@article{guo_yu_li_zhang_zhu_flint-garcia_mcmullen_holland_szalma_wisser_et al._2019, title={Optimal Designs for Genomic Selection in Hybrid Crops}, volume={12}, ISSN={["1752-9867"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85061008767&partnerID=MN8TOARS}, DOI={10.1016/j.molp.2018.12.022}, abstractNote={Improved capacity of genomics and biotechnology has greatly enhanced genetic studies in different areas. Genomic selection exploits the genotype-to-phenotype relationship at the whole-genome level and is being implemented in many crops. Here we show that design-thinking and data-mining techniques can be leveraged to optimize genomic prediction of hybrid performance. We phenotyped a set of 276 maize hybrids generated by crossing founder inbreds of nested association mapping populations for flowering time, ear height, and grain yield. With 10 296 310 SNPs available from the parental inbreds, we explored the patterns of genomic relationships and phenotypic variation to establish training samples based on clustering, graphic network analysis, and genetic mating scheme. Our analysis showed that training set designs outperformed random sampling and earlier methods that either minimize the mean of prediction error variance or maximize the mean of generalized coefficient of determination. Additional analyses of 2556 wheat hybrids from an early-stage hybrid breeding system and 1439 rice hybrids from an established hybrid breeding system validated the approaches. Together, we demonstrated that effective genomic prediction models can be established with a training set 2%-13% of the size of the whole set, enabling an efficient exploration of enormous inference space of genetic combinations.}, number={3}, journal={MOLECULAR PLANT}, author={Guo, Tingting and Yu, Xiaoqing and Li, Xianran and Zhang, Haozhe and Zhu, Chengsong and Flint-Garcia, Sherry and McMullen, Michael D. and Holland, James B. and Szalma, Stephen J. and Wisser, Randall J. and et al.}, year={2019}, month={Mar}, pages={390–401} }
 @article{wisser_fang_holland_teixeira_dougherty_weldekidan_leon_flint-garcia_lauter_murray_et al._2019, title={The Genomic Basis for Short-Term Evolution of Environmental Adaptation in Maize}, volume={213}, ISSN={["1943-2631"]}, url={https://doi.org/10.1534/genetics.119.302780}, DOI={10.1534/genetics.119.302780}, abstractNote={Abstract}, number={4}, journal={GENETICS}, publisher={Genetics Society of America}, author={Wisser, Randall J. and Fang, Zhou and Holland, James B. and Teixeira, Juliana E. C. and Dougherty, John and Weldekidan, Teclemariam and Leon, Natalia and Flint-Garcia, Sherry and Lauter, Nick and Murray, Seth C. and et al.}, year={2019}, month={Dec}, pages={1479–1494} }
 @article{lopez-zuniga_wolters_davis_weldekidan_kolkman_nelson_hooda_rucker_thomason_wisser_et al._2019, title={Using Maize Chromosome Segment Substitution Line Populations for the Identification of Loci Associated with Multiple Disease Resistance}, volume={9}, ISSN={2160-1836}, url={http://dx.doi.org/10.1534/g3.118.200866}, DOI={10.1534/g3.118.200866}, abstractNote={Abstract}, number={1}, journal={G3 Genes|Genomes|Genetics}, publisher={Oxford University Press (OUP)}, author={Lopez-Zuniga, Luis O and Wolters, Petra and Davis, Scott and Weldekidan, Teclemariam and Kolkman, Judith M and Nelson, Rebecca and Hooda, K S and Rucker, Elizabeth and Thomason, Wade and Wisser, Randall and et al.}, year={2019}, month={Jan}, pages={189–201} }
 @article{martins_rucker_thomason_wisser_holland_balint-kurti_2019, title={Validation and Characterization of Maize Multiple Disease Resistance QTL}, volume={9}, ISSN={2160-1836}, url={http://dx.doi.org/10.1534/g3.119.400195}, DOI={10.1534/g3.119.400195}, abstractNote={Abstract}, number={9}, journal={G3 Genes|Genomes|Genetics}, publisher={Oxford University Press (OUP)}, author={Martins, Lais B and Rucker, Elizabeth and Thomason, Wade and Wisser, Randall J and Holland, James B and Balint-Kurti, Peter}, year={2019}, month={Sep}, pages={2905–2912} }
