We are proudly supported by:

+ Basic Genomic Research

Gene expression variation defines much of phenotypic diversity. We work to characterize the genomic regulation of gene expression and this information to uncover genes that regulate complex evolutionary and economic traits.

+ Applied Research

Genomics is beginning to revolutionize breeding. Part of our research is in developing methods to accelerate the use of genomic data in plant breeding, by identifying polymorphisms that regulate complex plant traits, and developing models that predict phenotypes.

+ Method Development

For our research we use standard approaches adopted by the community, but also frequently require creating of new methods for genomic and data analysis. These include novel approaches to genotype by next-generation sequencing and genomic prediction.


National Science Foundation Plant Genome Research Program

Genome and transcriptome based prediction, and regulator inference, of molecular and whole-plant phenotypes
Co-PIs: Matias Kirst (PI), "Brad" Barbazuk, Márcio Resende, Gustavo de los Campos (Michigan State University)

The ability to use DNA to predict the traits of a plant, from its development to its productivity, remains one of most significant challenges of plant biology. Even more relevant and incomplete is the understanding of the chain of events that lead that trait, from DNA to RNA and protein, to the phenotype. A complete understanding of a plant’s biological system will allow the identification of the key regulatory points that impact its properties, while also allowing their prediction. In this project novel approaches will be developed to predict the development and the growth properties of plants, and their immediate regulators. These approaches will integrate genomic information beyond DNA sequence variation, to include transcriptome data, and create a more complete description and prediction of traits and their regulators. Tools developed here will be disseminated to the community by the release of analysis packages, and workshops will be conducted to enhance teaching of quantitative genetics and statistical methods in predictive models to the scientific community. The project incorporates a training component focused on high-school teachers and students. High-school teachers will join the investigator laboratories to learn about real-world applications of genomics and develop curriculum with support of UF’s Center for Precollegiate Education and Training (CPET). Students from underrepresented groups will be trained in science through CPET’s Student Science Training Program at the University of Florida. The proposed research will also provide ample opportunities to train graduate students at the intersection between quantitative and statistical genetics, and genomics.

USDA/DOE - Plant Feedstock Genomics for Bioenergy

Accelerated development of optimal pine feedstocks for bioenergy and renewable chemicals using genome-wide selection
Co-PIs: Matias Kirst (PI), Patricio Munoz and Gary Peter

Southern pines are a proven sustainable source of renewable biomass for bioenergy and renewable chemicals. However, for pines to meet their full potential as a major bioenergy crop, cultivars that are more productive and more efficiently converted into liquid fuels need to be developed. This aim will not be achieved using traditional breeding, which is logistically complex, expensive, and time-consuming in pines, where a single breeding cycle takes almost two decades. Thus, new breeding strategies that hyper-accelerate the development of cultivars that are suitable for bioenergy production need to be applied. The goal of this project is to hyper-accelerate pine breeding using genome-wide selection, to generate cultivars of loblolly and slash pine tailored to produce high energy yields, that are ready for deployment within the duration of this project. To achieve these goals we are pursuing these aims: First, available highly accurate genome-wide selection prediction models are being used to rapidly identify and generate crosses of loblolly pine designed to support the short-term needs of the bioenergy industry. Highly productive families with high cellulose (for biofuels), high lignin (for biopower) or high terpene (for renewable chemicals/biofuels) content are being generated from an elite breeding population, based on prediction models were previously developed. Second, advanced breeding populations of loblolly and slash pine, that encompass broad genetic diversity of each species, are being genotyped and phenotyped to create GWS prediction models for growth traits, wood chemistry and terpene flow. These genetically diverse populations will serve as the foundation for the next generation of advanced pine feedstocks for the bioenergy, biofuels and renewable chemicals industries.

