Genome-wide identification of LRR-containing sequences and the response of these sequences to nematode infection in Arachis duranensis

Abstract Background Leucine-rich repeat (LRR)-containing genes are involved in responses to various diseases. Recently, RNA-seq data from A. duranensis after nematode (Meloidogyne arenaria) infection were released. However, the number of LRR-containing genes present in A. duranensis and the response of LRR-containing genes to nematode infection are poorly understood. Results In this study, we found 509 amino acid sequences containing nine types of LRR domains in A. duranensis. The inferred phylogenetic relationships revealed that the nine types of LRR domains had two originations. The inferred selective pressure was mainly consistent with LRR domains undergoing purifying selection. Twenty-one LRR-containing genes were associated with possible resistance to nematode infection after 3, 6, and 9 days. Among them, Aradu.T5WNW, Aradu.JM17V, and Aradu.MKP1A were up-regulate at these three time points, while Aradu.QD5DS and Aradu.M0ENQ were up-regulated 6 and 9 days after nematode infection. The expression of the above mentioned five genes was significantly and negatively correlated with the number of LRR8 domain, indicating that fewer LRR8 domains are associated with the promotion of LRR-containing genes that resist nematode infection. Patterns of co-expression and cis-acting elements indicated that WRKY possibly regulate the responses of LRR-containing genes to nematode infection and that expansin genes may work together with LRR-containing genes in response to nematode infection. Conclusions We identified the number and type of LRR-containing genes in A. duranensis. The LRR-containing genes that were found appear to be involved in responses to nematode infection. The number of LRR8 domains was negatively correlated with expression after nematode infection. The WRKY transcription factor may regulate resistance to nematode infection based on LRR-containing genes. Our results could improve the understanding of resistance to nematodes and molecular breeding in peanuts

Identification of Species-Specific MicroRNAs Provides Insights into Dynamic Evolution of MicroRNAs in Plants

MicroRNAs (miRNAs) are an important class of regulatory small RNAs that program gene expression, mainly at the post-transcriptional level. Although sporadic examples of species-specific miRNAs (termed SS-miRNAs) have been reported, a genome-scale study across a variety of distant species has not been assessed. Here, by comprehensively analyzing miRNAs in 81 plant species phylogenetically ranging from chlorophytes to angiosperms, we identified 8048 species-specific miRNAs from 5499 families, representing over 61.2% of the miRNA families in the examined species. An analysis of the conservation from different taxonomic levels supported the high turnover rate of SS-miRNAs, even over short evolutionary distances. A comparison of the intrinsic features between SS-miRNAs and NSS-miRNAs (non-species-specific miRNAs) indicated that the AU content of mature miRNAs was the most striking difference. Our data further illustrated a significant bias of the genomic coordinates towards SS-miRNAs lying close to or within genes. By analyzing the 125,267 putative target genes for the 7966 miRNAs, we found the preferentially regulated functions of SS-miRNAs related to diverse metabolic processes. Collectively, these findings underscore the dynamic evolution of miRNAs in the species-specific lineages

Enclosing contour tracking of highway construction equipment based on orientation-aware bounding box using UAV

Abstract Construction equipment tracking of highway construction site can obtain the spatiotemporal location in real time and provide data basis for construction risk control. The complete 2D moving of construction equipment in surveillance videos could be spatially represented by the translation, rotation and size change of corresponding images. To describe the temporal relationships of these variables, this study proposes a construction equipment enclosing contour tracking method based on orientation-aware bounding box (OABB), where UAV surveillance videos are employed to alleviate the occlusion problem. The method balances the rotation insensitivity of horizontal bounding box and the complexity of pixel-level segmented contour, which has three modules. The first module integrates OABB into a deep learning detector to provide detected contours. The second module updates OABBs with Kalman prediction to output tracked contours. The third module manages IDs of multiple tracked contours for construction equipment motions. Five in-situ UAV videos including 4325 frames were employed as the evaluation dataset. The tracking performance achieved 2.657 degrees in angle error, 97.523% in MOTA and 83.243% in MOTP

