Analytical and numerical comparisons of two methods of estimation of additive × additive × additive interaction of QTL effects

This paper presents the analytical and numerical comparison of two methods of estimation of additive × additive × additive (aaa) interaction of QTL effects. The first method takes into account only the plant phenotype, while in the second we also included genotypic information from molecular marker observation. Analysis was made on 150 doubled haploid (DH) lines of barley derived from cross Steptoe × Morex and 145 DH lines from Harrington × TR306 cross. In total, 153 sets of observation was analyzed. In most cases, aaa interactions were found with an exert effect on QTL. Results also show that with molecular marker observations, obtained estimators had smaller absolute values than phenotypic estimators.

Modulation of the Wheat Seed-Borne Bacterial Community by Herbaspirillum seropedicae RAM10 and Its Potential Effects for Tryptophan Metabolism in the Root Endosphere

Plants and their associated microbiota share ecological and evolutionary traits that are considered to be inseparably woven. Their coexistence foresees the use of similar metabolic pathways, leading to the generation of molecules that can cross-regulate each other’s metabolism and ultimately influence plant phenotype. However, the extent to which the microbiota contributes to the overall plant metabolic landscape remains largely unexplored. Due to their early presence in the seed, seed-borne endophytic bacteria can intimately colonize the plant’s endosphere while conferring a series of phytobeneficial services to their host. Understanding the dynamics of these endophytic communities is a crucial step toward the formulation of microbial inoculants that can modulate the functionality of the plant-associated microbiota for improved plant fitness. In this work, wheat (Triticum aestivum) roots non-inoculated and inoculated with the bacterium Herbaspirillum seropedicae strain RAM10 were analyzed to explore the impact of inoculant–endophyte–wheat interrelationships on the regulation of tryptophan (Trp) metabolism in the endosphere environment. Root inoculation with H. seropedicae led to phylum-specific changes in the cultivable seed-borne endophytic community. This modulation shifted the metabolic potential of the community in light of its capacity to modulate the levels of key Trp-related metabolites involved in both indole-3-acetic acid (IAA) biosynthesis and in the kynurenine pathway. Our results support a mode of action of H. seropedicae relying on a shift in both the composition and functionality of the seed-borne endophytic community, which may govern important processes such as root growth. We finally provide a conceptual framework illustrating that interactions among roots, inoculants, and seed-borne endophytes are critical to fine-tuning the levels of IAA in the endosphere. Understanding the outcomes of these interactions is a crucial step toward the formulation of microbial inoculants based on their joint action with seed-borne endophytic communities to promote crop growth and health in a sustainable manner.

Does Organic Farming Increase Raspberry Quality, Aroma and Beneficial Bacterial Biodiversity?

Plant-associated microbes can shape plant phenotype, performance, and productivity. Cultivation methods can influence the plant microbiome structure and differences observed in the nutritional quality of differently grown fruits might be due to variations in the microbiome taxonomic and functional composition. Here, the influence of organic and integrated pest management (IPM) cultivation on quality, aroma and microbiome of raspberry (Rubus idaeus L.) fruits was evaluated. Differences in the fruit microbiome of organic and IPM raspberry were examined by next-generation sequencing and bacterial isolates characterization to highlight the potential contribution of the resident-microflora to fruit characteristics and aroma. The cultivation method strongly influenced fruit nutraceutical traits, aroma and epiphytic bacterial biocoenosis. Organic cultivation resulted in smaller fruits with a higher anthocyanidins content and lower titratable acidity content in comparison to IPM berries. Management practices also influenced the amounts of acids, ketones, aldehydes and monoterpenes, emitted by fruits. Our results suggest that the effects on fruit quality could be related to differences in the population of Gluconobacter, Sphingomonas, Rosenbergiella, Brevibacillus and Methylobacterium on fruit. Finally, changes in fruit aroma can be partly explained by volatile organic compounds (VOCs) emitted by key bacterial genera characterizing organic and IPM raspberry fruits.