US Department of Agriculture – Foundational Program

Accelerated breeding by improved accuracy and mate allocation using genome-wide selection
Co-PIs: Matias Kirst (PI), Patricio Munoz

The use of genome-wide selection (GWS) to predict yet-to-be-observed phenotypes is already common place in animal breeding and will increasingly improve selection gains in agriculture and forestry. However, limited advances have been made in developing more accurate prediction models, which are currently largely focused on additive effects. In preliminary work we demonstrated that the incorporation of non-additive effects dramatically improves accuracies and, consequently, genetic gains from GWS. Inclusion of non-additive effects also creates an unprecedented opportunity to apply GWS as a tool to predict which crosses generate optimal allele combination in the progeny (mate-pair allocation). For mate-pair allocation, the inclusion of non-additive effects in prediction models is essential to account for the dominance contribution of combining alleles from parents. In this project we are creating and disseminating improved methods of GWS for early selection of elite genotypes and identification of the most valuable crosses from a breeding population. Our goals are to (i) increase and accelerate genetic gain by developing and applying improved GWS models that incorporate non-additive effect; (ii) predict the performance of crosses to generate families with superior properties in future generations; and (iii) develop tools and resources to facilitate the use of these advanced methods by breeders. Methods developed in this proposal are being applied to forestry breeding populations, for productivity and disease resistance traits, and can be readily extended to agricultural crops.


Principal Investigator

Dr. Matias Kirst, PhD - (CV)
   Phone: (352) 846 0900 Fax: (352) 392.1707
   Office address: 367 Newins-Ziegler Hall, 1745 McCarty Drive, Gainesville, FL 32611-0410
   Lab address: UF Cancer and Genetics Research Complex, 2033 Mowry Rd., Gainesville, FL 32610-3610

Project Coordinator

Chris Dervinis -

Graduate Students

Annette Fahrenkrog - (PMCB Graduate Program)
   Annette has genotyped over 500 individuals of an association population of P. deltoides.
Rodrigo Santo - (PMCB Graduate Program)
   Rodrigo is working on the development and application of improved methods of genomic selection.
Johnathon Blahut - (PMCB Graduate Program)
   Johnathon is helping to characterize the evolutionary function of EVE1, and its molecular role.

Visiting Scholars

Flora Bittencourt (Universidade Estadual de Santa Cruz, Brazil)
   Flora works on population genetics of Virola officinalis.
Fernanda Gaiotto (Universidade Estadual de Santa Cruz, Brazil)
   Fernanda is Flora's PhD advisor and will work supervising and assistin in her research.
Isabela Sant'anna (Universidade Federal de Vicosa, Brazil)
   Isabela will work on the interaction between bioinformatics/RNA-seq and quantiative genetics.

Tomotaka Shinya (Nippon Paper, Japan)
   Tomotaka will spend a year in the lab learning about GWAS and genomic selection.

Undergraduate Students and Lab Staff

Madelyn Thiele - lab technician

Alumni - PhD Students (UF)

Cintia Leite Ribeiro (Ph.D. PMCB, August 2014)
   Now Emerging Science Leader at Monsanto
Juan Acosta Jaramillo (Ph.D. Forest Resources and Conservation, June 2014)
   Now Research Assistant Professor at North Carolina State University
Marcio Resende (Ph.D. Genetics and Genomics, May 2014)
   Now EVP Commercial Operations RAPiD Genomics LLC
Leandro Neves (Ph.D. PMCB, August 2013)
   Now EVP Science Operations RAPiD Genomics LLC
Patricio Munoz (Ph.D. PMCB, August 2013)
   Now Assistant Professor at the University of Florida
Evandro Novaes (Ph.D. Forest Resources and Conservation, May 2010)
   Now Assistant Professor at the Universidade Federal de Goias, Brazil
Derek Drost (Ph.D. PMCB, December 2009)
   Now Project Leader at Monsanto

Alumni - MSc Students

Ryan Brown (MSFRC, Forest Resources and Conservation, May 2010)
Cynthia Silva (M.Sc. Forest Resources and Conservation, December 2010)

Alumni - Students and Visiting Scientists

Joao Filipi Rodrigues Guimaraes (Universidade Federal de Vicosa, Brazil, 2014-2015)
Janeo de Almeida Filho (Universidade Federal de Vicosa, Brazil, 2014-2015)
Ana Maria Cruz e Oliveira (Universidade Federal de Vicosa, Brazil, 2012-2013)
Jaana Vuosku (University of Oulu, Finland, 2013)
Enrique Saez Laguna (Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria, Spain, 2012)
Leandro Boava (Centro de Citricultura, Brazil, 2011)
Judith Gomez (Centro de Biotecnología y Genomica de Plantas UPM/INIA, Spain, 2011)
Emilie Villar (Institute National de Recherche Agronomique, France, 2010)


