@article{babar_harrison_blount_barnett_johnson_mergoum_mailhot_murphy_mason_shakiba_et al._2024, title={Registration of 'FL12034-10' oat: A new dual-purpose disease resistant cultivar for Florida and southern United States}, ISSN={["1940-3496"]}, DOI={10.1002/plr2.20362}, abstractNote={Abstract‘FL12034‐10’ (Reg. no. CV‐389, PI 704483), a facultative oat (Avena sativa L.) cultivar, co‐developed by the University of Florida and Louisiana State University Agricultural Center, was released in October 2022. FL12034‐10 was derived from a three‐way cross LA06055SBSBSB‐79/FL11048 F1. It is well adapted across the southern United States and provides producers with a medium‐tall, mid‐season, awnless, white‐glumed, dual‐purpose oat that has high yield potential, good straw strength, and good forage yield. FL12034‐10 was observed to be uniform and stable across environments in the southern United States from 2017 to present. The line possesses a semi‐prostrate growth habit, vigorous growth, and high tillering capacity, and has large leaves that are dark green in color. It expresses moderate‐to‐high levels of resistance to most oat diseases prevalent in the southern United States. The crown and stem rust and Barley yellow dwarf virus ratings (0–9 scale) of FL12034‐10 were 1.7, 0.7, and 1.5, respectively, across different environments. The disease ratings were better than most of the checks. The grain yield average of FL12034‐10 from 41 environments during 2018–2021 was 6437 kg ha−1, which is competitive with check cultivars that are widely used in the southern part of the United States. The forage yield of FL12034‐10 ranged from 2358 to 6617 kg ha−1 (20 environments), which was higher than most of the checks. FL12034‐10 demonstrated better lodging and disease resistance, higher grain yield potential, and higher mid‐winter to late spring season forage yield potential than Horizon 720 and Legend 567 oats released by University of Florida.}, journal={JOURNAL OF PLANT REGISTRATIONS}, author={Babar, Md Ali and Harrison, Stephen A. and Blount, Ann and Barnett, Ronald D. and Johnson, Jerry and Mergoum, Mohamed and Mailhot, Daniel J. and Murphy, J. Paul and Mason, Richard E. and Shakiba, Ehsan and et al.}, year={2024}, month={Apr} }
 @article{babar_khan_blount_barnett_harrison_dewitt_johnson_mergoum_boyles_murphy_et al._2024, title={Registration of 'FL16045-25': An early-maturing, high-yielding, disease-resistant soft red facultative wheat cultivar for the southern United States}, volume={4}, ISSN={["1940-3496"]}, DOI={10.1002/plr2.20343}, abstractNote={Abstract‘FL16045‐25’ (Reg. no. CV‐1207, PI 704484), a soft red, facultative doubled‐haploid wheat (Triticum aestivum L.) cultivar, was developed and tested as FL16045DH‐25 by the University of Florida and released in October 2022. FL16045‐25 was derived from the cross MD07W478‐14‐5/GA06112‐13EE16. It is well adapted from Texas to Virginia and provides producers with an early‐season, facultative (Vrn‐A1_short), medium‐height, awned, semi‐dwarf (Rht2) cultivar that has high yield potential, good straw strength, good grain volume weight, and good end‐use quality. It expresses moderate‐to‐high levels of resistance to most diseases prevalent in the southern United States. Molecular marker analysis confirms the presence of Sbm1, Yr17/Lr37/Sr38, Lr18, Sr36/Pm6, Pm54, and Pm1a‐linked disease‐resistant genes. The yield average of FL16045‐25 from 41 environments during 2020–2022 ranged from 4211 to 5782 kg ha−1, which is competitive with check cultivars that are widely used in the southern part of the United States. The grain volume weight of FL16045‐25 ranged from 749 to 785 kg m−3 (32 environments), which was higher than most of the checks. FL16045‐25 has soft grain texture with softness equivalence varying from 51.3% to 59.3% and sodium carbonate solvent retention capacity (SRC) ranging from 66.8% to 68.5%. Flour yields on a Quadrumat Senior milling system varied from 68.7% to 69.5%. Flour protein content varied from 8.9% to 9.1%. Cookie spread diameter varied from 19.4 to 19.5 cm. The presence of TaSus2‐2B, Sucrose Synthase2 gene on 2B or 2G:2B, was confirmed by marker analysis.}, journal={JOURNAL OF PLANT REGISTRATIONS}, author={Babar, Md Ali and Khan, Naeem and Blount, Ann and Barnett, Ronald D. and Harrison, Stephen A. and Dewitt, Noah and Johnson, Jerry and Mergoum, Mohamed and Boyles, Rick and Murphy, Paul and et al.}, year={2024}, month={Apr} }
