Biology subjects

Higgins, S. A.

Publications and source records attributed to Higgins, S. A..

6 recordsLinked to original sources

bioRxiv2026

Application of Computer Vision Tools to Maize Genomic Data for Trait Prediction and Gene Discovery

Artificial intelligence and machine learning for computer vision (CV) and image recognition is a rapidly evolving field with multiple potential applications in plant genomics. While CV has been widely adopted by the research community for plant phenotyping and disease surveillance, applications of CV tools to plant genome analysis are underrepresented. CV tools may complement traditional statistical classification tools used in plant genomics, since CV perceives problems holistically rather than granularly (in terms of pattern recognition), which is particularly applicable to analysis of large, complex eukaryotic genomes. In this study, we report on a new strategy to apply existing CV tools to classify plant genotypes and predict genotype-phenotype relationships. A technique was developed for converting maize genome resequencing data into a set of images reminiscent of a quick response (QR) code. Several hundred maize genomes were processed and it was demonstrated that CV models can successfully categorize genome images into heterotic groups (accuracy and recall > 0.8). Models for classifying genome images into phenotypic trait groups (such as short, medium, and high plant height) performed with moderate success for the most heritable trait analyzed (ear height; accuracy and recall > 0.5). Querying model results permitted identification of genome regions that were important for model classification predictions. The CV model results revealed enriched metabolic pathways consistent with traits under consideration. Overall, our initial application of CV tools to plant genome analysis highlights its applicability to genomic data. Design of new CV architectures optimized for genome-derived images may further improve upon our initial results generated using only off-the-shelf CV tools optimized for unrelated image analysis tasks. Core ideasO_LIAI/ML computer vision (CV) tools were applied to encoded maize genomes C_LIO_LICV image classification tools were able to successfully classify encoded genomes into heterotic groups C_LIO_LITrait values of maize strain ear height could be predicted with moderate success C_LIO_LIGenome regions encoding plausible metabolic pathways used by the classifier were identified C_LIO_LIRecommendations for improved success of CV for genotype-to-phenotype are discussed C_LI

bioinformatics↗

bioRxiv2023

Plant-derived, nodule-specific cysteine rich peptides inhibit growth and psyllid acquisition of 'Candidatus Liberibacter asiaticus', the citrus Huanglongbing bacterium

AbstractThe Asian citrus psyllid, Diaphorina citri, is a vector of Candidatus Liberibacter asiaticus (CLas), a gram-negative, obligate biotroph whose infection in Citrus species is associated with citrus greening disease, or Huanglongbing (HLB). Strategies to block CLas transmission by D. citri remain the best way to prevent the spread of the disease into new citrus growing regions. However, identifying control strategies to block HLB transmission poses significant challenges, such as the discovery and delivery of antimicrobial compounds targeting the bacterium and overcoming consumer hesitancy towards accepting the treatment. Here, we computationally identified and tested a series of 20-mer nodule-specific cysteine-rich peptides (NCRs) derived from the Mediterranean legume, Medicago truncatula Gaertn. (barrelclover) to identify those peptides that could effectively prevent or reduce CLas infection in citrus leaves and/or prevent CLas acquisition by the bacteriums insect vector, D. citri. A set of NCR peptides were tested in a screening pipeline involving three distinct assays: a bacterial culture assay, a CLas-infected excised citrus leaf assay, and a CLas-infected nymph acquisition assay that included D. citri nymphs, the only stage of D. citris life-cycle that can acquire CLas leading to the development of vector competent adult insects. We demonstrate that a subset of M. truncatula-derived NCRs inhibit both CLas growth in citrus leaves and CLas acquisition by D. citri from CLas-infected leaves. These findings reveal NCR peptides as a new class and source of biopesticide molecules to control CLas for the prevention and/or treatment of HLB.

plant biology↗

bioRxiv2022

Direct DNA sequencing of "Candidatus Liberibacter asiaticus" from Diaphorina citri, the Asian citrus psyllid, and its implications for citrus greening disease management

The Asian citrus psyllid, Diaphorina citri is an invasive insect 1 and a vector of Candidatus Liberibacter asiaticus (CLas), a bacterium whose growth in Citrus species results in citrus greening disease 2,3. Methods to enrich and sequence CLas from D. citri often rely on biased genome amplification 4 and nevertheless contain significant quantities of host DNA 5,6. To overcome these hurdles, we developed a simple pre-treatment DNase and filtration (hereafter PDF) protocol to directly sequence CLas and the complete, primarily uncultivable, microbiome from D. citri adults. The PDF protocol yielded CLas abundances upwards of 60% and enabled detection of 156 genetic variants in these strains compared to progenitor strains in Florida, which included prophage encoding regions with key functions in CLas pathogenesis, putative antibiotic resistance loci, and a single secreted effector. These variants suggest laboratory propagation of CLas may result in different phenotypic trajectories among laboratories, and may confound CLas physiology or therapeutic design and evaluation if these differences remain undocumented. Finally, we obtained genetic signatures affiliated with Citrus nuclear and organellar genomes, entomopathogenic fungal mitochondria, and commensal bacteria from laboratory-reared and field-collected D. citri adults. Hence, the PDF protocol can inform agricultural management strategies related to pathogen evolution 7, insect microbiome surveillance 8, antibiotic resistance screening 9, and gut content analysis 10.