Prediction of Phenotype Using Genomic Data - August 25, 2015

The third UF Workshop Prediction of Phenotype Using Genomic Data was held on August 25th 2015 in the Auditorium of the Cancer and Genetics Research Institute at the University of Florida. The event was accessible via online streaming for those unable to attend in person, with over 600 participants from 54 countries. The complete event can be viewed by accessing Details about the workshop program can be found here. This workshop is supported by the Agriculture and Food Research Initiative competitive grant no. 2013-67013-21159 from the USDA National Institute of Food and Agriculture.

PCB 5065, Advanced Genetics - Fall 2014

Advanced Genetics is a required course for graduate students in the Plant Molecular and Cellular Biology (PMCB) and in the Genetics and Genomics graduate programs, and is one of the pre-requisites for the course GMS 6231 (Genomics and Bioinformatics). I teach the section on Quantitative and Population Genetics, in which students are first given an overview of the properties of a population in equilibrium. This is followed by classes focused on how factors such as selection, migration and other evolutionary forces contribute to changes in gene frequencies. In the last part of this section, cover topics in quantitative genetics, with an emphasis on standard and advanced methods for identification of genes that regulate complex traits.

PCB 7299, Journal Colloquium - Fall 2014

This is a seminar course for graduate students in plant sciences, where the primary literature about genomics and molecular breeding is discussed. Students from the Plant Molecular and Cellular Biology Program are required to attend one journal colloquium each semester, but the meetings also include the participation of graduate students from other programs. Meetings are organized so that students spent the first weeks reading and discussing the fundamental aspects of the topic of discussion. In the later part of the semester, the primary scientific literature that applies these methods are reviewed and discussed.

GMS 6231 Genomic Sciences and Bioinformatics - Spring 2015

Genomics Sciences and Bioinformatics is a graduate course offered through the College of Medicine/Department of Molecular Genetics and Microbiology. The course is required for graduate students of the recently created graduate program in Genetics and Genomics. The course introduces students to the principles of genome and bioinformatic analyses of eukaryotes. It includes an overview of analytical platforms, computational tools, experimental design, analysis methods and databases used to study DNA sequence, gene expression and protein data. The course is divided into five sections: (1) DNA and genome sequencing, (2) DNA sequence variation, (3) transcriptome analysis, (4) proteome analysis and (5) integrative genomics. I am the course director, and also responsible for teaching the first and last section of the course.



Munoz PR, Resende MF Jr, Huber DA, Quesada T, Resende MDV, Neale DB, Wegrzyn JL, Kirst M, Peter GF. (2014) Genomic relationship matrix for correcting pedigree errors in breeding populations: impact on genetic parameters and genomic selection accuracy. Crop Sciences 54:1115-1123. doi:10.2135/cropsci2012.12.0673.

Neves LG, Davis JM, Barbazuk WB, Kirst M. (2014) A high-density gene map of loblolly pine (Pinus taeda L.) based on exome sequence capture genotyping. Genes, Genetics and Genomes 4:29-37. doi: 10.1534/g3.113.008714.

Quesada T, Resende MF, Muñoz PR, Wegrzyn JL, Neale DB, Kirst M, Peter GF, Gezan SA, Nelson CD, Davis JM. (2014) Mapping fusiform rust resistance genes within a complex mating design of loblolly pine. Forests 5:347-362. doi:10.3390/f5020347.

White T, Davis J, Gezan S, Hulcr J, Jokela E, Kirst M, Martin TA, Peter G, Powell G, Smith J. (2014) Breeding for value in a changing world: past achievements and future prospects. New Forests 45:301-309. doi: 10.1007/s11056-013-9400-x.

Zhang J, Novaes E, Kirst M, Peter GF. (2014) Comparison of pyrolysis mass spectrometry and near infrared spectroscopy for genetic analysis of lignocellulose chemical composition in Populus. Forests 5:466-481. doi:10.3390/f5030466.


