in the Mediterranean rim steadily increased during the last 20 years due to its good adaptation to a wide range of soils. Nevertheless, under Mediterranean cultivation conditions, oats have to face high temperatures and drought episodes that reduce its yield as compared with northern regions. Therefore, oat crop needs to be improved for adaptation to Mediterranean environments. In this work, we investigated the influence of climatic and edaphic variables on a collection of 709 Mediterranean landraces and cultivars growing under Mediterranean conditions. We performed genotype-environment interaction analysis using heritability-adjusted genotype plus genotype-environment biplot analyses to determine the best performing accessions. Further, their local adaptation to different environmental variables and the partial contribution of climate and edaphic factors to the different agronomic traits was determined through canonical correspondence, redundancy analysis, and variation partitioning. Here, we show that northern bred elite cultivars were not among the best performing accessions in Mediterranean environments, with several landraces outyielding these. While all the best performing cultivars had early flowering, this was not the case for all the best performing landraces, which showed different patterns of adaption to Mediterranean agroclimatic conditions. Thus, higher yielding landraces showed adaptation to moderate to low levels of rain during pre- and post-flowering periods and moderate to high temperature and radiation during post-flowering period. This analysis also highlights landraces adapted to more extreme environmental conditions. The study allowed the selection of oat genotypes adapted to different climate and edaphic factors, reducing undesired effect of environmental variables on agronomic traits and highlights the usefulness of variation partitioning for selecting genotypes adapted to specific climate and edaphic conditions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Canales, Montilla-Bascón, Gallego-Sánchez, Flores, Rispail and Prats.)

Key Message: The strong genetic structure observed in Mediterranean oats affects the predictive ability of genomic prediction as well as the performance of training set optimization methods. In this study, we investigated the efficiency of genomic prediction and training set optimization in a highly structured population of cultivars and landraces of cultivated oat (Avena sativa) from the Mediterranean basin, including white (subsp. sativa) and red (subsp. byzantina) oats, genotyped using genotype-by-sequencing markers and evaluated for agronomic traits in Southern Spain. For most traits, the predictive abilities were moderate to high with little differences between models, except for biomass for which Bayes-B showed a substantial gain compared to other models. The consistency between the structure of the training population and the population to be predicted was key to the predictive ability of genomic predictions. The predictive ability of inter-subspecies predictions was indeed much lower than that of intra-subspecies predictions for all traits. Regarding training set optimization, the linear mixed model optimization criteria (prediction error variance (PEVmean) and coefficient of determination (CDmean)) performed better than the heuristic approach "partitioning around medoids," even under high population structure. The superiority of CDmean and PEVmean could be explained by their ability to adapt the representation of each genetic group according to those represented in the population to be predicted. These results represent an important step towards the implementation of genomic prediction in oat breeding programs and address important issues faced by the genomic prediction community regarding population structure and training set optimization., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Recently, phenotyping has become one of the main bottlenecks in plant breeding and fundamental plant science. This is particularly true for plant disease assessment, which has to deal with time-consuming evaluations and the subjectivity of visual assessments. In this work, we have developed an open source Robust, User-friendy Script Tool (RUST) for semi-automated evaluation of leaf rust diseases. RUST runs under the free Fiji imaging software (developed from ImageJ), which is a well-recognized software among the scientific community. The script enables the evaluation of leaf rust diseases using a color transformation tool and provides three different automation modes. The script opens images sequentially and records infection frequency (pustules per area) (semi-)automatically for high-throughput analysis. Furthermore, it can manage several scanned leaf segments in the same image, consecutively selecting the desired segments. The script has been validated with nearly 900 samples from 80 oat genotypes ranging from resistant to susceptible and from very light to heavily infected leaves showing a high accuracy with a Lin's concordance correlation coefficient of 0.99. The analysis show a high repeatability as indicated by the low variation coefficients obtained when repeating the measurement of the same samples. The script also has optional steps for calibration and training to ensure accuracy, even in low-resolution images. This script can evaluate efficiently hundreds of leaves facilitating the screening of novel sources of resistance to this important cereal disease.

