Biology subjects

Holland, J. B.

Publications and source records attributed to Holland, J. B..

15 recordsLinked to original sources

bioRxiv2026

An open field phenomics resource for multimodal maize yield prediction across divergent environments

Temporal drone phenotyping captures crop development, but irregular flight schedules complicate comparisons across environments. We release curated imagery from 356 flights across 19 Genomes to Fields environments containing 1,180 maize (Zea mays L.) hybrids. To evaluate its utility, we integrated functional principal components of vegetation index and weather trajectories with genomic information. Combinined genomic and phenomic kernels improved yield prediction, reaching correlations up to r = 0.501 for held-out hybrids in environments represented in training and 0.408 when environments were also withheld. Accumulated growing degree days offered no consistent predictive advantage over days after planting, and weather contributed modest, task-dependent gains. A transformer neural process learned directly from irregular observations, serving as a novel application of neural process models in agriculture. Mapping vegetation index functional principal components identified recurrent quantitative trait loci on chromosomes 3 and 7. This resource and its reproducible analyses guide the use of temporal spectral data for crop prediction and genetic discovery.

plant biology↗

bioRxiv2026

Cis-regulatory variation and transcription factor binding contribute to allelic genotype-by-environment interactions for gene expression in maize

Genotype-by-environment interactions (GxE), or differences in how genotypes perform across varying environments, are a pervasive source of phenotypic variation and underlie differences in local adaptation. Though GxE is well characterized across kingdoms of life, less is known about what causes GxE interactions, particularly at the molecular level. In this study, we use allele-specific gene expression estimates in a maize (Zea mays L.) B73 x Mo17 hybrid to isolate cis-regulatory effects on gene expression for each of the two parental alleles. The hybrid was grown in two environments, and expression differences between the parental alleles were used to characterize allele-by-environment (AxE) interactions and study the influence of gene-proximal sequence variation on transcript abundance AxE. We tested the hypothesis that gene-proximal sequence variation can cause GxE in gene expression by modifying transcription factor binding. Our results show that sequence variation in gene promoter regions has a small but consistent enrichment in genes that show transcriptional AxE. Further, we demonstrate that differential transcription factor binding potential caused by sequence variation is also enriched in AxE genes. Predictive models trained on sequence and transcription factor binding variation show that while these features contain some information about whether a gene will show transcriptional AxE, they alone are not sufficient to reliably distinguish AxE genes. These findings support the hypothesis that gene expression GxE can be caused by sequence variation that modifies transcription factor binding, while also reinforcing the complex and context-specific nature of GxE interactions.

genomics↗

bioRxiv2026

Zea Lip: An atlas of glycerolipid profiles across leaf development in maize

Lipids are the predominant building blocks of plant membranes and are essential for plant growth and development. They are crucial for survival during times of stress as lipids are involved in multiple signaling pathways, and their relative abundances can change in response to environmental factors. To better characterize the lipid composition of the vital food crop maize, we generated a comprehensive glycerolipid atlas using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. We surveyed the lipid profiles of three different maize genotypes: B73, a temperate inbred; CML312, a subtropical inbred; and Palomero Toluqueno, an open-pollinated variety from the Mexican highlands. We collected leaf samples from 4 developmental stages and 6 leaves. From one growth stage, we also sampled along with three leaf zones: base, center, and tip. The genotype and leaf number were the major drivers of lipid differences. Phosphatidylcholine, lysophosphatidylcholine, and triacylglycerol genotypic differences were particularly high. We generated an eFP browser to be integrated into the maize genome browser, as well as a separate web interface to easily browse and compare lipid levels across tissues and genotypes, available at https://bar.utoronto.ca/~dev/efp_maize_lipid/cgi-bin/efpWeb.cgi and https://rrellan.shinyapps.io/Zea-Lip/ respectively. SIGNIFICANCE STATEMENTThis work creates a spatial map of lipids in maize leaves across four growth stages for three genotypes: a lowland, a sub-tropical, and a highland. The resources generated here will directly benefit both the maize and lipid communities by creating a large dataset that can be used to generate new hypotheses in understanding lipid metabolism and environmental responses in maize.

plant biology↗

bioRxiv2026

Inter-variety competition dynamics in US inbred and hybrid maize

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.

plant biology↗

bioRxiv2025

Gene-by-Environment Interaction Significantly Drives Bacterial Endophyte Communities in Maize Stalks

