+1-302-831-1356 rjw@udel.edu
In prearation or review
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Wisser, R. J., Z. Fang, J. Teixeira, T. Weldekidan, N. de Leon, S. Flint-Garcia, N. Lauter, S. Murray, W. Xu, A. Hallauer, and J. B. Holland (2018) The genetic basis of rapid evolution for environmental adaptation in maize. [In preparation]

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Francis, F., S. B. Davis, J. Dunne, J. Holland, R. J. Nelson, T. Jamann, and R. J. Wisser (2018) Resequencing of a quantitative disease resistance locus provides benchmark data and insight into the spectrum of sequence variation in maize. [In preparation]

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Guo, T., X. Yu, X. Li, H. Zhang, C. Zhu, S. Flint-Garcia, M. D. McMullen, J. B. Holland, R. J. Wisser, and J. Yu (2018) Optimal Designs for Genomic Prediction in Hybrid CropsMolecular Plant [In Review]

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Lopez-Zuniga, L. O., T. Weldekidan, P. Wolters, S. Davis, J. Kolkman, R. J. Nelson, K. S. Hooda, E. Rucker, W. Thomason, R. J. Wisser, and P. Balint-Kurti (2018) Using maize chromosome segment substitution line populations for the identification of loci associated with multiple disease resistance. G3 [In Revision]

2018

Bioinformatic pipeline for PacBio amplicon libraries

Francis, F., Michael D. Dumas, Scott B. Davis, and R. J. Wisser (2018) Clustering of circular consensus sequences: accurate error correction and assembly of single molecule real-time reads from multiplexed amplicon libraries. BMC Bioinformatics 19:302

Genomes to Fields: the 2014-15 data

AlKhalifah, N., D. A. Campbell, C. M. Falcon, J. M. Gardiner, N. D. Miller, M. C. Romay, R. Walls, R. Walton, C.-T. Yeh, M. Bohn, J. Bubert, E. S. Buckler, I. Ciampitti, S. Flint-Garcia, M. A. Gore, C. Graham, C. Hirsch, J. B. Holland, D. Hooker, S. Kaeppler, J. Knoll, N. Lauter, E. C. Lee, A. Lorenz, J. P. Lynch, S. P. Moose, S. C. Murray, R. Nelson, T. Rocheford, O. Rodriguez, J. C. Schnable, B. Scully, M. Smith, N. Springer, P. Thomison, M. Tuinstra, \textbf{R. J. Wisser}, W. Xu, D. Ertl, P. S. Schnable, N. De Leon, E. P. Spalding, J. Edwards, C. J. Lawrence-Dill (2018) Maize genomes to fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets. BMC Research Notes 11:452.

Review of quantitative disease resistance: multi-scale complexity is durable

Nelson, R. J., T. Wiesner-Hanks, R. J. Wisser, and Peter Balint-Kurti (2018) Navigating complexity to breed disease-resistant crops. Nature Reviews Genetics 19:21-33.

New pedagogy: graduate students in genome science course develop active learning exercise for undergraduates

Wax, J., Z. Zhuo, A. Bower, J. Cooper, S. Gachara, I. Kamweru, T. Mhora, S. N. Neerukonda, D. Novick, J. Winkeler, T. Yoder, and R. J. Wisser (2018) A problem based learning exercise on food security: understanding the role of genomic variation and plant breeding. Genetics Society of America Peer-Reviewed Education Portal (GSA PREP) 004

2017

Genomes to Fields: reduction in GxE associated with adaptation

Gage, J., D. Jarquin, C. Romay, A. Lorenz, E. Buckler, S. Kaeppler, N. Alkhalifah, M. Bohn, D. Campbell, J. Edwards, D. Ertl, S. Flint-Garcia, J. Gardiner, B. Good, M. Gore, C. Hirsch, J. Holland, D. Hooker, J. Knoll, J. Kolkman, G. Kruger, N. Lauter, C. Lawrence-Dill, E. Lee, J. Lynch, S. Murray, R. Nelson, J. Petzoldt, T. Rocheford, J. Schnable, P. Schnable, B. Scully, M. Smith, N. Springer, S. Srinivasan, R. Walton, T. Weldekidan, R. Wisser, W. Xu, and J. Yu, and N. de Leon (2017) The effect of artificial selection on phenotypic plasticity in maize. Nature Communications 8:1348.

U-net CNN for macroscopic microcopy data (#1)

Saponaro, P., W. Treible, A. Kolagunda, S. Rhein, J. Caplan, C. Kambhamettu, and R. J. Wisser (2017) Three-dimensional segmentation of vesicular networks of fungal hyphae in macroscopic microscopy image stacks. IEEE International Conference on Image Processing Beijing, China., September, 2017. (arXiv:1704.02356)

U-net CNN for macroscopic microcopy data (#2)

Saponaro, P., W. Treible, A, Kolagunda, T. Chaya, J. Caplan, C. Kambhamettu, and R. Wisser (2017) DeepXScope: segmenting microscopy images with a deep neural network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops; Computer Vision for Microscopy Image Analysis (CVMI) Honolulu, Hawaii, July, 2017.

