Plant somatic mutations in nature conferring insect and herbicide resistance

Because of the role of the meristem in plant growth and reproduction, somatic mutations in plants have long been suspected of conferring herbivore and pathogen resistance on individual plants and, in the case of trees, individual branches within single plants. A few instances of resistance to phytophagous insects owing to somatic mutations have been reported in the literature. More recently, a striking example has demonstrated how somatic mutations confer resistance to an herbicide on an invasive plant, Hydrilla verticillata. The array of new methods for manipulating genomes (e.g., gene‐editing) plus existing examples of somatic mutation‐associated resistance suggest that such mutations might be useful in silviculture, agriculture, and horticulture. Answering several general questions about somatic mutations in plants would facilitate such applications: Why are so few examples reported? Do other cases exist but go undetected for want of adequate attention or methods? Under what circumstances do somatic mutations enter gametophytes? © 2018 Society of Chemical Industry     

红富士苹果芽变系DNA甲基化研究

以35份富士苹果(Malus×domestica Borkh.‘Fuji’)芽变材料为试材,利用甲基化敏感扩增多态性(Methylation Sensitive Amplified Polymorphism,MSAP)分析和UPGMA聚类方法,对其基因组甲基化修饰水平、变异模式以及表观遗传变异关系进行研究。结果表明:(1)不同富士系得到不同的MSAP扩增,总DNA甲基化水平27.90%～36.16%,平均32.87%,双链全甲基化为主要甲基化方式;(2)富士芽变材料绝大多数位点保持了原有甲基化模式;(3)绝大多数芽变(68.57%)检测到全部的甲基化变异模式(12种),去甲基化频率极显著高于甲基化频率(P 0.01),且CG去甲基化极显著高于CHG;(4)36份种质遗传相似系数平均值0.89(0.79～0.92),在聚类图上,富士原种分布在芽变系集中区外,新近发生的芽变系更倾向于聚在一起,着色系片红型和条红型芽变呈分散排布状态。总的来看,富士芽变的甲基化变异模式丰富,超甲基化和去甲基化相伴发生,但以去甲基化为主;‘富士’着色芽变与其最原始品种富士,以及芽变之间发生了较大表观遗传变异;片红和条红型芽变聚类未表现明显偏好性。本研究将为进一步开展富士着色系芽变机理研究提供指导,可以CG去甲基化为切入点展开深入研究。     

秋水仙素处理日本矮紫薇种子变异的初步研究

用0.05％、0.10％、0.15％3种不同浓度秋水仙素和24、48、72 h 3个不同处理时间,对日本矮紫薇种子发芽性状和幼苗生长性状进行研究.结果表明:0.05％、0.10％、0.15％浓度秋水仙素处理日本紫薇种子24、48、72 h,随着秋水仙素浓度的增加和处理时间的延长其种子发芽率、发芽势、出苗率均有降低的现象,0.15％浓度秋水仙素溶液处理的日本矮紫薇种子72 h时出苗率低于10％.随着秋水仙素处理浓度和时间的延长,幼苗生长表现出矮化、根部变短、叶片变厚的趋势.该研究获得了3株矮化的变异植株及2株株型变异的幼苗,对日本矮紫薇突变体产生、筛选及良种选育提供了基础.     

基于特征金字塔注意力与深度卷积网络的多目标生猪检测

在生猪饲养环境中,猪只黏连、杂物遮挡等给生猪个体多目标检测带来很大困难。该研究以猪圈群养生猪为研究对象,以视频帧为数据源,提出一种适用于生猪形体检测的特征金字塔注意力(FeaturePyramidAttention,FPA)与Tiny-YOLO相结合的模型FPA-Tiny-YOLO。该模型将注意力信息融入到特征提取过程,在不大幅增加计算量的前提下即可提升特征提取能力、提高检测精度。对8栏日龄20～105 d的45头生猪视频截取图像进行图像处理,获得标注图片4 102张,构建了4种深度FPA模块分别加入YOLOV3与Tiny-YOLO模型中。试验表明,深度为3的FPA模块(即FPA-3)的Tiny-YOLO模型在测试集上对群养生猪多目标检测的召回率Recall、F1与平均检测精度m AP指标值最佳,分别达到86.09%、91.47%和85.85%,比未引入FPA模块的Tiny-YOLO模型均有不同程度的提高。选用不同的IOU(Intersection Over Union)和score阈值超参数值对模型预测结果均有不同程度影响;将测试集图像按照是否黏连与遮挡划分4种场景来探究该模型的鲁棒性。试验表明,加入FPA-3模块后Tiny-YOLO的Recall、F1与m AP比Tiny-YOLO分别提升6.73、4.34和7.33个百分点,说明特征金字塔注意力信息有利于精确、有效地对不同场景群养生猪进行多目标检测。研究结果可为后续开展生猪身份识别和行为分析移动端应用提供参考。     

The effects of various plant protection methods on the development of Zymoseptoria tritici and Cephalosporium gramineum,grain yield and protein profile

Septoria leaf blotch progresses rapidly, leading to the development of Zymoseptoria titici forms resistant to fungicides. Cephalosporium stripe is caused by Cephalosporium gramineum. The aim of this study was to evaluate the effectiveness of selected pesticides in limiting the symptoms of both diseases on winter wheat leaves, and to determine their influence on grain yield and the content and composition of protein fractions in wheat kernels. Propiconazoles were most effective in inhibiting the development of Septoria leaf blotch (symptoms were reduced from 54.7% to 78.6%). Strobilurins were less effective due to the presence of isolates with the G143A mutation. Symptoms of Cephalosporium stripe were rarely observed, and protective treatments did not reduce their severity. The highest content of grain protein (14.81%) was found in plants most intensely protected with the fungicides containing fenpropimorph, pyraclostrobin and epoxiconazole. The principal component analysis revealed that the plant protection method influenced the grain protein profile. The accumulation of HMW glutenins and α/β gliadins was mutually interrelated and higher in high-input treatments; control grain was characterized by close relationships between ω-gliadins, LMW glutenins, albumins and globulins, whereas low-input treatments influenced mostly γ-gliadins.