Albert VA et al. The Amborella genome and the evolution of flowering plants. Science 342: 1516-1517. doi: 10.1126/science.1241089.

Maron LG, Guimarães CT, Kirst M, Albert PS, Birchler JA, Bradbury PJ, Buckler ES, Coluccio AE, Danilova TV, Kudrna D, Magalhaes JV, Piñeros MA, Schatz MC, Wing RA, Kochian LV. (2013) Aluminum tolerance in maize is associated with higher MATE1 gene copy-number. Proc. Natl. Acad. Sci. USA. 110:5241-5246. doi: 10.1073/pnas.1220766110.

Neves LG, Davis JM, Barbazuk WB, Kirst M. (2013) Whole-exome targeted sequencing of the uncharacterized pine genome. Plant J. 75:146-156. doi: 10.1111/tpj.12193.

Westbrook JW, Resende MF Jr, Munoz P, Walker AR, Wegrzyn JL, Nelson CD, Neale DB, Kirst M, Huber DA, Gezan SA, Peter GF, Davis JM. (2013) Association genetics of oleoresin flow in loblolly pine: discovering genes and predicting phenotype for improved resistance to bark beetles and bioenergy potential. New Phytol. 199:89-100. doi: 10.1111/nph.12240.


Resende MF Jr, Muñoz P, Resende MD, Garrick DJ, Fernando RL, Davis JM, Jokela EJ, Martin TA, Peter GF, Kirst M. (2012) Accuracy of genomic selection methods in a standard dataset of loblolly pine (Pinus taeda L.). Genetics. 190:1503-1510. doi: 10.1534/genetics.111.137026.

Harfouche A, Meilan R, Kirst M, Morgante M, Boerjan W, Sabatti M, Mugnozza GS. (2012) Accelerating the domestication of forest trees in a changing world. Trends in Plant Sciences. 17:64-72. doi: 10.1016/j.tplants.2011.11.005.

Resende MFR, Muñoz P, Acosta JJ; Peter GF, Davis JM, Grattapaglia D, Resende MDV, Kirst M. (2012) Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytologist. 193:617-624. doi: 10.1111/j.1469-8137.2011.03895.x.


Villar E, Klopp C, Noirot C, Novaes E, Kirst M, Plomion C, Gion JM. (2011) RNA-Seq reveals genotype-specific molecular responses to water deficit in eucalyptus. BMC Genomics. 12:538. doi: 10.1186/1471-2164-12-538.

Neves LG, Mc Mamani E, Alfenas AC, Kirst M, Grattapaglia D. (2011) A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus. BMC Genomics. 12:189. doi: 10.1186/1471-2164-12-189.

Grattapaglia D, Silva-Junior OB, Kirst M, de Lima BM, Faria DA, Pappas GJ Jr. (2011) High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species. BMC Plant Biology 11:65. doi: 10.1186/1471-2229-11-65.

Lourenço VM, Pires AM, Kirst M. Robust linear regression methods in association studies. (2011) Bioinformatics. 27:815-21. doi: 10.1093/bioinformatics/btr006.

Prosdocimi F, Bittencourt D, da Silva FR, Kirst M, Motta PC, Rech EL. (2011) Spinning gland transcriptomics from two main clades of spiders (order: Araneae) - insights on their molecular, anatomical and behavioral evolution. PLoS One. 6:e21634. doi: 10.1371/journal.pone.0021634.


Novaes, E., M. Kirst, V. Chiang, H. Winter-Sederoff and R. Sederoff. (2010) Lignin and biomass: a negative correlation for wood formation and lignin content in trees. Plant Physiology 154:555-561. doi: 10.1104/pp.110.161281.

Mattiello, L., M. Kirst, F.R. da Silva, R.A. Jorge and M. Menossi. (2010) Transcriptional profile of maize roots under acid soil growth. BMC Plant Biology 10:196. doi: 10.1186/1471-2229-10-196.

