Biology subjects

Hirsch, C. D.

Publications and source records attributed to Hirsch, C. D..

14 recordsLinked to original sources

bioRxiv2024

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits

Plant height can be an indicator of plant health across environments and used to identify superior genotypes or evaluate abiotic stress factors. Typically plant height is measured at a single time point when plants have reached terminal height for the season. Evaluating plant height using unoccupied aerial vehicles (UAVs) is faster, allowing for measurements throughout the growing season, which facilitates a better understanding of plant-environment interactions and the genetic basis of this complex trait. To assess variation throughout development, plant height data was collected weekly for a panel of [~]500 diverse maize inbred lines over four growing seasons. The variation in plant height throughout the season was significantly explained by genotype, year, and genotype-by-year interactions to varying extents throughout development. Genome-wide association studies revealed significant SNPs associated with plant height and growth rate at different parts of the growing season specific to certain phases of vegetative growth that would not be identified by terminal height associations alone. When plant height growth rates were compared to growth rates estimated from canopy cover, greater Frechet distance stability was observed in plant height growth curves than for canopy cover. This indicated canopy cover may be more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. This study demonstrated that substantial information can be gained from high temporal resolution data to understand how plants differentially interact with the environment and can enhance our understanding of the genetic basis of complex polygenic traits.

plant biology↗

bioRxiv2024

Dissecting the temporal phenomics and genomics of maize canopy cover using UAV mediated image capture

Canopy cover is an important agronomic trait influencing photosynthesis, weed suppression, biomass accumulation, and yield. Conventional methods to quantify canopy cover are time and labor-intensive. As such, little is known about how canopy cover develops over time, the stability of canopy cover across environments, or the genetic architecture of canopy cover. We used unoccupied aerial vehicle-mediated image capture to quantify plot-level canopy coverage in maize throughout the growing season. Images of 501 diverse inbred lines were acquired between 300 and 1300 growing degree days in the 2018-2021 growing seasons. We observed that the maize canopy developed following a logistic curve. Phenotypic variation in percent canopy coverage and canopy growth rate was explained by genetic and environmental factors and genotype-by-environment interactions, however the percent of variance explained by each factor varied throughout the growing season. Environmental factors explained the largest portion of trait variance during the adult vegetative growth stage and had a larger impact on canopy growth rates than percent canopy coverage. We conducted multiple genome wide association studies and found that canopy cover is a complex, polygenic trait with a diverse range of marker trait associations throughout development. The change in associations indicated that single time point phenotyping was insufficient to capture the full phenomic and genetic diversity of canopy cover in maize.

plant biology↗

bioRxiv2024

Plant height defined growth curves during vegetative development have the potential to predict end of season maize yield and assist with mid-season management decisions

Precision farming has been developing with the intention of identifying within field variability to adjust management strategies and maximize end of season yield and profitability and minimize negative environmental impacts. The development of quick, easy, and low cost methods to quantify field level variation is essential to successful implementation of precision agriculture at scale. Temporal plant height and growth rates collected with unoccupied aerial vehicles mounted with red, green, blue sensors have the potential to predict end of season grain yield, which could facilitate mid-season management decisions. Image-based plant height data was collected weekly from commercial maize fields in three growing seasons to assess variation within fields and the relationship with grain yield variation. Plant height, growth rate, and grain yield had variable relationships depending on the time point and growth environment. Models developed using temporal traits predicted grain yield variation within a commercial field up to r = 0.7, though insufficient water affected the prediction accuracy in one field due to the limited representation of drought environments in the model development. In the future, with more data from stress environments, such as drought, this method has potential for high accuracy grain yield prediction across a range of environmental conditions. This study demonstrates the potential of using unoccupied aerial vehicles to derive vegetative growth patterns and model within field variations, and has application in making mid-season management decisions.

plant biology↗

bioRxiv2023

An RGB based deep neural network for high fidelity Fusarium head blight phenotyping in wheat

Fusarium head blight (FHB) in wheat is an economically important disease, which can cause yield losses exceeding 50% and the causal pathogen that infects spikes produces harmful mycotoxins. Breeding for host resistance remains the most effective disease control method; but time, labor, and human subjectivity during disease scoring limits selection advancements. In this study we describe an innovative, high-throughput phenotyping rover for capturing in-field RGB images and a deep neural network pipeline for wheat spike detection and FHB disease quantification. The image analysis pipeline successfully detects wheat spikes from images under variable field conditions, segments spikes and diseased tissue in the spikes, and quantifies disease severity as the region of intersection between spike and disease masks. Model inferences on an individual spike and plot basis were compared to human visual disease scoring in the field and on imagery for model evaluation. The precision and throughput of the model surpassed traditional field rating methods. The accuracy of FHB severity assessments of the model was equivalent to human disease annotations of images, however individual spike disease assessment was influenced by field location. The model was able to quantify FHB in images taken with different camera orientations in an unseen year, which demonstrates strong generalizability. This innovative pipeline represents a breakthrough in FHB phenotyping, offering precise and efficient assessment of FHB on both individual spikes and plot aggregates. The model is robust to different conditions and the potential to standardize disease evaluation methods across the community make it a valuable tool for studying and managing this economically significant fungal disease.

