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portfolio
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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
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 The Plant Genome, 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. (2020) Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions. The Plant Genome. doi:10.1002/tpg2.20011 http://malachycampbell.github.io/files/WH_2019_vQTL.pdf
Characterization of the transcriptional divergence between the subspecies of cultivated rice (Oryza sativa)
Published in BMC Genomics, 2020
Recommended citation: Campbell MT, Du Q, Liu K, Sharma S, Zhang C, Walia H. 2020. Characterization of the transcriptional divergence between the subspecies of cultivated rice (Oryza sativa). BMC Genomics. 21(1):1-6. http://malachycampbell.github.io/files/2020-BMC.pdf
Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice
Published in J. Exp. Bot., 2020
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. (2020) Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice. J. Exp. Bot 71(18):5669–5679. http://malachycampbell.github.io/files/2020-JxB.pdf
resources
Materials for a short course on omics assisted breeding methods
Slides for short course on ‘omics assisted breeding methods.
Leveraging breeding values obtained from random regression models for genetic inference of longitudinal traits
Malachy Campbell, Medhi Momen, Harkamal Walia, Gota Morota
talks
Natural variation in a rice sodium transporter, OsHKT1.1, provides insight into origins of salinity tolerance in rice
Published:
See Campbell et al (2017) in PLoS Genetics for the complete story.
Allelic variants of OsHKT1;1 underlie the divergence between Indica and Japonica subspecies of rice for root sodium content
Published:
Thsi talk summarised our PLoS Genetics paper on HKT1;1.
Allelic variants of OsHKT1;1 underlie the divergence between Indica and Japonica subspecies of rice for root sodium content
Published:
This is a presentation summarising the results of our PLoS Genetics paper where we identified HKT1;1 as a major regulator of natural variation for root sodium conent.
Genetic and Computational Approaches for Studying Plant Development and Abiotic Stress Responses Using Image-Based Phenotyping
Published:
Here, I discussed methods that I have used for genomic prediction and genome wide association mapping for longitudinal traits. The methods are discussed in detail in Campbell et al (2015), Campbell et al (2017), and Campbell et al (2018).
Utility of longitudinal traits derived from high-throughput phenotyping platforms for genomic prediction and GWAS
Published:
This presentation discussed the my current research in genomic prediction with Gota Morota, and some previous work on a two-step functional GWAS approach. The details of the methods discussed in this talk are outlined in Campbell et al (2017) and Campbell et al (2018).
Utilizing Longitudinal Phenotypes Derived from High Throughput Phenotyping to Study and Improve Adaptation to Water Limitation in Rice
Published:
Here I presented a study where we applied the random regression genomic prediction approach outlined here to select accessions with contrasting drought responses for high-resolution phenotyping.
Introducing the time axis in genomic prediction and association studies. Faculty of Agriculture
Published:
This talk outlined several methods to utilize temporal traits in genomic and prediction studies, and discussed some prelimiary research on integrating environmental covariates into longitudinal frameworks.
teaching
Statistical Methods for ‘Omics Assisted Breeding
Short Workshop, University of Tokyo 1, Department of Agricultural and Environmental Biology, 2018
The official webpage for ‘omics assisted breeding methods.
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.
Advanced Statistics and Experimental Design (PLSCI 7201)
Short Course, Cornell University, School of Integrative Plant Sciences, 2020
Advanced Statistics and Experimental Design
Instructors: Kelly Robbins (Bradfield 310), Malachy Campbell
Office Hours: by appointment
Meets: MWF (10:10am - 12:05pm; Aug 28 - Sept 25)
Grading: Letter Grade, 2 credit hours
woodworking
Cutting Boards
Small dish made of maple burl.
First Guitar
Just about finished. Just waiting for a proper set up.
Second Guitar
Assembled and awaiting a set up.