@article{uhdre_coyne_bourland_piaskowski_zheng_ganjyal_zhang_mcgee_main_bandillo_et al._2024, title={Association study of crude seed protein and fat concentration in a USDA pea diversity panel}, url={https://doi.org/10.1002/tpg2.20485}, DOI={10.1002/tpg2.20485}, abstractNote={Abstract Pea ( Pisum sativum L.) is a key rotational crop and is increasingly important in the food processing sector for its protein. This study focused on identifying diverse high seed protein concentration (SPC) lines in pea plant genetic resources. Objectives included identifying high‐protein pea lines, exploring genetic architecture across environments, pinpointing genes and metabolic pathways associated with high protein, and documenting information for single nucleotide polymorphism (SNP)‐based marker‐assisted selection. From 2019 to 2021, a 487‐accession pea diversity panel, More protein, More pea, More profit, was evaluated in a randomized complete block design. DNA was extracted for genomic analysis via genotype‐by‐sequencing. Phenotypic analysis included protein and fat measurements in seeds and flower color. Genome‐wide association study (GWAS) used multiple models, and the Pathways Association Study Tool was used for metabolic pathway analysis. Significant associations were found between SNPs and pea seed protein and fat concentration. Gene Psat7g216440 on chromosome 7, which targets proteins to cellular destinations, including seed storage proteins, was identified as associated with SPC. Genes Psat4g009200 , Psat1g199800 , Psat1g199960 , and Psat1g033960 , all involved in lipid metabolism, were associated with fat concentration. GWAS also identified genes annotated for storage proteins associated with fat concentration, indicating a complex relationship between fat and protein. Metabolic pathway analysis identified 20 pathways related to fat and seven to protein concentration, involving fatty acids, amino acid and protein metabolism, and the tricarboxylic acid cycle. These findings will assist in breeding of high‐protein, diverse pea cultivars, and SNPs that can be converted to breeder‐friendly molecular marker assays are identified for genes associated with high protein.}, journal={The Plant Genome}, author={Uhdre, Renan and Coyne, Clarice J. and Bourland, Britton and Piaskowski, Julia and Zheng, Ping and Ganjyal, Girish M. and Zhang, Zhiwu and McGee, Rebecca J. and Main, Dorrie and Bandillo, Nonoy and et al.}, year={2024}, month={Jul} }
 @article{saludares_atanda_piche_worral_dariva_mcphee_bandillo_2024, title={Multi-trait multi-environment genomic prediction of preliminary yield trial in pulse crop}, volume={8}, ISSN={["1940-3372"]}, url={https://doi.org/10.1002/tpg2.20496}, DOI={10.1002/tpg2.20496}, abstractNote={Abstract Phenotypic selection of complex traits such as seed yield and protein in the preliminary yield trial (PYT) is often constrained by limited seed availability, resulting in trials with few environments and minimal to no replications. Multi‐trait multi‐environment enabled genomic prediction (MTME‐GP) offers a valuable alternative to predict missing phenotypes of selection candidates for multiple traits and diverse environments. In this study, we assessed the efficiency of MTME‐GP for improving seed protein and seed yield in field pea, the top two breeding targets but highly antagonistic traits in pulse crop. We utilized a set of 300 selection candidates in the PYT that virtually represented all possible families of the North Dakota State University field pea breeding program. Selection candidates were evaluated in three diverse, contrasting environments, as indicated by a range of heritability. Using whole‐ and split‐environment cross validation schemes, MTME‐GP had higher predictive ability than a standard additive G‐BLUP model. Integrating a range of overlapping genotypes in between environments showed improvement on the predictive ability of the MTME‐GP model but tends to plateau at 50%–80% training set size. Regardless of the cross‐validation scheme, accuracy was among the lowest in stressed environments, presumably due to low heritability for seed protein and yield. This study provided insights into the potential of MTME‐GP in a public pulse crop breeding program. The MTME‐GP framework can be further improved with more testing environments and integration of additional orthogonal information in the early stages of the breeding pipeline.}, journal={PLANT GENOME}, author={Saludares, Rica Amor and Atanda, Sikiru Adeniyi and Piche, Lisa and Worral, Hannah and Dariva, Francoise and McPhee, Kevin and Bandillo, Nonoy}, year={2024}, month={Aug} }