 @article{boyles_ballen-taborda_brown-guedira_costa_cowger_dewitt_griffey_harrison_ibrahim_johnson_et al._2023, title={Approaching 25 years of progress towards Fusarium head blight resistance in southern soft red winter wheat (Triticum aestivum L.)}, volume={8}, ISSN={["1439-0523"]}, DOI={10.1111/pbr.13137}, abstractNote={AbstractTremendous progress has been made in variety development and host plant resistance to mitigate the impact of Fusarium head blight (FHB) since the disease manifested in the southeastern United States in the early 2000s. Much of this improvement was made possible through the establishment of and recurring support from the US Wheat & Barley Scab Initiative (USWBSI). Since its inception in 1997, the USWBSI has enabled land‐grant institutions to make advances in reducing the annual threat of devastating FHB epidemics. A coordinated field phenotyping effort for annual germplasm screening has become a staple tool for selection in public and private soft red winter wheat (SRWW) breeding programmes. Dedicated efforts of many SRWW breeders to identify and utilize resistance genes from both native and exotic sources provided a strong foundation for improvement. In recent years, implementation of genomics‐enabled breeding has further accelerated genetic gains in FHB resistance. This article reflects on the improvement of FHB resistance in southern SRWW and contextualizes the monumental progress made by collaborative, persistent, and good old‐fashioned cultivar development.}, journal={PLANT BREEDING}, author={Boyles, Richard E. and Ballen-Taborda, Carolina and Brown-Guedira, Gina and Costa, Jose and Cowger, Christina and DeWitt, Noah and Griffey, Carl A. and Harrison, Stephen A. and Ibrahim, Amir and Johnson, Jerry and et al.}, year={2023}, month={Aug} }
 @article{dewitt_lyerly_guedira_holland_murphy_ward_boyles_mergoum_babar_shakiba_et al._2023, title={Bearded or smooth? Awns improve yield when wheat experiences heat stress during grain fill in the southeastern United States}, volume={74}, ISSN={["1460-2431"]}, url={https://doi.org/10.1093/jxb/erad318}, DOI={10.1093/jxb/erad318}, abstractNote={Abstract
               The presence or absence of awns—whether wheat heads are ‘bearded’ or ‘smooth’ – is the most visible phenotype distinguishing wheat cultivars. Previous studies suggest that awns may improve yields in heat or water-stressed environments, but the exact contribution of awns to yield differences remains unclear. Here we leverage historical phenotypic, genotypic, and climate data for wheat (Triticum aestivum) to estimate the yield effects of awns under different environmental conditions over a 12-year period in the southeastern USA. Lines were classified as awned or awnless based on sequence data, and observed heading dates were used to associate grain fill periods of each line in each environment with climatic data and grain yield. In most environments, awn suppression was associated with higher yields, but awns were associated with better performance in heat-stressed environments more common at southern locations. Wheat breeders in environments where awns are only beneficial in some years may consider selection for awned lines to reduce year-to-year yield variability, and with an eye towards future climates.}, number={21}, journal={JOURNAL OF EXPERIMENTAL BOTANY}, author={DeWitt, Noah and Lyerly, Jeanette and Guedira, Mohammed and Holland, James B. and Murphy, J. Paul and Ward, Brian P. and Boyles, Richard E. and Mergoum, Mohamed and Babar, Md Ali and Shakiba, Ehsan and et al.}, editor={Dreisigacker, SusanneEditor}, year={2023}, month={Nov}, pages={6749–6759} }
 @article{winn_hudson-arns_hammers_dewitt_lyerly_bai_st. amand_nachappa_haley_mason_2023, title={HaploCatcher: An R package for prediction of haplotypes}, ISSN={["1940-3372"]}, DOI={10.1002/tpg2.20412}, abstractNote={AbstractWheat (Triticum aestivum L.) is crucial to global food security but is often threatened by diseases, pests, and environmental stresses. Wheat‐stem sawfly (Cephus cinctus Norton) poses a major threat to food security in the United States, and solid‐stem varieties, which carry the stem‐solidness locus (Sst1), are the main source of genetic resistance against sawfly. Marker‐assisted selection uses molecular markers to identify lines possessing beneficial haplotypes, like that of the Sst1 locus. In this study, an R package titled “HaploCatcher” was developed to predict specific haplotypes of interest in genome‐wide genotyped lines. A training population of 1056 lines genotyped for the Sst1 locus, known to confer stem solidness, and genome‐wide markers was curated to make predictions of the Sst1 haplotypes for 292 lines from the Colorado State University wheat breeding program. Predicted Sst1 haplotypes were compared to marker‐derived haplotypes. Our results indicated that the training set was substantially predictive, with kappa scores of 0.83 for k‐nearest neighbors and 0.88 for random forest models. Forward validation on newly developed breeding lines demonstrated that a random forest model, trained on the total available training data, had comparable accuracy between forward and cross‐validation. Estimated group means of lines classified by haplotypes from PCR‐derived markers and predictive modeling did not significantly differ. The HaploCatcher package is freely available and may be utilized by breeding programs, using their own training populations, to predict haplotypes for whole‐genome sequenced early generation material.}, journal={PLANT GENOME}, author={Winn, Zachary James and Hudson-Arns, Emily and Hammers, Mikayla and DeWitt, Noah and Lyerly, Jeanette and Bai, Guihua and St. Amand, Paul and Nachappa, Punya and Haley, Scott and Mason, Richard Esten}, year={2023}, month={Nov} }
