@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={AbstractThe geographical distribution of many crop species spans far beyond their centers of origin and the native range of their wild ancestors. Maize is exemplary of this adaptability, which has contributed to its agricultural...Understanding the evolutionary capacity of populations to adapt to novel environments is one of the major pursuits in genetics. Moreover, for plant breeding, maladaptation is the foremost barrier to capitalizing on intraspecific variation in order to develop new breeds for future climate scenarios in agriculture. Using a unique study design, we simultaneously dissected the population and quantitative genomic basis of short-term evolution in a tropical landrace of maize that was translocated to a temperate environment and phenotypically selected for adaptation in flowering time phenology. Underlying 10 generations of directional selection, which resulted in a 26-day mean decrease in female-flowering time, 60% of the heritable variation mapped to 14% of the genome, where, overall, alleles shifted in frequency beyond the boundaries of genetic drift in the expected direction given their flowering time effects. However, clustering these non-neutral alleles based on their profiles of frequency change revealed transient shifts underpinning a transition in genotype–phenotype relationships across generations. This was distinguished by initial reductions in the frequencies of few relatively large positive effect alleles and subsequent enrichment of many rare negative effect alleles, some of which appear to represent allelic series. With these genomic shifts, the population reached an adapted state while retaining 99% of the standing molecular marker variation in the founding population. Robust selection and association mapping tests highlighted several key genes driving the phenotypic response to selection. Our results reveal the evolutionary dynamics of a finite polygenic architecture conditioning a capacity for rapid environmental adaptation in maize.}, 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={AbstractSouthern Leaf Blight (SLB), Northern Leaf Blight (NLB), and Gray Leaf Spot (GLS) caused by Cochliobolus heterostrophus, Setosphaeria turcica, and Cercospora zeae-maydis respectively, are among the most important diseases of corn worldwide. Previously, moderately high and significantly positive genetic correlations between resistance levels to each of these diseases were identified in a panel of 253 diverse maize inbred lines. The goal of this study was to identify loci underlying disease resistance in some of the most multiple disease resistant (MDR) lines by the creation of chromosome segment substitution line (CSSL) populations in multiple disease susceptible (MDS) backgrounds. Four MDR lines (NC304, NC344, Ki3, NC262) were used as donor parents and two MDS lines (Oh7B, H100) were used as recurrent parents to produce eight BC3F4:5 CSSL populations comprising 1,611 lines in total. Each population was genotyped and assessed for each disease in replicated trials in two environments. Moderate to high heritabilities on an entry mean basis were observed (0.32 to 0.83). Several lines in each population were significantly more resistant than the MDS parental lines for each disease. Multiple quantitative trait loci (QTL) for disease resistance were detected for each disease in most of the populations. Seventeen QTL were associated with variation in resistance to more than one disease (SLB/NLB: 2; SLB/GLS: 7; NLB/GLS: 2 and 6 to all three diseases). For most populations and most disease combinations, significant correlations were observed between disease scores and also between marker effects for each disease. The number of lines that were resistant to more than one disease was significantly higher than would be expected by chance. Using the results from individual QTL analyses, a composite statistic based on Mahalanobis distance (Md) was used to identify joint marker associations with multiple diseases. Across all populations and diseases, 246 markers had significant Md values. However further analysis revealed that most of these associations were due to strong QTL effects on a single disease. Together, these findings reinforce our previous conclusions that loci associated with resistance to different diseases are clustered in the genome more often than would be expected by chance. Nevertheless true MDR loci which have significant effects on more than one disease are still much rarer than loci with single disease effects.}, 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
               Southern Leaf Blight, Northern Leaf Blight, and Gray Leaf Spot, caused by ascomycete fungi, are among the most important foliar diseases of maize worldwide. Previously, disease resistance quantitative trait loci (QTL) for all three diseases were identified in a connected set of chromosome segment substitution line (CSSL) populations designed for the identification of disease resistance QTL. Some QTL for different diseases co-localized, indicating the presence of multiple disease resistance (MDR) QTL. The goal of this study was to perform an independent test of several of the MDR QTL identified to confirm their existence and derive a more precise estimate of allele additive and dominance effects. Twelve F2:3 family populations were produced, in which selected QTL were segregating in an otherwise uniform genetic background. The populations were assessed for each of the three diseases in replicated trials and genotyped with markers previously associated with disease resistance. Pairwise phenotypic correlations across all the populations for resistance to the three diseases ranged from 0.2 to 0.3 and were all significant at the alpha level of 0.01. Of the 44 QTL tested, 16 were validated (identified at the same genomic location for the same disease or diseases) and several novel QTL/disease associations were found. Two MDR QTL were associated with resistance to all three diseases. This study identifies several potentially important MDR QTL and demonstrates the importance of independently evaluating QTL effects following their initial identification.}, 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} }