 @article{saludares_atanda_piche_worral_dariva_mcphee_bandillo_2024, title={Multi-trait multi-environment genomic prediction of preliminary yield trials in pulse crops}, url={https://doi.org/10.1101/2024.02.18.580909}, DOI={10.1101/2024.02.18.580909}, abstractNote={ABSTRACT Phenotypic selection in preliminary yield trials (PYT) is challenged by limited seeds, resulting in trials with few replications and environments. The emergence of multi-trait multi-environment enabled genomic prediction (MTME-GP) offers opportunity for enhancing prediction accuracy and genetic gain across multiple traits and diverse environments. Using a set of 300 advanced breeding lines in the North Dakota State University (NDSU) pulse crop breeding program, we assessed the efficiency of a MTME-GP model for improving seed yield and protein content in field peas in stress and non-stress environments. MTME-GP significantly improved predictive ability, improving up to 2.5-fold, particularly when a significant number of genotypes overlapped across environments. Heritability of the training environments contributed significantly to the overall prediction of the model. Average predictive ability ranged from 3 to 7-folds when environments with low heritability were excluded from the training set. Overall, the Reproducing Kernel Hilbert Spaces (RKHS) model consistently resulted in improved predictive ability across all breeding scenarios considered in our study. Our results lay the groundwork for further exploration, including integration of diverse traits, incorporation of deep learning techniques, and the utilization of multi-omics data in predictive modeling. Core ideas Phenotypic selection in PYT is challenged by limited seeds, resulting to few replications and environments. MTME-GP offers opportunity for enhancing prediction accuracy of multi-trait and diverse environments in PYT. MTME-GP enhances prediction by up to 2.5-fold, especially with numerous overlapping genotypes in various tested environments. RKHS MTME-GP models, excels in low-heritability, negatively correlated traits, like drought-affected conditions.}, author={Saludares, Rica Amor and Atanda, Sikiru Adeniyi and Piche, Lisa and Worral, Hannah and Dariva, Francoise and McPhee, Kevin and Bandillo, Nonoy}, year={2024}, month={Feb} }
 @article{bandillo_worral_forster_stefaniak_piche_ross_jain_pasche_kalil_wunsch_et al._2023, title={Registration of ‘ND Victory’ green field pea}, url={https://doi.org/10.1002/plr2.20266}, DOI={10.1002/plr2.20266}, abstractNote={Abstract ‘ND Victory’ (Reg. no. CV‐31, PI 701908) is the first semi‐leafless, green cotyledon field pea cultivar ( Pisum sativum L.) developed by the North Dakota State University Pulse Crops Breeding Program and approved for release by the North Dakota Agricultural Experiment Station. It has white flowers, opaque seed coat, and smooth, round seed. It is semi‐dwarf, with lodging score of 3.3/9 and canopy height of 57 cm. Based on 30 environments (location‐year) of replicated yield trials in North Dakota, seed yield of ND Victory (2847 kg ha −1 ) was similar to commercial cultivar ‘CDC Striker’ (2819 kg ha −1 ) but significantly greater than ‘Cruiser’ (2653 kg ha −1 ) and ‘Aragorn’ (2639 kg ha −1 ) by 7.3 and 7.9%, respectively. ND Victory was also tested across 14 environments in Montana, where it had an average seed yield of 3264 kg ha −1 , which was similar to ‘Hampton’ (3355 kg ha −1 ) but significantly greater than Aragorn (3110 kg ha −1 ) by 4.9%. ND Victory matures in approximately 90 days. ND Victory is a high protein cultivar, with protein content of 25.2%, exceeding the premium protein threshold of 24%. ND Victory (20%) is resistant to powdery mildew and performed similarly with resistant check ‘Spider’ (15%) and had significantly lower disease severity than ‘Salamanca’ (97%, susceptible check) and CDC Striker (82%). In irrigated field trials conducted under high Ascochyta blight pressure, ND Victory (5%) had lower disease severity than ‘AC Agassiz’ (10%) and CDC Striker (14%). ND Victory and CDC Striker exhibited similar response but significantly lower severity than AC Agassiz to Fusarium root rot inoculated with multiple Fusarium species pathogenic to pea.}, journal={Journal of Plant Registrations}, author={Bandillo, Nonoy and Worral, Hannah and Forster, Shana M. and Stefaniak, Thomas and Piche, Lisa and Ross, Andrew and Jain, Shalu and Pasche, Julie S. and Kalil, Audrey and Wunsch, Michael and et al.}, year={2023}, month={May} }
 @article{bandillo_jarquin_posadas_lorenz_graef_2023, title={Genomic selection performs as effectively as phenotypic selection for increasing seed yield in soybean}, url={https://doi.org/10.1002/tpg2.20285}, DOI={10.1002/tpg2.20285}, abstractNote={Increasing the rate of genetic gain for seed yield remains the primary breeding objective in both public and private soybean [Glycine max (L.) Merr.] breeding programs. Genomic selection (GS) has the potential to accelerate the rate of genetic gain for soybean seed yield. Limited studies to date have validated GS accuracy and directly compared GS with phenotypic selection (PS), and none have been reported in soybean. This study conducted the first empirical validation of GS for increasing seed yield using over 1,500 lines and over 7 yr (2010-2016) of replicated experiments in the University of Nebraska-Lincoln soybean breeding program. The study was designed to capture the varying genetic relatedness of the training population to three validation sets: two large biparental populations (TBP-1 and TBP-2) and a large validation set comprised of 457 preselected advanced lines derived from 45 biparental populations (TMP). We found that prediction accuracy (.54) realized in our validation experiments was comparable with what we obtained from a series of cross-validation experiments (.64). Both GS and PS were more effective for increasing the population mean performance compared with random selection (RS). We found a selection advantage of GS over PS, where higher genetic gain and identification of top-performing lines was maximized at 10-20% selected proportion. Genomic selection led to small increases in genetic similarity when compared with PS and RS presumably because of a significant shift on allelic frequencies toward the extremes, suggesting that it could erode genetic diversity more quickly. Overall, we found that GS can perform as effectively as PS but that measures should be considered to protect against loss of genetic variance when using GS.}, journal={The Plant Genome}, author={Bandillo, Nonoy B. and Jarquin, Diego and Posadas, Luis G. and Lorenz, Aaron J. and Graef, George L.}, year={2023}, month={Mar} }
