ArticlePlant biotechnology journal2016
Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.
Article in Plant biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 62 citations in OpenAlex.
- Multi-Omics Analysis of Drought and Growth Responses inPlants (Basel, Switzerland) · 2026Article
- Molecular and physiological characterization of two sunflower near-isogenic lines with contrasting haplotypes for leaf senescence.BMC plant biology · 2026Article
- Expression of a constitutively active nitrate reductase increases SARS-CoV-2 Spike protein production in Nicotiana benthamiana leaves that otherwise show traits of senescence.Plant biotechnology journal · 2026Article
- Transcriptome analysis unveils the intricate dynamics of senescence responses in Himalayan treeline species,Journal of genetics · 2025Article
- Identification and functional characterization of the MYB transcription factorFrontiers in plant science · 2025Article
- Comprehensive Proteome and Acetylome Analysis of Needle Senescence inInternational journal of molecular sciences · 2024Article
- Integrative Physiological, Transcriptome, and Proteome Analyses Provide Insights into the Photosynthetic Changes in Maize in a Maize-Peanut Intercropping System.Plants (Basel, Switzerland) · 2023Article
- Integrated transcriptomics and miRNAomics provide insights into the complex multi-tiered regulatory networks associated with coleoptile senescence in rice.Frontiers in plant science · 2022Article
- Function of Protein Kinases in Leaf Senescence of Plants.Frontiers in plant science · 2022Review
- Genome-wide and comparative phylogenetic analysis of senescence-associated NAC transcription factors in sunflower (Helianthus annuus).BMC genomics · 2021Article
- Genetic Improvement in Sunflower Breeding-Integrated Omics Approach.Plants (Basel, Switzerland) · 2021Review
- Comparative Transcriptome Analysis of Salt Stress-Induced Leaf Senescence inFrontiers in plant science · 2021Article
- Identification of a New Giant Emrbryo Allele, and Integrated Transcriptomics and Metabolomics Analysis of Giant Embryo Development in Rice.Frontiers in plant science · 2021Article
- Exploring sunflower responses to Sclerotinia head rot at early stages of infection using RNA-seq analysis.Scientific reports · 2020Article
- Source-sink modifications affect leaf senescence and grain mass in wheat as revealed by proteomic analysis.BMC plant biology · 2020Article
- Article
- Transcriptomic analysis reveals flavonoid biosynthesis of Syringa oblata Lindl. in response to different light intensity.BMC plant biology · 2019Article
- Asparagine Synthesis During Tobacco Leaf Curing.Plants (Basel, Switzerland) · 2019Article
- Transgenic expression of rice MYB102 (OsMYB102) delays leaf senescence and decreases abiotic stress tolerance in Arabidopsis thaliana.BMB reports · 2019Article
- Exploring gene networks in two sunflower lines with contrasting leaf senescence phenotype using a system biology approach.BMC plant biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 8 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Leaf senescence is a complex process, which has dramatic consequences on crop yield. In sunflower, gap between potential and actual yields reveals the economic impact of senescence. Indeed, sunflower plants are incapable of maintaining their green leaf area over sustained periods. This study characterizes the leaf senescence process in sunflower through a systems biology approach integrating transcriptomic and metabolomic analyses: plants being grown under both glasshouse and field conditions. Our results revealed a correspondence between profile changes detected at the molecular, biochemical and physiological level throughout the progression of leaf senescence measured at different plant developmental stages. Early metabolic changes were detected prior to anthesis and before the onset of the first senescence symptoms, with more pronounced changes observed when physiological and molecular variables were assessed under field conditions. During leaf development, photosynthetic activity and cell growth processes decreased, whereas sucrose, fatty acid, nucleotide and amino acid metabolisms increased. Pathways related to nutrient recycling processes were also up-regulated. Members of the NAC, AP2-EREBP, HB, bZIP and MYB transcription factor families showed high expression levels, and their expression level was highly correlated, suggesting their involvement in sunflower senescence. The results of this study thus contribute to the elucidation of the molecular mechanisms involved in the onset and progression of leaf senescence in sunflower leaves as well as to the identification of candidate genes involved in this process.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.