Salicylic acid (SA) is involved in several plant processes including responses to abiotic stresses. Although SA is thought to interact with other regulatory molecules in a complex way, currently, little information is available regarding its molecular mechanisms of action in response to abiotic stresses. In a previous work, we observed that drought-resistant oat plants significantly increased their SA levels as compared with a susceptible cultivar. Furthermore, exogenous SA treatment alleviated drought symptoms. Here, we investigated the interaction between SA and polyamine biosynthesis during drought responses in oat and revealed that SA regulated polyamine biosynthesis through changes in polyamine gene expression. Overall, SA treatment decreased the levels of putrescine under drought conditions while increased those of spermine. This correlates with the downregulation of the ADC gene and upregulation of the AdoMetDC gene. Based on the presented results, we propose that SA modulates drought responses in oat by regulating polyamine content and biosynthesis.

Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of field assessed phenotypes of genetic variants and of the weight of associated markers across different environmental variables. Association models accounting for oat population structure were applied on either arithmetic means or best linear unbiased prediction (BLUPs) to ensure robust identification of associations with the agronomic traits evaluated. The meta-analysis of the six joint environments (mega-environment) identified several markers associated with several agronomic traits and crown rust severity. Five of these associated markers were located within expressed genes. These associations were only mildly influenced by climatic variables indicating that these markers are good candidates to improve the genetic potential of oat under Mediterranean conditions. The models also highlighted several marker-trait associations, strongly affected by particular climatic variables including high rain pre- or post-heading dates and high temperatures, revealing strong potential for oat adaptation to specific agro-climatic conditions. These results will contribute to increase oat resilience for particular climatic conditions and facilitate breeding for plant adaptation to a wider range of climatic conditions in the current scenario of climate change.

Despite the established importance of nitric oxide (NO) in many physiological and molecular processes in plants, most methods for quantifying NO are open to criticism This reflects the differing methods either lacking specificity or sensitivity, or even from an undue dependence of results on experimental conditions (i.e., chemical concentrations, pH, etc.). In this chapter we describe a protocol to measure gaseous NO produced by a biological sample using quantum cascade laser (QCL)-based spectroscopy. This technique is based on absorption of the laser light by the NO molecules which have been passed from a biological sample into an optical s cell that is equipped with two mirrors placed at both ends. This design greatly increases the interaction path length with the NO molecules due to multiple reflections of the light coupled inside the cell. Thus, the method is able to provide online, in planta measurements of the dynamics of NO production, being highly selective and sensitive (down to ppbv levels;1 ppbv = part per billion by volume mixing ratio = 1:10 -9 ).

Nitric oxide (NO) is a key messenger in plant stress responses but its exact role in drought response remains unclear. To investigate the role of NO in drought response we employed transgenic barley plants (UHb) overexpressing the barley non-symbiotic hemoglobin gene HvHb1 that oxidizes NO to NO 3 - . Reduced NO production under drought conditions in UHb plants was associated with increased drought tolerance. Since NO biosynthesis has been related to polyamine metabolism, we investigated whether the observed drought-related NO changes could involve polyamine pathway. UHb plants showed increases in total polyamines and in particular polyamines such as spermidine. These increases correlated with the accumulation of the amino acid precursors of polyamines and with the expression of specific polyamine biosynthesis genes. This suggests a potential interplay between NO and polyamine biosynthesis during drought response. Since ethylene has been linked to NO signaling and it is also related to polyamine metabolism, we explored this connection. In vivo ethylene measurement showed that UHb plants significantly decrease ethylene production and expression of aminocyclopropane-1-carboxylic acid synthase gene, the first committed step in ethylene biosynthesis compared with wild type. These data suggest a NO-ethylene influenced regulatory node in polyamine biosynthesis linked to drought tolerance/susceptibility in barley.

In this work, we investigated the involvement of the long-term dynamics of cytoskeletal reorganization on the induced inaccessibility phenomenon by which cells that successfully defend against a previous fungal attack become highly resistant to subsequent attacks. This was performed on pea through double inoculation experiments using inappropriate (Blumeria graminis f. sp. avenae, Bga) and appropriate (Erysiphe pisi, Ep) powdery mildew fungi. Pea leaves previously inoculated with Bga showed a significant reduction of later Ep infection relative to leaves inoculated only with Ep, indicating that cells had developed induced inaccessibility. This reduction in Ep infection was higher when the time interval between Bga and Ep inoculation ranged between 18 and 24 h, although increased penetration resistance in co-infected cells was observed even with time intervals of 24 days between inoculations. Interestingly, this increase in resistance to Ep following successful defence to the inappropriate Bga was associated with an increase in actin microfilament density that reached a maximum at 18-24 h after Bga inoculation and very slowly decreased afterwards. The putative role of cytoskeleton reorganization/disorganization leading to inaccessibility is supported by the suppression of the induced resistance mediated by specific actin (cytochalasin D, latrunculin B) or general protein (cycloheximide) inhibitors., (© 2016 BSPP AND JOHN WILEY & SONS LTD.)

