Identification and characterization of contrasting sunflower genotypes to early leaf senescence process combining molecular and physiological studies (Helianthus annuus L.)

Sunpheno: A Deep Neural Network for Phenological Classification of Sunflower Images

Leaf senescence is a complex trait which becomes crucial for grain filling because photoassimilates are translocated to the seeds. Therefore, a correct sync between leaf senescence and phenological stages is necessary to obtain increasing yields. In this study, we evaluated the performance of five deep machine-learning methods for the evaluation of the phenological stages of sunflowers using images taken with cell phones in the field. From the analysis, we found that the method based on the pre-trained network resnet50 outperformed the other methods, both in terms of accuracy and velocity. Finally, the model generated, Sunpheno, was used to evaluate the phenological stages of two contrasting lines, B481_6 and R453, during senescence. We observed clear differences in phenological stages, confirming the results obtained in previous studies. A database with 5000 images was generated and was classified by an expert. This is important to end the subjectivity involved in decision making regarding the progression of this trait in the field and could be correlated with performance and senescence parameters that are highly associated with yield increase.

Genome-wide and comparative phylogenetic analysis of senescence-associated NAC transcription factors in sunflower (Helianthus annuus)

BACKGROUND

Leaf senescence delay impacts positively in grain yield by maintaining the photosynthetic area during the reproductive stage and during grain filling. Therefore a comprehensive understanding of the gene families associated with leaf senescence is essential. NAC transcription factors (TF) form a large plant-specific gene family involved in regulating development, senescence, and responses to biotic and abiotic stresses. The main goal of this work was to identify sunflower NAC TF (HaNAC) and their association with senescence, studying their orthologous to understand possible functional relationships between genes of different species.

RESULTS

To clarify the orthologous relationships, we used an in-depth comparative study of four divergent taxa, in dicots and monocots, with completely sequenced genomes (Arabidopsis thaliana, Vitis vinifera, Musa acuminata and Oryza sativa). These orthologous groups provide a curated resource for large scale protein sequence annotation of NAC TF. From the 151 HaNAC genes detected in the latest version of the sunflower genome, 50 genes were associated with senescence traits. These genes showed significant differential expression in two contrasting lines according to an RNAseq assay. An assessment of overexpressing the Arabidopsis line for HaNAC001 (a gene of the same orthologous group of Arabidopsis thaliana ORE1) revealed that this line displayed a significantly higher number of senescent leaves and a pronounced change in development rate.

CONCLUSIONS

This finding suggests HaNAC001 as an interesting candidate to explore the molecular regulation of senescence in sunflower.

Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach

BACKGROUND

Leaf senescence is a complex process, controlled by multiple genetic and environmental variables. In sunflower, leaf senescence is triggered abruptly following anthesis thereby limiting the capacity of plants to keep their green leaf area during grain filling, which subsequently has a strong impact on crop yield. Recently, we performed a selection of contrasting sunflower inbred lines for the progress of leaf senescence through a physiological, cytological and molecular approach. Here we present a large scale transcriptomic analysis using RNA-seq and its integration with metabolic profiles for two contrasting sunflower inbred lines, R453 and B481-6 (early and delayed senescence respectively), with the aim of identifying metabolic pathways associated to leaf senescence.

RESULTS

Gene expression profiles revealed a higher number of differentially expressed genes, as well as, higher expression levels in R453, providing evidence for early activation of the senescence program in this line. Metabolic pathways associated with sugars and nutrient recycling were differentially regulated between the lines. Additionally, we identified transcription factors acting as hubs in the co-expression networks; some previously reported as senescence-associated genes in model species but many are novel candidate genes.

CONCLUSIONS

Understanding the onset and the progress of the senescence process in crops and the identification of these new candidate genes will likely prove highly useful for different management strategies to mitigate the impact of senescence on crop yield. Functional characterization of candidate genes will help to develop molecular tools for biotechnological applications in breeding crop yield.

Transcription Factors Associated with Leaf Senescence in Crops

Leaf senescence is a complex mechanism controlled by multiple genetic and environmental variables. Different crops present a delay in leaf senescence with an important impact on grain yield trough the maintenance of the photosynthetic leaf area during the reproductive stage. Additionally, because of the temporal gap between the onset and phenotypic detection of the senescence process, candidate genes are key tools to enable the early detection of this process. In this sense and given the importance of some transcription factors as hub genes in senescence pathways, we present a comprehensive review on senescence-associated transcription factors, in model plant species and in agronomic relevant crops. This review will contribute to the knowledge of leaf senescence process in crops, thus providing a valuable tool to assist molecular crop breeding.