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Jones, R.

Publications and source records attributed to Jones, R..

3 recordsLinked to original sources

Modeling Spatial Correlation of Transcripts With Application to Developing Pancreas

Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. As an illustration, we analyze the spatial distribution of single mRNA molecules measured by in situ sequencing on human fetal pancreas at three developmental time points 80, 87 and 117 days post-fertilization. We develop a density profile-based method to capture the spatial relationship between gene expression and other morphological features of the tissue sample such as position of nuclei and endocrine cells of the pancreas. In addition, we build a statistical model to characterize correlations in the spatial distribution of the expression level among different genes. This model enables us to infer the inhibitory and clustering effects throughout different time points. Our analysis framework is applicable to a wide variety of spatially-resolved transcriptomic data to derive biological insights.

bioinformatics

A fungal ribonuclease-like effector protein inhibits plant host ribosomal RNA degradation

The biotrophic fungal pathogen Blumeria graminis causes the powdery mildew disease of cereals and grasses. Proteins with a predicted ribonuclease (RNase)-like fold (termed RALPHs) comprise the largest set of secreted effector candidates within the B. graminis f. sp. hordei genome. Their exceptional abundance suggests they play crucial functions during pathogenesis. We show that transgenic expression of RALPH CSEP0064/BEC1054 increases susceptibility to infection in monocotyledenous and dicotyledonous plants. CSEP0064/BEC1054 interacts in planta with five host proteins: two translation elongation factors (eEF1 and eEF1{gamma}), two pathogenesis-related proteins (PR5 and PR10) and a glutathione-S-transferase. We present the first crystal structure of a RALPH, CSEP0064/BEC1054, demonstrating it has an RNase-like fold. The protein interacts with total RNA and weakly with DNA. Methyl jasmonate levels modulate susceptibility to aniline-induced host RNA fragmentation. In planta expression of CSEP0064/BEC1054 reduces the formation of this RNA fragment. We propose that CSEP0064/BEC1054 is a pseudoenzyme that binds to host ribosomes, thereby inhibiting the action of plant ribosome-inactivating proteins that would otherwise lead to host cell death, an unviable interaction and demise of the fungus.

plant biology

A risk assessment framework for seed degeneration: Informing an integrated seed health strategy for vegetatively-propagated crops

Pathogen build-up in vegetative planting material, termed seed degeneration, is a major problem in many low-income countries. When smallholder farmers use seed produced on-farm or acquired outside certified programs, it is often infected. We introduce a risk assessment framework for seed degeneration, evaluating the relative performance of individual and combined components of an integrated seed health strategy. The frequency distribution of management performance outcomes was evaluated for models incorporating biological and environmental heterogeneity, with the following results. (1) On-farm seed selection can perform as well as certified seed, if the rate of success in selecting healthy plants for seed production is high; (2) When choosing among within-season management strategies, external inoculum can determine the relative usefulness of incidence-altering management (affecting the proportion of diseased plants/seeds) and rate-altering management (affecting the rate of disease transmission in the field); (3) Under severe disease scenarios, where it is difficult to implement management components at high levels of effectiveness, combining management components can produce synergistic benefits and keep seed degeneration below a threshold; (4) Combining management components can also close the yield gap between average and worst-case scenarios. We also illustrate the potential for expert elicitation to provide parameter estimates when data are unavailable.

epidemiology