The genome of the soybean pathogen Phytophthora sojae contains nearly 400 genes encoding candidate effector proteins carrying the host cell entry motif RXLR-dEER. Here, we report a broad survey of the transcription, variation, and functions of a large sample of the P. sojae candidate effectors. Forty-five (12%) effector genes showed high levels of polymorphism among P. sojae isolates and significant evidence for positive selection. Of 169 effectors tested, most could suppress programmed cell death triggered by BAX, effectors, and/or the PAMP INF1, while several triggered cell death themselves. Among the most strongly expressed effectors, one immediate-early class was highly expressed even prior to infection and was further induced 2- to 10-fold following infection. A second early class, including several that triggered cell death, was weakly expressed prior to infection but induced 20- to 120-fold during the first 12 h of infection. The most strongly expressed immediate-early effectors could suppress the cell death triggered by several early effectors, and most early effectors could suppress INF1-triggered cell death, suggesting the two classes of effectors may target different functional branches of the defense response. In support of this hypothesis, misexpression of key immediate-early and early effectors severely reduced the virulence of P. sojae transformants.

Recently, many Deep Learning models have been employed to classify different kinds of plant diseases, but very little work has been done for disease severity detection. However, it is more important to master the severities of plant diseases accurately and timely, as it helps to make effective decisions to protect the plants from being further infected and reduce financial loss. In this paper, based on the Huanglongbing (HLB)-infected leaf images obtained from PlantVillage and crowdAI, we created a dataset with 5,406 citrus leaf images infected by HLB. Then six popular models were trained to perform the severity detection of citrus HLB with the goal to find which types of models are more suitable to detect HLB severity with the same training circumstance. The experimental results show that the Inception_v3 model with epochs=60 can achieve higher accuracy than that of other models for severity detection with an accuracy of 74.38% due to its highly computational efficiency and small number of parameters. Additionally, aiming for evaluating whether the augmented data can contribute to improve the model learning performance, we adopted Generative Adversarial Networks (GANs) to augment the original training dataset up to two times itself. Finally, a new training dataset with 14,056 leaf images composed by the original training images and the augmented ones were used to train the Inception_v3. As a result, we achieved an accuracy of 92.60%, about 20% higher than that of model trained by the original training dataset, which suggested that the GANs-based data augmentation is very useful to improve the model learning performance.

BackgroundIn avian species, liver is the main site of de novo lipogenesis, and hepatic lipid metabolism relates closely to adipose fat deposition. Using our fat and lean chicken lines of striking differences in abdominal fat content, post-hatch lipid metabolism in both liver and adipose tissues has been studied extensively. However, whether molecular discrepancy for hepatic lipid metabolism exists in chicken embryos remains obscure.ResultsWe performed transcriptome and proteome profiling on chicken livers at five embryonic stages (E7, E12, E14, E17 and E21) between the fat and lean chicken lines. At each stage, 521, 141, 882, 979 and 169 differentially expressed genes were found by the digital gene expression, respectively, which were significantly enriched in the metabolic, PPAR signaling and fatty acid metabolism pathways. Quantitative proteomics analysis found 20 differentially expressed proteins related to lipid metabolism, PPAR signaling, fat digestion and absorption, and oxidative phosphorylation pathways. Combined analysis showed that genes and proteins related to lipid transport (intestinal fatty acid-binding protein, nucleoside diphosphate kinase, and apolipoprotein A-I), lipid clearance (heat shock protein beta-1) and energy metabolism (NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 10 and succinate dehydrogenase flavoprotein subunit) were significantly differentially expressed between the two lines.ConclusionsFor hepatic lipid metabolism at embryonic stages, molecular differences related to lipid transport, lipid clearance and energy metabolism exist between the fat and lean chicken lines, which might contribute to the striking differences of abdominal fat deposition at post-hatch stages.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4776-9) contains supplementary material, which is available to authorized users.

Through posttranscriptional gene regulation, microRNA (miRNA) is linked to a wide variety of biological processes, including adipogenesis and lipid metabolism. Although miRNAs in mammalian adipogenesis have been worked on extensively, their study in chicken adipogenesis is still very limited. To find miRNAs potentially important for chicken preadipocyte development, we compared the preadipocyte miRNA expression profiles in two broiler lines divergently selected for abdominal fat content, by sequencing two small RNA libraries constructed for primary preadipocytes isolated from abdominal adipose tissues. After bioinformatics analyses, from chicken miRNAs deposited in miRBase 20.0, we identified 225 miRNAs to be expressed in preadipocytes, 185 in the lean line and 200 in the fat line (derived from 208 and 203 miRNA precursors, respectively), which corresponds to 114 miRNA families. The let-7 family miRNAs were the most abundant. Furthermore, we validated the sequencing results of 15 known miRNAs by qRT-PCR, and confirmed that the expression levels of most miRNAs correlated well with those of Solexa sequencing. A total of 33 miRNAs was significantly differentially expressed between the two chicken lines (P<0.05). Gene ontology analysis revealed that they could target genes enriched in the regulation of gene transcription and chromatin function, response to insulin stimulation, and IGF-1 signaling pathways, which could have important roles in preadipocyte development. Therefore, a valuable information and resource of miRNAs on chicken adipogenesis were provided in this study. Future functional investigations on these miRNAs could help explore related genes and molecular networks fundamental to preadipocyte development.

One of the main objectives of broiler breeding is to prevent excessive abdominal adipose deposition. The role of RNA modification in adipose deposition is not clear. This study was aimed to map m6A modification landscape in chicken adipose tissue. MeRIP-seq was performed to compare the differences in m6A methylation pattern between fat and lean broilers. We found that start codons, stop codons, coding regions, and 3′-untranslated regions were generally enriched for m6A peaks. The high m6A methylated genes (fat birds vs. lean birds) were primarily associated with fatty acid biosynthesis and fatty acid metabolism, while the low m6A methylated genes were mainly involved in processes associated with development. Furthermore, we found that the mRNA levels of many genes may be regulated by m6A modification. This is the first comprehensive characterization of m6A patterns in the chicken adipose transcriptome, and provides a basis for studying the role of m6A modification in fat deposition.

Many bacterial, fungal, and oomycete species secrete necrosis and ethylene-inducing peptide 1 (Nep1)-like proteins (NLP) that trigger programmed cell death (PCD) and innate immune responses in dicotyledonous plants. However, how NLP induce such immune responses is not understood. Here, we show that silencing of the MAPKKKα-MEK2-WIPK mitogen-activated protein kinase (MAPK) cascade through virus-induced gene silencing compromises hydrogen peroxide accumulation and PCD induced by Nep1(Mo) from Magnaporthe oryzae. WIPK interacts with NbWRKY2, a transcription factor in Nicotiana benthamiana, in vitro and in vivo, suggesting an effector pathway that mediates Nep1(Mo)-induced cell death. Unexpectedly, salicylic acid-induced protein kinase (SIPK)- and NbWRKY2-silenced plants showed impaired Nep1(Mo)-induced stomatal closure, decreased Nep1(Mo)-promoted nitric oxide (NO) production in guard cells, and a reduction in Nep1(Mo)-induced resistance against Phytophthora nicotianae. Expression studies by real-time polymerase chain reaction suggested that the MEK2-WIPK-NbWRKY2 pathway regulated Nep1(Mo)triggered NO accumulation could be partly dependent on nitrate reductase, which was implicated in NO synthesis. Taken together, these studies demonstrate that the MAPK cascade is involved in Nep1(Mo)-triggered plant responses and MAPK signaling associated with PCD exhibits shared and distinct components with that for stomatal closure.

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