E. S. Buckler

This study quantifies the fitness costs of transposable elements in maize by analyzing TE content across thousands of inbred lines and linking TE accumulation to reduced grain yield.

The paper measures terminator activity in Arabidopsis and maize using Plant STARR-seq, identifies factors influencing strength, and develops a predictive model for synthetic terminators.

The paper reports a novel reference genome for Poa pratensis, demonstrating its utility in studying genetic diversity and population structure.

This paper develops a predictive model to identify drought responses in sorghum and applies it to maize, finding conserved drought response genes across species.

This study uses evolutionary conservation to detect deleterious mutations in cassava and improves genomic prediction by incorporating functional variants.

This study investigates pleiotropy in maize using GWAS data across 120,597 traits, finding limited evidence of widespread biological pleiotropy.

This study compares inbreeding depression in maize and teosinte, finding greater depression in maize due to polygenic small-effect recessive variation and reduced large-effect variants after domestication.

The paper uses homologous prokaryote sequences to predict Pfam temperature adaptation in three plant species, revealing species-specific patterns of thermostability across organs.

This paper uses CNNs to predict phenotypes from genetic, environmental, and management data, showing improved accuracy with pre-training on historical data.

Rapid phenotyping of 659 Sorghum bicolor accessions revealed heritable stomatal responses to light decrease. GWAS/TWAS identified candidate genes influencing water-use efficiency traits.

This study demonstrates root-mediated yield heterosis in melons by grafting common scions onto hybrid rootstocks, showing significant yield improvements over parental lines and commercial varieties.

This study identifies an introgression from teosinte mexicana that affects HPC1, modulating phosphatidylcholine levels and influencing maize flowering time under low-temperature conditions.

The paper uses a massively parallel reporter assay to analyze plant promoters and designs synthetic promoters with high activity.

This study uses machine learning and phenotyping to identify 394 genes associated with water use efficiency traits in sorghum through GWAS and TWAS of 869 field-grown accessions.

This study identifies genes under local adaptation in maize by comparing gene expression divergence across populations and tissues, finding enrichment for stress-response genes.

The paper identifies constrained non-coding sequences in maize, showing their role in gene regulation and phenotypic variation through evolutionary analysis.

The paper identifies ten genes in maize that drive antibiotic biosynthesis, revealing a resilient pathway critical for disease resistance.

This study uses LiDar and Latent Space Phenotyping to extract quantitative plant architecture traits from maize fields, showing heritability and predictive power for breeding and research.

The paper identifies adaptive genetic loci in Mexican maize landraces by analyzing genotype-environment interactions across multiple environments, showing their potential for climate adaptation.

This study identifies the multi-allelic APRR2 gene as a key regulator of fruit pigment accumulation in melon and watermelon, demonstrating its role in rind and flesh color variation.

The paper identifies two antifungal metabolites in maize roots and shows ethylene signaling regulates their ratio, affecting resistance to Fusarium graminearum.

The paper develops computational models to identify regulatory regions in maize using k-mer sequence features, achieving over 90% accuracy.