 @article{pignon_fernandes_valluru_bandillo_lozano_buckler_gore_long_brown_leakey_2021, title={Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes}, url={https://doi.org/10.1101/2021.05.06.442962}, DOI={10.1101/2021.05.06.442962}, abstractNote={Abstract Stomata allow CO 2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO 2 and water fluxes and are essential to maintenance of water-use efficiency (WUE). However, little is known about the genetic basis for natural variation in stomatal movement, especially in C 4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. High-throughput thermal imaging was used to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance ( g s ) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum accessions. Results from thermal imaging significantly correlated with photosynthetic gas-exchange measurements. g s traits varied substantially across the population and were moderately heritable ( h 2 up to 0.72). An integrated genome-wide and transcriptome-wide association study (GWAS/TWAS) identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with greatest confidence, 77 were orthologs of Arabidopsis genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C 4 grass for bioenergy, food, and forage production. One sentence summary Rapid phenotyping of 659 accessions of Sorghum bicolor revealed heritable stomatal responses to a decrease in light. GWAS/TWAS was used to identify candidate genes influencing traits important to WUE.}, author={Pignon, Charles P. and Fernandes, Samuel B. and Valluru, Ravi and Bandillo, Nonoy and Lozano, Roberto and Buckler, Edward and Gore, Michael A. and Long, Stephen P. and Brown, Patrick J. and Leakey, Andrew D. B.}, year={2021}, month={May} }
 @article{pignon_fernandes_valluru_bandillo_lozano_buckler_gore_long_brown_leakey_2021, title={Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes}, volume={8}, url={https://doi.org/10.1093/plphys/kiab395}, DOI={10.1093/plphys/kiab395}, abstractNote={Abstract Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.}, journal={Plant Physiology}, publisher={Oxford University Press (OUP)}, author={Pignon, Charles P and Fernandes, Samuel B and Valluru, Ravi and Bandillo, Nonoy and Lozano, Roberto and Buckler, Edward and Gore, Michael A and Long, Stephen P and Brown, Patrick J and Leakey, Andrew D B}, year={2021}, month={Dec} }
 @article{chang_lan_bandillo_ohm_chen_rao_2022, title={Plant proteins from green pea and chickpea: Extraction, fractionation, structural characterization and functional properties}, url={https://doi.org/10.1016/j.foodhyd.2021.107165}, DOI={10.1016/j.foodhyd.2021.107165}, journal={Food Hydrocolloids}, author={Chang, Liuyi and Lan, Yang and Bandillo, Nonoy and Ohm, Jae-Bom and Chen, Bingcan and Rao, Jiajia}, year={2022}, month={Feb} }
 @article{bandillo_stefaniak_worral_mihov_ostlie_schatz_rickertsen_wahlstrom_ramsey_dragseth_et al._2021, title={Registration of ‘ND Crown’ chickpea}, volume={15}, url={https://doi.org/10.1002/plr2.20122}, DOI={10.1002/plr2.20122}, abstractNote={Abstract ‘ND Crown’ (Reg. no. CV‐342, PI 694865), a large‐seeded kabuli chickpea ( Cicer arietinum L.), was developed by the North Dakota State University Pulse Crops Breeding Program and approved for release by the North Dakota Agricultural Experiment Station. ND Crown, the first chickpea cultivar from the program, was selected specifically for adaptation to North Dakota growing conditions on the basis of its high yield potential, medium maturity, large seed size, and moderate resistance to Ascochyta blight. Based on 21 environments (location‐years) of yield trials across North Dakota and Montana, ND Crown had an average yield (2,152 kg ha −1 ) that was similar to the commercial chickpea cultivars ‘CDC Frontier’ (2,248 kg ha −1 ) and ‘CDC Orion’ (2,108 kg ha −1 ) but significantly greater than ‘Sierra’ (1,262 kg ha −1 ). ND Crown was moderately resistant to Ascochyta blight, with similar reaction as CDC Frontier and CDC Orion under moderate disease pressure. Under high disease pressure, ND Crown displayed significantly lower Ascochyta blight severity than CDC Frontier and CDC Orion. ND Crown exhibited an upright indeterminate growth habit and resistance to lodging. ND Crown had a greater percentage of large seeds (>8 mm) and higher 1,000‐seed weight than CDC Frontier but was similar to CDC Orion. As a high‐yielding large‐seeded chickpea cultivar, ND Crown is a promising alternative to CDC Frontier and CDC Orion in North Dakota and nearby states.}, number={2}, journal={Journal of Plant Registrations}, publisher={Wiley}, author={Bandillo, Nonoy and Stefaniak, Thomas and Worral, Hannah and Mihov, Miho and Ostlie, Michael and Schatz, Blaine and Rickertsen, John and Wahlstrom, Cameron and Ramsey, Meredith and Dragseth, Kyle and et al.}, year={2021}, month={May}, pages={278–284} }