 @article{winn_larkin_lozada_dewitt_brown-guedira_mason_2023, title={Multivariate genomic selection models improve prediction accuracy of agronomic traits in soft red winter wheat}, volume={5}, ISSN={["1435-0653"]}, DOI={10.1002/csc2.20994}, abstractNote={AbstractUnivariate genomic selection (UVGS) is an important tool for increasing genetic gain and multivariate GS (MVGS), where correlated traits are included in genomic selection, which can improve genomic prediction accuracy. The objectives for this study were to evaluate MVGS approaches to improve prediction accuracy for four agronomic traits using a training population of 351 soft red winter wheat (Triticum aestivum L.) genotypes, evaluated over six site‐years in Arkansas from 2014 to 2017. Genotypes were phenotyped for grain yield, heading date, plant height, and test weight in both the training and test populations. In cross‐validations, various combinations of traits in MVGS models significantly improved prediction accuracy for test weight in comparison to a UVGS model. Marginal increases in predictive accuracy were also observed for grain yield, plant height, and heading date. Multivariate models which were identified as superior to the univariate case in cross‐validations were forward validated by predicting the advanced breeding nurseries of 2018 and 2020. In forward validation, consistent increases in accuracy were observed for test weight, plant height, and heading date using MVGS instead of UVGS. Overall, MVGS models improved prediction accuracies when correlated traits were included with the predicted response. The methods outlined in this study may be used to achieve higher prediction accuracies in unbalanced datasets over multiple environments.}, journal={CROP SCIENCE}, author={Winn, Zachary J. and Larkin, Dylan L. and Lozada, Dennis N. and DeWitt, Noah and Brown-Guedira, Gina and Mason, Richard Esten}, year={2023}, month={May} }
 @article{dewitt_guedira_murphy_marshall_mergoum_maltecca_brown-guedira_2022, title={A network modeling approach provides insights into the environment-specific yield architecture of wheat}, volume={5}, ISSN={["1943-2631"]}, url={https://doi.org/10.1093/genetics/iyac076}, DOI={10.1093/genetics/iyac076}, abstractNote={Abstract
               Wheat (Triticum aestivum) yield is impacted by a diversity of developmental processes which interact with the environment during plant growth. This complex genetic architecture complicates identifying quantitative trait loci that can be used to improve yield. Trait data collected on individual processes or components of yield have simpler genetic bases and can be used to model how quantitative trait loci generate yield variation. The objectives of this experiment were to identify quantitative trait loci affecting spike yield, evaluate how their effects on spike yield proceed from effects on component phenotypes, and to understand how the genetic basis of spike yield variation changes between environments. A 358 F5:6 recombinant inbred line population developed from the cross of LA-95135 and SS-MPV-57 was evaluated in 2 replications at 5 locations over the 2018 and 2019 seasons. The parents were 2 soft red winter wheat cultivars differing in flowering, plant height, and yield component characters. Data on yield components and plant growth were used to assemble a structural equation model to characterize the relationships between quantitative trait loci, yield components, and overall spike yield. The effects of major quantitative trait loci on spike yield varied by environment, and their effects on total spike yield were proportionally smaller than their effects on component traits. This typically resulted from contrasting effects on component traits, where an increase in traits associated with kernel number was generally associated with a decrease in traits related to kernel size. In all, the complete set of identified quantitative trait loci was sufficient to explain most of the spike yield variation observed within each environment. Still, the relative importance of individual quantitative trait loci varied dramatically. Path analysis based on coefficients estimated through structural equation model demonstrated that these variations in effects resulted from both different effects of quantitative trait loci on phenotypes and environment-by-environment differences in the effects of phenotypes on one another, providing a conceptual model for yield genotype-by-environment interactions in wheat.}, number={3}, journal={GENETICS}, author={DeWitt, Noah and Guedira, Mohammed and Murphy, Joseph Paul and Marshall, David and Mergoum, Mohamed and Maltecca, Christian and Brown-Guedira, Gina}, editor={Juenger, TEditor}, year={2022}, month={May} }
