转基因大豆MON89788芯片式数字PCR定量方法的建立

针对抗虫耐除草剂大豆转基因品系MON89788,从转基因植物基因组DNA的提取、核酸模板的质量和浓度控制、引物探针的筛选、PCR反应过程的建立等方面建立了一套完整的转基因大豆芯片式dPCR定量检测方法。本实验也对该方法的重复性和定量检测限进行考察。10组5%转基因品系大豆MON89788样品定量重复性RSD在1.17%-9.97%之间,均满足国际上转基因定量结果RSD小于25%的要求。用该方法对转基因含量为5%、1%、0.1%的大豆MON89788进行定量检测,其定量结果为5.20%、0.94%和0.11%,RSD分别为6.2%、3.6%和15.2%。该检测方法的定量限达到0.1%,能满足欧盟对转基因定量标识0.9%的要求。将本实验建立的方法用于转基因大豆的定量检测,能为规范我国转基因监管工作的实施提供强有力的技术支撑。     

小麦丛矮病毒基因组5‘端尾随区的克隆及序列分析

根据已知的弹状病毒聚合酶Ｌ蛋白分子中一段高保守的８个氨基酸顺序ＥＧＬＲＱＫＧＷ，合成简并的２４核苷酸引物，用锚定ＰＣＲ方法从小麦丛矮病毒（ＷＲＳＶ）基因组中扩增出包含全长５‘尾随区和部分Ｌ蛋白基因的ＤＮＡ片段，并克隆到ｐＵＣ１９Ｔ载体上，经测序，获得全长的ＷＲＳＶ基因组５’尾随区顺序。     

免疫细胞浸润在非小细胞肺癌诊断与预后中的应用

免疫细胞浸润对癌症的诊断与预后有着重要意义。文中收集TCGA数据库已收录的非小细胞肺癌肿瘤与正常组织基因表达数据,利用CIBERSORT工具得到22种免疫细胞占比来评估免疫细胞浸润情况。以22种免疫细胞占比为特征,用机器学习方法构建了非小细胞肺癌肿瘤与正常组织的分类模型,其中随机森林方法构建的模型分类效果AUC=0.987、敏感性0.98及特异性0.84。并且用随机森林方法构建的肺腺癌和肺鳞癌肿瘤组织分类模型效果AUC=0.827、敏感性0.75及特异性0.77。用LASSO回归筛选22种免疫细胞特征,保留8种强相关特征组成的免疫细胞评分结合临床特征构建了非小细胞肺癌预后模型。经评估及验证,预后模型C-index=0.71并且3年和5年的校准曲线拟合良好,可以对预后风险度进行准确预测。本研究基于免疫细胞浸润所构建的分类模型与预后模型,旨在对非小细胞肺癌的诊断与预后研究提供新的策略。     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

小克银汉霉核糖体DNAPCR扩增产物的限制性片段长度多型性

应用一对寡苷酸引物ＩＴＳ１与ＩＴＳ４对核ＤＮＡＧ＋Ｃ百分数小于３０％的小克银汉霉属的核糖体ＤＮＡ（ｒＤＮＡ）内转录间区（ＩＴＳ）进行了扩增。测试的属于１０个种和变种的２２株菌都得到了扩增产物，在同属不同种之间扩增的ＩＴＳ片段长度有巨大差别。据此可分为三组。这三组所含分类群数及其ＤＮＡ长度 ：第一组４种１变种，小于７６４碱基对；第二组２种，７６５－８２４ｂｐ；第三组２种１变种，大于８２５ｂｐ。所研究     

甘蔗杆状病毒荧光定量PCR检测方法的建立及初步应用

为建立一种能够快速、灵敏、特异的检测甘蔗杆状病毒(sugarcane bacilliform virus, SCBV)的SYBR GreenⅠ荧光定量PCR方法,针对SCBV的基因序列,设计了特异性扩增引物,利用构建的标准品建立和优化针对SCBV的荧光定量PCR检测方法,并对该方法进行了特异性、稳定性、灵敏性等的测试,随后用于田间样品的检测。结果表明:将含有SCBV基因组序列的重组质粒进行梯度稀释制成标准品,利用标准品进行荧光定量PCR,获得标准曲线y=-3.482 1x+37.264,相关系数r~2=0.999 9,说明CT值与反应起始模板数量呈线性关系,可进行准确定量;组内和组间变异系数在0.19%～1.68%之间,表明检测方法重复性良好;建立的荧光定量PCR方法最低可检测到10个拷贝重组质粒/μL,是常规PCR检测灵敏度的100倍。使用建立的荧光定量PCR方法和常规PCR方法对采集的90份甘蔗叶片样品进行检测,常规PCR检出53份阳性样品,荧光定量PCR检出56份阳性样品,表明所建立的荧光定量PCR方法较常规PCR敏感性高,且准确性高。本研究建立的SCBV荧光定量PCR检测方法重复性好,灵敏度高,为构建甘蔗健康种苗体系提供了一种高效检测方法。