microbiology↗

bioRxiv2020

Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules

Proteins evolve through the modular rearrangement of elements known as domains. It is hypothesized that extant, multidomain proteins are the result of domain accretion, but there has been limited experimental validation of this idea. Here, we introduce a technique for genetic minimization by iterative size-exclusion and recombination (MISER) that comprehensively assays all possible deletions of a protein. Using MISER, we generated a deletion landscape for the CRISPR protein Cas9. We found that Cas9 can tolerate large single deletions to the REC2, REC3, HNH, and RuvC domains, while still functioning in vitro and in vivo, and that these deletions can be stacked together to engineer minimal, DNA-binding effector proteins. In total, our results demonstrate that extant proteins retain significant modularity from the accretion process and, as genetic size is a major limitation for viral delivery systems, establish a general technique to improve genome editing and gene therapy-based therapeutics.

molecular biology↗

bioRxiv2020

The biogeography of Streptomyces in New Zealand enabled by high-throughput sequencing of genus-specific rpoB amplicons

We evaluated Streptomyces biogeography in soils along a 1,200 km latitudinal transect across New Zealand (NZ). Streptomyces diversity was examined using high-throughput sequencing of rpoB amplicons generated with a Streptomyces specific primer set. We detected 1,287 Streptomyces rpoB operational taxonomic units (OTUs) with 159 {+/-} 92 (average {+/-} s.d.) rpoB OTUs per site. Only 12% (n = 149) of these OTUs matched rpoB sequences from cultured specimens (99% nucleotide identity cutoff). Streptomyces phylogenetic diversity (Faiths PD) was correlated with soil pH, mean annual temperature, and plant community richness (Spearmans r: 0.77, 0.64, and -0.79, respectively; p < 0.05), but not with latitude. In addition, soil pH and plant community richness both explained significant variation in Streptomyces beta diversity. Streptomyces communities exhibited both high dissimilarity and strong dominance of one or a few species at each site. Taken together, these results suggest that dispersal limitation due to competitive interactions limits the colonization success of spores that relocate to new sites. Cultivated Streptomyces isolates represent a major source of clinically useful antibiotics, but only a small fraction of extant diversity within the genus have been identified and most species of Streptomyces have yet to be described.

microbiology↗

bioRxiv2018

Phylogenomics reveals dynamic evolution of fungal nitric oxide reductases and their relationship to secondary metabolism

Fungi expressing P450nor, an unconventional nitric oxide (NO) reducing cytochrome P450, are thought to be significant contributors to soil nitrous oxide (N2O) emissions. However, fungal contributions to N2O emissions remain uncertain due to inconsistencies in measurements of N2O formation by fungi. Much of the N2O emitted from antibiotic-amended soil microcosms is attributed to fungal activity, yet fungal isolates examined in pure culture are poor N2O producers. To assist in reconciling these conflicting observations and produce a benchmark genomic analysis of fungal denitrifiers, genes underlying fungal denitrification were examined in >700 fungal genomes. Of 167 p450nor-containing genomes identified, 0, 30, and 48 also harbored the denitrification genes narG, napA or nirK, respectively. Compared to napA and nirK, p450nor was twice as abundant and exhibited two to five-fold more gene duplications, losses, and transfers, indicating a disconnect between p450nor presence and denitrification potential. Furthermore, co-occurrence of p450nor with genes encoding NO-detoxifying flavohemoglobins (Spearman r = 0.87, p = 1.6e-10) confounds hypotheses regarding P450nors primary role in NO detoxification. Instead, ancestral state reconstruction united P450nor with actinobacterial cytochrome P450s (CYP105) involved in secondary metabolism (SM) and 19 (11 %) p450nor-containing genomic regions were predicted to be SM clusters. Another 40 (24 %) genomes harbored genes nearby p450nor predicted to encode hallmark SM functions, providing additional contextual evidence linking p450nor to SM. These findings underscore the potential physiological implications of widespread p450nor gene transfer, support the novel affiliation of p450nor with fungal SM, and challenge the hypothesis of p450nors primary role in denitrification.

microbiology↗