Comparative genome analysis of plant ascomycete fungal pathogens with different lifestyles reveals distinctive virulence strategies

Background: Pathogens have evolved diverse lifestyles and adopted pivotal new roles in both natural ecosystems and human environments. However, the molecular mechanisms underlying their adaptation to new lifestyles are obscure. Comparative genomics was adopted to determine distinct strategies of plant ascomycete fungal pathogens with different lifestyles and to elucidate their distinctive virulence strategies. Results: We found that plant ascomycete biotrophs exhibited lower gene gain and loss events and loss of CAZyme-encoding genes involved in plant cell wall degradation and biosynthesis gene clusters for the production of secondary metabolites in the genome. Comparison with the candidate effectome detected distinctive variations between plant biotrophic pathogens and other groups (including human, necrotrophic and hemibiotrophic pathogens). The results revealed the biotroph-specific and lifestyle-conserved candidate effector families. These data have been configured in web-based genome browser applications for public display (http://lab.malab.cn/soft/PFPG). This resource allows researchers to profile the genome, proteome, secretome and effectome of plant fungal pathogens. Conclusions: Our findings demonstrated different genome evolution strategies of plant fungal pathogens with different lifestyles and explored their lifestyle-conserved and specific candidate effectors. It will provide a new basis for discovering the novel effectors and their pathogenic mechanisms

Spatial repellency, antifeedant activity and toxicity of three medium chain fatty acids and their methyl esters of coconut fatty acid against stable flies

BACKGROUND: Stable flies are one of the most detrimental arthropod pests to livestock. With changing climates and agronomic practices, they expand their roles as pests and disease vectors as well. Their painful bites reduce livestock productivity, annoy companion animals, and interfere with human recreational activities. Current management technologies are unable to effectively control stable flies. The present study reports new results concerning the contact, spatial repellency, and toxicity of a bio-based product, coconut fatty acid and their methyl ester derivatives of free fatty acids of C8:0, C10:0 and C12:0 to stable flies. RESULTS: Three medium chain fatty acid methyl esters (C8:0 , C10:0 and C12:0 ) showed strong antifeedant activity against stable flies and their strengths were dose-dependent. Only the C8:0 acid, C8:0 - and C10:0 methyl esters elicited significant antennal responses. Laboratory single cage olfactometer bioassays revealed that coconut fatty acid and C8:0 methyl ester displayed active spatial repellency. All three methyl esters showed strong toxicity against stable flies. CONCLUSION: Antifeedant activity is the main method through which coconut fatty acid deters stable fly blood-feeding. The C8:0, C10:0 and C12:0 methyl esters act not only as strong antifeedants, but also possess strong toxicity against stable fly adults. Limited spatial repellency was observed from coconut fatty acid and C8:0 methyl ester

Spatial repellency, antifeedant activity and toxicity of three medium chain fatty acids and their methyl esters of coconut fatty acid against stable flies

BACKGROUND: Stable flies are one of the most detrimental arthropod pests to livestock. With changing climates and agronomic practices, they expand their roles as pests and disease vectors as well. Their painful bites reduce livestock productivity, annoy companion animals, and interfere with human recreational activities. Current management technologies are unable to effectively control stable flies. The present study reports new results concerning the contact, spatial repellency, and toxicity of a bio-based product, coconut fatty acid and their methyl ester derivatives of free fatty acids of C8:0, C10:0 and C12:0 to stable flies. RESULTS: Three medium chain fatty acid methyl esters (C8:0 , C10:0 and C12:0 ) showed strong antifeedant activity against stable flies and their strengths were dose-dependent. Only the C8:0 acid, C8:0 - and C10:0 methyl esters elicited significant antennal responses. Laboratory single cage olfactometer bioassays revealed that coconut fatty acid and C8:0 methyl ester displayed active spatial repellency. All three methyl esters showed strong toxicity against stable flies. CONCLUSION: Antifeedant activity is the main method through which coconut fatty acid deters stable fly blood-feeding. The C8:0, C10:0 and C12:0 methyl esters act not only as strong antifeedants, but also possess strong toxicity against stable fly adults. Limited spatial repellency was observed from coconut fatty acid and C8:0 methyl ester

Brassinosteroids are involved in response of cucumber (Cucumis sativus) to iron deficiency

BACKGROUND AND AIMS: Brassinosteroids (BR) are a class of plant polyhydroxysteroids with diverse functions in plant growth and development. However, there is little information on the role of BRs played in the response to nutrient deficiency. METHODS: To evaluate the role of BR in the response of plants to iron (Fe) deficiency, the effect of 24-epibrassinolide (EBR) on ferric reductase (FRO) activity, acidification of the rhizosphere and Fe content in cucumber (Cucumis sativus) seedlings under Fe-deficient (1 µm FeEDTA) and Fe-sufficient (50 µm FeEDTA) conditions were investigated. KEY RESULTS: There was a significant increase in FRO activity upon exposure of cucumber seedlings to an Fe-deficient medium, and the Fe deficiency-induced increase in FRO activity was substantially suppressed by EBR. In contrast, application of EBR to Fe-sufficient seedlings stimulated FRO activity. Ethylene production evoked by Fe deficiency was suppressed by EBR, while EBR induced ethylene production from Fe-sufficient seedlings. Fe contents in shoots were reduced by treatment with EBR, while Fe contents in roots were markedly increased under both Fe-deficient and Fe-sufficient conditions. The reductions in Fe contents of shoots were independent of chlorophyll (CHL) contents under Fe-sufficient conditions, but they were positively correlated with CHL contents under Fe-deficient conditions. At the transcriptional level, transcripts encoding FRO (CsFRO1) and Fe transporter (CsIRT1) were increased upon exposure to the Fe-deficient medium, and the increases in transcripts were reversed by EBR. CONCLUSIONS: The results demonstrate that BRs are likely to play a negative role in regulating Fe-deficiency-induced FRO, expressions of CsFRO1 and CsIRT1, as well as Fe translocation from roots to shoots

Recall DNA methylation levels at low coverage sites using a CNN model in WGBS.