The carboxy terminal transmembrane domain of SPL7 mediates interaction with RAN1 at the endoplasmic reticulum to regulate ethylene signalling in Arabidopsis

Summary: In Arabidopsis, copper (Cu) transport to the ethylene receptor ETR1 mediated using RAN1, a Cu transporter located at the endoplasmic reticulum (ER), and Cu homeostasis mediated using SPL7, the key Cu‐responsive transcription factor, are two deeply conserved vital processes. However, whether and how the two processes interact to regulate plant development remain elusive. We found that its C‐terminal transmembrane domain (TMD) anchors SPL7 to the ER, resulting in dual compartmentalisation of the transcription factor. Immunoprecipitation coupled mass spectrometry, yeast‐two‐hybrid assay, luciferase complementation imaging and subcellular co‐localisation analyses indicate that SPL7 interacts with RAN1 at the ER via the TMD. Genetic analysis revealed that the ethylene‐induced triple response was significantly compromised in the spl7 mutant, a phenotype rescuable by RAN1 overexpression but not by SPL7 without the TMD. The genetic interaction was corroborated by molecular analysis showing that SPL7 modulates RAN1 abundance in a TMD‐dependent manner. Moreover, SPL7 is feedback regulated by ethylene signalling via EIN3, which binds the SPL7 promoter and represses its transcription. These results demonstrate that ER‐anchored SPL7 constitutes a cellular mechanism to regulate RAN1 in ethylene signalling and lay the foundation for investigating how Cu homeostasis conditions ethylene sensitivity in the developmental context

Oligopeptide transporter Slc15A modulates macropinocytosis in Dictyostelium by maintaining intracellular nutrient status

ABSTRACT: Macropinocytosis mediates non-selective bulk uptake of extracellular fluid. It is the major route by which axenic Dictyostelium cells obtain nutrients and has emerged as a nutrient-scavenging pathway in mammalian cells. How environmental and cellular nutrient status modulates macropinocytic activity is not well understood. By developing a high-content imaging-based genetic screen in Dictyostelium discoideum we identified Slc15A, an oligopeptide transporter located at the plasma membrane and early macropinosome, as a novel macropinocytosis regulator. We show that deletion of slc15A but not two other related slc15 genes, leads to reduced macropinocytosis, reduced cell growth and aberrantly increased autophagy in cells grown in nutrient-rich medium. Expression of Slc15A protein or supplying cells with free amino acids rescues these defects. In contrast, expression of transport-defective Slc15A or supplying cells with amino acids in their di-peptide forms fails to rescue these defects. Therefore, Slc15A modulates the level of macropinocytosis by maintaining the intracellular availability of key amino acids through extraction of oligopeptides from the early macropinocytic pathway. We propose that Slc15A constitutes part of a positive feedback mechanism coupling cellular nutrient status and macropinocytosis. This article has an associated First Person interview with the first authors of the paper

Highly accurate and large-scale collision cross sections prediction with graph neural networks

Abstract The collision cross section (CCS) values derived from ion mobility spectrometry can be used to improve the accuracy of compound identification. Here, we have developed the Structure included graph merging with adduct method for CCS prediction (SigmaCCS) based on graph neural networks using 3D conformers as inputs. A model was trained, evaluated, and tested with >5,000 experimental CCS values. It achieved a coefficient of determination of 0.9945 and a median relative error of 1.1751% on the test set. The model-agnostic interpretation method and the visualization of the learned representations were used to investigate the chemical rationality of SigmaCCS. An in-silico database with 282 million CCS values was generated for three different adduct types of 94 million compounds. Its source code is publicly available at https://github.com/zmzhang/SigmaCCS . Altogether, SigmaCCS is an accurate, rational, and off-the-shelf method to directly predict CCS values from molecular structures