About

Edward S. Buckler is a plant geneticist with the USDA Agricultural Research Service and holds an adjunct appointment at Cornell University in the School of Integrative Plant Science's Plant Breeding and Genetics Section. His work focuses on both quantitative and statistical genetics in maize as well as other crops such as cassava. The Buckler Lab for Maize Genetics and Diversity uses functional genomic approaches to dissect complex traits in maize, biofuel grasses, and grapes. The lab utilizes the natural diversity of these plant genomes to identify the individual nucleotides responsible for complex (quantitative) variation.

Research topics

• Biology
• Genetics
• Computer Science
• Agronomy
• Artificial Intelligence
• Computational biology
• Evolutionary biology
• Botany
• Ecology
• Data science
• Machine Learning
• Biotechnology
• Sociology
• Geography
• World Wide Web
• Agroforestry
• Demography
• Medicine

Selected publications

• Genomes to fields 2024 maize genotype by environment prediction competition

  BMC Research Notes · 2026-02-09 · 1 citations

  articleOpen access

  The genomes to fields (G2F) 2024 Maize Genotype by Environment (GxE) Prediction Competition challenged participants to develop and submit their best performing models to predict grain yield for the 2024 maize GxE project field trials, using G2F data collected from 2014 to 2023 and other publicly available data. The G2F Maize GxE Project is a collaborative effort, with all generated data made publicly available. The resource presented here includes the training and test datasets used for the G2F 2024 Maize GxE Prediction Competition. Specifically, data collected from 2014 to 2023 served as the training set to predict grain yield in the 2024 test set. The dataset comprises phenotypic, genotypic, soil, weather, and environmental covariate data, along with metadata describing environments (year-location combinations). It has been curated and lightly filtered for quality control and to ensure consistent naming across years. Competitors also had access to readme files that describe the structure and content of the datasets.

  PublisherDOI

• Correction: DeltaBreed: A BrAPI-centric breeding data information system

  PLoS ONE · 2026-01-22

  articleOpen access

  [This corrects the article DOI: 10.1371/journal.pone.0324104.].

  PublisherOA PDFDOI

• Higher order repeat structures reflect diverging evolutionary paths in maize centromeres and knobs

  Genome biology · 2026-02-14

  articleOpen access

  BACKGROUND: Highly repetitive tandem repeat arrays, known as satellite DNAs, are enriched in low-recombination regions such as centromeres. Satellite arrays often contain complex internal structures called higher-order repeats (HORs), which may have functional significance. Maize is unusual in that its satellites occur in two distinct genomic contexts: centromeres, which interact with kinetochore proteins, and knobs, which undergo meiotic drive in the presence of Abnormal chromosome 10. Whether maize centromeres or knobs contain HOR patterns, and how such patterns relate to function, remains unclear. RESULTS: Here, we generate 13 repeat-sensitive genome assemblies of maize and its recent ancestor, teosinte. We develop a new graph-based pipeline, HiReNET, to classify HORs and demonstrate its utility in both Arabidopsis and maize. We find that HORs are ubiquitous in maize satellites but are typically low-frequency with small patterns, unlike the large, continuous HOR blocks characteristic of human centromeres. Approximately 38% of centromeric CentC monomers occur in HORs; however, no specific HOR class dominates any functional centromere as marked by centromeric histone H3. Arabidopsis centromeres have a similar HOR landscape. In contrast, maize knobs exhibit a more structured HOR distribution. Large knobs contain megabase-scale similarity blocks with repeated HOR patterns. These repeat units likely promote unequal crossing over, enabling rapid knob expansion, and may harbor motifs recognized by trans-acting factors involved in meiotic drive. CONCLUSIONS: HORs occur in all major maize satellite arrays. Specific HORs are not associated with centromere function, but knobs contain conserved HOR patterns within similarity blocks that may facilitate meiotic drive.