Oats (A. sativa L.) have an important and positive role in human diet and health. The health benefits of oats are attributed to its multifunctional characteristic and nutritional profile, being an important source of soluble dietary fiber, well-balanced proteins, unsaturated fatty acids, vitamins, essential minerals, and a good source of natural antioxidants. These antioxidants include the avenanthramides (Avns) and avenalumic acids, which are unique to oats among cereals. High-performance liquid chromatography allows a simultaneous quantification of free amino acids and biogenic amines in oat samples as their OPA/FMOC-CL (o-phthalaldehyde/9-fluorenylmethoxycarbonyl chloride) derivatives. In addition, an ultra-performance liquid chromatography/mass spectrometry method was developed to quantify and characterize avenanthramides contained in oat samples.

This chapter provides a practical overview of the statistical analysis using R [1] and genotype by sequencing (GBS) markers for genome-wide association studies (GWAS) in oats. Statistical analysis is performed by R package rrBLUP [2] and issues associated with the analysis are addressed along with the R code. The ultimate aim of this chapter is to provide a practical guideline to do GWAS analysis using R, rather than describe the theory in depth. For more details about the subject, readers are referred to the excellent resource book in GWAS [3]. A basic programming experience in R is assumed.

Stomatal dysfunction known as "locking" has been linked to the elicitation of a hypersensitive response (HR) following attack of fungal pathogens in cereals. We here assess how spatial and temporal patterns of different resistance mechanisms, such as HR and penetration resistance influence stomatal and photosynthetic parameters in oat ( Avena sativa ) and the possible involvement of hydrogen peroxide (H 2 O 2 ) in the dysfunctions observed. Four oat cultivars with differential resistance responses (i.e., penetration resistance, early and late HR) to powdery mildew ( Blumeria graminis f. sp. avenae , Bga ) were used. Results demonstrated that stomatal dysfunctions were genotype but not response-type dependent since genotypes with similar resistance responses when assessed histologically showed very different locking patterns. Maximum quantum yield (Fv/Fm) of photosystem II were compromised in most Bga -oat interactions and photoinhibition increased. However, the extent of the photosynthetic alterations was not directly related to the extent of HR. H 2 O 2 generation is triggered during the execution of resistance responses and can influence stomatal function. Artificially increasing H 2 O 2 by exposing plants to increased light intensity further reduced Fv/Fm ratios and augmented the patterns of stomatal dysfunctions previously observed. The latter results suggest that the observed dysfunctions and hence a cost of resistance may be linked with oxidative stress occurring during defense induced photosynthetic disruption.

Diseases caused by crown rust (Puccinia coronata f. sp. avenae) and powdery mildew (Blumeria graminis f. sp. avenae) are among the most important constraints for the oat crop. Breeding for resistance is one of the most effective, economical, and environmentally friendly means to control these diseases. The purpose of this work was to identify elite alleles for rust and powdery mildew resistance in oat by association mapping to aid selection of resistant plants. To this aim, 177 oat accessions including white and red oat cultivars and landraces were evaluated for disease resistance and further genotyped with 31 simple sequence repeat and 15,000 Diversity Arrays Technology (DArT) markers to reveal association with disease resistance traits. After data curation, 1712 polymorphic markers were considered for association analysis. Principal component analysis and a Bayesian clustering approach were applied to infer population structure. Five different general and mixed linear models accounting for population structure and/or kinship corrections and two different statistical tests were carried out to reduce false positive. Five markers, two of them highly significant in all models tested were associated with rust resistance. No strong association between any marker and powdery mildew resistance at the seedling stage was identified. However, one DArT sequence, oPt-5014, was strongly associated with powdery mildew resistance in adult plants. Overall, the markers showing the strongest association in this study provide ideal candidates for further studies and future inclusion in strategies of marker-assisted selection.