Author

Mitchell R. Tuinstra

Purdue University West LafayetteORCID 0000-0002-5322-6519Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Genomics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Organism:plant (other)· 3 Research Focus:variant calling· 3 Assay:whole-genome sequencing· 3 Research Focus:gene regulatory network inference· 2 Organism:zebrafish· 2 Research Focus:genome assembly· 1

Frequent Co-Authors

Charles Addo‐QuayeiD· 2 shared Clifford F. WeiliD· 2 shared Edward S. BuckleriD· 2 shared Elhan S. ErsoziD· 2 shared James Brendan HollandiD· 2 shared Jode W. EdwardsiD· 2 shared M. Cinta RomayiD· 2 shared Michael D. McMullen· 2 shared

Activity by Year

2017-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Charles Addo‐QuayeORCID

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Author profile →

5 papers

Recent·Most cited

Developing future resilience from signatures of adaptation across the sorghum pangenome

Geoffrey P. Morris, Avril M. Harder, Adam L. Healey, Chloee M. McLaughlin, Brian R. Rice, Clara M Cruet-Burgos, Jerry W. Jenkins, Joanna L. Rifkin, Shengqiang Shu, John J Spiekerman, Carl J. VanGessel, Erica Agnew, Alain Audebert, Kerrie Barry, Ivan R. Baxter, , John T. Lovell

This paper constructs a sorghum pangenome and identifies trait-associated variants to inform climate-aware genome-enabled breeding strategies.

bioRxiv · Aug 1, 2025 · PreprintGenomics

A High-Resolution Method for the Systematic Detection of EMS-Induced Mutations in a Sequenced Population

Jared M. Simons, Tim C. Herbert, Coleby Kauffman, Marc Y. Batete, Andrew T. Simpson, Yuka Katsuki, Dong Le, Danielle Amundson, Elizabeth M. Buescher, Clifford F. Weil, Mitchell R. Tuinstra, Charles Addo‐Quaye

The paper introduces a high-resolution method to detect EMS-induced mutations in sorghum mutants, improving SNP detection accuracy and uncovering additional false-negative mutations.

bioRxiv · Oct 13, 2021 · PreprintBioinformatics

The relevance of dominance and functional annotations to predict agronomic traits in hybrid maize

Guillaume P. Ramstein, Sara J. Larsson, Jason P. Cook, Jode W. Edwards, Elhan S. Ersoz, Sherry A. Flint-Garcia, Candice A. C. Gardner, James Brendan Holland, Aaron Joel Lorenz, Michael D. McMullen, Mark J. Millard, Torbert Rocheford, Mitchell R. Tuinstra, Peter J. Bradbury, Edward S. Buckler, M. Cinta Romay

This study shows dominance and gene annotations improve genomic prediction of agronomic traits in maize hybrids.

bioRxiv · Aug 24, 2019 · PreprintGenomics

Whole genome sequence accuracy is improved by replication in a population of mutagenized sorghum.

Charles Addo‐Quaye, Mitchell R. Tuinstra, Nicola Carraro, Clifford F. Weil, Brian P. Dilkes

The paper improves whole genome sequence accuracy by using replication to detect false positives in mutagenized sorghum, identifying 1.2 million high-quality EMS-induced SNPs.

G3 Genes Genomes Genetics · Jan 29, 2018Peer-reviewedGenetics

Genetic Analysis of Lodging in Diverse Maize Hybrids

Sara J. Larsson, Jason A. Peiffer, Jode W. Edwards, Elhan S. Ersoz, Sherry A. Flint-Garcia, James Brendan Holland, Michael D. McMullen, Mitchell R. Tuinstra, M. Cinta Romay, Edward S. Buckler

This study identifies quantitative trait loci (QTL) for lodging in maize by evaluating diverse inbred lines across multiple environments, finding overlaps with genes involved in lignin and cellulose synthesis.

bioRxiv · Sep 7, 2017 · PreprintGenetics