DNA methylation is an important regulator of gene transcription. WGBS is the gold-standard approach for base-pair resolution quantitative of DNA methylation. It requires high sequencing depth. Many CpG sites with insufficient coverage in the WGBS data, resulting in inaccurate DNA methylation levels of individual sites. Many state-of-arts computation methods were proposed to predict the missing value. However, many methods required either other omics datasets or other cross-sample data. And most of them only predicted the state of DNA methylation. In this study, we proposed the RcWGBS, which can impute the missing (or low coverage) values from the DNA methylation levels on the adjacent sides. Deep learning techniques were employed for the accurate prediction. The WGBS datasets of H1-hESC and GM12878 were down-sampled. The average difference between the DNA methylation level at 12× depth predicted by RcWGBS and that at >50× depth in the H1-hESC and GM2878 cells are less than 0.03 and 0.01, respectively. RcWGBS performed better than METHimpute even though the sequencing depth was as low as 12×. Our work would help to process methylation data of low sequencing depth. It is beneficial for researchers to save sequencing costs and improve data utilization through computational methods

Biological Sequence Classification: A Review on Data and General Methods

With the rapid development of biotechnology, the number of biological sequences has grown exponentially. The continuous expansion of biological sequence data promotes the application of machine learning in biological sequences to construct predictive models for mining biological sequence information. There are many branches of biological sequence classification research. In this review, we mainly focus on the function and modification classification of biological sequences based on machine learning. Sequence-based prediction and analysis are the basic tasks to understand the biological functions of DNA, RNA, proteins, and peptides. However, there are hundreds of classification models developed for biological sequences, and the quite varied specific methods seem dizzying at first glance. Here, we aim to establish a long-term support website (http://lab.malab.cn/~acy/BioseqData/home.html), which provides readers with detailed information on the classification method and download links to relevant datasets. We briefly introduce the steps to build an effective model framework for biological sequence data. In addition, a brief introduction to single-cell sequencing data analysis methods and applications in biology is also included. Finally, we discuss the current challenges and future perspectives of biological sequence classification research

Stair-Step Pattern of Soil Bacterial Diversity Mainly Driven by pH and Vegetation Types Along the Elevational Gradients of Gongga Mountain, China

Ecological understandings of soil bacterial community succession and assembly mechanism along elevational gradients in mountains remain not well understood. Here, by employing the high-throughput sequencing technique, we systematically examined soil bacterial diversity patterns, the driving factors, and community assembly mechanisms along the elevational gradients of 1800–4100 m on Gongga Mountain in China. Soil bacterial diversity showed an extraordinary stair-step pattern along the elevational gradients. There was an abrupt decrease of bacterial diversity between 2600 and 2800 m, while no significant change at either lower (1800–2600 m) or higher (2800–4100 m) elevations, which coincided with the variation in soil pH. In addition, the community structure differed significantly between the lower and higher elevations, which could be primarily attributed to shifts in soil pH and vegetation types. Although there was no direct effect of MAP and MAT on bacterial community structure, our partial least squares path modeling analysis indicated that bacterial communities were indirectly influenced by climate via the effect on vegetation and the derived effect on soil properties. As for bacterial community assembly mechanisms, the null model analysis suggested that environmental filtering played an overwhelming role in the assembly of bacterial communities in this region. In addition, variation partition analysis indicated that, at lower elevations, environmental attributes explained much larger fraction of the β-deviation than spatial attributes, while spatial attributes increased their contributions at higher elevations. Our results highlight the importance of environmental filtering, as well as elevation-related spatial attributes in structuring soil bacterial communities in mountain ecosystems

The prognostic value of SOX2 expression in non-small cell lung cancer: a meta-analysis.

OBJECTIVE: To investigate the association of SOX2 expression in tumor with clinicopathological features and survival of non-small-cell lung carcinoma (NSCLC) patients. METHODS: Publications assessing the clinicopathological characteristics and prognostic significance of SOX2 in NSCLC were identified up to May 2013. A meta-analysis of eligible studies was performed using standard statistical methods to clarify the association between SOX2 expression and these clinical parameters. RESULTS: A total of eight studies met the inclusion criteria. Analysis of these data showed that SOX2 expression was positively associated with squamous histology, (pooled OR = 5.26, 95% CI: 1.08-25.6, P = 0.040). Simultaneously, we also found that SOX2 expression was positively associated with overall survival (pooled HR = 0.65, 95% CI: 0.47-0.89, P = 0.007, random-effect). CONCLUSIONS: SOX2 expression in tumor is a candidate positive prognostic biomarker for NSCLC patients