plant biology↗

bioRxiv2022

DNA-based detection of Aphanomyces cochlioides in soil and sugar beet plants

Aphanomyces cochlioides, the causal agent of seedling damping-off and Aphanomyces root rot (ARR) of sugar beet, causes yield losses in major sugar beet growing regions. Currently, a 4-week soil bioassay and a 2-day culture-based assay are used to diagnose presence of A. cochlioides. However, these assays can be time-consuming and lack sensitivity. In this study we developed a sensitive, specific, and rapid assay to detect and quantify DNA of A. cochlioides. We developed a TaqMan qPCR assay targeting a region of the mitochondrial genome of A. cochlioides representing a unique gene order for Aphanomyces with genus-specific primers and a species-specific probe. The qPCR assay detected A. cochlioides in 12 naturally infested field soil samples with disease severity index (DSI) values of 48-100, in sugar beet seedlings 5-7 days after planting, and with as little as 1 fg of pure A. cochlioides DNA. Adult sugar beet roots with ARR symptoms were sampled to further validate this qPCR assay. Aphanomyces cochlioides was detected in 95% of these samples using this qPCR assay, while only 23% of the same samples were positive using a culture-based assay. This shows the improved sensitivity of this qPCR assay for disease diagnosis and could provide growers with ARR risk of a field, which would help them make informed disease management decisions. However, further research is required to translate the results of this study to growers fields to quantify A. cochlioides with a high degree of accuracy.

plant biology↗

bioRxiv2021

A reference genome sequence resource for the sugar beet root rot pathogen Aphanomyces cochlioides

Aphanomyces cochlioides, the causal agent of damping-off and root rot of sugar beet (Beta vulgaris L.), is a soil-dwelling oomycete responsible for yield losses in all major sugar beet growing regions. Currently, genomic resources for A. cochlioides are limited. Here we report a de novo genome assembly using a combination of long-read MinION (Oxford Nanopore Technologies) and short-read Illumina sequence data for A. cochlioides isolate 103-1, from Breckenridge, MN. The assembled genome was 76.3 Mb, with a contig N50 of 2.6 Mb. The reference assembly was annotated and was composed of 32.1% repetitive elements and 20,274 gene models. This high-quality genome assembly of A. cochlioides will be a valuable resource for understanding genetic variation, virulence factors, and comparative genomics of this important sugar beet pathogen.

genomics↗

bioRxiv2021

Identification of candidate susceptibility genes to Puccinia graminis f. sp. tritici in wheat

Wheat stem rust disease caused by Puccinia graminis f. sp. tritici (Pgt) is a global threat to wheat production. Fast evolving populations of Pgt limit the efficacy of plant genetic resistance and constrain disease management strategies. Understanding molecular mechanisms that lead to rust infection and disease susceptibility could deliver novel strategies to deploy crop resistance through genetic loss of disease susceptibility. We used comparative transcriptome-based and orthology-guided approaches to characterize gene expression changes associated with Pgt infection in susceptible and resistant Triticum aestivum genotypes as well as the non-host Brachypodium distachyon. We targeted our analysis to genes with differential expression in T. aestivum and genes suppressed or not affected in B. distachyon and report several processes potentially linked to susceptibility to Pgt, such as cell death suppression and impairment of photosynthesis. We complemented our approach with a gene co-expression network analysis to identify wheat targets to deliver resistance to Pgt through removal or modification of putative susceptibility genes.

plant biology↗

bioRxiv2020

Evaluating the Effects of Propiconazole on Hard Fescue (Festuca brevipila) via RNA sequencing and Liquid Chromatography Mass Spectrometry