 @article{he_wang_rutter_jordan_ren_taagen_dewitt_sehgal_sukumaran_dreisigacker_et al._2022, title={Genomic variants affecting homoeologous gene expression dosage contribute to agronomic trait variation in allopolyploid wheat}, volume={13}, ISSN={["2041-1723"]}, DOI={10.1038/s41467-022-28453-y}, abstractNote={AbstractAllopolyploidy greatly expands the range of possible regulatory interactions among functionally redundant homoeologous genes. However, connection between the emerging regulatory complexity and expression and phenotypic diversity in polyploid crops remains elusive. Here, we use diverse wheat accessions to map expression quantitative trait loci (eQTL) and evaluate their effects on the population-scale variation in homoeolog expression dosage. The relative contribution of cis- and trans-eQTL to homoeolog expression variation is strongly affected by both selection and demographic events. Though trans-acting effects play major role in expression regulation, the expression dosage of homoeologs is largely influenced by cis-acting variants, which appear to be subjected to selection. The frequency and expression of homoeologous gene alleles showing strong expression dosage bias are predictive of variation in yield-related traits, and have likely been impacted by breeding for increased productivity. Our study highlights the importance of genomic variants affecting homoeolog expression dosage in shaping agronomic phenotypes and points at their potential utility for improving yield in polyploid crops.}, number={1}, journal={NATURE COMMUNICATIONS}, author={He, Fei and Wang, Wei and Rutter, William B. and Jordan, Katherine W. and Ren, Jie and Taagen, Ellie and DeWitt, Noah and Sehgal, Deepmala and Sukumaran, Sivakumar and Dreisigacker, Susanne and et al.}, year={2022}, month={Feb} }
 @article{dewitt_guedira_lauer_murphy_marshall_mergoum_johnson_holland_brown-guedira_2021, title={Characterizing the oligogenic architecture of plant growth phenotypes informs genomic selection approaches in a common wheat population}, volume={22}, ISSN={["1471-2164"]}, DOI={10.1186/s12864-021-07574-6}, abstractNote={Abstract
                Background
                Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL.
              
                Results
                We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models.
              
                Conclusions
                In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.
              }, number={1}, journal={BMC GENOMICS}, author={DeWitt, Noah and Guedira, Mohammed and Lauer, Edwin and Murphy, J. Paul and Marshall, David and Mergoum, Mohamed and Johnson, Jerry and Holland, James B. and Brown-Guedira, Gina}, year={2021}, month={May} }
 @article{glenn_zhang_brown-guedira_dewitt_cook_li_akhunov_dubcovsky_2021, title={Identification and characterization of a natural polymorphism in FT-A2 associated with increased number of grains per spike in wheat}, volume={11}, ISSN={["1432-2242"]}, DOI={10.1007/s00122-021-03992-y}, abstractNote={Abstract
                Key message
                We discovered a natural FT-A2 allele that increases grain number per spike in both pasta and bread wheat with limited effect on heading time.
              
                Abstract
                Increases in wheat grain yield are necessary to meet future global food demands. A previous study showed that loss-of-function mutations in FLOWERING LOCUS T2 (FT2) increase spikelet number per spike (SNS), an important grain yield component. However, these mutations were also associated with reduced fertility, offsetting the beneficial effect of the increases in SNS on grain number. Here, we report a natural mutation resulting in an aspartic acid to alanine change at position 10 (D10A) associated with significant increases in SNS and no negative effects on fertility. Using a high-density genetic map, we delimited the SNS candidate region to a 5.2-Mb region on chromosome 3AS including 28 genes. Among them, only FT-A2 showed a non-synonymous polymorphism (D10A) present in two different populations segregating for the SNS QTL on chromosome arm 3AS. These results, together with the known effect of the ft-A2 mutations on SNS, suggest that variation in FT-A2 is the most likely cause of the observed differences in SNS. We validated the positive effects of the A10 allele on SNS, grain number, and grain yield per spike in near-isogenic tetraploid wheat lines and in an hexaploid winter wheat population. The A10 allele is present at very low frequency in durum wheat and at much higher frequency in hexaploid wheat, particularly in winter and fall-planted spring varieties. These results suggest that the FT-A2 A10 allele may be particularly useful for improving grain yield in durum wheat and fall-planted common wheat varieties.
