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Harnessing phenotypic networks and structural equation models to improve genome-wide association analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Utilizing random regression models for genomic prediction of a longitudinal trait derived from high‐throughput phenotyping
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Integrated genomics, physiology and breeding approaches for improving drought tolerance in crops
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GW-SEM: A Statistical Package to Conduct Genome-Wide Structural Equation Modeling
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The rice OsDIL gene plays a role in drought tolerance at vegetative and reproductive stages
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SMALL ORGAN SIZE 1 and SMALL ORGAN SIZE 2/DWARF AND LOW-TILLERING Form a Complex to Integrate Auxin and Brassinosteroid Signaling in Rice
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OVP1, a Vacuolar H+-translocating inorganic pyrophosphatase (V-PPase), overexpression improved rice cold tolerance
inferredcites →https://doi.org/10.1016/j.tplants.2006.06.003openalex-snapshot
Genomics-based approaches to improve drought tolerance of crops
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Challenges in breeding for yield increase for drought
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Cause and Correlation in Biology
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Bayesian mixture structural equation modelling in multiple-trait QTL mapping
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A meta-analysis of crop yield under climate change and adaptation
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Open access resources for genome-wide association mapping in rice
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Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa
inferredcites →https://doi.org/10.1038/ng1702openalex-snapshot
A unified mixed-model method for association mapping that accounts for multiple levels of relatedness
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Root architectural tradeoffs for water and phosphorus acquisition
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Phenotyping for drought tolerance in grain crops: when is it useful to breeders?
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Correlation Between Water-Use Efficiency and Carbon Isotope Discrimination in Diverse Peanut ( Arachis ) Germplasm
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Phospho enol pyruvate carboxylase intrinsically located in the chloroplast of rice plays a crucial role in ammonium assimilation
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Climate change and California drought in the 21st century
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Temperature increase reduces global yields of major crops in four independent estimates
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Mutations in a subfamily of abscisic acid receptor genes promote rice growth and productivity
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PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
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Rapid and Accurate Haplotype Phasing and Missing-Data Inference for Whole-Genome Association Studies By Use of Localized Haplotype Clustering
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Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales
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Multiple trait analysis of genetic mapping for quantitative trait loci.
inferredcites →https://doi.org/10.1093/jxb/erq201openalex-snapshot
High-throughput shoot imaging to study drought responses
inferredcites →https://doi.org/10.1093/jxb/err338openalex-snapshot
A rice orthologue of the ABA receptor, OsPYL/RCAR5, is a positive regulator of the ABA signal transduction pathway in seed germination and early seedling growth
inferredcites →https://doi.org/10.1093/jxb/ers349openalex-snapshot
The SNAC1-targeted gene OsSRO1c modulates stomatal closure and oxidative stress tolerance by regulating hydrogen peroxide in rice
inferredcites →https://doi.org/10.1093/pcp/pcu023openalex-snapshot
A Novel AP2-Type Transcription Factor, SMALL ORGAN SIZE1, Controls Organ Size Downstream of an Auxin Signaling Pathway
inferredcites →https://doi.org/10.1104/pp.103.033696openalex-snapshot
An Overview of Gibberellin Metabolism Enzyme Genes and Their Related Mutants in Rice
inferredcites →https://doi.org/10.1104/pp.15.00450openalex-snapshot
Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice
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Constitutive and Companion Cell-Specific Overexpression of AVP1 , Encoding a Proton-Pumping Pyrophosphatase, Enhances Biomass Accumulation, Phloem Loading, and Long-Distance Transport
inferredcites →https://doi.org/10.1105/tpc.021832openalex-snapshot
Arabidopsis RADICAL-INDUCED CELL DEATH1 Belongs to the WWE Protein–Protein Interaction Domain Protein Family and Modulates Abscisic Acid, Ethylene, and Methyl Jasmonate Responses
inferredcites →https://doi.org/10.1105/tpc.108.060913openalex-snapshot
A Novel Class of Gibberellin 2-Oxidases Control Semidwarfism, Tillering, and Root Development in Rice
inferredcites →https://doi.org/10.1111/j.1365-313x.2012.05091.xopenalex-snapshot
Rice MPR25 encodes a pentatricopeptide repeat protein and is essential for RNA editing of nad5 transcripts in mitochondria
inferredcites →https://doi.org/10.1111/j.1439-0388.2009.00835.xopenalex-snapshot
Bayesian structural equation models for inferring relationships between phenotypes: a review of methodology, identifiability, and applications
inferredcites →https://doi.org/10.1111/jbg.12002openalex-snapshot
An assessment of linkage disequilibrium in H olstein cattle using a B ayesian network
inferredcites →https://doi.org/10.1111/pbi.12145openalex-snapshot
Expression of the A rabidopsis vacuolar H +‐pyrophosphatase gene ( AVP 1) improves the shoot biomass of transgenic barley and increases grain yield in a saline field
inferredcites →https://doi.org/10.1145/956750.956838openalex-snapshot
Time and sample efficient discovery of Markov blankets and direct causal relations
inferredcites →https://doi.org/10.1146/annurev-arplant-050213-035715openalex-snapshot
Natural Variations and Genome-Wide Association Studies in Crop Plants
inferredcites →https://doi.org/10.1146/annurev.so.03.080177.001033openalex-snapshot
Structural Equation Models
inferredcites →https://doi.org/10.1175/bams-d-17-0149.1openalex-snapshot
Flash Droughts: A Review and Assessment of the Challenges Imposed by Rapid-Onset Droughts in the United States
inferredcites →https://doi.org/10.1186/1746-4811-7-2openalex-snapshot
Accurate inference of shoot biomass from high-throughput images of cereal plants
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Genetic studies of complex human diseases: Characterizing SNP-disease associations using Bayesian networks
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A predictive assessment of genetic correlations between traits in chickens using markers
inferredcites →https://doi.org/10.1199/tab.0140openalex-snapshot
Proline Metabolism and Its Implications for Plant-Environment Interaction
inferredcites →https://doi.org/10.1371/journal.pgen.0020114openalex-snapshot
Structural Model Analysis of Multiple Quantitative Traits
inferredcites →https://doi.org/10.1371/journal.pgen.1006823openalex-snapshot
Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content
inferredcites →https://doi.org/10.1371/journal.pone.0103997openalex-snapshot
A New Method to Infer Causal Phenotype Networks Using QTL and Phenotypic Information
inferredcites →https://doi.org/10.1371/journal.pone.0148609openalex-snapshot
Uncovering a Nuisance Influence of a Phenological Trait of Plants Using a Nonlinear Structural Equation: Application to Days to Heading and Culm Length in Asian Cultivated Rice (Oryza Sativa L.)