 @article{kump_bradbury_wisser_buckler_belcher_oropeza-rosas_zwonitzer_kresovich_mcmullen_ware_et al._2011, title={Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population}, volume={43}, ISSN={["1061-4036"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79251575784&partnerID=MN8TOARS}, DOI={10.1038/ng.747}, abstractNote={Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.}, number={2}, journal={NATURE GENETICS}, publisher={Nature Publishing Group}, author={Kump, Kristen L. and Bradbury, Peter J. and Wisser, Randall J. and Buckler, Edward S. and Belcher, Araby R. and Oropeza-Rosas, Marco A. and Zwonitzer, John C. and Kresovich, Stephen and McMullen, Michael D. and Ware, Doreen and et al.}, year={2011}, month={Feb}, pages={163–U120} }
 @article{wisser_kolkman_patzoldt_holland_yu_krakowsky_nelson_balint-kurti_2011, title={Multivariate analysis of maize disease resistances suggests a pleiotropic genetic basis and implicates a GST gene}, volume={108}, ISSN={["0027-8424"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-79956318799&partnerID=MN8TOARS}, DOI={10.1073/pnas.1011739108}, abstractNote={
            Plants are attacked by pathogens representing diverse taxonomic groups, such that genes providing multiple disease resistance (MDR) are expected to be under positive selection pressure. To address the hypothesis that naturally occurring allelic variation conditions MDR, we extended the framework of structured association mapping to allow for the analysis of correlated complex traits and the identification of pleiotropic genes. The multivariate analytical approach used here is directly applicable to any species and set of traits exhibiting correlation. From our analysis of a diverse panel of maize inbred lines, we discovered high positive genetic correlations between resistances to three globally threatening fungal diseases. The maize panel studied exhibits rapidly decaying linkage disequilibrium that generally occurs within 1 or 2 kb, which is less than the average length of a maize gene. The positive correlations therefore suggested that functional allelic variation at specific genes for MDR exists in maize. Using a multivariate test statistic, a glutathione
            S
            -transferase (
            GST
            ) gene was found to be associated with modest levels of resistance to all three diseases. Resequencing analysis pinpointed the association to a histidine (basic amino acid) for aspartic acid (acidic amino acid) substitution in the encoded protein domain that defines GST substrate specificity and biochemical activity. The known functions of GSTs suggested that variability in detoxification pathways underlie natural variation in maize MDR.
          }, number={18}, journal={PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}, author={Wisser, Randall J. and Kolkman, Judith M. and Patzoldt, Megan E. and Holland, James B. and Yu, Jianming and Krakowsky, Matthew and Nelson, Rebecca J. and Balint-Kurti, Peter J.}, year={2011}, month={May}, pages={7339–7344} }
 @misc{poland_balint-kurti_wisser_pratt_nelson_2009, title={Shades of gray: the world of quantitative disease resistance}, volume={14}, ISSN={["1878-4372"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-58149490801&partnerID=MN8TOARS}, DOI={10.1016/j.tplants.2008.10.006}, abstractNote={A thorough understanding of quantitative disease resistance (QDR) would contribute to the design and deployment of durably resistant crop cultivars. However, the molecular mechanisms that control QDR remain poorly understood, largely due to the incomplete and inconsistent nature of the resistance phenotype, which is usually conditioned by many loci of small effect. Here, we discuss recent advances in research on QDR. Based on inferences from analyses of the defense response and from the few isolated QDR genes, we suggest several plausible hypotheses for a range of mechanisms underlying QDR. We propose that a new generation of genetic resources, complemented by careful phenotypic analysis, will produce a deeper understanding of plant defense and more effective utilization of natural resistance alleles. A thorough understanding of quantitative disease resistance (QDR) would contribute to the design and deployment of durably resistant crop cultivars. However, the