Propiconazole is often used to remove fungal endophytes from turfgrass to study the effects of Epichloe endophytes. However, besides a fungicidal effect, propiconazole can bind to the genes in the cytochrome P450 family and affect the biosynthesis of brassinosteroids. For this reason, outside of fungicidal application, propiconazole has also been used as plant growth regulator. In this study, we used a combination of RNA sequencing and liquid chromatography-mass spectrometry (LC-MS) to study how hard fescue (Festuca brevipila) responded to the high dose of propiconazole treatment. To test the long-term effect of the heavy use of propiconazole on plants, we inoculated with Microdochium nivale (causal agent of pink snow mold) half year post the last fungicide application. Propiconazole-treated plants showed enhanced pink snow mold resistance. This study suggested that the high dose use of propiconazole fungicide resulted in phenotypic and physiological changes in the plant such as slow growth and change in disease resistance. Genes and pathways affected by propiconazole identified in this study provide turfgrass breeders new information for genetic improvement of hard fescue and also provide turfgrass management new ways to control turfgrass diseases.

plant biology↗

bioRxiv2020

Building a Reference Transcriptome for the Hexaploid Hard Fescue Turfgrass (Festuca brevipila) Using a Combination of PacBio IsoSeq and Illumina Sequencing

BackgroundHard fescue (Festuca brevipila Tracey, 2n=6x=42) is a cool season turfgrass with a fine leaf texture that performs well under low-input management. Breeding and genetics studies of F. brevipila have been limited due to the complexity of its hexaploid genome. To advance our knowledge of F. brevipila genomics, we used PacBio isoform sequencing to develop a reference transcriptome for this species. ResultsHere, we report the F. brevipila reference transcriptome generated from root, crown, leaf, and inflorescence tissues. We obtained 59,510 full-length transcripts, of which 38,556 were non-redundant full-length transcripts. The longest and shortest transcripts were 11,487 and 58 bp, respectively. Distribution of synonymous distances among paralogs within F. brevipila suggested highly similar subgenomes that are difficult to distinguish from sequencing errors. To evaluate the phylogenetic relationships among F. brevipila and close relatives, we sequenced three additional transcriptomes using closely related species on an Illumina platform. The results of our phylotranscriptomic analysis supported the close relationships among F. brevipila (6x), Festuca ovina (4x), Festuca ovina subsp. ovina (2x), and Festuca valesiaca (2x), with high levels of discordance among gene trees. ConclusionsOverall, the F. brevipila PacBio Isoseq reference transcriptome provided the foundation for transcriptome studies and allowed breeders a resource for gene discovery in this important turfgrass species.

plant biology↗

bioRxiv2019

Chloroplast Genome Sequencing and Comparative Analysis for Five Species of the Turfgrass Fine Fescues (Festuca L., Poaceae)

Fine fescues (Festuca L., Poaceae) are turfgrass species that perform well in low-input environments. Based on morphological characteristics, the most commonly-utilized fine fescues are divided into five taxa: three are subspecies within F. rubra L. and the remaining two are treated as species within the F. ovina L. complex. Morphologically, these five taxa are very similar, both identification and classification of fine fescues remain challenging. In an effort to develop identification methods for fescues, we used flow cytometry to estimate genome size, ploidy level, and sequenced the chloroplast genome of all five taxa. Fine fescue chloroplast genome sizes ranged from 133,331 to 133,841 bp and contained 113 to 114 genes. Phylogenetic relationship reconstruction using whole chloroplast genome sequences agreed with previous work based on morphology. Comparative genomics suggested unique repeat signatures for each fine fescue taxon that could potentially be used for marker development for taxon identification.

plant biology↗

bioRxiv2019

Dynamic patterns of transcript abundance of transposable element families in maize

Transposable Elements (TEs) are mobile elements that contribute the majority of DNA sequences in the maize genome. Due to their repetitive nature, genomic studies of TEs are complicated by the difficulty of properly attributing multi-mapped short reads to specific genomic loci. Here, we utilize a method to attribute RNA-seq reads to TE families rather than particular loci in order to characterize transcript abundance for TE families in the maize genome. We applied this method to assess per-family expression of transposable elements in >800 published RNA-seq libraries representing a range of maize development, genotypes, and hybrids. While a relatively small proportion of TE families are transcribed, expression is highly dynamic with most families exhibiting tissue-specific expression. A large number of TE families were specifically detected in pollen and endosperm, consistent with reproductive dynamics that maintain silencing of TEs in the germ line. We find that B73 transcript abundance is a poor predictor of TE expression in other genotypes and that transcript levels can differ even for shared TEs. Finally, by assessing recombinant inbred line and hybrid transcriptomes, complex patterns of TE transcript abundance across genotypes emerged. Taken together, this study reveals a dynamic contribution of TEs to maize transcriptomes.

