Endometrial extracellular matrix rigidity and IFNτ ensure the establishment of early pregnancy through activation of YAP

BackgroundIn mammals, early pregnancy is a critical vulnerable period during which complications may arise, including pregnancy failure. Establishment of a maternal endometrial acceptance phenotype is a prerequisite for semiheterogeneous embryo implantation, comprising the rate‐limiting step of early pregnancy.MethodsConfocal fluorescence, immunohistochemistry and western blot for nuclear and cytoplasmic protein were used to examine the activation of yes‐associated protein (YAP) in uterine tissue and primary endometrial cells. The target binding between miR16a and YAP was verified by dual‐luciferase reporter gene assay. The mouse pregnancy model and pseudopregnancy model were used to investigate the role of YAP in the maternal uterus during early pregnancy in vivo.ResultsWe showed that YAP translocates into the nucleus in the endometrium of cattle and mice during early pregnancy. Mechanistically, YAP acts as a mediator of ECM rigidity and cell density, which requires the actomyosin cytoskeleton and is partially dependent on the Hippo pathway. Furthermore, we found that the soluble factor IFNτ, which is a ruminant pregnancy recognition factor, also induced activation of YAP by reducing the expression of miR‐16a.ConclusionsThis study revealed that activation of YAP is necessary for early pregnancy in bovines because it induced cell proliferation and established an immunosuppressive local environment that allowed conceptus implantation into the uterine epithelium.     

Target-specific mutations efficiency at multiple loci of CRISPR/Cas9 system using one sgRNA in soybean

Soybean has a palaeopolyploid genome with nearly 75% of the genes present in multiple copies. Although the CRISPR/Cas9 system has been employed in soybean to generate site-directed mutagenesis, a systematical assessment of mutation efficiency of the CRISPR/Cas9 system for the multiple-copy genes is still urgently needed. Here, we successfully optimize one sgRNA CRISPR/Cas9 system in soybean by testing the efficiency, pattern, specificity of the mutations at multiple loci of GmFAD2 and GmALS. The results showed that simultaneous site-directed mutagenesis of two homoeologous loci by one sgRNA, the mutation frequency in the T0 generation were 64.71% for GmPDS, 60.0% for GmFAD2 and 42.86% for GmALS, respectively. The chimeric and heterozygous mutations were dominant types. Moreover, association of phenotypes with mutation pattern at target loci of GmPDS11 and GmPDS18 could help us further demonstrate that the CRISPR/Cas9 system can efficiently generate target specific mutations at multiple loci using one sgRNA in soybean, albeit with a relatively low transformation efficiency.

     

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .     

三氟苯嘧啶不同种子处理方式对稻飞虱的控制效应

为探明三氟苯嘧啶不同种子处理方式对稻飞虱的田间防治效果、防治时长以及对稻田蜘蛛和水稻的安全性,为该药剂种子处理防治稻飞虱提供科学依据,本研究设置10％三氟苯嘧啶悬浮剂按不同浓度(0.375、0.75、1.125和1.5 g a.i./kg种子)对水稻种子分别以干种子拌种(干拌)、清水浸种后拌种(湿拌)和药剂浸种3种方式,清水处理作为空白对照.结果表明,3种处理方式下的水稻发芽率和出苗率均与空白对照间无显著差异,播种后100 d,各浓度对稻飞虱的防治效果均在90％以上;当药剂浓度相同时,干拌与湿拌防治时长要优于药剂浸种;不同浓度三氟苯嘧啶药剂处理在3种方式下稻田蜘蛛种群数量均略低于空白对照田蜘蛛数量.因此,水稻生产中使用三氟苯嘧啶0.375～1.5 g a.i./kg种子干拌或湿拌处理,可有效降低田间稻飞虱种群数量,对天敌蜘蛛影响较小,对水稻种子发芽、出苗安全,可在水稻生产中推广使用.     

Morphology and Genetic Diversity of Phragmites australis in Beijing

为探明北京地区芦苇(Phragmites australis)的资源状态和多样性, 实地考察北京主要河流、湿地和水库, 发现北京地区芦苇总生长面积已超过600 hm²。芦苇染色体倍性以八倍体为主, 四倍体次之。在面积较大的湿地内, 八倍体单一芦苇群落占据优势地位; 而在城市的浅河内有形态和遗传性多样的混合种群。研究表明, 植物性状和倍性水平之间无显著相关性。在小清河发现了6种形态各异的芦苇克隆, 均属于叶绿体DNA片段的P单倍型; 其单倍体基因组大小为(0.499±0.019) pg, 变异系数为3.8%。这表明表型与单倍型之间也不具相关性。此外, 发现1个具有变叶特性的芦苇, 将其命名为金条芦苇。北京地区芦苇形态和遗传多样性为研究芦苇基因型与环境适应性之间的关系提供了珍贵的资源。     

基于GEO数据库的肝癌相关基因的筛选及验证

肝细胞癌(hepatocellular carcinoma,HCC)是中国高发的恶性肿瘤之一,识别肝细胞癌发生发展相关基因,对于深入研究肝癌发病机制和开发诊疗靶点均具有重要意义.本研究利用GEO2R工具从基因表达汇编数据库(Gene Expression Omnibus Database,GEO)筛选5个数据集中共有的差异表达基因作为潜在的肝癌相关基因.利用Metascape网站,对差异表达基因进行功能富集及信号通路分析.结合GEPIA(Gene Expres-sion Profiling Interaction Analysis)网站筛选具有临床意义的基因.利用荧光定量PCR技术验证与肝癌预后相关的差异表达基因,候选肝癌相关基因,为后续的深入研究奠定扎实的基础.结果显示,从5个数据集中共发现94个共有的差异表达基因.文献检索后发现24个基因与肝癌发生发展的关系少见文献报道,属于肝癌中未知功能基因.利用GEPIA分析癌症基因组图谱(the cancer genome atlas,TCGA)中数据后发现,GINS1在肝癌组织中高表达,与肝癌患者生存期呈负相关;CFHR4和DNASE1L3在肝癌组织中显著低表达,与肝癌患者生存期呈正相关.荧光定量PCR技术证实GINS1在81.3％的肝癌组织中呈现高表达,CFHR4和DNAS-E1L3分别在71.9％和93.8％肝癌组织中低表达.因此,本研究发现GINS1、CFHR4和DNASE 1L3在肝癌组织中显著差异表达,与肝癌患者的预后密切相关,可能作为潜在的判断肝癌患者预后的分子标志物和研发肝癌治疗的潜在靶标.     

Novel artificial intelligence machine learning approaches to precisely predict survival and site-specific recurrence in cervical cancer: A multi-institutional study

BackgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.MethodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.ResultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.ConclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.