molecular mechanisms that control QDR remain poorly understood, largely due to the incomplete and inconsistent nature of the resistance phenotype, which is usually conditioned by many loci of small effect. Here, we discuss recent advances in research on QDR. Based on inferences from analyses of the defense response and from the few isolated QDR genes, we suggest several plausible hypotheses for a range of mechanisms underlying QDR. We propose that a new generation of genetic resources, complemented by careful phenotypic analysis, will produce a deeper understanding of plant defense and more effective utilization of natural resistance alleles. a host–pathogen interaction that results in disease (the host is susceptible). a resistance gene that has become ineffective. a host–pathogen interaction that does not result in disease (the host is resistant). two amino acid sequence motifs commonly found in resistance genes. inbred lines that differ at only a small genomic region. the combination of a specific host species and pathogen species. proteins that identify molecules, such as flagellin or chitin components, that are associated with microbial pathogens. resistance that is expressed as a reduction in disease, rather than as the absence of disease. a locus with an effect on QDR. a locus with an effect on a quantitative trait (i.e. a trait showing continuous variation). an inbred line produced from an initial cross followed by continuous inbreeding; populations of RILs are often used for QTL-mapping studies. the phenomenon of a resistant cultivar becoming susceptible owing to changes in the pathogen race. putative genes that share sequence similarity with known R-genes. the phenomenon of a resistance gene becoming ineffective in a crop variety.}, number={1}, journal={TRENDS IN PLANT SCIENCE}, publisher={Elsevier BV}, author={Poland, Jesse A. and Balint-Kurti, Peter J. and Wisser, Randall J. and Pratt, Richard C. and Nelson, Rebecca J.}, year={2009}, month={Jan}, pages={21–29} }
 @article{balint-kurti_wisser_zwonitzer_2008, title={Use of an advanced intercross line population for precise mapping of quantitative trait loci for gray leaf spot resistance in maize}, volume={48}, ISSN={["1435-0653"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-54949084231&partnerID=MN8TOARS}, DOI={10.2135/cropsci2007.12.0679}, abstractNote={Gray leaf spot [GLS, causal agent Cercospora zeae‐maydis (Tehon and E. Y. Daniels)] is an important fungal disease of maize in the U.S. and worldwide. The IBM population, an advanced intercross recombinant inbred line population derived from a cross between the maize lines Mo17 (resistant) and B73 (susceptible), was evaluated in three environments (Andrews, NC in 2005, 2006, and 2007) for resistance to GLS and for days from planting to anthesis (DTA). A conventional recombinant inbred line population derived from the same two parents (the “Stuber” population) was also assessed for GLS resistance in two environments (Andrews NC, 2004 and 2005). Quantitative trait loci (QTL) for GLS resistance were detected in each population. Five significant QTL were detected in the IBM population in bins 1.05, 2.04, 4.05, 9.03, and 9.05. In each case the QTL were localized to regions less than 3 centiMorgans (cM). Two QTL for GLS resistance were identified in the Stuber population in bins 2.04 and 7.05. The GLS QTL in bin 2.04 was previously identified as a QTL for southern leaf blight resistance in the IBM population. These results were compared with results from five previous GLS QTL studies and two potential GLS QTL “hotspots” were identified in bins 1.05–1.06 and 2.03–2.05. As expected, QTL were identified with much more precision in the IBM population compared to the Stuber population and to previous studies. There was no significant correlation between disease resistance and days to anthesis. Three DTA QTL were detected in bins 4.09, 8.05, and 9.02, which did not co‐localize with GLS QTL.}, number={5}, journal={CROP SCIENCE}, publisher={Crop Science Society of America}, author={Balint-Kurti, Peter J. and Wisser, Randall and Zwonitzer, John C.}, year={2008}, pages={1696–1704} }