Visscher, A.M., A.L. Paul, M. Kirst, C.L. Guy, A.C. Schuerger and R.J. Ferl. (2010) Growth performance and root transcriptome remodeling of Arabidopsis in response to Mars-like levels of magnesium sulfate. PLoS One. 5:e12348. doi: 10.1371/journal.pone.0012348.
Drost, D.R., C.I. Benedict, A. Berg, E. Novaes, C.R. Novaes, Q. Yu, C. Dervinis, J.M. Maia, J. Yap, B. Miles and M. Kirst. (2010) Diversification in the genetic architecture of gene expression and transcriptional networks in organ differentiation of Populus. Proc. Natl. Acad. Sci. USA. 107:8492-8497. doi: 10.1073/pnas.0914709107.

Krill, A.M., M. Kirst, L.V. Kochian, E.S. Buckler and O.A. Hoekenga. (2010) Association and linkage analysis of aluminum tolerance genes in maize. PLoS One. 5:e9958. doi: 10.1371/journal.pone.0009958.


Brunings, A.M., L.E. Datnoff, J.F. Ma, N. Mitani, Y. Nagamura, B. Rathinasabapathi and M. Kirst. (2009) Differential gene expression of rice in response to silicon and rice blast fungus Magnaporthe oryzae. Annals of Applied Biology 155: 161-170. doi: 10.1111/j.1744-7348.2009.00347.x.

Visscher, A.M., A-L. Paul, M. Kirst, A.K. Alling, S. Silverstone, G. Nechitailo, M. Nelson, W.F. Dempster, M. Van Thillo, J.P. Allen and R.J. Ferl. (2009) Effects of a spaceflight environment on heritable changes in wheat gene expression. Astrobiology 9: 359-367. doi: 10.1089/ast.2008.0311.

Drost, D.R., E. Novaes, C. Boaventura-Novaes, C.I. Benedict, R.S. Brown, T. Yin, G.A. Tuskan and M. Kirst. (2009) A microarray-based genotyping and genetic mapping approach for highly heterozygous outcrossing species localizes a large fraction of the unassembled Populus trichocarpa genome sequence. Plant Journal 58: 1054-1067. doi: 10.1111/j.1365-313X.2009.03828.x.

Grattapaglia, D., C. Plomion, M. Kirst and R.R. Sederoff. (2009) Genomics of growth traits in forest trees. Current Opinion in Plant Biology 12: 148-156. doi: 10.1016/j.pbi.2008.12.008.

Novaes, E., L.F. Osorio, D.R. Drost, B.L. Miles, C. Boaventura-Novaes, C.I. Benedict, C. Dervinis, Q. Yu, R. Sykes, M. Davis, T.A. Martin, G.F. Peter and M. Kirst. (2009) Quantitative genetic analysis of biomass and wood chemistry of Populus under different nitrogen levels. New Phytologist 182: 878-890. doi: 10.1111/j.1469-8137.2009.02785.x.

2008</h2> Quesada, T., Z. Li, C. Dervinis, Y. Li, P.N. Bocock, G.A. Tuskan, G. Casella, J.M. Davis and M. Kirst. (2008) Comparative analysis of the transcriptomes of Populus trichocarpa and Arabidopsis thaliana suggests extensive evolution of gene expression regulation in angiosperms. New Phytologist 180: 408-420. doi: 10.1111/j.1469-8137.2008.02586.x.

Novaes, E., D.R. Drost, W.G. Farmerie, G.J. Pappas Jr., D. Grattapaglia, R.R. Sederoff and M. Kirst. (2008) High-throughput gene and SNP discovery in Eucalyptus grandis, an uncharacterized genome. BMC Genomics 9: 312-325. doi: 10.1186/1471-2164-9-312.

Grattapaglia, D. and M. Kirst. (2008) Eucalyptus applied genomics: from gene sequences to breeding tools. New Phytologist 179: 911-929. doi: 10.1111/j.1469-8137.2008.02503.x.

Maron, L.G., M. Kirst, C. Mao, M. Menossi and L.V. Kochian. (2008) Transcriptional profiling of Al toxicity and tolerance responses in maize roots. New Phytologist 179: 116-128.