Explaining preemptive acclimation by linking information to plant phenotype

We review mechanisms for preemptive acclimation in plants and propose a conceptual model linking developmental and evolutionary ecology with the acquisition of information through sensing of cues and signals. The idea is that plants acquire much of the information in the environment not from individual cues and signals but instead from their joint multivariate properties such as correlations. If molecular signalling has evolved to extract such information, the joint multivariate properties of the environment must be encoded in the genome, epigenome and phenome. We contend that multivariate complexity explains why extrapolating from experiments done in artificial contexts into natural or agricultural systems almost never works for characters under complex environmental regulation: biased relationships among the state variables both in time and space create a mismatch between the evolutionary history reflected in the genotype and the artificial growing conditions in which the phenotype is expressed. Our model can generate testable hypotheses bridging levels of organization. In this note we describe the model, its theoretical bases and discuss its implications. We illustrate the hypotheses that can be derived from the model in two cases of preemptive acclimation based on correlations in the environment: the shade avoidance response and acclimation to drought.

Metric learning for image-based flower cultivars identification

Background The study of plant phenotype by deep learning has received increased interest in recent years, which impressive progress has been made in the fields of plant breeding. Deep learning extremely relies on a large amount of training data to extract and recognize target features in the field of plant phenotype classification and recognition tasks. However, for some flower cultivars identification tasks with a huge number of cultivars, it is difficult for traditional deep learning methods to achieve better recognition results with limited sample data. Thus, a method based on metric learning for flower cultivars identification is proposed to solve this problem. Results We added center loss to the classification network to make inter-class samples disperse and intra-class samples compact, the script of ResNet18, ResNet50, and DenseNet121 were used for feature extraction. To evaluate the effectiveness of the proposed method, a public dataset Oxford 102 Flowers dataset and two novel datasets constructed by us are chosen. For the method of joint supervision of center loss and L2-softmax loss, the test accuracy rate is 91.88%, 97.34%, and 99.82% across three datasets, respectively. Feature distribution observed by T-distributed stochastic neighbor embedding (T-SNE) verifies the effectiveness of the method presented above. Conclusions An efficient metric learning method has been described for flower cultivars identification task, which not only provides high recognition rates but also makes the feature extracted from the recognition network interpretable. This study demonstrated that the proposed method provides new ideas for the application of a small amount of data in the field of identification, and has important reference significance for the flower cultivars identification research.

Extension of Plant Phenotypes by the Foliar Microbiome

The foliar microbiome can extend the host plant phenotype by expanding its genomic and metabolic capabilities. Despite increasing recognition of the importance of the foliar microbiome for plant fitness, stress physiology, and yield, the diversity, function, and contribution of foliar microbiomes to plant phenotypic traits remain largely elusive. The recent adoption of high-throughput technologies is helping to unravel the diversityand spatiotemporal dynamics of foliar microbiomes, but we have yet to resolve their functional importance for plant growth, development, and ecology. Here, we focus on the processes that govern the assembly of the foliar microbiome and the potential mechanisms involved in extended plant phenotypes. We highlight knowledge gaps and provide suggestions for new research directions that can propel the field forward. These efforts will be instrumental in maximizing the functional potential of the foliar microbiome for sustainable crop production.

DNA Modification Patterns within the Transposable Elements of the Fig (Ficus carica L.) Genome

Transposable element activity can be harmful to the host’s genome integrity, but it can also provide selective advantages. One strategy to cope with transposons is epigenetic control through DNA base modifications. We report the non-canonic DNA modification dynamics of fig (Ficus carica L.) by exploiting high-quality genome reference and related N4-methylcytosine (4mC) and N6-methyladenine (6mA) data. Overall, 1.49% of transposon nucleotides showed either 4mC or 6mA modifications: the 4mC/6mA ratio was similar in Class I and Class II transposons, with a prevalence of 4mC, which is comparable to coding genes. Different percentages of 4mC or 6mA were observed among LTR-retrotransposon lineages and sub-lineages. Furthermore, both the Copia and Gypsy retroelements showed higher modification rates in the LTR and coding regions compared with their neighbour regions. Finally, the unconventional methylation of retrotransposons is unrelated to the number of close genes, suggesting that the 4mC and 6mA frequency in LTR-retrotransposons should not be related to transcriptional repression in the adjacency of the element. In conclusion, this study highlighted unconventional DNA modification patterns in fig transposable elements. Further investigations will focus on functional implications, in regards to how modified retroelements affect the expression of neighbouring genes, and whether these epigenetic markers can spread from repeats to genes, shaping the plant phenotype.