1.BackgroundMany microbes are known to boost the performance of crop plants, and their use as crop treatments ("biologicals") is an active area of research and commercialization. Although many identified microbes can boost plant production under laboratory settings, most fail to translate to field settings, and even the ones that are commercialized are often unreliable. While many factors likely underlie these issues, one that has been underexplored is the idea that interactions between plants and microbes can vary across both different host genetics and different environments, and that specific combinations of host and environment can result in very different microbial outcomes. ResultsTo quantify how a plant microbiome can change across host genotype and environment and to determine the relative importance of these factors, we sampled maize stalks from 20 specific hybrid varieties grown at 15 locations in the United States. Using 16S rRNA gene sequencing, we find that the stalk microbiome is highly variable, with a handful of bacterial taxa conserved at broader taxonomic levels (Phylum, Class) and almost none at finer levels (Genus, Species). Local environment and gene-by-environment interactions both had consistently large and significant effects on the microbial community (measured by alpha-and beta-diversity summary statistics, individual taxa, and inferred functional capacity), whereas host genotype had little to no consistent effect across environments. We also identified specific soil factors (pH and potassium) as the most significant environmental drivers of the community, even though these communities were living inside the stalks. ConclusionsTaken together, our results indicate that while host genetics can significantly affect the stalk microbial community, these effects are almost entirely predicated on interactions with the environment. These results imply that reliable deployment of microbes for crop production will require significant investment in trials across many locations and genetic backgrounds, either to estimate the GxE effects directly or to screen for microbes whose effects are less dependent on these two factors.

microbiology↗

bioRxiv2025

A maize near-isogenic line population designed for gene discovery and characterization of allelic effects

In this study we characterized a panel of 1,264 maize near-isogenic lines (NILs), developed from crosses between 18 diverse inbred lines and the recurrent parent B73, referred to as nested NILs (nNILs). 884 of the nNILs were genotyped using genotyping-by-sequencing (GBS). Subsequently, 24 of these nNILs, and all the parental lines, were re-genotyped using a high-density SNP chip. A novel pipeline for calling introgressions, which does not rely on knowing the donor parent of each nNIL, was developed based on a hidden Markov model (HMM) algorithm. By comparing the introgressions detected using GBS data with those identified using chip data, we optimized the HMM parameters for analyzing the entire nNIL population. A total of 2,972 introgressions were identified across the 884 nNILs. Individual introgression blocks ranged from 21 bp to 204 Mbp, with an average size of 17 Mbp. By comparing SNP genotypes within introgressed segments to the known genotypes of the donor lines we determined that in about one third of the lines, the identity of the donors did not match expectation based on their pedigrees. We characterized the entire nNIL population for three foliar diseases. Using these data, we mapped a number of quantitative trait loci (QTL) for disease resistance in the nNIL population and observed extensive variation in effects among the alleles from different donor parents at most QTL identified. This population will be of significant utility for dissecting complex agronomic traits and allelic series in maize. Significance StatementThe study reports the characterization of a publicly available population of 1,264 maize near-isogenic lines largely derived from a single recurrent parent and 18 donor lines. This population is likely to be of significant utility for the characterization of allelic series at loci of interest.

plant biology↗

bioRxiv2024

Global Genotype by Environment Prediction Competition Reveals That Diverse Modeling Strategies Can Deliver Satisfactory Maize Yield Estimates

Predicting phenotypes from a combination of genetic and environmental factors is a grand challenge of modern biology. Slight improvements in this area have the potential to save lives, improve food and fuel security, permit better care of the planet, and create other positive outcomes. In 2022 and 2023 the first open-to-the-public Genomes to Fields (G2F) initiative Genotype by Environment (GxE) prediction competition was held using a large dataset including genomic variation, phenotype and weather measurements and field management notes, gathered by the project over nine years. The competition attracted registrants from around the world with representation from academic, government, industry, and non-profit institutions as well as unaffiliated. These participants came from diverse disciplines include plant science, animal science, breeding, statistics, computational biology and others. Some participants had no formal genetics or plant-related training, and some were just beginning their graduate education. The teams applied varied methods and strategies, providing a wealth of modeling knowledge based on a common dataset. The winners strategy involved two models combining machine learning and traditional breeding tools: one model emphasized environment using features extracted by Random Forest, Ridge Regression and Least-squares, and one focused on genetics. Other high-performing teams methods included quantitative genetics, classical machine learning/deep learning, mechanistic models, and model ensembles. The dataset factors used, such as genetics; weather; and management data, were also diverse, demonstrating that no single model or strategy is far superior to all others within the context of this competition.

genetics↗

bioRxiv2023

Bearded or Smooth? Awns Improve Yield when Wheat Experiences Heat Stress During Grain Fill

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 to estimate the yield effects of awns under different environmental conditions over a 12-year period in the Southeast US. 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.

genetics↗

bioRxiv2021

Not so local: the population genetics of convergent adaptation in maize and teosinte.

What is the genetic architecture of local adaptation and what is the geographic scale over which it operates? We investigated patterns of local and convergent adaptation in five sympatric population pairs of traditionally cultivated maize and its wild relative teosinte (Zea mays subsp. parviglumis). We found that signatures of local adaptation based on the inference of adaptive fixations and selective sweeps are frequently exclusive to individual populations, more so in teosinte compared to maize. However, for both maize and teosinte, selective sweeps are also frequently shared by several populations, and often between subspecies. We were further able to infer that selective sweeps were shared among populations most often via migration, though sharing via standing variation was also common. Our analyses suggest that teosinte has been a continued source of beneficial alleles for maize, even after domestication, and that maize populations have facilitated adaptation in teosinte by moving beneficial alleles across the landscape. Taken together, our results suggest local adaptation in maize and teosinte has an intermediate geographic scale, one that is larger than individual populations but smaller than the species range.