 @article{bandillo_stefaniak_worral_jain_ostlie_schatz_rickertsen_wahlstrom_miller_dragseth_et al._2021, title={Registration of ‘ND Dawn’ large yellow pea}, url={https://doi.org/10.1002/plr2.20097}, DOI={10.1002/plr2.20097}, abstractNote={Abstract ‘ND Dawn’ (Reg. no. CV‐30, PI 694866), a semi‐dwarf, semi‐leafless, large‐seeded yellow field pea ( Pisum sativum L.) cultivar, was developed by the pulse crops breeding program at North Dakota State University and approved for release by the North Dakota Agricultural Experiment Station. ND Dawn, the first yellow field pea cultivar from the program, was developed by the bulk‐pedigree method. Based on 18 environments (location‐years) of yield trials across North Dakota, ND Dawn had similar seed yield (2,843 kg ha −1 ) with the commercial yellow pea cultivars ‘AC Agassiz’ (2,875 kg ha −1 ) and ‘DS Admiral’ (2,799 kg ha −1 ) but significantly greater than ‘CDC Golden’ (2,633 kg ha −1 ). ND Dawn was also tested across eight environments in Montana, where it had an average seed yield of 3,803 kg ha −1 , which was significantly greater than ‘Delta’ (3,554 kg ha −1 ) but similar to DS Admiral (3,686 kg ha −1 ) or AC Agassiz (3,565 kg ha −1 ). ND Dawn matures in approximately 94 d. It is resistant to lodging, with a plant height index of 0.66. It has uniform round seed, with size larger than Agassiz, a medium‐seeded yellow pea cultivar. ND Dawn's protein content, 24%, is acceptable to get a premium price in the current market for high‐protein pea. ND Dawn and AC Agassiz exhibited similar responses to Fusarium root rot based on a field trial inoculated with multiple Fusarium species pathogenic to pea . In an irrigated field trial conducted under high Ascochyta blight pressure, ND Dawn yielded similarly to AC Agassiz and ‘CDC Striker’ despite having a higher leaf necrosis percentage. Other agronomic traits of ND Dawn are within market acceptable ranges.}, journal={Journal of Plant Registrations}, author={Bandillo, Nonoy and Stefaniak, Thomas and Worral, Hannah and Jain, Shalu and Ostlie, Michael and Schatz, Blaine and Rickertsen, John and Wahlstrom, Cameron and Miller, Meridith and Dragseth, Kyle and et al.}, year={2021}, month={Jan} }
 @article{lozano_gazave_santos_stetter_valluru_bandillo_fernandes_brown_shakoor_mockler_et al._2019, title={Comparative evolutionary analysis and prediction of deleterious mutation patterns between sorghum and maize}, volume={9}, url={https://doi.org/10.1101/777623}, DOI={10.1101/777623}, abstractNote={Abstract Sorghum and maize share a close evolutionary history that can be explored through comparative genomics. To perform a large-scale comparison of the genomic variation between these two species, we analyzed 13 million variants identified from whole genome resequencing of 468 sorghum lines together with 25 million variants previously identified in 1,218 maize lines. Deleterious mutations in both species were prevalent in pericentromeric regions, enriched in non-syntenic genes, and present at low allele frequencies. A comparison of deleterious burden between sorghum and maize revealed that sorghum, in contrast to maize, departed from the “domestication cost” hypothesis that predicts a higher deleterious burden among domesticates compared to wild lines. Additionally, sorghum and maize population genetic summary statistics were used to predict a gene deleterious index with an accuracy higher than 0.5. This research represents a key step towards understanding the evolutionary dynamics of deleterious variants in sorghum and provides a comparative genomics framework to start prioritizing them for removal through genome editing and breeding.}, publisher={Cold Spring Harbor Laboratory}, author={Lozano, Roberto and Gazave, Elodie and Santos, Jhonathan P.R. and Stetter, Markus and Valluru, Ravi and Bandillo, Nonoy and Fernandes, Samuel B. and Brown, Patrick J. and Shakoor, Nadia and Mockler, Todd C. and et al.}, year={2019}, month={Sep} }
 @article{valluru_gazave_fernandes_ferguson_lozano_hirannaiah_zuo_brown_leakey_gore_et al._2019, title={Deleterious mutation burden and its association with complex traits in sorghum (Sorghum bicolor)}, volume={211}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85062600765&partnerID=MN8TOARS}, DOI={10.1534/genetics.118.301742}, abstractNote={Sorghum (Sorghum bicolor L.) is a major food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. The lack of recombination, drift, and the coupling with favorable loci impede the removal of deleterious mutations from the genome by selection. To study how deleterious variants impact phenotypes, we identified putative deleterious mutations among ∼5.5 M segregating variants of 229 diverse biomass sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that ∼33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups. Across racial groups, the mutation burden correlated negatively with biomass, plant height, specific leaf area (SLA), and tissue starch content (TSC), suggesting that deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly one-half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (average of 3.1% across all stages). There is no advantage in total heritable variance for SLA and TSC. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, these results suggest that incorporating putatively deleterious variants into genomic models slightly improves prediction accuracy because of extensive linkage. Knowledge of deleterious variants could be leveraged for sorghum breeding through either genome editing and/or conventional breeding that focuses on the selection of progeny with fewer deleterious alleles.}, number={3}, journal={Genetics}, author={Valluru, R. and Gazave, E.E. and Fernandes, S.B. and Ferguson, J.N. and Lozano, R. and Hirannaiah, P. and Zuo, T. and Brown, P.J. and Leakey, A.D.B. and Gore, M.A. and et al.}, year={2019}, pages={1075–1087} }