  PublisherDOI

• Inter-variety competition dynamics in US inbred and hybrid maize

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-02-28

  articleOpen access

  ABSTRACT Variety mixtures provide a potential avenue in US cropping systems to improve yield stability and disease resistance. However, implementation of variety mixtures requires an understanding of the competitive dynamics of the crop. In this study, we examine the effects of plant competition both between and within plots through five unique experiments: 1) 5,000 diverse inbred lines in single-row plots, 2) hybrids in two-row plots developed from the above inbred lines, 3) over 4,000 hybrids measured in 141 locations in two-row plots as part of Genomes to Fields, 4) mixtures of two hybrids within a two-row plot planted across two years and five locations, and 5) mixtures of up to twenty hybrids in four-row plots in three locations. Across all experiments, we find that competitive interactions are extremely limited. Within inbred lines, height of the neighboring plot accounts for 1.2% of the variance in focal plot height. Similarly, neighbor height explains 1.7% of the variance in focal plot yield in hybrids developed from the inbred lines. The genetics of neighboring plots explains 1.55% of the variation in yield across 141 location-year environments, reinforcing the generally modest impacts of neighbor competition. In evaluating mixtures of hybrids in both two and four-row plots, we observe no yield penalty compared to conventional single hybrid plots, even with large height differentials of the hybrids included in the mixture or in mixtures of up to 20 hybrids within a plot. Finally, we observe that mixtures have more yield stability compared to conventional plots, highlighting a new avenue for increased stability in higher risk environments. The lack of yield penalty and stability benefits are promising for future investigations of mixtures that may complement each other in disease resistance or abiotic stress tolerance and increase overall yield stability in the field.

  PublisherOA PDFDOI

• Cross-species optimization of nuclei isolation in ten plant species

  Plant Methods · 2026-01-16

  articleOpen access

  Single-cell technologies are transforming plant biology, yet broadly transferable nuclei isolation remains a key bottleneck for snRNA-seq. We developed a reproducible, cost-efficient Percoll-based workflow that is applicable to multiple maize tissues and nine additional plant species. In maize, nuclei from root, shoot, leaf, and embryo consistently concentrated at the 80% Percoll interface and exhibited high integrity, with typical recoveries > 50,000 nuclei per sample. For other species, gradient compositions were tuned according to genome size to achieve efficient enrichment and clean suspensions, and yields ranged from 17,000 to 40,000 nuclei per sample. Downstream validation showed that nuclei from special interest maize and Tripsacum generated high-quality snRNA-seq libraries, as supported by cDNA quality profiles. These results demonstrate the versatility and robustness of the method across species and tissues.

  PublisherDOI

• Translating functional molecular knowledge into crop-breeding success

  Nature Reviews Genetics · 2026-05-20

  article
  PublisherDOI

• A transcriptomic atlas of grass senescence reveals divergent underground sink networks limit nitrogen recycling in annuals

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-06

  articleOpen access

  Abstract Senescence enables plants to remobilize and recycle nutrients from aging organs to support growth, reproduction, and survival. In annual crops like maize, nitrogen remobilization from leaves to grain is incomplete, with 30-50% of nitrogen stranded in aboveground tissues and subject to environmental loss. Mitigating nitrogen loss in annual crops could be achieved by leveraging the physiological strategies of perennial grasses, which remobilize nitrogen and other nutrients into underground organs at the end of the growing season, thereby preventing environmental leakage. To uncover the molecular basis of perennial nitrogen recycling to underground organs, we built a transcriptomic atlas from field-grown plants, comprising 2,685 RNA-seq libraries from 14 grass species within the Panicoideae (Poaceae), utilizing maize and sorghum as annual references for comparative analyses. The atlas spans leaves, roots, stalks, and rhizomes across two seasons, from mid-growing season to senescence. Using a photosynthetic index to align the leaf’s transition from nitrogen sink to source across species, co-expression network analysis revealed that the subnetworks driving leaf nitrogen recycling are preserved across annuals and perennials. However, we discovered that the subnetworks associated with underground sink establishment, specifically those associated with seed-like dormancy and desiccation tolerance pathways, have diverged among annual crop accessions. Our work identifies conserved gene candidates and networks that could be used to reintroduce perennial-like nutrient recycling into annual crops to enhance long-term nutrient retention in the field.

  PublisherOA PDFDOI

• Environmental data provide marginal benefit for predicting climate adaptation

  PLoS Genetics · 2025-06-09 · 11 citations

  articleOpen accessCorresponding

  Climate change poses a major challenge for both natural and cultivated species. Genomic tools are increasingly used in both conservation and breeding to identify adaptive loci that can be used to guide management in future climates. Here, we study the utility of climate and genomic data for identifying promising alleles using common gardens of a large, geographically diverse sample of traditional maize varieties to evaluate multiple approaches. First, we used genotype data to predict environmental characteristics of germplasm collections to identify varieties that may be pre-adapted to target environments. Second, we used environmental GWAS (envGWAS) to identify loci associated with historical divergence along climatic gradients. Finally, we compared the value of environmental data and envGWAS-prioritized loci to genomic data for prioritizing traditional varieties. We find that maize yield traits are best predicted by genome-wide relatedness and population structure, and that incorporating envGWAS-identified variants or environment-of-origin data provide little additional predictive information. While our results suggest that environmental data provide limited benefit in predicting fitness-related phenotypes, environmental GWAS is nonetheless a potentially powerful approach to identify individual novel loci associated with adaptation, especially when coupled with high density genotyping.

