Biology subjects

Hale, B.

Publications and source records attributed to Hale, B..

3 recordsLinked to original sources

bioRxiv2022

A transcriptome atlas of Striga hermonthica germination

Societal Impact StatementWitchweeds, parasitic plants of the genus Striga, are nicknamed "cereal killers" because of their devasting destruction of Africas most staple cereals, including maize, sorghum, millets, and upland rice. The parasite relies on biomolecules emitted from the host roots to germinate and therefore initiate its infectious lifecycle. Some sorghum varieties have evolved to not produce effective germination stimulants, making them resistant to the parasite. Here, we assess genetic factors that underpin Striga germination. We discuss how such knowledge can be used to develop new Striga management strategies through the disruption of host-parasite communication exchange. SummaryO_LISeeds of the parasitic plant Striga are dormant. They only germinate in response to biomolecules emitted from the hosts root exudate, strigolactones (SL). But, it is now emerging that Striga germination is a much more complex process regulated by crosstalk of hormone signaling pathways. C_LIO_LITo further understand the genetic basis of the communication exchange between Striga and its host sorghum, we performed a comparative transcriptomic analysis. We sought to identify major transcriptomic changes that define the germination process in Striga and a set of genes that may contribute to the differences in germination rates. C_LIO_LIResults showed that germination proceeds immediately after SL perception and is marked by a wave of transcriptional reprogramming to allow for metabolic processes of energy mobilization. Cluster analysis using self-organizing maps (SOMs) revealed a time-phased and genotype-differentiated response to germination stimulation. The variation in germination was also a function of hormonal crosstalk. The early germination stage was associated with significant repression of genes in the abscisic acid (ABA) biosynthesis pathway. Other hormones influenced germination as follows: (i) ABA and auxin repressed germination, (ii) brassinosteroid, ethylene and jasmonic acid promoted germination, and (iii) cytokinin had a more prominent role post-germination rather than during germination. Perception of SL sets the germination programme leading to different rates of germination in sorghum followed by a complex hormonal regulation network that acts to either repress or enhance germination. These results have far-reaching implications for developing Striga management strategies by disrupting hormonal communication exchange. C_LI

plant biology↗

bioRxiv2022

Resolving intergenotypic Striga resistance in sorghum

Genetic underpinnings of host-pathogen interactions in the parasitic plant Striga hermonthica,a root parasitic plant that ravages cereals in sub-Saharan Africa, are unclear. We performed a comparative transcriptome study on five genotypes of sorghum exhibiting diverse resistance responses to S. hermonthica using weighted gene co-expression network analysis (WGCNA). We found that S. hermonthica elicits both basal and effector-triggered immunity - like a bona fide pathogen. Resistance response was genotype-specific. Some resistance responses followed the salicylic acid-dependent signaling pathway for systemic acquired resistance characterized by cell wall reinforcements, lignification and callose deposition while in others the WRKY-dependent signaling pathway was activated leading to a hypersensitive response (HR). In some genotypes, both modes of resistance were activated while in others, either mode dominated the resistance response. Cell-wall-based resistance was common to all sorghum genotypes but strongest in IS2814, while HR-based response was specific to N13, IS9830 and IS41724. WGCNA further allowed for pinpointing of S. hermonthica resistance causative genes in sorghum. Some highlights include a Glucan synthase-like 10, a pathogenesis-related thaumatin-like family, and a phosphoinositide phosphatase gene. Such candidate genes will form a good basis for subsequent functional validation and possibly future resistance breeding. HighlightParasitic plants of the Striga genus are major pests to cereals in Africa. We pinpointed genetic causes of Striga resistance in sorghum that can be harnessed for future resistance breeding.

plant biology↗

bioRxiv2022

Gene regulatory network inference in soybean upon infection by Phytophthora sojae

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean (Glycine max [L.] Merrill). Yield losses attributed to P. sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P. sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P. sojae. In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P. sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis (Arabidopsis thaliana) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P. sojae. Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P. sojae. Author SummaryGlobal food security is threatened continually by plant pathogens. One approach to circumvent these disease-causing agents entails understanding how hosts balance primary growth and defense upon pathogen perception. Molecular signatures of perception-rendered defense may be leveraged subsequently to develop resistant/tolerant crop plants. Additionally, evidence suggests that the plant immune system is characterized by tuning primary and secondary metabolic activity via transcription factor-mediated transcriptional reprogramming. Therefore, we investigated transcription factor-target gene interactions in soybean upon infection by compatible and incompatible races of Phytophthora sojae. Through transcriptome analysis, we found that the interactions elicited vast, overlapping transcriptional responses and identified overrepresented, defense-related transcription factor families. We then generated/acquired DNA-protein interactome data for the most represented transcription factor families in the transcriptome analysis and trained deep learning-based models to predict novel transcription factor targets. Transcription factor/target gene metrics were used to construct a gene regulatory network with prioritized components. We identified hub transcription factors belonging to WRKY and ERF families, the majority of which function in response to various biotic and abiotic stressors. These findings propose novel regulators in the soybean defense response to Phytophthora sojae and provide an avenue for the investigation of transcription factor-target gene interactions in plants.

plant biology↗