QTL cloning of a multiple disease resistance gene

Yang, Q., Y. He, M. Kabahuma, A. Kelly, E. Borrego, Y. Bian, F. E. Kasmi, L. Yang, J. Dunne, J. Kolkman, M. Kolomiets, R. Nelson, J. Holland, X. Li, N. Lauter, T. Chaya, J. Caplan, R. J. Wisser, and Peter Balint-Kurti (2017) A maize caffeoyl-CoA O-methyltransferase gene confers quantitative resistance to multiple pathogens. Nature Genetics 49:1364-1372.

Phased genotyping-by-sequencing

Manching. H., S. Segupta, K. Hopper, S. Polson, Y. Ji, and R. J. Wisser (2017) Phased genotyping-by-sequencing enhances analysis of genetic diversity and reveals divergent copy number variants in maize. Genes, Genomes, Genetics 7:2161-2170.

Genome-aware primer design tool

Francis, F., M. Dumas, and R. J. Wisser (2017) ThermoAlign: a genome-aware primer design tool for tiled amplicon resequencing. Scientific Reports 16(7):44437.

Ion AmpliSeq of flowering time genes in maize landraces

Jamann, T., S. Sood, R. J. Wisser, J. Holland (2017) High-throughput resequencing of maize landraces at genomic regions associated with flowering time. PLoS ONE 12(1): e0168910.

2016

Computer vision for fungal spore detection

Kolagunda, A., R. Wisser, T. Chaya, J. Caplan, and C. Kambhamettu (2016) Detection of fungal spores in 3D microscopy images of macroscopic areas of host tissue. IEEE International Conference on Bioinformatics and Biomedicine Shenzhen, China, December, 2016.

Platform for macroscopic microscopy

Minker, K*. R., M. L. Biedrzycki*, A. Kolagunda, S. Rhein, F. J. Perina, S. S. Jacobs, M. Moore, T. M. Jamann, R. Nelson, Q. Yang, P. Balint-Kurti, C. Kambhamettu, R. J. Wisser, J. L. Caplan (2016) Semi-automated confocal imaging of fungal pathogenesis on plants: microscopic analysis of macroscopic specimens. Microscopy Research and Technique, 141-152. In: Special Issue: Intact Organs: Super Resolution Multimodal Optical 4D Imaging. 2018. Volume 81, Issue 2.

*equal contributions: KRM and MLB; co-corresponding authors: RJW and JLC

BSA-GBS of lima bean downy mildew identifies markers predictive of qualitative resistance

Mhora, T., E. Ernest, R. J. Wisser, T. Evans, M. Patzoldt, N. Gregory, S. Polson, N. Donofrio (2016) Genotyping-by-sequencing to predict resistance to lima bean downy mildew in a diversity panel. Phytopathology; (Focus issue) Disease Management in the Genomics Era 106:1152-1158.

Genetics of leaf flecking in maize

Olukolu, B. A., Y. Bian, B. De Vries, W. F. Tracy, R. J. Wisser, J. B. Holland, P. J. Balint-Kurti (2016) The genetics of leaf flecking in maize and its relationship to the defense response and broad-spectrum disease resistance. Plant Physiology 172(3):1787-1803.

Association mapping of variation in resistance to common rust of maize

Olukolu, B. A., W. F. Tracy, R. J. Wisser, B. De Vries, P. J. Balint-Kurti (2016) A genome-wide association study for partial resistance to maize common rust. Phytopathology 106(7):745-51.

2015

After a decade of tropical-to-temperate adaptation...

Teixeira, J., T. Weldekidan, N. De Leon, S. Flint-Garcia, N. Lauter, J. Holland, S. Murray, W. Xu, D. Hessel, A. Kleintop, J. Hawk, A. Hallauer, R. J. Wisser (2015) Hallauer’s Tusón: a decade of selection for tropical-to-temperate phenological adaptation in maize. Heredity 114:229-240.

New plant tissue clearing technique

Warner, C. A., M. Biedrzycki, B, S. Jacobs, R. J. Wisser, J. L. Caplan, and J. Sherrier (2014) An optical clearing technique for plant tissues allowing deep imaging and compatible with fluorescence microscopy. Plant Physiology 166(4):1684-1687.

*Illuminated Cell Paper of the Month (May 2015)

2014

Refining NAM based inference for SLB

Bian, Y., Q. Yang, P. Balint-Kurit, R. J. Wisser, and J. Holland (2014) Limits on the reproducibility of marker associations with southern leaf blight resistance in the maize nested association mapping population. BMC Genomics 15:1068.

Overview on QTVs, not QTLs

Murray, S. C. and R. J. Wisser (2014) Genetic Inference on Quantitative Traits through Linkage and Association Studies. In R. Wusirika, M. Bohn, J. Lai, C. Kole (Eds.), Genetics, Genomics and Breeding of Maize (Chapter 3) Science Publishers, Inc, NH and CRC Press of Taylor and Francis Group, FL.

