Author

Christopher J. Stubbs

University of IdahoORCID 0000-0002-3121-3223Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:whole-genome sequencing· 2 Organism:zebrafish· 2 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:genome assembly· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Bharath KunduruiD· 3 shared Christopher S. McMahaniD· 3 shared Daniel J. RobertsoniD· 3 shared Kaitlin TabaracciiD· 3 shared Manwinder S. BrariD· 3 shared Norbert T. BokrosiD· 3 shared Rajandeep S. SekhoniD· 3 shared Seth DeBoltiD· 3 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersGenetics

Bharath KunduruORCID

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Author profile →

3 papers

Recent·Most cited

Phenotypic plasticity, stalk geometry, and noncoding variation underpin stalk lodging resistance in maize

Bharath Kunduru, Norbert T. Bokros, Kaitlin Tabaracci, Rohit Kumar, Manwinder S. Brar, Christopher J. Stubbs, Yusuf Oduntan, Caíque Machado e Silva, W.C. Bridges, Ravi V. Mural, Seth DeBolt, Gota Morota, Christopher S. McMahan, Daniel J. Robertson, Rajandeep S. Sekhon

This study identifies genetic and phenotypic factors contributing to stalk lodging resistance in maize by analyzing intermediate traits and their genetic correlations.

bioRxiv · Aug 27, 2026 · PreprintGenetics

Genomic prediction of stalk lodging resistance and the associated intermediate phenotypes in maize using whole-genome resequence and multi-environmental data

Caíque Machado e Silva, Bharath Kunduru, Norbert T. Bokros, Kaitlin Tabaracci, Yusuf Oduntan, Manwinder S. Brar, Rohit Kumar, Christopher J. Stubbs, Maicon Nardino, Christopher S. McMahan, Seth DeBolt, Daniel J. Robertson, Rajandeep S. Sekhon, Gota Morota

This study improves genomic prediction of stalk lodging resistance in maize by integrating multi-environment data, showing that multi-environment models significantly enhance prediction accuracy for most traits.

The Plant Genome · Sep 1, 2025Peer-reviewedGenetics

High Density Phenotypic Map of Natural Variation for Intermediate Phenotypes Associated with Stalk Lodging Resistance in Maize

Bharath Kunduru, Norbert T. Bokros, Kaitlin Tabaracci, Rohit Kumar, Manwinder S. Brar, Christopher J. Stubbs, Yusuf Oduntan, Joseph DeKold, Rebecca Bishop, Joseph Woomer, Virginia L. Verges, Armando Gabriel McDonald, Christopher S. McMahan, Seth DeBolt, Daniel J. Robertson, Rajandeep S. Sekhon

The paper identifies 11 intermediate phenotypes related to stalk lodging resistance in maize and develops a high-density phenotypic dataset to enable genetic analysis and improve resistance.

bioRxiv · Apr 3, 2025 · PreprintPlant Biology