内蒙古草甸草原土壤理化性质和微生物学特性对刈割与氮添加的响应

频繁的刈割和氮输入增加是导致草地生态系统退化的重要原因.土壤微生物学特性作为评估土壤质量的重要生物学指标,对草地刈割和氮输入增加的响应规律仍不十分明确.本研究依托内蒙古呼伦贝尔草原刈割复合氮添加野外实验平台,分析了土壤理化性质、土壤微生物生物量、土壤呼吸和土壤酶对刈割、氮添加的响应及其生长季动态变化.结果表明: 刈割显著降低了土壤微生物生物量碳、氮、磷和土壤呼吸(基础呼吸和底物诱导呼吸),与刈割后导致的水分限制及碳限制有关.刈割显著降低了氮磷获取酶(N-乙酰-β-D-葡萄糖苷酶和酸性磷酸单酯酶)的活性,符合“资源分配假说”.氮添加显著降低土壤pH值,但土壤微生物生物量对氮添加和pH降低均无显著响应,表明氮输入增加引起的土壤酸化不是影响微生物生物量的主要因素.氮添加对土壤呼吸和酶活性也无显著影响,与以往在典型草原的大多数研究结果不一致.刈割和氮添加复合处理显著降低了土壤微生物生物量磷,但提高了土壤中有效磷含量,降低了酸性磷酸酶活性.微生物生物量碳、氮、磷和土壤呼吸等的相关参数均在7月最高,这与夏季高温多雨有关.土壤酶活性在春夏季较高,生长季末期较低.这表明在该草甸草原,刈割将导致土壤碳氮磷养分失衡,从而加剧草原退化;而氮添加在短期内并未对土壤微生物生物量和活性产生显著影响.     

Generation of virus‐resistant potato plants by RNA genome targeting

CRISPR/Cas systems provide bacteria and archaea with molecular immunity against invading phages and foreign plasmids. The class 2 type VI CRISPR/Cas effector Cas13a is an RNA‐targeting CRISPR effector that provides protection against RNA phages. Here we report the repurposing of CRISPR/Cas13a to protect potato plants from a eukaryotic virus, Potato virus Y (PVY). Transgenic potato lines expressing Cas13a/sgRNA (small guide RNA) constructs showed suppressed PVY accumulation and disease symptoms. The levels of viral resistance correlated with the expression levels of the Cas13a/sgRNA construct in the plants. Our data further demonstrate that appropriately designed sgRNAs can specifically interfere with multiple PVY strains, while having no effect on unrelated viruses such as PVA or Potato virus S. Our findings provide a novel and highly efficient strategy for engineering crops with resistances to viral diseases.     

乌龟血液生物化学指标的初步研究

乌龟Chinemys reevesii 隶属龟鳖目、龟科、乌龟属。       

啤酒抗日光嗅味的研究

啤酒中的３－甲基－２－丁烯－１－硫醇是由光照产生的。减少光照或减少其胶驱物质的产生是降低啤酒日光嗅味的有效途径。酵母和核黄素在ＭＢＴ的形成过程中起到关键作用同,还原酒花苦味物质能从根本上解决啤酒的日光嗅味。     

基于MuSIASEM理论的大连经济技术开发区可持续发展评价

基于社会生态系统代谢多尺度综合评估（MuSIASEM）理论,对2000-2007年大连经济技术开发区人类活动时间、体外能投入量和增加值进行综合评价.结果表明：2000-2007年,大连开发区居民生活水平逐年提高;农业逐渐萎缩;第二产业仍为区域支柱产业,能耗较大;第三产业发展落后于第二产业;区域整体和各个产业的体外能代谢率明显提高,能源密度不断下降;人类活动时间与体外能投入量不断减少的情况下,经济增加值稳步增长,区域整体发展呈可持续态势.     

大豆倒伏性相关QTL的整合及Overview分析

倒伏性是影响大豆产量的重要因素,发掘与大豆倒伏相关的基因对于培育抗倒伏优良高产大豆品种具有重要意义。目前利用不同群体所构建的遗传图谱已经定位了大量与大豆倒伏性相关的QTLs。本研究在对已报道的QTLs进行物理整合的基础上,选择元分析方法将这些倒伏性相关的QTLs进一步整合,鉴定出位于C2(6号染色体)、F(13号染色体)、L(19号染色体)这3个连锁群上重复次数较多的QTL区间6个。选用基于统计学原理的Overview方法进行优化,获得了这些QTL在各个连锁群上的有效遗传位置,这些QTL的置信区间长度最小可缩至0.2 cM。通过在这些区间内进一步筛选,获得一个稳定性较好的标记Satt277。本研究可为大豆抗倒伏基因发掘及分子标记辅助选择育种提供理论依据。     

An eco-informatics tool for microbial community studies: supervised classification of Amplicon Length Heterogeneity (ALH) profiles of 16S rRNA

Support vector machines (SVM) and K-nearest neighbors (KNN) are two computational machine learning tools that perform supervised classification. This paper presents a novel application of such supervised analytical tools for microbial community profiling and to distinguish patterning among ecosystems. Amplicon length heterogeneity (ALH) profiles from several hypervariable regions of 16S rRNA gene of eubacterial communities from Idaho agricultural soil samples and from Chesapeake Bay marsh sediments were separately analyzed. The profiles from all available hypervariable regions were concatenated to obtain a combined profile, which was then provided to the SVM and KNN classifiers. Each profile was labeled with information about the location or time of its sampling. We hypothesized that after a learning phase using feature vectors from labeled ALH profiles, both these classifiers would have the capacity to predict the labels of previously unseen samples. The resulting classifiers were able to predict the labels of the Idaho soil samples with high accuracy. The classifiers were less accurate for the classification of the Chesapeake Bay sediments suggesting greater similarity within the Bay's microbial community patterns in the sampled sites. The profiles obtained from the V1+V2 region were more informative than that obtained from any other single region. However, combining them with profiles from the V1 region (with or without the profiles from the V3 region) resulted in the most accurate classification of the samples. The addition of profiles from the V 9 region appeared to confound the classifiers. Our results show that SVM and KNN classifiers can be effectively applied to distinguish between eubacterial community patterns from different ecosystems based only on their ALH profiles.     

苋科植物化学成分的研究进展

苋科植物有65个属,约1000余种,主要分布在热带、亚热带和温带地区.该科的很多植物具有良好的食用和药用价值,化学成分丰富,含有三萜类、甾体类、黄酮类、生物碱类、色素类和多肽类物质.为推动我国苋科植物资源的更深层次利用和开发,对苋科植物的化学成分研究概况做一综述.