M. Cinta Romay

This study identifies convergent genomic and gene-level constraints in grasses adapting to extreme environments using phylogenomic data and large language models.

Drone imagery from 356 flights in 19 Genomes to Fields maize environments; vegetation-index functional principal components complement genomic kernels, predicting yield of held-out hybrids at r up to 0.501.

PlantCAD2 is a DNA foundation model pre-trained on 65 angiosperm genomes, showing improved performance in evolutionary conservation and chromatin accessible region prediction compared to existing models.

This study identifies 9 QTLs associated with freezing tolerance in Tripsacum dactyloides using bulk segregant analysis and regression-based allele frequency imputation.

The paper constructs a transcriptomic atlas of grass senescence to identify molecular mechanisms of nitrogen recycling, finding divergent underground sink networks in annual crops.

This study examines competitive dynamics in maize varieties and finds limited competition effects, no yield penalty in mixtures, and increased yield stability.

The paper analyzes higher-order repeat (HOR) structures in maize centromeres and knobs, finding they are widespread but not functionally specific to centromeres, while knobs show structured HOR patterns linked to meiotic drive.

The paper identifies a conserved cis-regulatory code across 589 grass species and finds that motif conservation declines rapidly but remains significant over evolutionary time, with adaptive changes linked to ecological transitions.

This study investigates the origins and adaptive consequences of polyploidy in the prairie grass Andropogon gerardi, finding that whole genome duplication is common and provides fitness advantages in xeric climates.

The paper generates high-quality genome assemblies for three Bouteloua species and identifies polyploidy and transposable elements, providing genomic resources for comparative studies.

The paper develops a Percoll-based nuclei isolation workflow for snRNA-seq in multiple plant species, showing high yield and quality across tissues and species.

reelGene evaluates gene models using machine learning and evolutionary data, finding 28% of maize gene models are incorrectly annotated or nonfunctional.

The paper examines nitrogen dynamics in Andropogoneae grasses, finding annual species conserve nitrogen while perennials vary in their impact on nitrification and nitrate loss.

The paper compares cold-responsive proteomes across five PACMAD grasses to assess conservation of protein-level responses and identifies LEA3 as a key cold-tolerant protein.

The paper identifies selection signatures and predicts deleterious mutations in common bean using phylogenetic analysis and machine learning, showing correlations with agronomic traits.

The paper examines genome evolution in maize and related grasses, revealing variable outcomes of polyploidy across species.

The paper examines allelic variation in diel transcription patterns across maize inbreds and identifies cis-regulatory sequence variation influencing gene expression.

The paper identifies genes under relaxed selection in cassava due to clonal propagation, highlighting pollen-related genes and their implications for breeding.

The paper reports on a competition to predict maize yield using genetic and environmental data, showing that diverse modeling approaches can achieve good results.

The paper introduces PlantCaduceus, a DNA language model for plants, showing high transferability across species and improved performance in mutation prediction and variant identification.

The paper benchmarks deep learning models on genomic data across 18 grass species, finding they generalize across species but not across alleles within species.

The paper improves genomic prediction of agronomic traits in maize by integrating spatio-temporal modeling of multi-spectral aerial images with genetic data.

The paper constructs a melon pan-genome and integrates it with a multi-parental framework to enable high-resolution trait dissection in melon.

The paper introduces the Practical Haplotype Graph (PHG) platform for storing and using pangenomes, demonstrating its effectiveness in imputing genomes from low-coverage data in crops like maize.

The paper demonstrates the effectiveness of the Practical Haplotype Graph for genotype imputation in the highly heterozygous crop cassava, achieving higher accuracy than Beagle.

The paper develops a multiple genome alignment workflow for plants, showing that k-mer masking and parameter tuning improve alignment of functional regions.

The paper constructs a maize pangenome haplotype graph (PHG) to improve genotype imputation accuracy across diverse germplasm using WGS and GBS data.

This paper introduces a sorghum Practical Haplotype Graph (PHG) that enables accurate SNP calling and imputation from low-coverage sequencing data, improving genomic prediction accuracy and reducing genotyping costs.

This study shows dominance and gene annotations improve genomic prediction of agronomic traits in maize hybrids.

This study identifies quantitative trait loci (QTL) for lodging in maize by evaluating diverse inbred lines across multiple environments, finding overlaps with genes involved in lignin and cellulose synthesis.