inferredcites →https://doi.org/10.1534/g3.117.044263openalex-snapshot
Bayesian Networks Illustrate Genomic and Residual Trait Connections in Maize (Zea maysL.)
inferredcites →https://doi.org/10.1534/g3.119.400154openalex-snapshot
Genomic Bayesian Confirmatory Factor Analysis and Bayesian Network To Characterize a Wide Spectrum of Rice Phenotypes
inferredcites →https://doi.org/10.1534/genetics.103.025734openalex-snapshot
Quantitative Genetic Models for Describing Simultaneous and Recursive Relationships Between PhenotypesThis article is dedicated to Arthur B. Chapman, teacher and mentor of numerous animal breeding students and disciple and friend of Sewall Wright.
inferredcites →https://doi.org/10.1534/genetics.107.077818openalex-snapshot
Analysis of Litter Size and Average Litter Weight in Pigs Using a Recursive Model
inferredcites →https://doi.org/10.1534/genetics.107.080069openalex-snapshot
Gene Network Inference via Structural Equation Modeling in Genetical Genomics Experiments
inferredcites →https://doi.org/10.1534/genetics.109.112979openalex-snapshot
Searching for Recursive Causal Structures in Multivariate Quantitative Genetics Mixed Models
inferredcites →https://doi.org/10.1534/genetics.111.134841openalex-snapshot
“SNP Snappy”: A Strategy for Fast Genome-Wide Association Studies Fitting a Full Mixed Model
inferredcites →https://doi.org/10.1534/genetics.113.151209openalex-snapshot
Is Structural Equation Modeling Advantageous for the Genetic Improvement of Multiple Traits?
inferredcites →https://doi.org/10.1534/genetics.115.179978openalex-snapshot
Do Molecular Markers Inform About Pleiotropy?
inferredcites →https://doi.org/10.18637/jss.v035.i03openalex-snapshot
Learning Bayesian Networks with the bnlearn R Package
inferredcites →https://doi.org/10.2135/cropsci1992.0011183x003200010003xopenalex-snapshot
Correlation between Water‐Use Efficiency and Carbon Isotope Discrimination in Diverse Cowpea Genotypes and Isogenic Lines
inferredcites →https://doi.org/10.2135/cropsci1995.0011183x003500060017xopenalex-snapshot
Variation in Water‐Use Efficiency and Its Components in Wheat: II. Pot and Field Experiments
inferredcites →https://doi.org/10.2307/1905714openalex-snapshot
The Statistical Implications of a System of Simultaneous Equations
inferredcites →https://doi.org/10.2307/1913851openalex-snapshot
Structural Equation Methods in the Social Sciences
inferredcites →https://doi.org/10.2307/2094445openalex-snapshot
The Decomposition of Effects in Path Analysis
inferredcites →https://doi.org/10.2527/1992.7072000xopenalex-snapshot
Estimation of effects of single genes on quantitative traits
inferredcites →https://doi.org/10.2527/jas1976.4361188xopenalex-snapshot
Multiple Trait Evaluation Using Relatives' Records
inferredcites →https://doi.org/10.3168/jds.2007-0980openalex-snapshot
Efficient Methods to Compute Genomic Predictions
inferredcites →https://doi.org/10.3389/fgene.2018.00455openalex-snapshot
Including Phenotypic Causal Networks in Genome-Wide Association Studies Using Mixed Effects Structural Equation Models
inferredcites →https://doi.org/10.3389/fgene.2018.00532openalex-snapshot
Structural Equation Modeling and Whole-Genome Scans Uncover Chromosome Regions and Enriched Pathways for Carcass and Meat Quality in Beef
inferredcites →https://doi.org/10.3835/plantgenome2016.07.0064openalex-snapshot
A Comprehensive Image‐based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice ( Oryza sativa )
inferredcites →https://doi.org/10.48550/arxiv.0908.3817openalex-snapshot
Learning Bayesian Networks with the bnlearn R Package
inferredcites →https://doi.org/10.7930/j0cj8bnnopenalex-snapshot
Ch. 8: Droughts, Floods, and Wildfires. Climate Science Special Report: Fourth National Climate Assessment, Volume I
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1038/s41598-020-64575-3openalex-snapshot
Structural equation modeling for investigating multi-trait genetic architecture of udder health in dairy cattle
inferred← citeshttps://doi.org/10.1111/jbg.12926openalex-snapshot
Novel Candidate Genes Detection Using Bayesian Network‐Based Genome‐Wide Association Study of Latent Traits in F2 Chicken Population
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