Posts by Collection

portfolio

publications

Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat

Published in Plant Physiology, 2013

This paper looks at the effects of an introgression from Agropyron elongatum into Triticum aestivum on drought tolerance.

Recommended citation: Placido, D.F., M.T. Campbell, J.J. Folsom, X. Cui, G.R. Kruger, P.S. Baenziger, and H. Walia. (2013). Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat. Plant Physiol. 161(4): 1806-1819. http://malachycampbell.github.io/files/Placido_2013.pdf

Genetic and Molecular Characterization of Submergence Response Identifies Subtol6 as a Major Submergence Tolerance Locus in Maize

Published in PLoS One, 2015

This paper assess natural variation for submegence tolerance in maize and identifies a QTL that influences submegence tolerance.

Recommended citation: Campbell, M.T., C.A. Proctor, Y. Dou, A.J. Schmitz, P. Phansak, G.R. Kruger, C. Zhang, and H. Walia. (2015). Genetic and molecular characterization of submergence response identifies Subtol6 as a major submergence tolerance locus in maize. PLoS One 10(3): e0120385. http://malachycampbell.github.io/files/Campbell_2015.pdf

Integrating image based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice

Published in Plant Physiology, 2015

Here, we used image based high thoughput phenotyping and association mapping to examine the genetic basis of temporal salinity responses.

Recommended citation: Campbell, M.T., A.C. Knecht, B. Berger, C.J. Brien, D. Wang, and H. Walia. (2015). Integrating image based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice. Plant Physiol. 168(August): pp.00450.2015. http://malachycampbell.github.io/files/Campbell_2015_pp.pdf

Image Harvest: an open source platform for high throughput plant image processing and analysis

Published in Journal of Experimental Botany, 2016

We developed a software to process and anayze images derived from high throughput phenotyping platforms.

Recommended citation: Knecht, A.C., M.T. Campbell, A. Caprez, D.R. Swanson, and H. Walia. (2016). Image Harvest: an open source platform for high throughput plant image processing and analysis. J. Exp. Bot. 67(11): 3587–3599 http://malachycampbell.github.io/files/Knecht_2016.pdf

Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content

Published in PLoS Genetics, 2017

HKT1;1 was identified as a major regualtor of root sodium content in rice. Variants that influence the transport of sodium were found to be a component of the divergence between to two subspecies of rice for root sodium content.

Recommended citation: Campbell, M.T., N. Bandillo, F.R.A. Al Shiblawi, S. Sharma, K. Liu, Q. Du, A.J. Schmitz, C. Zhang, A.A. Very, A.J. Lorenz, and H. Walia. 2017. Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content. PLoS Genet. 13(6). http://malachycampbell.github.io/files/Campbell_2017_hkt.pdf

A Comprehensive Image based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa)

Published in Plant Genome, 2017

We used a functional model of shoot biomass over 20 days and used model parameters for association mapping and genomic prediction.

Recommended citation: Campbell, M.T., Q. Du, K. Liu, C.J. Brien, B. Berger, C. Zhang, and H. Walia. 2017. A Comprehensive Image based Phenomic Analysis Reveals the Complex Genetic Architecture of Shoot Growth Dynamics in Rice (Oryza sativa). Plant Genome 10(2): 0 http://malachycampbell.github.io/files/Campbell_2017_pg.pdf

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

Published in Plant Direct, 2018

Here we used several random regression (RR) models with Legendre polynomials for genomic prediction of shoot growth trajectories in rice (Oryza sativa).

Recommended citation: Campbell, M.T., H. Walia, and G. Morota. 2018. Utilizing random regression models for genomic prediction of a longitudinal trait derived from high-throughput phenotyping. Plant Direct 2(9): e00080. http://malachycampbell.github.io/files/Campbell_2018_PD.pdf

Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice

Published in Plant Direct, 2018

Here, we used LASSO to select gene coexpression modules associated with salinity tolerance traits.

Recommended citation: Du, Q., M.T. Campbell, H. Yu, K. Liu, H. Walia, Q. Zhang, C. Zhang. (2018) Using LASSO in gene co-expression network for genome-wide identification of gene interactions responding to salt stress in rice. Plant Direct. http://malachycampbell.github.io/files/Du_LASSO_2018.pdf

ShinyAIM: Shiny-based Application of Interactive Manhattan Plots for Longitudinal Genome-Wide Association Studies

Published in Plant Direct, 2018

We developed a nice tool to easily visualize multiple manhattan plots. This is particaully useful for phenomics datasets or longitudinal studies.