 @article{zhou_kremling_bandillo_richter_zhang_ahern_artyukhin_hui_younkin_schroeder_et al._2019, title={Metabolome-scale genome-wideassociation studies reveal chemical diversity and genetic control of maize specialized metabolites}, volume={31}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85066163571&partnerID=MN8TOARS}, DOI={10.1105/tpc.18.00772}, abstractNote={Cultivated maize (Zea mays) has retained much of the genetic diversity of its wild ancestors. Here, we performed nontargeted liquid chromatography-mass spectrometry metabolomics to analyze the metabolomes of the 282 maize inbred lines in the Goodman Diversity Panel. This analysis identified a bimodal distribution of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated by flavonoid abundance, maize varieties (stiff-stalk, nonstiff-stalk, tropical, sweet maize, and popcorn) showed differential accumulation of benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often structurally related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS data set constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.}, number={5}, journal={Plant Cell}, publisher={American Society of Plant Biologists (ASPB)}, author={Zhou, Shaoqun and Kremling, Karl A. and Bandillo, Nonoy and Richter, Annett and Zhang, Ying K. and Ahern, Kevin R. and Artyukhin, Alexander B. and Hui, Joshua X. and Younkin, Gordon C. and Schroeder, Frank C. and et al.}, year={2019}, pages={937–955} }
 @article{kremling_diepenbrock_gore_buckler_bandillo_2019, title={Transcriptome-Wide Association Supplements Genome-Wide Association in Zea mays}, volume={9}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85071786128&partnerID=MN8TOARS}, DOI={10.1534/g3.119.400549}, abstractNote={Abstract Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The usefulness of endophenotypes for delineating the regulatory landscape of the genome and genetic dissection of complex trait variation remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299-genotype and seven-tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation acts through altered transcript abundance for maize kernel traits, including 30 grain carotenoid abundance traits, 20 grain tocochromanol abundance traits, and 22 field-measured agronomic traits. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the largely independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits than the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This not only improves the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants.}, number={9}, journal={G3 (Bethesda, Md.)}, publisher={Oxford University Press (OUP)}, author={Kremling, Karl A G and Diepenbrock, Christine H and Gore, Michael A and Buckler, Edward S and Bandillo, Nonoy B}, year={2019}, pages={3023–3033} }
 @article{valluru_gazave_fernandes_ferguson_lozano_hirannaiah_zuo_brown_leakey_gore_et al._2018, title={Leveraging mutational burden for complex trait prediction in sorghum}, url={http://europepmc.org/abstract/PPR/PPR8133}, DOI={10.1101/357418}, abstractNote={ABSTRACT Sorghum ( Sorghum bicolor (L.) Moench) is a major staple food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. Though selection keeps deleterious mutations rare, their complete removal from the genome is impeded due to lack of recombination, drift, and their coupling with favorable loci. To study how deleterious mutations impact agronomic phenotypes, we identified putative deleterious mutations among ~5.5M segregating variants of 229 diverse sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that about 33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups; the caudatum shows higher mutation burden while the guinea has lower burden. Across racial groups, the mutation burden correlated negatively with biomass, plant height, Specific Leaf Area (SLA), and tissue starch content, suggesting deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (5.2%). There is no advantage in total heritable variance for SLA and starch. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, our results suggest that including putatively deleterious variants in models do not significantly improve breeding accuracy because of extensive linkage. However, knowledge of deleterious variants could be leveraged for sorghum breeding through genome editing.}, author={Valluru, R and Gazave, EE and Fernandes, SB and Ferguson, JN and Lozano, R and Hirannaiah, P and Zuo, T and Brown, PJ and Leakey, AD and Gore, MA and et al.}, year={2018}, month={Jun} }