Ma, C.-X., Q. Yu, A. Berg, D. Drost, E. Novaes, G. Fu, J.S. Yap, A. Tang, M. Kirst, Y. Cui and R. Wu. (2008) A pleiotropic model for mapping phenotypic plasticity of a count trait. Genetics 179: 627-636. doi: 10.1534/genetics.107.081794.


Gore, M., P. Bradbury, R. Hogers, M. Kirst, E. Verstege, J. van Oeveren, J. Peleman, E. Buckler and M. van Eijk. (2007) Evaluation of target preparation methods for single feature polymorphism detection in large complex plant genomes. Crop Science 47: S135-S148.


Kirst, M., R. Caldo, P. Casati, G. Tanimoto, V. Walbot, R.P. Wise and E.S. Buckler. (2006) Genetic diversity contribution to errors in short-oligonucleotide microarray analysis. Plant Biotechnology Journal 4: 489-498.

Tuskan, G.A., et al. (2006) The genome of western black cottonwood, Populus trichocarpa (Torr. & Gray ex Brayshaw). Science 313:1596-1604.

Tieman, D.M., M. Zeigler, E.A. Schmelz, M.G. Taylor, P. Bliss, M. Kirst and H.J. Klee. (2006) Identification of loci affecting flavour volatile emissions in tomato fruits. Journal of Experimental Botany 57:887-896.


Kirst, M., C.J. Basten, A. Myburg, Z.-B. Zeng and R. Sederoff. (2005) Genetic architecture of transcript level variation in differentiating xylem of Eucalyptus hybrids. Genetics 169: 2295-2303.

Kirst, M., C.M. Cordeiro, G.D.S.P. Rezende and D. Grattapaglia. (2005) Power of microsatellite markers for fingerprinting and parentage analysis in Eucalyptus grandis breeding populations. Journal of Heredity 96:161-166.


Egertsdotter, U., L.M. van Zyl, J. MacKay, G. Peter, M. Kirst, C. Clark, R. Whetten and R. Sederoff. (2004) Gene expression during formation of earlywood and latewood in loblolly pine: expression profiles of 350 genes. Plant Biology 6:654-663.

Kirst, M., A. Myburg, M.E. Kirst, J. Scott and R. Sederoff. (2004) Quantitative analysis of transcript variation on microarrays reveals coordinated downregulation of lignin gene transcripts associated with two quantitative trait loci for growth in a Eucalyptus hybrid backcross. Plant Physiology 135:2368-2378.


Kirst, M., A.F. Johnson, C. Baucom, E. Ulrich, K. Hubbard, R. Staggs, C. Paule, E. Retzel, R. Whetten and R. Sederoff. (2003) Apparent homology of expressed genes from wood-forming tissues of loblolly pine (Pinus taeda L.) with Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the U.S.A 100:7383-7388.

Brondani, R.P.V., Gaiotto, F.A., Missiaggia, A.A., Kirst, M., Gribel, R. and Grattapaglia, D. (2003) Microsatellite markers for Ceiba pentandra (Bombacaceae), an endangered tree species of the Amazon forest. Molecular Ecology Notes 3:177-179.


Genotype database for Populus deltoides

The complete genotype dataset generated for western cottonwood (poplar) is available upon request. The data was generated using sequence capture and next-generation sequencing of all known expressed genes, and putative regulatory sequences.

Germplasm collection of Populus deltoides

We assembled a populations of 600 individuals of Populus deltoides (Eastern cottonwood) derived from university-funded collections made across 13 states in the central, southern, and eastern US, in the last two decades. We manage this publically available resource that serves as the foundation for the major P. deltoides breeding program in the US and Europe. All the germplasm is readily available and is the basis for a GWAS study.

Standard genotypic and phenotypic dataset of loblolly pine

for benchmarking new methods in genomic prediction published in GENETICS (Resende et al. 2012. Genetics. 190:1503-1510). Files can be found here (Supporting Information – Table S1-6).

Microarray platforms and gene expression data for published Populus deltoides research

(Drost et al. 2010 107:8492-8497) is deposited in the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information ( GPL7169 and GPL7234,

Sequences of short expressed sequence tags

From Eucalyptus (Novaes et al. 2008.
BMC Genomics. 9:312) can be found here.