Recommended citation: Hussain W., Campbell M., Walia H., Morota G. (2018) ShinyAIM: Shiny-based Application of Interactive Manhattan Plots for Longitudinal Genome-Wide Association Studies. Plant Direct 2(10), p.e00091. http://malachycampbell.github.io/files/Hussain_ShinyAIM_2018.pdf

The genetic basis of cis-regulatory divergence between the subspecies of cultivated rice (Oryza sativa)

Published in bioRxiv, 2019

The differences between the subspecies of rice has been extensively studied at the morphological and genetic levels, however few studies have examined how these subspecies diverge at the transcriptional level. Here, we provide a comprehensive comparison of transcriptome diversity within cultivated rice and document the cis regulatory divergence between Indica and Japonica. To date, this is the largest collection of rice transcriptomes.

Recommended citation: Campbell, M. T., Du, Q., Liu, K., Sharma, S., Zhang, C., & Walia, H. (2019). The genetic basis of cis-regulatory divergence between the subspecies of cultivated rice (Oryza sativa). bioRxiv, 511550. http://malachycampbell.github.io/files/Campbell2019_subspecies.pdf

Leveraging breeding values obtained from random regression models for genetic inference of longitudinal traits

Published in The Plant Genome, 2019

This study builds on the random regression genomic prediction approach described in Campbell et al 2018, and used the derived breeding values for genomic inferenece across time points.

Recommended citation: Campbell M.T., Momen M., Walia H., Morota G. (2019) Leveraging breeding values obtained from random regression models for genetic inference of longitudinal traits. The Plant Genome. http://malachycampbell.github.io/files/PlantGenome_2019.pdf

Genomic Bayesian confirmatory factor analysis and Bayesian network to characterize a wide spectrum of rice phenotypes

Published in G3, 2019

This is a really nice approach to reduce the dimensionality of phenomics datasets and understand the genetic interrelationships between trait classes. Haipeng used confirmatory factor analysis to reduce 48 observed phenotypes into six latent variables, which essentailly respresent unobserved biological processes that contribute to the traits, and used Bayesian network to understand the interdependence among latent variables. Check out the preprint!

Recommended citation: Yu, H., M.T. Campbell, Q. Zhang, H. Walia, G. Morota. (2018) Genomic Bayesian confirmatory factor analysis and Bayesian network to characterize a wide spectrum of rice phenotypes. G3: Genes, Genomes, Genetics. g3--400154. http://malachycampbell.github.io/files/Yu2019.pdf

Published in , 1900

Predicting longitudinal traits derived from high-throughput phenomics in contrasting environments using genomic Legendre polynomials and B-splines

Published in bioXriv, 2019

We sought to apply random regression models to forecast shoot growth trajectories using B-splines and Legendre polynomials in well-watered and water-limited conditions under various longitudinal cross-validation scenarios. We showed that the frequency of phenotypic evaluation can be reduced without impacing prediction accuracy.

Recommended citation: Momen M., Campbell M.T., Walia H., Morota G. (2019) Predicting longitudinal traits derived from high-throughput phenomics in contrasting environments using genomic Legendre polynomials and B-splines. bioXriv. http://malachycampbell.github.io/files/Momen_2019b.pdf

Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

Published in bioXriv, 2019

We applied variance-heterogeneity GWAS to identify several loci associated with grain cadmium concentration in bread wheat. Moreover, we showed that several of the vQTL loci were involved in pairwise interactions with other vQTL loci, indicating that epistasis may underlie differences in variance heterogeniety.

Recommended citation: Hussain W., Campbell M.T., Jarquin D., Walia H., Morota G. (2019) Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions. bioXriv. http://malachycampbell.github.io/files/WH_2019_vQTL.pdf

Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice

Published in bioXriv, 2019

We used a novel, genome-enabled growth model that integrates genome-wide SNP markers and empirical data derived from image-based phenotyping platforms to jointly model water use and shoot biomass trajectories. We show that there is a trade-off between early vigor and drought tolerance, and identify an aquaporin gene, OsPIP1;1, as a potential candidate that regulates the timing of shoot growth responses to water deficit.

Recommended citation: Campbell M.T., Grondin A., Walia H., Morota G. (2019) Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice. bioXriv. http://malachycampbell.github.io/files/MTC_2019_CGM.pdf

resources

talks

teaching

GWAS Workshop @ VT

Short Workshop, Virginia Tech, School of Plant and Environmental Sciences, 2019

This workshop is intended to give students an introduction to running GWAS in R. It covers genotyping quality control, single marker regression, whole genome regression, and advanced topics for GWAS on multidimensional datasets. Below are the course materials for the sections I taught.

woodworking