ReviewPlant & cell physiology2025
Beyond the Standard GWAS-A Guide for Plant Biologists.
Review in Plant & cell physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Review
- In Situ GWAS in Two Range-Edge Populations of European Beech (Fagus sylvatica L.) Identify Genetic Factors of Adaptation to Climate Change.Molecular ecology · 2026Article
- Higher-order structural organization of mitochondrial metabolism.The Journal of biological chemistry · 2026Review
- Constitutive and inducible oleoresin defenses share genetic architectures and mechanisms in Pinus taeda.The New phytologist · 2026Article
- Synthetic-augmented multimodal deep learning fuses dual-angle RGB images and phenology to unlock genotype-informative canopy structural trait in wheat.Plant phenomics (Washington, D.C.) · 2026Article
- GWAS-Guided Compact SNP Panels Enable Breeding-Relevant Prediction of Bolting and Flowering Timing of Lettuce.Plants (Basel, Switzerland) · 2026Article
- MateR: a novel genomic mating framework.Genetics · 2026Article
- Trait Association for Flowering Time in Lentil from Global Multi-Environment Data Using GWAS and Machine Learning.Plants (Basel, Switzerland) · 2026Article
- Accelerating Resistance Breeding: Emerging Methods to Identify and Validate Plant Immunity Genes.Plants (Basel, Switzerland) · 2026Review
- A bittersweet symphony: genetic insights into cider apple fruit quality.G3 (Bethesda, Md.) · 2026Article
- Genome-wide association study reveals genomic regions associated withFrontiers in plant science · 2026Article
- Genetic and molecular breeding perspectives on developing abiotic stress tolerant pea (Frontiers in plant science · 2026Review
- Article
- Functional Study ofPlants (Basel, Switzerland) · 2025Article
- Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Pangenome analysis of Liriodendron reveals presence/absence variations associated with growth traits.BMC plant biology · 2025Article
- Large-scale identification and association analysis of wheat grain weight genes using rice orthologs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- MADI: A multispectral automated dynamic imager to monitor plant health.Plant phenomics (Washington, D.C.) · 2025Article
- The Genetics of Plant-Plant Interactions and Their Cascading Effects on Agroecosystems-from Model Plants to Applications.Plant & cell physiology · 2025Review
- Chromosome-level assemblies of Amaranthus palmeri, Amaranthus retroflexus, and Amaranthus hybridus allow for genomic comparisons and identification of a sex-determining region.The Plant journal : for cell and molecular biology · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Classic genome-wide association studies (GWAS) look for associations between individual single-nucleotide polymorphisms (SNPs) and phenotypes of interest. With the rapid progress of high-throughput genotyping and phenotyping technologies, GWAS have become increasingly powerful for detecting genetic determinants and their molecular mechanisms underpinning natural phenotypic variation. However, GWAS frequently yield results with neither expected nor promising loci, nor any significant associations. This is often because associations between SNPs and a single phenotype are confounded, for example with the environment, other traits or complex genetic structures. Such confounding can mask true genotype-phenotype associations, or inflate spurious associations. To address these problems, numerous methods have been developed that go beyond the standard model. Such advanced GWAS models are flexible and can offer improved statistical power for understanding the genetics underlying complex traits. Despite this advantage, these models have not been widely adopted and implemented compared to the standard GWAS approach, partly because this literature is diverse and often technical. In this review, our aim is to provide an overview of the application and the benefits of various advanced GWAS models for handling complex traits and genetic structures, targeting plant biologists who wish to carry out GWAS more effectively.
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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.