2019年度中国古生物学十大进展评选结果及简介

按照中国古生物学会2020年工作计划和十二届三次常务理事会议关于开展 “中国古生物学年度十大进展”评选活动的决定, 中国古生物学会于2020年1月开展了2019年度中国古生物学十大进展的推荐和评选工作。提名推荐阶段学会秘书处共收到理事和分支机构推荐的提名成果22项。其中, 科研成果21项, 教学成果1项。 经中国古生物学会第十二届理事会成员和荣誉理事(含院士)组成的评审委员会投票评选, 评委会主任和副主任审定, 学会功能型党委审核, 2019年度中国古生物学十大进展评选结果如下(按照得票高低排序):     

Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.     

Structure of the scientific community modelling the evolution of resistance

Faced with the recurrent evolution of resistance to pesticides and drugs, the scientific community has developed theoretical models aimed at identifying the main factors of this evolution and predicting the efficiency of resistance management strategies. The evolutionary forces considered by these models are generally similar for viruses, bacteria, fungi, plants or arthropods facing drugs or pesticides, so interaction between scientists working on different biological organisms would be expected. We tested this by analysing co-authorship and co-citation networks using a database of 187 articles published from 1977 to 2006 concerning models of resistance evolution to all major classes of pesticides and drugs. These analyses identified two main groups. One group, led by ecologists or agronomists, is interested in agricultural crop or stock pests and diseases. It mainly uses a population genetics approach to model the evolution of resistance to insecticidal proteins, insecticides, herbicides, antihelminthic drugs and miticides. By contrast, the other group, led by medical scientists, is interested in human parasites and mostly uses epidemiological models to study the evolution of resistance to antibiotic and antiviral drugs. Our analyses suggested that there is also a small scientific group focusing on resistance to antimalaria drugs, and which is only poorly connected with the two larger groups. The analysis of cited references indicates that each of the two large communities publishes its research in a different set of literature and has its own keystone references: citations with a large impact in one group are almost never cited by the other. We fear the lack of exchange between the two communities might slow progress concerning resistance evolution which is currently a major issue for society.     

不同氮素供应下水稻酚类物质代谢关键酶基因差异表达

运用实时荧光定量PCR技术探讨了不同供氮条件下强化感与弱化感水稻苯丙烷代谢途径中9个关键酶基因的表达差异。结果表明,与正常氮素供应相比,低氮胁迫引起强化感水稻‘P1312777’中与酚类代谢途径相关的9个关键酶基因表达量均上调,表达量增幅在1.9～5.4倍之间,且以PAL基因上调倍数最大。而弱化感水稻‘Lemont’则相反,只有2个基因(苯丙氨酸裂解酶基因和肉桂酰CoA基因)表达上调,但上调倍数分别是强化感水稻对应的基因的22%和74%,其余的7个基因表达均下调,降幅在29%～72%之间,表明低氮胁迫诱发的水稻化感抑草能力增强与其体内酚类物质合成代谢增强有关。     

水稻转录因子OsBP-73靶基因的初步筛选

OsBP-73是用酵母单杂交系统,以水稻蜡质基因(Wx)的顺式作用元件为诱饵,从水稻cDNA表达文库中筛选获得的转录因子。本文以OsBP-73基因为例介绍了用"下拉"(pull-down)方法筛选转录因子靶基因的一般步骤。将含有该基因DNA结合功能域的cDNA片段构建到原核表达载体上,并在大肠杆菌中诱导表达获得其蛋白p73。用纯化后的p73蛋白通过"下拉"实验对OsBP-73靶基因进行初步筛选,获得了22个阳性克隆,为进一步研究转录因子OsBP-73参与的水稻转录调控网络提供依据。     

The Genographic Project public participation mitochondrial DNA database

The Genographic Project is studying the genetic signatures of ancient human migrations and creating an open-source research database. It allows members of the public to participate in a real-time anthropological genetics study by submitting personal samples for analysis and donating the genetic results to the database. We report our experience from the first 18 months of public participation in the Genographic Project, during which we have created the largest standardized human mitochondrial DNA (mtDNA) database ever collected, comprising 78,590 genotypes. Here, we detail our genotyping and quality assurance protocols including direct sequencing of the mtDNA HVS-I, genotyping of 22 coding-region SNPs, and a series of computational quality checks based on phylogenetic principles. This database is very informative with respect to mtDNA phylogeny and mutational dynamics, and its size allows us to develop a nearest neighbor-based methodology for mtDNA haplogroup prediction based on HVS-I motifs that is superior to classic rule-based approaches. We make available to the scientific community and general public two new resources: a periodically updated database comprising all data donated by participants, and the nearest neighbor haplogroup prediction tool.     

In situ proteolysis for protein crystallization and structure determination

We tested the general applicability of in situ proteolysis to form protein crystals suitable for structure determination by adding a protease (chymotrypsin or trypsin) digestion step to crystallization trials of 55 bacterial and 14 human proteins that had proven recalcitrant to our best efforts at crystallization or structure determination. This is a work in progress; so far we determined structures of 9 bacterial proteins and the human aminoimidazole ribonucleotide synthetase (AIRS) domain.     

向日葵根石油醚萃取部分化学成分研究

利用75%乙醇对向日葵根化学成分进行提取;再用萃取法将向日葵根化学成分乙醇提取物分为石油醚萃取物浸膏、乙酸乙酯萃取物漫膏、正丁醇萃取物浸膏;最后用常压硅胶色谱从石油醚萃取物漫膏中分离得到1个甾体类化合物A,经质谱、碳核磁共振和氢核磁共振谱鉴定,确定出其结构为β-谷甾醇。