Assessment of genetic diversity and population structure in crops is essential for breeding and germplasm conservation. A collection of 354 bread wheat genotypes, including Mediterranean landraces and modern cultivars representative of the ones most widely grown in the Mediterranean Basin, were characterized with 11196 single nucleotide polymorphism (SNP) markers. Total genetic diversity ( H T ) and polymorphic information content (PIC) were 0.36 and 0.30 respectively for both landraces and modern cultivars. Linkage disequilibrium for the modern cultivars was higher than for the landraces (0.18 and 0.12, respectively). Analysis of the genetic structure showed a clear geographical pattern for the landraces, which were clustered into three subpopulations (SPs) representing the western, northern and eastern Mediterranean, whereas the modern cultivars were structured according to the breeding programmes that developed them: CIMMYT/ICARDA, France/Italy, and Balkan/eastern European countries. The modern cultivars showed higher genetic differentiation ( G ST ) and lower gene flow (0.1673 and 2.49, respectively) than the landraces (0.1198 and 3.67, respectively), indicating a better distinction between subpopulations. The maximum gene flow was observed between landraces from the northern Mediterranean SPs and the modern cultivars released mainly by French and Italian breeding programmes.

Background: Roots are essential for drought adaptation because of their involvement in water and nutrient uptake. As the study of the root system architecture (RSA) is costly and time-consuming, it is not generally considered in breeding programs. Thus, the identification of molecular markers linked to RSA traits is of special interest to the breeding community. The reported correlation between the RSA of seedlings and adult plants simplifies its assessment. Methods: In this study, a panel of 170 bread wheat landraces from 24 Mediterranean countries was used to identify molecular markers associated with the seminal RSA and related traits: seminal root angle, total root number, root dry weight, seed weight and shoot length, and grain yield (GY). Results: A genome-wide association study identified 135 marker-trait associations explaining 6% to 15% of the phenotypic variances for root related traits and 112 for GY. Fifteen QTL hotspots were identified as the most important for controlling root trait variation and were shown to include 31 candidate genes related to RSA traits, seed size, root development, and abiotic stress tolerance (mainly drought). Co-location for root related traits and GY was found in 17 genome regions. In addition, only four out of the fifteen QTL hotspots were reported previously. Conclusions: The variability found in the Mediterranean wheat landraces is a valuable source of root traits to introgress into adapted phenotypes through marker-assisted breeding. The study reveals new loci affecting root development in wheat.

The adaptability and stability of new bread wheat cultivars that can be successfully grown in rainfed conditions are of paramount importance. Plant improvement can be boosted using effective high-throughput phenotyping tools in dry areas of the Mediterranean basin, where drought and heat stress are expected to increase yield instability. Remote sensing has been of growing interest in breeding programs since it is a cost-effective technology useful for assessing the canopy structure as well as the physiological traits of large genotype collections. The purpose of this study was to evaluate the use of a 4-band multispectral camera on-board an unmanned aerial vehicle (UAV) and ground-based RGB imagery to predict agronomic traits as well as quantify the best estimation of leaf area index (LAI) in rainfed conditions. A collection of 365 bread wheat genotypes, including 181 Mediterranean landraces and 184 modern cultivars, was evaluated during two consecutive growing seasons. Several vegetation indices (VI) derived from multispectral UAV and ground-based RGB images were calculated at different image acquisition dates of the crop cycle. The modified triangular vegetation index (MTVI2) proved to have a good accuracy to estimate LAI (R2 = 0.61). Although the stepwise multiple regression analysis showed that grain yield and number of grains per square meter (NGm2) were the agronomic traits most suitable to be predicted, the R2 were low due to field trials were conducted under rainfed conditions. Moreover, the prediction of agronomic traits was slightly better with ground-based RGB VI rather than with UAV multispectral VIs. NDVI and GNDVI, from multispectral images, were present in most of the prediction equations. Repeated measurements confirmed that the ability of VIs to predict yield depends on the range of phenotypic data. The current study highlights the potential use of VI and RGB images as an efficient tool for high-throughput phenotyping under rainfed Mediterranean conditions.

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Understanding the genetic basis of agronomic traits is essential for wheat breeding programs to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can be a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin. The collection was phenotyped for agronomic and VI traits derived from multispectral images over 3 and 2 years, respectively. The GWAS identified 2,579 marker-trait associations (MTAs). The quantitative trait loci (QTL) overview index statistic detected 11 QTL hotspots involving more than one trait in at least 2 years. A CG analysis detected 12 CGs upregulated under abiotic stress in six QTL hotspots and 46 downregulated CGs in 10 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

Understanding the genetic basis of agronomic traits is essential for wheat breeding programmes to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can become a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin that were phenotyped for agronomic and VI traits derived from multispectral images over three and two years, respectively. GWAS identified 2579 marker–trait associations (MTAs). The QTL overview index statistic detected 11 QTL hotspots involving more than one trait in at least two years. A candidate gene analysis detected 12 CGs upregulated under abiotic stress in 6 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

Three experimental treatments consisting of inoculation with an arbuscular mycorrhizal fungus, application of a synthetic antimicrobial peptide or application of a resistance inducer, were evaluated in Madagascar periwinkle as control methods for rubus stunt and stolbur diseases caused by 'Candidatus Phytoplasma rubi' and 'Candidatus Phytoplasma solani', respectively. Two experiments were conducted under controlled environment conditions. In the first experiment, 4 months after graft-inoculating the phytoplasmas, the root colonization achieved by Rhizophagus irregularis significantly reduced both disease symptoms and the frequency of detection of the pathogens by real-time PCR. In the second experiment, the antimicrobial peptide BP100 totally prevented disease symptoms, despite the molecular detection of the phytoplasmas in 75% and 50% of the plants inoculated with 'Ca. Phytoplasma rubi' and 'Ca. Phytoplasma solani', respectively, and was more effective than benzothiadiazole (BTH) at increasing resistance against the pathogenic infections. A potential combination of early mycorrhizal inoculation and BP100 antimicrobial peptide application is envisaged as a future control strategy for phytoplasma diseases.

Knowledge of the genetic basis of traits controlling phenology, differentiation patterns, and environmental adaptation is essential to develop new cultivars under climate change conditions. Landrace collections are an appropriate platform to study the hidden variation caused by crop breeding. The use of genome-wide association analysis for phenology, climatic data and differentiation among Mediterranean landraces led to the identification of 651 marker-trait associations that could be grouped in 46 QTL hotspots. A candidate gene analysis using the annotation of the genome sequence of the wheat cultivar ‘Chinese Spring’ detected 1097 gene models within 33 selected QTL hotspots. From all the gene models, 42 were shown to be differentially expressed (upregulated) under abiotic stress conditions, and 9 were selected based on their levels of expression. Different gene families previously reported for their involvement in different stress responses were found (protein kinases, ras-like GTP binding proteins and ethylene-responsive transcription factors). Finally, the synteny analysis in the QTL hotspots regions among the genomes of wheat and other cereal species identified 23, 21 and 7 ortho-QTLs for Brachypodium, rice and maize, respectively, confirming the importance of these loci.