 @article{shaoqun_kremling_nonoy_annett_zhang_ahern_artyukhin_hui_schroeder_buckler_et al._2018, title={Metabolome-scale genome-wide association studies reveal chemical diversity and genetic control of maize specialized metabolites}, url={http://europepmc.org/abstract/PPR/PPR59409}, DOI={10.1101/450338}, abstractNote={One Sentence Summary HPLC-MS metabolite profiling of maize seedlings, in combination with genome-wide association studies, identifies numerous quantitative trait loci that influence the accumulation of foliar metabolites. Abstract Cultivated maize ( Zea mays ) retains much of the genetic and metabolic diversity of its wild ancestors. Non-targeted HPLC-MS metabolomics using a diverse panel of 264 maize inbred lines identified a bimodal distribution in the prevalence of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated primarily by flavonoid abundance, maize varieties (stiff-stalk, non-stiff-stalk, tropical, sweet corn, and popcorn) were differentiated predominantly by benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often metabolically related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS dataset constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.}, author={Shaoqun, Z and Kremling, KA and Nonoy, B and Annett, R and Zhang, YK and Ahern, KR and Artyukhin, AB and Hui, JX and Schroeder, FC and Buckler, ES and et al.}, year={2018}, month={Oct} }
 @article{kremling_diepenbrock_gore_buckler_bandillo_2018, title={Transcriptome-wide association supplements genome-wide association in Zea mays}, url={http://europepmc.org/abstract/PPR/PPR7538}, DOI={10.1101/363242}, abstractNote={Abstract Modern improvement of complex traits in agricultural species relies on successful associations of heritable molecular variation with observable phenotypes. Historically, this pursuit has primarily been based on easily measurable genetic markers. The recent advent of new technologies allows assaying and quantifying biological intermediates (hereafter endophenotypes) which are now readily measurable at a large scale across diverse individuals. The potential of using endophenotypes for dissecting traits of interest remains underexplored in plants. The work presented here illustrated the utility of a large-scale (299 genotype and 7 tissue) gene expression resource to dissect traits across multiple levels of biological organization. Using single-tissue- and multi-tissue-based transcriptome-wide association studies (TWAS), we revealed that about half of the functional variation for agronomic and seed quality (carotenoid, tocochromanol) traits is regulatory. Comparing the efficacy of TWAS with genome-wide association studies (GWAS) and an ensemble approach that combines both GWAS and TWAS, we demonstrated that results of TWAS in combination with GWAS increase the power to detect known genes and aid in prioritizing likely causal genes. Using a variance partitioning approach in the independent maize Nested Association Mapping (NAM) population, we also showed that the most strongly associated genes identified by combining GWAS and TWAS explain more heritable variance for a majority of traits, beating the heritability captured by the random genes and the genes identified by GWAS or TWAS alone. This improves not only the ability to link genes to phenotypes, but also highlights the phenotypic consequences of regulatory variation in plants. Author summary We examined the ability to associate variability in gene expression directly with terminal phenotypes of interest, as a supplement linking genotype to phenotype. We found that transcriptome-wide association studies (TWAS) are a useful accessory to genome-wide association studies (GWAS). In a combined test with GWAS results, TWAS improves the capacity to re-detect genes known to underlie quantitative trait loci for kernel and agronomic phenotypes. This improves not only the capacity to link genes to phenotypes, but also illustrates the widespread importance of regulation for phenotype.}, author={Kremling, KAG and Diepenbrock, CH and Gore, MA and Buckler, ES and Bandillo, NB}, year={2018}, month={Jul} }
 @article{campbell_bandillo_al shiblawi_sharma_liu_du_schmitz_zhang_véry_lorenz_et al._2017, title={Allelic variants of OsHKT1;1 underlie the divergence between indica and japonica subspecies of rice (Oryza sativa) for root sodium content}, volume={13}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85021833956&partnerID=MN8TOARS}, DOI={10.1371/journal.pgen.1006823}, abstractNote={Salinity is a major factor limiting crop productivity. Rice (Oryza sativa), a staple crop for the majority of the world, is highly sensitive to salinity stress. To discover novel sources of genetic variation for salt tolerance-related traits in rice, we screened 390 diverse accessions under 14 days of moderate (9 dS·m-1) salinity. In this study, shoot growth responses to moderate levels of salinity were independent of tissue Na+ content. A significant difference in root Na+ content was observed between the major subpopulations of rice, with indica accessions displaying higher root Na+ and japonica accessions exhibiting lower root Na+ content. The genetic basis of the observed variation in phenotypes was elucidated through genome-wide association (GWA). The strongest associations were identified for root Na+:K+ ratio and root Na+ content in a region spanning ~575 Kb on chromosome 4, named Root Na+ Content 4 (RNC4). Two Na+ transporters, HKT1;1 and HKT1;4 were identified as candidates for RNC4. Reduced expression of both HKT1;1 and HKT1;4 through RNA interference indicated that HKT1;1 regulates shoot and root Na+ content, and is likely the causal gene underlying RNC4. Three non-synonymous mutations within HKT1;1 were present at higher frequency in the indica subpopulation. When expressed in Xenopus oocytes the indica-predominant isoform exhibited higher inward (negative) currents and a less negative voltage threshold of inward rectifying current activation compared to the japonica-predominant isoform. The introduction of a 4.5kb fragment containing the HKT1;1 promoter and CDS from an indica variety into a japonica background, resulted in a phenotype similar to the indica subpopulation, with higher root Na+ and Na+:K+. This study provides evidence that HKT1;1 regulates root Na+ content, and underlies the divergence in root Na+ content between the two major subspecies in rice.}, number={6}, journal={PLoS Genetics}, author={Campbell, M.T. and Bandillo, N. and Al Shiblawi, F.R.A. and Sharma, S. and Liu, K. and Du, Q. and Schmitz, A.J. and Zhang, C. and Véry, A.-A. and Lorenz, A.J. and et al.}, year={2017} }
