The genomic history and global migration of a windborne pest.

Many insect pests, including the brown planthopper (BPH), undergo windborne migration that is challenging to observe and track. It remains controversial about their migration patterns and largely unknown regarding the underlying genetic basis. By analyzing 360 whole genomes from around the globe, we clarify the genetic sources of worldwide BPHs and illuminate a landscape of BPH migration showing that East Asian populations perform closed-circuit journeys between Indochina and the Far East, while populations of Malay Archipelago and South Asia undergo one-way migration to Indochina. We further find round-trip migration accelerates population differentiation, with highly diverged regions enriching in a gene desert chromosome that is simultaneously the speciation hotspot between BPH and related species. This study not only shows the power of applying genomic approaches to demystify the migration in windborne migrants but also enhances our understanding of how seasonal movements affect speciation and evolution in insects.

Correction: Ser-653-Asn substitution in the acetohydroxyacid synthase gene confers resistance in weedy rice to imidazolinone herbicides in Malaysia.

[This corrects the article DOI: 10.1371/journal.pone.0227397.].

Ser-653-Asn substitution in the acetohydroxyacid synthase gene confers resistance in weedy rice to imidazolinone herbicides in Malaysia.

The continuous and sole dependence on imidazolinone (IMI) herbicides for weedy rice control has led to the evolution of herbicide resistance in weedy rice populations across various countries growing IMI herbicide-resistant rice (IMI-rice), including Malaysia. A comprehensive study was conducted to elucidate occurrence, level, and mechanisms endowing resistance to IMI herbicides in putative resistant (R) weedy rice populations collected from three local Malaysian IMI-rice fields. Seed bioassay and whole-plant dose-response experiments were conducted using commercial IMI herbicides. Based on the resistance index (RI) quantification in both experiments, the cross-resistance pattern of R and susceptible (S) weedy rice populations and control rice varieties (IMI-rice variety MR220CL2 and non-IMI-rice variety MR219) to imazapic and imazapyr was determined. A molecular investigation was carried out by comparing the acetohydroxyacid synthase (AHAS) gene sequences of the R and S populations and the MR220CL2 and MR219 varieties. The AHAS gene sequences of R weedy rice were identical to those of MR220CL2, exhibiting a Ser-653-Asn substitution, which was absent in MR219 and S plants. In vitro assays were conducted using analytical grade IMI herbicides of imazapic (99.3%) and imazapyr (99.6%) at seven different concentrations. The results demonstrated that the AHAS enzyme extracted from the R populations and MR220CL2 was less sensitive to IMI herbicides than that from S and MR219, further supporting that IMI herbicide resistance was conferred by target-site mutation. In conclusion, IMI resistance in the selected populations of Malaysian weedy rice could be attributed to a Ser-653-Asn mutation that reduced the sensitivity of the target site to IMI herbicides. To our knowledge, this study is the first to show the resistance mechanism in weedy rice from Malaysian rice fields.

Recent Strategies for Detection and Improvement of Brown Planthopper Resistance Genes in Rice: A Review.

Brown planthopper (BPH; Nilaparvata lugens Stal) is considered the main rice insect pest in Asia. Several BPH-resistant varieties of rice have been bred previously and released for large-scale production in various rice-growing regions. However, the frequent surfacing of new BPH biotypes necessitates the evolution of new rice varieties that have a wide genetic base to overcome BPH attacks. Nowadays, with the introduction of molecular approaches in varietal development, it is possible to combine multiple genes from diverse sources into a single genetic background for durable resistance. At present, above 37 BPH-resistant genes/polygenes have been detected from wild species and indica varieties, which are situated on chromosomes 1, 3, 4, 6, 7, 8, 9, 10, 11 and 12. Five BPH gene clusters have been identified from chromosomes 3, 4, 6, and 12. In addition, eight BPH-resistant genes have been successfully cloned. It is hoped that many more resistance genes will be explored through screening of additional domesticated and undomesticated species in due course.

Minimum inhibitory concentration of nano-silver bactericides for beneficial microbes and its effect on Ralstonia solanacearum and seed germination of Japanese Cucumber (Cucumis sativus).

BACKGROUND: Plant growth-promoting rhizobacteria (PGPR) are highly promising biofertilizers that contribute to eco-friendly sustainable agriculture. There have been many reports on the anti-microbial properties of nanoparticles (NPs). Toxic effects of NPs under laboratory conditions have also reported; however, there is a lack of information about their uptake and mobility in organisms under environmental conditions. There is an urgent need to determine the highest concentration of NPs which is not detrimental for growth and proliferation of PGPR. METHODS: Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) were used to measure the size and shape of NPs. Minimum inhibitory concentrations (MIC) of nano-silver on selected beneficial microbes and Ralstonia solanacearum were measured using the microdilution broth method. The percentage of seed germination was measured under in vitro conditions. RESULTS: NPs were spherical with a size of 16 ± 6 nm. Nano-silver at 12-40 mg l-1 inhibited the growth of bacteria. Seed application at 40 mg l-1 protected seeds from R. solanacearum and improved the rate of seed germination.

PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and monitoring of its abundance has been conducted manually by experts and is time-consuming, fatiguing and tedious. Automated detection of BPH has been proposed by many studies to overcome human fallibility. However, all studies regarding automated recognition of BPH are investigated based on intact specimen although most of the specimens are imperfect, with missing parts have distorted shapes. The automated recognition of an imperfect insect image is more difficult than recognition of the intact specimen. This study proposes an automated, deep-learning-based detection pipeline, PENYEK, to identify BPH pest in images taken from a readily available sticky pad, constructed by clipping plastic sheets onto steel plates and spraying with glue. This study explores the effectiveness of a convolutional neural network (CNN) architecture, VGG16, in classifying insects as BPH or benign based on grayscale images constructed from Euclidean Distance Maps (EDM). The pipeline identified imperfect images of BPH with an accuracy of 95% using deep-learning's hyperparameters: softmax, a mini-batch of 30 and an initial learning rate of 0.0001.