              }, journal={THEORETICAL AND APPLIED GENETICS}, author={Glenn, Priscilla and Zhang, Junli and Brown-Guedira, Gina and DeWitt, Noah and Cook, Jason P. and Li, Kun and Akhunov, Eduard and Dubcovsky, Jorge}, year={2021}, month={Nov} }
 @article{kuzay_xu_zhang_katz_pearce_su_fraser_anderson_brown-guedira_dewitt_et al._2019, title={Identification of a candidate gene for a QTL for spikelet number per spike on wheat chromosome arm 7AL by high-resolution genetic mapping}, volume={132}, ISSN={["1432-2242"]}, DOI={10.1007/s00122-019-03382-5}, abstractNote={A high-resolution genetic map combined with haplotype analyses identified a wheat ortholog of rice gene APO1 as the best candidate gene for a 7AL locus affecting spikelet number per spike. A better understanding of the genes controlling differences in wheat grain yield components can accelerate the improvements required to satisfy future food demands. In this study, we identified a promising candidate gene underlying a quantitative trait locus (QTL) on wheat chromosome arm 7AL regulating spikelet number per spike (SNS). We used large heterogeneous inbred families ( > 10,000 plants) from two crosses to map the 7AL QTL to an 87-kb region (674,019,191-674,106,327 bp, RefSeq v1.0) containing two complete and two partial genes. In this region, we found three major haplotypes that were designated as H1, H2 and H3. The H2 haplotype contributed the high-SNS allele in both H1 × H2 and H2 × H3 segregating populations. The ancestral H3 haplotype is frequent in wild emmer (48%) but rare (~ 1%) in cultivated wheats. By contrast, the H1 and H2 haplotypes became predominant in modern cultivated durum and common wheat, respectively. Among the four candidate genes, only TraesCS7A02G481600 showed a non-synonymous polymorphism that differentiated H2 from the other two haplotypes. This gene, designated here as WHEAT ORTHOLOG OF APO1 (WAPO1), is an ortholog of the rice gene ABERRANT PANICLE ORGANIZATION 1 (APO1), which affects spikelet number. Taken together, the high-resolution genetic map, the association between polymorphisms in the different mapping populations with differences in SNS, and the known role of orthologous genes in other grass species suggest that WAPO-A1 is the most likely candidate gene for the 7AL SNS QTL among the four genes identified in the candidate gene region.}, number={9}, journal={THEORETICAL AND APPLIED GENETICS}, author={Kuzay, Saarah and Xu, Yunfeng and Zhang, Junli and Katz, Andrew and Pearce, Stephen and Su, Zhenqi and Fraser, Max and Anderson, James A. and Brown-Guedira, Gina and DeWitt, Noah and et al.}, year={2019}, month={Sep}, pages={2689–2705} }
 @article{dewitt_guedira_lauer_sarinelli_tyagi_fu_hao_murphy_marshall_akhunova_et al._2020, title={Sequence-based mapping identifies a candidate transcription repressor underlying awn suppression at the B1 locus in wheat}, volume={225}, ISSN={["1469-8137"]}, DOI={10.1111/nph.16152}, abstractNote={Summary


Awns are stiff, hair‐like structures which grow from the lemmas of wheat (Triticum aestivum) and other grasses that contribute to photosynthesis and play a role in seed dispersal. Variation in awn length in domesticated wheat is controlled primarily by three major genes, most commonly the dominant awn suppressor Tipped1 (B1). This study identifies a transcription repressor responsible for awn inhibition at the B1 locus.

Association mapping was combined with analysis in biparental populations to delimit B1 to a distal region of 5AL colocalized with QTL for number of spikelets per spike, kernel weight, kernel length, and test weight.

Fine‐mapping located B1 to a region containing only two predicted genes, including C2H2 zinc finger transcriptional repressor TraesCS5A02G542800 upregulated in developing spikes of awnless individuals. Deletions encompassing this candidate gene were present in awned mutants of an awnless wheat. Sequence polymorphisms in the B1 coding region were not observed in diverse wheat germplasm whereas a nearby polymorphism was highly predictive of awn suppression.

Transcriptional repression by B1 is the major determinant of awn suppression in global wheat germplasm. It is associated with increased number of spikelets per spike and decreased kernel size.

}, number={1}, journal={NEW PHYTOLOGIST}, author={DeWitt, Noah and Guedira, Mohammed and Lauer, Edwin and Sarinelli, Martin and Tyagi, Priyanka and Fu, Daolin and Hao, QunQun and Murphy, J. Paul and Marshall, David and Akhunova, Alina and et al.}, year={2020}, month={Jan}, pages={326–339} }