evolutionary biology↗

bioRxiv2021

Domestication Reshaped the Genetic Basis of Inbreeding Depression in a Maize Landrace Compared to its Wild Relative, Teosinte

Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. The extent to which the genetic load of mutations contributing to inbreeding depression is due to rare large-effect variation versus potentially more common variants with very small individual effects is unknown and may be affected by population history. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits, congruent with the greater segregating genetic load predicted from sequence data in the maize population. For many traits - and more commonly in maize - genetic variation among selffertilized families was less than expected based on additive and dominance variance estimated in outcrossed families, suggesting that a negative covariance between additive and homozygous dominance effects limits the variation available to selection under partial inbreeding. We identified quantitative trait loci (QTL) representing large-effect rare variants carried by only a single parent, which were more important in teosinte than maize. Teosinte also carried more putative juvenile-acting lethal variants identified by segregation distortion. These results suggest a mixture of mostly polygenic, smalleffect recessive variation underlying inbreeding depression, with an additional contribution from rare larger-effect variants that was more important in teosinte but depleted in maize following to the domestication bottleneck. Purging associated with the maize domestication bottleneck may have selected against large effect variants, but polygenic load is harder to purge and segregating mutational burden increased in maize compared to teosinte.

evolutionary biology↗

bioRxiv2020

Genetic variation for plant growth traits in a common wheat population is dominated by known variants and novel QTL

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. 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. 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.

genetics↗

bioRxiv2020

Eleven biosynthetic genes explain the majority of natural variation for carotenoid levels in maize grain

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize is a food staple. Extensive natural variation exists for carotenoids in maize grain; to understand its genetic basis, we conducted a joint linkage and genome-wide association study in the U.S. maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percent phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide the most comprehensive genome-level understanding of the genetic and molecular control of carotenoids in any plant system, and a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

genetics↗

bioRxiv2020

Microbiome composition differs in hybrid and inbred maize

O_LIMacroorganisms genotypes shape their phenotypes, which in turn shape the habitat available to potential microbial symbionts. This influence of host genotype on microbiome composition has been demonstrated in many systems; however, most previous studies have either compared unrelated genotypes or delved into molecular mechanisms. As a result, it is currently unclear whether the heritability of host-associated microbiomes follows similar patterns to the heritability of other complex traits. C_LIO_LIWe take a new approach to this question by comparing the microbiomes of diverse maize inbred lines and their F1 hybrid offspring, which we quantified in both rhizosphere and leaves of field-grown plants using 16S-v4 and ITS1 amplicon sequencing. C_LIO_LIWe show that inbred lines and hybrids differ consistently in composition of bacterial and fungal rhizosphere communities, as well as leaf-associated fungal communities. A wide range of microbiome features display heterosis within individual crosses, consistent with patterns for non-microbial maize phenotypes. For leaf microbiomes, these results were supported by the observation that broad-sense heritability in hybrids was substantially higher than narrow-sense heritability. C_LIO_LIOur results support our hypothesis that at least some heterotic host traits affect microbiome composition in maize. C_LI

plant biology↗

bioRxiv2019

The relevance of dominance and functional annotations to predict agronomic traits in hybrid maize

Heterosis has been key to the development of maize breeding but describing its genetic basis has been challenging. Previous studies of heterosis have shown the contribution of within-locus complementation effects (dominance) and their differential importance across genomic regions. However, they have generally considered panels of limited genetic diversity and have shown little benefit to including dominance effects for predicting genotypic value in breeding populations. This study examined within-locus complementation and enrichment of genetic effects by functional classes in maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the United States (1,106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1,640 hybrids). We assayed three agronomic traits: days to silking (DTS), plant height (PH) and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results point to mechanisms by which heterosis arises through local complementation in proximal gene regions and suggest the relevance of dominance and gene annotations for genomic prediction in maize.

genomics↗

bioRxiv2017

Genetic Analysis of Lodging in Diverse Maize Hybrids

Damage caused by lodging is a significant problem in corn production that results in estimated annual yield losses of 5-20%. Over the past 100 years, substantial maize breeding efforts have increased lodging resistance by artificial selection. However, less research has focused on understanding the genetic architecture underlying lodging. Lodging is a problematic trait to evaluate since it is greatly influenced by environmental factors such as wind, rain, and insect infestation, which make replication difficult. In this study over 1,723 diverse inbred maize genotypes were crossed to a common tester and evaluated in five environments over multiple years. Natural lodging due to severe weather conditions occurred in all five environments. By testing a large population of genetically diverse maize lines in multiple field environments, we detected significant correlations for this highly environmentally influenced trait across environments and with important agronomic traits such as yield and plant height. This study also permitted the mapping of quantitative trait loci (QTL) for lodging. Several QTL identified in this study overlapped with loci previously mapped for stalk strength in related maize inbred lines. QTL intervals mapped in this study also overlapped candidate genes implicated in the regulation of lignin and cellulose synthesis.

genetics↗