ArticlePlant biotechnology journal2018
Metabolite and transcript markers for the prediction of potato drought tolerance.
Article in Plant biotechnology journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.
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Who cites it
37 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Abiotic Stress in Crop Production.International journal of molecular sciences · 2023Pooled it
- Integration of meta-analysis, machine learning and systems biology approach for investigating the transcriptomic response to drought stress in Populus species.Scientific reports · 2023Pooled it
- Artificial Intelligence Methods in Forest Biotechnology: Current Status and Future Prospects.International journal of molecular sciences · 2026Review
- Role of Altered Metabolites and Metabolic Pathways in Major Tuber Crops Under Drought Stress.Plant-environment interactions (Hoboken, N.J.) · 2026Review
- Progress and Impacts of "Omics" Technologies in Understanding the Drought Response in Cassava: Adoption for Food Security in Africa.Plant-environment interactions (Hoboken, N.J.) · 2025Review
- Machine Learning-Based identification of resistance genes associated with sunflower broomrape.Plant methods · 2025Article
- Journal of plant diseases and protection : scientific journal of the German Phytomedical Society (DPG) · 2025Article
- Deciphering Drought Resilience in Solanaceae Crops: Unraveling Molecular and Genetic Mechanisms.Biology · 2024Review
- Whole-genome sequencing of tetraploid potato varieties reveals different strategies for drought tolerance.Scientific reports · 2024Article
- Potential of desiccation-tolerant plant growth-promoting rhizobacteria in growth augmentation of wheat (Frontiers in microbiology · 2023Article
- Transcriptome Analysis of Two Tetraploid Potato Varieties under Water-Stress Conditions.International journal of molecular sciences · 2022Article
- Construction of drought stress regulation networks in potato based on SMRT and RNA sequencing data.BMC plant biology · 2022Article
- Differential Physio-Biochemical and Metabolic Responses of Peanut (International journal of molecular sciences · 2022Article
- Comparative physiological, transcriptomic, and WGCNA analyses reveal the key genes and regulatory pathways associated with drought tolerance in Tartary buckwheat.Frontiers in plant science · 2022Article
- Genotype determinesFrontiers in plant science · 2022Article
- Emerging Roles of Plant DNA-Binding With One Finger Transcription Factors in Various Hormone and Stress Signaling Pathways.Frontiers in plant science · 2022Article
- The metabolomic landscape of rice heterosis highlights pathway biomarkers for predicting complex phenotypes.Plant physiology · 2021Article
- Natural variation in wild tomato trichomes; selecting metabolites that contribute to insect resistance using a random forest approach.BMC plant biology · 2021Article
- Genome-Wide Approach to Identify Quantitative Trait Loci for Drought Tolerance in Tetraploid Potato (International journal of molecular sciences · 2021Article
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11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions.
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