2013

Mutant-assisted GWAS of auto-induced HR

Olukolu, B. A., A. Negeri, R. Dhawan, B. P. Venkata, P. Sharma, A. Garg, E. Gachomo, S. Marla, K. Chu, A. Hasan, J. Ji, S. Chintamanani, J. Green, C. Shyu, R. Wisser, J. Holland, G. Johal, and P. Balint-Kurti (2013) A connected set of genes associated with programmed cell death implicated in controlling the hypersensitive response in maize. Genetics 193(2):609–620.

2012

Statistical modeling of quantitative resistance data

Veturi, Y., K. Kump, E. Walsh, O. Ott, J. Poland, J. M. Kolkman, P. J. Balint-Kurti, J. B. Holland, and R. J. Wisser (2012) Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing plant disease resistance. Phytopathology 102(11):1016–25

2011

Design for genetically dissecting responsive variation

Wisser, R. J., P. J. Balint-Kurti, and J. B. Holland (2011) A novel genetic framework for studying response to artificial selection. Plant Genetic Resources: Characterization and Utilization 9(2):281–283.

Multi-trait assocaition mapping: GST assocaited with MDR

Wisser, R. J., J. M. Kolkman, M. E. Patzoldt, J. B. Holland, J. Yu, M. Krakowsky, R. J. Nelson, and P. J. Balint-Kurti (2011) Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a glutathione S-transferase gene. Proc. Natl. Acad. Sci. U. S. A. 108(18):7339–7344.

Nested association mapping of resistance to SLB

Kump, K. L., P. J. Bradbury, R. J. Wisser, E. S. Buckler, A. R. Belcher, M. A. Oropeza-Rosas, J. C. Zwonitzer, S. Kresovich, M. D. McMullen, D. Ware, P. J. Balint-Kurti, and J. B. Holland (2011) Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nature Genetics 43:163–168.

*commentary: Haley, C. (2011) A cornucopia of maize genes. Nature Genetics 43:87–88.

2010
i

Basic intro to quantitative disease resistance

Wisser, R. J. (2010) Maize: Durable Resistance Breeding. In D. R. Heldman, D. G. Hoover, and M. B. Wheeler (Eds.), Encyclopedia of Biotechnology in Agriculture and Food (pp. 375–380) Taylor and Francis Group LLC, New York, NY.

2009

Hypothesized mechanisms of quantitative disease resistance

Poland, J. A., P. J. Balint-Kurti, R. J. Wisser, R. C. Pratt, and R. J. Nelson (2009) Shades of gray: the world of quantitative disease resistance. Trends in Plant Science 14:21–29.

2008

Selection mapping of resistance to NLB

Wisser, R. J., S. C. Murray, J. M. Kolkman, H. Ceballos, and R. J. Nelson (2008) Selection mapping of loci for quantitative disease resistance in a diverse maize population. Genetics 180:583–599.

AIL mapping of resistance to GLS

Balint-Kurti, P. J., R. Wisser, and J. C. Zwonitzer (2008) Use of an advanced intercross line population for precise mapping of quantitative trait loci for gray leaf spot resistance in maize. Crop Science 48:1696–1704.

2007

AIL mapping of resistance to SLB

Balint-Kurti, P. J., C. Zwonitzer, R. J. Wisser, M. Carson, M. A. Oropeza-Rosas, J. B. Holland, and S. J. Szalma (2007) Precise mapping of quantitative trait loci for resistance to southern leaf blight, caused by Cochliobolus heterostrophus race O, using an advanced intercross maize population. Genetics 176:645–657.

2006

Synthesis of disease resistance loci in maize

Wisser, R. J., P. J. Balint-Kurti, and R. J. Nelson (2006) The genetic architecture of disease resistance in maize: a synthesis of published studies. Phytopathology 96:120–129.

2005

Synthesis of disease resistance loci in rice

Wisser, R. J., Q. Sun, S. H. Hulbert, S. Kresovich, and R. J. Nelson (2005) Identification and characterization of regions of the rice genome associated with broad-spectrum, quantitative disease resistance. Genetics 169:2277–2293.

2004

Resistance gene homologues in rice

Monosi, B., R. J. Wisser, L. Pennill, and S. H. Hulbert (2004) Full-genome analysis of resistance gene homologues in rice. Theoretical and Applied Genetics 109:1434–1447.

Sources of variation in microarray data

Brown, J. S., D. Kuhn, R. Wisser, E. Power, and R. Schnell (2004) Quantification of sources of variation and accuracy of sequence discrimination in a replicated microarray experiment. BioTechniques 36:324–332.

2003

Resistance gene homologues in chocolate

Kuhn, D.N., Heath, M., R. J. Wisser, A. Meerow, J. S. Brown, U. Lopes, and R. J. Schnell (2003) Resistance gene homologues in Theobroma cacao as useful genetic markers. Theoretical and Applied Genetics 107:191–202.

Genetic diversity of coconut germplasm

Meerow, A. W., R. J. Wisser, S. J. Brown, D. N. Kuhn, R. J. Schnell, and T. K. Broschat (2003) Analysis of genetic diversity and population structure within Florida coconut (Cocos nucifera L.) germplasm using microsatellite DNA, with special emphasis on the Fiji Dwarf cultivar. Theoretical and Applied Genetics 106:715–726.

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