  PublisherDOI

• DeltaBreed: A BrAPI-centric breeding data information system

  PLoS ONE · 2025-12-12 · 2 citations

  articleOpen accessCorresponding

  DeltaBreed is a unified breeding data management system designed by Breeding Insight (BI, Cornell University) to serve the wide diversity of USDA-ARS specialty crop and livestock breeding programs. DeltaBreed has a RESTful microservice architecture that utilizes the BrAPI v2.1 Java Test Server as its primary database. The system is interoperable with many BrAPI-compliant applications (BrApps), including Field Book v6.1.0, and is continually aligned with the most recent BrAPI specifications (BrAPI v2.1). Here we describe the features of DeltaBreed v1.0, a minimum viable product, and how we aligned data capture and validation with community standards. We highlight the modules for management of germplasm, observation variables, experiments and observations, genotypic sample submission, and a prototype genomic database that supports polyploid and multiallelic genomic data, as well as SNP data. Several test cases are illustrated to demonstrate the successes and challenges of interoperability with other open-source BrAPI-enabled software packages. We also discuss expansion and enhancement plans for future DeltaBreed versions, as well as outline possible solutions to known limitations. To our knowledge, DeltaBreed is the first species-agnostic, fully BrAPI-compliant breeding data management system built for transactional use.

  PublisherDOI

• Widespread turnover of a conserved cis <i>-</i> regulatory code across 589 grass species

  Molecular Biology and Evolution · 2025-12-09

  articleOpen accessSenior author

  The growing availability of genomes from non-model organisms offers new opportunities to identify functional loci underlying trait variation through comparative genomics. While cis-regulatory regions drive much of phenotypic evolution, linking them to specific functions remains challenging. We identified 514 cis-regulatory motifs enriched in regulatory regions of five diverse grass species, with 73% consistently enriched across all, suggesting a deeply conserved regulatory code. Leveraging 57 new contig-level genome assemblies, we then quantified shared occupancy of specific motif instances within gene-proximal regions across 589 grass species, revealing widespread gain and loss over evolutionary time. Shared occupancy declined rapidly over the first few million years of divergence, yet ∼50% of motif instances were shared back to the origin of grasses ∼100 million years ago. We used phylogenetic mixed models to identify motif gains and losses associated with ecological niche transitions. Our models revealed significant environmental associations across 1282 motif-orthogroup combinations, including convergent gains of HSF/GARP motifs at an alpha-N-acetylglucosaminidase gene associated with occurrence in temperate environments. Our findings support a "stable motifs, variable binding sites" model in which cis-regulatory evolution involves turnover of thousands of individual binding site instances while largely preserving transcription factors' binding preferences. Our results highlight the potential of comparative genomics and phylogenetic mixed models to reveal the genetic basis of complex traits.

  PublisherOA PDFDOI

Recent grants

• Biology of Rare Alleles in Maize and Its Wild Relatives

  NSF · $13.3M · 2013–2019

• High Density Scoreable Markers for Maize Trait Dissection

  NSF · $963k · 2006–2009

• BREAD: Platform, Pipeline, and Analytical Tools for Next Generation Genotyping to Serve Breeding Efforts in Africa

  NSF · $1.7M · 2010–2014

• RESEARCH-PGR: PanAnd - Harnessing convergence and constraint to predict adaptations to abiotic stress for maize and sorghum

  NSF · $5.0M · 2018–2023

• Genetic Architecture of Maize and Teosinte

  NSF · $9.8M · 2009–2014

Frequent coauthors

• Peter J. Bradbury

  340 shared

• M. Cinta Romay

  Cornell University

  184 shared

• James B. Holland

  Agricultural Research Service

  182 shared

• Michael A. Gore

  Cornell University

  166 shared

• Michael D. McMullen

  162 shared

• Sherry Flint‐Garcia

  United States Department of Agriculture

  153 shared

• Zhiwu Zhang

  Washington State University

  122 shared

• John Doebley

  University of Wisconsin–Madison

  121 shared

Education

• PhD, Biological Science

  University of Missouri Columbia

  1997

Awards & honors

• 2025 Barbara McClintock Prize for Plant Genetics and Genome…