genomics↗

bioRxiv2019

Transposable elements contribute to dynamic genome content in maize

Transposable elements (TEs) are ubiquitous components of eukaryotic genomes and can create variation in genomic organization. The majority of maize genomes are composed of TEs. We developed an approach to define shared and variable TE insertions across genome assemblies and applied this method to four maize genomes (B73, W22, Mo17, and PH207). Among these genomes we identified 1.6 Gb of variable TE sequence representing a combination of recent TE movement and deletion of previously existing TEs. Although recent TE movement only accounted for a portion of the TE variability, we identified 4,737 TEs unique to one genome with defined insertion sites in all other genomes. Variable TEs are found for all superfamilies and are distributed across the genome, including in regions of recent shared ancestry among individuals. There are 2,380 genes annotated in the B73 genome located within variable TEs, providing evidence for the role of TEs in contributing to the substantial differences in gene content among these genotypes. The large scope of TE variation present in this limited sample of temperate maize genomes highlights the major contribution of TEs in driving variation in genome organization and gene content. Significance StatementThe majority of the maize genome is comprised of transposable elements (TEs) that have the potential to create genomic variation within species. We developed a method to identify shared and non-shared TEs using whole genome assemblies of four maize inbred lines. Variable TEs are found throughout the maize genome and in comparisons of any two genomes we find ~20% of the genome is due to non-shared TEs. Several thousand maize genes are found within TEs that are variable across lines, highlighting the contribution of TEs to gene content variation. This study creates a comprehensive resource for genomic studies of TE variability among four maize genomes, which will enable studies on the consequences of variable TEs on genome function.

genomics↗

bioRxiv2018

Classifying cold stress responses of inbred maize seedlings using RGB imaging

Increasing the tolerance of maize seedlings to low temperature episodes could mitigate the effects of increasing climate variability on yield. To aid progress toward this goal, we established a growth chamber-based system for subjecting seedlings of 40 maize inbred genotypes to a defined, temporary cold stress while collecting digital profile images over a 9-day time course. Image analysis performed with PlantCV software quantified shoot height, shoot area, 14 other morphological traits, and necrosis identified by color analysis. Hierarchical clustering of changes in growth rates of morphological traits and quantification of leaf necrosis over two time intervals resulted in three clusters of genotypes, which are characterized by unique responses to cold stress. For any given genotype, the set of traits with similar growth rates is unique. However, the patterns among traits are different between genotypes. Cold sensitivity was not correlated with the latitude where the inbred varieties were released suggesting potential further improvement for this trait. This work will serve as the basis for future experiments investigating the genetic basis of recovery to cold stress in maize seedlings.

plant biology↗

bioRxiv2017

De novo assembly and phasing of dikaryotic genomes from two isolates of Puccinia coronata f. sp. avenae, the causal agent of oat crown rust

Oat crown rust, caused by the fungus Puccinia coronata f. sp. avenae (Pca), is a devastating disease that impacts worldwide oat production. For much of its life cycle, Pca is dikaryotic, with two separate haploid nuclei that may vary in virulence genotype, highlighting the importance of understanding haplotype diversity in this species. We generated highly contiguous de novo genome assemblies of two Pca isolates, 12SD80 and 12NC29, from long-read sequences. In total, we assembled 603 primary contigs for a total assembly length of 99.16 Mbp for 12SD80 and 777 primary contigs with a total length of 105.25 Mbp for 12NC29, and approximately 52% of each genome was assembled into alternate haplotypes. This revealed structural variation between haplotypes in each isolate equivalent to more than 2% of the genome size, in addition to about 260,000 and 380,000 heterozygous single-nucleotide polymorphisms in 12SD80 and 12NC29, respectively. Transcript-based annotation identified 26,796 and 28,801 coding sequences for isolates 12SD80 and 12NC29, respectively, including about 7,000 allele pairs in haplotype-phased regions. Furthermore, expression profiling revealed clusters of co-expressed secreted effector candidates, and the majority of orthologous effectors between isolates showed conservation of expression patterns. However, a small subset of orthologs showed divergence in expression, which may contribute to differences in virulence between 12SD80 and 12NC29. This study provides the first haplotype-phased reference genome for a dikaryotic rust fungus as a foundation for future studies into virulence mechanisms in Pca.\n\nImportanceDisease management strategies for oat crown rust are challenged by the rapid evolution of Puccinia coronata f. sp. avenae (Pca), which renders resistance genes in oat varieties ineffective. Despite the economic importance of understanding Pca, resources to study the molecular mechanisms underpinning pathogenicity and emergence of new virulence traits are lacking. Such limitations are partly due to the obligate biotrophic lifestyle of Pca as well as the dikaryotic nature of the genome, features that are also shared with other important rust pathogens. This study reports the first release of a haplotype-phased genome assembly for a dikaryotic fungal species and demonstrates the amenability of using emerging technologies to investigate genetic diversity in populations of Pca.

genomics↗