Biology subjects

Mahood, E. H.

Publications and source records attributed to Mahood, E. H..

3 recordsLinked to original sources

bioRxiv2023

A comparative approach for selecting orthologous candidate genes underlying signal in genome-wide association studies across multiple species

Advances in quantitative genetics have enabled researchers to identify genomic regions associated with changes in phenotype. However, genomic regions can contain hundreds to thousands of genes, and progressing from genomic regions to causative genes is still challenging. In genome-wide association studies (GWAS) measuring elemental accumulation (ionomic) traits, only 5% of loci overlap genes known to control the ionome - indicating that many causal genes are still unknown. To identify candidates for the remaining 95% loci, we developed a method that uses GWAS studies across multiple species to identify conserved causative genes. By Filtering the Results of Multi-species, Analogous, GWAS Experiments (FiREMAGE) we were able to take the GWAS of 19 ionomic traits in Arabidopsis, soybean, rice, maize, and sorghum, and identify alleles affecting trait variation at conserved genes. Permutation testing demonstrated that GWAS loci affecting the same trait contained homologs more often than expected by chance. Most of the top 10% most significant conserved candidate sets encoded alleles in all five species, highlighting the conservation of ionomic genetic regulators in flowering plants. The candidates include proteins with known biochemical functions that regulate the ionome, validating the approach. In addition to genes with known functions, this approach also identified many conserved genes underlying GWAS loci affecting the same trait in multiple species that have no previously identified function in regulating the ionome, providing a path to discover the as yet unknown mechanisms of element accumulation in plants. This method enables the identification of conserved genes of previously unknown function via GWAS. Author summaryQuantitative genetics identifies a genomic region of interest but not the causal gene. We developed an approach to narrow these gene lists using genetic loci affecting elemental (i.e., calcium, iron, zinc) accumulation. Comparative genomics and GWAS demonstrates that alleles at evolutionarily conserved genes alter the same phenotype in multiple species. This produced a list of conserved candidate genes including previously known elemental regulators and genes whose elemental accumulation mechanism has yet to be determined. Combining datasets across species boosted the signal at these loci. This approach accelerates the discovery of new functional roles of genes.

genetics↗

bioRxiv2022

Characterization and visualization of global metabolomic responses of Brachypodium distachyon to environmental changes

Plant responses to environmental change are mediated via changes in cellular metabolomes. However, <5% of signals obtained from tandem liquid chromatography mass spectrometry (LC-MS/MS) can be identified, limiting our understanding of how different metabolite classes change under biotic/abiotic stress. To address this challenge, we performed untargeted LC-MS/MS of leaves, roots and other organs of Brachypodium distachyon, a model Poaceae species, under 17 different organ-condition combinations, including copper deficiency, heat stress, low phosphate and arbuscular mycorrhizal symbiosis (AMS). We used a combination of information theory-based metrics and machine learning-based identification of metabolite structural classes to assess metabolomic changes. Both leaf and root metabolomes were significantly affected by the growth medium. Leaf metabolomes were more diverse than root metabolomes, but the latter were more specialized and more responsive to environmental change. We also found that one week of copper deficiency shielded the root metabolome, but not the leaf metabolome, from perturbation due to heat stress. Using a recently published deep learning based method for metabolite class predictions, we analyzed the responsiveness of each metabolite class to environmental change, which revealed significant perturbations of various lipid classes and phenylpropanoids such as cinnamic acids and flavonoids. Co-accumulation analysis further identified condition-specific metabolic biomarkers. Finally, to make these results publicly accessible, we developed a novel visualization platform on the Bioanalytical Resource website, where significantly perturbed metabolic classes can be readily visualized. Overall, our study illustrates how emerging chemoinformatic methods can be applied to reveal novel insights into the dynamic plant metabolome and plant stress adaptation.

plant biology↗

bioRxiv2021

Computational metabolomics illuminates the lineage-specific diversification of resin glycoside acylsugars in the morning glory (Convolvulaceae) family

Acylsugars are a class of plant defense compounds produced across many distantly related families. Members of the horticulturally important morning glory (Convolvulaceae) family produce a diverse sub-class of acylsugars called resin glycosides (RGs), which comprise oligosaccharide cores, hydroxyacyl chain(s), and decorating aliphatic and aromatic acyl chains. While many RG structures are characterized, the extent of structural diversity of this class in different genera and species is not known. In this study, we asked whether there has been lineage-specific diversification of RG structures in different Convolvulaceae species that may suggest diversification of the underlying biosynthetic pathways. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was performed from root and leaf extracts of 26 species sampled in a phylogeny-guided manner. LC-MS/MS revealed thousands of peaks with signature RG fragmentation patterns with one species producing over 300 signals, mirroring the diversity in Solanaceae-type acylsugars. A novel RG from Dichondra argentea was characterized using Nuclear Magnetic Resonance spectroscopy, supporting previous observations of RGs with open hydroxyacyl chains instead of closed macrolactone ring structures. Substantial lineage-specific differentiation in utilization of sugars, hydroxyacyl chains, and decorating acyl chains was discovered, especially among Ipomoea and Convolvulus - the two largest genera in Convolvulaceae. Adopting a computational, knowledge-based strategy, we further developed a high-recall workflow that successfully explained ~72% of the MS/MS fragments, predicted the structural components of 11/13 previously characterized RGs, and partially annotated ~45% of the RGs. Overall, this study improves our understanding of phytochemical diversity and lays a foundation for characterizing the evolutionary mechanisms underlying RG diversification.

plant biology↗