 @article{bandillo_anderson_kantar_stupar_specht_graef_lorenz_2017, title={Dissecting the Genetic Basis of Local Adaptation in Soybean}, volume={7}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85037642408&partnerID=MN8TOARS}, DOI={10.1038/s41598-017-17342-w}, abstractNote={Abstract Soybean ( Glycine max ) is the most widely grown oilseed in the world and is an important source of protein for both humans and livestock. Soybean is widely adapted to both temperate and tropical regions, but a changing climate demands a better understanding of adaptation to specific environmental conditions. Here, we explore genetic variation in a collection of 3,012 georeferenced, locally adapted landraces from a broad geographical range to help elucidate the genetic basis of local adaptation. We used geographic origin, environmental data and dense genome-wide SNP data to perform an environmental association analysis and discover loci displaying steep gradients in allele frequency across geographical distance and between landrace and modern cultivars. Our combined application of methods in environmental association mapping and detection of selection targets provide a better understanding of how geography and selection may have shaped genetic variation among soybean landraces. Moreover, we identified several important candidate genes related to drought and heat stress, and revealed important genomic regions possibly involved in the geographic divergence of soybean.}, number={1}, journal={Scientific Reports}, author={Bandillo, N.B. and Anderson, J.E. and Kantar, M.B. and Stupar, R.M. and Specht, J.E. and Graef, G.L. and Lorenz, A.J.}, year={2017} }
 @article{bandillo_lorenz_graef_jarquin_hyten_nelson_specht_2017, title={Genome-wide association mapping of qualitatively inherited traits in a germplasm collection}, volume={10}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85024473328&partnerID=MN8TOARS}, DOI={10.3835/plantgenome2016.06.0054}, abstractNote={Genome‐wide association (GWA) has been used as a tool for dissecting the genetic architecture of quantitatively inherited traits. We demonstrate here that GWA can also be highly useful for detecting many major genes governing categorically defined phenotype variants that exist for qualitatively inherited traits in a germplasm collection. Genome‐wide association mapping was applied to categorical phenotypic data available for 10 descriptive traits in a collection of ∼13,000 soybean [ Glycine max (L.) Merr.] accessions that had been genotyped with a 50,000 single nucleotide polymorphism (SNP) chip. A GWA on a panel of accessions of this magnitude can offer substantial statistical power and mapping resolution, and we found that GWA mapping resulted in the identification of strong SNP signals for 24 classical genes as well as several heretofore unknown genes controlling the phenotypic variants in those traits. Because some of these genes had been cloned, we were able to show that the narrow GWA mapping SNP signal regions that we detected for the phenotypic variants had chromosomal bp spans that, with just one exception, overlapped the bp region of the cloned genes, despite local variation in SNP number and nonuniform SNP distribution in the chip set.}, number={2}, journal={Plant Genome}, author={Bandillo, N.B. and Lorenz, A.J. and Graef, G.L. and Jarquin, D. and Hyten, D.L. and Nelson, R.L. and Specht, J.E.}, year={2017} }
 @article{bandillo_jarquin_song_nelson_cregan_specht_lorenz_2015, title={A population structure and genome-wide association analysis on the USDA soybean germplasm collection}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84946780316&partnerID=MN8TOARS}, DOI={10.3835/plantgenome2015.04.0024}, abstractNote={Population structure analyses and genome‐wide association studies (GWAS) conducted on crop germplasm collections provide valuable information on the frequency and distribution of alleles governing economically important traits. The value of these analyses is substantially enhanced when the accession numbers can be increased from ∼1,000 to ∼10,000 or more. In this research, we conducted the first comprehensive analysis of population structure on the collection of 14,000 soybean accessions [ Glycine max (L.) Merr. and G. soja Siebold & Zucc.] using a 50K‐SNP chip. Accessions originating from Japan were relatively homogenous and distinct from the Korean accessions. As a whole, both Japanese and Korean accessions diverged from the Chinese accessions. The ancestry of founders of the American accessions derived mostly from two Chinese subpopulations, which reflects the composition of the American accessions as a whole. A 12,000 accession GWAS conducted