Dataset Information

Evidence of a trans-kingdom plant disease complex between a fungus and plant-parasitic nematodes.

ABSTRACT: Disease prediction tools improve management efforts for many plant diseases. Prediction and downstream prevention demand information about disease etiology, which can be complicated for some diseases, like those caused by soilborne microorganisms. Fortunately, the availability of machine learning methods has enabled researchers to elucidate complex relationships between hosts and pathogens without invoking difficult-to-satisfy assumptions. The etiology of a destructive plant disease, Verticillium wilt of mint, caused by the fungus Verticillium dahliae was reevaluated with several supervised machine learning methods. Specifically, the objective of this research was to identify drivers of wilt in commercial mint fields, describe the relationships between these drivers, and predict wilt. Soil samples were collected from commercial mint fields. Wilt foci, V. dahliae, and plant-parasitic nematodes that can exacerbate wilt were quantified. Multiple linear regression, a generalized additive model, random forest, and an artificial neural network were fit to the data, validated with 10-fold cross-validation, and measures of explanatory and predictive performance were compared. All models selected nematodes within the genus Pratylenchus as the most important predictor of wilt. The fungus after which this disease is named, V. dahliae, was the fourth most important predictor of wilt, after crop age and cultivar. All models explained around 50% of the total variation (R2 ≤ 0.46), and exhibited comparable predictive error (RMSE ≤ 1.21). Collectively, these models revealed that the quantitative relationships between two pathogens, mint cultivars and age are required to explain wilt. The ascendance of Pratylenchus spp. in predicting symptoms of a disease assumed to primarily be caused by V. dahliae exposes the underestimated contribution of these nematodes to wilt. This research provides a foundation on which predictive forecasting tools can be developed for mint growers and reminds us of the lessons that can be learned by revisiting assumptions about disease etiology.

SUBMITTER: Wheeler DL

PROVIDER: S-EPMC6373923 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Plant-parasitic nematodes are an important group of pests causing economic losses in agriculture worldwide. Among the plant-parasitic nematodes, the root-knot (Meloidogyne spp.) and root-lesion nematodes (Pratylenchus spp.) are considered the two most important ones affecting soybeans. In general, they damage soybean roots, causing a reduction of about one-third in productivity. The soil microbial community can exert a suppressive effect on the parasitism of plant-parasitic nematodes. Here, we investigated the effects of soil bacterial diversity on Meloidogyne javanica (Meloidogyne-assay) and Pratylenchus brachyurus (Pratylenchus-assay) suppression by manipulating microbial diversity using the dilution-to-extinction approach in two independent experiments under controlled conditions. Furthermore, we recorded the changes in the soil microbial community induced by plant-parasitic nematode infection. In Meloidogyne-assay, microbial diversity reduced the population density of M. javanica and improved plant performance. In Pratylenchus-assay, microbial diversity sustained the performance of soybean plants even at high levels of P. brachyurus parasitism. Each nematode population affected the relative abundance of different bacterial genera and altered the core microbiome of key groups within the bacterial community. Our findings provide fundamental insights into the interactions between soil bacterial diversity and plant-parasitic nematodes in soybean plants. IMPORTANCE Root-knot and root-lesion nematodes cause losses of billions of dollars every year to agriculture worldwide. Traditionally, they are controlled by using chemical nematicides, which in general have a negative impact on the environment and human health. Fortunately, the soil microbial community may suppress these pests, acting as an environmentally friendly alternative to control nematodes. However, the effects of soil microbial diversity on the parasitism of plant-parasitic nematodes still poorly understood. In this study, we provide fundamental insight into the interactions between soil bacterial diversity and plant-parasitic nematodes in soybean plants, which may be useful for the development of new strategies to control these phytopathogens.

Project description:Morphological and molecular analyses of plant-parasitic nematodes (PPN) from 12 sugarcane plantation sites of Tanganyika Planting Company (TPC) Limited in Kilimanjaro region of Tanzania revealed the presence of six PPN genera, i.e. Helicotylenchus, Hemicycliophora, Pratylenchus, Rotylenchulus, Scutellonema, and Tylenchorhynchus. The genera with the highest densities and present in virtually all samples were Pratylenchus and Rotylenchulus, and the most important species appeared to be R. parvus, P. zeae, T. crassicaudatus, and T. ventrosignatus. A total sequences of 11 partial ITS, 15 D2-D3 of 28S, and 6 partial 18S of rRNA gene, and 7 partial COI gene of mtDNA of these species were obtained in this study. Morphology and molecular data comparisons between the Tanzanian R. parvus and the South African R. parvus indicated that R. parvus is a cryptic species complex. Based on the results of morphological and molecular analyses of T. crassicaudatus and T. agri from China, Haiti, Indonesia, Iran, Niger and the USA, T. agri syn. n. is proposed as a junior synonym of T. crassicaudatus.Morphological and molecular analyses of plant-parasitic nematodes (PPN) from 12 sugarcane plantation sites of Tanganyika Planting Company (TPC) Limited in Kilimanjaro region of Tanzania revealed the presence of six PPN genera, i.e. Helicotylenchus, Hemicycliophora, Pratylenchus, Rotylenchulus, Scutellonema, and Tylenchorhynchus. The genera with the highest densities and present in virtually all samples were Pratylenchus and Rotylenchulus, and the most important species appeared to be R. parvus, P. zeae, T. crassicaudatus, and T. ventrosignatus. A total sequences of 11 partial ITS, 15 D2-D3 of 28S, and 6 partial 18S of rRNA gene, and 7 partial COI gene of mtDNA of these species were obtained in this study. Morphology and molecular data comparisons between the Tanzanian R. parvus and the South African R. parvus indicated that R. parvus is a cryptic species complex. Based on the results of morphological and molecular analyses of T. crassicaudatus and T. agri from China, Haiti, Indonesia, Iran, Niger and the USA, T. agri syn. n. is proposed as a junior synonym of T. crassicaudatus.

Dataset Information

Evidence of a trans-kingdom plant disease complex between a fungus and plant-parasitic nematodes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets