Candice N. Hirsch

This paper introduces a regression-based framework to predict flowering time from sparse UAV observations, reducing the need for repeated data collection.

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.

This study evaluates genomic prediction models for maize hybrids using GBLUP-based multi-kernel models to estimate genetic variance components and predict hybrid performance.

The paper identifies promoter structural variants in maize that are associated with differential gene expression across tissues, often involving transposable elements.

This study identifies compositional and morphological traits of maize kernels that predict pericarp retention during nixtamalization using stain-based scoring and correlation analysis.

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

This paper improves simulation accuracy for digital breeding by integrating GWAS-derived genetic architecture into trait simulations, achieving high concordance with empirical data.

The paper investigates how host genotype and environment interact to shape bacterial endophyte communities in maize stalks, finding that gene-by-environment interactions significantly influence microbial communities.

This study uses long-read genome assemblies from maize to develop a new method for detecting selection on transposable elements, identifying factors like gene distance and DNA methylation levels that influence TE selection.

This paper introduces distributional data analysis to plant phenomics, showing it captures novel heritable features in cotton and maize imagery that improve yield prediction and explain genetic variation.

SWIF-TE identifies novel transposable element insertions from short read data with high efficiency and precision.

The paper uses UAV-derived plant height data to predict maize grain yield variation within fields, showing moderate predictive accuracy but limitations in drought-stressed environments.

This study shows nixtamalization moisture content can be selected early in maize breeding using genomic prediction and NIR spectroscopy, with no significant correlation to yield.

The paper identifies structural variants in maize using whole genome alignment and short-read sequencing, linking them to life history traits and genotype-by-environment interactions.

The paper tests gene regulatory network predictions in maize by analyzing transcriptomic and metabolic changes in TF mutants, finding limited phenotypic impacts but some altered target gene expression.

This study uses high-temporal-resolution plant height data to show that genetic and environmental factors influence plant growth differently across the growing season.

The paper develops a pan-TE annotation tool to analyze TE variation in maize, finding that tropical maize has more TE sequences due to active and less methylated LTR retrotransposons.

This study uses UAV imagery to track maize canopy cover over time, revealing its genetic and environmental influences and the limitations of single-time-point phenotyping.

The paper analyzes transposable elements and structural variation in maize genomes, finding that deletions of transposable elements contribute more to genomic differences than insertions.

A multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

The paper presents a high-quality whole genome assembly and annotation of Northern Wild Rice, revealing a whole genome duplication event in the Zizania genus.

The paper presents a gapless maize genome assembly using long read technologies and optical maps, achieving telomere-to-telomere assemblies for chromosomes 3 and 9.

This study evaluates the impact of sequence depth and read length on long-read assembly quality for the maize genome, finding that lower depths and shorter reads result in fragmented assemblies.

The paper identifies and resolves split-gene misannotations across multiple maize reference genomes using RNAseq data and a simulation framework.

The paper benchmarks TE annotation methods and develops a pipeline called EDTA to create a comprehensive, condensed TE library for both intact and fragmented elements in rice genomes.

This study characterizes sRNA variation and inheritance in maize inbreds and F1 hybrids, revealing genotype and developmental influences on sRNA expression and non-additive inheritance patterns.

The paper identifies variable transposable element (TE) insertions across four maize genomes, showing their role in genome organization and gene content variation.

The paper analyzes gene expression in maize hybrids and inbreds to show that single-parent expression is genotype- and tissue-specific, with implications for heterosis.

The paper identifies thousands of tandem duplicate genes in maize, showing they are abundant and date to two distinct periods of genomic instability.

This study examines how genotype-by-environment interactions affect heterosis in maize hybrids and their inbred parents across 16 environments and 25 traits.