on seed protein and oil is the largest reported to date in plants and identified single nucleotide polymorphisms (SNPs) with strong signals on chromosomes 20 and 15. A chromosome 20 region previously reported to be important for protein and oil content was further narrowed and now contains only three plausible candidate genes. The haplotype effects show a strong negative relationship between oil and protein at this locus, indicating negative pleiotropic effects or multiple closely linked loci in repulsion phase linkage. The vast majority of accessions carry the haplotype allele conferring lower protein and higher oil. Our results provide a fuller understanding of the distribution of genetic variation contained within the USDA soybean collection and how it relates to phenotypic variation for economically important traits.}, number={3}, journal={Plant Genome}, author={Bandillo, N. and Jarquin, D. and Song, Q. and Nelson, R. and Cregan, P. and Specht, J. and Lorenz, A.}, year={2015} }
 @article{multi-parent advanced generation inter-cross (magic) populations in rice: progress and potential for genetics research and breeding_2013, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84878774677&partnerID=MN8TOARS}, DOI={10.1186/1939-8433-6-11}, abstractNote={This article describes the development of Multi-parent Advanced Generation Inter-Cross populations (MAGIC) in rice and discusses potential applications for mapping quantitative trait loci (QTLs) and for rice varietal development. We have developed 4 multi-parent populations: indica MAGIC (8 indica parents); MAGIC plus (8 indica parents with two additional rounds of 8-way F1 inter-crossing); japonica MAGIC (8 japonica parents); and Global MAGIC (16 parents - 8 indica and 8 japonica). The parents used in creating these populations are improved varieties with desirable traits for biotic and abiotic stress tolerance, yield, and grain quality. The purpose is to fine map QTLs for multiple traits and to directly and indirectly use the highly recombined lines in breeding programs. These MAGIC populations provide a useful germplasm resource with diverse allelic combinations to be exploited by the rice community.The indica MAGIC population is the most advanced of the MAGIC populations developed thus far and comprises 1328 lines produced by single seed descent (SSD). At the S4 stage of SSD a subset (200 lines) of this population was genotyped using a genotyping-by-sequencing (GBS) approach and was phenotyped for multiple traits, including: blast and bacterial blight resistance, salinity and submergence tolerance, and grain quality. Genome-wide association mapping identified several known major genes and QTLs including Sub1 associated with submergence tolerance and Xa4 and xa5 associated with resistance to bacterial blight. Moreover, the genome-wide association study (GWAS) results also identified potentially novel loci associated with essential traits for rice improvement.The MAGIC populations serve a dual purpose: permanent mapping populations for precise QTL mapping and for direct and indirect use in variety development. Unlike a set of naturally diverse germplasm, this population is tailor-made for breeders with a combination of useful traits derived from multiple elite breeding lines. The MAGIC populations also present opportunities for studying the interactions of genome introgressions and chromosomal recombination.}, number={1}, journal={Rice}, year={2013} }
 @article{multi-parent advanced generation inter-cross (magic) populations in rice: progress and potential for genetics research and breeding_2013, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84885948797&partnerID=MN8TOARS}, DOI={10.1186/1939-8433-6-1}, abstractNote={A lesion-mimic mutant in rice (Oryza sativa L.), spotted leaf 5 (spl5), displays a disease-resistance-enhanced phenotype, indicating that SPL5 negatively regulates cell death and resistance responses. To understand the molecular mechanisms of SPL5 mutation-induced cell death and resistance responses, a proteomics-based approach was used to identify differentially accumulated proteins between the spl5 mutant and wild type (WT).Proteomic data from two-dimensional gel electrophoresis showed that 14 candidate proteins were significantly up- or down-regulated in the spl5 mutant compared with WT. These proteins are involved in diverse biological processes including pre-mRNA splicing, amino acid metabolism, photosynthesis, glycolysis, reactive oxygen species (ROS) metabolism, and defense responses. Two candidate proteins with a significant up-regulation in spl5 - APX7, a key ROS metabolism enzyme and Chia2a, a pathogenesis-related protein - were further analyzed by qPCR and enzyme activity assays. Consistent with the proteomic results, both transcript levels and enzyme activities of APX7 and Chia2a were significantly induced during the course of lesion formation in spl5 leaves.Many functional proteins involving various metabolisms were likely to be responsible for the lesion formation of spl5 mutant. Generally, in spl5, the up-regulated proteins involve in defense response or PCD, and the down-regulated ones involve in amino acid metabolism and photosynthesis. These results may help to gain new insight into the molecular mechanism underlying spl5-induced cell death and disease resistance in plants.}, number={1}, journal={Rice}, year={2013}, pages={1–15} }