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1

Deciphering Cattle Temperament Measures Derived From a Four-Platform Standing Scale Using Genetic Factor Analytic Modeling.

Yu H, Morota G, Celestino EF Jr, Dahlen CR, Wagner SA, Riley DG, Hulsman Hanna LL. Yu H, et al. Among authors: Morota G. Front Genet. 2020 Jun 12;11:599. doi: 10.3389/fgene.2020.00599. eCollection 2020. Front Genet. 2020. PMID: 32595702 Free PMC article.

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2

Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice (Oryza sativa).

Campbell MT, Grondin A, Walia H, Morota G. Campbell MT, et al. Among authors: Morota G. J Exp Bot. 2020 Jun 12:eraa280. doi: 10.1093/jxb/eraa280. Online ahead of print. J Exp Bot. 2020. PMID: 32526013

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3

Structural equation modeling for investigating multi-trait genetic architecture of udder health in dairy cattle.

Pegolo S, Momen M, Morota G, Rosa GJM, Gianola D, Bittante G, Cecchinato A. Pegolo S, et al. Among authors: Morota G. Sci Rep. 2020 May 8;10(1):7751. doi: 10.1038/s41598-020-64575-3. Sci Rep. 2020. PMID: 32385377 Free PMC article.

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4

Integration of single nucleotide variants and whole-genome DNA methylation profiles for classification of rheumatoid arthritis cases from controls.

Amiri Roudbar M, Mohammadabadi MR, Ayatollahi Mehrgardi A, Abdollahi-Arpanahi R, Momen M, Morota G, Brito Lopes F, Gianola D, Rosa GJM. Amiri Roudbar M, et al. Among authors: Morota G. Heredity (Edinb). 2020 May;124(5):658-674. doi: 10.1038/s41437-020-0301-4. Epub 2020 Mar 3. Heredity (Edinb). 2020. PMID: 32127659

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5

Multi-trait random regression models increase genomic prediction accuracy for a temporal physiological trait derived from high-throughput phenotyping.

Baba T, Momen M, Campbell MT, Walia H, Morota G. Baba T, et al. Among authors: Morota G. PLoS One. 2020 Feb 3;15(2):e0228118. doi: 10.1371/journal.pone.0228118. eCollection 2020. PLoS One. 2020. PMID: 32012182 Free PMC article.

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6

Divergent phenotypic response of rice accessions to transient heat stress during early seed development.

Paul P, Dhatt BK, Sandhu J, Hussain W, Irvin L, Morota G, Staswick P, Walia H. Paul P, et al. Among authors: Morota G. Plant Direct. 2020 Jan 12;4(1):e00196. doi: 10.1002/pld3.196. eCollection 2020 Jan. Plant Direct. 2020. PMID: 31956854 Free PMC article.

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7

Utilizing trait networks and structural equation models as tools to interpret multi-trait genome-wide association studies.

Momen M, Campbell MT, Walia H, Morota G. Momen M, et al. Among authors: Morota G. Plant Methods. 2019 Sep 18;15:107. doi: 10.1186/s13007-019-0493-x. eCollection 2019. Plant Methods. 2019. PMID: 31548847 Free PMC article.

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8

Predicting Longitudinal Traits Derived from High-Throughput Phenomics in Contrasting Environments Using Genomic Legendre Polynomials and B-Splines.

Momen M, Campbell MT, Walia H, Morota G. Momen M, et al. Among authors: Morota G. G3 (Bethesda). 2019 Oct 7;9(10):3369-3380. doi: 10.1534/g3.119.400346. G3 (Bethesda). 2019. PMID: 31427454 Free PMC article.

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9

Leveraging Breeding Values Obtained from Random Regression Models for Genetic Inference of Longitudinal Traits.

Campbell M, Momen M, Walia H, Morota G. Campbell M, et al. Among authors: Morota G. Plant Genome. 2019 Jun;12(2). doi: 10.3835/plantgenome2018.10.0075. Plant Genome. 2019. PMID: 31290928 Free article.

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10

Utilizing random regression models for genomic prediction of a longitudinal trait derived from high-throughput phenotyping.

Campbell M, Walia H, Morota G. Campbell M, et al. Among authors: Morota G. Plant Direct. 2018 Sep 10;2(9):e00080. doi: 10.1002/pld3.80. eCollection 2018 Sep. Plant Direct. 2018. PMID: 31245746 Free PMC article.

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